diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000000000000000000000000000000000000..6a543795430a618105c6002ecf7b6711c4407772 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,50 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/src/audeo/thumbnail_image.png filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000000.mp4 filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000001.mp4 filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/scps/tango-master/data/audiocaps/train_audiocaps.json filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/scps/tango-master/data/train_audioset_sl.json filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/scps/tango-master/data/train_bbc_sound_effects.json filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/scps/tango-master/data/train_val_audioset_sl.json filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/scps/VGGSound/train.scp filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/VGGSound/video/1u1orBeV4xI_000428.mp4 filter=lfs diff=lfs merge=lfs -text +Video-to-Audio-and-Piano-HF/tests/VGGSound/video/1uCzQCdCC1U_000170.mp4 filter=lfs diff=lfs merge=lfs -text +src/audeo/thumbnail_image.png filter=lfs diff=lfs merge=lfs -text +tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000000.mp4 filter=lfs diff=lfs merge=lfs -text +tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000001.mp4 filter=lfs diff=lfs merge=lfs -text +tests/VGGSound/video/1u1orBeV4xI_000428.mp4 filter=lfs diff=lfs merge=lfs -text +tests/VGGSound/video/1uCzQCdCC1U_000170.mp4 filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..78b0a8e67b9d07de143373fca66af9f998db9780 --- /dev/null +++ b/.gitignore @@ -0,0 +1,8 @@ +**/__pycache__ +src/audeo/data/ +ckpts/ +outputs/ +outputs_piano/ +outputs_vgg/ +src/train* +src/inference3* diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..5f0b8d2dbaef972414daa009bf36262b34877d08 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2024 Phil Wang + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..5b354055ba02ab7d50918838150b99e8190e8dba --- /dev/null +++ b/README.md @@ -0,0 +1,78 @@ +--- +title: DeepAudio-V1 +emoji: 🔊 +colorFrom: blue +colorTo: indigo +sdk: gradio +app_file: app.py +pinned: false +--- + + +## Enhance Generation Quality of Flow Matching V2A Model via Multi-Step CoT-Like Guidance and Combined Preference Optimization +## Towards Video to Piano Music Generation with Chain-of-Perform Support Benchmarks + +## Results + +**1. Results of Video-to-Audio Synthesis** + +https://github.com/user-attachments/assets/d6761371-8fc2-427c-8b2b-6d2ac22a2db2 + +https://github.com/user-attachments/assets/50b33e54-8ba1-4fab-89d3-5a5cc4c22c9a + +**2. Results of Video-to-Piano Synthesis** + +https://github.com/user-attachments/assets/b6218b94-1d58-4dc5-873a-c3e8eef6cd67 + +https://github.com/user-attachments/assets/ebdd1d95-2d9e-4add-b61a-d181f0ae38d0 + + +## Installation + +**1. Create a conda environment** + +```bash +conda create -n v2ap python=3.10 +conda activate v2ap +``` + +**2. Install requirements** + +```bash +pip install -r requirements.txt +``` + + +**Pretrained models** + +The models are available at https://huggingface.co/lshzhm/Video-to-Audio-and-Piano/tree/main. + + +## Inference + +**1. Video-to-Audio inference** + +```bash +python src/inference_v2a.py +``` + +**2. Video-to-Piano inference** + +```bash +python src/inference_v2p.py +``` + +## Dateset is in progress + + +## Metrix + + +## Acknowledgement + +- [Audeo](https://github.com/shlizee/Audeo) for video to midi prediction +- [E2TTS](https://github.com/lucidrains/e2-tts-pytorch) for CFM structure and base E2 implementation +- [FLAN-T5](https://huggingface.co/google/flan-t5-large) for FLAN-T5 text encode +- [CLIP](https://huggingface.co/laion/CLIP-ViT-bigG-14-laion2B-39B-b160k) for CLIP image encode +- [AudioLDM Eval](https://github.com/haoheliu/audioldm_eval) for audio evaluation + diff --git a/app.py b/app.py new file mode 100644 index 0000000000000000000000000000000000000000..43fc04c7de2e6a25c8663fcab863103addf89a5d --- /dev/null +++ b/app.py @@ -0,0 +1,86 @@ +import os +try: + import torchaudio +except ImportError: + os.system("cd ./F5-TTS; pip install -e .") + + +import spaces +import logging +from datetime import datetime +from pathlib import Path + +import gradio as gr +import torch +import torchaudio + +import tempfile + +import requests +import shutil +import numpy as np + +from huggingface_hub import hf_hub_download + +model_path = "./ckpts/" + +if not os.path.exists(model_path): + os.makedirs(model_path) + +file_path = hf_hub_download(repo_id="lshzhm/Video-to-Audio-and-Piano", local_dir=model_path) + +print(f"Model saved at: {file_path}") + +log = logging.getLogger() + + +#@spaces.GPU(duration=120) +def video_to_audio(video: gr.Video, prompt: str, num_steps: int): + + + return video_save_path, video_gen + + +def video_to_piano(video: gr.Video, prompt: str, num_steps: int): + + return video_save_path, video_gen + + +video_to_audio_and_speech_tab = gr.Interface( + fn=video_to_audio_and_speech, + description=""" + Project page: https://acappemin.github.io/DeepAudio-V1.github.io
+ Code: https://github.com/acappemin/DeepAudio-V1
+ """, + inputs=[ + gr.Video(label="Input Video"), + gr.Text(label='Video-to-Audio Text Prompt'), + gr.Number(label='Video-to-Audio Num Steps', value=64, precision=0, minimum=1), + gr.Text(label='Video-to-Speech Transcription'), + gr.Audio(label='Video-to-Speech Speech Prompt'), + gr.Text(label='Video-to-Speech Speech Prompt Transcription'), + gr.Number(label='Video-to-Speech Num Steps', value=64, precision=0, minimum=1), + ], + outputs=[ + gr.Video(label="Video-to-Audio Output"), + gr.Video(label="Video-to-Speech Output"), + ], + cache_examples=False, + title='Video-to-Audio-and-Speech', + examples=[ + [ + './tests/VGGSound/video/1u1orBeV4xI_000428.mp4', + '', + 64, + ], + [ + './tests/VGGSound/video/1uCzQCdCC1U_000170.mp4', + '', + 64, + ], + ]) + + +if __name__ == "__main__": + gr.TabbedInterface([video_to_audio_and_speech_tab], ['Video-to-Audio-and-Speech']).launch() + diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..14a2184afb0b2a2c3748c8bd1866f2a81f1ecbd1 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,26 @@ +accelerate==0.34.2 +beartype==0.18.5 +einops==0.8.0 +einx==0.3.0 +ema-pytorch==0.6.2 +g2p-en==2.1.0 +jaxtyping==0.2.34 +loguru==0.7.2 +tensorboard==2.18.0 +torch==2.4.1 +torchaudio==2.4.1 +torchdiffeq==0.2.4 +torchlibrosa==0.1.0 +torchmetrics==1.6.1 +torchvision==0.19.1 +numpy==1.23.5 +tqdm==4.66.5 +vocos==0.1.0 +x-transformers==1.37.4 +transformers==4.46.0 +moviepy==1.0.3 +jieba==0.42.1 +pypinyin==0.44.0 +progressbar==2.5 +datasets==3.0.1 +matplotlib==3.9.2 \ No newline at end of file diff --git a/src/audeo/Midi_synth.py b/src/audeo/Midi_synth.py new file mode 100644 index 0000000000000000000000000000000000000000..eeef8efee0682b6ab4091c89cc7a8d7ab23586b0 --- /dev/null +++ b/src/audeo/Midi_synth.py @@ -0,0 +1,165 @@ +import os +import numpy as np +os.environ["LD_PRELOAD"] = "/usr/lib/x86_64-linux-gnu/libffi.so.7" +import pretty_midi +import glob +import librosa +import soundfile as sf + +# Synthesizing Audio using Fluid Synth +class MIDISynth(): + def __init__(self, out_folder, video_name, instrument, midi=True): + self.video_name = video_name + # synthesize midi or roll + self.midi = False + # synthsized output dir, change to your own path + self.syn_dir = '/ailab-train/speech/shansizhe/audeo/data/Midi_Synth/training/' + self.min_key = 15 + self.max_key = 65 + self.frame = 50 + self.piano_keys = 88 + if self.midi: + self.midi_out_folder = out_folder + video_name + self.syn_dir = self.syn_dir + 'w_Roll2Midi/' + self.process_midi() + else: + self.est_roll_folder = out_folder + video_name + self.syn_dir = self.syn_dir + 'wo_Roll2Midi/' + self.process_roll() + self.spf = 0.04 # second per frame + self.sample_rate = 16000 + self.ins = instrument + + def process_roll(self): + self.wo_Roll2Midi_data = [] + self.est_roll_files = glob.glob(self.est_roll_folder + '/*.npz') + self.est_roll_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0])) + + # Use the Roll prediction for Synthesis + print("need to process {0} files".format(len(self.est_roll_folder))) + for i in range(len(self.est_roll_files)): + with np.load(self.est_roll_files[i]) as data: + est_roll = data['roll'] + if est_roll.shape[0] != self.frame: + target = np.zeros((self.frame, self.piano_keys)) + target[:est_roll.shape[0], :] = est_roll + est_roll = target + est_roll = np.where(est_roll > 0, 1, 0) + self.wo_Roll2Midi_data.append(est_roll) + self.complete_wo_Roll2Midi_midi = np.concatenate(self.wo_Roll2Midi_data) + print("Without Roll2MidiNet, the Roll result has shape:", self.complete_wo_Roll2Midi_midi.shape) + # compute onsets and offsets + onset = np.zeros(self.complete_wo_Roll2Midi_midi.shape) + offset = np.zeros(self.complete_wo_Roll2Midi_midi.shape) + for j in range(self.complete_wo_Roll2Midi_midi.shape[0]): + if j != 0: + onset[j][np.setdiff1d(self.complete_wo_Roll2Midi_midi[j].nonzero(), + self.complete_wo_Roll2Midi_midi[j - 1].nonzero())] = 1 + offset[j][np.setdiff1d(self.complete_wo_Roll2Midi_midi[j - 1].nonzero(), + self.complete_wo_Roll2Midi_midi[j].nonzero())] = -1 + else: + onset[j][self.complete_wo_Roll2Midi_midi[j].nonzero()] = 1 + onset += offset + self.complete_wo_Roll2Midi_onset = onset.T + print("Without Roll2MidiNet, the onset has shape:", self.complete_wo_Roll2Midi_onset.shape) + + def process_midi(self): + self.w_Roll2Midi_data = [] + self.infer_out_files = glob.glob(self.midi_out_folder + '/*.npz') + self.infer_out_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0])) + + # Use the Midi prediction for Synthesis + for i in range(len(self.infer_out_files)): + with np.load(self.infer_out_files[i]) as data: + est_midi = data['midi'] + target = np.zeros((self.frame, self.piano_keys)) + target[:est_midi.shape[0], self.min_key:self.max_key+1] = est_midi + est_midi = target + est_midi = np.where(est_midi > 0, 1, 0) + self.w_Roll2Midi_data.append(est_midi) + self.complete_w_Roll2Midi_midi = np.concatenate(self.w_Roll2Midi_data) + print("With Roll2MidiNet Midi, the Midi result has shape:", self.complete_w_Roll2Midi_midi.shape) + # compute onsets and offsets + onset = np.zeros(self.complete_w_Roll2Midi_midi.shape) + offset = np.zeros(self.complete_w_Roll2Midi_midi.shape) + for j in range(self.complete_w_Roll2Midi_midi.shape[0]): + if j != 0: + onset[j][np.setdiff1d(self.complete_w_Roll2Midi_midi[j].nonzero(), + self.complete_w_Roll2Midi_midi[j - 1].nonzero())] = 1 + offset[j][np.setdiff1d(self.complete_w_Roll2Midi_midi[j - 1].nonzero(), + self.complete_w_Roll2Midi_midi[j].nonzero())] = -1 + else: + onset[j][self.complete_w_Roll2Midi_midi[j].nonzero()] = 1 + onset += offset + self.complete_w_Roll2Midi_onset = onset.T + print("With Roll2MidiNet, the onset has shape:", self.complete_w_Roll2Midi_onset.shape) + + def GetNote(self): + if self.midi: + self.w_Roll2Midi_notes = {} + for i in range(self.complete_w_Roll2Midi_onset.shape[0]): + tmp = self.complete_w_Roll2Midi_onset[i] + start = np.where(tmp == 1)[0] + end = np.where(tmp == -1)[0] + if len(start) != len(end): + end = np.append(end, tmp.shape) + merged_list = [(start[i], end[i]) for i in range(0, len(start))] + # 21 is the lowest piano key in the Midi note number (Midi has 128 notes) + self.w_Roll2Midi_notes[21 + i] = merged_list + else: + self.wo_Roll2Midi_notes = {} + for i in range(self.complete_wo_Roll2Midi_onset.shape[0]): + tmp = self.complete_wo_Roll2Midi_onset[i] + start = np.where(tmp==1)[0] + end = np.where(tmp==-1)[0] + if len(start)!=len(end): + end = np.append(end, tmp.shape) + merged_list = [(start[i], end[i]) for i in range(0, len(start))] + self.wo_Roll2Midi_notes[21 + i] = merged_list + + + + def Synthesize(self): + if self.midi: + wav = self.generate_midi(self.w_Roll2Midi_notes, self.ins) + path = self.create_output_dir() + out_file = path + f'/Midi-{self.video_name}-{self.ins}.wav' + #librosa.output.write_wav(out_file, wav, sr=self.sample_rate) + sf.write(out_file, wav, self.sample_rate) + else: + wav = self.generate_midi(self.wo_Roll2Midi_notes, self.ins) + path = self.create_output_dir() + out_file = path + f'/Roll-{self.video_name}-{self.ins}.wav' + #librosa.output.write_wav(out_file, wav, sr=self.sample_rate) + sf.write(out_file, wav, self.sample_rate) + + def generate_midi(self, notes, ins): + pm = pretty_midi.PrettyMIDI(initial_tempo=80) + piano_program = pretty_midi.instrument_name_to_program(ins) #Acoustic Grand Piano + piano = pretty_midi.Instrument(program=piano_program) + for key in list(notes.keys()): + values = notes[key] + for i in range(len(values)): + start, end = values[i] + note = pretty_midi.Note(velocity=100, pitch=key, start=start * self.spf, end=end * self.spf) + piano.notes.append(note) + pm.instruments.append(piano) + wav = pm.fluidsynth(fs=16000) + return wav + + def create_output_dir(self): + synth_out_dir = os.path.join(self.syn_dir, self.video_name) + os.makedirs(synth_out_dir, exist_ok=True) + return synth_out_dir + +if __name__ == "__main__": + # could select any instrument available in Midi + instrument = 'Acoustic Grand Piano' + for i in [1,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,19,21,22,23,24,25,26,27]: + video_name = f'{i}' + #print(video_name) + Midi_out_folder = '/ailab-train/speech/shansizhe/audeo/data/estimate_Roll/training/'# Generated Midi output folder, change to your own path + Synth = MIDISynth(Midi_out_folder, video_name, instrument) + Synth.GetNote() + Synth.Synthesize() + diff --git a/src/audeo/README.md b/src/audeo/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7d9dd8865ec51303fe9ba0ec3a29983d4557122e --- /dev/null +++ b/src/audeo/README.md @@ -0,0 +1,67 @@ +# Audeo + +## Introduction +This repository contains the code for the paper **"Audeo: Audio Generation for a Silent Performance Video"**, which is avilable [here](https://proceedings.neurips.cc/paper/2020/file/227f6afd3b7f89b96c4bb91f95d50f6d-Paper.pdf), published in NeurIPS 2020. More samples can be found in our [project webpage](http://faculty.washington.edu/shlizee/audeo/) and [Youtube Video](https://www.youtube.com/watch?v=8rS3VgjG7_c). + +[![Alt text](https://img.youtube.com/vi/8rS3VgjG7_c/0.jpg)](https://www.youtube.com/watch?v=8rS3VgjG7_c) + +## Abstract +We present a novel system that gets as an input, video frames of a musician playing the piano, and generates the music for that video. The generation of music from +visual cues is a challenging problem and it is not clear whether it is an attainable goal at all. Our main aim in this work is to explore the plausibility of such a +transformation and to identify cues and components able to carry the association of sounds with visual events. To achieve the transformation we built a full pipeline +named ‘Audeo’ containing three components. We first translate the video frames of the keyboard and the musician hand movements into raw mechanical musical +symbolic representation Piano-Roll (Roll) for each video frame which represents the keys pressed at each time step. We then adapt the Roll to be amenable for audio +synthesis by including temporal correlations. This step turns out to be critical for meaningful audio generation. In the last step, we implement Midi synthesizers +to generate realistic music. Audeo converts video to audio smoothly and clearly with only a few setup constraints. We evaluate Audeo on piano performance videos +collected from Youtube and obtain that their generated music is of reasonable audio quality and can be successfully recognized with high precision by popular +music identification software. + +## Data +We use Youtube Channel videos recorded by [Paul Barton](https://www.youtube.com/user/PaulBartonPiano) to evaluate the Audeo pipeline. For **Pseudo Midi Evaluation**, we use 24 videos of Bach Well-Tempered Clavier Book One (WTC B1). The testing set contains the first 3 Prelude and Fugue performances of Bach Well-Tempered Clavier Book Two (WTC B2) The Youtube Video Id can be found in [here](https://github.com/shlizee/Audeo/blob/master/Video_Id.md). For **Audio Evaluation**, we use 35 videos from WTC B2 (24 Prelude and Fugue pairs and their 11 variants), 8 videos from WTC B1 Variants, and 9 videos from other composers. Since we cannot host the videos due to copyright issues, you need to download the videos yourself. + +All videos are set at the frame of 25 fps and the audio sampling rate of 16kHz. The **Pseudo GT Midi** are obtained via [Onsets and Frames framework (OF)](https://github.com/magenta/magenta/tree/master/magenta/models/onsets_frames_transcription). We process all videos and keep the full keyboard only and remove all frames that do not contribute to the piano performance (e.g., logos, black screens, etc). The **cropped piano coordinates** can be found in [here](https://github.com/shlizee/Audeo/blob/master/piano_coords.py) (The order is the same as in **Video_Id** file. We trim the initial silent sections up to the first frame in which the first key is being pressed, to align the video, Pseudo GT Midi, and the audio. All silent frames inside each performance are kept. + +For your convenience, we provide the following folders/files in [Google Drive](https://drive.google.com/drive/folders/1w9wsZM-tPPUVqwdpsefEkrDgkN3kfg7G?usp=sharing): +- **input_images**: examples of how the images data should look like. +- **labels**: training and testing labels of for training/testing Video2Roll Net. Each folder contains a **pkl** file for one video. The labels are dictionaries where **key** is the **frame number** and **value** is a 88 dim vector. See **Video2Roll_dataset.py** for more details. +- **OF_midi_files**: the original Pseudo ground truth midi files obtained from **Onsets and Frames Framework**. +- **midi**: we process the Pseudo GT Midi files to 2D matrix (Piano keys x Time) and down-sampled to 25 fps. Then for each video, we divide them into multiple 2 seconds (50 frames) segments. For example **253-303.npz** includes the 2D matrix from frame 253 to frame 302. +- **estimate_Roll**: the **Roll** predictions obtained from **Video2Roll Net**. Same format as the **midi**. You can directly use them for training **Roll2Midi Net**. +- **Roll2Midi_results**: the **Midi** predictions obtained from **Roll2Midi Net**. Same format as the **midi** and **estimate_Roll**. Ready for **Midy Synth**. +- **Midi_Synth**: synthesized audios from **Roll2Midi_results**. +- **Video2Roll_models**: contains the pre-trained **Video2RollNet.pth**. +- **Roll2Midi_models**: contains the pre-trained **Roll2Midi Net**. + +## How to Use +- Video2Roll Net + 1. Please check the **Video2Roll_dataset.py** and make sure you satisfy the data formats. + 2. Run **Video2Roll_train.py** for training. + 3. Run **Video2Roll_evaluate.py** for evaluation. + 4. Run **Video2Roll_inference.py** to generate **Roll** predictions. +- Roll2Midi Net + 1. Run **Roll2Midi_train.py** for training. + 2. Run **Roll2Midi_evaluate.py** for evaluation. + 2. Run **Roll2Midi_inference.py** to generate **Midi** predictions. +- Midi Synth + 1. Run **Midi_synth.py** to use **Fluid Synth** to synthesize audio. + +## Requirements +- Pytorch >= 1.6 +- Python 3 +- numpy 1.19 +- scikit-learn 0.22.1 +- librosa 0.7.1 +- pretty-midi 0.2.8 + +## Citation + +Please cite ["Audeo: Audio Generation for a Silent Performance Video"](https://proceedings.neurips.cc/paper/2020/file/227f6afd3b7f89b96c4bb91f95d50f6d-Paper.pdf) when you use this code: +``` +@article{su2020audeo, + title={Audeo: Audio generation for a silent performance video}, + author={Su, Kun and Liu, Xiulong and Shlizerman, Eli}, + journal={Advances in Neural Information Processing Systems}, + volume={33}, + year={2020} +} +``` diff --git a/src/audeo/Roll2MidiNet.py b/src/audeo/Roll2MidiNet.py new file mode 100644 index 0000000000000000000000000000000000000000..83e1a3140200081ffb498fe22b4b1993301fb332 --- /dev/null +++ b/src/audeo/Roll2MidiNet.py @@ -0,0 +1,139 @@ +import torch.nn as nn +import torch.nn.functional as F +import torch +############################## +# U-NET +############################## +class UNetDown(nn.Module): + def __init__(self, in_size, out_size, normalize=True, dropout=0.0): + super(UNetDown, self).__init__() + model = [nn.Conv2d(in_size, out_size, 3, stride=1, padding=1, bias=False)] + if normalize: + model.append(nn.BatchNorm2d(out_size, 0.8)) + model.append(nn.LeakyReLU(0.2)) + if dropout: + model.append(nn.Dropout(dropout)) + + self.model = nn.Sequential(*model) + + def forward(self, x): + return self.model(x) + + +class UNetUp(nn.Module): + def __init__(self, in_size, out_size, dropout=0.0): + super(UNetUp, self).__init__() + model = [ + nn.ConvTranspose2d(in_size, out_size, 3, stride=1, padding=1, bias=False), + nn.BatchNorm2d(out_size, 0.8), + nn.ReLU(inplace=True), + ] + if dropout: + model.append(nn.Dropout(dropout)) + + self.model = nn.Sequential(*model) + + def forward(self, x, skip_input): + x = self.model(x) + out = torch.cat((x, skip_input), 1) + return out + + +class Generator(nn.Module): + def __init__(self, input_shape): + super(Generator, self).__init__() + channels, _ , _ = input_shape + self.down1 = UNetDown(channels, 64, normalize=False) + self.down2 = UNetDown(64, 128) + self.down3 = UNetDown(128, 256, dropout=0.5) + self.down4 = UNetDown(256, 512, dropout=0.5) + self.down5 = UNetDown(512, 1024, dropout=0.5) + self.down6 = UNetDown(1024, 1024, dropout=0.5) + + self.up1 = UNetUp(1024, 512, dropout=0.5) + self.up2 = UNetUp(1024+512, 256, dropout=0.5) + self.up3 = UNetUp(512+256, 128, dropout=0.5) + self.up4 = UNetUp(256+128, 64) + self.up5 = UNetUp(128+64, 16) + self.conv1d = nn.Conv2d(80, 1, kernel_size=1) + + def forward(self, x): + # U-Net generator with skip connections from encoder to decoder + d1 = self.down1(x) + + d2 = self.down2(d1) + + d3 = self.down3(d2) + + d4 = self.down4(d3) + + d5 = self.down5(d4) + + d6 = self.down6(d5) + + u1 = self.up1(d6, d5) + + u2 = self.up2(u1, d4) + + u3 = self.up3(u2, d3) + + u4 = self.up4(u3, d2) + + u5 = self.up5(u4, d1) + + out = self.conv1d(u5) + + out = F.sigmoid(out) + return out + + +class Discriminator(nn.Module): + def __init__(self, input_shape): + super(Discriminator, self).__init__() + + channels, height, width = input_shape #1 51 50 + + # Calculate output of image discriminator (PatchGAN) + patch_h, patch_w = int(height / 2 ** 3)+1, int(width / 2 ** 3)+1 + self.output_shape = (1, patch_h, patch_w) + + def discriminator_block(in_filters, out_filters, stride, normalize): + """Returns layers of each discriminator block""" + layers = [nn.Conv2d(in_filters, out_filters, 3, stride, 1)] + if normalize: + layers.append(nn.InstanceNorm2d(out_filters)) + layers.append(nn.LeakyReLU(0.2, inplace=True)) + return layers + + layers = [] + in_filters = channels + for out_filters, stride, normalize in [(64, 2, False), (128, 2, True), (256, 2, True), (512, 1, True)]: + layers.extend(discriminator_block(in_filters, out_filters, stride, normalize)) + in_filters = out_filters + + layers.append(nn.Conv2d(out_filters, 1, 3, 1, 1)) + + self.model = nn.Sequential(*layers) + + def forward(self, img): + return self.model(img) + +def weights_init_normal(m): + classname = m.__class__.__name__ + if classname.find("Conv") != -1: + torch.nn.init.normal_(m.weight.data, 0.0, 0.02) + elif classname.find("BatchNorm2d") != -1: + torch.nn.init.normal_(m.weight.data, 1.0, 0.02) + torch.nn.init.constant_(m.bias.data, 0.0) + +if __name__ == "__main__": + input_shape = (1,51, 100) + gnet = Generator(input_shape) + dnet = Discriminator(input_shape) + print(dnet.output_shape) + imgs = torch.rand((64,1,51,100)) + gen = gnet(imgs) + print(gen.shape) + dis = dnet(gen) + print(dis.shape) + diff --git a/src/audeo/Roll2MidiNet_enhance.py b/src/audeo/Roll2MidiNet_enhance.py new file mode 100644 index 0000000000000000000000000000000000000000..cd5593ceceafc484e6e8e8554a1d3dbeb99e8849 --- /dev/null +++ b/src/audeo/Roll2MidiNet_enhance.py @@ -0,0 +1,164 @@ +import torch.nn as nn +import torch.nn.functional as F +import torch +############################## +# U-NET +############################## +class UNetDown(nn.Module): + def __init__(self, in_size, out_size, normalize=True, dropout=0.0): + super(UNetDown, self).__init__() + model = [nn.Conv2d(in_size, out_size, 3, stride=1, padding=1, bias=False)] + if normalize: + model.append(nn.BatchNorm2d(out_size, 0.8)) + model.append(nn.LeakyReLU(0.2)) + if dropout: + model.append(nn.Dropout(dropout)) + + self.model = nn.Sequential(*model) + + def forward(self, x): + return self.model(x) + + +class UNetUp(nn.Module): + def __init__(self, in_size, out_size, dropout=0.0): + super(UNetUp, self).__init__() + model = [ + nn.ConvTranspose2d(in_size, out_size, 3, stride=1, padding=1, bias=False), + nn.BatchNorm2d(out_size, 0.8), + nn.ReLU(inplace=True), + ] + if dropout: + model.append(nn.Dropout(dropout)) + + self.model = nn.Sequential(*model) + + def forward(self, x, skip_input): + x = self.model(x) + out = torch.cat((x, skip_input), 1) + return out + +class AttentionGate(nn.Module): + def __init__(self, in_channels, g_channels, out_channels): + super(AttentionGate, self).__init__() + self.theta_x = nn.Conv2d(in_channels, out_channels, kernel_size=1) + self.phi_g = nn.Conv2d(g_channels, out_channels, kernel_size=1) + self.psi = nn.Conv2d(out_channels, 1, kernel_size=1) + self.sigmoid = nn.Sigmoid() + + def forward(self, x, g): + theta_x = self.theta_x(x) + phi_g = self.phi_g(g) + f = theta_x + phi_g + f = self.psi(f) + alpha = self.sigmoid(f) + return x * alpha + +class Generator(nn.Module): + def __init__(self, input_shape): + super(Generator, self).__init__() + channels, _ , _ = input_shape + self.down1 = UNetDown(channels, 64, normalize=False) + self.down2 = UNetDown(64, 128) + self.down3 = UNetDown(128, 256, dropout=0.5) + self.down4 = UNetDown(256, 512, dropout=0.5) + self.down5 = UNetDown(512, 1024, dropout=0.5) + self.down6 = UNetDown(1024, 1024, dropout=0.5) + + # Attention Gates + self.att1 = AttentionGate(2048, 1024, 512) + self.att2 = AttentionGate(1024, 512, 256) + self.att3 = AttentionGate(512, 256, 128) + self.att4 = AttentionGate(256, 128, 64) + + self.up1 = UNetUp(1024, 1024, dropout=0.5) + self.up2 = UNetUp(2048, 512, dropout=0.5) + self.up3 = UNetUp(1024, 256, dropout=0.5) + self.up4 = UNetUp(512, 128) + self.up5 = UNetUp(256, 64) + self.conv1d = nn.Conv2d(128, 1, kernel_size=1) + + def forward(self, x): + # U-Net generator with skip connections from encoder to decoder + d1 = self.down1(x) + + d2 = self.down2(d1) + + d3 = self.down3(d2) + + d4 = self.down4(d3) + + d5 = self.down5(d4) + + d6 = self.down6(d5) + + u1 = self.up1(d6, d5) + u1 = self.att1(u1, d5) + + u2 = self.up2(u1, d4) + u2 = self.att2(u2, d4) + + u3 = self.up3(u2, d3) + u3 = self.att3(u3, d3) + + u4 = self.up4(u3, d2) + u4 = self.att4(u4, d2) + + u5 = self.up5(u4, d1) + + out = self.conv1d(u5) + + out = F.sigmoid(out) + return out + + +class Discriminator(nn.Module): + def __init__(self, input_shape): + super(Discriminator, self).__init__() + + channels, height, width = input_shape #1 51 50 + + # Calculate output of image discriminator (PatchGAN) + patch_h, patch_w = int(height / 2 ** 3)+1, int(width / 2 ** 3)+1 + self.output_shape = (1, patch_h, patch_w) + + def discriminator_block(in_filters, out_filters, stride, normalize): + """Returns layers of each discriminator block""" + layers = [nn.Conv2d(in_filters, out_filters, 3, stride, 1)] + if normalize: + layers.append(nn.InstanceNorm2d(out_filters)) + layers.append(nn.LeakyReLU(0.2, inplace=True)) + return layers + + layers = [] + in_filters = channels + for out_filters, stride, normalize in [(64, 2, False), (128, 2, True), (256, 2, True), (512, 1, True)]: + layers.extend(discriminator_block(in_filters, out_filters, stride, normalize)) + in_filters = out_filters + + layers.append(nn.Conv2d(out_filters, 1, 3, 1, 1)) + + self.model = nn.Sequential(*layers) + + def forward(self, img): + return self.model(img) + +def weights_init_normal(m): + classname = m.__class__.__name__ + if classname.find("Conv") != -1: + torch.nn.init.normal_(m.weight.data, 0.0, 0.02) + elif classname.find("BatchNorm2d") != -1: + torch.nn.init.normal_(m.weight.data, 1.0, 0.02) + torch.nn.init.constant_(m.bias.data, 0.0) + +if __name__ == "__main__": + input_shape = (1,51, 100) + gnet = Generator(input_shape) + dnet = Discriminator(input_shape) + print(dnet.output_shape) + imgs = torch.rand((64,1,51,100)) + gen = gnet(imgs) + print(gen.shape) + dis = dnet(gen) + print(dis.shape) + diff --git a/src/audeo/Roll2Midi_dataset.py b/src/audeo/Roll2Midi_dataset.py new file mode 100644 index 0000000000000000000000000000000000000000..142580eff0afeda40e077f80f7f26767db38133d --- /dev/null +++ b/src/audeo/Roll2Midi_dataset.py @@ -0,0 +1,160 @@ +import matplotlib.pyplot as plt +import numpy as np +import torch +from torch.utils.data import Dataset,DataLoader +import glob +print(torch.cuda.current_device()) +DEFAULT_DEVICE = 'cuda' + +torch.cuda.set_device(0) + +frames = 50 #2 seconds + +min_key = 15 +max_key = 65 + +class Roll2MidiDataset(Dataset): + def __init__(self, path='/ailab-train/speech/shansizhe/audeo/data/midi_npz', est_roll_path='/ailab-train/speech/shansizhe/audeo/data/estimate_Roll_exp3', + train=True, device=DEFAULT_DEVICE): + self.path = path + self.est_roll_path = est_roll_path + self.device = device + self.train = train + self.load_data() + def __getitem__(self, index): + if self.train: + gt, roll = self.final_data['train'][index] + else: + gt, roll = self.final_data['test'][index] + gt_ = gt.T.float().to(self.device) + roll_ = roll.T.float().to(self.device) + return torch.unsqueeze(gt_, dim=0), torch.unsqueeze(torch.sigmoid(roll_), dim=0) + + def __len__(self): + if self.train: + return len(self.final_data['train']) + else: + return len(self.final_data['test']) + + def load_data(self): + self.files = [] + self.labels = [] + + # ground truth midi dir + path = self.path + #print(path) + train_gt_folders = glob.glob(path + '/training/*') + train_gt_folders.sort(key=lambda x: int(x.split('/')[-1])) + print(train_gt_folders) + test_gt_folders = glob.glob(path + '/testing/*') + test_gt_folders.sort(key=lambda x: int(x.split('/')[-1])) + print(test_gt_folders) + + # Roll predictions dir + train_roll_folder = glob.glob(self.est_roll_path + '/training/*') + train_roll_folder.sort(key=lambda x: int(x.split('/')[-1])) + print(train_roll_folder) + test_roll_folder = glob.glob(self.est_roll_path + '/testing/*') + test_roll_folder.sort(key=lambda x: int(x.split('/')[-1])) + print(test_roll_folder) + + # self.folders: dictionary + # key: train/test, values: list of tuples [(ground truth midi folder name, roll prediction folder name)] + self.folders = {} + self.folders['train'] = [(train_gt_folders[i], train_roll_folder[i]) for i in range(len(train_gt_folders))] + print(self.folders['train']) + self.folders['test'] = [(test_gt_folders[i], test_roll_folder[i]) for i in range(len(test_gt_folders))] + print(self.folders['test']) + + # self.data: dictionary + # key: train/test, value:list of tuples [(2 sec ground truth Midi, 2 sec Roll prediction logits)] + self.data = {} + self.data['train'] = [] + self.data['test'] = [] + + # self.final_data: similar to the data, but concat two continuous 2 sec Roll prediction (4 seconds, 100 frames) + self.final_data = {} + self.final_data['train'] = [] + self.final_data['test'] = [] + + # load training data + for train_gt_folder, est_roll_folder in self.folders['train']: + gt_files = glob.glob(train_gt_folder + '/*.npz') + gt_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0].split('_')[1])) + est_roll_files = glob.glob(est_roll_folder + '/*.npz') + est_roll_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0])) + print("have the same files of training gt and est roll:", len(gt_files) == len(est_roll_files)) + for i in range(len(gt_files)): + with np.load(gt_files[i]) as data: + gt = data['midi'][:, min_key:max_key + 1] + if gt.shape[0] != frames: + target = np.zeros((frames, max_key-min_key+1)) + target[:gt.shape[0], :] = gt + gt = target + gt = np.where(gt > 0, 1, 0) + with np.load(est_roll_files[i]) as data: + est_roll_logit = data['logit'][:, min_key:max_key + 1] + if est_roll_logit.shape[0] != frames: + target = np.zeros((frames, max_key-min_key+1)) + target[:est_roll_logit.shape[0], :] = est_roll_logit + est_roll_logit = target + self.data['train'].append((torch.from_numpy(gt), torch.from_numpy(est_roll_logit))) + # make 4 sec data + for i in range(len(self.data['train'])): + if i + 1 < len(self.data['train']): + one_gt, one_roll = self.data['train'][i] + two_gt, two_roll = self.data['train'][i + 1] + final_gt = torch.cat([one_gt, two_gt], dim=0) + final_roll = torch.cat([one_roll, two_roll], dim=0) + self.final_data['train'].append((final_gt, final_roll)) + + print("total number of training data:", len(self.final_data['train'])) + + # load testing data + for test_gt_folder, est_roll_folder in self.folders['test']: + gt_files = glob.glob(test_gt_folder + '/*.npz') + gt_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0].split('_')[1])) + est_roll_files = glob.glob(est_roll_folder + '/*.npz') + est_roll_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0])) + print("have the same files of testing midi and roll:", len(gt_files) == len(est_roll_files)) + for i in range(len(gt_files)): + with np.load(gt_files[i]) as data: + gt = data['midi'][:, min_key:max_key + 1] + if gt.shape[0] != frames: + target = np.zeros((frames, max_key-min_key+1)) + target[:gt.shape[0], :] = gt + gt = target + gt = np.where(gt > 0, 1, 0) + with np.load(est_roll_files[i]) as data: + est_roll = data['logit'][:, min_key:max_key + 1] # data['midi'] + if est_roll.shape[0] != frames: + target = np.zeros((frames, max_key-min_key+1)) + target[:est_roll.shape[0], :] = est_roll + est_roll = target + self.data['test'].append((torch.from_numpy(gt), torch.from_numpy(est_roll))) + for i in range(0, len(self.data['test']), 2): + if i + 1 < len(self.data['test']): + one_gt, one_roll = self.data['test'][i] + two_gt, two_roll = self.data['test'][i + 1] + final_gt = torch.cat([one_gt, two_gt], dim=0) + final_roll = torch.cat([one_roll, two_roll], dim=0) + self.final_data['test'].append((final_gt, final_roll)) + + print("total number of testing data:", len(self.final_data['test'])) + + + +if __name__ == "__main__": + dataset = Roll2MidiDataset() + gt,midi = dataset.__getitem__(0) + print(gt.shape) + print(midi.shape) + fig, (ax1,ax2,ax3) = plt.subplots(1, 3) + ax1.imshow(gt.cpu().numpy().squeeze(), plt.cm.gray) + ax2.imshow(midi.cpu().numpy().squeeze(), plt.cm.gray) + plt.show() + data_loader = DataLoader(dataset, batch_size=64) + for i,data in enumerate(data_loader): + gts,midis = data + break + diff --git a/src/audeo/Roll2Midi_dataset_tv2a_eval.py b/src/audeo/Roll2Midi_dataset_tv2a_eval.py new file mode 100644 index 0000000000000000000000000000000000000000..8c5bdbe1415b6cb1ca6942d7177fd8287d2bf4c7 --- /dev/null +++ b/src/audeo/Roll2Midi_dataset_tv2a_eval.py @@ -0,0 +1,118 @@ +import matplotlib.pyplot as plt +import numpy as np +import torch +from torch.utils.data import Dataset,DataLoader +import glob +print(torch.cuda.current_device()) +DEFAULT_DEVICE = 'cuda' + +torch.cuda.set_device(0) + +frames = 50 #2 seconds + +min_key = 15 +max_key = 65 + +class Roll2MidiDataset(Dataset): + def __init__(self, path='/ailab-train/speech/shansizhe/audeo/data/tv2a_piano3_4000_pkl_npz/gt/npz/', est_roll_path='/ailab-train/speech/shansizhe/audeo/data/tv2a_piano3_4000_pkl_npz/v2a/npz/', + train=True, device=DEFAULT_DEVICE): + self.path = path + self.est_roll_path = est_roll_path + self.device = device + self.train = train + self.load_data() + def __getitem__(self, index): + if self.train: + gt, roll = self.final_data['train'][index] + else: + gt, roll = self.final_data['test'][index] + gt_ = gt.T.float().to(self.device) + roll_ = roll.T.float().to(self.device) + return torch.unsqueeze(gt_, dim=0), torch.unsqueeze(roll_, dim=0) + + def __len__(self): + if self.train: + return len(self.final_data['train']) + else: + return len(self.final_data['test']) + + def load_data(self): + self.files = [] + self.labels = [] + + # ground truth midi dir + path = self.path + #print(path) + train_gt_folders = glob.glob(path + '/*') + train_gt_folders.sort(key=lambda x: x.split('/')[-1].split('__')[-1]) + print(train_gt_folders) + + + # Roll predictions dir + train_roll_folder = glob.glob(self.est_roll_path + '/*') + train_roll_folder.sort(key=lambda x: x.split('/')[-1].split('__')[-1]) + print(train_roll_folder) + + # self.folders: dictionary + # key: train/test, values: list of tuples [(ground truth midi folder name, roll prediction folder name)] + self.folders = {} + self.folders['train'] = [(train_gt_folders[i], train_roll_folder[i]) for i in range(len(train_gt_folders))] + print(self.folders['train']) + + # self.data: dictionary + # key: train/test, value:list of tuples [(2 sec ground truth Midi, 2 sec Roll prediction logits)] + self.data = {} + self.data['train'] = [] + + # self.final_data: similar to the data, but concat two continuous 2 sec Roll prediction (4 seconds, 100 frames) + self.final_data = {} + self.final_data['train'] = [] + + # load training data + for train_gt_folder, est_roll_folder in self.folders['train']: + gt_files = glob.glob(train_gt_folder + '/*.npz') + gt_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0])) + est_roll_files = glob.glob(est_roll_folder + '/*.npz') + est_roll_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0])) + print("have the same files of training gt and est roll:", len(gt_files) == len(est_roll_files)) + for i in range(len(gt_files)): + with np.load(gt_files[i]) as data: + gt = data['midi'][:, min_key:max_key + 1] + if gt.shape[0] != frames: + target = np.zeros((frames, max_key-min_key+1)) + target[:gt.shape[0], :] = gt + gt = target + gt = np.where(gt > 0, 1, 0) + with np.load(est_roll_files[i]) as data: + est_roll_logit = data['midi'][:, min_key:max_key + 1] + if est_roll_logit.shape[0] != frames: + target = np.zeros((frames, max_key-min_key+1)) + target[:est_roll_logit.shape[0], :] = est_roll_logit + est_roll_logit = target + est_roll_logit = np.where(est_roll_logit > 0, 1, 0) + self.data['train'].append((torch.from_numpy(gt), torch.from_numpy(est_roll_logit))) + # make 4 sec data + for i in range(len(self.data['train'])): + if i + 1 < len(self.data['train']): + one_gt, one_roll = self.data['train'][i] + two_gt, two_roll = self.data['train'][i + 1] + final_gt = torch.cat([one_gt, two_gt], dim=0) + final_roll = torch.cat([one_roll, two_roll], dim=0) + self.final_data['train'].append((final_gt, final_roll)) + + print("total number of training data:", len(self.final_data['train'])) + +if __name__ == "__main__": + dataset = Roll2MidiDataset() + gt,midi = dataset.__getitem__(0) + print(gt.shape) + print(midi.shape) + fig, (ax1,ax2,ax3) = plt.subplots(1, 3) + ax1.imshow(gt.cpu().numpy().squeeze(), plt.cm.gray) + ax2.imshow(midi.cpu().numpy().squeeze(), plt.cm.gray) + plt.show() + data_loader = DataLoader(dataset, batch_size=64) + for i,data in enumerate(data_loader): + gts,midis = data + break + diff --git a/src/audeo/Roll2Midi_evaluate.py b/src/audeo/Roll2Midi_evaluate.py new file mode 100644 index 0000000000000000000000000000000000000000..d172726798249ea5ab362696237ea6fdc5b8ab9a --- /dev/null +++ b/src/audeo/Roll2Midi_evaluate.py @@ -0,0 +1,126 @@ +import os +import json +from Roll2Midi_dataset import Roll2MidiDataset +from sklearn import metrics +import torch.utils.data as utils +import torch +from Roll2MidiNet_enhance import Generator +from torch.autograd import Variable +import numpy as np +from sklearn.metrics import _classification +cuda = torch.device("cuda") +Tensor = torch.cuda.FloatTensor +def process_data(): + test_dataset = Roll2MidiDataset(train=False) + test_loader = utils.DataLoader(test_dataset, batch_size=16) + return test_loader + +def test(generator, test_loader): + all_label = [] + all_pred_label = [] + all_pred_label_ = [] + with torch.no_grad(): + generator.eval() + for idx, data in enumerate(test_loader): + gt, roll = data + # Adversarial ground truths + gt = gt.type(Tensor) + roll = roll.type(Tensor) + + real = Variable(gt) + roll_ = Variable(roll) + gen_imgs = generator(roll_) + + pred_label = gen_imgs >= 0.4 + numpy_label = gt.cpu().detach().numpy().astype(int) # B,1, 51, 50 + numpy_label = np.transpose(numpy_label.squeeze(), (0, 2, 1)) # B,50,51 + numpy_label = np.reshape(numpy_label, (-1, 51)) + numpy_pre_label = pred_label.cpu().detach().numpy().astype(int) + numpy_pre_label = np.transpose(numpy_pre_label.squeeze(), (0, 2, 1)) #B,50,51 + numpy_pre_label = np.reshape(numpy_pre_label, (-1, 51)) + all_label.append(numpy_label) + all_pred_label.append(numpy_pre_label) + + pred_label_ = gen_imgs >= 0.5 + numpy_pre_label_ = pred_label_.cpu().detach().numpy().astype(int) + numpy_pre_label_ = np.transpose(numpy_pre_label_.squeeze(), (0, 2, 1)) # B,50,51 + numpy_pre_label_ = np.reshape(numpy_pre_label_, (-1, 51)) + all_pred_label_.append(numpy_pre_label_) + + all_label = np.vstack(all_label) + all_pred_label = np.vstack(all_pred_label) + labels = _classification._check_set_wise_labels(all_label, all_pred_label, labels=None, pos_label=1, + average='samples') + MCM = metrics.multilabel_confusion_matrix(all_label, all_pred_label, sample_weight=None, labels=labels, + samplewise=True) + tp_sum = MCM[:, 1, 1] + fp_sum = MCM[:, 0, 1] + fn_sum = MCM[:, 1, 0] + # tn_sum = MCM[:, 0, 0] + accuracy = _prf_divide(tp_sum, tp_sum + fp_sum + fn_sum, zero_division=1) + accuracy = np.average(accuracy) + all_precision = metrics.precision_score(all_label, all_pred_label, average='samples', zero_division=1) + all_recall = metrics.recall_score(all_label, all_pred_label, average='samples', zero_division=1) + all_f1_score = metrics.f1_score(all_label, all_pred_label, average='samples', zero_division=1) + print( + "Threshold 0.4, avg precision:{0:.3f} | avg recall:{1:.3f} | avg acc:{2:.3f} | f1 score:{3:.3f}".format( + all_precision, all_recall, accuracy, all_f1_score)) + + all_pred_label_ = np.vstack(all_pred_label_) + labels = _classification._check_set_wise_labels(all_label, all_pred_label_, labels=None, pos_label=1, + average='samples') + MCM = metrics.multilabel_confusion_matrix(all_label, all_pred_label_, sample_weight=None, labels=labels, + samplewise=True) + tp_sum = MCM[:, 1, 1] + fp_sum = MCM[:, 0, 1] + fn_sum = MCM[:, 1, 0] + # tn_sum = MCM[:, 0, 0] + accuracy = _prf_divide(tp_sum, tp_sum + fp_sum + fn_sum, zero_division=1) + accuracy = np.average(accuracy) + all_precision = metrics.precision_score(all_label, all_pred_label_, average='samples', zero_division=1) + all_recall = metrics.recall_score(all_label, all_pred_label_, average='samples', zero_division=1) + all_f1_score = metrics.f1_score(all_label, all_pred_label_, average='samples', zero_division=1) + print( + "Threshold 0.5, avg precision:{0:.3f} | avg recall:{1:.3f} | avg acc:{2:.3f} | f1 score:{3:.3f}".format( + all_precision, all_recall,accuracy, all_f1_score)) + return + +def _prf_divide(numerator, denominator, zero_division="warn"): + """Performs division and handles divide-by-zero. + On zero-division, sets the corresponding result elements equal to + 0 or 1 (according to ``zero_division``). Plus, if + ``zero_division != "warn"`` raises a warning. + The metric, modifier and average arguments are used only for determining + an appropriate warning. + """ + mask = denominator == 0.0 + denominator = denominator.copy() + denominator[mask] = 1 # avoid infs/nans + result = numerator / denominator + + if not np.any(mask): + return result + + # if ``zero_division=1``, set those with denominator == 0 equal to 1 + result[mask] = 0.0 if zero_division in ["warn", 0] else 1.0 + + # the user will be removing warnings if zero_division is set to something + # different than its default value. If we are computing only f-score + # the warning will be raised only if precision and recall are ill-defined + if zero_division != "warn": + return result + +if __name__ == "__main__": + est_midi_folder = '/ailab-train/speech/shansizhe/audeo/data/estimate_Roll_exp3/testing' + exp_dir = "/ailab-train/speech/shansizhe/audeo/Correct_Roll2Midi_experiments/Roll2MidiNet_4_ep14_enhance" + with open(os.path.join(exp_dir,'hyperparams.json'), 'r') as hpfile: + hp = json.load(hpfile) + print(hp['best_loss']) + print(hp['best_epoch']) + checkpoints = 'checkpoint-best.tar' + checkpoint = torch.load(os.path.join(exp_dir, checkpoints)) + test_loader = process_data() + input_shape = (1, 51, 100) + model = Generator(input_shape).cuda() + model.load_state_dict(checkpoint['state_dict_G']) + test(model, test_loader) \ No newline at end of file diff --git a/src/audeo/Roll2Midi_evaluate_tv2a.py b/src/audeo/Roll2Midi_evaluate_tv2a.py new file mode 100644 index 0000000000000000000000000000000000000000..f62dbaa57812299c9c75dc0255b12915fa6c3c76 --- /dev/null +++ b/src/audeo/Roll2Midi_evaluate_tv2a.py @@ -0,0 +1,93 @@ +import os +import json +from Roll2Midi_dataset_tv2a_eval import Roll2MidiDataset +from sklearn import metrics +import torch.utils.data as utils +import torch +from Roll2MidiNet import Generator +from torch.autograd import Variable +import numpy as np +from sklearn.metrics import _classification +cuda = torch.device("cuda") +Tensor = torch.cuda.FloatTensor +def process_data(): + test_dataset = Roll2MidiDataset(train=True) + test_loader = utils.DataLoader(test_dataset, batch_size=16) + return test_loader + +def test(test_loader): + all_label = [] + all_pred_label = [] + all_pred_label_ = [] + with torch.no_grad(): + #generator.eval() + for idx, data in enumerate(test_loader): + gt, roll = data + # Adversarial ground truths + gt = gt.type(Tensor) + roll = roll.type(Tensor) + + real = Variable(gt) + roll_ = Variable(roll) + #gen_imgs = generator(roll_) + + #pred_label = gen_imgs >= 0.4 + numpy_label = gt.cpu().detach().numpy().astype(int) # B,1, 51, 50 + numpy_label = np.transpose(numpy_label.squeeze(), (0, 2, 1)) # B,50,51 + numpy_label = np.reshape(numpy_label, (-1, 51)) + numpy_pre_label = roll.cpu().detach().numpy().astype(int) + numpy_pre_label = np.transpose(numpy_pre_label.squeeze(), (0, 2, 1)) #B,50,51 + numpy_pre_label = np.reshape(numpy_pre_label, (-1, 51)) + all_label.append(numpy_label) + all_pred_label.append(numpy_pre_label) + + all_label = np.vstack(all_label) + all_pred_label = np.vstack(all_pred_label) + labels = _classification._check_set_wise_labels(all_label, all_pred_label, labels=None, pos_label=1, + average='samples') + MCM = metrics.multilabel_confusion_matrix(all_label, all_pred_label, sample_weight=None, labels=labels, + samplewise=True) + tp_sum = MCM[:, 1, 1] + fp_sum = MCM[:, 0, 1] + fn_sum = MCM[:, 1, 0] + # tn_sum = MCM[:, 0, 0] + accuracy = _prf_divide(tp_sum, tp_sum + fp_sum + fn_sum, zero_division=1) + accuracy = np.average(accuracy) + all_precision = metrics.precision_score(all_label, all_pred_label, average='weighted', zero_division=1) + all_recall = metrics.recall_score(all_label, all_pred_label, average='weighted', zero_division=1) + all_f1_score = metrics.f1_score(all_label, all_pred_label, average='weighted', zero_division=1) + print( + "avg precision:{0:.3f} | avg recall:{1:.3f} | avg acc:{2:.3f} | f1 score:{3:.3f}".format( + all_precision, all_recall, accuracy, all_f1_score)) + + return + +def _prf_divide(numerator, denominator, zero_division="warn"): + """Performs division and handles divide-by-zero. + On zero-division, sets the corresponding result elements equal to + 0 or 1 (according to ``zero_division``). Plus, if + ``zero_division != "warn"`` raises a warning. + The metric, modifier and average arguments are used only for determining + an appropriate warning. + """ + mask = denominator == 0.0 + denominator = denominator.copy() + denominator[mask] = 1 # avoid infs/nans + result = numerator / denominator + + if not np.any(mask): + return result + + # if ``zero_division=1``, set those with denominator == 0 equal to 1 + result[mask] = 0.0 if zero_division in ["warn", 0] else 1.0 + + # the user will be removing warnings if zero_division is set to something + # different than its default value. If we are computing only f-score + # the warning will be raised only if precision and recall are ill-defined + if zero_division != "warn": + return result + +if __name__ == "__main__": + #est_midi_folder = '/ailab-train/speech/shansizhe/audeo/data/estimate_Roll/testing' + test_loader = process_data() + test(test_loader) \ No newline at end of file diff --git a/src/audeo/Roll2Midi_inference.py b/src/audeo/Roll2Midi_inference.py new file mode 100644 index 0000000000000000000000000000000000000000..c8dda8f215658fae7a2b815e42fe321cf4d1e6ea --- /dev/null +++ b/src/audeo/Roll2Midi_inference.py @@ -0,0 +1,100 @@ +import os +import json +import numpy as np +import torch +import glob +from Roll2MidiNet import Generator +from torch.autograd import Variable +torch.cuda.set_device(0) +cuda = torch.device("cuda") +print(torch.cuda.current_device()) +Tensor = torch.cuda.FloatTensor +class Midi_Generation(): + def __init__(self, checkpoint, exp_dir, est_roll_folder, video_name): + # model dir + self.exp_dir = exp_dir + # load model checkpoint + self.checkpoint = torch.load(os.path.join(exp_dir,checkpoint)) + # the video name + self.video_name = video_name + # the Roll prediction folder + self.est_roll_folder = est_roll_folder + video_name + # Midi output dir + self.infer_out_dir = '/ailab-train/speech/shansizhe/audeo/data/Roll2Midi_results/training/' + + self.min_key = 15 + self.max_key = 65 + self.frame = 50 + self.process_est_roll(self.est_roll_folder) + + def process_est_roll(self, est_roll_folder): + self.data = [] + self.final_data = [] + self.est_roll_files = glob.glob(est_roll_folder + '/*.npz') + self.est_roll_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0])) + print("need to infer {0} files".format(len(est_roll_folder))) + for i in range(len(self.est_roll_files)): + with np.load(self.est_roll_files[i]) as data: + est_roll = data['logit'][:,self.min_key:self.max_key+1] + if est_roll.shape[0] != self.frame: + target = np.zeros((self.frame, self.max_key-self.min_key+1)) + target[:est_roll.shape[0], :] = est_roll + est_roll = target + self.data.append(torch.from_numpy(est_roll)) + for i in range(0,len(self.data), 2): + if i + 1 < len(self.data): + one_roll = self.data[i] + two_roll = self.data[i+1] + final_roll = torch.cat([one_roll, two_roll], dim=0) + self.final_data.append(final_roll) + + def inference(self): + input_shape = (1, self.max_key-self.min_key+1, 2*self.frame) + model = Generator(input_shape).cuda() + model.load_state_dict(self.checkpoint['state_dict_G']) + test_results = [] + print('Inferencing MIDI......') + for i, data in enumerate(self.final_data): + roll = torch.unsqueeze(torch.unsqueeze(torch.sigmoid(data.T.float().cuda()), dim=0), dim=0) + print("piece ", i) + with torch.no_grad(): + model.eval() + roll = roll.type(Tensor) + roll_ = Variable(roll) + gen_img = model(roll_) + gen_img = gen_img >= 0.5 + + numpy_pre_label = gen_img.cpu().detach().numpy().astype(int) # 1,1,88,100 + numpy_pre_label = np.transpose(numpy_pre_label.squeeze(), (1, 0)) # 100,88 + + test_results.append(numpy_pre_label[:self.frame, :]) + test_results.append(numpy_pre_label[self.frame:, :]) + midi_out_dir = self.create_output_dir() + for i in range(len(test_results)): + print(self.est_roll_files[i]) + idx = self.est_roll_files[i].split("/")[-1].split(".")[0].split("-") + idx1 = int(idx[0]) + idx2 = int(idx[1]) + print(idx1, idx2) + np.savez(midi_out_dir+f'/{idx1}-{idx2}.npz', midi=test_results[i]) + + def create_output_dir(self): + midi_out_dir = os.path.join(self.infer_out_dir, self.video_name) + os.makedirs(midi_out_dir, exist_ok=True) + return midi_out_dir + +if __name__ == "__main__": + # example for generating the Midi output from training Roll predictions + est_roll_folder = '/ailab-train/speech/shansizhe/audeo/data/estimate_Roll/training/' + exp_dir = "/ailab-train/speech/shansizhe/audeo/Correct_Roll2Midi_experiments/Roll2MidiNet_1" + with open(os.path.join(exp_dir,'hyperparams.json'), 'r') as hpfile: + hp = json.load(hpfile) + print("the best loss:", hp['best_loss']) + print("the best epoch:", hp['best_epoch']) + + checkpoints = 'checkpoint-{}.tar'.format(hp['best_epoch']) + for i in [1,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,19,21,22,23,24,25,26,27]: + video_name = f'{i}' + generator = Midi_Generation(checkpoints, exp_dir, est_roll_folder, video_name) + generator.inference() + diff --git a/src/audeo/Roll2Midi_train.py b/src/audeo/Roll2Midi_train.py new file mode 100644 index 0000000000000000000000000000000000000000..d23db95f6dbfea8619dee9178e2d5bde479802c4 --- /dev/null +++ b/src/audeo/Roll2Midi_train.py @@ -0,0 +1,280 @@ +import os +import torch +import torch.optim as optim +import numpy as np +from torchvision.utils import save_image +import json +import torch.utils.data as utils +from Roll2MidiNet_enhance import Generator, Discriminator,weights_init_normal +from Roll2Midi_dataset import Roll2MidiDataset +from torch.autograd import Variable +from sklearn import metrics +from tqdm import tqdm +from torch.utils.tensorboard import SummaryWriter + +torch.cuda.set_device(0) +cuda = torch.device("cuda") +print(torch.cuda.current_device()) +Tensor = torch.cuda.FloatTensor + +class hyperparams(object): + def __init__(self): + self.train_epoch = 200 + self.test_freq = 1 + self.exp_name = 'Roll2MidiNet_4_ep14_enhance' + + self.channels = 1 + self.h = 51 #input Piano key ranges + self.w = 100 # 4 seconds, 100 frames predictions + + self.iter_train_g_loss = [] + self.iter_train_d_loss = [] + + self.iter_test_g_loss = [] + self.iter_test_d_loss = [] + + self.g_loss_history = [] + self.d_loss_history = [] + + self.test_g_loss_history = [] + self.test_d_loss_history = [] + self.best_loss = 1e10 + self.best_epoch = 0 + +def process_data(): + train_dataset = Roll2MidiDataset(train=True) + train_loader = utils.DataLoader(train_dataset, batch_size=16, shuffle=True) + test_dataset = Roll2MidiDataset(train=False) + test_loader = utils.DataLoader(test_dataset, batch_size=16) + return train_loader, test_loader + +def train(generator, discriminator, epoch, train_loader, optimizer_G, optimizer_D, + scheduler, adversarial_loss, iter_train_g_loss, iter_train_d_loss): + generator.train() + discriminator.train() + train_g_loss = 0 + train_d_loss = 0 + for batch_idx, data in tqdm(enumerate(train_loader)): + gt, roll = data + # Adversarial ground truths + valid = Variable(Tensor(gt.shape[0], *discriminator.output_shape).fill_(1.0), requires_grad=False) + fake = Variable(Tensor(gt.shape[0], *discriminator.output_shape).fill_(0.0), requires_grad=False) + gt = gt.type(Tensor) + roll = roll.type(Tensor) + + real = Variable(gt) + roll_ = Variable(roll) + + # ----------------- + # Train Generator + # ----------------- + + optimizer_G.zero_grad() + + # Generate a batch of images + gen_imgs = generator(roll_) + + # Loss measures generator's ability to fool the discriminator + g_loss = 0.001*adversarial_loss(discriminator(gen_imgs), valid) + 0.999*adversarial_loss(gen_imgs, gt) + + g_loss.backward() + + iter_train_g_loss.append(g_loss.item()) + train_g_loss += g_loss + + optimizer_G.step() + + # --------------------- + # Train Discriminator + # --------------------- + + optimizer_D.zero_grad() + + # Measure discriminator's ability to classify real from generated samples + real_loss = adversarial_loss(discriminator(real), valid) + fake_loss = adversarial_loss(discriminator(gen_imgs.detach()), fake) + d_loss = 0.5 * (real_loss + fake_loss) + + d_loss.backward() + + iter_train_d_loss.append(d_loss.item()) + train_d_loss += d_loss + + optimizer_D.step() + + if batch_idx % 2 == 0: + print('Train Epoch: {0} [{1}/{2} ({3:.0f}%)]\t g Loss: {4:.6f} | d Loss: {5:.6f}'.format(epoch, batch_idx * roll.shape[0], + len(train_loader.dataset), + 100. * batch_idx / len(train_loader), + g_loss.item() / roll.shape[0], d_loss.item() / roll.shape[0])) + scheduler.step(train_g_loss / len(train_loader.dataset)) + print('====> Epoch: {} Average g loss: {:.4f} | d loss: {:.4f}'.format(epoch, train_g_loss / len(train_loader.dataset), train_d_loss / len(train_loader.dataset))) + return train_g_loss / len(train_loader.dataset),train_d_loss / len(train_loader.dataset) + +def test(generator, discriminator, epoch, test_loader, adversarial_loss, + iter_test_g_loss,iter_test_d_loss): + all_label = [] + all_pred_label = [] + all_pred_label_ = [] + with torch.no_grad(): + generator.eval() + discriminator.eval() + test_g_loss = 0 + test_d_loss = 0 + for idx, data in enumerate(test_loader): + gt, roll = data + # Adversarial ground truths + valid = Variable(Tensor(gt.shape[0], *discriminator.output_shape).fill_(1.0), requires_grad=False) + fake = Variable(Tensor(gt.shape[0], *discriminator.output_shape).fill_(0.0), requires_grad=False) + gt = gt.type(Tensor) + roll = roll.type(Tensor) + + real = Variable(gt) + roll_ = Variable(roll) + gen_imgs = generator(roll_) + + # Loss measures generator's ability to fool the discriminator + g_loss = adversarial_loss(gen_imgs, gt) + + iter_test_g_loss.append(g_loss.item()) + test_g_loss += g_loss + + # Measure discriminator's ability to classify real from generated samples + real_loss = adversarial_loss(discriminator(real), valid) + fake_loss = adversarial_loss(discriminator(gen_imgs.detach()), fake) + d_loss = 0.5 * (real_loss + fake_loss) + + iter_test_d_loss.append(d_loss.item()) + test_d_loss += d_loss + + pred_label = gen_imgs >= 0.4 + numpy_label = gt.cpu().detach().numpy().astype(int) # B,1,51, 50 + numpy_label = np.transpose(numpy_label.squeeze(), (0, 2, 1)) # B,50,51 + + numpy_label = np.reshape(numpy_label, (-1, 51)) + numpy_pre_label = pred_label.cpu().detach().numpy().astype(int) + numpy_pre_label = np.transpose(numpy_pre_label.squeeze(), (0, 2, 1)) #B,50,51 + numpy_pre_label = np.reshape(numpy_pre_label, (-1, 51)) + all_label.append(numpy_label) + all_pred_label.append(numpy_pre_label) + + pred_label_ = gen_imgs >= 0.5 + numpy_pre_label_ = pred_label_.cpu().detach().numpy().astype(int) + numpy_pre_label_ = np.transpose(numpy_pre_label_.squeeze(), (0, 2, 1)) # B,50,51 + numpy_pre_label_ = np.reshape(numpy_pre_label_, (-1, 51)) + all_pred_label_.append(numpy_pre_label_) + + + test_g_loss /= len(test_loader.dataset) + test_d_loss /= len(test_loader.dataset) + + writer = SummaryWriter(log_dir='/ailab-train/speech/shansizhe/audeo/log/roll2midi/exp4_enhance') + + # scheduler.step(test_loss) + print('====> Test set g loss: {:.4f} | d loss: {:.4f}'.format(test_g_loss, test_d_loss)) + + all_label = np.vstack(all_label) + all_pred_label = np.vstack(all_pred_label) + all_precision = metrics.precision_score(all_label, all_pred_label, average='samples', zero_division=1) + all_recall = metrics.recall_score(all_label, all_pred_label, average='samples', zero_division=1) + all_f1_score = metrics.f1_score(all_label, all_pred_label, average='samples', zero_division=1) + print( + "Threshold 0.4, epoch {0} avg precision:{1:.3f} | avg recall:{2:.3f} | f1 score:{3:.3f}".format( + epoch, all_precision, all_recall, all_f1_score)) + + writer.add_scalar('g_loss', test_g_loss, epoch) + writer.add_scalar('d_loss', test_d_loss, epoch) + writer.add_scalar('loss', test_d_loss + test_g_loss, epoch) + writer.add_scalar('Precision/t=0.4', all_precision, epoch) + writer.add_scalar('Recall/t=0.4', all_recall, epoch) + writer.add_scalar('F1_score/t=0.4', all_f1_score, epoch) + + all_pred_label_ = np.vstack(all_pred_label_) + all_precision = metrics.precision_score(all_label, all_pred_label_, average='samples', zero_division=1) + all_recall = metrics.recall_score(all_label, all_pred_label_, average='samples', zero_division=1) + all_f1_score = metrics.f1_score(all_label, all_pred_label_, average='samples', zero_division=1) + print( + "Threshold 0.5, epoch {0} avg precision:{1:.3f} | avg recall:{2:.3f} | f1 score:{3:.3f}".format( + epoch, all_precision, all_recall, all_f1_score)) + + writer.add_scalar('Precision/t=0.5', all_precision, epoch) + writer.add_scalar('Recall/t=0.5', all_recall, epoch) + writer.add_scalar('F1_score/t=0.5', all_f1_score, epoch) + + return test_g_loss, test_d_loss + + +def main(): + hp = hyperparams() + + try: + # the dir to save the Roll2Midi model + exp_root = "/ailab-train/speech/shansizhe/audeo/Correct_Roll2Midi_experiments" + os.makedirs(exp_root, exist_ok=True) + except FileExistsError: + pass + + exp_dir = os.path.join(exp_root, hp.exp_name) + os.makedirs(exp_dir, exist_ok=True) + input_shape = (hp.channels, hp.h, hp.w) + # Loss function + adversarial_loss = torch.nn.MSELoss() + + generator = Generator(input_shape) + discriminator = Discriminator(input_shape) + + # Initialize weights + generator.apply(weights_init_normal) + discriminator.apply(weights_init_normal) + + generator.cuda() + discriminator.cuda() + optimizer_G = torch.optim.Adam(generator.parameters(), lr=0.5*1e-3, betas=(0.9, 0.999)) + optimizer_D = torch.optim.Adam(discriminator.parameters(), lr=0.5*1e-3, betas=(0.9, 0.999)) + + scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer_G, 'min', patience=2) + train_loader, test_loader = process_data() + print ('start training') + for epoch in tqdm(range(hp.train_epoch)): + # training loop + g_loss, d_loss = train(generator, discriminator, epoch, train_loader, optimizer_G, optimizer_D, + scheduler, adversarial_loss, hp.iter_train_g_loss, hp.iter_train_d_loss) + hp.g_loss_history.append(g_loss.item()) + hp.d_loss_history.append(d_loss.item()) + + # test + if epoch % hp.test_freq == 0: + test_g_loss,test_d_loss = test(generator, discriminator, epoch, test_loader, adversarial_loss, + hp.iter_test_g_loss, hp.iter_test_d_loss) + hp.test_g_loss_history.append(test_g_loss.item()) + hp.test_d_loss_history.append(test_d_loss.item()) + + max_checkpoints = 5 + # 在每个 epoch 后保存 checkpoint + torch.save({'epoch': epoch + 1, + 'state_dict_G': generator.state_dict(), + 'optimizer_G': optimizer_G.state_dict(), + 'state_dict_D': discriminator.state_dict(), + 'optimizer_D': optimizer_D.state_dict()}, + os.path.join(exp_dir, 'checkpoint-{}.tar'.format(str(epoch + 1)))) + + # 如果达到最大 checkpoint 数量，删除最旧的 checkpoint + saved_checkpoints = sorted(os.listdir(exp_dir)) + saved_checkpoints = [f for f in saved_checkpoints if f != 'checkpoint-best.tar'] + if len(saved_checkpoints) > max_checkpoints: + oldest_checkpoint = saved_checkpoints[0] + os.remove(os.path.join(exp_dir, oldest_checkpoint)) + + if test_g_loss + test_d_loss < hp.best_loss: + torch.save({'epoch': epoch + 1, 'state_dict_G': generator.state_dict(), + 'optimizer_G': optimizer_G.state_dict(), + 'state_dict_D': discriminator.state_dict(), + 'optimizer_D': optimizer_D.state_dict()}, + os.path.join(exp_dir, 'checkpoint-best.tar')) + hp.best_loss = test_g_loss.item()+test_d_loss.item() + hp.best_epoch = epoch + 1 + with open(os.path.join(exp_dir, 'hyperparams.json'), 'w') as outfile: + json.dump(hp.__dict__, outfile) + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/src/audeo/Video2RollNet.py b/src/audeo/Video2RollNet.py new file mode 100644 index 0000000000000000000000000000000000000000..cd8c759725f558c9768dd11f3616deb5ba8eebc8 --- /dev/null +++ b/src/audeo/Video2RollNet.py @@ -0,0 +1,264 @@ +import torch.nn as nn +import math +import torch.nn.functional as F +import torch + +__all__ = ['ResNet', 'resnet18'] + + +def conv3x3(in_planes, out_planes, stride=1): + """3x3 convolution with padding""" + return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, + padding=1, bias=False) + +class FTB(nn.Module): + def __init__(self,in_planes, out_planes=512, stride=1): + super(FTB,self).__init__() + self.conv0 = nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, padding=1,bias=False) + self.conv1 = conv3x3(out_planes, out_planes, stride) + self.bn1 = nn.BatchNorm2d(out_planes) + self.relu = nn.ReLU(inplace=True) + self.conv2 = conv3x3(out_planes, out_planes) + self.avgpool1 = nn.AvgPool2d(kernel_size=(2, 2), stride=2) + self.avgpool2 = nn.AvgPool2d(kernel_size=(3, 3), stride=1) + def forward(self, x, avg=True): + x1 = self.conv0(x) + residual = x1 + out = self.conv1(x1) + out = self.bn1(out) + out = self.relu(out) + out = self.conv2(out) + out += residual + if avg: + out = self.avgpool1(out) + else: + out = self.avgpool2(out) + return out + +class FRB(nn.Module): + def __init__(self,in_planes1,in_planes2): + super(FRB,self).__init__() + self.fc1 = nn.Linear(in_planes1+in_planes2, in_planes2) + self.relu = nn.ReLU(inplace=True) + self.fc2 = nn.Linear(in_planes2, in_planes2) + def forward(self, xl, xh): + xc = torch.cat([xl,xh],dim=1) + zc = F.avg_pool2d(xc, kernel_size=xc.size()[2:]) # C x 1 x 1 + zc = torch.flatten(zc, 1) + out = self.fc1(zc) + out = self.relu(out) + out = self.fc2(out) + zc_ = F.sigmoid(out) + zc_ = torch.unsqueeze(zc_,dim=2) + zc_ = zc_.repeat(1, 1, xl.shape[2] * xl.shape[3]).view(-1,xl.shape[1],xl.shape[2],xl.shape[3]) + xl_ = zc_ * xl #n,c,h,w + return xl_ + +class BasicBlock(nn.Module): + expansion = 1 + + def __init__(self, inplanes, planes, stride=1, downsample=None): + super(BasicBlock, self).__init__() + self.conv1 = conv3x3(inplanes, planes, stride) + self.bn1 = nn.BatchNorm2d(planes) + self.relu = nn.ReLU(inplace=True) + self.conv2 = conv3x3(planes, planes) + self.bn2 = nn.BatchNorm2d(planes) + self.downsample = downsample + self.stride = stride + + def forward(self, x): + residual = x + + out = self.conv1(x) + out = self.bn1(out) + out = self.relu(out) + + out = self.conv2(out) + out = self.bn2(out) + + if self.downsample is not None: + residual = self.downsample(x) + + out += residual + out = self.relu(out) + + return out + + +class Bottleneck(nn.Module): + expansion = 4 + + def __init__(self, inplanes, planes, stride=1, downsample=None): + super(Bottleneck, self).__init__() + self.conv1 = nn.Conv2d(inplanes, planes, kernel_size=1, bias=False) + self.bn1 = nn.BatchNorm2d(planes) + self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride,padding=1, bias=False) + self.bn2 = nn.BatchNorm2d(planes) + self.conv3 = nn.Conv2d(planes, planes * 4, kernel_size=1, bias=False) + self.bn3 = nn.BatchNorm2d(planes * 4) + self.relu = nn.ReLU(inplace=True) + self.downsample = downsample + self.stride = stride + + def forward(self, x): + residual = x + + out = self.conv1(x) + out = self.bn1(out) + out = self.relu(out) + + out = self.conv2(out) + out = self.bn2(out) + out = self.relu(out) + + out = self.conv3(out) + out = self.bn3(out) + + if self.downsample is not None: + residual = self.downsample(x) + + out += residual + out = self.relu(out) + + return out + + +class ResNet(nn.Module): + + def __init__(self, block, layers, top_channel_nums=2048, reduced_channel_nums=256, num_classes=51, scale=1): + self.inplanes = 64 + super(ResNet, self).__init__() + self.conv1 = nn.Conv2d(5, 64, kernel_size=(11, 11), stride=(2, 2), padding=(4, 4),bias=False) + self.bn1 = nn.BatchNorm2d(64) + self.relu1 = nn.ReLU(inplace=True) + self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1) + self.layer1 = self._make_layer(block, 64, layers[0]) + self.layer2 = self._make_layer(block, 128, layers[1], stride=2) + + self.FTB2_1 = FTB(128, 128) + self.FTB2_2 = FTB(128, 128) + self.FRB2 = FRB(128, 128) + + self.layer3 = self._make_layer(block, 256, layers[2], stride=2) + + self.FTB3 = FTB(256, 128) + self.FRB3 = FRB(128, 128) + + self.layer4 = self._make_layer(block, 512, layers[3], stride=2) + + self.FTB4 = FTB(512, 128) + self.FRB4 = FRB(64, 128) + + + #FPN PARTS + # Top layer + self.toplayer = nn.Conv2d(top_channel_nums, reduced_channel_nums, kernel_size=1, stride=1, padding=0) # Reduce channels, + self.toplayer_bn = nn.BatchNorm2d(reduced_channel_nums) + self.toplayer_relu = nn.ReLU(inplace=True) + + self.conv2 = nn.Conv2d(128, 128, kernel_size=1) + self.fc = nn.Linear(128, num_classes) + + for m in self.modules(): + if isinstance(m, nn.Conv2d): + n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels + m.weight.data.normal_(0, math.sqrt(2. / n)) + elif isinstance(m, nn.BatchNorm2d): + m.weight.data.fill_(1) + m.bias.data.zero_() + + def _make_layer(self, block, planes, blocks, stride=1): + downsample = None + if stride != 1 or self.inplanes != planes * block.expansion: + downsample = nn.Sequential( + nn.Conv2d(self.inplanes, planes * block.expansion, + kernel_size=1, stride=stride, bias=False), + nn.BatchNorm2d(planes * block.expansion), + ) + + layers = [] + layers.append(block(self.inplanes, planes, stride, downsample)) + self.inplanes = planes * block.expansion + for i in range(1, blocks): + layers.append(block(self.inplanes, planes)) + + return nn.Sequential(*layers) + + def _upsample(self, x, y, scale=1): + _, _, H, W = y.size() + return F.upsample(x, size=(H // scale, W // scale), mode='bilinear') + + def _upsample_add(self, x, y): + _, _, H, W = y.size() + return F.upsample(x, size=(H, W), mode='bilinear') + y + + def forward(self, x): + h = x + h = self.conv1(h) + h = self.bn1(h) + h = self.relu1(h) + h = self.maxpool(h) + + h = self.layer1(h) + x1 = h + + h = self.layer2(h) + x2 = h + + h = self.layer3(h) + + x3 = h + + h = self.layer4(h) + x4 = h + + # Top-down + x5 = self.toplayer(x4) + x5 = self.toplayer_relu(self.toplayer_bn(x5)) + + x2_ = self.FTB2_1(x2) + + x2_ = self.FTB2_2(x2_) + + x3_ = self.FTB3(x3) + + x4_ = self.FTB4(x4, avg=False) + + p4 = self.FRB4(x4_, x5) + + p3 = self.FRB3(x3_, p4) + + p2 = self.FRB2(x2_, p3) + + out1 = p2*p3 + + out1_ = F.softmax(out1.view(*out1.size()[:2], -1),dim=2).view_as(out1) + + out2 = out1_*p4 + + out2 = self.conv2(out2) + + out = out2 + p4 + + out = F.avg_pool2d(out, kernel_size=out.size()[2:]) + + out = torch.flatten(out, 1) + + out = self.fc(out) + + return out + + +def resnet18(**kwargs): + """Constructs a ResNet-18 model. + """ + model = ResNet(BasicBlock, layers=[2, 2, 2, 2], top_channel_nums=512, reduced_channel_nums=64, **kwargs) + return model + +if __name__ == "__main__": + net = resnet18() + print(net) + imgs = torch.rand((2, 5, 100,900)) + logits = net(imgs) + print(logits.shape) \ No newline at end of file diff --git a/src/audeo/Video2Roll_dataset.py b/src/audeo/Video2Roll_dataset.py new file mode 100644 index 0000000000000000000000000000000000000000..c7d2829f4ead67af5cbd0bfc62e2bb730c2cbd2c --- /dev/null +++ b/src/audeo/Video2Roll_dataset.py @@ -0,0 +1,148 @@ +import numpy as np +import glob +import matplotlib.pyplot as plt +from PIL import Image +from torch.utils.data import Dataset, DataLoader +import torchvision.transforms as transforms +import torch +from balance_data import MultilabelBalancedRandomSampler +# Resize all input images to 1 x 100 x 900 +transform = transforms.Compose([lambda x: x.resize((900,100)), + lambda x: np.reshape(x,(100,900,1)), + lambda x: np.transpose(x,[2,0,1]), + lambda x: x/255.]) + +class Video2RollDataset(Dataset): + def __init__(self, img_root='./data/frame',label_root='./data/label', transform = transform, subset='train', device='cuda'): + self.img_root = img_root #images root dir + self.label_root = label_root #labels root dir + self.transform = transform + self.subset = subset + # the minimum and maximum Piano Key values in the data, depending on the data stats + self.min_key = 15 #3 + self.max_key = 65 #79 + self.device = device + self.load_data() + + def __getitem__(self,index): + if self.subset=='train': + input_file_list, label = self.data['train'][index] + else: + input_file_list, label = self.data['test'][index] + input_img_list = [] + # 5 consecutive frames, set binary + for input_file in input_file_list: + input_img = Image.open(input_file).convert('L') + binarr = np.array(input_img) + input_img = Image.fromarray(binarr.astype(np.uint8)) + input_img_list.append(input_img) + + new_input_img_list = [] + for input_img in input_img_list: + new_input_img_list.append(self.transform(input_img)) + # stack 5 consecutive frames + final_input_img = np.concatenate(new_input_img_list) + torch_input_img = torch.from_numpy(final_input_img).float().to(self.device) + torch_label = torch.from_numpy(label).float().to(self.device) + + return torch_input_img, torch_label + def __len__(self): + if self.subset == 'train': + # return 20000 + return len(self.data['train']) + else: + return len(self.data['test']) + + def load_data(self): + # self.folders: dictionary + # key: train/test, values: list of tuples [(video_i_image_folder, video_i_label_folder)] + self.folders = {} + + train_img_folder = glob.glob(self.img_root+'/training/*') + train_img_folder.sort(key=lambda x:int(x.split('/')[-1])) + test_img_folder = glob.glob(self.img_root+'/testing/*') + test_img_folder.sort(key=lambda x:int(x.split('/')[-1])) + train_label_folder = glob.glob(self.label_root+'/training/*') + train_label_folder.sort(key=lambda x: int(x.split('/')[-1].split('.')[0])) + test_label_folder = glob.glob(self.label_root+'/testing/*') + test_label_folder.sort(key=lambda x: int(x.split('/')[-1].split('.')[0])) + + self.folders['train'] = [(train_img_folder[i],train_label_folder[i]) for i in range(len(train_img_folder))] + print(self.folders['train']) + self.folders['test'] = [(test_img_folder[i],test_label_folder[i]) for i in range(len(test_img_folder))] + print(self.folders['test']) + + # self.data: dictionary + # key: train/test, value: list of tuples [([frame_{i-2, i+2}_image_filename], frame_i_label)] + self.data = {} + self.data['train'] = [] + self.data['test'] = [] + self.train_labels = [] + count_zero = 0 + # load train data + for img_folder, label_file in self.folders['train']: + # each folder contains all image frames of one video, format: frame{number}.jpg + img_files = glob.glob(img_folder + '/*.jpg') + img_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0][5:])) + # label is a pkl file. The key is frame number, value is the label vector of 88 dim + labels = np.load(label_file, allow_pickle=True) + for i, file in enumerate(img_files): + key = int(file.split('/')[-1].split('.')[0][5:]) + label = labels[key] + # count the number of frames that no key is activate + if not np.any(label): + count_zero += 1 + # continue + new_label = label[self.min_key:self.max_key + 1] + if i >= 2 and i= 2 and i= 0.4 + numpy_label = label.cpu().detach().numpy().astype(int) + numpy_pre_label = pred_label.cpu().detach().numpy().astype(int) + all_label.append(numpy_label) + all_pred_label.append(numpy_pre_label) + epoch_loss += loss.item() + count += 1 + all_label = np.vstack(all_label) + all_pred_label = np.vstack(all_pred_label) + labels = _classification._check_set_wise_labels(all_label, all_pred_label,labels=None, pos_label=1, average='samples') + MCM = metrics.multilabel_confusion_matrix(all_label, all_pred_label,sample_weight=None, labels=labels, samplewise=True) + tp_sum = MCM[:, 1, 1] + fp_sum = MCM[:, 0, 1] + fn_sum = MCM[:, 1, 0] + # tn_sum = MCM[:, 0, 0] + accuracy = _prf_divide(tp_sum, tp_sum+fp_sum+fn_sum, zero_division=1) + accuracy = np.average(accuracy) + all_precision = metrics.precision_score(all_label, all_pred_label, average='samples', zero_division=1) + all_recall = metrics.recall_score(all_label, all_pred_label, average='samples', zero_division=1) + all_f1_score = metrics.f1_score(all_label, all_pred_label, average='samples', zero_division=1) + return epoch_loss/count, all_precision, all_recall, accuracy, all_f1_score + + +def _prf_divide(numerator, denominator, zero_division="warn"): + """Performs division and handles divide-by-zero. + On zero-division, sets the corresponding result elements equal to + 0 or 1 (according to ``zero_division``). Plus, if + ``zero_division != "warn"`` raises a warning. + The metric, modifier and average arguments are used only for determining + an appropriate warning. + """ + mask = denominator == 0.0 + denominator = denominator.copy() + denominator[mask] = 1 # avoid infs/nans + result = numerator / denominator + + if not np.any(mask): + return result + + # if ``zero_division=1``, set those with denominator == 0 equal to 1 + result[mask] = 0.0 if zero_division in ["warn", 0] else 1.0 + + # the user will be removing warnings if zero_division is set to something + # different than its default value. If we are computing only f-score + # the warning will be raised only if precision and recall are ill-defined + if zero_division != "warn": + return result + +if __name__ == "__main__": + model_path = './models/Video2Roll_50_0.4/14.pth' + device = torch.device('cuda') + net = Video2RollNet.resnet18() + # net = torch.nn.DataParallel(net) + net.cuda() + net.load_state_dict(torch.load(model_path)) + print(net) + test_dataset = Video2RollDataset(subset='test') + test_data_loader = DataLoader(test_dataset, batch_size=64) + net.eval() + criterion=nn.BCEWithLogitsLoss() + val_avg_loss, val_avg_precision, val_avg_recall, val_avg_acc, val_fscore = validate(net, criterion, test_data_loader) + epoch = 0 + print('-' * 85) + print( + "epoch {0} validation loss:{1:.3f} | avg precision:{2:.3f} | avg recall:{3:.3f} | avg acc:{4:.3f} | f1 score:{5:.3f}".format( + epoch + 1, val_avg_loss, val_avg_precision, val_avg_recall, val_avg_acc, val_fscore)) + print('-' * 85) \ No newline at end of file diff --git a/src/audeo/Video2Roll_inference.py b/src/audeo/Video2Roll_inference.py new file mode 100644 index 0000000000000000000000000000000000000000..cc92dbff34c1637509c28cb399faff2f12f330a0 --- /dev/null +++ b/src/audeo/Video2Roll_inference.py @@ -0,0 +1,151 @@ +import Video2RollNet +import os +import glob +import numpy as np +from PIL import Image +import torchvision.transforms as transforms +import torch +transform = transforms.Compose([lambda x: x.resize((900,100)), + lambda x: np.reshape(x,(100,900,1)), + lambda x: np.transpose(x,[2,0,1]), + lambda x: x/255.]) + +# video images root dir, change to your path +img_root='./data/frame' +# labels root dir, change to your path +label_root='./data/label' +# midi ground truth root dir, change to your path +midi_root = './data/midi_npz' +# Roll prediction output, change to your path +#est_roll_root = '/ailab-train/speech/shansizhe/audeo/data/estimate_Roll_exp3/' + +# the range of Piano keys (maximum is 88), depending on your data +min_key = 15 +max_key = 65 + +def load_data(img_folder, label_file, midi_folder): + img_files = glob.glob(img_folder + '/*.jpg') + img_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0][5:])) + labels = np.load(label_file, allow_pickle=True) + # Midi info for every video is divided into multiple npz files + # each npz contains 2 seconds (50 frames) Midi information + # format: frame_{i}-frame_{i+50}.npz + midi_files = glob.glob(midi_folder + '/*.npz') + midi_files.sort(key=lambda x: int(x.split('/')[-1].split('.')[0].split('-')[0].split('_')[1])) + intervals = [] + for file in midi_files: + interval = file.split('/')[-1].split('.')[0].split('-') + start = int(interval[0].split('_')[1]) + end = int(interval[1].split('_')[1]) + intervals.append([start, end]) + data = [] + for i, file in enumerate(img_files): + key = int(file.split('/')[-1].split('.')[0][5:]) + label = np.where(labels[key] > 0, 1, 0) + new_label = label[min_key:max_key + 1] + if i >= 2 and i < len(img_files) - 2: + file_list = [img_files[i - 2], img_files[i - 1], file, img_files[i + 1], img_files[i + 2]] + elif i < 2: + file_list = [file, file, file, img_files[i + 1], img_files[i + 2]] + else: + file_list = [img_files[i - 2], img_files[i - 1], file, file, file] + data.append((file_list, new_label)) + print("data", i, file, file_list, new_label) + return intervals, data + +# infer 2 seconds every time +def inference(net, intervals, data, est_roll_folder): + net.eval() + i = 0 + for interval in intervals: + start, end = interval + print("infer interval {0} - {1}".format(start, end)) + save_est_roll = [] + save_est_logit = [] + infer_data = data[i:i+50] + for frame in infer_data: + file_list, label = frame + torch_input_img, torch_label = torch_preprocess(file_list, label) + logits = net(torch.unsqueeze(torch_input_img,dim=0)) + print("####", torch_input_img.shape, torch_label.shape, logits.shape) + pred_label = torch.sigmoid(logits) >= 0.4 + numpy_pre_label = pred_label.cpu().detach().numpy().astype(int) + numpy_logit = logits.cpu().detach().numpy() + save_est_roll.append(numpy_pre_label) + save_est_logit.append(numpy_logit) + # Roll prediction + target = np.zeros((50, 88)) + target[:, min_key:max_key+1] = np.asarray(save_est_roll).squeeze() + save_est_roll = target + # Logit + target_ = np.zeros((50, 88)) + target_[:, min_key:max_key + 1] = np.asarray(save_est_logit).squeeze() + save_est_logit = target_ + # save both Roll predictions and logits as npz files + np.savez(f'{est_roll_folder}/' + str(start) + '-' + str(end) + '.npz', logit=save_est_logit, roll=save_est_roll) + i = i+50 + +def torch_preprocess(input_file_list, label): + input_img_list = [] + for input_file in input_file_list: + input_img = Image.open(input_file).convert('L') + binarr = np.array(input_img) + input_img = Image.fromarray(binarr.astype(np.uint8)) + input_img_list.append(input_img) + new_input_img_list = [] + for input_img in input_img_list: + new_input_img_list.append(transform(input_img)) + final_input_img = np.concatenate(new_input_img_list) + torch_input_img = torch.from_numpy(final_input_img).float().cuda() + torch_label = torch.from_numpy(label).float().cuda() + return torch_input_img, torch_label + + +if __name__ == "__main__": + model_path = './models/Video2Roll_50_0.4/14.pth' # change to your path + device = torch.device('cuda') + net = Video2RollNet.resnet18() + net.cuda() + net.load_state_dict(torch.load(model_path)) + + #training_data = [True,False] + training_data = [False] + # infer Roll predictions + folders = {} + + train_img_folder = glob.glob(img_root +'/training/*') + train_img_folder.sort(key=lambda x:int(x.split('/')[-1])) + test_img_folder = glob.glob(img_root +'/testing/*') + test_img_folder.sort(key=lambda x:int(x.split('/')[-1])) + train_label_folder = glob.glob(label_root +'/training/*') + train_label_folder.sort(key=lambda x: int(x.split('/')[-1].split('.')[0])) + test_label_folder = glob.glob(label_root +'/testing/*') + test_label_folder.sort(key=lambda x: int(x.split('/')[-1].split('.')[0])) + train_midi_folder = glob.glob(midi_root +'/training/*') + train_midi_folder.sort(key=lambda x:int(x.split('/')[-1])) + test_midi_folder = glob.glob(midi_root +'/testing/*') + test_midi_folder.sort(key=lambda x:int(x.split('/')[-1])) + + folders['train'] = [(train_img_folder[i],train_label_folder[i],train_midi_folder[i]) for i in range(len(train_img_folder))] + print(folders['train']) + folders['test'] = [(test_img_folder[i],test_label_folder[i],test_midi_folder[i]) for i in range(len(test_img_folder))] + print(folders['test']) + for item in training_data: + if item: + for img_folder, label_file, midi_folder in folders['train']: + est_roll_folder = midi_folder.replace('midi_npz','estimate_Roll_exp4') + #/ailab-train/speech/shansizhe/audeo/data/midi_npz/testing/2 + print("save file in:", est_roll_folder) + os.makedirs(est_roll_folder, exist_ok=True) + intervals, data = load_data(img_folder, label_file, midi_folder) + print("starting inference--------------------") + inference(net,intervals, data, est_roll_folder) + else: + for img_folder, label_file, midi_folder in folders['test']: + est_roll_folder = midi_folder.replace('midi_npz','estimate_Roll_exp4') + print("save file in:", est_roll_folder) + os.makedirs(est_roll_folder, exist_ok=True) + intervals, data = load_data(img_folder, label_file, midi_folder) + print("starting inference--------------------") + inference(net, intervals, data, est_roll_folder) + diff --git a/src/audeo/Video2Roll_solver.py b/src/audeo/Video2Roll_solver.py new file mode 100644 index 0000000000000000000000000000000000000000..0f024cf5671c996856dab8158127643a4562e569 --- /dev/null +++ b/src/audeo/Video2Roll_solver.py @@ -0,0 +1,204 @@ +import time +import numpy as np +import torch +from sklearn import metrics +from sklearn.metrics import _classification +from torch.utils.tensorboard import SummaryWriter +from tqdm import tqdm +import os + +class Solver(object): + + def __init__(self, data_loader, test_data_loader, model, criterion, optimizer, lr_scheduler, epochs): + self.save_model_path = '/ailab-train/speech/shansizhe/audeo/models/Video2Roll_50_0.4/' # change to your path + self.test_loader = test_data_loader + self.data_loader = data_loader + self.net = model + self.criterion = criterion + self.optimizer = optimizer + self.lr_scheduler = lr_scheduler + # Training config + self.epochs = epochs + # logging + self.step = 0 + self.global_step = 0 + self.writer = SummaryWriter(log_dir='/ailab-train/speech/shansizhe/audeo/log/50_0.4/') + # visualizing loss using visdom + self.tr_loss = torch.Tensor(self.epochs) + self.val_loss = torch.zeros(self.epochs) + self.visdom = False + self.visdom_epoch = 1 + self.visdom_id = 'key classification' + if self.visdom: + from visdom import Visdom + self.vis = Visdom(env=self.visdom_id) + self.vis_opts = dict(title=self.visdom_id, + ylabel='Loss', xlabel='Epoch', + legend=['train loss', 'val loss']) + self.vis_window = None + self.vis_epochs = torch.arange(1, self.epochs + 1) + + def train(self): + # Train model multi-epoches + pre_val_loss = 1e4 + for epoch in tqdm(range(self.epochs)): + print("Training...") + self.net.train() # Turn on BatchNorm & Dropout + start = time.time() + # training loop + tr_avg_loss, tr_avg_precision, tr_avg_recall = self.train_loop() + + # evaluate + self.net.eval() + val_avg_loss, val_avg_precision, val_avg_recall, val_avg_acc, val_fscore = self.validate() + print('-' * 85) + print('Train Summary | Epoch {0} | Time {1:.2f}s | ' + 'Train Loss {2:.3f}'.format( + epoch+1, time.time() - start, tr_avg_loss, tr_avg_precision, tr_avg_recall)) + print("epoch {0} validation loss:{1:.3f} | avg precision:{2:.3f} | avg recall:{3:.3f} | avg acc:{4:.3f} | f1 score:{5:.3f}".format( + epoch+1, val_avg_loss, val_avg_precision, val_avg_recall, val_avg_acc, val_fscore)) + print('-' * 85) + + # Log metrics to TensorBoard + self.writer.add_scalar('Loss/train', tr_avg_loss, epoch) + self.writer.add_scalar('Precision/train', tr_avg_precision, epoch) + self.writer.add_scalar('Recall/train', tr_avg_recall, epoch) + self.writer.add_scalar('Loss/val', val_avg_loss, epoch) + self.writer.add_scalar('Precision/val', val_avg_precision, epoch) + self.writer.add_scalar('Recall/val', val_avg_recall, epoch) + self.writer.add_scalar('Accuracy/val', val_avg_acc, epoch) + self.writer.add_scalar('F1_score/val', val_fscore, epoch) + + os.makedirs(self.save_model_path, exist_ok=True) + model_save_path = f"{self.save_model_path}{epoch}.pth" + torch.save(self.net.state_dict(), model_save_path) + if val_avg_loss < pre_val_loss: + pre_val_loss = val_avg_loss + torch.save(self.net.state_dict(), f"{self.save_model_path}best.pth") + # Save model each epoch + self.val_loss[epoch] = val_avg_loss + self.tr_loss[epoch] = tr_avg_loss + + # visualizing loss using visdom + if self.visdom: + x_axis = self.vis_epochs[0:epoch + 1] + # train_y_axis = self.tr_loss[0:epoch+1] + # val_x_axis = self.vis_epochs[0:epoch+1:10] + # val_y_axis = self.val_loss[0:epoch//10+1] + y_axis = torch.stack( + (self.tr_loss[0:epoch + 1], self.val_loss[0:epoch + 1]), dim=1) + if self.vis_window is None: + self.vis_window = self.vis.line( + X=x_axis, + Y=y_axis, + opts=self.vis_opts, + ) + else: + self.vis.line( + X=x_axis.unsqueeze(0).expand(y_axis.size( + 1), x_axis.size(0)).transpose(0, 1), # Visdom fix + Y=y_axis, + win=self.vis_window, + update='replace', + ) + + def train_loop(self): + data_loader = self.data_loader + epoch_loss = 0 + epoch_precision = 0 + epoch_recall = 0 + count = 0 + start = time.time() + + for i, data in tqdm(enumerate(data_loader)): + imgs, label = data + logits = self.net(imgs) + loss = self.criterion(logits,label) + # set the threshold of the logits + pred_label = torch.sigmoid(logits) >= 0.4 + numpy_label = label.cpu().detach().numpy().astype(int) + numpy_pre_label = pred_label.cpu().detach().numpy().astype(int) + + precision = metrics.precision_score(numpy_label,numpy_pre_label, average='samples', zero_division=1) + recall = metrics.recall_score(numpy_label,numpy_pre_label, average='samples', zero_division=1) + + self.writer.add_scalar('loss/step', loss, self.global_step) + self.writer.add_scalar('precision/step', precision, self.global_step) + self.writer.add_scalar('recall/step', recall, self.global_step) + + if self.global_step % 100 == 0: + end = time.time() + print( + "step {0} loss:{1:.4f} | precision:{2:.3f} | recall:{3:.3f} | time:{4:.2f}".format(self.global_step, loss.item(), precision, + recall,end - start)) + start = end + + epoch_precision += precision + epoch_recall += recall + epoch_loss += loss.item() + self.optimizer.zero_grad() + loss.backward() + self.optimizer.step() + count += 1 + self.global_step += 1 + self.lr_scheduler.step(epoch_loss / count) + return epoch_loss/count, epoch_precision/count, epoch_recall/count + + def validate(self): + epoch_loss = 0 + count = 0 + all_pred_label = [] + all_label = [] + with torch.no_grad(): + for i, data in enumerate(self.test_loader): + imgs, label = data + logits = self.net(imgs) + loss = self.criterion(logits, label) + pred_label = torch.sigmoid(logits) >= 0.4 + numpy_label = label.cpu().detach().numpy().astype(int) + numpy_pre_label = pred_label.cpu().detach().numpy().astype(int) + all_label.append(numpy_label) + all_pred_label.append(numpy_pre_label) + epoch_loss += loss.item() + count += 1 + all_label = np.vstack(all_label) + all_pred_label = np.vstack(all_pred_label) + labels = _classification._check_set_wise_labels(all_label, all_pred_label,labels=None, pos_label=1, average='samples') + MCM = metrics.multilabel_confusion_matrix(all_label, all_pred_label,sample_weight=None, labels=labels, samplewise=True) + tp_sum = MCM[:, 1, 1] + fp_sum = MCM[:, 0, 1] + fn_sum = MCM[:, 1, 0] + # tn_sum = MCM[:, 0, 0] + accuracy = _prf_divide(tp_sum, tp_sum+fp_sum+fn_sum, zero_division=1) + accuracy = np.average(accuracy) + all_precision = metrics.precision_score(all_label, all_pred_label, average='samples', zero_division=1) + all_recall = metrics.recall_score(all_label, all_pred_label, average='samples', zero_division=1) + all_f1_score = metrics.f1_score(all_label, all_pred_label, average='samples', zero_division=1) + return epoch_loss/count, all_precision, all_recall, accuracy, all_f1_score + + +def _prf_divide(numerator, denominator, zero_division="warn"): + """Performs division and handles divide-by-zero. + On zero-division, sets the corresponding result elements equal to + 0 or 1 (according to ``zero_division``). Plus, if + ``zero_division != "warn"`` raises a warning. + The metric, modifier and average arguments are used only for determining + an appropriate warning. + """ + mask = denominator == 0.0 + denominator = denominator.copy() + denominator[mask] = 1 # avoid infs/nans + result = numerator / denominator + + if not np.any(mask): + return result + + # if ``zero_division=1``, set those with denominator == 0 equal to 1 + result[mask] = 0.0 if zero_division in ["warn", 0] else 1.0 + + # the user will be removing warnings if zero_division is set to something + # different than its default value. If we are computing only f-score + # the warning will be raised only if precision and recall are ill-defined + if zero_division != "warn": + return result + diff --git a/src/audeo/Video2Roll_train.py b/src/audeo/Video2Roll_train.py new file mode 100644 index 0000000000000000000000000000000000000000..e3e48c9d68db07f318c86e50bd8976400a052eec --- /dev/null +++ b/src/audeo/Video2Roll_train.py @@ -0,0 +1,26 @@ +from Video2Roll_dataset import Video2RollDataset +from torch.utils.data import DataLoader +import torch +from torch import optim + +import Video2RollNet + +from Video2Roll_solver import Solver +import torch.nn as nn +from balance_data import MultilabelBalancedRandomSampler + +if __name__ == "__main__": + train_dataset = Video2RollDataset(subset='train') + train_sampler = MultilabelBalancedRandomSampler(train_dataset.train_labels) + train_data_loader = DataLoader(train_dataset, batch_size=64, sampler=train_sampler) + test_dataset = Video2RollDataset(subset='test') + test_data_loader = DataLoader(test_dataset, batch_size=64) + device = torch.device('cuda:6') + + net = Video2RollNet.resnet18() + net.cuda() + optimizer = optim.Adam(net.parameters(), lr=0.001, betas=(0.9, 0.999)) + criterion = nn.BCEWithLogitsLoss() + scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, 'min', patience=2) + solver = Solver(train_data_loader, test_data_loader, net, criterion, optimizer, scheduler, epochs=50) + solver.train() diff --git a/src/audeo/Video_Id.md b/src/audeo/Video_Id.md new file mode 100644 index 0000000000000000000000000000000000000000..6acc11d55855931a75557fdfd65a5ca8e9acd09f --- /dev/null +++ b/src/audeo/Video_Id.md @@ -0,0 +1,30 @@ +# Training +- https://youtu.be/_3qnL9ddHuw +- https://youtu.be/HB8-w5CvMls +- https://youtu.be/vGdV4mJhaKU +- https://youtu.be/W5lOLZsjOp8 +- https://youtu.be/vHi3_k4XOrA +- https://youtu.be/PIS76X17Mf8 +- https://youtu.be/DMdJLEGrUrg +- https://youtu.be/xXwCryMItHs +- https://youtu.be/49dCBsIGsgY +- https://youtu.be/OZVMVVQPPPI +- https://youtu.be/cAnmwgC-JRw +- https://youtu.be/w77mBaWOOh0 +- https://youtu.be/MGMxImcYhiI +- https://youtu.be/WqFyqbD9VEQ +- https://youtu.be/V0P_2QG84MM +- https://youtu.be/1eEcy3MgqxA +- https://youtu.be/GH-kkZQQ8G8 +- https://youtu.be/Kk58v56rD0s +- https://youtu.be/WWqRR7RZGXw +- https://youtu.be/ouhp7O3Sz8M +- https://youtu.be/U0v4CckNE68 +- https://youtu.be/VaqWF70DjYs +- https://youtu.be/m2yadhLP8H8 +- https://youtu.be/wRJlm0lCyoI + +# Testing +- https://youtu.be/u5nBBJndN3I +- https://youtu.be/nwwHuxHMIpc +- https://youtu.be/ra1jf2nzJPg diff --git a/src/audeo/balance_data.py b/src/audeo/balance_data.py new file mode 100644 index 0000000000000000000000000000000000000000..fd5bf2594b5ffea92a89e0ac524c06089898b05f --- /dev/null +++ b/src/audeo/balance_data.py @@ -0,0 +1,91 @@ +import random +import numpy as np +import torch +from torch.utils.data.sampler import Sampler +# torch.cuda.set_device(1) + +class MultilabelBalancedRandomSampler(Sampler): + """ + MultilabelBalancedRandomSampler: Given a multilabel dataset of length n_samples and + number of classes n_classes, samples from the data with equal probability per class + effectively oversampling minority classes and undersampling majority classes at the + same time. Note that using this sampler does not guarantee that the distribution of + classes in the output samples will be uniform, since the dataset is multilabel and + sampling is based on a single class. This does however guarantee that all classes + will have at least batch_size / n_classes samples as batch_size approaches infinity + """ + + def __init__(self, labels, indices=None, class_choice="random"): + """ + Parameters: + ----------- + labels: a multi-hot encoding numpy array of shape (n_samples, n_classes) + indices: an arbitrary-length 1-dimensional numpy array representing a list + of indices to sample only from. + class_choice: a string indicating how class will be selected for every + sample. + "random": class is chosen uniformly at random. + "cycle": the sampler cycles through the classes sequentially. + """ + self.labels = labels + self.indices = indices + if self.indices is None: + self.indices = range(len(labels)) + self.map = [] + for class_ in range(self.labels.shape[1]): + lst = np.where(self.labels[:, class_] == 1)[0] + lst = lst[np.isin(lst, self.indices)] + self.map.append(lst) + all_zero = [] + for row in range(self.labels.shape[0]): + if not np.any(labels[row]): + all_zero.append(row) + + print("all zero sample number is: ",len(all_zero)) + self.map.append(all_zero) + print("counting-----") + for i in range(len(self.map)): + print("class {0} has {1} samples:".format(i,len(self.map[i]))) + + assert class_choice in ["random", "cycle"] + self.class_choice = class_choice + self.current_class = 0 + + def __iter__(self): + self.count = 0 + return self + + def __next__(self): + # if self.count >= len(self.indices): + if self.count >= 20000: + raise StopIteration + self.count += 1 + return self.sample() + + def sample(self): + if self.class_choice == "random": + class_ = random.randint(0, self.labels.shape[1])# - 1) + # print(class_) + elif self.class_choice == "cycle": + class_ = self.current_class + self.current_class = (self.current_class + 1) % self.labels.shape[1] + class_indices = self.map[class_] + return np.random.choice(class_indices) + + def __len__(self): + return 20000 + # return len(self.indices) + +# if __name__ == "__main__": +# train_dataset = Video2RollDataset(subset='train') +# train_sampler = MultilabelBalancedRandomSampler(train_dataset.train_labels) +# train_data_loader = DataLoader(train_dataset, batch_size=64, sampler=train_sampler) +# for i, data in enumerate(train_data_loader): +# print(i) +# imgs,label,ref_imgs,rng = data +# print(torch.unique(torch.nonzero(label)[:,1])) +# for j in range(len(label)): +# if label[j].sum()==0: +# print("yes") +# if i == 1: +# break \ No newline at end of file diff --git a/src/audeo/models/Video2Roll_50_0.4/14.pth b/src/audeo/models/Video2Roll_50_0.4/14.pth new file mode 100644 index 0000000000000000000000000000000000000000..dc7478113ad4bac3c23c8a72bf9488f701f34a34 --- /dev/null +++ b/src/audeo/models/Video2Roll_50_0.4/14.pth @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c0e46b8dcf33cb6bf953fe09326edb0bbdcf06b697f64a6f448e3baa42bd822c +size 50945493 diff --git a/src/audeo/piano_coords.py b/src/audeo/piano_coords.py new file mode 100644 index 0000000000000000000000000000000000000000..5437ab127a6db6974cfe3243143849e443d24126 --- /dev/null +++ b/src/audeo/piano_coords.py @@ -0,0 +1,9 @@ +# upper_left_x, upper_left_y, lower_right_x, lower_right_y +train_piano_coords = [(68,674,1869,863), (38,680,1882,875), (42,678,1870,874), (42,678,1870,874), + (44,670,1876,865), (35,678,1875,869), (30,451,1249,583), (28,454,1254,584), + (39,678,1886,881), (33,671,1886,860), (29,446,1252,576), (26,447,1252,577), + (42,673,1879,871), (43,669,1870,869), (45,675,1864,870), (53,674,1868,860), + (51,679,1866,866), (51,674,1861,861), (48,674,1878,861), (45,671,1879,870), + (50,671,1879,866), (54,670,1864,863), (50,670,1870,867), (43,673,1882,869)] + +test_piano_coords = [(41,679,1880,881), (43,675,1883,875), (40,671,1879,871)] \ No newline at end of file diff --git a/src/audeo/thumbnail_image.png b/src/audeo/thumbnail_image.png new file mode 100644 index 0000000000000000000000000000000000000000..6fe5a69f22230d0d69174ba3d12e21c9e2c3c8ea --- /dev/null +++ b/src/audeo/thumbnail_image.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:edbba8fb9a0d6b1ca69c09482a88556882a0a99c6e34c5c4b5d39a1472fdb64b +size 124994 diff --git a/src/audeo/videomae_fintune.ipynb b/src/audeo/videomae_fintune.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..322ef397dc9c16651738a4d00016476dd951561d --- /dev/null +++ b/src/audeo/videomae_fintune.ipynb @@ -0,0 +1,12757 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "id": "SHEFxC8AoBHx" + }, + "outputs": [], + "source": [ + "model_ckpt = \"/ailab-train/speech/shansizhe/videomae/vit/VideoMAE/videomae-base\" # pre-trained model from which to fine-tune\n", + "batch_size = 16 # batch size for training and evaluation" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2I1tApJsoX_K" + }, + "source": [ + "## Fine-tuning a model on a video classification task" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "02SWnr4Poauk" + }, + "source": [ + "In this notebook, we will see how to fine-tune one of the [🤗 Transformers](https://github.com/huggingface/transformers) vision models on a Video Classification dataset.\n", + "\n", + "Given a video, the goal is to predict an appropriate class for it, like \"archery\"." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "TNUCBLe6HoLY", + "outputId": "f66069fb-8625-4f9e-dcb0-66a9b31561c0" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[PosixPath('/ailab-train/speech/shansizhe/audeo/data/piano_2h_cropped2/training/3.mp4'),\n", + " PosixPath('/ailab-train/speech/shansizhe/audeo/data/piano_2h_cropped2/training/27.mp4'),\n", + " PosixPath('/ailab-train/speech/shansizhe/audeo/data/piano_2h_cropped2/training/4.mp4'),\n", + " PosixPath('/ailab-train/speech/shansizhe/audeo/data/piano_2h_cropped2/training/5.mp4'),\n", + " PosixPath('/ailab-train/speech/shansizhe/audeo/data/piano_2h_cropped2/training/12.mp4')]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pathlib\n", + "\n", + "dataset_root_path = '/ailab-train/speech/shansizhe/audeo/data/piano_2h_cropped2'\n", + "dataset_root_path = pathlib.Path(dataset_root_path) # sort!\n", + "all_video_file_paths = (\n", + " list(dataset_root_path.glob(\"training/*.mp4\"))\n", + " + list(dataset_root_path.glob(\"testing/*.mp4\"))\n", + ")\n", + "all_video_file_paths[:5]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1NFY4jkcpA9N" + }, + "source": [ + "Next up, we derive the set of labels we have in the dataset. Let's also create two dictionaries that'll be helpful when initializing the model:\n", + "\n", + "* `label2id`: maps the class names to integers.\n", + "* `id2label`: maps the integers to class names." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "VeWXvJSDHpbw", + "outputId": "57d14916-7d04-4edf-d304-7142f801f8d5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{0: 0, 1: 1}\n", + "{0: 0, 1: 1}\n", + "Unique classes: [0, 1].\n" + ] + } + ], + "source": [ + "class_labels = [0,1]\n", + "label2id = {label: i for i, label in enumerate(class_labels)}\n", + "id2label = {i: label for label, i in label2id.items()}\n", + "print(label2id)\n", + "print(id2label)\n", + "print(f\"Unique classes: {list(label2id.keys())}.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "iQ_Q_ysnq_q3" + }, + "source": [ + "We've got 10 unique classes. For each class we have 30 videos in the training set." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "A6qmNcvQpXwW" + }, + "source": [ + "### Loading the model" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "5l8MehCcpe70" + }, + "source": [ + "In the next cell, we initialize a video classification model where the encoder is initialized with the pre-trained parameters and the classification head is randomly initialized. We also initialize the feature extractor associated to the model. This will come in handy during writing the preprocessing pipeline for our dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 287, + "referenced_widgets": [ + "3464464ed1be4fe4bdfb6469972e3876", + "dfaf1f52e72e46e9ac179318bf110bc0", + "4c70bf518b6f482da26cdb1c1e5ff5f5", + "545c940c15e248afb328330fd656a561", + "318221e012c048308c5a02c25c14c69c", + "61e659a4f2c54977977f62659bc285ef", + "695accef9c584e3f8bb9e786eb6baddb", + "96b372c4627d4060b1f104c3e6449e1b", + "64b88140506c4fa0a903ba8f7028cdfa", + "e40efde3ddcf4ef4813677254b32dd31", + "bef6f4f2d2a944fa92247edafa1c704a", + "f76081e885a04bf882788abd6f41ece8", + "f355cde714004982949850722db14492", + "5bc80dce1151498b86e366ba85be210f", + "2090d3a07fbc411586e818ec8eaf9a13", + "ef78d69e38a2430f8c0a0fb4ccb2d01e", + "0a6f6c53d0da40989ab6dd050ae01f1e", + "60694d9d82594745a3cfbb39613df1dc", + "c29ff56ae84642809a27e2d2706e8434", + "b6caab498afe4001b16e4e1be3444dca", + "6520791d3bb34153b68515b05447725b", + "096f20df2ae04b488afb9a74dad83247", + "b98135d7340147a5b770b329737a24c1", + "420440e9be914ad5a2e8c085f3ce38b8", + "e6121d423e7248e4a97584f3bced8213", + "bc39d23971b44d90b6e547940621e273", + "b1c76bfa7e3443c990c8003c959a7cb0", + "0f8fd9e099814d5a8b7a6fe026169bab", + "0d34afb786524bdca06e68c1439df07e", + "487271a9b47744f6955d5142fcf49193", + "49d02356353a44a5801ecd52a9dcf2ee", + "78b5a688669f4b38a4dcdc24be70c968", + "d189558fee3d49098ecb40e5311f4839", + "cf37d532685641e2a529048810f31b5e", + "f668c927d1a847848ef8b67a8944c913", + "3918ce51ec6848d3823f4f9ff8c346cf", + "8d34071d957941dea14a93ac6625333c", + "5877a9154ff84f5c9e8ea72c65e0a633", + "7afed804c8f7440ab376adc92a584eaa", + "e65c96afdd9a44149c7175630a1abe58", + "3c263458380f409fbec5c69f6e0f406e", + "3d12f9deffe944f6869d686766b00ae2", + "ba3fb47ff39247f089fee557150c66cc", + "2dc1a9f3e3aa498484ae173fc4ebdf9c" + ] + }, + "id": "vv2Sjp94MW2f", + "outputId": "d13874bf-14fc-4a1b-f4cf-af244b371c3a" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Some weights of VideoMAEForVideoClassification were not initialized from the model checkpoint at /ailab-train/speech/shansizhe/videomae/vit/VideoMAE/videomae-base and are newly initialized: ['classifier.bias', 'classifier.weight']\n", + "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n" + ] + } + ], + "source": [ + "from transformers import VideoMAEImageProcessor, VideoMAEForVideoClassification\n", + "\n", + "\n", + "image_processor = VideoMAEImageProcessor.from_pretrained(model_ckpt)\n", + "model = VideoMAEForVideoClassification.from_pretrained(\n", + " model_ckpt,\n", + " label2id=label2id,\n", + " id2label=id2label,\n", + " #label=class_labels,\n", + " #ignore_mismatched_sizes=True, # provide this in case you're planning to fine-tune an already fine-tuned checkpoint\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "d5AOoVryp2Qj" + }, + "source": [ + "The warning is telling us we are throwing away some weights (e.g. the weights and bias of the `classifier` layer) and randomly initializing some other (the weights and bias of a new `classifier` layer). This is expected in this case, because we are adding a new head for which we don't have pretrained weights, so the library warns us we should fine-tune this model before using it for inference, which is exactly what we are going to do." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "gP9lWPmaawJT" + }, + "source": [ + "**Note** that [this checkpoint](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) leads to better performance on this task as the checkpoint was obtained fine-tuning on a similar downstream task having considerable domain overlap. You can check out [this checkpoint](https://huggingface.co/sayakpaul/videomae-base-finetuned-kinetics-finetuned-ucf101-subset) which was obtained by fine-tuning `MCG-NJU/videomae-base-finetuned-kinetics` and it obtains much better performance. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "p27JMEEHp5DZ" + }, + "source": [ + "### Constructing the datasets for training" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XnNa_UIDp-hr" + }, + "source": [ + "For preprocessing the videos, we'll leverage the [PyTorch Video library](https://pytorchvideo.org/). We start by importing the dependencies we need." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "7Mkg_DzsMsSt" + }, + "outputs": [], + "source": [ + "import pytorchvideo.data\n", + "\n", + "from pytorchvideo.transforms import (\n", + " ApplyTransformToKey,\n", + " Normalize,\n", + " RandomShortSideScale,\n", + " RemoveKey,\n", + " ShortSideScale,\n", + " UniformTemporalSubsample,\n", + ")\n", + "\n", + "from torchvision.transforms import (\n", + " Compose,\n", + " Lambda,\n", + " RandomCrop,\n", + " RandomHorizontalFlip,\n", + " Resize,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "VT_RZTmFqX9I" + }, + "source": [ + "For the training dataset transformations, we use a combination of uniform temporal subsampling, pixel normalization, random cropping, and random horizontal flipping. For the validation and evaluation dataset transformations, we keep the transformation chain the same except for random cropping and horizontal flipping. To learn more about the details of these transformations check out the [official documentation of PyTorch Video](https://pytorchvideo.org). \n", + "\n", + "We'll use the `image_processor` associated with the pre-trained model to obtain the following information:\n", + "\n", + "* Image mean and standard deviation with which the video frame pixels will be normalized.\n", + "* Spatial resolution to which the video frames will be resized." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "LwNh61AxMu6Q" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "mean = image_processor.image_mean\n", + "std = image_processor.image_std\n", + "if \"shortest_edge\" in image_processor.size:\n", + " height = width = image_processor.size[\"shortest_edge\"]\n", + "else:\n", + " height = image_processor.size[\"height\"]\n", + " width = image_processor.size[\"width\"]\n", + "resize_to = (height, width)\n", + "\n", + "num_frames_to_sample = model.config.num_frames\n", + "sample_rate = 4\n", + "fps = 30\n", + "clip_duration = num_frames_to_sample * sample_rate / fps\n", + "\n", + "\n", + "# Training dataset transformations.\n", + "train_transform = Compose(\n", + " [\n", + " ApplyTransformToKey(\n", + " key=\"video\",\n", + " transform=Compose(\n", + " [\n", + " UniformTemporalSubsample(num_frames_to_sample),\n", + " Lambda(lambda x: x / 255.0),\n", + " Normalize(mean, std),\n", + " RandomShortSideScale(min_size=256, max_size=320),\n", + " RandomCrop(resize_to),\n", + " RandomHorizontalFlip(p=0.5),\n", + " ]\n", + " ),\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "# Training dataset.\n", + "train_dataset = pytorchvideo.data.Ucf101(\n", + " data_path=os.path.join(dataset_root_path, \"train\"),\n", + " clip_sampler=pytorchvideo.data.make_clip_sampler(\"random\", clip_duration),\n", + " decode_audio=False,\n", + " transform=train_transform,\n", + ")\n", + "\n", + "# Validation and evaluation datasets' transformations.\n", + "val_transform = Compose(\n", + " [\n", + " ApplyTransformToKey(\n", + " key=\"video\",\n", + " transform=Compose(\n", + " [\n", + " UniformTemporalSubsample(num_frames_to_sample),\n", + " Lambda(lambda x: x / 255.0),\n", + " Normalize(mean, std),\n", + " Resize(resize_to),\n", + " ]\n", + " ),\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "# Validation and evaluation datasets.\n", + "val_dataset = pytorchvideo.data.Ucf101(\n", + " data_path=os.path.join(dataset_root_path, \"val\"),\n", + " clip_sampler=pytorchvideo.data.make_clip_sampler(\"uniform\", clip_duration),\n", + " decode_audio=False,\n", + " transform=val_transform,\n", + ")\n", + "\n", + "test_dataset = pytorchvideo.data.Ucf101(\n", + " data_path=os.path.join(dataset_root_path, \"test\"),\n", + " clip_sampler=pytorchvideo.data.make_clip_sampler(\"uniform\", clip_duration),\n", + " decode_audio=False,\n", + " transform=val_transform,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "VlMg2MjF40xI" + }, + "source": [ + "**Note**: The above dataset pipelines are taken from the [official PyTorch Video example](https://pytorchvideo.org/docs/tutorial_classification#dataset). We're using the [`pytorchvideo.data.Ucf101()`](https://pytorchvideo.readthedocs.io/en/latest/api/data/data.html#pytorchvideo.data.Ucf101) function because it's tailored for the UCF-101 dataset. Under the hood, it returns a [`pytorchvideo.data.labeled_video_dataset.LabeledVideoDataset`](https://pytorchvideo.readthedocs.io/en/latest/api/data/data.html#pytorchvideo.data.LabeledVideoDataset) object. `LabeledVideoDataset` class is the base class for all things video in the PyTorch Video dataset. So, if you wanted to use a custom dataset not supported off-the-shelf by PyTorch Video, you can extend the `LabeledVideoDataset` class accordingly. Refer to the `data` API [documentation to](https://pytorchvideo.readthedocs.io/en/latest/api/data/data.html) learn more. Also, if your dataset follows a similar structure (as shown above), then using the `pytorchvideo.data.Ucf101()` should work just fine." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "v-39840bVLtc", + "outputId": "cb8d8949-aa42-4c78-910a-78bb2ac96fdb" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(300, 30, 75)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# We can access the `num_videos` argument to know the number of videos we have in the\n", + "# dataset.\n", + "train_dataset.num_videos, val_dataset.num_videos, test_dataset.num_videos" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "XA8XnMMqsPKE" + }, + "source": [ + "Let's now take a preprocessed video from the dataset and investigate it." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "z9VwjeQPM0nH", + "outputId": "a33a3ce5-f4e3-4ff2-cc85-26a32afc473d" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['video', 'video_name', 'video_index', 'clip_index', 'aug_index', 'label'])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sample_video = next(iter(train_dataset))\n", + "sample_video.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Xk-DcRJuM3lS", + "outputId": "e9dd8695-d8e1-4cb6-d4a4-c7124a4458ea" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "video torch.Size([3, 16, 224, 224])\n", + "video_name v_Basketball_g01_c01.avi\n", + "video_index 210\n", + "clip_index 0\n", + "aug_index 0\n", + "label 7\n", + "Video label: Basketball\n" + ] + } + ], + "source": [ + "def investigate_video(sample_video):\n", + " \"\"\"Utility to investigate the keys present in a single video sample.\"\"\"\n", + " for k in sample_video:\n", + " if k == \"video\":\n", + " print(k, sample_video[\"video\"].shape)\n", + " else:\n", + " print(k, sample_video[k])\n", + "\n", + " print(f\"Video label: {id2label[sample_video[k]]}\")\n", + "\n", + "\n", + "investigate_video(sample_video)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ua8Sd_a1sZqS" + }, + "source": [ + "We can also visualize the preprocessed videos for easier debugging." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "m8lUv_VvPIRP" + }, + "outputs": [], + "source": [ + "import imageio\n", + "import numpy as np\n", + "from IPython.display import Image\n", + "\n", + "\n", + "def unnormalize_img(img):\n", + " \"\"\"Un-normalizes the image pixels.\"\"\"\n", + " img = (img * std) + mean\n", + " img = (img * 255).astype(\"uint8\")\n", + " return img.clip(0, 255)\n", + "\n", + "\n", + "def create_gif(video_tensor, filename=\"sample.gif\"):\n", + " \"\"\"Prepares a GIF from a video tensor.\n", + "\n", + " The video tensor is expected to have the following shape:\n", + " (num_frames, num_channels, height, width).\n", + " \"\"\"\n", + " frames = []\n", + " for video_frame in video_tensor:\n", + " frame_unnormalized = unnormalize_img(video_frame.permute(1, 2, 0).numpy())\n", + " frames.append(frame_unnormalized)\n", + " kargs = {\"duration\": 0.25}\n", + " imageio.mimsave(filename, frames, \"GIF\", **kargs)\n", + " return filename\n", + "\n", + "\n", + "def display_gif(video_tensor, gif_name=\"sample.gif\"):\n", + " \"\"\"Prepares and displays a GIF from a video tensor.\"\"\"\n", + " video_tensor = video_tensor.permute(1, 0, 2, 3)\n", + " gif_filename = create_gif(video_tensor, gif_name)\n", + " return Image(filename=gif_filename)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 241 + }, + "id": "zJIPKvyqQBqL", + "outputId": "37ed4b68-885f-44cd-9049-c9344db4777f" + }, + "outputs": [ + { + "data": { + "image/gif": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "video_tensor = sample_video[\"video\"]\n", + "display_gif(video_tensor)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4lcHvCL1silT" + }, + "source": [ + "### Training the model" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9uc1ibDftk1z" + }, + "source": [ + "We'll leverage [`Trainer`](https://huggingface.co/docs/transformers/main_classes/trainer) from 🤗 Transformers for training the model. To instantiate a `Trainer`, we will need to define the training configuration and an evaluation metric. The most important is the [`TrainingArguments`](https://huggingface.co/transformers/main_classes/trainer.html#transformers.TrainingArguments), which is a class that contains all the attributes to configure the training. It requires an output folder name, which will be used to save the checkpoints of the model. It also helps sync all the information in the model repository on 🤗 Hub.\n", + "\n", + "Most of the training arguments are pretty self-explanatory, but one that is quite important here is `remove_unused_columns=False`. This one will drop any features not used by the model's call function. By default it's `True` because usually it's ideal to drop unused feature columns, making it easier to unpack inputs into the model's call function. But, in our case, we need the unused features ('video' in particular) in order to create `pixel_values` (which is a mandatory key our model expects in its inputs)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "Z4DumIl1Qpdb" + }, + "outputs": [], + "source": [ + "from transformers import TrainingArguments, Trainer\n", + "\n", + "model_name = model_ckpt.split(\"/\")[-1]\n", + "new_model_name = f\"{model_name}-finetuned-ucf101-subset\"\n", + "num_epochs = 4\n", + "\n", + "args = TrainingArguments(\n", + " new_model_name,\n", + " remove_unused_columns=False,\n", + " evaluation_strategy=\"epoch\",\n", + " save_strategy=\"epoch\",\n", + " learning_rate=5e-5,\n", + " per_device_train_batch_size=batch_size,\n", + " per_device_eval_batch_size=batch_size,\n", + " warmup_ratio=0.1,\n", + " logging_steps=10,\n", + " load_best_model_at_end=True,\n", + " metric_for_best_model=\"accuracy\",\n", + " push_to_hub=True,\n", + " max_steps=(train_dataset.num_videos // batch_size) * num_epochs,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6Agf6aabAFDj" + }, + "source": [ + "There's no need to define `max_steps` when instantiating `TrainingArguments`. Since the dataset returned by `pytorchvideo.data.Ucf101()` doesn't implement the `__len__()` method we had to specify `max_steps`. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GNA25v_P2pqf" + }, + "source": [ + "Next, we need to define a function for how to compute the metrics from the predictions, which will just use the `metric` we'll load now. The only preprocessing we have to do is to take the argmax of our predicted logits:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49, + "referenced_widgets": [ + "72ce5912013c49f4b22366b6a4e11856", + "63a3cb1af2c94c3ab39a4ad54adb3901", + "7761bdc24ef642eebca4ddd5f3b562dc", + "8aa4d6eb1e8c4b73a5a1e1760fdd8491", + "a419dca4853d432b968f1c0bcdde3584", + "860eda03dd3545a3bcfb2856ab87fc2a", + "f25e259817164176bf6a61d1d03f971f", + "a06af5e772544ecd958a80c6e27ff1b5", + "bebc44b9de144576a888ddb458330acc", + "c8f3ccfe74fd4434b95662cebe822c37", + "3c43505235da40db8f4755015a30b699" + ] + }, + "id": "EWZIHEDTSddw", + "outputId": "d862b1b5-3dbf-46a3-eb6c-4be6701cf015" + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "72ce5912013c49f4b22366b6a4e11856", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading builder script: 0%| | 0.00/4.20k [00:00\n", + " \n", + " \n", + " [148/148 03:50, Epoch 3/9223372036854775807]\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
EpochTraining LossValidation LossAccuracy
02.1374001.7412830.571429
10.7949000.7746670.800000
20.4279000.4053410.914286
30.2910000.3428820.928571

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "***** Running Evaluation *****\n", + " Num examples: Unknown\n", + " Batch size = 8\n", + "Saving model checkpoint to videomae-base-finetuned-ucf101-subset/checkpoint-38\n", + "Configuration saved in videomae-base-finetuned-ucf101-subset/checkpoint-38/config.json\n", + "Model weights saved in videomae-base-finetuned-ucf101-subset/checkpoint-38/pytorch_model.bin\n", + "Feature extractor saved in videomae-base-finetuned-ucf101-subset/checkpoint-38/preprocessor_config.json\n", + "Feature extractor saved in videomae-base-finetuned-ucf101-subset/preprocessor_config.json\n", + "***** Running Evaluation *****\n", + " Num examples: Unknown\n", + " Batch size = 8\n", + "Saving model checkpoint to videomae-base-finetuned-ucf101-subset/checkpoint-76\n", + "Configuration saved in videomae-base-finetuned-ucf101-subset/checkpoint-76/config.json\n", + "Model weights saved in videomae-base-finetuned-ucf101-subset/checkpoint-76/pytorch_model.bin\n", + "Feature extractor saved in videomae-base-finetuned-ucf101-subset/checkpoint-76/preprocessor_config.json\n", + "***** Running Evaluation *****\n", + " Num examples: Unknown\n", + " Batch size = 8\n", + "Saving model checkpoint to videomae-base-finetuned-ucf101-subset/checkpoint-114\n", + "Configuration saved in videomae-base-finetuned-ucf101-subset/checkpoint-114/config.json\n", + "Model weights saved in videomae-base-finetuned-ucf101-subset/checkpoint-114/pytorch_model.bin\n", + "Feature extractor saved in videomae-base-finetuned-ucf101-subset/checkpoint-114/preprocessor_config.json\n", + "***** Running Evaluation *****\n", + " Num examples: Unknown\n", + " Batch size = 8\n", + "Saving model checkpoint to videomae-base-finetuned-ucf101-subset/checkpoint-148\n", + "Configuration saved in videomae-base-finetuned-ucf101-subset/checkpoint-148/config.json\n", + "Model weights saved in videomae-base-finetuned-ucf101-subset/checkpoint-148/pytorch_model.bin\n", + "Feature extractor saved in videomae-base-finetuned-ucf101-subset/checkpoint-148/preprocessor_config.json\n", + "\n", + "\n", + "Training completed. Do not forget to share your model on huggingface.co/models =)\n", + "\n", + "\n", + "Loading best model from videomae-base-finetuned-ucf101-subset/checkpoint-148 (score: 0.9285714285714286).\n" + ] + } + ], + "source": [ + "train_results = trainer.train()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RPyg-jgd3YPN" + }, + "source": [ + "We can check with the `evaluate` method that our `Trainer` did reload the best model properly (if it was not the last one):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "T9C-eDjZkoQC", + "outputId": "fb8e3ea6-ca6f-4c26-e339-c7d348e5f2eb" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "***** Running Evaluation *****\n", + " Num examples: Unknown\n", + " Batch size = 8\n" + ] + }, + { + "data": { + "text/plain": [ + "{'eval_loss': 0.3992488980293274,\n", + " 'eval_accuracy': 0.864516129032258,\n", + " 'eval_runtime': 14.1288,\n", + " 'eval_samples_per_second': 10.971,\n", + " 'eval_steps_per_second': 1.416,\n", + " 'epoch': 3.23}" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "trainer.evaluate(test_dataset)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 773, + "referenced_widgets": [ + "1f183008b3fd44c386ab6f261fcf2315", + "5908b424607c4958a5397970c59db243", + "89b7dfdf770344afae1ace10f2dce570", + "ae73a27a278f4515846a2476a3f7ba8f", + "58ca0e604a6e40a9a38348677e44e07f", + "1ab69fa2e53342a9a3c45c80cc45e4de", + "e3e09c7fba254320a49d00ff224e82f3", + "2873dde9c61241fba37fc46f60949fda", + "0933f36ee0f6428eab7b14be713b2ce0", + "e0b9d87d2d0c4aa093c5eba9de5f45ac", + "9e46b326fc04465eac707a311c322f25", + "d165e2dbf644425daa97807bd51e0266", + "4e3908955b6d40b1a32e32313b88058c", + "47c4d8aba191419094ac0fc2e526497c", + "f1406b17c63e4b749181a6ca94c5dd35", + "bd1dea9523e24784a7718bbfb7783b1f", + "a5967d8bfee846d9a7218e66d7c205d7", + "b337dba3465941928622326681041c4a", + "71d995077fd14827873776addb3f971a", + "8d8b0025c64749ef8279c380dd870daa", + "06b1d13fce394268adcf7ec754e86240", + "4b38a442cb344852b0709f7112a4432f", + "e7b3efb577d745fab7dd0a5c601e6790", + "f4244def2ed94015aed3f3c2eb9390c1", + "7504f080b0944b15a33167832d606c2a", + "ddcb2446584249b4bbae795402867d90", + "7f98eeea478e42238e342614905f25bf", + "c1a2b246d9d643efbe80cfb1c75c60b5", + "d2013ee5a5e6495886c29549010ea5a8", + "ce7a70b98f454ba3ba7bbc8f4c95fac8", + "8ce984fdd334464aade98bbdf9ca99e6", + "f316ded2fc6a41b3a59876f5242e7519", + "817b9b6abe4e42078e44aa0ee534bbe8" + ] + }, + "id": "hq9DR-qwkfwv", + "outputId": "ee9b6932-3e7f-4cf9-f328-68122954d98b" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Saving model checkpoint to videomae-base-finetuned-ucf101-subset\n", + "Configuration saved in videomae-base-finetuned-ucf101-subset/config.json\n", + "Model weights saved in videomae-base-finetuned-ucf101-subset/pytorch_model.bin\n", + "Feature extractor saved in videomae-base-finetuned-ucf101-subset/preprocessor_config.json\n", + "Saving model checkpoint to videomae-base-finetuned-ucf101-subset\n", + "Configuration saved in videomae-base-finetuned-ucf101-subset/config.json\n", + "Model weights saved in videomae-base-finetuned-ucf101-subset/pytorch_model.bin\n", + "Feature extractor saved in videomae-base-finetuned-ucf101-subset/preprocessor_config.json\n", + "Several commits (2) will be pushed upstream.\n", + "WARNING:huggingface_hub.repository:Several commits (2) will be pushed upstream.\n", + "The progress bars may be unreliable.\n", + "WARNING:huggingface_hub.repository:The progress bars may be unreliable.\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "1f183008b3fd44c386ab6f261fcf2315", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Upload file pytorch_model.bin: 0%| | 3.34k/329M [00:00 main\n", + "\n", + "WARNING:huggingface_hub.repository:remote: Scanning LFS files for validity, may be slow... \n", + "remote: LFS file scan complete. \n", + "To https://huggingface.co/sayakpaul/videomae-base-finetuned-ucf101-subset\n", + " 7e47bcb..9ad4c6d main -> main\n", + "\n", + "To https://huggingface.co/sayakpaul/videomae-base-finetuned-ucf101-subset\n", + " 9ad4c6d..e3ebcb5 main -> main\n", + "\n", + "WARNING:huggingface_hub.repository:To https://huggingface.co/sayakpaul/videomae-base-finetuned-ucf101-subset\n", + " 9ad4c6d..e3ebcb5 main -> main\n", + "\n", + "***** Running Evaluation *****\n", + " Num examples: Unknown\n", + " Batch size = 8\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "***** test metrics *****\n", + " epoch = 3.23\n", + " eval_accuracy = 0.8645\n", + " eval_loss = 0.3992\n", + " eval_runtime = 0:00:13.79\n", + " eval_samples_per_second = 11.233\n", + " eval_steps_per_second = 1.449\n" + ] + } + ], + "source": [ + "trainer.save_model()\n", + "test_results = trainer.evaluate(test_dataset)\n", + "trainer.log_metrics(\"test\", test_results)\n", + "trainer.save_metrics(\"test\", test_results)\n", + "trainer.save_state()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tCV83SVG3kDo" + }, + "source": [ + "You can now upload the result of the training to the Hub, just execute this instruction (note that the Trainer will automatically create a model card as well as Tensorboard logs - see the \"Training metrics\" tab - amazing isn't it?):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 310, + "referenced_widgets": [ + "60cde208bce141fc9cdc6f9e75d25fcd", + "ed3281d1f7ef462c9ea03fb11c801521", + "35756ebbee4b49988f449f147bb96358", + "49bb8d76e7164b8f9574f0e06ce03d75", + "d8f056d4273a491e9a29b27689a753c0", + "1da0fb7e57d843bcb8fbc42757d7dcc1", + "012c8742b9984d86a56836bcef74fedf", + "461b29f07f48447994e25e3e183aeef7", + "2aa86323603242a1928210b9926c6854", + "426e87090b1d41b898025e50e3f78a71", + "3f730122e7954b4d91549161c13aac29" + ] + }, + "id": "fkNll31Fn29k", + "outputId": "12789c64-a28b-45aa-8dc2-f375d02a0c17" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Saving model checkpoint to videomae-base-finetuned-ucf101-subset\n", + "Configuration saved in videomae-base-finetuned-ucf101-subset/config.json\n", + "Model weights saved in videomae-base-finetuned-ucf101-subset/pytorch_model.bin\n", + "Feature extractor saved in videomae-base-finetuned-ucf101-subset/preprocessor_config.json\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "60cde208bce141fc9cdc6f9e75d25fcd", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Upload file runs/Nov10_08-33-15_c4cf3c5cebad/events.out.tfevents.1668069624.c4cf3c5cebad.106.2: 100%|#########…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "remote: Scanning LFS files for validity, may be slow... \n", + "remote: LFS file scan complete. \n", + "To https://huggingface.co/sayakpaul/videomae-base-finetuned-ucf101-subset\n", + " e3ebcb5..60d2897 main -> main\n", + "\n", + "WARNING:huggingface_hub.repository:remote: Scanning LFS files for validity, may be slow... \n", + "remote: LFS file scan complete. \n", + "To https://huggingface.co/sayakpaul/videomae-base-finetuned-ucf101-subset\n", + " e3ebcb5..60d2897 main -> main\n", + "\n" + ] + }, + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'https://huggingface.co/sayakpaul/videomae-base-finetuned-ucf101-subset/commit/60d28970cff3c61201790c839f35a17936df4022'" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "trainer.push_to_hub()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tPacV3EX3qWT" + }, + "source": [ + "Now that our model is trained, let's use it to run inference on a video from `test_dataset`." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "NSSgIGsf3yqX" + }, + "source": [ + "## Inference" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "68858mLQ30VD" + }, + "source": [ + "Let's load the trained model checkpoint and fetch a video from `test_dataset`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "2EGrIj52NOjr", + "outputId": "f572cccc-1fee-4cbd-e6a1-26866941005a" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "loading configuration file videomae-base-finetuned-ucf101-subset/config.json\n", + "Model config VideoMAEConfig {\n", + " \"_name_or_path\": \"MCG-NJU/videomae-base\",\n", + " \"architectures\": [\n", + " \"VideoMAEForVideoClassification\"\n", + " ],\n", + " \"attention_probs_dropout_prob\": 0.0,\n", + " \"decoder_hidden_size\": 384,\n", + " \"decoder_intermediate_size\": 1536,\n", + " \"decoder_num_attention_heads\": 6,\n", + " \"decoder_num_hidden_layers\": 4,\n", + " \"hidden_act\": \"gelu\",\n", + " \"hidden_dropout_prob\": 0.0,\n", + " \"hidden_size\": 768,\n", + " \"id2label\": {\n", + " \"0\": \"ApplyEyeMakeup\",\n", + " \"1\": \"ApplyLipstick\",\n", + " \"2\": \"Archery\",\n", + " \"3\": \"BabyCrawling\",\n", + " \"4\": \"BalanceBeam\",\n", + " \"5\": \"BandMarching\",\n", + " \"6\": \"BaseballPitch\",\n", + " \"7\": \"Basketball\",\n", + " \"8\": \"BasketballDunk\",\n", + " \"9\": \"BenchPress\"\n", + " },\n", + " \"image_size\": 224,\n", + " \"initializer_range\": 0.02,\n", + " \"intermediate_size\": 3072,\n", + " \"label2id\": {\n", + " \"ApplyEyeMakeup\": 0,\n", + " \"ApplyLipstick\": 1,\n", + " \"Archery\": 2,\n", + " \"BabyCrawling\": 3,\n", + " \"BalanceBeam\": 4,\n", + " \"BandMarching\": 5,\n", + " \"BaseballPitch\": 6,\n", + " \"Basketball\": 7,\n", + " \"BasketballDunk\": 8,\n", + " \"BenchPress\": 9\n", + " },\n", + " \"layer_norm_eps\": 1e-12,\n", + " \"model_type\": \"videomae\",\n", + " \"norm_pix_loss\": true,\n", + " \"num_attention_heads\": 12,\n", + " \"num_channels\": 3,\n", + " \"num_frames\": 16,\n", + " \"num_hidden_layers\": 12,\n", + " \"patch_size\": 16,\n", + " \"problem_type\": \"single_label_classification\",\n", + " \"qkv_bias\": true,\n", + " \"torch_dtype\": \"float32\",\n", + " \"transformers_version\": \"4.24.0\",\n", + " \"tubelet_size\": 2,\n", + " \"use_mean_pooling\": false\n", + "}\n", + "\n", + "loading weights file videomae-base-finetuned-ucf101-subset/pytorch_model.bin\n", + "All model checkpoint weights were used when initializing VideoMAEForVideoClassification.\n", + "\n", + "All the weights of VideoMAEForVideoClassification were initialized from the model checkpoint at videomae-base-finetuned-ucf101-subset.\n", + "If your task is similar to the task the model of the checkpoint was trained on, you can already use VideoMAEForVideoClassification for predictions without further training.\n" + ] + } + ], + "source": [ + "trained_model = VideoMAEForVideoClassification.from_pretrained(new_model_name)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "A_yObs_zlflE", + "outputId": "eac1ad56-88df-4eb3-9711-bd71b9d0c3f4" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "video torch.Size([3, 16, 224, 224])\n", + "video_name v_BasketballDunk_g12_c05.avi\n", + "video_index 62\n", + "clip_index 0\n", + "aug_index 0\n", + "label 8\n", + "Video label: BasketballDunk\n" + ] + } + ], + "source": [ + "sample_test_video = next(iter(test_dataset))\n", + "investigate_video(sample_test_video)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RGJHV26538OU" + }, + "source": [ + "We then prepare the video as a `torch.Tensor` and run inference." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "JdlpFA34mp1O" + }, + "outputs": [], + "source": [ + "def run_inference(model, video):\n", + " \"\"\"Utility to run inference given a model and test video.\n", + "\n", + " The video is assumed to be preprocessed already.\n", + " \"\"\"\n", + " # (num_frames, num_channels, height, width)\n", + " perumuted_sample_test_video = video.permute(1, 0, 2, 3)\n", + "\n", + " inputs = {\n", + " \"pixel_values\": perumuted_sample_test_video.unsqueeze(0),\n", + " \"labels\": torch.tensor(\n", + " [sample_test_video[\"label\"]]\n", + " ), # this can be skipped if you don't have labels available.\n", + " }\n", + " device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", + " inputs = {k: v.to(device) for k, v in inputs.items()}\n", + " model = model.to(device)\n", + "\n", + " # forward pass\n", + " with torch.no_grad():\n", + " outputs = model(**inputs)\n", + " logits = outputs.logits\n", + "\n", + " return logits" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "ht-hpKLBnbS7" + }, + "outputs": [], + "source": [ + "logits = run_inference(trained_model, sample_test_video[\"video\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "PJ3sdzzx4De-" + }, + "source": [ + "We can now check if the model got the prediction right." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 241 + }, + "id": "i4gF4pIjoXPO", + "outputId": "6d8fa317-5c4c-41ce-809f-a8add981fc86" + }, + "outputs": [ + { + "data": { + "image/gif": 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+ "text/plain": [ + "" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "display_gif(sample_test_video[\"video\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "IE8TdTV_o9cm", + "outputId": "e9ce32d0-42b2-48f9-9ab0-8f2628ec96e1" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Predicted class: BasketballDunk\n" + ] + } + ], + "source": [ + "predicted_class_idx = logits.argmax(-1).item()\n", + "print(\"Predicted class:\", model.config.id2label[predicted_class_idx])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pdxWO1qO4PtH" + }, + "source": [ + "And it looks like it got it right!\n", + "\n", + "You can also use this model to bring in your own videos. Check out [this Space](https://huggingface.co/spaces/sayakpaul/video-classification-ucf101-subset) to know more. The Space will also show you how to run inference for a single video file.\n", + "\n", + "

\n", + " \n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "fWxR5SOwAFDo" + }, + "source": [ + "## Next steps\n", + "\n", + "Now that you've learned to train a well-performing video classification model on a custom dataset here is some homework for you:\n", + "\n", + "* Increase the dataset size: include more classes and more samples per class.\n", + "* Try out different hyperparameters to study how the model converges.\n", + "* Analyze the classes for which the model fails to perform well.\n", + "* Try out a different video encoder.\n", + "\n", + "Don't forget to share your models with the community =)" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "gpuClass": "premium", + "machine_shape": "hm", + "provenance": [] + }, + "gpuClass": "premium", + "kernelspec": { + "display_name": "v2a_haomin", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + 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+CACHE_DIR = os.getenv( + "AUDIOLDM_CACHE_DIR", + os.path.join(os.path.expanduser("~"), ".cache/audioldm")) + +parser = argparse.ArgumentParser() + +parser.add_argument( + "--mode", + type=str, + required=False, + default="generation", + help="generation: text-to-audio generation; transfer: style transfer", + choices=["generation", "transfer"] +) + +parser.add_argument( + "-t", + "--text", + type=str, + required=False, + default="", + help="Text prompt to the model for audio generation", +) + +parser.add_argument( + "-f", + "--file_path", + type=str, + required=False, + default=None, + help="(--mode transfer): Original audio file for style transfer; Or (--mode generation): the guidance audio file for generating simialr audio", +) + +parser.add_argument( + "--transfer_strength", + type=float, + required=False, + default=0.5, + help="A value between 0 and 1. 0 means original audio without transfer, 1 means completely transfer to the audio indicated by text", +) + +parser.add_argument( + "-s", + "--save_path", + type=str, + required=False, + help="The path to save model output", + default="./output", +) + +parser.add_argument( + "--model_name", + type=str, + required=False, + help="The checkpoint you gonna use", + default="audioldm-s-full", + choices=["audioldm-s-full", "audioldm-l-full", "audioldm-s-full-v2"] +) + +parser.add_argument( + "-ckpt", + "--ckpt_path", + type=str, + required=False, + help="The path to the pretrained .ckpt model", + default=None, +) + +parser.add_argument( + "-b", + "--batchsize", + type=int, + required=False, + default=1, + help="Generate how many samples at the same time", +) + +parser.add_argument( + "--ddim_steps", + type=int, + required=False, + default=200, + help="The sampling step for DDIM", +) + +parser.add_argument( + "-gs", + "--guidance_scale", + type=float, + required=False, + default=2.5, + help="Guidance scale (Large => better quality and relavancy to text; Small => better diversity)", +) + +parser.add_argument( + "-dur", + "--duration", + type=float, + required=False, + default=10.0, + help="The duration of the samples", +) + +parser.add_argument( + "-n", + "--n_candidate_gen_per_text", + type=int, + required=False, + default=3, + help="Automatic quality control. This number control the number of candidates (e.g., generate three audios and choose the best to show you). A Larger value usually lead to better quality with heavier computation", +) + +parser.add_argument( + "--seed", + type=int, + required=False, + default=42, + help="Change this value (any integer number) will lead to a different generation result.", +) + +args = parser.parse_args() + +if(args.ckpt_path is not None): + print("Warning: ckpt_path has no effect after version 0.0.20.") + +assert args.duration % 2.5 == 0, "Duration must be a multiple of 2.5" + +mode = args.mode +if(mode == "generation" and args.file_path is not None): + mode = "generation_audio_to_audio" + if(len(args.text) > 0): + print("Warning: You have specified the --file_path. --text will be ignored") + args.text = "" + +save_path = os.path.join(args.save_path, mode) + +if(args.file_path is not None): + save_path = os.path.join(save_path, os.path.basename(args.file_path.split(".")[0])) + +text = args.text +random_seed = args.seed +duration = args.duration +guidance_scale = args.guidance_scale +n_candidate_gen_per_text = args.n_candidate_gen_per_text + +os.makedirs(save_path, exist_ok=True) +audioldm = build_model(model_name=args.model_name) + +if(args.mode == "generation"): + waveform = text_to_audio( + audioldm, + text, + args.file_path, + random_seed, + duration=duration, + guidance_scale=guidance_scale, + ddim_steps=args.ddim_steps, + n_candidate_gen_per_text=n_candidate_gen_per_text, + batchsize=args.batchsize, + ) + +elif(args.mode == "transfer"): + assert args.file_path is not None + assert os.path.exists(args.file_path), "The original audio file \'%s\' for style transfer does not exist." % args.file_path + waveform = style_transfer( + audioldm, + text, + args.file_path, + args.transfer_strength, + random_seed, + duration=duration, + guidance_scale=guidance_scale, + ddim_steps=args.ddim_steps, + batchsize=args.batchsize, + ) + waveform = waveform[:,None,:] + +save_wave(waveform, save_path, name="%s_%s" % (get_time(), text)) diff --git a/src/audioldm/audio/__init__.py b/src/audioldm/audio/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..dfb71893f29e14d2039285cfb14a57fa5a5cba89 --- /dev/null +++ b/src/audioldm/audio/__init__.py @@ -0,0 +1,2 @@ +from .tools import wav_to_fbank, read_wav_file +from .stft import TacotronSTFT diff --git a/src/audioldm/audio/audio_processing.py b/src/audioldm/audio/audio_processing.py new file mode 100644 index 0000000000000000000000000000000000000000..00d130ef091a1a075547561aa68cce22d0d0650c --- /dev/null +++ b/src/audioldm/audio/audio_processing.py @@ -0,0 +1,100 @@ +import torch +import numpy as np +import librosa.util as librosa_util +from scipy.signal import get_window + + +def window_sumsquare( + window, + n_frames, + hop_length, + win_length, + n_fft, + dtype=np.float32, + norm=None, +): + """ + # from librosa 0.6 + Compute the sum-square envelope of a window function at a given hop length. + + This is used to estimate modulation effects induced by windowing + observations in short-time fourier transforms. + + Parameters + ---------- + window : string, tuple, number, callable, or list-like + Window specification, as in `get_window` + + n_frames : int > 0 + The number of analysis frames + + hop_length : int > 0 + The number of samples to advance between frames + + win_length : [optional] + The length of the window function. By default, this matches `n_fft`. + + n_fft : int > 0 + The length of each analysis frame. + + dtype : np.dtype + The data type of the output + + Returns + ------- + wss : np.ndarray, shape=`(n_fft + hop_length * (n_frames - 1))` + The sum-squared envelope of the window function + """ + if win_length is None: + win_length = n_fft + + n = n_fft + hop_length * (n_frames - 1) + x = np.zeros(n, dtype=dtype) + + # Compute the squared window at the desired length + win_sq = get_window(window, win_length, fftbins=True) + win_sq = librosa_util.normalize(win_sq, norm=norm) ** 2 + win_sq = librosa_util.pad_center(win_sq, n_fft) + + # Fill the envelope + for i in range(n_frames): + sample = i * hop_length + x[sample : min(n, sample + n_fft)] += win_sq[: max(0, min(n_fft, n - sample))] + return x + + +def griffin_lim(magnitudes, stft_fn, n_iters=30): + """ + PARAMS + ------ + magnitudes: spectrogram magnitudes + stft_fn: STFT class with transform (STFT) and inverse (ISTFT) methods + """ + + angles = np.angle(np.exp(2j * np.pi * np.random.rand(*magnitudes.size()))) + angles = angles.astype(np.float32) + angles = torch.autograd.Variable(torch.from_numpy(angles)) + signal = stft_fn.inverse(magnitudes, angles).squeeze(1) + + for i in range(n_iters): + _, angles = stft_fn.transform(signal) + signal = stft_fn.inverse(magnitudes, angles).squeeze(1) + return signal + + +def dynamic_range_compression(x, normalize_fun=torch.log, C=1, clip_val=1e-5): + """ + PARAMS + ------ + C: compression factor + """ + return normalize_fun(torch.clamp(x, min=clip_val) * C) + + +def dynamic_range_decompression(x, C=1): + """ + PARAMS + ------ + C: compression factor used to compress + """ + return torch.exp(x) / C diff --git a/src/audioldm/audio/stft.py b/src/audioldm/audio/stft.py new file mode 100644 index 0000000000000000000000000000000000000000..924489797058493815ecb64865f99b17f32f30b4 --- /dev/null +++ b/src/audioldm/audio/stft.py @@ -0,0 +1,186 @@ +import torch +import torch.nn.functional as F +import numpy as np +from scipy.signal import get_window +from librosa.util import pad_center, tiny +from librosa.filters import mel as librosa_mel_fn + +from audioldm.audio.audio_processing import ( + dynamic_range_compression, + dynamic_range_decompression, + window_sumsquare, +) + + +class STFT(torch.nn.Module): + """adapted from Prem Seetharaman's https://github.com/pseeth/pytorch-stft""" + + def __init__(self, filter_length, hop_length, win_length, window="hann"): + super(STFT, self).__init__() + self.filter_length = filter_length + self.hop_length = hop_length + self.win_length = win_length + self.window = window + self.forward_transform = None + scale = self.filter_length / self.hop_length + fourier_basis = np.fft.fft(np.eye(self.filter_length)) + + cutoff = int((self.filter_length / 2 + 1)) + fourier_basis = np.vstack( + [np.real(fourier_basis[:cutoff, :]), np.imag(fourier_basis[:cutoff, :])] + ) + + forward_basis = torch.FloatTensor(fourier_basis[:, None, :]) + inverse_basis = torch.FloatTensor( + np.linalg.pinv(scale * fourier_basis).T[:, None, :] + ) + + if window is not None: + assert filter_length >= win_length + # get window and zero center pad it to filter_length + fft_window = get_window(window, win_length, fftbins=True) + fft_window = pad_center(fft_window, filter_length) + fft_window = torch.from_numpy(fft_window).float() + + # window the bases + forward_basis *= fft_window + inverse_basis *= fft_window + + self.register_buffer("forward_basis", forward_basis.float()) + self.register_buffer("inverse_basis", inverse_basis.float()) + + def transform(self, input_data): + device = self.forward_basis.device + input_data = input_data.to(device) + + num_batches = input_data.size(0) + num_samples = input_data.size(1) + + self.num_samples = num_samples + + # similar to librosa, reflect-pad the input + input_data = input_data.view(num_batches, 1, num_samples) + input_data = F.pad( + input_data.unsqueeze(1), + (int(self.filter_length / 2), int(self.filter_length / 2), 0, 0), + mode="reflect", + ) + input_data = input_data.squeeze(1) + + forward_transform = F.conv1d( + input_data, + torch.autograd.Variable(self.forward_basis, requires_grad=False), + stride=self.hop_length, + padding=0, + )#.cpu() + + cutoff = int((self.filter_length / 2) + 1) + real_part = forward_transform[:, :cutoff, :] + imag_part = forward_transform[:, cutoff:, :] + + magnitude = torch.sqrt(real_part**2 + imag_part**2) + phase = torch.autograd.Variable(torch.atan2(imag_part.data, real_part.data)) + + return magnitude, phase + + def inverse(self, magnitude, phase): + device = self.forward_basis.device + magnitude, phase = magnitude.to(device), phase.to(device) + + recombine_magnitude_phase = torch.cat( + [magnitude * torch.cos(phase), magnitude * torch.sin(phase)], dim=1 + ) + + inverse_transform = F.conv_transpose1d( + recombine_magnitude_phase, + torch.autograd.Variable(self.inverse_basis, requires_grad=False), + stride=self.hop_length, + padding=0, + ) + + if self.window is not None: + window_sum = window_sumsquare( + self.window, + magnitude.size(-1), + hop_length=self.hop_length, + win_length=self.win_length, + n_fft=self.filter_length, + dtype=np.float32, + ) + # remove modulation effects + approx_nonzero_indices = torch.from_numpy( + np.where(window_sum > tiny(window_sum))[0] + ) + window_sum = torch.autograd.Variable( + torch.from_numpy(window_sum), requires_grad=False + ) + window_sum = window_sum + inverse_transform[:, :, approx_nonzero_indices] /= window_sum[ + approx_nonzero_indices + ] + + # scale by hop ratio + inverse_transform *= float(self.filter_length) / self.hop_length + + inverse_transform = inverse_transform[:, :, int(self.filter_length / 2) :] + inverse_transform = inverse_transform[:, :, : -int(self.filter_length / 2) :] + + return inverse_transform + + def forward(self, input_data): + self.magnitude, self.phase = self.transform(input_data) + reconstruction = self.inverse(self.magnitude, self.phase) + return reconstruction + + +class TacotronSTFT(torch.nn.Module): + def __init__( + self, + filter_length, + hop_length, + win_length, + n_mel_channels, + sampling_rate, + mel_fmin, + mel_fmax, + ): + super(TacotronSTFT, self).__init__() + self.n_mel_channels = n_mel_channels + self.sampling_rate = sampling_rate + self.stft_fn = STFT(filter_length, hop_length, win_length) + mel_basis = librosa_mel_fn( + sampling_rate, filter_length, n_mel_channels, mel_fmin, mel_fmax + ) + mel_basis = torch.from_numpy(mel_basis).float() + self.register_buffer("mel_basis", mel_basis) + + def spectral_normalize(self, magnitudes, normalize_fun): + output = dynamic_range_compression(magnitudes, normalize_fun) + return output + + def spectral_de_normalize(self, magnitudes): + output = dynamic_range_decompression(magnitudes) + return output + + def mel_spectrogram(self, y, normalize_fun=torch.log): + """Computes mel-spectrograms from a batch of waves + PARAMS + ------ + y: Variable(torch.FloatTensor) with shape (B, T) in range [-1, 1] + + RETURNS + ------- + mel_output: torch.FloatTensor of shape (B, n_mel_channels, T) + """ + assert torch.min(y.data) >= -1, torch.min(y.data) + assert torch.max(y.data) <= 1, torch.max(y.data) + + magnitudes, phases = self.stft_fn.transform(y) + magnitudes = magnitudes.data + mel_output = torch.matmul(self.mel_basis, magnitudes) + mel_output = self.spectral_normalize(mel_output, normalize_fun) + energy = torch.norm(magnitudes, dim=1) + + log_magnitudes = self.spectral_normalize(magnitudes, normalize_fun) + + return mel_output, log_magnitudes, energy diff --git a/src/audioldm/audio/tools.py b/src/audioldm/audio/tools.py new file mode 100644 index 0000000000000000000000000000000000000000..a3c8ba61f79761eceb445aaf14545ea1507ebefe --- /dev/null +++ b/src/audioldm/audio/tools.py @@ -0,0 +1,85 @@ +import torch +import numpy as np +import torchaudio + + +def get_mel_from_wav(audio, _stft): + audio = torch.clip(torch.FloatTensor(audio).unsqueeze(0), -1, 1) + audio = torch.autograd.Variable(audio, requires_grad=False) + melspec, log_magnitudes_stft, energy = _stft.mel_spectrogram(audio) + melspec = torch.squeeze(melspec, 0).numpy().astype(np.float32) + log_magnitudes_stft = ( + torch.squeeze(log_magnitudes_stft, 0).numpy().astype(np.float32) + ) + energy = torch.squeeze(energy, 0).numpy().astype(np.float32) + return melspec, log_magnitudes_stft, energy + + +def _pad_spec(fbank, target_length=1024): + n_frames = fbank.shape[0] + p = target_length - n_frames + # cut and pad + if p > 0: + m = torch.nn.ZeroPad2d((0, 0, 0, p)) + fbank = m(fbank) + elif p < 0: + fbank = fbank[0:target_length, :] + + if fbank.size(-1) % 2 != 0: + fbank = fbank[..., :-1] + + return fbank + + +def pad_wav(waveform, segment_length): + waveform_length = waveform.shape[-1] + assert waveform_length > 100, "Waveform is too short, %s" % waveform_length + if segment_length is None or waveform_length == segment_length: + return waveform + elif waveform_length > segment_length: + return waveform[:segment_length] + elif waveform_length < segment_length: + temp_wav = np.zeros((1, segment_length)) + temp_wav[:, :waveform_length] = waveform + return temp_wav + +def normalize_wav(waveform): + waveform = waveform - np.mean(waveform) + waveform = waveform / (np.max(np.abs(waveform)) + 1e-8) + return waveform * 0.5 + + +def read_wav_file(filename, segment_length): + # waveform, sr = librosa.load(filename, sr=None, mono=True) # 4 times slower + waveform, sr = torchaudio.load(filename) # Faster!!! + waveform = torchaudio.functional.resample(waveform, orig_freq=sr, new_freq=16000) + waveform = waveform.numpy()[0, ...] + waveform = normalize_wav(waveform) + waveform = waveform[None, ...] + waveform = pad_wav(waveform, segment_length) + + waveform = waveform / np.max(np.abs(waveform)) + waveform = 0.5 * waveform + + return waveform + + +def wav_to_fbank(filename, target_length=1024, fn_STFT=None): + assert fn_STFT is not None + + # mixup + waveform = read_wav_file(filename, target_length * 160) # hop size is 160 + + waveform = waveform[0, ...] + waveform = torch.FloatTensor(waveform) + + fbank, log_magnitudes_stft, energy = get_mel_from_wav(waveform, fn_STFT) + + fbank = torch.FloatTensor(fbank.T) + log_magnitudes_stft = torch.FloatTensor(log_magnitudes_stft.T) + + fbank, log_magnitudes_stft = _pad_spec(fbank, target_length), _pad_spec( + log_magnitudes_stft, target_length + ) + + return fbank, log_magnitudes_stft, waveform diff --git a/src/audioldm/clap/__init__.py b/src/audioldm/clap/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/src/audioldm/clap/encoders.py b/src/audioldm/clap/encoders.py new file mode 100644 index 0000000000000000000000000000000000000000..b4c55c623ecc435bf5ca01d587fe122d4bbaad9d --- /dev/null +++ b/src/audioldm/clap/encoders.py @@ -0,0 +1,170 @@ +import torch +import torch.nn as nn +from audioldm.clap.open_clip import create_model +from audioldm.clap.training.data import get_audio_features +import torchaudio +from transformers import RobertaTokenizer +import torch.nn.functional as F + + +class CLAPAudioEmbeddingClassifierFreev2(nn.Module): + def __init__( + self, + pretrained_path="", + key="class", + sampling_rate=16000, + embed_mode="audio", + amodel = "HTSAT-tiny", + unconditional_prob=0.1, + random_mute=False, + max_random_mute_portion=0.5, + training_mode=True, + ): + super().__init__() + + self.key = key + self.device = "cpu" + self.precision = "fp32" + self.amodel = amodel # or 'PANN-14' + self.tmodel = "roberta" # the best text encoder in our training + self.enable_fusion = False # False if you do not want to use the fusion model + self.fusion_type = "aff_2d" + self.pretrained = pretrained_path + self.embed_mode = embed_mode + self.embed_mode_orig = embed_mode + self.sampling_rate = sampling_rate + self.unconditional_prob = unconditional_prob + self.random_mute = random_mute + self.tokenize = RobertaTokenizer.from_pretrained("roberta-base") + self.max_random_mute_portion = max_random_mute_portion + self.training_mode = training_mode + self.model, self.model_cfg = create_model( + self.amodel, + self.tmodel, + self.pretrained, + precision=self.precision, + device=self.device, + enable_fusion=self.enable_fusion, + fusion_type=self.fusion_type, + ) + for p in self.model.parameters(): + p.requires_grad = False + + self.model.eval() + + def get_unconditional_condition(self, batchsize): + self.unconditional_token = self.model.get_text_embedding( + self.tokenizer(["", ""]) + )[0:1] + return torch.cat([self.unconditional_token.unsqueeze(0)] * batchsize, dim=0) + + def batch_to_list(self, batch): + ret = [] + for i in range(batch.size(0)): + ret.append(batch[i]) + return ret + + def make_decision(self, probability): + if float(torch.rand(1)) < probability: + return True + else: + return False + + def random_uniform(self, start, end): + val = torch.rand(1).item() + return start + (end - start) * val + + def _random_mute(self, waveform): + # waveform: [bs, t-steps] + t_steps = waveform.size(-1) + for i in range(waveform.size(0)): + mute_size = int( + self.random_uniform(0, end=int(t_steps * self.max_random_mute_portion)) + ) + mute_start = int(self.random_uniform(0, t_steps - mute_size)) + waveform[i, mute_start : mute_start + mute_size] = 0 + return waveform + + def cos_similarity(self, waveform, text): + # waveform: [bs, t_steps] + with torch.no_grad(): + self.embed_mode = "audio" + audio_emb = self(waveform.cuda()) + self.embed_mode = "text" + text_emb = self(text) + similarity = F.cosine_similarity(audio_emb, text_emb, dim=2), audio_emb, text_emb + return similarity.squeeze() + + def forward(self, batch, key=None): + # If you want this conditioner to be unconditional, set self.unconditional_prob = 1.0 + # If you want this conditioner to be fully conditional, set self.unconditional_prob = 0.0 + if self.model.training == True and not self.training_mode: + print( + "The pretrained CLAP model should always be in eval mode. Reloading model just in case you change the parameters." + ) + self.model, self.model_cfg = create_model( + self.amodel, + self.tmodel, + self.pretrained, + precision=self.precision, + device="cuda", + enable_fusion=self.enable_fusion, + fusion_type=self.fusion_type, + ) + for p in self.model.parameters(): + p.requires_grad = False + self.model.eval() + + # the 'fusion' truncate mode can be changed to 'rand_trunc' if run in unfusion mode + if self.embed_mode == "audio": + with torch.no_grad(): + audio_dict_list = [] + assert ( + self.sampling_rate == 16000 + ), "We only support 16000 sampling rate" + if self.random_mute: + batch = self._random_mute(batch) + # batch: [bs, 1, t-samples] + batch = torchaudio.functional.resample( + batch, orig_freq=self.sampling_rate, new_freq=48000 + ) + for waveform in self.batch_to_list(batch): + audio_dict = {} + audio_dict = get_audio_features( + audio_dict, + waveform, + 480000, + data_truncating="fusion", + data_filling="repeatpad", + audio_cfg=self.model_cfg["audio_cfg"], + ) + audio_dict_list.append(audio_dict) + # [bs, 512] + embed = self.model.get_audio_embedding(audio_dict_list) + elif self.embed_mode == "text": + with torch.no_grad(): + # the 'fusion' truncate mode can be changed to 'rand_trunc' if run in unfusion mode + text_data = self.tokenizer(batch) + embed = self.model.get_text_embedding(text_data) + + embed = embed.unsqueeze(1) + self.unconditional_token = self.model.get_text_embedding( + self.tokenizer(["", ""]) + )[0:1] + + for i in range(embed.size(0)): + if self.make_decision(self.unconditional_prob): + embed[i] = self.unconditional_token + + # [bs, 1, 512] + return embed.detach() + + def tokenizer(self, text): + result = self.tokenize( + text, + padding="max_length", + truncation=True, + max_length=512, + return_tensors="pt", + ) + return {k: v.squeeze(0) for k, v in result.items()} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/__init__.py b/src/audioldm/clap/open_clip/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..6bb144d1ae834a4d131daa2107002f186c89b07b --- /dev/null +++ b/src/audioldm/clap/open_clip/__init__.py @@ -0,0 +1,25 @@ +from .factory import ( + list_models, + create_model, + create_model_and_transforms, + add_model_config, +) +from .loss import ClipLoss, gather_features, LPLoss, lp_gather_features, LPMetrics +from .model import ( + CLAP, + CLAPTextCfg, + CLAPVisionCfg, + CLAPAudioCfp, + convert_weights_to_fp16, + trace_model, +) +from .openai import load_openai_model, list_openai_models +from .pretrained import ( + list_pretrained, + list_pretrained_tag_models, + list_pretrained_model_tags, + get_pretrained_url, + download_pretrained, +) +from .tokenizer import SimpleTokenizer, tokenize +from .transform import image_transform diff --git a/src/audioldm/clap/open_clip/bert.py b/src/audioldm/clap/open_clip/bert.py new file mode 100644 index 0000000000000000000000000000000000000000..2974147779c5b5f2070958cb2744df422f00bb5b --- /dev/null +++ b/src/audioldm/clap/open_clip/bert.py @@ -0,0 +1,40 @@ +from transformers import BertTokenizer, BertModel + +tokenizer = BertTokenizer.from_pretrained("bert-base-uncased") +model = BertModel.from_pretrained("bert-base-uncased") +text = "Replace me by any text you'd like." + + +def bert_embeddings(text): + # text = "Replace me by any text you'd like." + encoded_input = tokenizer(text, return_tensors="pt") + output = model(**encoded_input) + return output + + +from transformers import RobertaTokenizer, RobertaModel + +tokenizer = RobertaTokenizer.from_pretrained("roberta-base") +model = RobertaModel.from_pretrained("roberta-base") +text = "Replace me by any text you'd like." + + +def Roberta_embeddings(text): + # text = "Replace me by any text you'd like." + encoded_input = tokenizer(text, return_tensors="pt") + output = model(**encoded_input) + return output + + +from transformers import BartTokenizer, BartModel + +tokenizer = BartTokenizer.from_pretrained("facebook/bart-base") +model = BartModel.from_pretrained("facebook/bart-base") +text = "Replace me by any text you'd like." + + +def bart_embeddings(text): + # text = "Replace me by any text you'd like." + encoded_input = tokenizer(text, return_tensors="pt") + output = model(**encoded_input) + return output diff --git a/src/audioldm/clap/open_clip/bpe_simple_vocab_16e6.txt.gz b/src/audioldm/clap/open_clip/bpe_simple_vocab_16e6.txt.gz new file mode 100644 index 0000000000000000000000000000000000000000..36a15856e00a06a9fbed8cdd34d2393fea4a3113 --- /dev/null +++ b/src/audioldm/clap/open_clip/bpe_simple_vocab_16e6.txt.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:924691ac288e54409236115652ad4aa250f48203de50a9e4722a6ecd48d6804a +size 1356917 diff --git a/src/audioldm/clap/open_clip/factory.py b/src/audioldm/clap/open_clip/factory.py new file mode 100644 index 0000000000000000000000000000000000000000..fbe5f9c4832c650a8d55c49c8deb556007342b76 --- /dev/null +++ b/src/audioldm/clap/open_clip/factory.py @@ -0,0 +1,279 @@ +import json +import logging +import os +import pathlib +import re +from copy import deepcopy +from pathlib import Path + +import torch + +from .model import CLAP, convert_weights_to_fp16 +from .openai import load_openai_model +from .pretrained import get_pretrained_url, download_pretrained +from .transform import image_transform + +_MODEL_CONFIG_PATHS = [Path(__file__).parent / f"model_configs/"] +_MODEL_CONFIGS = {} # directory (model_name: config) of model architecture configs +CACHE_DIR = os.getenv("AUDIOLDM_CACHE_DIR", "~/.cache/audioldm") + + + +def _natural_key(string_): + return [int(s) if s.isdigit() else s for s in re.split(r"(\d+)", string_.lower())] + + +def _rescan_model_configs(): + global _MODEL_CONFIGS + + config_ext = (".json",) + config_files = [] + for config_path in _MODEL_CONFIG_PATHS: + if config_path.is_file() and config_path.suffix in config_ext: + config_files.append(config_path) + elif config_path.is_dir(): + for ext in config_ext: + config_files.extend(config_path.glob(f"*{ext}")) + + for cf in config_files: + if os.path.basename(cf)[0] == ".": + continue # Ignore hidden files + + with open(cf, "r") as f: + model_cfg = json.load(f) + if all(a in model_cfg for a in ("embed_dim", "audio_cfg", "text_cfg")): + _MODEL_CONFIGS[cf.stem] = model_cfg + + _MODEL_CONFIGS = { + k: v + for k, v in sorted(_MODEL_CONFIGS.items(), key=lambda x: _natural_key(x[0])) + } + + +_rescan_model_configs() # initial populate of model config registry + + +def load_state_dict(checkpoint_path: str, map_location="cpu", skip_params=True): + checkpoint = torch.load(checkpoint_path, map_location=map_location) + if isinstance(checkpoint, dict) and "state_dict" in checkpoint: + state_dict = checkpoint["state_dict"] + else: + state_dict = checkpoint + if skip_params: + if next(iter(state_dict.items()))[0].startswith("module"): + state_dict = {k[7:]: v for k, v in state_dict.items()} + # for k in state_dict: + # if k.startswith('transformer'): + # v = state_dict.pop(k) + # state_dict['text_branch.' + k[12:]] = v + return state_dict + + +def create_model( + amodel_name: str, + tmodel_name: str, + pretrained: str = "", + precision: str = "fp32", + device: torch.device = torch.device("cpu"), + jit: bool = False, + force_quick_gelu: bool = False, + openai_model_cache_dir: str = os.path.expanduser(f"{CACHE_DIR}/clip"), + skip_params=True, + pretrained_audio: str = "", + pretrained_text: str = "", + enable_fusion: bool = False, + fusion_type: str = "None" + # pretrained_image: bool = False, +): + amodel_name = amodel_name.replace( + "/", "-" + ) # for callers using old naming with / in ViT names + pretrained_orig = pretrained + pretrained = pretrained.lower() + if pretrained == "openai": + if amodel_name in _MODEL_CONFIGS: + logging.info(f"Loading {amodel_name} model config.") + model_cfg = deepcopy(_MODEL_CONFIGS[amodel_name]) + else: + logging.error( + f"Model config for {amodel_name} not found; available models {list_models()}." + ) + raise RuntimeError(f"Model config for {amodel_name} not found.") + + logging.info(f"Loading pretrained ViT-B-16 text encoder from OpenAI.") + # Hard Code in model name + model_cfg["text_cfg"]["model_type"] = tmodel_name + model = load_openai_model( + "ViT-B-16", + model_cfg, + device=device, + jit=jit, + cache_dir=openai_model_cache_dir, + enable_fusion=enable_fusion, + fusion_type=fusion_type, + ) + # See https://discuss.pytorch.org/t/valueerror-attemting-to-unscale-fp16-gradients/81372 + if precision == "amp" or precision == "fp32": + model = model.float() + else: + if amodel_name in _MODEL_CONFIGS: + logging.info(f"Loading {amodel_name} model config.") + model_cfg = deepcopy(_MODEL_CONFIGS[amodel_name]) + else: + logging.error( + f"Model config for {amodel_name} not found; available models {list_models()}." + ) + raise RuntimeError(f"Model config for {amodel_name} not found.") + + if force_quick_gelu: + # override for use of QuickGELU on non-OpenAI transformer models + model_cfg["quick_gelu"] = True + + # if pretrained_image: + # if 'timm_amodel_name' in model_cfg.get('vision_cfg', {}): + # # pretrained weight loading for timm models set via vision_cfg + # model_cfg['vision_cfg']['timm_model_pretrained'] = True + # else: + # assert False, 'pretrained image towers currently only supported for timm models' + model_cfg["text_cfg"]["model_type"] = tmodel_name + model_cfg["enable_fusion"] = enable_fusion + model_cfg["fusion_type"] = fusion_type + model = CLAP(**model_cfg) + + if pretrained: + checkpoint_path = "" + url = get_pretrained_url(amodel_name, pretrained) + if url: + checkpoint_path = download_pretrained(url, root=openai_model_cache_dir) + elif os.path.exists(pretrained_orig): + checkpoint_path = pretrained_orig + if checkpoint_path: + logging.info( + f"Loading pretrained {amodel_name}-{tmodel_name} weights ({pretrained})." + ) + ckpt = load_state_dict(checkpoint_path, skip_params=True) + model.load_state_dict(ckpt) + param_names = [n for n, p in model.named_parameters()] + # for n in param_names: + # print(n, "\t", "Loaded" if n in ckpt else "Unloaded") + else: + logging.warning( + f"Pretrained weights ({pretrained}) not found for model {amodel_name}." + ) + raise RuntimeError( + f"Pretrained weights ({pretrained}) not found for model {amodel_name}." + ) + + if pretrained_audio: + if amodel_name.startswith("PANN"): + if "Cnn14_mAP" in pretrained_audio: # official checkpoint + audio_ckpt = torch.load(pretrained_audio, map_location="cpu") + audio_ckpt = audio_ckpt["model"] + keys = list(audio_ckpt.keys()) + for key in keys: + if ( + "spectrogram_extractor" not in key + and "logmel_extractor" not in key + ): + v = audio_ckpt.pop(key) + audio_ckpt["audio_branch." + key] = v + elif os.path.basename(pretrained_audio).startswith( + "PANN" + ): # checkpoint trained via HTSAT codebase + audio_ckpt = torch.load(pretrained_audio, map_location="cpu") + audio_ckpt = audio_ckpt["state_dict"] + keys = list(audio_ckpt.keys()) + for key in keys: + if key.startswith("sed_model"): + v = audio_ckpt.pop(key) + audio_ckpt["audio_branch." + key[10:]] = v + elif os.path.basename(pretrained_audio).startswith( + "finetuned" + ): # checkpoint trained via linear probe codebase + audio_ckpt = torch.load(pretrained_audio, map_location="cpu") + else: + raise ValueError("Unknown audio checkpoint") + elif amodel_name.startswith("HTSAT"): + if "HTSAT_AudioSet_Saved" in pretrained_audio: # official checkpoint + audio_ckpt = torch.load(pretrained_audio, map_location="cpu") + audio_ckpt = audio_ckpt["state_dict"] + keys = list(audio_ckpt.keys()) + for key in keys: + if key.startswith("sed_model") and ( + "spectrogram_extractor" not in key + and "logmel_extractor" not in key + ): + v = audio_ckpt.pop(key) + audio_ckpt["audio_branch." + key[10:]] = v + elif os.path.basename(pretrained_audio).startswith( + "HTSAT" + ): # checkpoint trained via HTSAT codebase + audio_ckpt = torch.load(pretrained_audio, map_location="cpu") + audio_ckpt = audio_ckpt["state_dict"] + keys = list(audio_ckpt.keys()) + for key in keys: + if key.startswith("sed_model"): + v = audio_ckpt.pop(key) + audio_ckpt["audio_branch." + key[10:]] = v + elif os.path.basename(pretrained_audio).startswith( + "finetuned" + ): # checkpoint trained via linear probe codebase + audio_ckpt = torch.load(pretrained_audio, map_location="cpu") + else: + raise ValueError("Unknown audio checkpoint") + else: + raise f"this audio encoder pretrained checkpoint is not support" + + model.load_state_dict(audio_ckpt, strict=False) + logging.info( + f"Loading pretrained {amodel_name} weights ({pretrained_audio})." + ) + param_names = [n for n, p in model.named_parameters()] + for n in param_names: + print(n, "\t", "Loaded" if n in audio_ckpt else "Unloaded") + + model.to(device=device) + if precision == "fp16": + assert device.type != "cpu" + convert_weights_to_fp16(model) + + if jit: + model = torch.jit.script(model) + + return model, model_cfg + + +def create_model_and_transforms( + model_name: str, + pretrained: str = "", + precision: str = "fp32", + device: torch.device = torch.device("cpu"), + jit: bool = False, + force_quick_gelu: bool = False, + # pretrained_image: bool = False, +): + model = create_model( + model_name, + pretrained, + precision, + device, + jit, + force_quick_gelu=force_quick_gelu, + # pretrained_image=pretrained_image + ) + preprocess_train = image_transform(model.visual.image_size, is_train=True) + preprocess_val = image_transform(model.visual.image_size, is_train=False) + return model, preprocess_train, preprocess_val + + +def list_models(): + """enumerate available model architectures based on config files""" + return list(_MODEL_CONFIGS.keys()) + + +def add_model_config(path): + """add model config path or file and update registry""" + if not isinstance(path, Path): + path = Path(path) + _MODEL_CONFIG_PATHS.append(path) + _rescan_model_configs() \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/feature_fusion.py b/src/audioldm/clap/open_clip/feature_fusion.py new file mode 100644 index 0000000000000000000000000000000000000000..703a4a90ed13e4908d5fd9535e9edbb0c502a0cf --- /dev/null +++ b/src/audioldm/clap/open_clip/feature_fusion.py @@ -0,0 +1,192 @@ +""" +Feature Fusion for Varible-Length Data Processing +AFF/iAFF is referred and modified from https://github.com/YimianDai/open-aff/blob/master/aff_pytorch/aff_net/fusion.py +According to the paper: Yimian Dai et al, Attentional Feature Fusion, IEEE Winter Conference on Applications of Computer Vision, WACV 2021 +""" + +import torch +import torch.nn as nn + + +class DAF(nn.Module): + """ + 直接相加 DirectAddFuse + """ + + def __init__(self): + super(DAF, self).__init__() + + def forward(self, x, residual): + return x + residual + + +class iAFF(nn.Module): + """ + 多特征融合 iAFF + """ + + def __init__(self, channels=64, r=4, type="2D"): + super(iAFF, self).__init__() + inter_channels = int(channels // r) + + if type == "1D": + # 本地注意力 + self.local_att = nn.Sequential( + nn.Conv1d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv1d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(channels), + ) + + # 全局注意力 + self.global_att = nn.Sequential( + nn.AdaptiveAvgPool1d(1), + nn.Conv1d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv1d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(channels), + ) + + # 第二次本地注意力 + self.local_att2 = nn.Sequential( + nn.Conv1d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv1d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(channels), + ) + # 第二次全局注意力 + self.global_att2 = nn.Sequential( + nn.AdaptiveAvgPool1d(1), + nn.Conv1d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv1d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(channels), + ) + elif type == "2D": + # 本地注意力 + self.local_att = nn.Sequential( + nn.Conv2d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv2d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(channels), + ) + + # 全局注意力 + self.global_att = nn.Sequential( + nn.AdaptiveAvgPool2d(1), + nn.Conv2d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv2d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(channels), + ) + + # 第二次本地注意力 + self.local_att2 = nn.Sequential( + nn.Conv2d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv2d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(channels), + ) + # 第二次全局注意力 + self.global_att2 = nn.Sequential( + nn.AdaptiveAvgPool2d(1), + nn.Conv2d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv2d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(channels), + ) + else: + raise f"the type is not supported" + + self.sigmoid = nn.Sigmoid() + + def forward(self, x, residual): + flag = False + xa = x + residual + if xa.size(0) == 1: + xa = torch.cat([xa, xa], dim=0) + flag = True + xl = self.local_att(xa) + xg = self.global_att(xa) + xlg = xl + xg + wei = self.sigmoid(xlg) + xi = x * wei + residual * (1 - wei) + + xl2 = self.local_att2(xi) + xg2 = self.global_att(xi) + xlg2 = xl2 + xg2 + wei2 = self.sigmoid(xlg2) + xo = x * wei2 + residual * (1 - wei2) + if flag: + xo = xo[0].unsqueeze(0) + return xo + + +class AFF(nn.Module): + """ + 多特征融合 AFF + """ + + def __init__(self, channels=64, r=4, type="2D"): + super(AFF, self).__init__() + inter_channels = int(channels // r) + + if type == "1D": + self.local_att = nn.Sequential( + nn.Conv1d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv1d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(channels), + ) + self.global_att = nn.Sequential( + nn.AdaptiveAvgPool1d(1), + nn.Conv1d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv1d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm1d(channels), + ) + elif type == "2D": + self.local_att = nn.Sequential( + nn.Conv2d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv2d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(channels), + ) + self.global_att = nn.Sequential( + nn.AdaptiveAvgPool2d(1), + nn.Conv2d(channels, inter_channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(inter_channels), + nn.ReLU(inplace=True), + nn.Conv2d(inter_channels, channels, kernel_size=1, stride=1, padding=0), + nn.BatchNorm2d(channels), + ) + else: + raise f"the type is not supported." + + self.sigmoid = nn.Sigmoid() + + def forward(self, x, residual): + flag = False + xa = x + residual + if xa.size(0) == 1: + xa = torch.cat([xa, xa], dim=0) + flag = True + xl = self.local_att(xa) + xg = self.global_att(xa) + xlg = xl + xg + wei = self.sigmoid(xlg) + xo = 2 * x * wei + 2 * residual * (1 - wei) + if flag: + xo = xo[0].unsqueeze(0) + return xo diff --git a/src/audioldm/clap/open_clip/htsat.py b/src/audioldm/clap/open_clip/htsat.py new file mode 100644 index 0000000000000000000000000000000000000000..76e2805457e7680a2282153a60295472f105b8f8 --- /dev/null +++ b/src/audioldm/clap/open_clip/htsat.py @@ -0,0 +1,1308 @@ +# Ke Chen +# knutchen@ucsd.edu +# HTS-AT: A HIERARCHICAL TOKEN-SEMANTIC AUDIO TRANSFORMER FOR SOUND CLASSIFICATION AND DETECTION +# Some layers designed on the model +# below codes are based and referred from https://github.com/microsoft/Swin-Transformer +# Swin Transformer for Computer Vision: https://arxiv.org/pdf/2103.14030.pdf + +import torch +import torch.nn as nn +import torch.nn.functional as F +from itertools import repeat +import collections.abc +import math +import warnings + +from torch.nn.init import _calculate_fan_in_and_fan_out +import torch.utils.checkpoint as checkpoint + +import random + +from torchlibrosa.stft import Spectrogram, LogmelFilterBank +from torchlibrosa.augmentation import SpecAugmentation + +from itertools import repeat +from .utils import do_mixup, interpolate + +from .feature_fusion import iAFF, AFF, DAF + +# from PyTorch internals +def _ntuple(n): + def parse(x): + if isinstance(x, collections.abc.Iterable): + return x + return tuple(repeat(x, n)) + + return parse + + +to_1tuple = _ntuple(1) +to_2tuple = _ntuple(2) +to_3tuple = _ntuple(3) +to_4tuple = _ntuple(4) +to_ntuple = _ntuple + + +def drop_path(x, drop_prob: float = 0.0, training: bool = False): + """Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks). + This is the same as the DropConnect impl I created for EfficientNet, etc networks, however, + the original name is misleading as 'Drop Connect' is a different form of dropout in a separate paper... + See discussion: https://github.com/tensorflow/tpu/issues/494#issuecomment-532968956 ... I've opted for + changing the layer and argument names to 'drop path' rather than mix DropConnect as a layer name and use + 'survival rate' as the argument. + """ + if drop_prob == 0.0 or not training: + return x + keep_prob = 1 - drop_prob + shape = (x.shape[0],) + (1,) * ( + x.ndim - 1 + ) # work with diff dim tensors, not just 2D ConvNets + random_tensor = keep_prob + torch.rand(shape, dtype=x.dtype, device=x.device) + random_tensor.floor_() # binarize + output = x.div(keep_prob) * random_tensor + return output + + +class DropPath(nn.Module): + """Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).""" + + def __init__(self, drop_prob=None): + super(DropPath, self).__init__() + self.drop_prob = drop_prob + + def forward(self, x): + return drop_path(x, self.drop_prob, self.training) + + +class PatchEmbed(nn.Module): + """2D Image to Patch Embedding""" + + def __init__( + self, + img_size=224, + patch_size=16, + in_chans=3, + embed_dim=768, + norm_layer=None, + flatten=True, + patch_stride=16, + enable_fusion=False, + fusion_type="None", + ): + super().__init__() + img_size = to_2tuple(img_size) + patch_size = to_2tuple(patch_size) + patch_stride = to_2tuple(patch_stride) + self.img_size = img_size + self.patch_size = patch_size + self.patch_stride = patch_stride + self.grid_size = ( + img_size[0] // patch_stride[0], + img_size[1] // patch_stride[1], + ) + self.num_patches = self.grid_size[0] * self.grid_size[1] + self.flatten = flatten + self.in_chans = in_chans + self.embed_dim = embed_dim + + self.enable_fusion = enable_fusion + self.fusion_type = fusion_type + + padding = ( + (patch_size[0] - patch_stride[0]) // 2, + (patch_size[1] - patch_stride[1]) // 2, + ) + + if (self.enable_fusion) and (self.fusion_type == "channel_map"): + self.proj = nn.Conv2d( + in_chans * 4, + embed_dim, + kernel_size=patch_size, + stride=patch_stride, + padding=padding, + ) + else: + self.proj = nn.Conv2d( + in_chans, + embed_dim, + kernel_size=patch_size, + stride=patch_stride, + padding=padding, + ) + self.norm = norm_layer(embed_dim) if norm_layer else nn.Identity() + + if (self.enable_fusion) and ( + self.fusion_type in ["daf_2d", "aff_2d", "iaff_2d"] + ): + self.mel_conv2d = nn.Conv2d( + in_chans, + embed_dim, + kernel_size=(patch_size[0], patch_size[1] * 3), + stride=(patch_stride[0], patch_stride[1] * 3), + padding=padding, + ) + if self.fusion_type == "daf_2d": + self.fusion_model = DAF() + elif self.fusion_type == "aff_2d": + self.fusion_model = AFF(channels=embed_dim, type="2D") + elif self.fusion_type == "iaff_2d": + self.fusion_model = iAFF(channels=embed_dim, type="2D") + + def forward(self, x, longer_idx=None): + if (self.enable_fusion) and ( + self.fusion_type in ["daf_2d", "aff_2d", "iaff_2d"] + ): + global_x = x[:, 0:1, :, :] + + # global processing + B, C, H, W = global_x.shape + assert ( + H == self.img_size[0] and W == self.img_size[1] + ), f"Input image size ({H}*{W}) doesn't match model ({self.img_size[0]}*{self.img_size[1]})." + global_x = self.proj(global_x) + TW = global_x.size(-1) + if len(longer_idx) > 0: + # local processing + local_x = x[longer_idx, 1:, :, :].contiguous() + B, C, H, W = local_x.shape + local_x = local_x.view(B * C, 1, H, W) + local_x = self.mel_conv2d(local_x) + local_x = local_x.view( + B, C, local_x.size(1), local_x.size(2), local_x.size(3) + ) + local_x = local_x.permute((0, 2, 3, 1, 4)).contiguous().flatten(3) + TB, TC, TH, _ = local_x.size() + if local_x.size(-1) < TW: + local_x = torch.cat( + [ + local_x, + torch.zeros( + (TB, TC, TH, TW - local_x.size(-1)), + device=global_x.device, + ), + ], + dim=-1, + ) + else: + local_x = local_x[:, :, :, :TW] + + global_x[longer_idx] = self.fusion_model(global_x[longer_idx], local_x) + x = global_x + else: + B, C, H, W = x.shape + assert ( + H == self.img_size[0] and W == self.img_size[1] + ), f"Input image size ({H}*{W}) doesn't match model ({self.img_size[0]}*{self.img_size[1]})." + x = self.proj(x) + + if self.flatten: + x = x.flatten(2).transpose(1, 2) # BCHW -> BNC + x = self.norm(x) + return x + + +class Mlp(nn.Module): + """MLP as used in Vision Transformer, MLP-Mixer and related networks""" + + def __init__( + self, + in_features, + hidden_features=None, + out_features=None, + act_layer=nn.GELU, + drop=0.0, + ): + super().__init__() + out_features = out_features or in_features + hidden_features = hidden_features or in_features + self.fc1 = nn.Linear(in_features, hidden_features) + self.act = act_layer() + self.fc2 = nn.Linear(hidden_features, out_features) + self.drop = nn.Dropout(drop) + + def forward(self, x): + x = self.fc1(x) + x = self.act(x) + x = self.drop(x) + x = self.fc2(x) + x = self.drop(x) + return x + + +def _no_grad_trunc_normal_(tensor, mean, std, a, b): + # Cut & paste from PyTorch official master until it's in a few official releases - RW + # Method based on https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf + def norm_cdf(x): + # Computes standard normal cumulative distribution function + return (1.0 + math.erf(x / math.sqrt(2.0))) / 2.0 + + if (mean < a - 2 * std) or (mean > b + 2 * std): + warnings.warn( + "mean is more than 2 std from [a, b] in nn.init.trunc_normal_. " + "The distribution of values may be incorrect.", + stacklevel=2, + ) + + with torch.no_grad(): + # Values are generated by using a truncated uniform distribution and + # then using the inverse CDF for the normal distribution. + # Get upper and lower cdf values + l = norm_cdf((a - mean) / std) + u = norm_cdf((b - mean) / std) + + # Uniformly fill tensor with values from [l, u], then translate to + # [2l-1, 2u-1]. + tensor.uniform_(2 * l - 1, 2 * u - 1) + + # Use inverse cdf transform for normal distribution to get truncated + # standard normal + tensor.erfinv_() + + # Transform to proper mean, std + tensor.mul_(std * math.sqrt(2.0)) + tensor.add_(mean) + + # Clamp to ensure it's in the proper range + tensor.clamp_(min=a, max=b) + return tensor + + +def trunc_normal_(tensor, mean=0.0, std=1.0, a=-2.0, b=2.0): + # type: (Tensor, float, float, float, float) -> Tensor + r"""Fills the input Tensor with values drawn from a truncated + normal distribution. The values are effectively drawn from the + normal distribution :math:`\mathcal{N}(\text{mean}, \text{std}^2)` + with values outside :math:`[a, b]` redrawn until they are within + the bounds. The method used for generating the random values works + best when :math:`a \leq \text{mean} \leq b`. + Args: + tensor: an n-dimensional `torch.Tensor` + mean: the mean of the normal distribution + std: the standard deviation of the normal distribution + a: the minimum cutoff value + b: the maximum cutoff value + Examples: + >>> w = torch.empty(3, 5) + >>> nn.init.trunc_normal_(w) + """ + return _no_grad_trunc_normal_(tensor, mean, std, a, b) + + +def variance_scaling_(tensor, scale=1.0, mode="fan_in", distribution="normal"): + fan_in, fan_out = _calculate_fan_in_and_fan_out(tensor) + if mode == "fan_in": + denom = fan_in + elif mode == "fan_out": + denom = fan_out + elif mode == "fan_avg": + denom = (fan_in + fan_out) / 2 + + variance = scale / denom + + if distribution == "truncated_normal": + # constant is stddev of standard normal truncated to (-2, 2) + trunc_normal_(tensor, std=math.sqrt(variance) / 0.87962566103423978) + elif distribution == "normal": + tensor.normal_(std=math.sqrt(variance)) + elif distribution == "uniform": + bound = math.sqrt(3 * variance) + tensor.uniform_(-bound, bound) + else: + raise ValueError(f"invalid distribution {distribution}") + + +def lecun_normal_(tensor): + variance_scaling_(tensor, mode="fan_in", distribution="truncated_normal") + + +def window_partition(x, window_size): + """ + Args: + x: (B, H, W, C) + window_size (int): window size + Returns: + windows: (num_windows*B, window_size, window_size, C) + """ + B, H, W, C = x.shape + x = x.view(B, H // window_size, window_size, W // window_size, window_size, C) + windows = ( + x.permute(0, 1, 3, 2, 4, 5).contiguous().view(-1, window_size, window_size, C) + ) + return windows + + +def window_reverse(windows, window_size, H, W): + """ + Args: + windows: (num_windows*B, window_size, window_size, C) + window_size (int): Window size + H (int): Height of image + W (int): Width of image + Returns: + x: (B, H, W, C) + """ + B = int(windows.shape[0] / (H * W / window_size / window_size)) + x = windows.view( + B, H // window_size, W // window_size, window_size, window_size, -1 + ) + x = x.permute(0, 1, 3, 2, 4, 5).contiguous().view(B, H, W, -1) + return x + + +class WindowAttention(nn.Module): + r"""Window based multi-head self attention (W-MSA) module with relative position bias. + It supports both of shifted and non-shifted window. + Args: + dim (int): Number of input channels. + window_size (tuple[int]): The height and width of the window. + num_heads (int): Number of attention heads. + qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True + qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set + attn_drop (float, optional): Dropout ratio of attention weight. Default: 0.0 + proj_drop (float, optional): Dropout ratio of output. Default: 0.0 + """ + + def __init__( + self, + dim, + window_size, + num_heads, + qkv_bias=True, + qk_scale=None, + attn_drop=0.0, + proj_drop=0.0, + ): + + super().__init__() + self.dim = dim + self.window_size = window_size # Wh, Ww + self.num_heads = num_heads + head_dim = dim // num_heads + self.scale = qk_scale or head_dim**-0.5 + + # define a parameter table of relative position bias + self.relative_position_bias_table = nn.Parameter( + torch.zeros((2 * window_size[0] - 1) * (2 * window_size[1] - 1), num_heads) + ) # 2*Wh-1 * 2*Ww-1, nH + + # get pair-wise relative position index for each token inside the window + coords_h = torch.arange(self.window_size[0]) + coords_w = torch.arange(self.window_size[1]) + coords = torch.stack(torch.meshgrid([coords_h, coords_w])) # 2, Wh, Ww + coords_flatten = torch.flatten(coords, 1) # 2, Wh*Ww + relative_coords = ( + coords_flatten[:, :, None] - coords_flatten[:, None, :] + ) # 2, Wh*Ww, Wh*Ww + relative_coords = relative_coords.permute( + 1, 2, 0 + ).contiguous() # Wh*Ww, Wh*Ww, 2 + relative_coords[:, :, 0] += self.window_size[0] - 1 # shift to start from 0 + relative_coords[:, :, 1] += self.window_size[1] - 1 + relative_coords[:, :, 0] *= 2 * self.window_size[1] - 1 + relative_position_index = relative_coords.sum(-1) # Wh*Ww, Wh*Ww + self.register_buffer("relative_position_index", relative_position_index) + + self.qkv = nn.Linear(dim, dim * 3, bias=qkv_bias) + self.attn_drop = nn.Dropout(attn_drop) + self.proj = nn.Linear(dim, dim) + self.proj_drop = nn.Dropout(proj_drop) + + trunc_normal_(self.relative_position_bias_table, std=0.02) + self.softmax = nn.Softmax(dim=-1) + + def forward(self, x, mask=None): + """ + Args: + x: input features with shape of (num_windows*B, N, C) + mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None + """ + B_, N, C = x.shape + qkv = ( + self.qkv(x) + .reshape(B_, N, 3, self.num_heads, C // self.num_heads) + .permute(2, 0, 3, 1, 4) + ) + q, k, v = ( + qkv[0], + qkv[1], + qkv[2], + ) # make torchscript happy (cannot use tensor as tuple) + + q = q * self.scale + attn = q @ k.transpose(-2, -1) + + relative_position_bias = self.relative_position_bias_table[ + self.relative_position_index.view(-1) + ].view( + self.window_size[0] * self.window_size[1], + self.window_size[0] * self.window_size[1], + -1, + ) # Wh*Ww,Wh*Ww,nH + relative_position_bias = relative_position_bias.permute( + 2, 0, 1 + ).contiguous() # nH, Wh*Ww, Wh*Ww + attn = attn + relative_position_bias.unsqueeze(0) + + if mask is not None: + nW = mask.shape[0] + attn = attn.view(B_ // nW, nW, self.num_heads, N, N) + mask.unsqueeze( + 1 + ).unsqueeze(0) + attn = attn.view(-1, self.num_heads, N, N) + attn = self.softmax(attn) + else: + attn = self.softmax(attn) + + attn = self.attn_drop(attn) + + x = (attn @ v).transpose(1, 2).reshape(B_, N, C) + x = self.proj(x) + x = self.proj_drop(x) + return x, attn + + def extra_repr(self): + return f"dim={self.dim}, window_size={self.window_size}, num_heads={self.num_heads}" + + +# We use the model based on Swintransformer Block, therefore we can use the swin-transformer pretrained model +class SwinTransformerBlock(nn.Module): + r"""Swin Transformer Block. + Args: + dim (int): Number of input channels. + input_resolution (tuple[int]): Input resulotion. + num_heads (int): Number of attention heads. + window_size (int): Window size. + shift_size (int): Shift size for SW-MSA. + mlp_ratio (float): Ratio of mlp hidden dim to embedding dim. + qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True + qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set. + drop (float, optional): Dropout rate. Default: 0.0 + attn_drop (float, optional): Attention dropout rate. Default: 0.0 + drop_path (float, optional): Stochastic depth rate. Default: 0.0 + act_layer (nn.Module, optional): Activation layer. Default: nn.GELU + norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm + """ + + def __init__( + self, + dim, + input_resolution, + num_heads, + window_size=7, + shift_size=0, + mlp_ratio=4.0, + qkv_bias=True, + qk_scale=None, + drop=0.0, + attn_drop=0.0, + drop_path=0.0, + act_layer=nn.GELU, + norm_layer=nn.LayerNorm, + norm_before_mlp="ln", + ): + super().__init__() + self.dim = dim + self.input_resolution = input_resolution + self.num_heads = num_heads + self.window_size = window_size + self.shift_size = shift_size + self.mlp_ratio = mlp_ratio + self.norm_before_mlp = norm_before_mlp + if min(self.input_resolution) <= self.window_size: + # if window size is larger than input resolution, we don't partition windows + self.shift_size = 0 + self.window_size = min(self.input_resolution) + assert ( + 0 <= self.shift_size < self.window_size + ), "shift_size must in 0-window_size" + + self.norm1 = norm_layer(dim) + self.attn = WindowAttention( + dim, + window_size=to_2tuple(self.window_size), + num_heads=num_heads, + qkv_bias=qkv_bias, + qk_scale=qk_scale, + attn_drop=attn_drop, + proj_drop=drop, + ) + + self.drop_path = DropPath(drop_path) if drop_path > 0.0 else nn.Identity() + if self.norm_before_mlp == "ln": + self.norm2 = nn.LayerNorm(dim) + elif self.norm_before_mlp == "bn": + self.norm2 = lambda x: nn.BatchNorm1d(dim)(x.transpose(1, 2)).transpose( + 1, 2 + ) + else: + raise NotImplementedError + mlp_hidden_dim = int(dim * mlp_ratio) + self.mlp = Mlp( + in_features=dim, + hidden_features=mlp_hidden_dim, + act_layer=act_layer, + drop=drop, + ) + + if self.shift_size > 0: + # calculate attention mask for SW-MSA + H, W = self.input_resolution + img_mask = torch.zeros((1, H, W, 1)) # 1 H W 1 + h_slices = ( + slice(0, -self.window_size), + slice(-self.window_size, -self.shift_size), + slice(-self.shift_size, None), + ) + w_slices = ( + slice(0, -self.window_size), + slice(-self.window_size, -self.shift_size), + slice(-self.shift_size, None), + ) + cnt = 0 + for h in h_slices: + for w in w_slices: + img_mask[:, h, w, :] = cnt + cnt += 1 + + mask_windows = window_partition( + img_mask, self.window_size + ) # nW, window_size, window_size, 1 + mask_windows = mask_windows.view(-1, self.window_size * self.window_size) + attn_mask = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2) + attn_mask = attn_mask.masked_fill( + attn_mask != 0, float(-100.0) + ).masked_fill(attn_mask == 0, float(0.0)) + else: + attn_mask = None + + self.register_buffer("attn_mask", attn_mask) + + def forward(self, x): + # pdb.set_trace() + H, W = self.input_resolution + # print("H: ", H) + # print("W: ", W) + # pdb.set_trace() + B, L, C = x.shape + # assert L == H * W, "input feature has wrong size" + + shortcut = x + x = self.norm1(x) + x = x.view(B, H, W, C) + + # cyclic shift + if self.shift_size > 0: + shifted_x = torch.roll( + x, shifts=(-self.shift_size, -self.shift_size), dims=(1, 2) + ) + else: + shifted_x = x + + # partition windows + x_windows = window_partition( + shifted_x, self.window_size + ) # nW*B, window_size, window_size, C + x_windows = x_windows.view( + -1, self.window_size * self.window_size, C + ) # nW*B, window_size*window_size, C + + # W-MSA/SW-MSA + attn_windows, attn = self.attn( + x_windows, mask=self.attn_mask + ) # nW*B, window_size*window_size, C + + # merge windows + attn_windows = attn_windows.view(-1, self.window_size, self.window_size, C) + shifted_x = window_reverse(attn_windows, self.window_size, H, W) # B H' W' C + + # reverse cyclic shift + if self.shift_size > 0: + x = torch.roll( + shifted_x, shifts=(self.shift_size, self.shift_size), dims=(1, 2) + ) + else: + x = shifted_x + x = x.view(B, H * W, C) + + # FFN + x = shortcut + self.drop_path(x) + x = x + self.drop_path(self.mlp(self.norm2(x))) + + return x, attn + + def extra_repr(self): + return ( + f"dim={self.dim}, input_resolution={self.input_resolution}, num_heads={self.num_heads}, " + f"window_size={self.window_size}, shift_size={self.shift_size}, mlp_ratio={self.mlp_ratio}" + ) + + +class PatchMerging(nn.Module): + r"""Patch Merging Layer. + Args: + input_resolution (tuple[int]): Resolution of input feature. + dim (int): Number of input channels. + norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm + """ + + def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm): + super().__init__() + self.input_resolution = input_resolution + self.dim = dim + self.reduction = nn.Linear(4 * dim, 2 * dim, bias=False) + self.norm = norm_layer(4 * dim) + + def forward(self, x): + """ + x: B, H*W, C + """ + H, W = self.input_resolution + B, L, C = x.shape + assert L == H * W, "input feature has wrong size" + assert H % 2 == 0 and W % 2 == 0, f"x size ({H}*{W}) are not even." + + x = x.view(B, H, W, C) + + x0 = x[:, 0::2, 0::2, :] # B H/2 W/2 C + x1 = x[:, 1::2, 0::2, :] # B H/2 W/2 C + x2 = x[:, 0::2, 1::2, :] # B H/2 W/2 C + x3 = x[:, 1::2, 1::2, :] # B H/2 W/2 C + x = torch.cat([x0, x1, x2, x3], -1) # B H/2 W/2 4*C + x = x.view(B, -1, 4 * C) # B H/2*W/2 4*C + + x = self.norm(x) + x = self.reduction(x) + + return x + + def extra_repr(self): + return f"input_resolution={self.input_resolution}, dim={self.dim}" + + +class BasicLayer(nn.Module): + """A basic Swin Transformer layer for one stage. + Args: + dim (int): Number of input channels. + input_resolution (tuple[int]): Input resolution. + depth (int): Number of blocks. + num_heads (int): Number of attention heads. + window_size (int): Local window size. + mlp_ratio (float): Ratio of mlp hidden dim to embedding dim. + qkv_bias (bool, optional): If True, add a learnable bias to query, key, value. Default: True + qk_scale (float | None, optional): Override default qk scale of head_dim ** -0.5 if set. + drop (float, optional): Dropout rate. Default: 0.0 + attn_drop (float, optional): Attention dropout rate. Default: 0.0 + drop_path (float | tuple[float], optional): Stochastic depth rate. Default: 0.0 + norm_layer (nn.Module, optional): Normalization layer. Default: nn.LayerNorm + downsample (nn.Module | None, optional): Downsample layer at the end of the layer. Default: None + use_checkpoint (bool): Whether to use checkpointing to save memory. Default: False. + """ + + def __init__( + self, + dim, + input_resolution, + depth, + num_heads, + window_size, + mlp_ratio=4.0, + qkv_bias=True, + qk_scale=None, + drop=0.0, + attn_drop=0.0, + drop_path=0.0, + norm_layer=nn.LayerNorm, + downsample=None, + use_checkpoint=False, + norm_before_mlp="ln", + ): + + super().__init__() + self.dim = dim + self.input_resolution = input_resolution + self.depth = depth + self.use_checkpoint = use_checkpoint + + # build blocks + self.blocks = nn.ModuleList( + [ + SwinTransformerBlock( + dim=dim, + input_resolution=input_resolution, + num_heads=num_heads, + window_size=window_size, + shift_size=0 if (i % 2 == 0) else window_size // 2, + mlp_ratio=mlp_ratio, + qkv_bias=qkv_bias, + qk_scale=qk_scale, + drop=drop, + attn_drop=attn_drop, + drop_path=drop_path[i] + if isinstance(drop_path, list) + else drop_path, + norm_layer=norm_layer, + norm_before_mlp=norm_before_mlp, + ) + for i in range(depth) + ] + ) + + # patch merging layer + if downsample is not None: + self.downsample = downsample( + input_resolution, dim=dim, norm_layer=norm_layer + ) + else: + self.downsample = None + + def forward(self, x): + attns = [] + for blk in self.blocks: + if self.use_checkpoint: + x = checkpoint.checkpoint(blk, x) + else: + x, attn = blk(x) + if not self.training: + attns.append(attn.unsqueeze(0)) + if self.downsample is not None: + x = self.downsample(x) + if not self.training: + attn = torch.cat(attns, dim=0) + attn = torch.mean(attn, dim=0) + return x, attn + + def extra_repr(self): + return f"dim={self.dim}, input_resolution={self.input_resolution}, depth={self.depth}" + + +# The Core of HTSAT +class HTSAT_Swin_Transformer(nn.Module): + r"""HTSAT based on the Swin Transformer + Args: + spec_size (int | tuple(int)): Input Spectrogram size. Default 256 + patch_size (int | tuple(int)): Patch size. Default: 4 + path_stride (iot | tuple(int)): Patch Stride for Frequency and Time Axis. Default: 4 + in_chans (int): Number of input image channels. Default: 1 (mono) + num_classes (int): Number of classes for classification head. Default: 527 + embed_dim (int): Patch embedding dimension. Default: 96 + depths (tuple(int)): Depth of each HTSAT-Swin Transformer layer. + num_heads (tuple(int)): Number of attention heads in different layers. + window_size (int): Window size. Default: 8 + mlp_ratio (float): Ratio of mlp hidden dim to embedding dim. Default: 4 + qkv_bias (bool): If True, add a learnable bias to query, key, value. Default: True + qk_scale (float): Override default qk scale of head_dim ** -0.5 if set. Default: None + drop_rate (float): Dropout rate. Default: 0 + attn_drop_rate (float): Attention dropout rate. Default: 0 + drop_path_rate (float): Stochastic depth rate. Default: 0.1 + norm_layer (nn.Module): Normalization layer. Default: nn.LayerNorm. + ape (bool): If True, add absolute position embedding to the patch embedding. Default: False + patch_norm (bool): If True, add normalization after patch embedding. Default: True + use_checkpoint (bool): Whether to use checkpointing to save memory. Default: False + config (module): The configuration Module from config.py + """ + + def __init__( + self, + spec_size=256, + patch_size=4, + patch_stride=(4, 4), + in_chans=1, + num_classes=527, + embed_dim=96, + depths=[2, 2, 6, 2], + num_heads=[4, 8, 16, 32], + window_size=8, + mlp_ratio=4.0, + qkv_bias=True, + qk_scale=None, + drop_rate=0.0, + attn_drop_rate=0.0, + drop_path_rate=0.1, + norm_layer=nn.LayerNorm, + ape=False, + patch_norm=True, + use_checkpoint=False, + norm_before_mlp="ln", + config=None, + enable_fusion=False, + fusion_type="None", + **kwargs, + ): + super(HTSAT_Swin_Transformer, self).__init__() + + self.config = config + self.spec_size = spec_size + self.patch_stride = patch_stride + self.patch_size = patch_size + self.window_size = window_size + self.embed_dim = embed_dim + self.depths = depths + self.ape = ape + self.in_chans = in_chans + self.num_classes = num_classes + self.num_heads = num_heads + self.num_layers = len(self.depths) + self.num_features = int(self.embed_dim * 2 ** (self.num_layers - 1)) + + self.drop_rate = drop_rate + self.attn_drop_rate = attn_drop_rate + self.drop_path_rate = drop_path_rate + + self.qkv_bias = qkv_bias + self.qk_scale = None + + self.patch_norm = patch_norm + self.norm_layer = norm_layer if self.patch_norm else None + self.norm_before_mlp = norm_before_mlp + self.mlp_ratio = mlp_ratio + + self.use_checkpoint = use_checkpoint + + self.enable_fusion = enable_fusion + self.fusion_type = fusion_type + + # process mel-spec ; used only once + self.freq_ratio = self.spec_size // self.config.mel_bins + window = "hann" + center = True + pad_mode = "reflect" + ref = 1.0 + amin = 1e-10 + top_db = None + self.interpolate_ratio = 32 # Downsampled ratio + # Spectrogram extractor + self.spectrogram_extractor = Spectrogram( + n_fft=config.window_size, + hop_length=config.hop_size, + win_length=config.window_size, + window=window, + center=center, + pad_mode=pad_mode, + freeze_parameters=True, + ) + # Logmel feature extractor + self.logmel_extractor = LogmelFilterBank( + sr=config.sample_rate, + n_fft=config.window_size, + n_mels=config.mel_bins, + fmin=config.fmin, + fmax=config.fmax, + ref=ref, + amin=amin, + top_db=top_db, + freeze_parameters=True, + ) + # Spec augmenter + self.spec_augmenter = SpecAugmentation( + time_drop_width=64, + time_stripes_num=2, + freq_drop_width=8, + freq_stripes_num=2, + ) # 2 2 + self.bn0 = nn.BatchNorm2d(self.config.mel_bins) + + # split spctrogram into non-overlapping patches + self.patch_embed = PatchEmbed( + img_size=self.spec_size, + patch_size=self.patch_size, + in_chans=self.in_chans, + embed_dim=self.embed_dim, + norm_layer=self.norm_layer, + patch_stride=patch_stride, + enable_fusion=self.enable_fusion, + fusion_type=self.fusion_type, + ) + + num_patches = self.patch_embed.num_patches + patches_resolution = self.patch_embed.grid_size + self.patches_resolution = patches_resolution + + # absolute position embedding + if self.ape: + self.absolute_pos_embed = nn.Parameter( + torch.zeros(1, num_patches, self.embed_dim) + ) + trunc_normal_(self.absolute_pos_embed, std=0.02) + + self.pos_drop = nn.Dropout(p=self.drop_rate) + + # stochastic depth + dpr = [ + x.item() for x in torch.linspace(0, self.drop_path_rate, sum(self.depths)) + ] # stochastic depth decay rule + + # build layers + self.layers = nn.ModuleList() + for i_layer in range(self.num_layers): + layer = BasicLayer( + dim=int(self.embed_dim * 2**i_layer), + input_resolution=( + patches_resolution[0] // (2**i_layer), + patches_resolution[1] // (2**i_layer), + ), + depth=self.depths[i_layer], + num_heads=self.num_heads[i_layer], + window_size=self.window_size, + mlp_ratio=self.mlp_ratio, + qkv_bias=self.qkv_bias, + qk_scale=self.qk_scale, + drop=self.drop_rate, + attn_drop=self.attn_drop_rate, + drop_path=dpr[ + sum(self.depths[:i_layer]) : sum(self.depths[: i_layer + 1]) + ], + norm_layer=self.norm_layer, + downsample=PatchMerging if (i_layer < self.num_layers - 1) else None, + use_checkpoint=use_checkpoint, + norm_before_mlp=self.norm_before_mlp, + ) + self.layers.append(layer) + + self.norm = self.norm_layer(self.num_features) + self.avgpool = nn.AdaptiveAvgPool1d(1) + self.maxpool = nn.AdaptiveMaxPool1d(1) + + SF = ( + self.spec_size + // (2 ** (len(self.depths) - 1)) + // self.patch_stride[0] + // self.freq_ratio + ) + self.tscam_conv = nn.Conv2d( + in_channels=self.num_features, + out_channels=self.num_classes, + kernel_size=(SF, 3), + padding=(0, 1), + ) + self.head = nn.Linear(num_classes, num_classes) + + if (self.enable_fusion) and ( + self.fusion_type in ["daf_1d", "aff_1d", "iaff_1d"] + ): + self.mel_conv1d = nn.Sequential( + nn.Conv1d(64, 64, kernel_size=5, stride=3, padding=2), + nn.BatchNorm1d(64), + ) + if self.fusion_type == "daf_1d": + self.fusion_model = DAF() + elif self.fusion_type == "aff_1d": + self.fusion_model = AFF(channels=64, type="1D") + elif self.fusion_type == "iaff_1d": + self.fusion_model = iAFF(channels=64, type="1D") + + self.apply(self._init_weights) + + def _init_weights(self, m): + if isinstance(m, nn.Linear): + trunc_normal_(m.weight, std=0.02) + if isinstance(m, nn.Linear) and m.bias is not None: + nn.init.constant_(m.bias, 0) + elif isinstance(m, nn.LayerNorm): + nn.init.constant_(m.bias, 0) + nn.init.constant_(m.weight, 1.0) + + @torch.jit.ignore + def no_weight_decay(self): + return {"absolute_pos_embed"} + + @torch.jit.ignore + def no_weight_decay_keywords(self): + return {"relative_position_bias_table"} + + def forward_features(self, x, longer_idx=None): + # A deprecated optimization for using a hierarchical output from different blocks + + frames_num = x.shape[2] + x = self.patch_embed(x, longer_idx=longer_idx) + if self.ape: + x = x + self.absolute_pos_embed + x = self.pos_drop(x) + for i, layer in enumerate(self.layers): + x, attn = layer(x) + # for x + x = self.norm(x) + B, N, C = x.shape + SF = frames_num // (2 ** (len(self.depths) - 1)) // self.patch_stride[0] + ST = frames_num // (2 ** (len(self.depths) - 1)) // self.patch_stride[1] + x = x.permute(0, 2, 1).contiguous().reshape(B, C, SF, ST) + B, C, F, T = x.shape + # group 2D CNN + c_freq_bin = F // self.freq_ratio + x = x.reshape(B, C, F // c_freq_bin, c_freq_bin, T) + x = x.permute(0, 1, 3, 2, 4).contiguous().reshape(B, C, c_freq_bin, -1) + # get latent_output + fine_grained_latent_output = torch.mean(x, dim=2) + fine_grained_latent_output = interpolate( + fine_grained_latent_output.permute(0, 2, 1).contiguous(), + 8 * self.patch_stride[1], + ) + + latent_output = self.avgpool(torch.flatten(x, 2)) + latent_output = torch.flatten(latent_output, 1) + + # display the attention map, if needed + + x = self.tscam_conv(x) + x = torch.flatten(x, 2) # B, C, T + + fpx = interpolate( + torch.sigmoid(x).permute(0, 2, 1).contiguous(), 8 * self.patch_stride[1] + ) + + x = self.avgpool(x) + x = torch.flatten(x, 1) + + output_dict = { + "framewise_output": fpx, # already sigmoided + "clipwise_output": torch.sigmoid(x), + "fine_grained_embedding": fine_grained_latent_output, + "embedding": latent_output, + } + + return output_dict + + def crop_wav(self, x, crop_size, spe_pos=None): + time_steps = x.shape[2] + tx = torch.zeros(x.shape[0], x.shape[1], crop_size, x.shape[3]).to(x.device) + for i in range(len(x)): + if spe_pos is None: + crop_pos = random.randint(0, time_steps - crop_size - 1) + else: + crop_pos = spe_pos + tx[i][0] = x[i, 0, crop_pos : crop_pos + crop_size, :] + return tx + + # Reshape the wavform to a img size, if you want to use the pretrained swin transformer model + def reshape_wav2img(self, x): + B, C, T, F = x.shape + target_T = int(self.spec_size * self.freq_ratio) + target_F = self.spec_size // self.freq_ratio + assert ( + T <= target_T and F <= target_F + ), "the wav size should less than or equal to the swin input size" + # to avoid bicubic zero error + if T < target_T: + x = nn.functional.interpolate( + x, (target_T, x.shape[3]), mode="bicubic", align_corners=True + ) + if F < target_F: + x = nn.functional.interpolate( + x, (x.shape[2], target_F), mode="bicubic", align_corners=True + ) + x = x.permute(0, 1, 3, 2).contiguous() + x = x.reshape( + x.shape[0], + x.shape[1], + x.shape[2], + self.freq_ratio, + x.shape[3] // self.freq_ratio, + ) + # print(x.shape) + x = x.permute(0, 1, 3, 2, 4).contiguous() + x = x.reshape(x.shape[0], x.shape[1], x.shape[2] * x.shape[3], x.shape[4]) + return x + + # Repeat the wavform to a img size, if you want to use the pretrained swin transformer model + def repeat_wat2img(self, x, cur_pos): + B, C, T, F = x.shape + target_T = int(self.spec_size * self.freq_ratio) + target_F = self.spec_size // self.freq_ratio + assert ( + T <= target_T and F <= target_F + ), "the wav size should less than or equal to the swin input size" + # to avoid bicubic zero error + if T < target_T: + x = nn.functional.interpolate( + x, (target_T, x.shape[3]), mode="bicubic", align_corners=True + ) + if F < target_F: + x = nn.functional.interpolate( + x, (x.shape[2], target_F), mode="bicubic", align_corners=True + ) + x = x.permute(0, 1, 3, 2).contiguous() # B C F T + x = x[:, :, :, cur_pos : cur_pos + self.spec_size] + x = x.repeat(repeats=(1, 1, 4, 1)) + return x + + def forward( + self, x: torch.Tensor, mixup_lambda=None, infer_mode=False, device=None + ): # out_feat_keys: List[str] = None): + + if self.enable_fusion and x["longer"].sum() == 0: + # if no audio is longer than 10s, then randomly select one audio to be longer + x["longer"][torch.randint(0, x["longer"].shape[0], (1,))] = True + + if not self.enable_fusion: + x = x["waveform"].to(device=device, non_blocking=True) + x = self.spectrogram_extractor(x) # (batch_size, 1, time_steps, freq_bins) + x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins) + x = x.transpose(1, 3) + x = self.bn0(x) + x = x.transpose(1, 3) + if self.training: + x = self.spec_augmenter(x) + + if self.training and mixup_lambda is not None: + x = do_mixup(x, mixup_lambda) + + x = self.reshape_wav2img(x) + output_dict = self.forward_features(x) + else: + longer_list = x["longer"].to(device=device, non_blocking=True) + x = x["mel_fusion"].to(device=device, non_blocking=True) + x = x.transpose(1, 3) + x = self.bn0(x) + x = x.transpose(1, 3) + longer_list_idx = torch.where(longer_list)[0] + if self.fusion_type in ["daf_1d", "aff_1d", "iaff_1d"]: + new_x = x[:, 0:1, :, :].clone().contiguous() + if len(longer_list_idx) > 0: + # local processing + fusion_x_local = x[longer_list_idx, 1:, :, :].clone().contiguous() + FB, FC, FT, FF = fusion_x_local.size() + fusion_x_local = fusion_x_local.view(FB * FC, FT, FF) + fusion_x_local = torch.permute( + fusion_x_local, (0, 2, 1) + ).contiguous() + fusion_x_local = self.mel_conv1d(fusion_x_local) + fusion_x_local = fusion_x_local.view( + FB, FC, FF, fusion_x_local.size(-1) + ) + fusion_x_local = ( + torch.permute(fusion_x_local, (0, 2, 1, 3)) + .contiguous() + .flatten(2) + ) + if fusion_x_local.size(-1) < FT: + fusion_x_local = torch.cat( + [ + fusion_x_local, + torch.zeros( + (FB, FF, FT - fusion_x_local.size(-1)), + device=device, + ), + ], + dim=-1, + ) + else: + fusion_x_local = fusion_x_local[:, :, :FT] + # 1D fusion + new_x = new_x.squeeze(1).permute((0, 2, 1)).contiguous() + new_x[longer_list_idx] = self.fusion_model( + new_x[longer_list_idx], fusion_x_local + ) + x = new_x.permute((0, 2, 1)).contiguous()[:, None, :, :] + else: + x = new_x + + elif self.fusion_type in ["daf_2d", "aff_2d", "iaff_2d", "channel_map"]: + x = x # no change + + if self.training: + x = self.spec_augmenter(x) + if self.training and mixup_lambda is not None: + x = do_mixup(x, mixup_lambda) + + x = self.reshape_wav2img(x) + output_dict = self.forward_features(x, longer_idx=longer_list_idx) + + # if infer_mode: + # # in infer mode. we need to handle different length audio input + # frame_num = x.shape[2] + # target_T = int(self.spec_size * self.freq_ratio) + # repeat_ratio = math.floor(target_T / frame_num) + # x = x.repeat(repeats=(1,1,repeat_ratio,1)) + # x = self.reshape_wav2img(x) + # output_dict = self.forward_features(x) + # else: + # if x.shape[2] > self.freq_ratio * self.spec_size: + # if self.training: + # x = self.crop_wav(x, crop_size=self.freq_ratio * self.spec_size) + # x = self.reshape_wav2img(x) + # output_dict = self.forward_features(x) + # else: + # # Change: Hard code here + # overlap_size = (x.shape[2] - 1) // 4 + # output_dicts = [] + # crop_size = (x.shape[2] - 1) // 2 + # for cur_pos in range(0, x.shape[2] - crop_size - 1, overlap_size): + # tx = self.crop_wav(x, crop_size = crop_size, spe_pos = cur_pos) + # tx = self.reshape_wav2img(tx) + # output_dicts.append(self.forward_features(tx)) + # clipwise_output = torch.zeros_like(output_dicts[0]["clipwise_output"]).float().to(x.device) + # framewise_output = torch.zeros_like(output_dicts[0]["framewise_output"]).float().to(x.device) + # for d in output_dicts: + # clipwise_output += d["clipwise_output"] + # framewise_output += d["framewise_output"] + # clipwise_output = clipwise_output / len(output_dicts) + # framewise_output = framewise_output / len(output_dicts) + # output_dict = { + # 'framewise_output': framewise_output, + # 'clipwise_output': clipwise_output + # } + # else: # this part is typically used, and most easy one + # x = self.reshape_wav2img(x) + # output_dict = self.forward_features(x) + # x = self.head(x) + + # We process the data in the dataloader part, in that here we only consider the input_T < fixed_T + + return output_dict + + +def create_htsat_model(audio_cfg, enable_fusion=False, fusion_type="None"): + try: + + assert audio_cfg.model_name in [ + "tiny", + "base", + "large", + ], "model name for HTS-AT is wrong!" + if audio_cfg.model_name == "tiny": + model = HTSAT_Swin_Transformer( + spec_size=256, + patch_size=4, + patch_stride=(4, 4), + num_classes=audio_cfg.class_num, + embed_dim=96, + depths=[2, 2, 6, 2], + num_heads=[4, 8, 16, 32], + window_size=8, + config=audio_cfg, + enable_fusion=enable_fusion, + fusion_type=fusion_type, + ) + elif audio_cfg.model_name == "base": + model = HTSAT_Swin_Transformer( + spec_size=256, + patch_size=4, + patch_stride=(4, 4), + num_classes=audio_cfg.class_num, + embed_dim=128, + depths=[2, 2, 12, 2], + num_heads=[4, 8, 16, 32], + window_size=8, + config=audio_cfg, + enable_fusion=enable_fusion, + fusion_type=fusion_type, + ) + elif audio_cfg.model_name == "large": + model = HTSAT_Swin_Transformer( + spec_size=256, + patch_size=4, + patch_stride=(4, 4), + num_classes=audio_cfg.class_num, + embed_dim=256, + depths=[2, 2, 12, 2], + num_heads=[4, 8, 16, 32], + window_size=8, + config=audio_cfg, + enable_fusion=enable_fusion, + fusion_type=fusion_type, + ) + + return model + except: + raise RuntimeError( + f"Import Model for {audio_cfg.model_name} not found, or the audio cfg parameters are not enough." + ) diff --git a/src/audioldm/clap/open_clip/linear_probe.py b/src/audioldm/clap/open_clip/linear_probe.py new file mode 100644 index 0000000000000000000000000000000000000000..27b6996af03be287523e19f9a94ebe2df1f89e87 --- /dev/null +++ b/src/audioldm/clap/open_clip/linear_probe.py @@ -0,0 +1,66 @@ +import numpy as np +import torch.nn.functional as F +from torch import nn +from .model import MLPLayers + + +class LinearProbe(nn.Module): + def __init__(self, model, mlp, freeze, in_ch, out_ch, act=None): + """ + Args: + model: nn.Module + mlp: bool, if True, then use the MLP layer as the linear probe module + freeze: bool, if Ture, then freeze all the CLAP model's layers when training the linear probe + in_ch: int, the output channel from CLAP model + out_ch: int, the output channel from linear probe (class_num) + act: torch.nn.functional, the activation function before the loss function + """ + super().__init__() + in_ch = 512 + self.clap_model = model + self.clap_model.text_branch = None # to save memory + self.freeze = freeze + if mlp: + self.lp_layer = MLPLayers(units=[in_ch, in_ch * 2, out_ch]) + else: + self.lp_layer = nn.Linear(in_ch, out_ch) + + if self.freeze: + for param in self.clap_model.parameters(): + param.requires_grad = False + + if act == "None": + self.act = None + elif act == "relu": + self.act = nn.ReLU() + elif act == "elu": + self.act = nn.ELU() + elif act == "prelu": + self.act = nn.PReLU(num_parameters=in_ch) + elif act == "softmax": + self.act = nn.Softmax(dim=-1) + elif act == "sigmoid": + self.act = nn.Sigmoid() + + def forward(self, x, mix_lambda=None, device=None): + """ + Args: + x: waveform, torch.tensor [batch, t_samples] / batch of mel_spec and longer list + mix_lambda: torch.tensor [batch], the mixup lambda + Returns: + class_prob: torch.tensor [batch, class_num] + + """ + # batchnorm cancel grandient + if self.freeze: + self.clap_model.eval() + + x = self.clap_model.audio_projection( + self.clap_model.audio_branch(x, mixup_lambda=mix_lambda, device=device)[ + "embedding" + ] + ) + out = self.lp_layer(x) + if self.act is not None: + out = self.act(out) + return out diff --git a/src/audioldm/clap/open_clip/loss.py b/src/audioldm/clap/open_clip/loss.py new file mode 100644 index 0000000000000000000000000000000000000000..5567119ad4534b10a4b0dfd8fb1becdff2352ed8 --- /dev/null +++ b/src/audioldm/clap/open_clip/loss.py @@ -0,0 +1,398 @@ +from multiprocessing.sharedctypes import Value +import torch +import torch.distributed.nn +from torch import distributed as dist, nn as nn +from torch.nn import functional as F +import numpy as np +from sklearn.metrics import average_precision_score, roc_auc_score, accuracy_score + +try: + import horovod.torch as hvd +except ImportError: + hvd = None + + +def gather_features( + audio_features, + text_features, + audio_features_mlp=None, + text_features_mlp=None, + local_loss=False, + gather_with_grad=False, + rank=0, + world_size=1, + use_horovod=False, + mlp_loss=False, +): + if use_horovod: + assert hvd is not None, "Please install horovod" + if gather_with_grad: + all_audio_features = hvd.allgather(audio_features) + all_text_features = hvd.allgather(text_features) + if mlp_loss: + all_audio_features_mlp = hvd.allgather(audio_features_mlp) + all_text_features_mlp = hvd.allgather(text_features_mlp) + else: + with torch.no_grad(): + all_audio_features = hvd.allgather(audio_features) + all_text_features = hvd.allgather(text_features) + if mlp_loss: + all_audio_features_mlp = hvd.allgather(audio_features_mlp) + all_text_features_mlp = hvd.allgather(text_features_mlp) + if not local_loss: + # ensure grads for local rank when all_* features don't have a gradient + gathered_audio_features = list( + all_audio_features.chunk(world_size, dim=0) + ) + gathered_text_features = list( + all_text_features.chunk(world_size, dim=0) + ) + gathered_audio_features[rank] = audio_features + gathered_text_features[rank] = text_features + all_audio_features = torch.cat(gathered_audio_features, dim=0) + all_text_features = torch.cat(gathered_text_features, dim=0) + if mlp_loss: + gathered_audio_features_mlp = list( + all_audio_features_mlp.chunk(world_size, dim=0) + ) + gathered_text_features_mlp = list( + all_text_features_mlp.chunk(world_size, dim=0) + ) + gathered_audio_features_mlp[rank] = audio_features_mlp + gathered_text_features_mlp[rank] = text_features_mlp + all_audio_features_mlp = torch.cat( + gathered_audio_features_mlp, dim=0 + ) + all_text_features_mlp = torch.cat(gathered_text_features_mlp, dim=0) + else: + # We gather tensors from all gpus + if gather_with_grad: + all_audio_features = torch.cat( + torch.distributed.nn.all_gather(audio_features), dim=0 + ) + all_text_features = torch.cat( + torch.distributed.nn.all_gather(text_features), dim=0 + ) + if mlp_loss: + all_audio_features_mlp = torch.cat( + torch.distributed.nn.all_gather(audio_features_mlp), dim=0 + ) + all_text_features_mlp = torch.cat( + torch.distributed.nn.all_gather(text_features_mlp), dim=0 + ) + else: + gathered_audio_features = [ + torch.zeros_like(audio_features) for _ in range(world_size) + ] + gathered_text_features = [ + torch.zeros_like(text_features) for _ in range(world_size) + ] + dist.all_gather(gathered_audio_features, audio_features) + dist.all_gather(gathered_text_features, text_features) + if mlp_loss: + gathered_audio_features_mlp = [ + torch.zeros_like(audio_features_mlp) for _ in range(world_size) + ] + gathered_text_features_mlp = [ + torch.zeros_like(text_features_mlp) for _ in range(world_size) + ] + dist.all_gather(gathered_audio_features_mlp, audio_features_mlp) + dist.all_gather(gathered_text_features_mlp, text_features_mlp) + if not local_loss: + # ensure grads for local rank when all_* features don't have a gradient + gathered_audio_features[rank] = audio_features + gathered_text_features[rank] = text_features + if mlp_loss: + gathered_audio_features_mlp[rank] = audio_features_mlp + gathered_text_features_mlp[rank] = text_features_mlp + + all_audio_features = torch.cat(gathered_audio_features, dim=0) + all_text_features = torch.cat(gathered_text_features, dim=0) + if mlp_loss: + all_audio_features_mlp = torch.cat(gathered_audio_features_mlp, dim=0) + all_text_features_mlp = torch.cat(gathered_text_features_mlp, dim=0) + if mlp_loss: + return ( + all_audio_features, + all_text_features, + all_audio_features_mlp, + all_text_features_mlp, + ) + else: + return all_audio_features, all_text_features + + +class ClipLoss(nn.Module): + def __init__( + self, + local_loss=False, + gather_with_grad=False, + cache_labels=False, + rank=0, + world_size=1, + use_horovod=False, + mlp_loss=False, + weight_loss_kappa=0, + ): + super().__init__() + self.local_loss = local_loss + self.gather_with_grad = gather_with_grad + self.cache_labels = cache_labels + self.rank = rank + self.world_size = world_size + self.use_horovod = use_horovod + self.mlp_loss = mlp_loss + self.weighted_loss = bool(weight_loss_kappa != 0) + self.weight_loss_kappa = weight_loss_kappa + # cache state + self.prev_num_logits = 0 + self.labels = {} + + def forward( + self, + audio_features, + text_features, + logit_scale_a, + logit_scale_t=None, + audio_features_mlp=None, + text_features_mlp=None, + ): + device = audio_features.device + if self.mlp_loss: + if self.world_size > 1: + ( + all_audio_features, + all_text_features, + all_audio_features_mlp, + all_text_features_mlp, + ) = gather_features( + audio_features=audio_features, + text_features=text_features, + audio_features_mlp=audio_features_mlp, + text_features_mlp=text_features_mlp, + local_loss=self.local_loss, + gather_with_grad=self.gather_with_grad, + rank=self.rank, + world_size=self.world_size, + use_horovod=self.use_horovod, + mlp_loss=self.mlp_loss, + ) + if self.local_loss: + a_logits_per_audio = ( + logit_scale_a * audio_features @ all_text_features_mlp.T + ) + a_logits_per_text = ( + logit_scale_a * text_features_mlp @ all_audio_features.T + ) + t_logits_per_audio = ( + logit_scale_t * audio_features_mlp @ all_text_features.T + ) + t_logits_per_text = ( + logit_scale_t * text_features @ all_audio_features_mlp.T + ) + else: + a_logits_per_audio = ( + logit_scale_a * all_audio_features @ all_text_features_mlp.T + ) + a_logits_per_text = a_logits_per_audio.T + t_logits_per_audio = ( + logit_scale_t * all_audio_features_mlp @ all_text_features.T + ) + t_logits_per_text = t_logits_per_audio.T + else: + a_logits_per_audio = ( + logit_scale_a * audio_features @ text_features_mlp.T + ) + a_logits_per_text = logit_scale_a * text_features_mlp @ audio_features.T + t_logits_per_audio = ( + logit_scale_t * audio_features_mlp @ text_features.T + ) + t_logits_per_text = logit_scale_t * text_features @ audio_features_mlp.T + + # calculated ground-truth and cache if enabled + num_logits = a_logits_per_audio.shape[0] + if self.prev_num_logits != num_logits or device not in self.labels: + labels = torch.arange(num_logits, device=device, dtype=torch.long) + if self.world_size > 1 and self.local_loss: + labels = labels + num_logits * self.rank + if self.cache_labels: + self.labels[device] = labels + self.prev_num_logits = num_logits + else: + labels = self.labels[device] + + if not self.weighted_loss: + total_loss = ( + F.cross_entropy(a_logits_per_audio, labels) + + F.cross_entropy(a_logits_per_text, labels) + + F.cross_entropy(t_logits_per_audio, labels) + + F.cross_entropy(t_logits_per_text, labels) + ) / 4 + else: + audio_weight = (audio_features @ audio_features.T).detach() + audio_weight = ( + torch.exp( + torch.sum(audio_weight, axis=1) + / (self.weight_loss_kappa * len(audio_weight)) + ) + ).detach() + text_weight = (text_features @ text_features.T).detach() + text_weight = ( + torch.exp( + torch.sum(text_weight, axis=1) + / (self.weight_loss_kappa * len(text_features)) + ) + ).detach() + total_loss = ( + F.cross_entropy(a_logits_per_audio, labels, weight=audio_weight) + + F.cross_entropy(a_logits_per_text, labels, weight=audio_weight) + + F.cross_entropy(t_logits_per_audio, labels, weight=text_weight) + + F.cross_entropy(t_logits_per_text, labels, weight=text_weight) + ) / 4 + else: + if self.world_size > 1: + all_audio_features, all_text_features = gather_features( + audio_features=audio_features, + text_features=text_features, + local_loss=self.local_loss, + gather_with_grad=self.gather_with_grad, + rank=self.rank, + world_size=self.world_size, + use_horovod=self.use_horovod, + mlp_loss=self.mlp_loss, + ) + + if self.local_loss: + logits_per_audio = ( + logit_scale_a * audio_features @ all_text_features.T + ) + logits_per_text = ( + logit_scale_a * text_features @ all_audio_features.T + ) + else: + logits_per_audio = ( + logit_scale_a * all_audio_features @ all_text_features.T + ) + logits_per_text = logits_per_audio.T + else: + logits_per_audio = logit_scale_a * audio_features @ text_features.T + logits_per_text = logit_scale_a * text_features @ audio_features.T + + # calculated ground-truth and cache if enabled + num_logits = logits_per_audio.shape[0] + if self.prev_num_logits != num_logits or device not in self.labels: + labels = torch.arange(num_logits, device=device, dtype=torch.long) + if self.world_size > 1 and self.local_loss: + labels = labels + num_logits * self.rank + if self.cache_labels: + self.labels[device] = labels + self.prev_num_logits = num_logits + else: + labels = self.labels[device] + if not self.weighted_loss: + total_loss = ( + F.cross_entropy(logits_per_audio, labels) + + F.cross_entropy(logits_per_text, labels) + ) / 2 + else: + audio_weight = (all_audio_features @ all_audio_features.T).detach() + audio_weight = ( + torch.exp( + torch.sum(audio_weight, axis=1) + / (self.weight_loss_kappa * len(all_audio_features)) + ) + ).detach() + text_weight = (all_text_features @ all_text_features.T).detach() + text_weight = ( + torch.exp( + torch.sum(text_weight, axis=1) + / (self.weight_loss_kappa * len(all_text_features)) + ) + ).detach() + total_loss = ( + F.cross_entropy(logits_per_audio, labels, weight=text_weight) + + F.cross_entropy(logits_per_text, labels, weight=audio_weight) + ) / 2 + return total_loss + + +def lp_gather_features(pred, target, world_size=1, use_horovod=False): + if use_horovod: + assert hvd is not None, "Please install horovod" + with torch.no_grad(): + all_preds = hvd.allgather(pred) + all_targets = hvd.allgath(target) + else: + gathered_preds = [torch.zeros_like(pred) for _ in range(world_size)] + gathered_targets = [torch.zeros_like(target) for _ in range(world_size)] + + dist.all_gather(gathered_preds, pred) + dist.all_gather(gathered_targets, target) + all_preds = torch.cat(gathered_preds, dim=0) + all_targets = torch.cat(gathered_targets, dim=0) + + return all_preds, all_targets + + +def get_map(pred, target): + pred = torch.sigmoid(pred).numpy() + target = target.numpy() + return np.mean(average_precision_score(target, pred, average=None)) + + +def get_acc(pred, target): + pred = torch.argmax(pred, 1).numpy() + target = torch.argmax(target, 1).numpy() + return accuracy_score(target, pred) + + +def get_mauc(pred, target): + pred = torch.sigmoid(pred).numpy() + target = target.numpy() + return np.mean(roc_auc_score(target, pred, average=None)) + + +class LPMetrics(object): + def __init__(self, metric_names=["map", "acc", "mauc"]): + self.metrics = [] + for name in metric_names: + self.metrics.append(self.get_metric(name)) + self.metric_names = metric_names + + def get_metric(self, name): + if name == "map": + return get_map + elif name == "acc": + return get_acc + elif name == "mauc": + return get_mauc + else: + raise ValueError(f"the metric should be at least one of [map, acc, mauc]") + + def evaluate_mertics(self, pred, target): + metric_dict = {} + for i in range(len(self.metric_names)): + metric_dict[self.metric_names[i]] = self.metrics[i](pred, target) + return metric_dict + + +def calc_celoss(pred, target): + target = torch.argmax(target, 1).long() + return nn.CrossEntropyLoss()(pred, target) + + +class LPLoss(nn.Module): + def __init__(self, loss_name): + super().__init__() + if loss_name == "bce": + self.loss_func = nn.BCEWithLogitsLoss() + elif loss_name == "ce": + self.loss_func = calc_celoss + elif loss_name == "mse": + self.loss_func = nn.MSELoss() + else: + raise ValueError(f"the loss func should be at least one of [bce, ce, mse]") + + def forward(self, pred, target): + loss = self.loss_func(pred, target) + return loss diff --git a/src/audioldm/clap/open_clip/model.py b/src/audioldm/clap/open_clip/model.py new file mode 100644 index 0000000000000000000000000000000000000000..33185e93bcc99351a1fbbe9782a9367956f65a53 --- /dev/null +++ b/src/audioldm/clap/open_clip/model.py @@ -0,0 +1,936 @@ +""" CLAP Model + +Adapted from CLIP: https://github.com/openai/CLIP. Originally MIT License, Copyright (c) 2021 OpenAI. +Adapted to the Audio Task. +""" + +from collections import OrderedDict +from dataclasses import dataclass +from email.mime import audio +from typing import Tuple, Union, Callable, Optional + +import numpy as np +import torch +import torch.nn.functional as F +from torch import nn + +from .timm_model import TimmModel +import logging +from .utils import freeze_batch_norm_2d + +from .pann_model import create_pann_model +from .htsat import create_htsat_model +from transformers import BertModel, RobertaModel, BartModel +from transformers.tokenization_utils_base import BatchEncoding + + +class MLPLayers(nn.Module): + def __init__(self, units=[512, 512, 512], nonlin=nn.ReLU(), dropout=0.1): + super(MLPLayers, self).__init__() + self.nonlin = nonlin + self.dropout = dropout + + sequence = [] + for u0, u1 in zip(units[:-1], units[1:]): + sequence.append(nn.Linear(u0, u1)) + sequence.append(self.nonlin) + sequence.append(nn.Dropout(self.dropout)) + sequence = sequence[:-2] + + self.sequential = nn.Sequential(*sequence) + + def forward(self, X): + X = self.sequential(X) + return X + + +class Bottleneck(nn.Module): + expansion = 4 + + def __init__(self, inplanes, planes, stride=1): + super().__init__() + + # all conv layers have stride 1. an avgpool is performed after the second convolution when stride > 1 + self.conv1 = nn.Conv2d(inplanes, planes, 1, bias=False) + self.bn1 = nn.BatchNorm2d(planes) + + self.conv2 = nn.Conv2d(planes, planes, 3, padding=1, bias=False) + self.bn2 = nn.BatchNorm2d(planes) + + self.avgpool = nn.AvgPool2d(stride) if stride > 1 else nn.Identity() + + self.conv3 = nn.Conv2d(planes, planes * self.expansion, 1, bias=False) + self.bn3 = nn.BatchNorm2d(planes * self.expansion) + + self.relu = nn.ReLU(inplace=True) + self.downsample = None + self.stride = stride + + if stride > 1 or inplanes != planes * Bottleneck.expansion: + # downsampling layer is prepended with an avgpool, and the subsequent convolution has stride 1 + self.downsample = nn.Sequential( + OrderedDict( + [ + ("-1", nn.AvgPool2d(stride)), + ( + "0", + nn.Conv2d( + inplanes, + planes * self.expansion, + 1, + stride=1, + bias=False, + ), + ), + ("1", nn.BatchNorm2d(planes * self.expansion)), + ] + ) + ) + + def forward(self, x: torch.Tensor): + identity = x + + out = self.relu(self.bn1(self.conv1(x))) + out = self.relu(self.bn2(self.conv2(out))) + out = self.avgpool(out) + out = self.bn3(self.conv3(out)) + + if self.downsample is not None: + identity = self.downsample(x) + + out += identity + out = self.relu(out) + return out + + +class AttentionPool2d(nn.Module): + def __init__( + self, spacial_dim: int, embed_dim: int, num_heads: int, output_dim: int = None + ): + super().__init__() + self.positional_embedding = nn.Parameter( + torch.randn(spacial_dim**2 + 1, embed_dim) / embed_dim**0.5 + ) + self.k_proj = nn.Linear(embed_dim, embed_dim) + self.q_proj = nn.Linear(embed_dim, embed_dim) + self.v_proj = nn.Linear(embed_dim, embed_dim) + self.c_proj = nn.Linear(embed_dim, output_dim or embed_dim) + self.num_heads = num_heads + + def forward(self, x): + x = x.reshape(x.shape[0], x.shape[1], x.shape[2] * x.shape[3]).permute( + 2, 0, 1 + ) # NCHW -> (HW)NC + x = torch.cat([x.mean(dim=0, keepdim=True), x], dim=0) # (HW+1)NC + x = x + self.positional_embedding[:, None, :].to(x.dtype) # (HW+1)NC + x, _ = F.multi_head_attention_forward( + query=x, + key=x, + value=x, + embed_dim_to_check=x.shape[-1], + num_heads=self.num_heads, + q_proj_weight=self.q_proj.weight, + k_proj_weight=self.k_proj.weight, + v_proj_weight=self.v_proj.weight, + in_proj_weight=None, + in_proj_bias=torch.cat( + [self.q_proj.bias, self.k_proj.bias, self.v_proj.bias] + ), + bias_k=None, + bias_v=None, + add_zero_attn=False, + dropout_p=0, + out_proj_weight=self.c_proj.weight, + out_proj_bias=self.c_proj.bias, + use_separate_proj_weight=True, + training=self.training, + need_weights=False, + ) + + return x[0] + + +class ModifiedResNet(nn.Module): + """ + A ResNet class that is similar to torchvision's but contains the following changes: + - There are now 3 "stem" convolutions as opposed to 1, with an average pool instead of a max pool. + - Performs anti-aliasing strided convolutions, where an avgpool is prepended to convolutions with stride > 1 + - The final pooling layer is a QKV attention instead of an average pool + """ + + def __init__(self, layers, output_dim, heads, image_size=224, width=64): + super().__init__() + self.output_dim = output_dim + self.image_size = image_size + + # the 3-layer stem + self.conv1 = nn.Conv2d( + 3, width // 2, kernel_size=3, stride=2, padding=1, bias=False + ) + self.bn1 = nn.BatchNorm2d(width // 2) + self.conv2 = nn.Conv2d( + width // 2, width // 2, kernel_size=3, padding=1, bias=False + ) + self.bn2 = nn.BatchNorm2d(width // 2) + self.conv3 = nn.Conv2d(width // 2, width, kernel_size=3, padding=1, bias=False) + self.bn3 = nn.BatchNorm2d(width) + self.avgpool = nn.AvgPool2d(2) + self.relu = nn.ReLU(inplace=True) + + # residual layers + self._inplanes = width # this is a *mutable* variable used during construction + self.layer1 = self._make_layer(width, layers[0]) + self.layer2 = self._make_layer(width * 2, layers[1], stride=2) + self.layer3 = self._make_layer(width * 4, layers[2], stride=2) + self.layer4 = self._make_layer(width * 8, layers[3], stride=2) + + embed_dim = width * 32 # the ResNet feature dimension + self.attnpool = AttentionPool2d(image_size // 32, embed_dim, heads, output_dim) + + self.init_parameters() + + def _make_layer(self, planes, blocks, stride=1): + layers = [Bottleneck(self._inplanes, planes, stride)] + + self._inplanes = planes * Bottleneck.expansion + for _ in range(1, blocks): + layers.append(Bottleneck(self._inplanes, planes)) + + return nn.Sequential(*layers) + + def init_parameters(self): + if self.attnpool is not None: + std = self.attnpool.c_proj.in_features**-0.5 + nn.init.normal_(self.attnpool.q_proj.weight, std=std) + nn.init.normal_(self.attnpool.k_proj.weight, std=std) + nn.init.normal_(self.attnpool.v_proj.weight, std=std) + nn.init.normal_(self.attnpool.c_proj.weight, std=std) + + for resnet_block in [self.layer1, self.layer2, self.layer3, self.layer4]: + for name, param in resnet_block.named_parameters(): + if name.endswith("bn3.weight"): + nn.init.zeros_(param) + + def lock(self, unlocked_groups=0, freeze_bn_stats=False): + assert ( + unlocked_groups == 0 + ), "partial locking not currently supported for this model" + for param in self.parameters(): + param.requires_grad = False + if freeze_bn_stats: + freeze_batch_norm_2d(self) + + def stem(self, x): + for conv, bn in [ + (self.conv1, self.bn1), + (self.conv2, self.bn2), + (self.conv3, self.bn3), + ]: + x = self.relu(bn(conv(x))) + x = self.avgpool(x) + return x + + def forward(self, x): + x = self.stem(x) + x = self.layer1(x) + x = self.layer2(x) + x = self.layer3(x) + x = self.layer4(x) + x = self.attnpool(x) + + return x + + +class LayerNorm(nn.LayerNorm): + """Subclass torch's LayerNorm to handle fp16.""" + + def forward(self, x: torch.Tensor): + orig_type = x.dtype + x = F.layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps) + return x.to(orig_type) + + +class QuickGELU(nn.Module): + # NOTE This is slower than nn.GELU or nn.SiLU and uses more GPU memory + def forward(self, x: torch.Tensor): + return x * torch.sigmoid(1.702 * x) + + +class ResidualAttentionBlock(nn.Module): + def __init__(self, d_model: int, n_head: int, act_layer: Callable = nn.GELU): + super().__init__() + + self.attn = nn.MultiheadAttention(d_model, n_head) + self.ln_1 = LayerNorm(d_model) + self.mlp = nn.Sequential( + OrderedDict( + [ + ("c_fc", nn.Linear(d_model, d_model * 4)), + ("gelu", act_layer()), + ("c_proj", nn.Linear(d_model * 4, d_model)), + ] + ) + ) + self.ln_2 = LayerNorm(d_model) + + def attention(self, x: torch.Tensor, attn_mask: Optional[torch.Tensor] = None): + return self.attn(x, x, x, need_weights=False, attn_mask=attn_mask)[0] + + def forward(self, x: torch.Tensor, attn_mask: Optional[torch.Tensor] = None): + x = x + self.attention(self.ln_1(x), attn_mask=attn_mask) + x = x + self.mlp(self.ln_2(x)) + return x + + +class Transformer(nn.Module): + def __init__( + self, width: int, layers: int, heads: int, act_layer: Callable = nn.GELU + ): + super().__init__() + self.width = width + self.layers = layers + self.resblocks = nn.ModuleList( + [ + ResidualAttentionBlock(width, heads, act_layer=act_layer) + for _ in range(layers) + ] + ) + + def forward(self, x: torch.Tensor, attn_mask: Optional[torch.Tensor] = None): + for r in self.resblocks: + x = r(x, attn_mask=attn_mask) + return x + + +class VisualTransformer(nn.Module): + def __init__( + self, + image_size: int, + patch_size: int, + width: int, + layers: int, + heads: int, + output_dim: int, + act_layer: Callable = nn.GELU, + ): + super().__init__() + self.image_size = image_size + self.output_dim = output_dim + self.conv1 = nn.Conv2d( + in_channels=3, + out_channels=width, + kernel_size=patch_size, + stride=patch_size, + bias=False, + ) + + scale = width**-0.5 + self.class_embedding = nn.Parameter(scale * torch.randn(width)) + self.positional_embedding = nn.Parameter( + scale * torch.randn((image_size // patch_size) ** 2 + 1, width) + ) + self.ln_pre = LayerNorm(width) + + self.text_branch = Transformer(width, layers, heads, act_layer=act_layer) + + self.ln_post = LayerNorm(width) + self.proj = nn.Parameter(scale * torch.randn(width, output_dim)) + + def lock(self, unlocked_groups=0, freeze_bn_stats=False): + assert ( + unlocked_groups == 0 + ), "partial locking not currently supported for this model" + for param in self.parameters(): + param.requires_grad = False + + def forward(self, x: torch.Tensor): + x = self.conv1(x) # shape = [*, width, grid, grid] + x = x.reshape(x.shape[0], x.shape[1], -1) # shape = [*, width, grid ** 2] + x = x.permute(0, 2, 1) # shape = [*, grid ** 2, width] + x = torch.cat( + [ + self.class_embedding.to(x.dtype) + + torch.zeros( + x.shape[0], 1, x.shape[-1], dtype=x.dtype, device=x.device + ), + x, + ], + dim=1, + ) # shape = [*, grid ** 2 + 1, width] + x = x + self.positional_embedding.to(x.dtype) + x = self.ln_pre(x) + + x = x.permute(1, 0, 2) # NLD -> LND + x = self.text_branch(x) + x = x.permute(1, 0, 2) # LND -> NLD + + x = self.ln_post(x[:, 0, :]) + + if self.proj is not None: + x = x @ self.proj + + return x + + +@dataclass +class CLAPVisionCfg: + layers: Union[Tuple[int, int, int, int], int] = 12 + width: int = 768 + patch_size: int = 16 + image_size: Union[Tuple[int, int], int] = 224 + timm_model_name: str = ( + None # a valid model name overrides layers, width, patch_size + ) + timm_model_pretrained: bool = ( + False # use (imagenet) pretrained weights for named model + ) + timm_pool: str = ( + "avg" # feature pooling for timm model ('abs_attn', 'rot_attn', 'avg', '') + ) + timm_proj: str = ( + "linear" # linear projection for timm model output ('linear', 'mlp', '') + ) + + +# Audio Config Class +@dataclass +class CLAPAudioCfp: + model_type: str = "PANN" + model_name: str = "Cnn14" + sample_rate: int = 48000 + # Param + audio_length: int = 1024 + window_size: int = 1024 + hop_size: int = 1024 + fmin: int = 50 + fmax: int = 14000 + class_num: int = 527 + mel_bins: int = 64 + clip_samples: int = 480000 + + +@dataclass +class CLAPTextCfg: + context_length: int + vocab_size: int + width: int + heads: int + layers: int + model_type: str + + +class CLAP(nn.Module): + def __init__( + self, + embed_dim: int, + audio_cfg: CLAPAudioCfp, + text_cfg: CLAPTextCfg, + quick_gelu: bool = False, + enable_fusion: bool = False, + fusion_type: str = "None", + joint_embed_shape: int = 512, + mlp_act: str = "relu", + ): + super().__init__() + if isinstance(audio_cfg, dict): + audio_cfg = CLAPAudioCfp(**audio_cfg) + if isinstance(text_cfg, dict): + text_cfg = CLAPTextCfg(**text_cfg) + + self.audio_cfg = audio_cfg + self.text_cfg = text_cfg + self.enable_fusion = enable_fusion + self.fusion_type = fusion_type + self.joint_embed_shape = joint_embed_shape + self.mlp_act = mlp_act + + self.context_length = text_cfg.context_length + + # OpenAI models are pretrained w/ QuickGELU but native nn.GELU is both faster and more + # memory efficient in recent PyTorch releases (>= 1.10). + # NOTE: timm models always use native GELU regardless of quick_gelu flag. + act_layer = QuickGELU if quick_gelu else nn.GELU + + if mlp_act == "relu": + mlp_act_layer = nn.ReLU() + elif mlp_act == "gelu": + mlp_act_layer = nn.GELU() + else: + raise NotImplementedError + + # audio branch + # audio branch parameters + if audio_cfg.model_type == "PANN": + self.audio_branch = create_pann_model(audio_cfg, enable_fusion, fusion_type) + elif audio_cfg.model_type == "HTSAT": + self.audio_branch = create_htsat_model( + audio_cfg, enable_fusion, fusion_type + ) + else: + logging.error(f"Model config for {audio_cfg.model_type} not found") + raise RuntimeError(f"Model config for {audio_cfg.model_type} not found.") + + # text branch + # text branch parameters + if text_cfg.model_type == "transformer": + self.text_branch = Transformer( + width=text_cfg.width, + layers=text_cfg.layers, + heads=text_cfg.heads, + act_layer=act_layer, + ) + self.vocab_size = text_cfg.vocab_size + self.token_embedding = nn.Embedding(text_cfg.vocab_size, text_cfg.width) + self.positional_embedding = nn.Parameter( + torch.empty(self.context_length, text_cfg.width) + ) + self.ln_final = LayerNorm(text_cfg.width) + self.text_transform = MLPLayers( + units=[ + self.joint_embed_shape, + self.joint_embed_shape, + self.joint_embed_shape, + ], + dropout=0.1, + ) + self.text_projection = nn.Sequential( + nn.Linear(text_cfg.width, self.joint_embed_shape), + mlp_act_layer, + nn.Linear(self.joint_embed_shape, self.joint_embed_shape), + ) + elif text_cfg.model_type == "bert": + self.text_branch = BertModel.from_pretrained("bert-base-uncased") + self.text_transform = MLPLayers( + units=[ + self.joint_embed_shape, + self.joint_embed_shape, + self.joint_embed_shape, + ], + dropout=0.1, + ) + self.text_projection = nn.Sequential( + nn.Linear(768, self.joint_embed_shape), + mlp_act_layer, + nn.Linear(self.joint_embed_shape, self.joint_embed_shape), + ) + elif text_cfg.model_type == "roberta": + self.text_branch = RobertaModel.from_pretrained("roberta-base") + self.text_transform = MLPLayers( + units=[ + self.joint_embed_shape, + self.joint_embed_shape, + self.joint_embed_shape, + ], + dropout=0.1, + ) + self.text_projection = nn.Sequential( + nn.Linear(768, self.joint_embed_shape), + mlp_act_layer, + nn.Linear(self.joint_embed_shape, self.joint_embed_shape), + ) + elif text_cfg.model_type == "bart": + self.text_branch = BartModel.from_pretrained("facebook/bart-base") + self.text_transform = MLPLayers( + units=[ + self.joint_embed_shape, + self.joint_embed_shape, + self.joint_embed_shape, + ], + dropout=0.1, + ) + self.text_projection = nn.Sequential( + nn.Linear(768, self.joint_embed_shape), + mlp_act_layer, + nn.Linear(self.joint_embed_shape, self.joint_embed_shape), + ) + else: + logging.error(f"Model config for {text_cfg.model_type} not found") + raise RuntimeError(f"Model config for {text_cfg.model_type} not found.") + self.text_branch_type = text_cfg.model_type + # text branch parameters + + # audio branch parameters + self.audio_transform = MLPLayers( + units=[ + self.joint_embed_shape, + self.joint_embed_shape, + self.joint_embed_shape, + ], + dropout=0.1, + ) + + # below here is text branch parameters + + # ============================================================================================================ + self.audio_projection = nn.Sequential( + nn.Linear(embed_dim, self.joint_embed_shape), + mlp_act_layer, + nn.Linear(self.joint_embed_shape, self.joint_embed_shape), + ) + + self.logit_scale_a = nn.Parameter(torch.ones([]) * np.log(1 / 0.07)) + self.logit_scale_t = nn.Parameter(torch.ones([]) * np.log(1 / 0.07)) + self.register_buffer("attn_mask", self.build_attention_mask(), persistent=False) + + self.init_text_branch_parameters() + + def init_text_branch_parameters(self): + if self.text_branch_type == "transformer": + nn.init.normal_(self.token_embedding.weight, std=0.02) + nn.init.normal_(self.positional_embedding, std=0.01) + proj_std = (self.text_branch.width**-0.5) * ( + (2 * self.text_branch.layers) ** -0.5 + ) + attn_std = self.text_branch.width**-0.5 + fc_std = (2 * self.text_branch.width) ** -0.5 + for block in self.text_branch.resblocks: + nn.init.normal_(block.attn.in_proj_weight, std=attn_std) + nn.init.normal_(block.attn.out_proj.weight, std=proj_std) + nn.init.normal_(block.mlp.c_fc.weight, std=fc_std) + nn.init.normal_(block.mlp.c_proj.weight, std=proj_std) + if self.text_branch_type == "bert" or self.text_branch_type == "roberta": + width = self.text_branch.embeddings.word_embeddings.weight.shape[-1] + elif self.text_branch_type == "bart": + width = self.text_branch.shared.weight.shape[-1] + else: + width = self.text_branch.width + nn.init.constant_(self.logit_scale_a, np.log(1 / 0.07)) + nn.init.constant_(self.logit_scale_t, np.log(1 / 0.07)) + + # deprecated + # if hasattr(self.visual, 'init_parameters'): + # self.visual.init_parameters() + + # if self.text_projection is not None: + # nn.init.normal_(self.text_projection, std=width**-0.5) + + def build_attention_mask(self): + # lazily create causal attention mask, with full attention between the vision tokens + # pytorch uses additive attention mask; fill with -inf + mask = torch.empty(self.context_length, self.context_length) + mask.fill_(float("-inf")) + mask.triu_(1) # zero out the lower diagonal + return mask + + def encode_audio(self, audio, device): + return self.audio_branch( + audio, mixup_lambda=None, device=device + ) # mix lambda needs to add + + # def list_of_dict_of_tensor2dict_of_tensor(self, x, device): + # tmp = {} + # for k in x[0].keys(): + # tmp[k] = [] + # for i in range(len(x)): + # tmp[k].append(x[i][k][:77]) + # for k in x[0].keys(): + # tmp[k] = torch.tensor(tmp[k]).to(device=device, non_blocking=True) + # return tmp + + def encode_text(self, text, device): + if self.text_branch_type == "transformer": + text = text.to(device=device, non_blocking=True) + x = self.token_embedding(text) # [batch_size, n_ctx, d_model] + + x = x + self.positional_embedding + x = x.permute(1, 0, 2) # NLD -> LND + x = self.text_branch(x, attn_mask=self.attn_mask) + x = x.permute(1, 0, 2) # LND -> NLD + x = self.ln_final(x) + + # x.shape = [batch_size, n_ctx, transformer.width] + # take features from the eot embedding (eot_token is the highest number in each sequence) + x = self.text_projection(x[torch.arange(x.shape[0]), text.argmax(dim=-1)]) + elif self.text_branch_type == "bert": + # text = self.list_of_dict_of_tensor2dict_of_tensor(text, device) + # text = BatchEncoding(text) + x = self.text_branch( + input_ids=text["input_ids"].to(device=device, non_blocking=True), + attention_mask=text["attention_mask"].to( + device=device, non_blocking=True + ), + token_type_ids=text["token_type_ids"].to( + device=device, non_blocking=True + ), + )["pooler_output"] + x = self.text_projection(x) + elif self.text_branch_type == "roberta": + x = self.text_branch( + input_ids=text["input_ids"].to(device=device, non_blocking=True), + attention_mask=text["attention_mask"].to( + device=device, non_blocking=True + ), + )["pooler_output"] + x = self.text_projection(x) + elif self.text_branch_type == "bart": + x = torch.mean( + self.text_branch( + input_ids=text["input_ids"].to(device=device, non_blocking=True), + attention_mask=text["attention_mask"].to( + device=device, non_blocking=True + ), + )["encoder_last_hidden_state"], + axis=1, + ) + x = self.text_projection(x) + else: + logging.error(f"Model type {self.text_branch_type} not found") + raise RuntimeError(f"Model type {self.text_branch_type} not found.") + return x + + def forward(self, audio, text, device=None): + """Forward audio and text into the CLAP + + Parameters + ---------- + audio: torch.Tensor (batch_size, audio_length) + the time-domain audio input / the batch of mel_spec and longer list. + text: torch.Tensor () // need to add + the text token input + """ + if device is None: + if audio is not None: + device = audio.device + elif text is not None: + device = text.device + if audio is None and text is None: + # a hack to get the logit scale + return self.logit_scale_a.exp(), self.logit_scale_t.exp() + elif audio is None: + return self.encode_text(text, device=device) + elif text is None: + return self.audio_projection( + self.encode_audio(audio, device=device)["embedding"] + ) + audio_features = self.audio_projection( + self.encode_audio(audio, device=device)["embedding"] + ) + audio_features = F.normalize(audio_features, dim=-1) + + text_features = self.encode_text(text, device=device) + # print("text_features", text_features) + # print("text_features.shape", text_features.shape) + # print("text_features.type", type(text_features)) + text_features = F.normalize(text_features, dim=-1) + + audio_features_mlp = self.audio_transform(audio_features) + text_features_mlp = self.text_transform(text_features) + # Four outputs: audio features (basic & MLP), text features (basic & MLP) + return ( + audio_features, + text_features, + audio_features_mlp, + text_features_mlp, + self.logit_scale_a.exp(), + self.logit_scale_t.exp(), + ) + + def get_logit_scale(self): + return self.logit_scale_a.exp(), self.logit_scale_t.exp() + + def get_text_embedding(self, data): + """Get the text embedding from the model + + Parameters + ---------- + data: torch.Tensor + a tensor of text embedding + + Returns + ---------- + text_embed: torch.Tensor + a tensor of text_embeds (N, D) + + """ + device = next(self.parameters()).device + for k in data: + data[k] = data[k].to(device) + if len(data[k].size()) < 2: + data[k] = data[k].unsqueeze(0) + text_embeds = self.encode_text(data, device=device) + text_embeds = F.normalize(text_embeds, dim=-1) + + return text_embeds + + def get_audio_embedding(self, data): + """Get the audio embedding from the model + + Parameters + ---------- + data: a list of dict + the audio input dict list from 'get_audio_feature' method + + Returns + ---------- + audio_embed: torch.Tensor + a tensor of audio_embeds (N, D) + + """ + device = next(self.parameters()).device + input_dict = {} + keys = data[0].keys() + for k in keys: + input_dict[k] = torch.cat([d[k].unsqueeze(0) for d in data], dim=0).to( + device + ) + + audio_embeds = self.audio_projection( + self.encode_audio(input_dict, device=device)["embedding"] + ) + audio_embeds = F.normalize(audio_embeds, dim=-1) + + return audio_embeds + + def audio_infer(self, audio, hopsize=None, device=None): + """Forward one audio and produce the audio embedding + + Parameters + ---------- + audio: (audio_length) + the time-domain audio input, notice that it must be only one input + hopsize: int + the overlap hopsize as the sliding window + + Returns + ---------- + output_dict: { + key: [n, (embedding_shape)] if "HTS-AT" + or + key: [(embedding_shape)] if "PANN" + } + the list of key values of the audio branch + + """ + + assert not self.training, "the inference mode must be run at eval stage" + output_dict = {} + # PANN + if self.audio_cfg.model_type == "PANN": + audio_input = audio.unsqueeze(dim=0) + output_dict[key] = self.encode_audio(audio_input, device=device)[ + key + ].squeeze(dim=0) + elif self.audio_cfg.model_type == "HTSAT": + # repeat + audio_len = len(audio) + k = self.audio_cfg.clip_samples // audio_len + if k > 1: + audio = audio.repeat(k) + audio_len = len(audio) + + if hopsize is None: + hopsize = min(hopsize, audio_len) + + if audio_len > self.audio_cfg.clip_samples: + audio_input = [ + audio[pos : pos + self.audio_cfg.clip_samples].clone() + for pos in range( + 0, audio_len - self.audio_cfg.clip_samples, hopsize + ) + ] + audio_input.append(audio[-self.audio_cfg.clip_samples :].clone()) + audio_input = torch.stack(audio_input) + output_dict[key] = self.encode_audio(audio_input, device=device)[key] + else: + audio_input = audio.unsqueeze(dim=0) + output_dict[key] = self.encode_audio(audio_input, device=device)[ + key + ].squeeze(dim=0) + + return output_dict + + +def convert_weights_to_fp16(model: nn.Module): + """Convert applicable model parameters to fp16""" + + def _convert_weights_to_fp16(l): + if isinstance(l, (nn.Conv1d, nn.Conv2d, nn.Linear)): + l.weight.data = l.weight.data.half() + if l.bias is not None: + l.bias.data = l.bias.data.half() + + if isinstance(l, nn.MultiheadAttention): + for attr in [ + *[f"{s}_proj_weight" for s in ["in", "q", "k", "v"]], + "in_proj_bias", + "bias_k", + "bias_v", + ]: + tensor = getattr(l, attr) + if tensor is not None: + tensor.data = tensor.data.half() + + for name in ["text_projection", "proj"]: + if hasattr(l, name): + attr = getattr(l, name) + if attr is not None: + attr.data = attr.data.half() + + model.apply(_convert_weights_to_fp16) + + +# Ignore the state dict of the vision part +def build_model_from_openai_state_dict( + state_dict: dict, model_cfg, enable_fusion: bool = False, fusion_type: str = "None" +): + + embed_dim = model_cfg["embed_dim"] + audio_cfg = model_cfg["audio_cfg"] + text_cfg = model_cfg["text_cfg"] + context_length = state_dict["positional_embedding"].shape[0] + vocab_size = state_dict["token_embedding.weight"].shape[0] + transformer_width = state_dict["ln_final.weight"].shape[0] + transformer_heads = transformer_width // 64 + transformer_layers = len( + set( + k.split(".")[2] + for k in state_dict + if k.startswith(f"transformer.resblocks") + ) + ) + + audio_cfg = CLAPAudioCfp(**audio_cfg) + text_cfg = CLAPTextCfg(**text_cfg) + + model = CLAP( + embed_dim, + audio_cfg=audio_cfg, + text_cfg=text_cfg, + quick_gelu=True, # OpenAI models were trained with QuickGELU + enable_fusion=enable_fusion, + fusion_type=fusion_type, + ) + state_dict["logit_scale_a"] = state_dict["logit_scale"] + state_dict["logit_scale_t"] = state_dict["logit_scale"] + pop_keys = list(state_dict.keys())[::] + # pop the visual branch saved weights + for key in pop_keys: + if key.startswith("visual."): + state_dict.pop(key, None) + + for key in ["logit_scale", "input_resolution", "context_length", "vocab_size"]: + state_dict.pop(key, None) + + # not use fp16 + # convert_weights_to_fp16(model) + model.load_state_dict(state_dict, strict=False) + return model.eval() + + +def trace_model(model, batch_size=256, device=torch.device("cpu")): + model.eval() + audio_length = model.audio_cfg.audio_length + example_audio = torch.ones((batch_size, audio_length), device=device) + example_text = torch.zeros( + (batch_size, model.context_length), dtype=torch.int, device=device + ) + model = torch.jit.trace_module( + model, + inputs=dict( + forward=(example_audio, example_text), + encode_text=(example_text,), + encode_image=(example_audio,), + ), + ) + model.audio_cfg.audio_length = audio_length # Question: what does this do? + return model diff --git a/src/audioldm/clap/open_clip/model_configs/HTSAT-base.json b/src/audioldm/clap/open_clip/model_configs/HTSAT-base.json new file mode 100644 index 0000000000000000000000000000000000000000..3339000ba9a8fa1d87b7b480d06175b36dcaf125 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/HTSAT-base.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 1024, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "HTSAT", + "model_name": "base" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/HTSAT-large.json b/src/audioldm/clap/open_clip/model_configs/HTSAT-large.json new file mode 100644 index 0000000000000000000000000000000000000000..74751279f1e052fde44cadf5b1fce7a8370cd27a --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/HTSAT-large.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 2048, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "HTSAT", + "model_name": "large" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/HTSAT-tiny-win-1536.json b/src/audioldm/clap/open_clip/model_configs/HTSAT-tiny-win-1536.json new file mode 100644 index 0000000000000000000000000000000000000000..facabaef0bd02f2b059de5b3c1f3fdf48bb7dce3 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/HTSAT-tiny-win-1536.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 768, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1536, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "HTSAT", + "model_name": "tiny" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/HTSAT-tiny.json b/src/audioldm/clap/open_clip/model_configs/HTSAT-tiny.json new file mode 100644 index 0000000000000000000000000000000000000000..c8c0590c23877a2eef61b2b0ec76a09a9513e5cf --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/HTSAT-tiny.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 768, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "HTSAT", + "model_name": "tiny" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/PANN-10.json b/src/audioldm/clap/open_clip/model_configs/PANN-10.json new file mode 100644 index 0000000000000000000000000000000000000000..696c525e04898c73c9a4d66d9b4a8be1222df4a9 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/PANN-10.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 1024, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "PANN", + "model_name": "Cnn10" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/PANN-14-fmax-18k.json b/src/audioldm/clap/open_clip/model_configs/PANN-14-fmax-18k.json new file mode 100644 index 0000000000000000000000000000000000000000..9e8fee618fe08a08fe12ce3debe749f371438ddc --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/PANN-14-fmax-18k.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 2048, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 480, + "fmin": 50, + "fmax": 18000, + "class_num": 527, + "model_type": "PANN", + "model_name": "Cnn14" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/PANN-14-fmax-8k-20s.json b/src/audioldm/clap/open_clip/model_configs/PANN-14-fmax-8k-20s.json new file mode 100644 index 0000000000000000000000000000000000000000..71eab81316ce10688df44d8f5fbb2edf75f6bf5b --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/PANN-14-fmax-8k-20s.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 2048, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 960000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 360, + "fmin": 50, + "fmax": 8000, + "class_num": 527, + "model_type": "PANN", + "model_name": "Cnn14" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/PANN-14-tiny-transformer.json b/src/audioldm/clap/open_clip/model_configs/PANN-14-tiny-transformer.json new file mode 100644 index 0000000000000000000000000000000000000000..709b08112de87b2232c5660de6490bd3fab54b96 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/PANN-14-tiny-transformer.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 2048, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "PANN", + "model_name": "Cnn14" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 4 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/PANN-14-win-1536.json b/src/audioldm/clap/open_clip/model_configs/PANN-14-win-1536.json new file mode 100644 index 0000000000000000000000000000000000000000..e546dd66ef6449604da86e8bd54cd4df0c45b5c2 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/PANN-14-win-1536.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 2048, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1536, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "PANN", + "model_name": "Cnn14" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/PANN-14.json b/src/audioldm/clap/open_clip/model_configs/PANN-14.json new file mode 100644 index 0000000000000000000000000000000000000000..da281400f857bb42232ea72e7971a2495c4da602 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/PANN-14.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 2048, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "PANN", + "model_name": "Cnn14" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/PANN-6.json b/src/audioldm/clap/open_clip/model_configs/PANN-6.json new file mode 100644 index 0000000000000000000000000000000000000000..737f3695ccd95112f8830a273ff7f3cdbe412867 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/PANN-6.json @@ -0,0 +1,23 @@ +{ + "embed_dim": 512, + "audio_cfg": { + "audio_length": 1024, + "clip_samples": 480000, + "mel_bins": 64, + "sample_rate": 48000, + "window_size": 1024, + "hop_size": 480, + "fmin": 50, + "fmax": 14000, + "class_num": 527, + "model_type": "PANN", + "model_name": "Cnn6" + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/RN101-quickgelu.json b/src/audioldm/clap/open_clip/model_configs/RN101-quickgelu.json new file mode 100644 index 0000000000000000000000000000000000000000..f5ca94cf7bffc117cdba90a0c00e457c6b58b7d3 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/RN101-quickgelu.json @@ -0,0 +1,22 @@ +{ + "embed_dim": 512, + "quick_gelu": true, + "vision_cfg": { + "image_size": 224, + "layers": [ + 3, + 4, + 23, + 3 + ], + "width": 64, + "patch_size": null + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/RN101.json b/src/audioldm/clap/open_clip/model_configs/RN101.json new file mode 100644 index 0000000000000000000000000000000000000000..1a63f17773c9ef8b150dd60f3c7efb67f0e119f0 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/RN101.json @@ -0,0 +1,21 @@ +{ + "embed_dim": 512, + "vision_cfg": { + "image_size": 224, + "layers": [ + 3, + 4, + 23, + 3 + ], + "width": 64, + "patch_size": null + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/RN50-quickgelu.json b/src/audioldm/clap/open_clip/model_configs/RN50-quickgelu.json new file mode 100644 index 0000000000000000000000000000000000000000..cf338792a68c92e98040965a77389d6632a93f17 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/RN50-quickgelu.json @@ -0,0 +1,22 @@ +{ + "embed_dim": 1024, + "quick_gelu": true, + "vision_cfg": { + "image_size": 224, + "layers": [ + 3, + 4, + 6, + 3 + ], + "width": 64, + "patch_size": null + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} diff --git a/src/audioldm/clap/open_clip/model_configs/RN50.json b/src/audioldm/clap/open_clip/model_configs/RN50.json new file mode 100644 index 0000000000000000000000000000000000000000..d53335b21bef7c5d8ae527204089eb331a24dbf2 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/RN50.json @@ -0,0 +1,21 @@ +{ + "embed_dim": 1024, + "vision_cfg": { + "image_size": 224, + "layers": [ + 3, + 4, + 6, + 3 + ], + "width": 64, + "patch_size": null + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/RN50x16.json b/src/audioldm/clap/open_clip/model_configs/RN50x16.json new file mode 100644 index 0000000000000000000000000000000000000000..dbdb2782589193f3b090188b9e5597be5309f8e2 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/RN50x16.json @@ -0,0 +1,21 @@ +{ + "embed_dim": 768, + "vision_cfg": { + "image_size": 384, + "layers": [ + 6, + 8, + 18, + 8 + ], + "width": 96, + "patch_size": null + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 768, + "heads": 12, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/RN50x4.json b/src/audioldm/clap/open_clip/model_configs/RN50x4.json new file mode 100644 index 0000000000000000000000000000000000000000..3dce2e9e851ef51ad42e841f1f26322b5478bd07 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/RN50x4.json @@ -0,0 +1,21 @@ +{ + "embed_dim": 640, + "vision_cfg": { + "image_size": 288, + "layers": [ + 4, + 6, + 10, + 6 + ], + "width": 80, + "patch_size": null + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 640, + "heads": 10, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/ViT-B-16.json b/src/audioldm/clap/open_clip/model_configs/ViT-B-16.json new file mode 100644 index 0000000000000000000000000000000000000000..0b22c2a72ad75bf60372ade0bce927527b459e84 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/ViT-B-16.json @@ -0,0 +1,16 @@ +{ + "embed_dim": 512, + "vision_cfg": { + "image_size": 224, + "layers": 12, + "width": 768, + "patch_size": 16 + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/ViT-B-32-quickgelu.json b/src/audioldm/clap/open_clip/model_configs/ViT-B-32-quickgelu.json new file mode 100644 index 0000000000000000000000000000000000000000..17bd87da5a4b591ecd9881547d2d3d7a4c6a8b13 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/ViT-B-32-quickgelu.json @@ -0,0 +1,17 @@ +{ + "embed_dim": 512, + "quick_gelu": true, + "vision_cfg": { + "image_size": 224, + "layers": 12, + "width": 768, + "patch_size": 32 + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/ViT-B-32.json b/src/audioldm/clap/open_clip/model_configs/ViT-B-32.json new file mode 100644 index 0000000000000000000000000000000000000000..ad11cb35dcfa2f544d2100afff46f6d8252a6bfa --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/ViT-B-32.json @@ -0,0 +1,16 @@ +{ + "embed_dim": 512, + "vision_cfg": { + "image_size": 224, + "layers": 12, + "width": 768, + "patch_size": 32 + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 512, + "heads": 8, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/model_configs/ViT-L-14.json b/src/audioldm/clap/open_clip/model_configs/ViT-L-14.json new file mode 100644 index 0000000000000000000000000000000000000000..824142e99cb17ca4aa15cd9afc96373644dfd709 --- /dev/null +++ b/src/audioldm/clap/open_clip/model_configs/ViT-L-14.json @@ -0,0 +1,16 @@ +{ + "embed_dim": 768, + "vision_cfg": { + "image_size": 224, + "layers": 24, + "width": 1024, + "patch_size": 14 + }, + "text_cfg": { + "context_length": 77, + "vocab_size": 49408, + "width": 768, + "heads": 12, + "layers": 12 + } +} \ No newline at end of file diff --git a/src/audioldm/clap/open_clip/openai.py b/src/audioldm/clap/open_clip/openai.py new file mode 100644 index 0000000000000000000000000000000000000000..26b592bad119ca1ed5e378810c82a5a12e8501a3 --- /dev/null +++ b/src/audioldm/clap/open_clip/openai.py @@ -0,0 +1,159 @@ +""" OpenAI pretrained model functions + +Adapted from https://github.com/openai/CLIP. Originally MIT License, Copyright (c) 2021 OpenAI. +""" + +import os +import warnings +from typing import Union, List + +import torch + +from .model import build_model_from_openai_state_dict +from .pretrained import ( + get_pretrained_url, + list_pretrained_tag_models, + download_pretrained, +) + +__all__ = ["list_openai_models", "load_openai_model"] + +CACHE_DIR = os.getenv("AUDIOLDM_CACHE_DIR", "~/.cache") + + + +def list_openai_models() -> List[str]: + """Returns the names of available CLIP models""" + return list_pretrained_tag_models("openai") + + +def load_openai_model( + name: str, + model_cfg, + device: Union[str, torch.device] = "cuda" if torch.cuda.is_available() else "cpu", + jit=True, + cache_dir=os.path.expanduser(f"{CACHE_DIR}/clip"), + enable_fusion: bool = False, + fusion_type: str = "None", +): + """Load a CLIP model, preserve its text pretrained part, and set in the CLAP model + + Parameters + ---------- + name : str + A model name listed by `clip.available_models()`, or the path to a model checkpoint containing the state_dict + device : Union[str, torch.device] + The device to put the loaded model + jit : bool + Whether to load the optimized JIT model (default) or more hackable non-JIT model. + + Returns + ------- + model : torch.nn.Module + The CLAP model + preprocess : Callable[[PIL.Image], torch.Tensor] + A torchvision transform that converts a PIL image into a tensor that the returned model can take as its input + """ + if get_pretrained_url(name, "openai"): + model_path = download_pretrained( + get_pretrained_url(name, "openai"), root=cache_dir + ) + elif os.path.isfile(name): + model_path = name + else: + raise RuntimeError( + f"Model {name} not found; available models = {list_openai_models()}" + ) + + try: + # loading JIT archive + model = torch.jit.load(model_path, map_location=device if jit else "cpu").eval() + state_dict = None + except RuntimeError: + # loading saved state dict + if jit: + warnings.warn( + f"File {model_path} is not a JIT archive. Loading as a state dict instead" + ) + jit = False + state_dict = torch.load(model_path, map_location="cpu") + + if not jit: + try: + model = build_model_from_openai_state_dict( + state_dict or model.state_dict(), model_cfg, enable_fusion, fusion_type + ).to(device) + except KeyError: + sd = {k[7:]: v for k, v in state_dict["state_dict"].items()} + model = build_model_from_openai_state_dict( + sd, model_cfg, enable_fusion, fusion_type + ).to(device) + + if str(device) == "cpu": + model.float() + return model + + # patch the device names + device_holder = torch.jit.trace( + lambda: torch.ones([]).to(torch.device(device)), example_inputs=[] + ) + device_node = [ + n + for n in device_holder.graph.findAllNodes("prim::Constant") + if "Device" in repr(n) + ][-1] + + def patch_device(module): + try: + graphs = [module.graph] if hasattr(module, "graph") else [] + except RuntimeError: + graphs = [] + + if hasattr(module, "forward1"): + graphs.append(module.forward1.graph) + + for graph in graphs: + for node in graph.findAllNodes("prim::Constant"): + if "value" in node.attributeNames() and str(node["value"]).startswith( + "cuda" + ): + node.copyAttributes(device_node) + + model.apply(patch_device) + patch_device(model.encode_audio) + patch_device(model.encode_text) + + # patch dtype to float32 on CPU + if str(device) == "cpu": + float_holder = torch.jit.trace( + lambda: torch.ones([]).float(), example_inputs=[] + ) + float_input = list(float_holder.graph.findNode("aten::to").inputs())[1] + float_node = float_input.node() + + def patch_float(module): + try: + graphs = [module.graph] if hasattr(module, "graph") else [] + except RuntimeError: + graphs = [] + + if hasattr(module, "forward1"): + graphs.append(module.forward1.graph) + + for graph in graphs: + for node in graph.findAllNodes("aten::to"): + inputs = list(node.inputs()) + for i in [ + 1, + 2, + ]: # dtype can be the second or third argument to aten::to() + if inputs[i].node()["value"] == 5: + inputs[i].node().copyAttributes(float_node) + + model.apply(patch_float) + patch_float(model.encode_audio) + patch_float(model.encode_text) + model.float() + + model.audio_branch.audio_length = model.audio_cfg.audio_length + return model diff --git a/src/audioldm/clap/open_clip/pann_model.py b/src/audioldm/clap/open_clip/pann_model.py new file mode 100644 index 0000000000000000000000000000000000000000..36a6e974c0f7d4852072f0f76c0845c6990b0717 --- /dev/null +++ b/src/audioldm/clap/open_clip/pann_model.py @@ -0,0 +1,704 @@ +# PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition +# Reference from https://github.com/qiuqiangkong/audioset_tagging_cnn +# Some layers are re-designed for CLAP +import os + +os.environ["NUMBA_CACHE_DIR"] = "/tmp/" + +import torch +import torch.nn as nn +import torch.nn.functional as F +from torchlibrosa.stft import Spectrogram, LogmelFilterBank +from torchlibrosa.augmentation import SpecAugmentation + +from .utils import do_mixup, interpolate, pad_framewise_output +from .feature_fusion import iAFF, AFF, DAF + + +def init_layer(layer): + """Initialize a Linear or Convolutional layer.""" + nn.init.xavier_uniform_(layer.weight) + + if hasattr(layer, "bias"): + if layer.bias is not None: + layer.bias.data.fill_(0.0) + + +def init_bn(bn): + """Initialize a Batchnorm layer.""" + bn.bias.data.fill_(0.0) + bn.weight.data.fill_(1.0) + + +class ConvBlock(nn.Module): + def __init__(self, in_channels, out_channels): + + super(ConvBlock, self).__init__() + + self.conv1 = nn.Conv2d( + in_channels=in_channels, + out_channels=out_channels, + kernel_size=(3, 3), + stride=(1, 1), + padding=(1, 1), + bias=False, + ) + + self.conv2 = nn.Conv2d( + in_channels=out_channels, + out_channels=out_channels, + kernel_size=(3, 3), + stride=(1, 1), + padding=(1, 1), + bias=False, + ) + + self.bn1 = nn.BatchNorm2d(out_channels) + self.bn2 = nn.BatchNorm2d(out_channels) + + self.init_weight() + + def init_weight(self): + init_layer(self.conv1) + init_layer(self.conv2) + init_bn(self.bn1) + init_bn(self.bn2) + + def forward(self, input, pool_size=(2, 2), pool_type="avg"): + + x = input + x = F.relu_(self.bn1(self.conv1(x))) + x = F.relu_(self.bn2(self.conv2(x))) + if pool_type == "max": + x = F.max_pool2d(x, kernel_size=pool_size) + elif pool_type == "avg": + x = F.avg_pool2d(x, kernel_size=pool_size) + elif pool_type == "avg+max": + x1 = F.avg_pool2d(x, kernel_size=pool_size) + x2 = F.max_pool2d(x, kernel_size=pool_size) + x = x1 + x2 + else: + raise Exception("Incorrect argument!") + + return x + + +class ConvBlock5x5(nn.Module): + def __init__(self, in_channels, out_channels): + + super(ConvBlock5x5, self).__init__() + + self.conv1 = nn.Conv2d( + in_channels=in_channels, + out_channels=out_channels, + kernel_size=(5, 5), + stride=(1, 1), + padding=(2, 2), + bias=False, + ) + + self.bn1 = nn.BatchNorm2d(out_channels) + + self.init_weight() + + def init_weight(self): + init_layer(self.conv1) + init_bn(self.bn1) + + def forward(self, input, pool_size=(2, 2), pool_type="avg"): + + x = input + x = F.relu_(self.bn1(self.conv1(x))) + if pool_type == "max": + x = F.max_pool2d(x, kernel_size=pool_size) + elif pool_type == "avg": + x = F.avg_pool2d(x, kernel_size=pool_size) + elif pool_type == "avg+max": + x1 = F.avg_pool2d(x, kernel_size=pool_size) + x2 = F.max_pool2d(x, kernel_size=pool_size) + x = x1 + x2 + else: + raise Exception("Incorrect argument!") + + return x + + +class AttBlock(nn.Module): + def __init__(self, n_in, n_out, activation="linear", temperature=1.0): + super(AttBlock, self).__init__() + + self.activation = activation + self.temperature = temperature + self.att = nn.Conv1d( + in_channels=n_in, + out_channels=n_out, + kernel_size=1, + stride=1, + padding=0, + bias=True, + ) + self.cla = nn.Conv1d( + in_channels=n_in, + out_channels=n_out, + kernel_size=1, + stride=1, + padding=0, + bias=True, + ) + + self.bn_att = nn.BatchNorm1d(n_out) + self.init_weights() + + def init_weights(self): + init_layer(self.att) + init_layer(self.cla) + init_bn(self.bn_att) + + def forward(self, x): + # x: (n_samples, n_in, n_time) + norm_att = torch.softmax(torch.clamp(self.att(x), -10, 10), dim=-1) + cla = self.nonlinear_transform(self.cla(x)) + x = torch.sum(norm_att * cla, dim=2) + return x, norm_att, cla + + def nonlinear_transform(self, x): + if self.activation == "linear": + return x + elif self.activation == "sigmoid": + return torch.sigmoid(x) + + +class Cnn14(nn.Module): + def __init__( + self, + sample_rate, + window_size, + hop_size, + mel_bins, + fmin, + fmax, + classes_num, + enable_fusion=False, + fusion_type="None", + ): + + super(Cnn14, self).__init__() + + window = "hann" + center = True + pad_mode = "reflect" + ref = 1.0 + amin = 1e-10 + top_db = None + + self.enable_fusion = enable_fusion + self.fusion_type = fusion_type + + # Spectrogram extractor + self.spectrogram_extractor = Spectrogram( + n_fft=window_size, + hop_length=hop_size, + win_length=window_size, + window=window, + center=center, + pad_mode=pad_mode, + freeze_parameters=True, + ) + + # Logmel feature extractor + self.logmel_extractor = LogmelFilterBank( + sr=sample_rate, + n_fft=window_size, + n_mels=mel_bins, + fmin=fmin, + fmax=fmax, + ref=ref, + amin=amin, + top_db=top_db, + freeze_parameters=True, + ) + + # Spec augmenter + self.spec_augmenter = SpecAugmentation( + time_drop_width=64, + time_stripes_num=2, + freq_drop_width=8, + freq_stripes_num=2, + ) + + self.bn0 = nn.BatchNorm2d(64) + + if (self.enable_fusion) and (self.fusion_type == "channel_map"): + self.conv_block1 = ConvBlock(in_channels=4, out_channels=64) + else: + self.conv_block1 = ConvBlock(in_channels=1, out_channels=64) + self.conv_block2 = ConvBlock(in_channels=64, out_channels=128) + self.conv_block3 = ConvBlock(in_channels=128, out_channels=256) + self.conv_block4 = ConvBlock(in_channels=256, out_channels=512) + self.conv_block5 = ConvBlock(in_channels=512, out_channels=1024) + self.conv_block6 = ConvBlock(in_channels=1024, out_channels=2048) + + self.fc1 = nn.Linear(2048, 2048, bias=True) + self.fc_audioset = nn.Linear(2048, classes_num, bias=True) + + if (self.enable_fusion) and ( + self.fusion_type in ["daf_1d", "aff_1d", "iaff_1d"] + ): + self.mel_conv1d = nn.Sequential( + nn.Conv1d(64, 64, kernel_size=5, stride=3, padding=2), + nn.BatchNorm1d(64), # No Relu + ) + if self.fusion_type == "daf_1d": + self.fusion_model = DAF() + elif self.fusion_type == "aff_1d": + self.fusion_model = AFF(channels=64, type="1D") + elif self.fusion_type == "iaff_1d": + self.fusion_model = iAFF(channels=64, type="1D") + + if (self.enable_fusion) and ( + self.fusion_type in ["daf_2d", "aff_2d", "iaff_2d"] + ): + self.mel_conv2d = nn.Sequential( + nn.Conv2d(1, 64, kernel_size=(5, 5), stride=(6, 2), padding=(2, 2)), + nn.BatchNorm2d(64), + nn.ReLU(inplace=True), + ) + + if self.fusion_type == "daf_2d": + self.fusion_model = DAF() + elif self.fusion_type == "aff_2d": + self.fusion_model = AFF(channels=64, type="2D") + elif self.fusion_type == "iaff_2d": + self.fusion_model = iAFF(channels=64, type="2D") + self.init_weight() + + def init_weight(self): + init_bn(self.bn0) + init_layer(self.fc1) + init_layer(self.fc_audioset) + + def forward(self, input, mixup_lambda=None, device=None): + """ + Input: (batch_size, data_length)""" + + if self.enable_fusion and input["longer"].sum() == 0: + # if no audio is longer than 10s, then randomly select one audio to be longer + input["longer"][torch.randint(0, input["longer"].shape[0], (1,))] = True + + if not self.enable_fusion: + x = self.spectrogram_extractor( + input["waveform"].to(device=device, non_blocking=True) + ) # (batch_size, 1, time_steps, freq_bins) + x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins) + + x = x.transpose(1, 3) + x = self.bn0(x) + x = x.transpose(1, 3) + else: + longer_list = input["longer"].to(device=device, non_blocking=True) + x = input["mel_fusion"].to(device=device, non_blocking=True) + longer_list_idx = torch.where(longer_list)[0] + x = x.transpose(1, 3) + x = self.bn0(x) + x = x.transpose(1, 3) + if self.fusion_type in ["daf_1d", "aff_1d", "iaff_1d"]: + new_x = x[:, 0:1, :, :].clone().contiguous() + # local processing + if len(longer_list_idx) > 0: + fusion_x_local = x[longer_list_idx, 1:, :, :].clone().contiguous() + FB, FC, FT, FF = fusion_x_local.size() + fusion_x_local = fusion_x_local.view(FB * FC, FT, FF) + fusion_x_local = torch.permute( + fusion_x_local, (0, 2, 1) + ).contiguous() + fusion_x_local = self.mel_conv1d(fusion_x_local) + fusion_x_local = fusion_x_local.view( + FB, FC, FF, fusion_x_local.size(-1) + ) + fusion_x_local = ( + torch.permute(fusion_x_local, (0, 2, 1, 3)) + .contiguous() + .flatten(2) + ) + if fusion_x_local.size(-1) < FT: + fusion_x_local = torch.cat( + [ + fusion_x_local, + torch.zeros( + (FB, FF, FT - fusion_x_local.size(-1)), + device=device, + ), + ], + dim=-1, + ) + else: + fusion_x_local = fusion_x_local[:, :, :FT] + # 1D fusion + new_x = new_x.squeeze(1).permute((0, 2, 1)).contiguous() + new_x[longer_list_idx] = self.fusion_model( + new_x[longer_list_idx], fusion_x_local + ) + x = new_x.permute((0, 2, 1)).contiguous()[:, None, :, :] + else: + x = new_x + elif self.fusion_type in ["daf_2d", "aff_2d", "iaff_2d", "channel_map"]: + x = x # no change + + if self.training: + x = self.spec_augmenter(x) + # Mixup on spectrogram + if self.training and mixup_lambda is not None: + x = do_mixup(x, mixup_lambda) + if (self.enable_fusion) and ( + self.fusion_type in ["daf_2d", "aff_2d", "iaff_2d"] + ): + global_x = x[:, 0:1, :, :] + + # global processing + B, C, H, W = global_x.shape + global_x = self.conv_block1(global_x, pool_size=(2, 2), pool_type="avg") + if len(longer_list_idx) > 0: + local_x = x[longer_list_idx, 1:, :, :].contiguous() + TH = global_x.size(-2) + # local processing + B, C, H, W = local_x.shape + local_x = local_x.view(B * C, 1, H, W) + local_x = self.mel_conv2d(local_x) + local_x = local_x.view( + B, C, local_x.size(1), local_x.size(2), local_x.size(3) + ) + local_x = local_x.permute((0, 2, 1, 3, 4)).contiguous().flatten(2, 3) + TB, TC, _, TW = local_x.size() + if local_x.size(-2) < TH: + local_x = torch.cat( + [ + local_x, + torch.zeros( + (TB, TC, TH - local_x.size(-2), TW), + device=global_x.device, + ), + ], + dim=-2, + ) + else: + local_x = local_x[:, :, :TH, :] + + global_x[longer_list_idx] = self.fusion_model( + global_x[longer_list_idx], local_x + ) + x = global_x + else: + x = self.conv_block1(x, pool_size=(2, 2), pool_type="avg") + + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block2(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block3(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block4(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block5(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block6(x, pool_size=(1, 1), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = torch.mean(x, dim=3) + + latent_x1 = F.max_pool1d(x, kernel_size=3, stride=1, padding=1) + latent_x2 = F.avg_pool1d(x, kernel_size=3, stride=1, padding=1) + latent_x = latent_x1 + latent_x2 + latent_x = latent_x.transpose(1, 2) + latent_x = F.relu_(self.fc1(latent_x)) + latent_output = interpolate(latent_x, 32) + + (x1, _) = torch.max(x, dim=2) + x2 = torch.mean(x, dim=2) + x = x1 + x2 + x = F.dropout(x, p=0.5, training=self.training) + x = F.relu_(self.fc1(x)) + embedding = F.dropout(x, p=0.5, training=self.training) + clipwise_output = torch.sigmoid(self.fc_audioset(x)) + + output_dict = { + "clipwise_output": clipwise_output, + "embedding": embedding, + "fine_grained_embedding": latent_output, + } + return output_dict + + +class Cnn6(nn.Module): + def __init__( + self, + sample_rate, + window_size, + hop_size, + mel_bins, + fmin, + fmax, + classes_num, + enable_fusion=False, + fusion_type="None", + ): + + super(Cnn6, self).__init__() + + window = "hann" + center = True + pad_mode = "reflect" + ref = 1.0 + amin = 1e-10 + top_db = None + + self.enable_fusion = enable_fusion + self.fusion_type = fusion_type + + # Spectrogram extractor + self.spectrogram_extractor = Spectrogram( + n_fft=window_size, + hop_length=hop_size, + win_length=window_size, + window=window, + center=center, + pad_mode=pad_mode, + freeze_parameters=True, + ) + + # Logmel feature extractor + self.logmel_extractor = LogmelFilterBank( + sr=sample_rate, + n_fft=window_size, + n_mels=mel_bins, + fmin=fmin, + fmax=fmax, + ref=ref, + amin=amin, + top_db=top_db, + freeze_parameters=True, + ) + + # Spec augmenter + self.spec_augmenter = SpecAugmentation( + time_drop_width=64, + time_stripes_num=2, + freq_drop_width=8, + freq_stripes_num=2, + ) + + self.bn0 = nn.BatchNorm2d(64) + + self.conv_block1 = ConvBlock5x5(in_channels=1, out_channels=64) + self.conv_block2 = ConvBlock5x5(in_channels=64, out_channels=128) + self.conv_block3 = ConvBlock5x5(in_channels=128, out_channels=256) + self.conv_block4 = ConvBlock5x5(in_channels=256, out_channels=512) + + self.fc1 = nn.Linear(512, 512, bias=True) + self.fc_audioset = nn.Linear(512, classes_num, bias=True) + + self.init_weight() + + def init_weight(self): + init_bn(self.bn0) + init_layer(self.fc1) + init_layer(self.fc_audioset) + + def forward(self, input, mixup_lambda=None, device=None): + """ + Input: (batch_size, data_length)""" + + x = self.spectrogram_extractor(input) # (batch_size, 1, time_steps, freq_bins) + x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins) + + x = x.transpose(1, 3) + x = self.bn0(x) + x = x.transpose(1, 3) + + if self.training: + x = self.spec_augmenter(x) + + # Mixup on spectrogram + if self.training and mixup_lambda is not None: + x = do_mixup(x, mixup_lambda) + + x = self.conv_block1(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block2(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block3(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block4(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = torch.mean(x, dim=3) + + latent_x1 = F.max_pool1d(x, kernel_size=3, stride=1, padding=1) + latent_x2 = F.avg_pool1d(x, kernel_size=3, stride=1, padding=1) + latent_x = latent_x1 + latent_x2 + latent_x = latent_x.transpose(1, 2) + latent_x = F.relu_(self.fc1(latent_x)) + latent_output = interpolate(latent_x, 16) + + (x1, _) = torch.max(x, dim=2) + x2 = torch.mean(x, dim=2) + x = x1 + x2 + x = F.dropout(x, p=0.5, training=self.training) + x = F.relu_(self.fc1(x)) + embedding = F.dropout(x, p=0.5, training=self.training) + clipwise_output = torch.sigmoid(self.fc_audioset(x)) + + output_dict = { + "clipwise_output": clipwise_output, + "embedding": embedding, + "fine_grained_embedding": latent_output, + } + + return output_dict + + +class Cnn10(nn.Module): + def __init__( + self, + sample_rate, + window_size, + hop_size, + mel_bins, + fmin, + fmax, + classes_num, + enable_fusion=False, + fusion_type="None", + ): + + super(Cnn10, self).__init__() + + window = "hann" + center = True + pad_mode = "reflect" + ref = 1.0 + amin = 1e-10 + top_db = None + + self.enable_fusion = enable_fusion + self.fusion_type = fusion_type + + # Spectrogram extractor + self.spectrogram_extractor = Spectrogram( + n_fft=window_size, + hop_length=hop_size, + win_length=window_size, + window=window, + center=center, + pad_mode=pad_mode, + freeze_parameters=True, + ) + + # Logmel feature extractor + self.logmel_extractor = LogmelFilterBank( + sr=sample_rate, + n_fft=window_size, + n_mels=mel_bins, + fmin=fmin, + fmax=fmax, + ref=ref, + amin=amin, + top_db=top_db, + freeze_parameters=True, + ) + + # Spec augmenter + self.spec_augmenter = SpecAugmentation( + time_drop_width=64, + time_stripes_num=2, + freq_drop_width=8, + freq_stripes_num=2, + ) + + self.bn0 = nn.BatchNorm2d(64) + + self.conv_block1 = ConvBlock(in_channels=1, out_channels=64) + self.conv_block2 = ConvBlock(in_channels=64, out_channels=128) + self.conv_block3 = ConvBlock(in_channels=128, out_channels=256) + self.conv_block4 = ConvBlock(in_channels=256, out_channels=512) + self.conv_block5 = ConvBlock(in_channels=512, out_channels=1024) + + self.fc1 = nn.Linear(1024, 1024, bias=True) + self.fc_audioset = nn.Linear(1024, classes_num, bias=True) + + self.init_weight() + + def init_weight(self): + init_bn(self.bn0) + init_layer(self.fc1) + init_layer(self.fc_audioset) + + def forward(self, input, mixup_lambda=None, device=None): + """ + Input: (batch_size, data_length)""" + + x = self.spectrogram_extractor(input) # (batch_size, 1, time_steps, freq_bins) + x = self.logmel_extractor(x) # (batch_size, 1, time_steps, mel_bins) + + x = x.transpose(1, 3) + x = self.bn0(x) + x = x.transpose(1, 3) + + if self.training: + x = self.spec_augmenter(x) + + # Mixup on spectrogram + if self.training and mixup_lambda is not None: + x = do_mixup(x, mixup_lambda) + + x = self.conv_block1(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block2(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block3(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block4(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = self.conv_block5(x, pool_size=(2, 2), pool_type="avg") + x = F.dropout(x, p=0.2, training=self.training) + x = torch.mean(x, dim=3) + + latent_x1 = F.max_pool1d(x, kernel_size=3, stride=1, padding=1) + latent_x2 = F.avg_pool1d(x, kernel_size=3, stride=1, padding=1) + latent_x = latent_x1 + latent_x2 + latent_x = latent_x.transpose(1, 2) + latent_x = F.relu_(self.fc1(latent_x)) + latent_output = interpolate(latent_x, 32) + + (x1, _) = torch.max(x, dim=2) + x2 = torch.mean(x, dim=2) + x = x1 + x2 + x = F.dropout(x, p=0.5, training=self.training) + x = F.relu_(self.fc1(x)) + embedding = F.dropout(x, p=0.5, training=self.training) + clipwise_output = torch.sigmoid(self.fc_audioset(x)) + + output_dict = { + "clipwise_output": clipwise_output, + "embedding": embedding, + "fine_grained_embedding": latent_output, + } + + return output_dict + + +def create_pann_model(audio_cfg, enable_fusion=False, fusion_type="None"): + try: + ModelProto = eval(audio_cfg.model_name) + model = ModelProto( + sample_rate=audio_cfg.sample_rate, + window_size=audio_cfg.window_size, + hop_size=audio_cfg.hop_size, + mel_bins=audio_cfg.mel_bins, + fmin=audio_cfg.fmin, + fmax=audio_cfg.fmax, + classes_num=audio_cfg.class_num, + enable_fusion=enable_fusion, + fusion_type=fusion_type, + ) + return model + except: + raise RuntimeError( + f"Import Model for {audio_cfg.model_name} not found, or the audio cfg parameters are not enough." + ) diff --git a/src/audioldm/clap/open_clip/pretrained.py b/src/audioldm/clap/open_clip/pretrained.py new file mode 100644 index 0000000000000000000000000000000000000000..d4a811ea0eb08f68fdbe6e405653a5a5d2285400 --- /dev/null +++ b/src/audioldm/clap/open_clip/pretrained.py @@ -0,0 +1,169 @@ +import hashlib +import os +import urllib +import warnings + +from tqdm import tqdm + +CACHE_DIR = os.getenv("AUDIOLDM_CACHE_DIR", "~/.cache") + +_RN50 = dict( + openai="https://openaipublic.azureedge.net/clip/models/afeb0e10f9e5a86da6080e35cf09123aca3b358a0c3e3b6c78a7b63bc04b6762/RN50.pt", + yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-quickgelu-yfcc15m-455df137.pt", + cc12m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-quickgelu-cc12m-f000538c.pt", +) + +_RN50_quickgelu = dict( + openai="https://openaipublic.azureedge.net/clip/models/afeb0e10f9e5a86da6080e35cf09123aca3b358a0c3e3b6c78a7b63bc04b6762/RN50.pt", + yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-quickgelu-yfcc15m-455df137.pt", + cc12m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-quickgelu-cc12m-f000538c.pt", +) + +_RN101 = dict( + openai="https://openaipublic.azureedge.net/clip/models/8fa8567bab74a42d41c5915025a8e4538c3bdbe8804a470a72f30b0d94fab599/RN101.pt", + yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn101-quickgelu-yfcc15m-3e04b30e.pt", +) + +_RN101_quickgelu = dict( + openai="https://openaipublic.azureedge.net/clip/models/8fa8567bab74a42d41c5915025a8e4538c3bdbe8804a470a72f30b0d94fab599/RN101.pt", + yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn101-quickgelu-yfcc15m-3e04b30e.pt", +) + +_RN50x4 = dict( + openai="https://openaipublic.azureedge.net/clip/models/7e526bd135e493cef0776de27d5f42653e6b4c8bf9e0f653bb11773263205fdd/RN50x4.pt", +) + +_RN50x16 = dict( + openai="https://openaipublic.azureedge.net/clip/models/52378b407f34354e150460fe41077663dd5b39c54cd0bfd2b27167a4a06ec9aa/RN50x16.pt", +) + +_RN50x64 = dict( + openai="https://openaipublic.azureedge.net/clip/models/be1cfb55d75a9666199fb2206c106743da0f6468c9d327f3e0d0a543a9919d9c/RN50x64.pt", +) + +_VITB32 = dict( + openai="https://openaipublic.azureedge.net/clip/models/40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af/ViT-B-32.pt", + laion400m_e31="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_e31-d867053b.pt", + laion400m_e32="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_e32-46683a32.pt", + laion400m_avg="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_avg-8a00ab3c.pt", +) + +_VITB32_quickgelu = dict( + openai="https://openaipublic.azureedge.net/clip/models/40d365715913c9da98579312b702a82c18be219cc2a73407c4526f58eba950af/ViT-B-32.pt", + laion400m_e31="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_e31-d867053b.pt", + laion400m_e32="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_e32-46683a32.pt", + laion400m_avg="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/vit_b_32-quickgelu-laion400m_avg-8a00ab3c.pt", +) + +_VITB16 = dict( + openai="https://openaipublic.azureedge.net/clip/models/5806e77cd80f8b59890b7e101eabd078d9fb84e6937f9e85e4ecb61988df416f/ViT-B-16.pt", +) + +_VITL14 = dict( + openai="https://openaipublic.azureedge.net/clip/models/b8cca3fd41ae0c99ba7e8951adf17d267cdb84cd88be6f7c2e0eca1737a03836/ViT-L-14.pt", +) + +_PRETRAINED = { + "RN50": _RN50, + "RN50-quickgelu": _RN50_quickgelu, + "RN101": _RN101, + "RN101-quickgelu": _RN101_quickgelu, + "RN50x4": _RN50x4, + "RN50x16": _RN50x16, + "ViT-B-32": _VITB32, + "ViT-B-32-quickgelu": _VITB32_quickgelu, + "ViT-B-16": _VITB16, + "ViT-L-14": _VITL14, +} + + +def list_pretrained(as_str: bool = False): + """returns list of pretrained models + Returns a tuple (model_name, pretrain_tag) by default or 'name:tag' if as_str == True + """ + return [ + ":".join([k, t]) if as_str else (k, t) + for k in _PRETRAINED.keys() + for t in _PRETRAINED[k].keys() + ] + + +def list_pretrained_tag_models(tag: str): + """return all models having the specified pretrain tag""" + models = [] + for k in _PRETRAINED.keys(): + if tag in _PRETRAINED[k]: + models.append(k) + return models + + +def list_pretrained_model_tags(model: str): + """return all pretrain tags for the specified model architecture""" + tags = [] + if model in _PRETRAINED: + tags.extend(_PRETRAINED[model].keys()) + return tags + + +def get_pretrained_url(model: str, tag: str): + if model not in _PRETRAINED: + return "" + model_pretrained = _PRETRAINED[model] + if tag not in model_pretrained: + return "" + return model_pretrained[tag] + + +def download_pretrained(url: str, root: str = os.path.expanduser(f"{CACHE_DIR}/clip")): + os.makedirs(root, exist_ok=True) + filename = os.path.basename(url) + + if "openaipublic" in url: + expected_sha256 = url.split("/")[-2] + else: + expected_sha256 = "" + + download_target = os.path.join(root, filename) + + if os.path.exists(download_target) and not os.path.isfile(download_target): + raise RuntimeError(f"{download_target} exists and is not a regular file") + + if os.path.isfile(download_target): + if expected_sha256: + if ( + hashlib.sha256(open(download_target, "rb").read()).hexdigest() + == expected_sha256 + ): + return download_target + else: + warnings.warn( + f"{download_target} exists, but the SHA256 checksum does not match; re-downloading the file" + ) + else: + return download_target + + with urllib.request.urlopen(url) as source, open(download_target, "wb") as output: + with tqdm( + total=int(source.info().get("Content-Length")), + ncols=80, + unit="iB", + unit_scale=True, + ) as loop: + while True: + buffer = source.read(8192) + if not buffer: + break + + output.write(buffer) + loop.update(len(buffer)) + + if ( + expected_sha256 + and hashlib.sha256(open(download_target, "rb").read()).hexdigest() + != expected_sha256 + ): + raise RuntimeError( + f"Model has been downloaded but the SHA256 checksum does not not match" + ) + + return download_target diff --git a/src/audioldm/clap/open_clip/timm_model.py b/src/audioldm/clap/open_clip/timm_model.py new file mode 100644 index 0000000000000000000000000000000000000000..87f722be5055d89c3de46f20a74fd7d79d262692 --- /dev/null +++ b/src/audioldm/clap/open_clip/timm_model.py @@ -0,0 +1,112 @@ +""" timm model adapter + +Wraps timm (https://github.com/rwightman/pytorch-image-models) models for use as a vision tower in CLIP model. +""" +from collections import OrderedDict + +import torch.nn as nn + +try: + import timm + from timm.models.layers import Mlp, to_2tuple + from timm.models.layers.attention_pool2d import RotAttentionPool2d + from timm.models.layers.attention_pool2d import ( + AttentionPool2d as AbsAttentionPool2d, + ) +except ImportError as e: + timm = None + +from .utils import freeze_batch_norm_2d + + +class TimmModel(nn.Module): + """timm model adapter + # FIXME this adapter is a work in progress, may change in ways that break weight compat + """ + + def __init__( + self, + model_name, + embed_dim, + image_size=224, + pool="avg", + proj="linear", + drop=0.0, + pretrained=False, + ): + super().__init__() + if timm is None: + raise RuntimeError("Please `pip install timm` to use timm models.") + + self.image_size = to_2tuple(image_size) + self.trunk = timm.create_model(model_name, pretrained=pretrained) + feat_size = self.trunk.default_cfg.get("pool_size", None) + feature_ndim = 1 if not feat_size else 2 + if pool in ("abs_attn", "rot_attn"): + assert feature_ndim == 2 + # if attn pooling used, remove both classifier and default pool + self.trunk.reset_classifier(0, global_pool="") + else: + # reset global pool if pool config set, otherwise leave as network default + reset_kwargs = dict(global_pool=pool) if pool else {} + self.trunk.reset_classifier(0, **reset_kwargs) + prev_chs = self.trunk.num_features + + head_layers = OrderedDict() + if pool == "abs_attn": + head_layers["pool"] = AbsAttentionPool2d( + prev_chs, feat_size=feat_size, out_features=embed_dim + ) + prev_chs = embed_dim + elif pool == "rot_attn": + head_layers["pool"] = RotAttentionPool2d(prev_chs, out_features=embed_dim) + prev_chs = embed_dim + else: + assert proj, "projection layer needed if non-attention pooling is used." + + # NOTE attention pool ends with a projection layer, so proj should usually be set to '' if such pooling is used + if proj == "linear": + head_layers["drop"] = nn.Dropout(drop) + head_layers["proj"] = nn.Linear(prev_chs, embed_dim) + elif proj == "mlp": + head_layers["mlp"] = Mlp(prev_chs, 2 * embed_dim, embed_dim, drop=drop) + + self.head = nn.Sequential(head_layers) + + def lock(self, unlocked_groups=0, freeze_bn_stats=False): + """lock modules + Args: + unlocked_groups (int): leave last n layer groups unlocked (default: 0) + """ + if not unlocked_groups: + # lock full model + for param in self.trunk.parameters(): + param.requires_grad = False + if freeze_bn_stats: + freeze_batch_norm_2d(self.trunk) + else: + # NOTE: partial freeze requires latest timm (master) branch and is subject to change + try: + # FIXME import here until API stable and in an official release + from timm.models.helpers import group_parameters, group_modules + except ImportError: + raise RuntimeError( + "Please install latest timm `pip install git+https://github.com/rwightman/pytorch-image-models`" + ) + matcher = self.trunk.group_matcher() + gparams = group_parameters(self.trunk, matcher) + max_layer_id = max(gparams.keys()) + max_layer_id = max_layer_id - unlocked_groups + for group_idx in range(max_layer_id + 1): + group = gparams[group_idx] + for param in group: + self.trunk.get_parameter(param).requires_grad = False + if freeze_bn_stats: + gmodules = group_modules(self.trunk, matcher, reverse=True) + gmodules = {k for k, v in gmodules.items() if v <= max_layer_id} + freeze_batch_norm_2d(self.trunk, gmodules) + + def forward(self, x): + x = self.trunk(x) + x = self.head(x) + return x diff --git a/src/audioldm/clap/open_clip/tokenizer.py b/src/audioldm/clap/open_clip/tokenizer.py new file mode 100644 index 0000000000000000000000000000000000000000..721820f656868dfe31551d972081069bbc8d2229 --- /dev/null +++ b/src/audioldm/clap/open_clip/tokenizer.py @@ -0,0 +1,197 @@ +""" CLIP tokenizer + +Copied from https://github.com/openai/CLIP. Originally MIT License, Copyright (c) 2021 OpenAI. +""" +import gzip +import html +import os +from functools import lru_cache +from typing import Union, List + +import ftfy +import regex as re +import torch + + +@lru_cache() +def default_bpe(): + return os.path.join( + os.path.dirname(os.path.abspath(__file__)), "bpe_simple_vocab_16e6.txt.gz" + ) + + +@lru_cache() +def bytes_to_unicode(): + """ + Returns list of utf-8 byte and a corresponding list of unicode strings. + The reversible bpe codes work on unicode strings. + This means you need a large # of unicode characters in your vocab if you want to avoid UNKs. + When you're at something like a 10B token dataset you end up needing around 5K for decent coverage. + This is a signficant percentage of your normal, say, 32K bpe vocab. + To avoid that, we want lookup tables between utf-8 bytes and unicode strings. + And avoids mapping to whitespace/control characters the bpe code barfs on. + """ + bs = ( + list(range(ord("!"), ord("~") + 1)) + + list(range(ord("¡"), ord("¬") + 1)) + + list(range(ord("®"), ord("ÿ") + 1)) + ) + cs = bs[:] + n = 0 + for b in range(2**8): + if b not in bs: + bs.append(b) + cs.append(2**8 + n) + n += 1 + cs = [chr(n) for n in cs] + return dict(zip(bs, cs)) + + +def get_pairs(word): + """Return set of symbol pairs in a word. + Word is represented as tuple of symbols (symbols being variable-length strings). + """ + pairs = set() + prev_char = word[0] + for char in word[1:]: + pairs.add((prev_char, char)) + prev_char = char + return pairs + + +def basic_clean(text): + text = ftfy.fix_text(text) + text = html.unescape(html.unescape(text)) + return text.strip() + + +def whitespace_clean(text): + text = re.sub(r"\s+", " ", text) + text = text.strip() + return text + + +class SimpleTokenizer(object): + def __init__(self, bpe_path: str = default_bpe(), special_tokens=None): + self.byte_encoder = bytes_to_unicode() + self.byte_decoder = {v: k for k, v in self.byte_encoder.items()} + merges = gzip.open(bpe_path).read().decode("utf-8").split("\n") + merges = merges[1 : 49152 - 256 - 2 + 1] + merges = [tuple(merge.split()) for merge in merges] + vocab = list(bytes_to_unicode().values()) + vocab = vocab + [v + "" for v in vocab] + for merge in merges: + vocab.append("".join(merge)) + if not special_tokens: + special_tokens = ["", ""] + else: + special_tokens = ["", ""] + special_tokens + vocab.extend(special_tokens) + self.encoder = dict(zip(vocab, range(len(vocab)))) + self.decoder = {v: k for k, v in self.encoder.items()} + self.bpe_ranks = dict(zip(merges, range(len(merges)))) + self.cache = {t: t for t in special_tokens} + special = "|".join(special_tokens) + self.pat = re.compile( + special + r"""|'s|'t|'re|'ve|'m|'ll|'d|[\p{L}]+|[\p{N}]|[^\s\p{L}\p{N}]+""", + re.IGNORECASE, + ) + + self.vocab_size = len(self.encoder) + self.all_special_ids = [self.encoder[t] for t in special_tokens] + + def bpe(self, token): + if token in self.cache: + return self.cache[token] + word = tuple(token[:-1]) + (token[-1] + "",) + pairs = get_pairs(word) + + if not pairs: + return token + "" + + while True: + bigram = min(pairs, key=lambda pair: self.bpe_ranks.get(pair, float("inf"))) + if bigram not in self.bpe_ranks: + break + first, second = bigram + new_word = [] + i = 0 + while i < len(word): + try: + j = word.index(first, i) + new_word.extend(word[i:j]) + i = j + except: + new_word.extend(word[i:]) + break + + if word[i] == first and i < len(word) - 1 and word[i + 1] == second: + new_word.append(first + second) + i += 2 + else: + new_word.append(word[i]) + i += 1 + new_word = tuple(new_word) + word = new_word + if len(word) == 1: + break + else: + pairs = get_pairs(word) + word = " ".join(word) + self.cache[token] = word + return word + + def encode(self, text): + bpe_tokens = [] + text = whitespace_clean(basic_clean(text)).lower() + for token in re.findall(self.pat, text): + token = "".join(self.byte_encoder[b] for b in token.encode("utf-8")) + bpe_tokens.extend( + self.encoder[bpe_token] for bpe_token in self.bpe(token).split(" ") + ) + return bpe_tokens + + def decode(self, tokens): + text = "".join([self.decoder[token] for token in tokens]) + text = ( + bytearray([self.byte_decoder[c] for c in text]) + .decode("utf-8", errors="replace") + .replace("", " ") + ) + return text + + +_tokenizer = SimpleTokenizer() + + +def tokenize( + texts: Union[str, List[str]], context_length: int = 77 +) -> torch.LongTensor: + """ + Returns the tokenized representation of given input string(s) + + Parameters + ---------- + texts : Union[str, List[str]] + An input string or a list of input strings to tokenize + context_length : int + The context length to use; all CLIP models use 77 as the context length + + Returns + ------- + A two-dimensional tensor containing the resulting tokens, shape = [number of input strings, context_length] + """ + if isinstance(texts, str): + texts = [texts] + + sot_token = _tokenizer.encoder[""] + eot_token = _tokenizer.encoder[""] + all_tokens = [[sot_token] + _tokenizer.encode(text) + [eot_token] for text in texts] + result = torch.zeros(len(all_tokens), context_length, dtype=torch.long) + + for i, tokens in enumerate(all_tokens): + if len(tokens) > context_length: + tokens = tokens[:context_length] # Truncate + result[i, : len(tokens)] = torch.tensor(tokens) + + return result diff --git a/src/audioldm/clap/open_clip/transform.py b/src/audioldm/clap/open_clip/transform.py new file mode 100644 index 0000000000000000000000000000000000000000..bc3bbac627e70e1dab2a05393f893d6165ae7b6b --- /dev/null +++ b/src/audioldm/clap/open_clip/transform.py @@ -0,0 +1,45 @@ +from torchvision.transforms import ( + Normalize, + Compose, + RandomResizedCrop, + InterpolationMode, + ToTensor, + Resize, + CenterCrop, +) + + +def _convert_to_rgb(image): + return image.convert("RGB") + + +def image_transform( + image_size: int, + is_train: bool, + mean=(0.48145466, 0.4578275, 0.40821073), + std=(0.26862954, 0.26130258, 0.27577711), +): + normalize = Normalize(mean=mean, std=std) + if is_train: + return Compose( + [ + RandomResizedCrop( + image_size, + scale=(0.9, 1.0), + interpolation=InterpolationMode.BICUBIC, + ), + _convert_to_rgb, + ToTensor(), + normalize, + ] + ) + else: + return Compose( + [ + Resize(image_size, interpolation=InterpolationMode.BICUBIC), + CenterCrop(image_size), + _convert_to_rgb, + ToTensor(), + normalize, + ] + ) diff --git a/src/audioldm/clap/open_clip/utils.py b/src/audioldm/clap/open_clip/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..bef8a52466263e981b0099e560ca1a1e6c9d61d2 --- /dev/null +++ b/src/audioldm/clap/open_clip/utils.py @@ -0,0 +1,362 @@ +import numpy as np +import torch +from torch import nn as nn +from torchvision.ops.misc import FrozenBatchNorm2d +import logging + +# import h5py +from tqdm import tqdm +import random +import json +import os +import pathlib + +# TODO: (yusong) this not a good place to store those information and does not scale. Need to be fixed later. +dataset_split = { + "audiocaps": ["train", "valid", "test"], + "audioset": ["balanced_train", "unbalanced_train", "eval"], + "BBCSoundEffects": ["train", "test"], + "Clotho": ["train", "test", "valid"], + "free_to_use_sounds": ["train", "test"], + "paramount_motion": ["train", "test"], + "sonniss_game_effects": ["train", "test"], + "wesoundeffects": ["train", "test"], + "MACS": ["train", "test"], + "freesound": ["train", "test"], + "FSD50K": ["train", "test", "valid"], + "fsd50k_class_label": ["train", "test", "valid"], + "esc50": ["train", "test"], + "audiostock": ["train", "test"], + "freesound_no_overlap_noesc50": ["train", "test"], + "epidemic_sound_effects": ["train", "test"], + "VGGSound": ["train", "test"], + "urbansound8k_class_label": ["train", "test"], + "audioset_t5": ["balanced_train", "unbalanced_train", "eval"], + "epidemic_sound_effects_t5": ["train", "test"], + "WavText5K": ["train", "test"], + "esc50_no_overlap": ["train", "test"], + "usd8k_no_overlap": ["train", "test"], + "fsd50k_200_class_label": ["train", "test", "valid"], +} + + +def freeze_batch_norm_2d(module, module_match={}, name=""): + """ + Converts all `BatchNorm2d` and `SyncBatchNorm` layers of provided module into `FrozenBatchNorm2d`. If `module` is + itself an instance of either `BatchNorm2d` or `SyncBatchNorm`, it is converted into `FrozenBatchNorm2d` and + returned. Otherwise, the module is walked recursively and submodules are converted in place. + + Args: + module (torch.nn.Module): Any PyTorch module. + module_match (dict): Dictionary of full module names to freeze (all if empty) + name (str): Full module name (prefix) + + Returns: + torch.nn.Module: Resulting module + + Inspired by https://github.com/pytorch/pytorch/blob/a5895f85be0f10212791145bfedc0261d364f103/torch/nn/modules/batchnorm.py#L762 + """ + res = module + is_match = True + if module_match: + is_match = name in module_match + if is_match and isinstance( + module, (nn.modules.batchnorm.BatchNorm2d, nn.modules.batchnorm.SyncBatchNorm) + ): + res = FrozenBatchNorm2d(module.num_features) + res.num_features = module.num_features + res.affine = module.affine + if module.affine: + res.weight.data = module.weight.data.clone().detach() + res.bias.data = module.bias.data.clone().detach() + res.running_mean.data = module.running_mean.data + res.running_var.data = module.running_var.data + res.eps = module.eps + else: + for child_name, child in module.named_children(): + full_child_name = ".".join([name, child_name]) if name else child_name + new_child = freeze_batch_norm_2d(child, module_match, full_child_name) + if new_child is not child: + res.add_module(child_name, new_child) + return res + + +def exist(dataset_name, dataset_type): + """ + Check if dataset exists + """ + if dataset_type in dataset_split[dataset_name]: + return True + else: + return False + + +def get_tar_path_from_dataset_name( + dataset_names, dataset_types, islocal, dataset_path, proportion=1, full_dataset=None +): + """ + Get tar path from dataset name and type + """ + output = [] + for n in dataset_names: + if full_dataset is not None and n in full_dataset: + current_dataset_types = dataset_split[n] + else: + current_dataset_types = dataset_types + for s in current_dataset_types: + tmp = [] + if islocal: + sizefilepath_ = f"{dataset_path}/{n}/{s}/sizes.json" + if not os.path.exists(sizefilepath_): + sizefilepath_ = f"./json_files/{n}/{s}/sizes.json" + else: + sizefilepath_ = f"./json_files/{n}/{s}/sizes.json" + if not os.path.exists(sizefilepath_): + continue + sizes = json.load(open(sizefilepath_, "r")) + for k in sizes.keys(): + if islocal: + tmp.append(f"{dataset_path}/{n}/{s}/{k}") + else: + tmp.append( + f"pipe:aws s3 --cli-connect-timeout 0 cp s3://s-laion-audio/webdataset_tar/{n}/{s}/{k} -" + ) + if proportion != 1: + tmp = random.sample(tmp, int(proportion * len(tmp))) + output.append(tmp) + return sum(output, []) + + +def get_tar_path_from_txts(txt_path, islocal, proportion=1): + """ + Get tar path from txt path + """ + if isinstance(txt_path, (list, tuple)): + return sum( + [ + get_tar_path_from_txts( + txt_path[i], islocal=islocal, proportion=proportion + ) + for i in range(len(txt_path)) + ], + [], + ) + if isinstance(txt_path, str): + with open(txt_path) as f: + lines = f.readlines() + if islocal: + lines = [ + lines[i] + .split("\n")[0] + .replace("pipe:aws s3 cp s3://s-laion-audio/", "/mnt/audio_clip/") + for i in range(len(lines)) + ] + else: + lines = [ + lines[i].split("\n")[0].replace(".tar", ".tar -") + for i in range(len(lines)) + ] + if proportion != 1: + print("Sampling tars with proportion of {}".format(proportion)) + lines = random.sample(lines, int(proportion * len(lines))) + return lines + + +def get_mix_lambda(mixup_alpha, batch_size): + mixup_lambdas = [ + np.random.beta(mixup_alpha, mixup_alpha, 1)[0] for _ in range(batch_size) + ] + return np.array(mixup_lambdas).astype(np.float32) + + +def do_mixup(x, mixup_lambda): + """ + Args: + x: (batch_size , ...) + mixup_lambda: (batch_size,) + Returns: + out: (batch_size, ...) + """ + out = ( + x.transpose(0, -1) * mixup_lambda + + torch.flip(x, dims=[0]).transpose(0, -1) * (1 - mixup_lambda) + ).transpose(0, -1) + return out + + +def interpolate(x, ratio): + """Interpolate data in time domain. This is used to compensate the + resolution reduction in downsampling of a CNN. + + Args: + x: (batch_size, time_steps, classes_num) + ratio: int, ratio to interpolate + Returns: + upsampled: (batch_size, time_steps * ratio, classes_num) + """ + (batch_size, time_steps, classes_num) = x.shape + upsampled = x[:, :, None, :].repeat(1, 1, ratio, 1) + upsampled = upsampled.reshape(batch_size, time_steps * ratio, classes_num) + return upsampled + + +def pad_framewise_output(framewise_output, frames_num): + """Pad framewise_output to the same length as input frames. The pad value + is the same as the value of the last frame. + Args: + framewise_output: (batch_size, frames_num, classes_num) + frames_num: int, number of frames to pad + Outputs: + output: (batch_size, frames_num, classes_num) + """ + pad = framewise_output[:, -1:, :].repeat( + 1, frames_num - framewise_output.shape[1], 1 + ) + """tensor for padding""" + + output = torch.cat((framewise_output, pad), dim=1) + """(batch_size, frames_num, classes_num)""" + + +# def process_ipc(index_path, classes_num, filename): +# # load data +# logging.info("Load Data...............") +# ipc = [[] for _ in range(classes_num)] +# with h5py.File(index_path, "r") as f: +# for i in tqdm(range(len(f["target"]))): +# t_class = np.where(f["target"][i])[0] +# for t in t_class: +# ipc[t].append(i) +# print(ipc) +# np.save(filename, ipc) +# logging.info("Load Data Succeed...............") + + +def save_to_dict(s, o_={}): + sp = s.split(": ") + o_.update({sp[0]: float(sp[1])}) + return o_ + + +def get_data_from_log(txt_path): + """ + Output dictionary from out.txt log file + """ + with open(txt_path) as f: + lines = f.readlines() + val_data = {} + train_data = {} + train_losses = [] + train_losses_epoch = [] + for i in range(len(lines)): + if "| INFO |" in lines[i]: + if "Eval Epoch" in lines[i]: + if "val_loss" in lines[i]: + # float(regex.sub("", lines[310].split(" ")[-1]).replace(" ", "")) + line = lines[i].split("Eval Epoch: ")[-1] + num_epoch = int(line.split(" ")[0].split(" ")[0]) + d = { + line.split(" ")[0] + .split(" ")[1] + .replace(":", ""): float(line.split(" ")[0].split(" ")[-1]) + } + for i in range(1, len(line.split(" "))): + d = save_to_dict(line.split(" ")[i], d) + val_data[num_epoch] = d + elif "Train Epoch" in lines[i]: + num_epoch = int(lines[i].split("Train Epoch: ")[1][0]) + loss = float(lines[i].split("Loss: ")[-1].split(" (")[0]) + train_losses.append(loss) + train_losses_epoch.append(num_epoch) + for i in range(len(train_losses)): + train_data[i] = { + "num_epoch": train_losses_epoch[i], + "train_loss": train_losses[i], + } + return train_data, val_data + + +def save_p(obj, filename): + import pickle + + try: + from deepdiff import DeepDiff + except: + os.system("pip install deepdiff") + from deepdiff import DeepDiff + with open(filename, "wb") as file: + pickle.dump(obj, file, protocol=pickle.HIGHEST_PROTOCOL) # highest protocol + with open(filename, "rb") as file: + z = pickle.load(file) + assert ( + DeepDiff(obj, z, ignore_string_case=True) == {} + ), "there is something wrong with the saving process" + return + + +def load_p(filename): + import pickle + + with open(filename, "rb") as file: + z = pickle.load(file) + return z + + +def save_json(data, name="data.json"): + import json + + with open(name, "w") as fp: + json.dump(data, fp) + return + + +def load_json(name): + import json + + with open(name, "r") as fp: + data = json.load(fp) + return data + + +from multiprocessing import Process, Manager +from multiprocessing import Process, Value, Array +from ctypes import c_wchar + + +def load_class_label(path): + # https://stackoverflow.com/questions/48004243/how-to-share-large-read-only-dictionary-list-across-processes-in-multiprocessing + # https://stackoverflow.com/questions/45693949/storing-strings-in-a-multiprocessing-sharedctypes-array + out = None + if path is not None: + if pathlib.Path(path).suffix in [".pkl", ".pickle"]: + out = load_p(path) + elif pathlib.Path(path).suffix in [".json", ".txt"]: + out = load_json(path) + elif pathlib.Path(path).suffix in [".npy", ".npz"]: + out = np.load(path) + elif pathlib.Path(path).suffix in [".csv"]: + import pandas as pd + + out = pd.read_csv(path) + return out + # if out is None: + # return None + # else: + # key = Array(c_wchar, '\n'.join(list(out.keys())), lock=False) + # val = Array('i', out.values(), lock=False) + # return (key, val) + + +from torch import optim + + +def get_optimizer(params, lr, betas, eps, momentum, optimizer_name): + if optimizer_name.lower() == "adamw": + optimizer = optim.AdamW(params, lr=lr, betas=betas, eps=eps) + elif optimizer_name.lower() == "sgd": + optimizer = optim.SGD(params, lr=lr, momentum=momentum) + elif optimizer_name.lower() == "adam": + optimizer = optim.Adam(params, lr=lr, betas=betas, eps=eps) + else: + raise ValueError("optimizer name is not correct") + return optimizer diff --git a/src/audioldm/clap/open_clip/version.py b/src/audioldm/clap/open_clip/version.py new file mode 100644 index 0000000000000000000000000000000000000000..c19de657bdbd6b7b4a2c091b447aac7e97c7afed --- /dev/null +++ b/src/audioldm/clap/open_clip/version.py @@ -0,0 +1 @@ +__version__ = "0.2.1" diff --git a/src/audioldm/clap/training/__init__.py b/src/audioldm/clap/training/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/src/audioldm/clap/training/audioset_textmap.npy b/src/audioldm/clap/training/audioset_textmap.npy new file mode 100644 index 0000000000000000000000000000000000000000..3da4c92d3819aaec11e5f576464a9973a6df811b --- /dev/null +++ b/src/audioldm/clap/training/audioset_textmap.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bada103070d92f9eadd33e1b4f45ec8583f59080ef218c966b43294bd4c86d5b +size 84448 diff --git a/src/audioldm/clap/training/data.py b/src/audioldm/clap/training/data.py new file mode 100644 index 0000000000000000000000000000000000000000..185bc9dd0d2454547813bb6ca158c56a6c92b87b --- /dev/null +++ b/src/audioldm/clap/training/data.py @@ -0,0 +1,981 @@ +import ast +import json +import logging +import math +import os +import random + +# import h5py +from dataclasses import dataclass +from audioldm.clap.training.params import parse_args + +# import braceexpand +import numpy as np +import pandas as pd +import torch +import torch.nn as nn +import torch.nn.functional as F +import torchvision.datasets as datasets +import torchvision.transforms + +# import webdataset as wds +from PIL import Image +from torch.utils.data import Dataset, DataLoader, SubsetRandomSampler +from torch.utils.data.distributed import DistributedSampler +from functools import partial +import soundfile as sf +import io +from pathlib import Path + +# import wget + +from audioldm.clap.open_clip.utils import ( + get_tar_path_from_dataset_name, + dataset_split, +) +from audioldm.clap.open_clip.utils import load_p, load_class_label +import copy + +try: + import horovod.torch as hvd +except ImportError: + hvd = None + +try: + import torchaudio +except ImportError: + torchaudio = None + +from audioldm.clap.open_clip import tokenize + + +def tokenizer(text): + return tokenize(text).squeeze(0) + + +from transformers import RobertaTokenizer + +tokenize = RobertaTokenizer.from_pretrained("roberta-base") + + +def tokenizer(text): + result = tokenize( + text, + padding="max_length", + truncation=True, + max_length=77, + return_tensors="pt", + ) + return {k: v.squeeze(0) for k, v in result.items()} + + +# initizlied the audioset map +_AUDIOSET_MAP_PATH = os.path.join(Path(__file__).parent, "audioset_textmap.npy") +_AUDIOSET_MAP = np.load(_AUDIOSET_MAP_PATH, allow_pickle=True) + + +def int16_to_float32(x): + return (x / 32767.0).astype(np.float32) + + +def float32_to_int16(x): + x = np.clip(x, a_min=-1.0, a_max=1.0) + return (x * 32767.0).astype(np.int16) + + +# For Toy Dataset +# class ToyDataset(Dataset): +# def __init__(self, index_path, ipc, config, eval_mode=False): +# """Toy Dataset for testing the audioset input with text labels +# Parameters +# ---------- +# index_path: str +# the link to the h5 file of each audio +# idc: str +# the link to the npy file, the number of samples in each class +# config: dict +# the audio cfg file +# eval_model (bool): to indicate if the dataset is a testing dataset +# """ +# self.audio_cfg = config["audio_cfg"] +# self.text_cfg = config["text_cfg"] +# self.fp = h5py.File(index_path, "r") +# self.ipc = np.load(ipc, allow_pickle=True) +# self.total_size = len(self.fp["audio_name"]) +# self.classes_num = self.audio_cfg["class_num"] +# self.eval_mode = eval_mode + +# if not eval_mode: +# self.generate_queue() +# else: +# self.queue = [] +# for i in range(self.total_size): +# target = self.fp["target"][i] +# if np.sum(target) > 0: +# self.queue.append(i) +# self.total_size = len(self.queue) +# logging.info("total dataset size: %d" % (self.total_size)) +# logging.info("class num: %d" % (self.classes_num)) + +# def time_shifting(self, x): +# frame_num = len(x) +# shift_len = random.randint(0, frame_num - 1) +# new_sample = np.concatenate([x[shift_len:], x[:shift_len]], axis=0) +# return new_sample + +# def generate_queue(self): +# self.queue = [] +# while len(self.queue) < self.total_size: +# class_set = [*range(self.classes_num)] +# random.shuffle(class_set) +# self.queue += [ +# self.ipc[d][random.randint(0, len(self.ipc[d]) - 1)] for d in class_set +# ] +# self.queue = self.queue[: self.total_size] + +# logging.info("queue regenerated:%s" % (self.queue[-5:])) + +# def crop_wav(self, x): +# crop_size = self.audio_cfg["crop_size"] +# crop_pos = random.randint(0, len(x) - crop_size - 1) +# return x[crop_pos : crop_pos + crop_size] + +# def prompt_text(self, target): +# events = _AUDIOSET_MAP[np.where(target > 0)] +# event_text = "The sounds of " + ", ".join(events[:-1]) + " and " + events[-1] +# text = tokenize(event_text)[0] +# return text + +# def __getitem__(self, index): +# """Load waveform, text, and target of an audio clip + +# Parameters +# ---------- +# index: int +# the index number +# Return +# ------ +# output: dict { +# "hdf5_path": str, +# "index_in_hdf5": int, +# "audio_name": str, +# "waveform": list (audio_length,), +# "target": list (class_num, ), +# "text": torch.tensor (context_length,) +# } +# the output dictionary +# """ +# s_index = self.queue[index] + +# audio_name = self.fp["audio_name"][s_index].decode() +# # Hardcode here CHANGE +# hdf5_path = ( +# self.fp["hdf5_path"][s_index] +# .decode() +# .replace( +# "../workspace", +# "/home/la/kechen/Research/ke_zsasp/workspace", +# ) +# ) +# r_idx = self.fp["index_in_hdf5"][s_index] +# target = self.fp["target"][s_index].astype(np.float32) +# text = self.prompt_text(target) +# with h5py.File(hdf5_path, "r") as f: +# waveform = int16_to_float32(f["waveform"][r_idx])[ +# : self.audio_cfg["clip_samples"] +# ] +# assert ( +# len(waveform) == self.audio_cfg["clip_samples"] +# ), "The sample length is not match" +# # Time shift +# # if (self.config.enable_time_shift) and (not self.eval_mode): +# # waveform = self.time_shifting(waveform) +# # # Label Enhance +# # if (self.config.crop_size is not None) and (not self.eval_mode): +# # waveform = self.crop_wav(waveform) +# # # the label enhance rate is fixed 0.5 +# # if (self.config.enable_label_enhance) and (not self.eval_mode) and random.random() < 0.5: +# # kidx = np.where(target)[0] +# # for k in kidx: +# # for add_key in self.class_map[k][1]: +# # target[add_key] = 1.0 +# # if len(self.class_map[k][2]) > 0: +# # add_key = random.choice(self.class_map[k][2]) +# # target[add_key] = 1.0 + +# # missing the text input +# mel_spec = get_mel(torch.from_numpy(waveform), self.audio_cfg)[None, :, :] +# mel_spec = ( +# torch.cat( +# [mel_spec, mel_spec.clone(), mel_spec.clone(), mel_spec.clone()], dim=0 +# ) +# .cpu() +# .numpy() +# ) +# longer = random.choice([True, False]) +# if longer == False: +# mel_spec[1:, :, :] = 0.0 +# data_dict = { +# "hdf5_path": hdf5_path, +# "index_in_hdf5": r_idx, +# "audio_name": audio_name, +# "waveform": waveform, +# "class_label": target, +# "text": text, +# "longer": longer, +# "mel_fusion": mel_spec, +# } +# return data_dict + +# def __len__(self): +# return self.total_size + + +class CsvDataset(Dataset): + def __init__(self, input_filename, transforms, img_key, caption_key, sep="\t"): + logging.debug(f"Loading csv data from {input_filename}.") + df = pd.read_csv(input_filename, sep=sep) + + self.images = df[img_key].tolist() + self.captions = df[caption_key].tolist() + self.transforms = transforms + logging.debug("Done loading data.") + + def __len__(self): + return len(self.captions) + + def __getitem__(self, idx): + images = self.transforms(Image.open(str(self.images[idx]))) + texts = tokenize([str(self.captions[idx])])[0] + return images, texts + + +@dataclass +class DataInfo: + dataloader: DataLoader + sampler: DistributedSampler + + +def preprocess_txt(text): + return tokenize([str(text)])[0] + + +def get_dataset_size(shards, sizefilepath_=None, is_local=True): + if isinstance(shards, list): + size_list = [] + for s in shards: + size_list.append( + get_dataset_size(s, sizefilepath_=sizefilepath_, is_local=is_local)[0] + ) + else: + if not is_local: + for n in dataset_split.keys(): + if n in shards.split("/"): + break + for s in dataset_split[n]: + if s in shards.split("/"): + break + sizefilepath_ = f"./json_files/{n}/{s}/sizes.json" + shards_list = list(braceexpand.braceexpand(shards)) + dir_path = os.path.dirname(shards) + if sizefilepath_ is not None: + sizes = json.load(open(sizefilepath_, "r")) + total_size = sum( + [ + int(sizes[os.path.basename(shard.replace(".tar -", ".tar"))]) + for shard in shards_list + ] + ) + else: + sizes_filename = os.path.join(dir_path, "sizes.json") + len_filename = os.path.join(dir_path, "__len__") + if os.path.exists(sizes_filename): + sizes = json.load(open(sizes_filename, "r")) + total_size = sum( + [int(sizes[os.path.basename(shard)]) for shard in shards_list] + ) + elif os.path.exists(len_filename): + # FIXME this used to be eval(open(...)) but that seemed rather unsafe + total_size = ast.literal_eval(open(len_filename, "r").read()) + else: + raise Exception( + "Cannot find sizes file for dataset. Please specify the path to the file." + ) + # total_size = None # num samples undefined + # some common dataset sizes (at time of authors last download) + # cc3m-train: 2905954 + # cc12m: 10968539 + # LAION-400m: 407332084 + num_shards = len(shards_list) + if isinstance(shards, list): + return sum(size_list), len(shards) + else: + return total_size, num_shards + + +def get_imagenet(args, preprocess_fns, split): + assert split in ["train", "val", "v2"] + is_train = split == "train" + preprocess_train, preprocess_val = preprocess_fns + + if split == "v2": + from imagenetv2_pytorch import ImageNetV2Dataset + + dataset = ImageNetV2Dataset(location=args.imagenet_v2, transform=preprocess_val) + else: + if is_train: + data_path = args.imagenet_train + preprocess_fn = preprocess_train + else: + data_path = args.imagenet_val + preprocess_fn = preprocess_val + assert data_path + + dataset = datasets.ImageFolder(data_path, transform=preprocess_fn) + + if is_train: + idxs = np.zeros(len(dataset.targets)) + target_array = np.array(dataset.targets) + k = 50 + for c in range(1000): + m = target_array == c + n = len(idxs[m]) + arr = np.zeros(n) + arr[:k] = 1 + np.random.shuffle(arr) + idxs[m] = arr + + idxs = idxs.astype("int") + sampler = SubsetRandomSampler(np.where(idxs)[0]) + else: + sampler = None + + dataloader = torch.utils.data.DataLoader( + dataset, + batch_size=args.batch_size, + num_workers=args.workers, + sampler=sampler, + ) + + return DataInfo(dataloader, sampler) + + +def count_samples(dataloader): + os.environ["WDS_EPOCH"] = "0" + n_elements, n_batches = 0, 0 + for images, texts in dataloader: + n_batches += 1 + n_elements += len(images) + assert len(images) == len(texts) + return n_elements, n_batches + + +def filter_no_caption(sample): + return "txt" in sample + + +def log_and_continue(exn): + """Call in an exception handler to ignore any exception, isssue a warning, and continue.""" + logging.warning(f"Handling webdataset error ({repr(exn)}). Ignoring.") + return True + + +_SHARD_SHUFFLE_SIZE = 2000 +_SHARD_SHUFFLE_INITIAL = 500 +_SAMPLE_SHUFFLE_SIZE = 5000 +_SAMPLE_SHUFFLE_INITIAL = 1000 + + +def sample_prop(sizefile, inputs, proportion, is_local=True): + """ + Sample a proportion of the data. + """ + file_path_dict = { + os.path.split(inputs[i])[1]: os.path.split(inputs[i])[0] + for i in range(len(inputs)) + } + sampled_filepath_dict = {} + sampled_size_dict = {} + if not is_local: + if os.path.exists("sizes.json"): + os.remove("sizes.json") + wget.download(sizefile, "sizes.json") + sizefile = "sizes.json" + with open(sizefile, "r", encoding="UTF-8") as f: + load_dict = json.load(f) + L = int(len(file_path_dict) * proportion) + subkeys = random.sample(file_path_dict.keys(), L) + for k in subkeys: + sampled_size_dict[k] = load_dict[k] + sampled_filepath_dict[k] = file_path_dict[k] + return ( + sum(sampled_size_dict.values()), + L, + [os.path.join(v, k) for k, v in sampled_filepath_dict.items()], + sampled_size_dict, + ) + + +def get_mel(audio_data, audio_cfg): + # mel shape: (n_mels, T) + mel = torchaudio.transforms.MelSpectrogram( + sample_rate=audio_cfg["sample_rate"], + n_fft=audio_cfg["window_size"], + win_length=audio_cfg["window_size"], + hop_length=audio_cfg["hop_size"], + center=True, + pad_mode="reflect", + power=2.0, + norm=None, + onesided=True, + n_mels=64, + f_min=audio_cfg["fmin"], + f_max=audio_cfg["fmax"], + ).to(audio_data.device) + mel = mel(audio_data) + # Align to librosa: + # librosa_melspec = librosa.feature.melspectrogram( + # waveform, + # sr=audio_cfg['sample_rate'], + # n_fft=audio_cfg['window_size'], + # hop_length=audio_cfg['hop_size'], + # win_length=audio_cfg['window_size'], + # center=True, + # pad_mode="reflect", + # power=2.0, + # n_mels=64, + # norm=None, + # htk=True, + # f_min=audio_cfg['fmin'], + # f_max=audio_cfg['fmax'] + # ) + # we use log mel spectrogram as input + mel = torchaudio.transforms.AmplitudeToDB(top_db=None)(mel) + return mel.T # (T, n_mels) + + +def get_audio_features( + sample, audio_data, max_len, data_truncating, data_filling, audio_cfg +): + """ + Calculate and add audio features to sample. + Sample: a dict containing all the data of current sample. + audio_data: a tensor of shape (T) containing audio data. + max_len: the maximum length of audio data. + data_truncating: the method of truncating data. + data_filling: the method of filling data. + audio_cfg: a dict containing audio configuration. Comes from model_cfg['audio_cfg']. + """ + with torch.no_grad(): + if len(audio_data) > max_len: + if data_truncating == "rand_trunc": + longer = torch.tensor([True]) + elif data_truncating == "fusion": + # fusion + mel = get_mel(audio_data, audio_cfg) + # split to three parts + chunk_frames = ( + max_len // audio_cfg["hop_size"] + 1 + ) # the +1 related to how the spectrogram is computed + total_frames = mel.shape[0] + if chunk_frames == total_frames: + # there is a corner case where the audio length is + # larger than max_len but smaller than max_len+hop_size. + # In this case, we just use the whole audio. + mel_fusion = torch.stack([mel, mel, mel, mel], dim=0) + sample["mel_fusion"] = mel_fusion + longer = torch.tensor([False]) + else: + ranges = np.array_split( + list(range(0, total_frames - chunk_frames + 1)), 3 + ) + # print('total_frames-chunk_frames:', total_frames-chunk_frames, + # 'len(audio_data):', len(audio_data), + # 'chunk_frames:', chunk_frames, + # 'total_frames:', total_frames) + if len(ranges[1]) == 0: + # if the audio is too short, we just use the first chunk + ranges[1] = [0] + if len(ranges[2]) == 0: + # if the audio is too short, we just use the first chunk + ranges[2] = [0] + # randomly choose index for each part + idx_front = np.random.choice(ranges[0]) + idx_middle = np.random.choice(ranges[1]) + idx_back = np.random.choice(ranges[2]) + # select mel + mel_chunk_front = mel[idx_front : idx_front + chunk_frames, :] + mel_chunk_middle = mel[idx_middle : idx_middle + chunk_frames, :] + mel_chunk_back = mel[idx_back : idx_back + chunk_frames, :] + + # shrink the mel + mel_shrink = torchvision.transforms.Resize(size=[chunk_frames, 64])( + mel[None] + )[0] + # logging.info(f"mel_shrink.shape: {mel_shrink.shape}") + + # stack + mel_fusion = torch.stack( + [mel_chunk_front, mel_chunk_middle, mel_chunk_back, mel_shrink], + dim=0, + ) + sample["mel_fusion"] = mel_fusion + longer = torch.tensor([True]) + else: + raise NotImplementedError( + f"data_truncating {data_truncating} not implemented" + ) + # random crop to max_len (for compatibility) + overflow = len(audio_data) - max_len + idx = np.random.randint(0, overflow + 1) + audio_data = audio_data[idx : idx + max_len] + + else: # padding if too short + if len(audio_data) < max_len: # do nothing if equal + if data_filling == "repeatpad": + n_repeat = int(max_len / len(audio_data)) + audio_data = audio_data.repeat(n_repeat) + # audio_data = audio_data.unsqueeze(0).unsqueeze(0).unsqueeze(0) + # audio_data = F.interpolate(audio_data,size=max_len,mode="bicubic")[0,0,0] + audio_data = F.pad( + audio_data, + (0, max_len - len(audio_data)), + mode="constant", + value=0, + ) + elif data_filling == "pad": + audio_data = F.pad( + audio_data, + (0, max_len - len(audio_data)), + mode="constant", + value=0, + ) + elif data_filling == "repeat": + n_repeat = int(max_len / len(audio_data)) + audio_data = audio_data.repeat(n_repeat + 1)[:max_len] + else: + raise NotImplementedError( + f"data_filling {data_filling} not implemented" + ) + if data_truncating == "fusion": + mel = get_mel(audio_data, audio_cfg) + mel_fusion = torch.stack([mel, mel, mel, mel], dim=0) + sample["mel_fusion"] = mel_fusion + longer = torch.tensor([False]) + + sample["longer"] = longer + sample["waveform"] = audio_data + + return sample + + +def preprocess( + sample, + audio_ext, + text_ext, + max_len, + audio_cfg, + class_index_dict=None, + data_filling="pad", + data_truncating="rand_trunc", + text_augment_selection=None, +): + """ + Preprocess a single sample for wdsdataloader. + """ + audio_data, orig_sr = sf.read(io.BytesIO(sample[audio_ext])) + audio_data = int16_to_float32(float32_to_int16(audio_data)) + audio_data = torch.tensor(audio_data).float() + + # TODO: (yusong) to be include in the future + # # if torchaudio not installed, use soundfile to load audio + # if torchaudio is None: + # audio_data, orig_sr = sf.read(io.BytesIO(sample[audio_ext])) + # audio_data = torch.tensor(audio_data).float() + # else: + # # https://github.com/webdataset/webdataset/blob/main/webdataset/autodecode.py + # with tempfile.TemporaryDirectory() as dirname: + # os.makedirs(dirname, exist_ok=True) + # fname = os.path.join(dirname, f"file.flac") + # with open(fname, "wb") as stream: + # stream.write(sample[audio_ext]) + # audio_data, orig_sr = torchaudio.load(fname) + # audio_data = audio_data[0, :].float() + + sample = get_audio_features( + sample, audio_data, max_len, data_truncating, data_filling, audio_cfg + ) + del sample[audio_ext] + + try: + json_dict_raw = json.loads(sample[text_ext].decode("utf-8")) + except: + print("sample[__url__]:", sample["__url__"]) + + # For selecting augmented text from dataset + if text_augment_selection is None or text_augment_selection == "none": + texts = json_dict_raw["text"] + elif text_augment_selection == "all": + if "text_augment_all" in json_dict_raw.keys(): + texts = json_dict_raw["text_augment_all"] + else: + texts = json_dict_raw["text"] + elif text_augment_selection == "augment_only": + if "text_augment_all" in json_dict_raw.keys(): + if json_dict_raw["text_augment_t5"] is None: + texts = json_dict_raw["text"] + else: + texts = json_dict_raw["text_augment_t5"] + else: + texts = json_dict_raw["text"] + else: + raise NotImplementedError( + f"text_augment_selection {text_augment_selection} not implemented" + ) + sample["full_text"] = texts + + if isinstance(texts, list) and isinstance(texts[0], str) and len(texts) > 1: + texts = random.choice(texts) + sample["raw_text"] = texts + sample["text"] = tokenizer(texts) # text shape: [num_token] + if class_index_dict is not None: + # https://stackoverflow.com/questions/48004243/how-to-share-large-read-only-dictionary-list-across-processes-in-multiprocessing + # https://stackoverflow.com/questions/45693949/storing-strings-in-a-multiprocessing-sharedctypes-array + # key, val = class_index_dict + # key = key[:].split('\n') + # _dict = {k: v for k, v in zip(key, val)} + sample["class_label"] = np.zeros(len(class_index_dict.keys())) + for x in json_dict_raw["tag"]: + sample["class_label"][class_index_dict[x]] = 1 + sample["class_label"] = torch.tensor(sample["class_label"]).float() + del sample[text_ext] + sample["audio_name"] = sample["__key__"].split("/")[-1] + "." + audio_ext + sample["text_name"] = sample["__key__"].split("/")[-1] + "." + text_ext + sample["audio_orig_sr"] = orig_sr + return sample + + +def collate_fn(batch): + """ + Collate function for wdsdataloader. + batch: a list of dict, each dict is a sample + """ + # concatenate values in each dictionary. if it is a tensor, concatenate. if it is a list, extend. + batch_dict = {} + for k in batch[0].keys(): + if isinstance(batch[0][k], dict): # dealwith bert tokenizer output + batch_dict[k] = {} + for kk in batch[0][k].keys(): + tmp = [] + for i in range(len(batch)): + tmp.append(batch[i][k][kk]) + batch_dict[k][kk] = torch.vstack(tmp) + elif isinstance(batch[0][k], torch.Tensor): + batch_dict[k] = torch.stack([sample[k] for sample in batch]) + elif isinstance(batch[0][k], np.ndarray): + batch_dict[k] = torch.tensor(np.stack([sample[k] for sample in batch])) + else: + batch_dict[k] = [sample[k] for sample in batch] + return batch_dict + + +def get_wds_dataset( + args, + model_cfg, + is_train, + audio_ext="flac", + text_ext="json", + max_len=480000, + proportion=1.0, + sizefilepath_=None, + is_local=None, +): + """ + Get a dataset for wdsdataloader. + """ + if is_local is None and (not args.remotedata is None): + is_local = not args.remotedata + + input_shards = args.train_data if is_train else args.val_data + assert input_shards is not None + + if not sizefilepath_ is None: + sizefilepath = sizefilepath_ + else: + sizefilepath = os.path.join(os.path.dirname(input_shards[0]), "sizes.json") + + if proportion != 1.0: + num_samples, num_shards, input_shards, _ = sample_prop( + sizefilepath, input_shards, proportion, is_local=is_local + ) + else: + num_samples, num_shards = get_dataset_size( + input_shards, sizefilepath_=sizefilepath_, is_local=is_local + ) + + if not num_samples: + if is_train: + num_samples = args.train_num_samples + if not num_samples: + raise RuntimeError( + "Currently, number of dataset samples must be specified for training dataset. " + "Please specify via `--train-num-samples` if no dataset length info present." + ) + else: + num_samples = ( + args.val_num_samples or 0 + ) # eval will just exhaust the iterator if not specified + + pipeline = [wds.SimpleShardList(input_shards)] + # at this point we have an iterator over all the shards + # TODO: (yusong): add a if statement of distributed. If not, we don't need to split_by_node + if is_train or args.parallel_eval: + pipeline.extend( + [ + wds.detshuffle( + bufsize=_SHARD_SHUFFLE_SIZE, + initial=_SHARD_SHUFFLE_INITIAL, + seed=args.seed, + ), + wds.split_by_node, + wds.split_by_worker, + # at this point, we have an iterator over the shards assigned to each worker at each node + wds.tarfile_to_samples(handler=log_and_continue), + wds.shuffle( + bufsize=_SAMPLE_SHUFFLE_SIZE, + initial=_SAMPLE_SHUFFLE_INITIAL, + rng=random.Random(args.seed), + ), + # wds.repeatedly, # FIXME determine if this is beneficial + ] + ) + else: + pipeline.extend( + [ + wds.split_by_worker, + # at this point, we have an iterator over the shards assigned to each worker + wds.tarfile_to_samples(handler=log_and_continue), + ] + ) + pipeline.append( + wds.map( + partial( + preprocess, + audio_ext=audio_ext, + text_ext=text_ext, + max_len=max_len, + audio_cfg=model_cfg["audio_cfg"], + class_index_dict=copy.deepcopy(args.class_index_dict), + data_filling=args.data_filling, + data_truncating=args.data_truncating, + text_augment_selection=args.text_augment_selection, + ) + ), + ) + + pipeline.append( + wds.batched( + args.batch_size, + partial=not (is_train or args.parallel_eval), + collation_fn=collate_fn, + ) + ) + + dataset = wds.DataPipeline(*pipeline) + if is_train or args.parallel_eval: + # (yusong): Currently parallel evaluation will be not precise as we are repeat the last few samples. + # (yusong): See comments below. + # roll over and repeat a few samples to get same number of full batches on each node + global_batch_size = args.batch_size * args.world_size + num_batches = math.ceil(num_samples / global_batch_size) + num_workers = max(1, args.workers) + num_worker_batches = math.ceil( + num_batches / num_workers + ) # per dataloader worker + num_batches = num_worker_batches * num_workers + num_samples = num_batches * global_batch_size + dataset = dataset.with_epoch( + num_worker_batches + ) # each worker is iterating over this + else: + # last batches are partial, eval is done on single (master) node + num_batches = math.ceil(num_samples / args.batch_size) + + kwargs = {} + if args.horovod: # multi-node training on summit + kwargs["multiprocessing_context"] = "forkserver" + + dataloader = wds.WebLoader( + dataset, batch_size=None, shuffle=False, num_workers=args.workers, **kwargs + ) + + # FIXME not clear which approach is better, with_epoch before vs after dataloader? + # hoping to resolve via https://github.com/webdataset/webdataset/issues/169 + # if is_train: + # # roll over and repeat a few samples to get same number of full batches on each node + # global_batch_size = args.batch_size * args.world_size + # num_batches = math.ceil(num_samples / global_batch_size) + # num_workers = max(1, args.workers) + # num_batches = math.ceil(num_batches / num_workers) * num_workers + # num_samples = num_batches * global_batch_size + # dataloader = dataloader.with_epoch(num_batches) + # else: + # # last batches are partial, eval is done on single (master) node + # num_batches = math.ceil(num_samples / args.batch_size) + + # add meta-data to dataloader instance for convenience + dataloader.num_batches = num_batches + dataloader.num_samples = num_samples + + return DataInfo(dataloader, None) + + +def wds_batch_list2dict( + batch, + keys=[ + "__url__", + "__key__", + "waveform", + "text", + "raw_text", + "audio_name", + "text_name", + "audio_orig_sr", + ], +): + """ + Return a dictionary of the batch, with keys as the names of the fields. + """ + assert len(keys) == len( + batch + ), "batch must have same number of keys as keys argument" + return {keys[i]: batch[i] for i in range(len(batch))} + + +def get_csv_dataset(args, preprocess_fn, is_train): + input_filename = args.train_data if is_train else args.val_data + assert input_filename + dataset = CsvDataset( + input_filename, + preprocess_fn, + img_key=args.csv_img_key, + caption_key=args.csv_caption_key, + sep=args.csv_separator, + ) + num_samples = len(dataset) + sampler = DistributedSampler(dataset) if args.distributed and is_train else None + shuffle = is_train and sampler is None + + dataloader = DataLoader( + dataset, + batch_size=args.batch_size, + shuffle=shuffle, + num_workers=args.workers, + pin_memory=True, + sampler=sampler, + drop_last=is_train, + ) + dataloader.num_samples = num_samples + dataloader.num_batches = len(dataloader) + + return DataInfo(dataloader, sampler) + + +def get_toy_dataset(args, model_cfg, is_train): + index_path = args.train_data if is_train else args.val_data + ipc_path = args.train_ipc if is_train else args.val_ipc + assert index_path and ipc_path + eval_mode = not is_train + dataset = ToyDataset(index_path, ipc_path, model_cfg, eval_mode=eval_mode) + + num_samples = len(dataset) + sampler = ( + DistributedSampler(dataset, shuffle=False) + if args.distributed and is_train + else None + ) + + dataloader = DataLoader( + dataset, + batch_size=args.batch_size, + shuffle=False, + num_workers=args.workers, + sampler=sampler, + drop_last=is_train, + ) + dataloader.num_samples = num_samples + dataloader.num_batches = len(dataloader) + + return DataInfo(dataloader, sampler) + + +def get_dataset_fn(data_path, dataset_type): + if dataset_type == "webdataset": + return get_wds_dataset + elif dataset_type == "csv": + return get_csv_dataset + elif dataset_type == "auto": + ext = data_path.split(".")[-1] + if ext in ["csv", "tsv"]: + return get_csv_dataset + elif ext in ["tar"]: + return get_wds_dataset + else: + raise ValueError( + f"Tried to figure out dataset type, but failed for extention {ext}." + ) + elif dataset_type == "toy": + return get_toy_dataset + else: + raise ValueError(f"Unsupported dataset type: {dataset_type}") + + +def get_data(args, model_cfg): + data = {} + + args.class_index_dict = load_class_label(args.class_label_path) + + if args.datasetinfos is None: + args.datasetinfos = ["train", "unbalanced_train", "balanced_train"] + if args.dataset_type == "webdataset": + args.train_data = get_tar_path_from_dataset_name( + args.datasetnames, + args.datasetinfos, + islocal=not args.remotedata, + proportion=args.dataset_proportion, + dataset_path=args.datasetpath, + full_dataset=args.full_train_dataset, + ) + + if args.full_train_dataset is None: + args.full_train_dataset = [] + if args.exclude_eval_dataset is None: + args.exclude_eval_dataset = [] + excluded_eval_datasets = args.full_train_dataset + args.exclude_eval_dataset + + val_dataset_names = ( + [n for n in args.datasetnames if n not in excluded_eval_datasets] + if excluded_eval_datasets + else args.datasetnames + ) + args.val_dataset_names = val_dataset_names + args.val_data = get_tar_path_from_dataset_name( + val_dataset_names, + ["valid", "test", "eval"], + islocal=not args.remotedata, + proportion=1, + dataset_path=args.datasetpath, + full_dataset=None, + ) + + if args.train_data: + data["train"] = get_dataset_fn(args.train_data, args.dataset_type)( + args, model_cfg, is_train=True + ) + + if args.val_data: + data["val"] = get_dataset_fn(args.val_data, args.dataset_type)( + args, model_cfg, is_train=False + ) + + return data diff --git a/src/audioldm/clap/training/distributed.py b/src/audioldm/clap/training/distributed.py new file mode 100644 index 0000000000000000000000000000000000000000..940dd5133926a04a3cedd96f820f8f64b4605054 --- /dev/null +++ b/src/audioldm/clap/training/distributed.py @@ -0,0 +1,150 @@ +import os + +import torch +import socket + +try: + import horovod.torch as hvd +except ImportError: + hvd = None + + +def is_global_master(args): + return args.rank == 0 + + +def is_local_master(args): + return args.local_rank == 0 + + +def is_master(args, local=False): + return is_local_master(args) if local else is_global_master(args) + + +def is_using_horovod(): + # NOTE w/ horovod run, OMPI vars should be set, but w/ SLURM PMI vars will be set + # Differentiating between horovod and DDP use via SLURM may not be possible, so horovod arg still required... + ompi_vars = ["OMPI_COMM_WORLD_RANK", "OMPI_COMM_WORLD_SIZE"] + pmi_vars = ["PMI_RANK", "PMI_SIZE"] + if all([var in os.environ for var in ompi_vars]) or all( + [var in os.environ for var in pmi_vars] + ): + return True + else: + return False + + +def is_using_distributed(): + if "WORLD_SIZE" in os.environ: + return int(os.environ["WORLD_SIZE"]) > 1 + if "SLURM_NTASKS" in os.environ: + return int(os.environ["SLURM_NTASKS"]) > 1 + return False + + +def world_info_from_env(): + local_rank = 0 + for v in ( + "SLURM_LOCALID", + "MPI_LOCALRANKID", + "OMPI_COMM_WORLD_LOCAL_RANK", + "LOCAL_RANK", + ): + if v in os.environ: + local_rank = int(os.environ[v]) + break + global_rank = 0 + for v in ("SLURM_PROCID", "PMI_RANK", "OMPI_COMM_WORLD_RANK", "RANK"): + if v in os.environ: + global_rank = int(os.environ[v]) + break + world_size = 1 + for v in ("SLURM_NTASKS", "PMI_SIZE", "OMPI_COMM_WORLD_SIZE", "WORLD_SIZE"): + if v in os.environ: + world_size = int(os.environ[v]) + break + + return local_rank, global_rank, world_size + + +def init_distributed_device(args): + # Distributed training = training on more than one GPU. + # Works in both single and multi-node scenarios. + args.distributed = False + args.world_size = 1 + args.rank = 0 # global rank + args.local_rank = 0 + if args.horovod: + assert hvd is not None, "Horovod is not installed" + hvd.init() + world_size = int(os.environ["OMPI_COMM_WORLD_SIZE"]) + world_rank = int(os.environ["OMPI_COMM_WORLD_RANK"]) + local_rank = int(os.environ["OMPI_COMM_WORLD_LOCAL_RANK"]) + args.local_rank = local_rank + args.rank = world_rank + args.world_size = world_size + # args.local_rank = int(hvd.local_rank()) + # args.rank = hvd.rank() + # args.world_size = hvd.size() + args.distributed = True + os.environ["LOCAL_RANK"] = str(args.local_rank) + os.environ["RANK"] = str(args.rank) + os.environ["WORLD_SIZE"] = str(args.world_size) + print( + f"Distributed training: local_rank={args.local_rank}, " + f"rank={args.rank}, world_size={args.world_size}, " + f"hostname={socket.gethostname()}, pid={os.getpid()}" + ) + elif is_using_distributed(): + if "SLURM_PROCID" in os.environ: + # DDP via SLURM + args.local_rank, args.rank, args.world_size = world_info_from_env() + # SLURM var -> torch.distributed vars in case needed + os.environ["LOCAL_RANK"] = str(args.local_rank) + os.environ["RANK"] = str(args.rank) + os.environ["WORLD_SIZE"] = str(args.world_size) + torch.distributed.init_process_group( + backend=args.dist_backend, + init_method=args.dist_url, + world_size=args.world_size, + rank=args.rank, + ) + elif "OMPI_COMM_WORLD_SIZE" in os.environ: # using Summit cluster + world_size = int(os.environ["OMPI_COMM_WORLD_SIZE"]) + world_rank = int(os.environ["OMPI_COMM_WORLD_RANK"]) + local_rank = int(os.environ["OMPI_COMM_WORLD_LOCAL_RANK"]) + args.local_rank = local_rank + args.rank = world_rank + args.world_size = world_size + torch.distributed.init_process_group( + backend=args.dist_backend, + init_method=args.dist_url, + world_size=args.world_size, + rank=args.rank, + ) + else: + # DDP via torchrun, torch.distributed.launch + args.local_rank, _, _ = world_info_from_env() + torch.distributed.init_process_group( + backend=args.dist_backend, init_method=args.dist_url + ) + args.world_size = torch.distributed.get_world_size() + args.rank = torch.distributed.get_rank() + args.distributed = True + print( + f"Distributed training: local_rank={args.local_rank}, " + f"rank={args.rank}, world_size={args.world_size}, " + f"hostname={socket.gethostname()}, pid={os.getpid()}" + ) + + if torch.cuda.is_available(): + if args.distributed and not args.no_set_device_rank: + device = "cuda:%d" % args.local_rank + else: + device = "cuda:0" + torch.cuda.set_device(device) + else: + device = "cpu" + args.device = device + device = torch.device(device) + return device diff --git a/src/audioldm/clap/training/imagenet_zeroshot_data.py b/src/audioldm/clap/training/imagenet_zeroshot_data.py new file mode 100644 index 0000000000000000000000000000000000000000..1b77eb77497d044f4aa2b757be2f82bc6d873bf8 --- /dev/null +++ b/src/audioldm/clap/training/imagenet_zeroshot_data.py @@ -0,0 +1,1088 @@ +# NOTE: This script is currently not supported for CLAP. + +imagenet_classnames = [ + "tench", + "goldfish", + "great white shark", + "tiger shark", + "hammerhead shark", + "electric ray", + "stingray", + "rooster", + "hen", + "ostrich", + "brambling", + "goldfinch", + "house finch", + "junco", + "indigo bunting", + "American robin", + "bulbul", + "jay", + "magpie", + "chickadee", + "American dipper", + "kite (bird of prey)", + "bald eagle", + "vulture", + "great grey owl", + "fire salamander", + "smooth newt", + "newt", + "spotted salamander", + "axolotl", + "American bullfrog", + "tree frog", + "tailed frog", + "loggerhead sea turtle", + "leatherback sea turtle", + "mud turtle", + "terrapin", + "box turtle", + "banded gecko", + "green iguana", + "Carolina anole", + "desert grassland whiptail lizard", + "agama", + "frilled-necked lizard", + "alligator lizard", + "Gila monster", + "European green lizard", + "chameleon", + "Komodo dragon", + "Nile crocodile", + "American alligator", + "triceratops", + "worm snake", + "ring-necked snake", + "eastern hog-nosed snake", + "smooth green snake", + "kingsnake", + "garter snake", + "water snake", + "vine snake", + "night snake", + "boa constrictor", + "African rock python", + "Indian cobra", + "green mamba", + "sea snake", + "Saharan horned viper", + "eastern diamondback rattlesnake", + "sidewinder rattlesnake", + "trilobite", + "harvestman", + "scorpion", + "yellow garden spider", + "barn spider", + "European garden spider", + "southern black widow", + "tarantula", + "wolf spider", + "tick", + "centipede", + "black grouse", + "ptarmigan", + "ruffed grouse", + "prairie grouse", + "peafowl", + "quail", + "partridge", + "african grey parrot", + "macaw", + "sulphur-crested cockatoo", + "lorikeet", + "coucal", + "bee eater", + "hornbill", + "hummingbird", + "jacamar", + "toucan", + "duck", + "red-breasted merganser", + "goose", + "black swan", + "tusker", + "echidna", + "platypus", + "wallaby", + "koala", + "wombat", + "jellyfish", + "sea anemone", + "brain coral", + "flatworm", + "nematode", + "conch", + "snail", + "slug", + "sea slug", + "chiton", + "chambered nautilus", + "Dungeness crab", + "rock crab", + "fiddler crab", + "red king crab", + "American lobster", + "spiny lobster", + "crayfish", + "hermit crab", + "isopod", + "white stork", + "black stork", + "spoonbill", + "flamingo", + "little blue heron", + "great egret", + "bittern bird", + "crane bird", + "limpkin", + "common gallinule", + "American coot", + "bustard", + "ruddy turnstone", + "dunlin", + "common redshank", + "dowitcher", + "oystercatcher", + "pelican", + "king penguin", + "albatross", + "grey whale", + "killer whale", + "dugong", + "sea lion", + "Chihuahua", + "Japanese Chin", + "Maltese", + "Pekingese", + "Shih Tzu", + "King Charles Spaniel", + "Papillon", + "toy terrier", + "Rhodesian Ridgeback", + "Afghan Hound", + "Basset Hound", + "Beagle", + "Bloodhound", + "Bluetick Coonhound", + "Black and Tan Coonhound", + "Treeing Walker Coonhound", + "English foxhound", + "Redbone Coonhound", + "borzoi", + "Irish Wolfhound", + "Italian Greyhound", + "Whippet", + "Ibizan Hound", + "Norwegian Elkhound", + "Otterhound", + "Saluki", + "Scottish Deerhound", + "Weimaraner", + "Staffordshire Bull Terrier", + "American Staffordshire Terrier", + "Bedlington Terrier", + "Border Terrier", + "Kerry Blue Terrier", + "Irish Terrier", + "Norfolk Terrier", + "Norwich Terrier", + "Yorkshire Terrier", + "Wire Fox Terrier", + "Lakeland Terrier", + "Sealyham Terrier", + "Airedale Terrier", + "Cairn Terrier", + "Australian Terrier", + "Dandie Dinmont Terrier", + "Boston Terrier", + "Miniature Schnauzer", + "Giant Schnauzer", + "Standard Schnauzer", + "Scottish Terrier", + "Tibetan Terrier", + "Australian Silky Terrier", + "Soft-coated Wheaten Terrier", + "West Highland White Terrier", + "Lhasa Apso", + "Flat-Coated Retriever", + "Curly-coated Retriever", + "Golden Retriever", + "Labrador Retriever", + "Chesapeake Bay Retriever", + "German Shorthaired Pointer", + "Vizsla", + "English Setter", + "Irish Setter", + "Gordon Setter", + "Brittany dog", + "Clumber Spaniel", + "English Springer Spaniel", + "Welsh Springer Spaniel", + "Cocker Spaniel", + "Sussex Spaniel", + "Irish Water Spaniel", + "Kuvasz", + "Schipperke", + "Groenendael dog", + "Malinois", + "Briard", + "Australian Kelpie", + "Komondor", + "Old English Sheepdog", + "Shetland Sheepdog", + "collie", + "Border Collie", + "Bouvier des Flandres dog", + "Rottweiler", + "German Shepherd Dog", + "Dobermann", + "Miniature Pinscher", + "Greater Swiss Mountain Dog", + "Bernese Mountain Dog", + "Appenzeller Sennenhund", + "Entlebucher Sennenhund", + "Boxer", + "Bullmastiff", + "Tibetan Mastiff", + "French Bulldog", + "Great Dane", + "St. Bernard", + "husky", + "Alaskan Malamute", + "Siberian Husky", + "Dalmatian", + "Affenpinscher", + "Basenji", + "pug", + "Leonberger", + "Newfoundland dog", + "Great Pyrenees dog", + "Samoyed", + "Pomeranian", + "Chow Chow", + "Keeshond", + "brussels griffon", + "Pembroke Welsh Corgi", + "Cardigan Welsh Corgi", + "Toy Poodle", + "Miniature Poodle", + "Standard Poodle", + "Mexican hairless dog (xoloitzcuintli)", + "grey wolf", + "Alaskan tundra wolf", + "red wolf or maned wolf", + "coyote", + "dingo", + "dhole", + "African wild dog", + "hyena", + "red fox", + "kit fox", + "Arctic fox", + "grey fox", + "tabby cat", + "tiger cat", + "Persian cat", + "Siamese cat", + "Egyptian Mau", + "cougar", + "lynx", + "leopard", + "snow leopard", + "jaguar", + "lion", + "tiger", + "cheetah", + "brown bear", + "American black bear", + "polar bear", + "sloth bear", + "mongoose", + "meerkat", + "tiger beetle", + "ladybug", + "ground beetle", + "longhorn beetle", + "leaf beetle", + "dung beetle", + "rhinoceros beetle", + "weevil", + "fly", + "bee", + "ant", + "grasshopper", + "cricket insect", + "stick insect", + "cockroach", + "praying mantis", + "cicada", + "leafhopper", + "lacewing", + "dragonfly", + "damselfly", + "red admiral butterfly", + "ringlet butterfly", + "monarch butterfly", + "small white butterfly", + "sulphur butterfly", + "gossamer-winged butterfly", + "starfish", + "sea urchin", + "sea cucumber", + "cottontail rabbit", + "hare", + "Angora rabbit", + "hamster", + "porcupine", + "fox squirrel", + "marmot", + "beaver", + "guinea pig", + "common sorrel horse", + "zebra", + "pig", + "wild boar", + "warthog", + "hippopotamus", + "ox", + "water buffalo", + "bison", + "ram (adult male sheep)", + "bighorn sheep", + "Alpine ibex", + "hartebeest", + "impala (antelope)", + "gazelle", + "arabian camel", + "llama", + "weasel", + "mink", + "European polecat", + "black-footed ferret", + "otter", + "skunk", + "badger", + "armadillo", + "three-toed sloth", + "orangutan", + "gorilla", + "chimpanzee", + "gibbon", + "siamang", + "guenon", + "patas monkey", + "baboon", + "macaque", + "langur", + "black-and-white colobus", + "proboscis monkey", + "marmoset", + "white-headed capuchin", + "howler monkey", + "titi monkey", + "Geoffroy's spider monkey", + "common squirrel monkey", + "ring-tailed lemur", + "indri", + "Asian elephant", + "African bush elephant", + "red panda", + "giant panda", + "snoek fish", + "eel", + "silver salmon", + "rock beauty fish", + "clownfish", + "sturgeon", + "gar fish", + "lionfish", + "pufferfish", + "abacus", + "abaya", + "academic gown", + "accordion", + "acoustic guitar", + "aircraft carrier", + "airliner", + "airship", + "altar", + "ambulance", + "amphibious vehicle", + "analog clock", + "apiary", + "apron", + "trash can", + "assault rifle", + "backpack", + "bakery", + "balance beam", + "balloon", + "ballpoint pen", + "Band-Aid", + "banjo", + "baluster / handrail", + "barbell", + "barber chair", + "barbershop", + "barn", + "barometer", + "barrel", + "wheelbarrow", + "baseball", + "basketball", + "bassinet", + "bassoon", + "swimming cap", + "bath towel", + "bathtub", + "station wagon", + "lighthouse", + "beaker", + "military hat (bearskin or shako)", + "beer bottle", + "beer glass", + "bell tower", + "baby bib", + "tandem bicycle", + "bikini", + "ring binder", + "binoculars", + "birdhouse", + "boathouse", + "bobsleigh", + "bolo tie", + "poke bonnet", + "bookcase", + "bookstore", + "bottle cap", + "hunting bow", + "bow tie", + "brass memorial plaque", + "bra", + "breakwater", + "breastplate", + "broom", + "bucket", + "buckle", + "bulletproof vest", + "high-speed train", + "butcher shop", + "taxicab", + "cauldron", + "candle", + "cannon", + "canoe", + "can opener", + "cardigan", + "car mirror", + "carousel", + "tool kit", + "cardboard box / carton", + "car wheel", + "automated teller machine", + "cassette", + "cassette player", + "castle", + "catamaran", + "CD player", + "cello", + "mobile phone", + "chain", + "chain-link fence", + "chain mail", + "chainsaw", + "storage chest", + "chiffonier", + "bell or wind chime", + "china cabinet", + "Christmas stocking", + "church", + "movie theater", + "cleaver", + "cliff dwelling", + "cloak", + "clogs", + "cocktail shaker", + "coffee mug", + "coffeemaker", + "spiral or coil", + "combination lock", + "computer keyboard", + "candy store", + "container ship", + "convertible", + "corkscrew", + "cornet", + "cowboy boot", + "cowboy hat", + "cradle", + "construction crane", + "crash helmet", + "crate", + "infant bed", + "Crock Pot", + "croquet ball", + "crutch", + "cuirass", + "dam", + "desk", + "desktop computer", + "rotary dial telephone", + "diaper", + "digital clock", + "digital watch", + "dining table", + "dishcloth", + "dishwasher", + "disc brake", + "dock", + "dog sled", + "dome", + "doormat", + "drilling rig", + "drum", + "drumstick", + "dumbbell", + "Dutch oven", + "electric fan", + "electric guitar", + "electric locomotive", + "entertainment center", + "envelope", + "espresso machine", + "face powder", + "feather boa", + "filing cabinet", + "fireboat", + "fire truck", + "fire screen", + "flagpole", + "flute", + "folding chair", + "football helmet", + "forklift", + "fountain", + "fountain pen", + "four-poster bed", + "freight car", + "French horn", + "frying pan", + "fur coat", + "garbage truck", + "gas mask or respirator", + "gas pump", + "goblet", + "go-kart", + "golf ball", + "golf cart", + "gondola", + "gong", + "gown", + "grand piano", + "greenhouse", + "radiator grille", + "grocery store", + "guillotine", + "hair clip", + "hair spray", + "half-track", + "hammer", + "hamper", + "hair dryer", + "hand-held computer", + "handkerchief", + "hard disk drive", + "harmonica", + "harp", + "combine harvester", + "hatchet", + "holster", + "home theater", + "honeycomb", + "hook", + "hoop skirt", + "gymnastic horizontal bar", + "horse-drawn vehicle", + "hourglass", + "iPod", + "clothes iron", + "carved pumpkin", + "jeans", + "jeep", + "T-shirt", + "jigsaw puzzle", + "rickshaw", + "joystick", + "kimono", + "knee pad", + "knot", + "lab coat", + "ladle", + "lampshade", + "laptop computer", + "lawn mower", + "lens cap", + "letter opener", + "library", + "lifeboat", + "lighter", + "limousine", + "ocean liner", + "lipstick", + "slip-on shoe", + "lotion", + "music speaker", + "loupe magnifying glass", + "sawmill", + "magnetic compass", + "messenger bag", + "mailbox", + "tights", + "one-piece bathing suit", + "manhole cover", + "maraca", + "marimba", + "mask", + "matchstick", + "maypole", + "maze", + "measuring cup", + "medicine cabinet", + "megalith", + "microphone", + "microwave oven", + "military uniform", + "milk can", + "minibus", + "miniskirt", + "minivan", + "missile", + "mitten", + "mixing bowl", + "mobile home", + "ford model t", + "modem", + "monastery", + "monitor", + "moped", + "mortar and pestle", + "graduation cap", + "mosque", + "mosquito net", + "vespa", + "mountain bike", + "tent", + "computer mouse", + "mousetrap", + "moving van", + "muzzle", + "metal nail", + "neck brace", + "necklace", + "baby pacifier", + "notebook computer", + "obelisk", + "oboe", + "ocarina", + "odometer", + "oil filter", + "pipe organ", + "oscilloscope", + "overskirt", + "bullock cart", + "oxygen mask", + "product packet / packaging", + "paddle", + "paddle wheel", + "padlock", + "paintbrush", + "pajamas", + "palace", + "pan flute", + "paper towel", + "parachute", + "parallel bars", + "park bench", + "parking meter", + "railroad car", + "patio", + "payphone", + "pedestal", + "pencil case", + "pencil sharpener", + "perfume", + "Petri dish", + "photocopier", + "plectrum", + "Pickelhaube", + "picket fence", + "pickup truck", + "pier", + "piggy bank", + "pill bottle", + "pillow", + "ping-pong ball", + "pinwheel", + "pirate ship", + "drink pitcher", + "block plane", + "planetarium", + "plastic bag", + "plate rack", + "farm plow", + "plunger", + "Polaroid camera", + "pole", + "police van", + "poncho", + "pool table", + "soda bottle", + "plant pot", + "potter's wheel", + "power drill", + "prayer rug", + "printer", + "prison", + "missile", + "projector", + "hockey puck", + "punching bag", + "purse", + "quill", + "quilt", + "race car", + "racket", + "radiator", + "radio", + "radio telescope", + "rain barrel", + "recreational vehicle", + "fishing casting reel", + "reflex camera", + "refrigerator", + "remote control", + "restaurant", + "revolver", + "rifle", + "rocking chair", + "rotisserie", + "eraser", + "rugby ball", + "ruler measuring stick", + "sneaker", + "safe", + "safety pin", + "salt shaker", + "sandal", + "sarong", + "saxophone", + "scabbard", + "weighing scale", + "school bus", + "schooner", + "scoreboard", + "CRT monitor", + "screw", + "screwdriver", + "seat belt", + "sewing machine", + "shield", + "shoe store", + "shoji screen / room divider", + "shopping basket", + "shopping cart", + "shovel", + "shower cap", + "shower curtain", + "ski", + "balaclava ski mask", + "sleeping bag", + "slide rule", + "sliding door", + "slot machine", + "snorkel", + "snowmobile", + "snowplow", + "soap dispenser", + "soccer ball", + "sock", + "solar thermal collector", + "sombrero", + "soup bowl", + "keyboard space bar", + "space heater", + "space shuttle", + "spatula", + "motorboat", + "spider web", + "spindle", + "sports car", + "spotlight", + "stage", + "steam locomotive", + "through arch bridge", + "steel drum", + "stethoscope", + "scarf", + "stone wall", + "stopwatch", + "stove", + "strainer", + "tram", + "stretcher", + "couch", + "stupa", + "submarine", + "suit", + "sundial", + "sunglasses", + "sunglasses", + "sunscreen", + "suspension bridge", + "mop", + "sweatshirt", + "swim trunks / shorts", + "swing", + "electrical switch", + "syringe", + "table lamp", + "tank", + "tape player", + "teapot", + "teddy bear", + "television", + "tennis ball", + "thatched roof", + "front curtain", + "thimble", + "threshing machine", + "throne", + "tile roof", + "toaster", + "tobacco shop", + "toilet seat", + "torch", + "totem pole", + "tow truck", + "toy store", + "tractor", + "semi-trailer truck", + "tray", + "trench coat", + "tricycle", + "trimaran", + "tripod", + "triumphal arch", + "trolleybus", + "trombone", + "hot tub", + "turnstile", + "typewriter keyboard", + "umbrella", + "unicycle", + "upright piano", + "vacuum cleaner", + "vase", + "vaulted or arched ceiling", + "velvet fabric", + "vending machine", + "vestment", + "viaduct", + "violin", + "volleyball", + "waffle iron", + "wall clock", + "wallet", + "wardrobe", + "military aircraft", + "sink", + "washing machine", + "water bottle", + "water jug", + "water tower", + "whiskey jug", + "whistle", + "hair wig", + "window screen", + "window shade", + "Windsor tie", + "wine bottle", + "airplane wing", + "wok", + "wooden spoon", + "wool", + "split-rail fence", + "shipwreck", + "sailboat", + "yurt", + "website", + "comic book", + "crossword", + "traffic or street sign", + "traffic light", + "dust jacket", + "menu", + "plate", + "guacamole", + "consomme", + "hot pot", + "trifle", + "ice cream", + "popsicle", + "baguette", + "bagel", + "pretzel", + "cheeseburger", + "hot dog", + "mashed potatoes", + "cabbage", + "broccoli", + "cauliflower", + "zucchini", + "spaghetti squash", + "acorn squash", + "butternut squash", + "cucumber", + "artichoke", + "bell pepper", + "cardoon", + "mushroom", + "Granny Smith apple", + "strawberry", + "orange", + "lemon", + "fig", + "pineapple", + "banana", + "jackfruit", + "cherimoya (custard apple)", + "pomegranate", + "hay", + "carbonara", + "chocolate syrup", + "dough", + "meatloaf", + "pizza", + "pot pie", + "burrito", + "red wine", + "espresso", + "tea cup", + "eggnog", + "mountain", + "bubble", + "cliff", + "coral reef", + "geyser", + "lakeshore", + "promontory", + "sandbar", + "beach", + "valley", + "volcano", + "baseball player", + "bridegroom", + "scuba diver", + "rapeseed", + "daisy", + "yellow lady's slipper", + "corn", + "acorn", + "rose hip", + "horse chestnut seed", + "coral fungus", + "agaric", + "gyromitra", + "stinkhorn mushroom", + "earth star fungus", + "hen of the woods mushroom", + "bolete", + "corn cob", + "toilet paper", +] + + +openai_imagenet_template = [ + lambda c: f"a bad photo of a {c}.", + lambda c: f"a photo of many {c}.", + lambda c: f"a sculpture of a {c}.", + lambda c: f"a photo of the hard to see {c}.", + lambda c: f"a low resolution photo of the {c}.", + lambda c: f"a rendering of a {c}.", + lambda c: f"graffiti of a {c}.", + lambda c: f"a bad photo of the {c}.", + lambda c: f"a cropped photo of the {c}.", + lambda c: f"a tattoo of a {c}.", + lambda c: f"the embroidered {c}.", + lambda c: f"a photo of a hard to see {c}.", + lambda c: f"a bright photo of a {c}.", + lambda c: f"a photo of a clean {c}.", + lambda c: f"a photo of a dirty {c}.", + lambda c: f"a dark photo of the {c}.", + lambda c: f"a drawing of a {c}.", + lambda c: f"a photo of my {c}.", + lambda c: f"the plastic {c}.", + lambda c: f"a photo of the cool {c}.", + lambda c: f"a close-up photo of a {c}.", + lambda c: f"a black and white photo of the {c}.", + lambda c: f"a painting of the {c}.", + lambda c: f"a painting of a {c}.", + lambda c: f"a pixelated photo of the {c}.", + lambda c: f"a sculpture of the {c}.", + lambda c: f"a bright photo of the {c}.", + lambda c: f"a cropped photo of a {c}.", + lambda c: f"a plastic {c}.", + lambda c: f"a photo of the dirty {c}.", + lambda c: f"a jpeg corrupted photo of a {c}.", + lambda c: f"a blurry photo of the {c}.", + lambda c: f"a photo of the {c}.", + lambda c: f"a good photo of the {c}.", + lambda c: f"a rendering of the {c}.", + lambda c: f"a {c} in a video game.", + lambda c: f"a photo of one {c}.", + lambda c: f"a doodle of a {c}.", + lambda c: f"a close-up photo of the {c}.", + lambda c: f"a photo of a {c}.", + lambda c: f"the origami {c}.", + lambda c: f"the {c} in a video game.", + lambda c: f"a sketch of a {c}.", + lambda c: f"a doodle of the {c}.", + lambda c: f"a origami {c}.", + lambda c: f"a low resolution photo of a {c}.", + lambda c: f"the toy {c}.", + lambda c: f"a rendition of the {c}.", + lambda c: f"a photo of the clean {c}.", + lambda c: f"a photo of a large {c}.", + lambda c: f"a rendition of a {c}.", + lambda c: f"a photo of a nice {c}.", + lambda c: f"a photo of a weird {c}.", + lambda c: f"a blurry photo of a {c}.", + lambda c: f"a cartoon {c}.", + lambda c: f"art of a {c}.", + lambda c: f"a sketch of the {c}.", + lambda c: f"a embroidered {c}.", + lambda c: f"a pixelated photo of a {c}.", + lambda c: f"itap of the {c}.", + lambda c: f"a jpeg corrupted photo of the {c}.", + lambda c: f"a good photo of a {c}.", + lambda c: f"a plushie {c}.", + lambda c: f"a photo of the nice {c}.", + lambda c: f"a photo of the small {c}.", + lambda c: f"a photo of the weird {c}.", + lambda c: f"the cartoon {c}.", + lambda c: f"art of the {c}.", + lambda c: f"a drawing of the {c}.", + lambda c: f"a photo of the large {c}.", + lambda c: f"a black and white photo of a {c}.", + lambda c: f"the plushie {c}.", + lambda c: f"a dark photo of a {c}.", + lambda c: f"itap of a {c}.", + lambda c: f"graffiti of the {c}.", + lambda c: f"a toy {c}.", + lambda c: f"itap of my {c}.", + lambda c: f"a photo of a cool {c}.", + lambda c: f"a photo of a small {c}.", + lambda c: f"a tattoo of the {c}.", +] diff --git a/src/audioldm/clap/training/infer_demo.py b/src/audioldm/clap/training/infer_demo.py new file mode 100644 index 0000000000000000000000000000000000000000..459704fd6d04c233499be5165a06f9a07c84e89c --- /dev/null +++ b/src/audioldm/clap/training/infer_demo.py @@ -0,0 +1,105 @@ +import sys + +import os +import torch +import librosa +from open_clip import create_model +from training.data import get_audio_features +from training.data import int16_to_float32, float32_to_int16 +from transformers import RobertaTokenizer + +tokenize = RobertaTokenizer.from_pretrained("roberta-base") + + +def tokenizer(text): + result = tokenize( + text, + padding="max_length", + truncation=True, + max_length=77, + return_tensors="pt", + ) + return {k: v.squeeze(0) for k, v in result.items()} + + +PRETRAINED_PATH = "/mnt/fast/nobackup/users/hl01486/projects/contrastive_pretraining/CLAP/assets/checkpoints/epoch_top_0_audioset_no_fusion.pt" +WAVE_48k_PATH = "/mnt/fast/nobackup/users/hl01486/projects/contrastive_pretraining/CLAP/assets/audio/machine.wav" + + +def infer_text(): + device = "cuda:0" if torch.cuda.is_available() else "cpu" + precision = "fp32" + amodel = "HTSAT-tiny" # or 'PANN-14' + tmodel = "roberta" # the best text encoder in our training + enable_fusion = False # False if you do not want to use the fusion model + fusion_type = "aff_2d" + pretrained = PRETRAINED_PATH + + model, model_cfg = create_model( + amodel, + tmodel, + pretrained, + precision=precision, + device=device, + enable_fusion=enable_fusion, + fusion_type=fusion_type, + ) + # load the text, can be a list (i.e. batch size) + text_data = ["I love the contrastive learning", "I love the pretrain model"] + # tokenize for roberta, if you want to tokenize for another text encoder, please refer to data.py#L43-90 + text_data = tokenizer(text_data) + + text_embed = model.get_text_embedding(text_data) + print(text_embed.size()) + + +def infer_audio(): + + device = "cuda:0" if torch.cuda.is_available() else "cpu" + precision = "fp32" + amodel = "HTSAT-tiny" # or 'PANN-14' + tmodel = "roberta" # the best text encoder in our training + enable_fusion = False # False if you do not want to use the fusion model + fusion_type = "aff_2d" + pretrained = PRETRAINED_PATH + + model, model_cfg = create_model( + amodel, + tmodel, + pretrained, + precision=precision, + device=device, + enable_fusion=enable_fusion, + fusion_type=fusion_type, + ) + + # load the waveform of the shape (T,), should resample to 48000 + audio_waveform, sr = librosa.load(WAVE_48k_PATH, sr=48000) + # quantize + audio_waveform = int16_to_float32(float32_to_int16(audio_waveform)) + audio_waveform = torch.from_numpy(audio_waveform).float() + audio_dict = {} + + # the 'fusion' truncate mode can be changed to 'rand_trunc' if run in unfusion mode + import ipdb + + ipdb.set_trace() + audio_dict = get_audio_features( + audio_dict, + audio_waveform, + 480000, + data_truncating="fusion", + data_filling="repeatpad", + audio_cfg=model_cfg["audio_cfg"], + ) + # can send a list to the model, to process many audio tracks in one time (i.e. batch size) + audio_embed = model.get_audio_embedding([audio_dict]) + print(audio_embed.size()) + import ipdb + + ipdb.set_trace() + + +if __name__ == "__main__": + infer_text() + infer_audio() diff --git a/src/audioldm/clap/training/logger.py b/src/audioldm/clap/training/logger.py new file mode 100644 index 0000000000000000000000000000000000000000..2456bc77f5624769b8aa1260b4e4c51046752597 --- /dev/null +++ b/src/audioldm/clap/training/logger.py @@ -0,0 +1,30 @@ +import logging + + +def setup_logging(log_file, level, include_host=False): + if include_host: + import socket + + hostname = socket.gethostname() + formatter = logging.Formatter( + f"%(asctime)s | {hostname} | %(levelname)s | %(message)s", + datefmt="%Y-%m-%d,%H:%M:%S", + ) + else: + formatter = logging.Formatter( + "%(asctime)s | %(levelname)s | %(message)s", datefmt="%Y-%m-%d,%H:%M:%S" + ) + + logging.root.setLevel(level) + loggers = [logging.getLogger(name) for name in logging.root.manager.loggerDict] + for logger in loggers: + logger.setLevel(level) + + stream_handler = logging.StreamHandler() + stream_handler.setFormatter(formatter) + logging.root.addHandler(stream_handler) + + if log_file: + file_handler = logging.FileHandler(filename=log_file) + file_handler.setFormatter(formatter) + logging.root.addHandler(file_handler) diff --git a/src/audioldm/clap/training/lp_main.py b/src/audioldm/clap/training/lp_main.py new file mode 100644 index 0000000000000000000000000000000000000000..fb03e64d390e63a4ce0eb831afa59604409e64c8 --- /dev/null +++ b/src/audioldm/clap/training/lp_main.py @@ -0,0 +1,670 @@ +from cmath import cos +from inspect import getargs +import logging +import os +import random +from datetime import datetime +import bisect +import copy +from sched import scheduler +import numpy as np +import torch +import torch.backends.cudnn as cudnn +from torch import optim +from torch.cuda.amp import GradScaler +import faulthandler +import pathlib +import argparse +import time + +try: + import wandb +except ImportError: + wandb = None + +try: + import torch.utils.tensorboard as tensorboard +except ImportError: + tensorboard = None + +try: + import horovod.torch as hvd +except ImportError: + hvd = None + +from open_clip import create_model_and_transforms, trace_model, create_model +from training.data import get_data +from training.params import parse_args +from training.distributed import is_master, init_distributed_device, world_info_from_env +from training.logger import setup_logging +from training.scheduler import cosine_lr +from training.lp_train import train_one_epoch, evaluate +from open_clip.utils import get_tar_path_from_dataset_name, dataset_split, get_optimizer +from open_clip.utils import load_p, load_class_label +from open_clip.linear_probe import LinearProbe + + +def maintain_ckpts(args, startidx, all_idx_len): + for i in reversed(range(startidx, all_idx_len)): + if os.path.exists(os.path.join(args.checkpoint_path, f"epoch_top_{i}.pt")): + os.rename( + os.path.join(args.checkpoint_path, f"epoch_top_{i}.pt"), + os.path.join(args.checkpoint_path, f"epoch_top_{i+1}.pt"), + ) + if os.path.exists( + os.path.join(args.checkpoint_path, f"epoch_top_{all_idx_len}.pt") + ): + os.remove(os.path.join(args.checkpoint_path, f"epoch_top_{all_idx_len}.pt")) + return + + +def update_top_k_performance( + new_metrics_inputs, current_top_k_ckpt_metrics, args, ckpt, bignumbetter=True +): + """ + Record the top-k performance of the current epoch. + current_top_k_metrics is a dictionary of the form: {1: top_1_ckpt_measure, 2: top_2_ckpt_measure, ...} + """ + if isinstance(new_metrics_inputs, (list, tuple)): + new_metrics_inputs = np.mean(new_metrics_inputs) + return update_top_k_performance( + new_metrics_inputs, + current_top_k_ckpt_metrics, + args=args, + ckpt=ckpt, + bignumbetter=bignumbetter, + ) + elif isinstance(new_metrics_inputs, dict): + new_metrics_inputs = np.mean(list(new_metrics_inputs.values())) + return update_top_k_performance( + new_metrics_inputs, + current_top_k_ckpt_metrics, + args=args, + ckpt=ckpt, + bignumbetter=bignumbetter, + ) + elif isinstance(new_metrics_inputs, (float, int)): + update_flag = {k: False for k in current_top_k_ckpt_metrics.keys()} + sorted_keys = sorted(current_top_k_ckpt_metrics.keys()) + sorted_values = sorted( + current_top_k_ckpt_metrics.values(), reverse=bignumbetter + ) + sorted_values_ = copy.deepcopy(sorted_values) + sorted_values.append(new_metrics_inputs) + sorted_values = sorted(sorted_values, reverse=bignumbetter) + sorted_values = sorted_values[:-1] + + if sorted_values == sorted_values_: + return current_top_k_ckpt_metrics, new_metrics_inputs + else: + for i in range(len(sorted_keys)): + if current_top_k_ckpt_metrics[sorted_keys[i]] != sorted_values[i]: + current_top_k_ckpt_metrics[sorted_keys[i]] = sorted_values[i] + update_flag[sorted_keys[i]] = True + for i in range(len(update_flag)): + if update_flag[i]: + maintain_ckpts(args, i, len(sorted_keys)) + torch.save( + ckpt, + os.path.join(args.checkpoint_path, f"epoch_top_{i}.pt"), + ) + break + return current_top_k_ckpt_metrics, new_metrics_inputs + + +# def updateifNone(a, b): +# a = b if None else a +# return a + + +def is_pretrained_params(n): + return ( + n.startswith("clap_model.transformer") + or n in ["clap_model.positional_embedding", "clap_model.text_projection"] + or n.startswith("clap_model.token_embedding") + or n.startswith("clap_model.ln_final") + or n.startswith("clap_model.logit_scale_t") + ) + + +def random_seed(seed=42, rank=0): + torch.manual_seed(seed + rank) + np.random.seed(seed + rank) + random.seed(seed + rank) + + +def config_lp_optimizer(model, data, args): + # set wd-related params to 0 if use adam optimizer + if args.optimizer == "adam": + args.wd = 0 + args.wd_pretrained = 0 + args.wd_new = 0 + + in_clap = lambda n, p: n.startswith("clap_model") + + named_parameters = list(model.named_parameters()) + + optimizer = {} + scheduler = {} + + # freeze text encoder + text_freeze_parameters = [ + p + for n, p in named_parameters + if n.startswith("clap_model.transformer") + or n in ["clap_model.positional_embedding", "clap_model.text_projection"] + or n.startswith("clap_model.token_embedding") + or n.startswith("clap_model.ln_final") + ] + + if args.freeze_text: + logging.info("Freeze Text!!!!") + for k in text_freeze_parameters: + k.requires_grad = False + + if not args.lp_freeze: + exclude = ( + lambda n, p: p.ndim < 2 + or "bn" in n + or "ln" in n + or "bias" in n + or "logit_scale" in n + ) + include = lambda n, p: not exclude(n, p) + + # (yusong): we do not split the learning rate anymore + # p for n, p in named_parameters if in_clap(n,p) and exclude(n, p) and p.requires_grad + gain_or_bias_params = [ + p for n, p in named_parameters if exclude(n, p) and p.requires_grad + ] + # rest_params = [p for n, p in named_parameters if in_clap(n,p) and include(n, p) and p.requires_grad] + rest_params = [ + p for n, p in named_parameters if include(n, p) and p.requires_grad + ] + + if args.train_data is None: + optimizer = None + scheduler = None + else: + total_steps = data["train"].dataloader.num_batches * args.epochs + + if args.split_opt: + for x in ["lr", "beta1", "beta2", "eps", "wd"]: + for y in ["_new", "_pretrained"]: + if getattr(args, x + y) is None: + setattr(args, x + y, getattr(args, x)) + + gain_or_bias_pretrained_params = [ + p + for n, p in named_parameters + if (exclude(n, p) and p.requires_grad) and is_pretrained_params(n) + ] + rest_pretrained_params = [ + p + for n, p in named_parameters + if (include(n, p) and p.requires_grad) and is_pretrained_params(n) + ] + gain_or_bias_new_params = [ + p + for n, p in named_parameters + if (exclude(n, p) and p.requires_grad) + and (not is_pretrained_params(n)) + ] + rest_new_params = [ + p + for n, p in named_parameters + if (include(n, p) and p.requires_grad) + and (not is_pretrained_params(n)) + ] + + pretrained_params_optimizer = get_optimizer( + [ + {"params": gain_or_bias_pretrained_params, "weight_decay": 0.0}, + { + "params": rest_pretrained_params, + "weight_decay": args.wd_pretrained, + }, + ], + lr=args.lr_pretrained, + betas=(args.beta1_pretrained, args.beta2_pretrained), + eps=args.eps_pretrained, + momentum=args.momentum_pretrained, + optimizer_name=args.optimizer, + ) + pretrained_params_scheduler = cosine_lr( + pretrained_params_optimizer, + args.lr_pretrained, + args.warmup, + total_steps, + ) + + new_params_optimizer = get_optimizer( + [ + {"params": gain_or_bias_new_params, "weight_decay": 0.0}, + {"params": rest_new_params, "weight_decay": args.wd_new}, + ], + lr=args.lr_new, + betas=(args.beta1_new, args.beta2_new), + eps=args.eps_new, + momentum=args.momentum_new, + optimizer_name=args.optimizer, + ) + new_params_scheduler = cosine_lr( + new_params_optimizer, args.lr_new, args.warmup, total_steps + ) + + optimizer["text"] = pretrained_params_optimizer + optimizer["audio"] = new_params_optimizer + scheduler["text"] = pretrained_params_scheduler + scheduler["audio"] = new_params_scheduler + + if args.horovod: + pretrained_params_optimizer = hvd.DistributedOptimizer( + pretrained_params_optimizer, + named_parameters=model.named_parameters(), + ) + new_params_optimizer = hvd.DistributedOptimizer( + new_params_optimizer, named_parameters=model.named_parameters() + ) + hvd.broadcast_parameters(model.state_dict(), root_rank=0) + hvd.broadcast_optimizer_state( + pretrained_params_optimizer, root_rank=0 + ) + hvd.broadcast_optimizer_state(new_params_optimizer, root_rank=0) + else: + + optimizer["clap"] = get_optimizer( + [ + {"params": gain_or_bias_params, "weight_decay": 0.0}, + {"params": rest_params, "weight_decay": args.wd}, + ], + lr=args.lr, + betas=(args.beta1, args.beta2), + eps=args.eps, + momentum=args.momentum, + optimizer_name=args.optimizer, + ) + scheduler["clap"] = cosine_lr( + optimizer["clap"], args.lr, args.warmup, total_steps + ) + + if args.horovod: + optimizer["clap"] = hvd.DistributedOptimizer( + optimizer["clap"], named_parameters=model.named_parameters() + ) + hvd.broadcast_parameters(model.state_dict(), root_rank=0) + hvd.broadcast_optimizer_state(optimizer["clap"], root_rank=0) + + # linear probe optimizer + else: + lp_params = [ + p for n, p in named_parameters if (not in_clap(n, p)) and p.requires_grad + ] + lp_optim = get_optimizer( + lp_params, + lr=args.lp_lr, + betas=(args.beta1, args.beta2), + eps=args.eps, + momentum=0.9, + optimizer_name=args.optimizer, + ) + optimizer["lp"] = lp_optim + + return optimizer, scheduler, text_freeze_parameters + + +def main(): + args = parse_args() + + time.sleep(args.sleep) + + # sanitize model name for filesystem / uri use, easier if we don't use / in name as a rule? + args.amodel = args.amodel.replace("/", "-") + # download sizes.json file + + # (yusong): the below two lines are for debug + # print("setting up faulthandler") + # faulthandler.register(10) + + random.seed(args.seed) + torch.manual_seed(args.seed) + torch.cuda.manual_seed(args.seed) + torch.cuda.manual_seed_all(args.seed) + np.random.seed(args.seed) + args.class_index_dict = load_class_label(args.class_label_path) + + # get the name of the experiments + if args.name is None: + args.name = "-".join( + [ + datetime.now().strftime("%Y_%m_%d-%H_%M_%S"), + f"linear_probe" f"model_{args.amodel}", + f"lr_{args.lr}", + f"b_{args.batch_size}", + f"j_{args.workers}", + f"p_{args.precision}", + ] + ) + + # discover initial world args early so we can log properly + args.distributed = False + args.local_rank, args.rank, args.world_size = world_info_from_env() + + if args.remotedata and is_master(args): + for dataset_name in args.datasetnames: + for split in dataset_split[dataset_name]: + if not os.path.exists(f"./json_files/{dataset_name}/{split}"): + os.makedirs(f"./json_files/{dataset_name}/{split}") + os.system( + f"aws s3 cp s3://s-laion-audio/webdataset_tar/{dataset_name}/{split}/sizes.json ./json_files/{dataset_name}/{split}/sizes.json" + ) + + args.log_path = None + if is_master(args, local=args.log_local): + log_base_path = os.path.join(args.logs, args.name) + os.makedirs(log_base_path, exist_ok=True) + log_filename = f"out-{args.rank}" if args.log_local else "out.log" + args.log_path = os.path.join(log_base_path, log_filename) + + # avoid log dir in same name: + postfix = 0 + while os.path.exists(args.log_path): + postfix += 1 + log_base_path_new = log_base_path + "-" + str(postfix) + os.makedirs(log_base_path_new, exist_ok=True) + log_filename = f"out-{args.rank}" if args.log_local else "out.log" + args.log_path = os.path.join(log_base_path_new, log_filename) + # print( + # "Error. Experiment already exists. Use --name {} to specify a new experiment." + # ) + # return -1 + + # Set logger + args.log_level = logging.DEBUG if args.debug else logging.INFO + setup_logging(args.log_path, args.log_level) + + # fully initialize distributed device environment + device = init_distributed_device(args) + + args.wandb = "wandb" in args.report_to or "all" in args.report_to + args.tensorboard = "tensorboard" in args.report_to or "all" in args.report_to + if is_master(args): + args.tensorboard_path = ( + os.path.join(args.logs, args.name, "tensorboard") + if args.tensorboard + else "" + ) + args.checkpoint_path = os.path.join(args.logs, args.name, "checkpoints") + for dirname in [args.tensorboard_path, args.checkpoint_path]: + if dirname: + os.makedirs(dirname, exist_ok=True) + else: + args.tensorboard_path = "" + args.checkpoint_path = "" + + if args.copy_codebase: + copy_codebase(args) + + assert args.precision in ["amp", "fp16", "fp32"] + if args.precision == "fp16": + logging.warning( + "It is recommended to use AMP mixed-precision instead of FP16. " + "FP16 support needs further verification and tuning, especially for train." + ) + + if args.horovod: + logging.info( + f"Running in horovod mode with multiple processes / nodes. Device: {args.device}." + f"Process (global: {args.rank}, local {args.local_rank}), total {args.world_size}." + ) + elif args.distributed: + logging.info( + f"Running in distributed mode with multiple processes. Device: {args.device}." + f"Process (global: {args.rank}, local {args.local_rank}), total {args.world_size}." + ) + else: + logging.info(f"Running with a single process. Device {args.device}.") + + logging.info(f"openai cache dir: {os.path.expanduser(args.openai_model_cache_dir)}") + + # Create CLAP model + clap_model, clap_model_cfg = create_model( + args.amodel, + args.tmodel, + args.pretrained, + precision=args.precision, + device=device, + jit=args.torchscript, + force_quick_gelu=args.force_quick_gelu, + openai_model_cache_dir=os.path.expanduser(args.openai_model_cache_dir), + skip_params=False, + pretrained_audio=args.pretrained_audio, + pretrained_text=args.pretrained_text, + enable_fusion=args.enable_fusion, + fusion_type=args.fusion_type, + ) + + args.lp_out_ch = len(list(args.class_index_dict.keys())) + # Linear Probe + logging.info(f"linear probe using mlp: {args.lp_mlp}") + logging.info(f"linear probe using freeze: {args.lp_freeze}") + logging.info(f"linear probe act layer: {args.lp_act}") + logging.info(f"linear probe out ch: {args.lp_out_ch}") + logging.info(f"linear probe learning rate (if applicable): {args.lp_lr}") + logging.info(f"linear probe loss func: {args.lp_loss}") + logging.info(f"linear probe lp_metrics: {args.lp_metrics}") + + model = LinearProbe( + clap_model, + mlp=args.lp_mlp, + freeze=args.lp_freeze, + in_ch=512, + out_ch=args.lp_out_ch, + act=args.lp_act, + ) # in_ch is fixed (i.e., 512) + model = model.to(device) + + if args.horovod: + with torch.no_grad(): + for param in model.parameters(): + param.set_(param.contiguous()) + + if args.trace: + model = trace_model(model, batch_size=args.batch_size, device=device) + + if is_master(args): + logging.info("Linear Probe CLAP Model:") + logging.info(f"{str(clap_model)}") + logging.info("Params:") + params_file = os.path.join(args.logs, args.name, "params.txt") + with open(params_file, "w") as f: + for name in sorted(vars(args)): + val = getattr(args, name) + logging.info(f" {name}: {val}") + f.write(f"{name}: {val}\n") + + if args.distributed and not args.horovod: + if args.use_bn_sync: + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + ddp_args = {} + if args.ddp_static_graph: + # this doesn't exist in older PyTorch, arg only added if enabled + ddp_args["static_graph"] = True + model = torch.nn.parallel.DistributedDataParallel( + model, device_ids=[device], find_unused_parameters=True, **ddp_args + ) + + data = get_data(args, clap_model_cfg) + assert len(data), "At least one train or eval dataset must be specified." + if args.trace: + assert "train" not in data, "Cannot train with traced model" + + optimizer, scheduler, text_freeze_parameters = config_lp_optimizer( + model, data, args + ) + + scaler = GradScaler() if args.precision == "amp" else None + + # optionally resume from a checkpoint + start_epoch = 0 + if args.resume is not None: + if os.path.isfile(args.resume): + checkpoint = torch.load(args.resume, map_location=device) + if "epoch" in checkpoint: + # resuming a train checkpoint w/ epoch and optimizer state + start_epoch = checkpoint["epoch"] + sd = checkpoint["state_dict"] + if not args.distributed and next(iter(sd.items()))[0].startswith( + "module" + ): + sd = {k[len("module.") :]: v for k, v in sd.items()} + model.load_state_dict(sd) + if args.split_opt: + if optimizer is not None: + for k, o_ in optimizer.items(): + o_.load_state_dict(checkpoint[k + "_" + "optimizer"]) + if optimizer is not None: + optimizer.load_state_dict(checkpoint["optimizer"]) + if scaler is not None and "scaler" in checkpoint: + scaler.load_state_dict(checkpoint["scaler"]) + logging.info( + f"=> resuming checkpoint '{args.resume}' (epoch {start_epoch})" + ) + else: + # loading a bare (model only) checkpoint for fine-tune or evaluation + model.load_state_dict(checkpoint) + logging.info( + f"=> loaded checkpoint '{args.resume}' (epoch {start_epoch})" + ) + if args.freeze_text: + print("Freeze Text!!!!") + for k in text_freeze_parameters: + k.requires_grad = False + else: + logging.info("=> no checkpoint found at '{}'".format(args.resume)) + + cudnn.benchmark = True + cudnn.deterministic = False + + # determine if this worker should save logs and checkpoints. only do so if it is rank == 0 + args.save_logs = args.logs and args.logs.lower() != "none" and is_master(args) + writer = None + if args.save_logs and args.tensorboard: + assert tensorboard is not None, "Please install tensorboard." + writer = tensorboard.SummaryWriter(args.tensorboard_path) + + if args.wandb and is_master(args): + assert wandb is not None, "Please install wandb." + logging.debug("Starting wandb.") + args.train_sz = data["train"].dataloader.num_samples + if args.val_data is not None: + args.val_sz = data["val"].dataloader.num_samples + # you will have to configure this for your project! + wandb.init( + project="clap", + notes=args.wandb_notes, + name=args.wandb_notes, + tags=[], + config=vars(args), + ) + if args.debug: + wandb.watch(model, log="all") + wandb.save(params_file) + logging.debug("Finished loading wandb.") + + if "train" not in data: + evaluate(model, data, start_epoch, args, writer) + return + elif start_epoch == 0 and "val" in data and not args.no_eval: + evaluate(model, data, 0, args, writer) + if args.save_top_performance: + current_top_k_ckpt_metrics = { + i: 0 for i in range(args.save_top_performance) + } # initialize the top-k metric for ckpts to 0 + + for epoch in range(start_epoch, args.epochs): + # freeze the text param after (include) args.freeze_text_after, this is -1 by default + if epoch == args.freeze_text_after: + print("Text pretrained parameters are freezed since this epoch.") + for k in text_freeze_parameters: + k.requires_grad = False + if is_master(args): + logging.info(f"Start epoch {epoch}") + + train_one_epoch(model, data, epoch, optimizer, scaler, scheduler, args, writer) + completed_epoch = epoch + 1 + + if ( + any(v in data for v in ("val", "imagenet-val", "imagenet-v2")) + and not args.no_eval + ): + metrics = evaluate(model, data, completed_epoch, args, writer) + if args.save_top_performance: + top_k_dataset = args.top_k_checkpoint_select_dataset + top_k_metric = args.top_k_checkpoint_select_metric + filtered_metrics = [ + v + for k, v in metrics.items() + if top_k_metric in k and top_k_dataset in k + ] # check all R@10 metrics (all dataset) and use it to update the ckpt + # Saving checkpoints. + if args.save_logs: + opt_dict = { + k + "_" + "optimizer": v.state_dict() for k, v in optimizer.items() + } + checkpoint_dict = { + "epoch": completed_epoch, + "name": args.name, + "state_dict": model.state_dict(), + } + checkpoint_dict.update(opt_dict) + if scaler is not None: + checkpoint_dict["scaler"] = scaler.state_dict() + + if completed_epoch == args.epochs or ( + args.save_frequency > 0 and (completed_epoch % args.save_frequency) == 0 + ): + torch.save( + checkpoint_dict, + os.path.join(args.checkpoint_path, f"epoch_{completed_epoch}.pt"), + ) + if args.save_most_recent: + torch.save( + checkpoint_dict, + os.path.join(args.checkpoint_path, f"epoch_latest.pt"), + ) + if args.save_top_performance and not args.no_eval: + update_top_k_performance( + filtered_metrics, + current_top_k_ckpt_metrics, + args, + checkpoint_dict, + bignumbetter=True, + ) + + if args.wandb and is_master(args): + wandb.finish() + + +def copy_codebase(args): + from shutil import copytree, ignore_patterns + + new_code_path = os.path.join(args.logs, args.name, "code") + if os.path.exists(new_code_path): + print( + f"Error. Experiment already exists at {new_code_path}. Use --name to specify a new experiment." + ) + return -1 + print(f"Copying codebase to {new_code_path}") + current_code_path = os.path.realpath(__file__) + for _ in range(3): + current_code_path = os.path.dirname(current_code_path) + copytree( + current_code_path, new_code_path, ignore=ignore_patterns("log", "logs", "wandb") + ) + print("Done copying code.") + return 1 + + +if __name__ == "__main__": + main() diff --git a/src/audioldm/clap/training/lp_train.py b/src/audioldm/clap/training/lp_train.py new file mode 100644 index 0000000000000000000000000000000000000000..1c2a5458788acf014e443732a9813d6aa24b2852 --- /dev/null +++ b/src/audioldm/clap/training/lp_train.py @@ -0,0 +1,301 @@ +import json +import logging +import math +import os +import time +from contextlib import suppress + +import numpy as np +import torch +import torch.nn.functional as F + +try: + import wandb +except ImportError: + wandb = None + +from open_clip import LPLoss, LPMetrics, lp_gather_features +from open_clip.utils import do_mixup, get_mix_lambda +from .distributed import is_master +from .zero_shot import zero_shot_eval + + +class AverageMeter(object): + """Computes and stores the average and current value""" + + def __init__(self): + self.reset() + + def reset(self): + self.val = 0 + self.avg = 0 + self.sum = 0 + self.count = 0 + + def update(self, val, n=1): + self.val = val + self.sum += val * n + self.count += n + self.avg = self.sum / self.count + + +def unwrap_model(model): + if hasattr(model, "module"): + return model.module + else: + return model + + +def train_one_epoch( + model, + data, + epoch, + optimizer, + scaler, + scheduler, + args, + tb_writer=None, + extra_suffix="", +): + device = torch.device(args.device) + autocast = torch.cuda.amp.autocast if args.precision == "amp" else suppress + model.train() + loss = LPLoss(args.lp_loss) + + dataloader, sampler = data["train"].dataloader, data["train"].sampler + if args.distributed and sampler is not None: + sampler.set_epoch(epoch) + num_batches_per_epoch = dataloader.num_batches + sample_digits = math.ceil(math.log(dataloader.num_samples + 1, 10)) + + # for toy dataset + if args.dataset_type == "toy": + dataloader.dataset.generate_queue() + + loss_m = AverageMeter() + batch_time_m = AverageMeter() + data_time_m = AverageMeter() + end = time.time() + + for i, batch in enumerate(dataloader): + step = num_batches_per_epoch * epoch + i + + if isinstance(scheduler, dict): + for s in scheduler.values(): + s(step) + else: + scheduler(step) + + audio = batch # contains mel_spec, wavform, and longer list + class_label = batch["class_label"] + # audio = audio.to(device=device, non_blocking=True) + class_label = class_label.to(device=device, non_blocking=True) + + if args.mixup: + # https://github.com/RetroCirce/HTS-Audio-Transformer/blob/main/utils.py#L146 + mix_lambda = torch.from_numpy( + get_mix_lambda(0.5, len(audio["waveform"])) + ).to(device) + class_label = do_mixup(class_label, mix_lambda) + else: + mix_lambda = None + + data_time_m.update(time.time() - end) + if isinstance(optimizer, dict): + for o_ in optimizer.values(): + o_.zero_grad() + else: + optimizer.zero_grad() + + with autocast(): + pred = model(audio, mix_lambda=mix_lambda, device=device) + total_loss = loss(pred, class_label) + + if isinstance(optimizer, dict): + if scaler is not None: + scaler.scale(total_loss).backward() + for o_ in optimizer.values(): + if args.horovod: + o_.synchronize() + scaler.unscale_(o_) + with o_.skip_synchronize(): + scaler.step(o_) + else: + scaler.step(o_) + scaler.update() + else: + total_loss.backward() + for o_ in optimizer.values(): + o_.step() + else: + if scaler is not None: + scaler.scale(total_loss).backward() + if args.horovod: + optimizer.synchronize() + scaler.unscale_(optimizer) + with optimizer.skip_synchronize(): + scaler.step(optimizer) + else: + scaler.step(optimizer) + scaler.update() + else: + total_loss.backward() + optimizer.step() + + # Note: we clamp to 4.6052 = ln(100), as in the original paper. + with torch.no_grad(): + unwrap_model(model).clap_model.logit_scale_a.clamp_(0, math.log(100)) + unwrap_model(model).clap_model.logit_scale_t.clamp_(0, math.log(100)) + + batch_time_m.update(time.time() - end) + end = time.time() + batch_count = i + 1 + + if is_master(args) and (i % 100 == 0 or batch_count == num_batches_per_epoch): + if isinstance(audio, dict): + batch_size = len(audio["waveform"]) + else: + batch_size = len(audio) + num_samples = batch_count * batch_size * args.world_size + samples_per_epoch = dataloader.num_samples + percent_complete = 100.0 * batch_count / num_batches_per_epoch + + # NOTE loss is coarsely sampled, just master node and per log update + loss_m.update(total_loss.item(), batch_size) + if isinstance(optimizer, dict): + logging.info( + f"Train Epoch: {epoch} [{num_samples:>{sample_digits}}/{samples_per_epoch} ({percent_complete:.0f}%)] " + f"Loss: {loss_m.val:#.5g} ({loss_m.avg:#.4g}) " + f"Data (t): {data_time_m.avg:.3f} " + f"Batch (t): {batch_time_m.avg:.3f} " + f"LR: {[o_.param_groups[0]['lr'] for o_ in optimizer.values()]}" + ) + log_data = { + "loss": loss_m.val, + "data_time": data_time_m.val, + "batch_time": batch_time_m.val, + "lr": [o_.param_groups[0]["lr"] for o_ in optimizer.values()], + } + else: + logging.info( + f"Train Epoch: {epoch} [{num_samples:>{sample_digits}}/{samples_per_epoch} ({percent_complete:.0f}%)] " + f"Loss: {loss_m.val:#.5g} ({loss_m.avg:#.4g}) " + f"Data (t): {data_time_m.avg:.3f} " + f"Batch (t): {batch_time_m.avg:.3f} " + f"LR: {optimizer.param_groups[0]['lr']:5f} " + ) + + # Save train loss / etc. Using non avg meter values as loggers have their own smoothing + log_data = { + "loss": loss_m.val, + "data_time": data_time_m.val, + "batch_time": batch_time_m.val, + "lr": optimizer.param_groups[0]["lr"], + } + for name, val in log_data.items(): + name = f"train{extra_suffix}/{name}" + if tb_writer is not None: + tb_writer.add_scalar(name, val, step) + if args.wandb: + assert wandb is not None, "Please install wandb." + wandb.log({name: val, "step": step}) + + # resetting batch / data time meters per log window + batch_time_m.reset() + data_time_m.reset() + # end for + + +def evaluate(model, data, epoch, args, tb_writer=None, extra_suffix=""): + metrics = {} + if not args.parallel_eval: + if not is_master(args): + return metrics + device = torch.device(args.device) + model.eval() + + # CHANGE + # zero_shot_metrics = zero_shot_eval(model, data, epoch, args) + # metrics.update(zero_shot_metrics) + if is_master(args): + print("Evaluating...") + metric_names = args.lp_metrics.split(",") + eval_tool = LPMetrics(metric_names=metric_names) + + autocast = torch.cuda.amp.autocast if args.precision == "amp" else suppress + if "val" in data and ( + args.val_frequency + and ((epoch % args.val_frequency) == 0 or epoch == args.epochs) + ): + if args.parallel_eval: + dataloader, sampler = data["val"].dataloader, data["val"].sampler + if args.distributed and sampler is not None: + sampler.set_epoch(epoch) + samples_per_val = dataloader.num_samples + else: + dataloader = data["val"].dataloader + num_samples = 0 + samples_per_val = dataloader.num_samples + + eval_info = {"pred": [], "target": []} + with torch.no_grad(): + for i, batch in enumerate(dataloader): + audio = batch # contains mel_spec, wavform, and longer list + class_label = batch["class_label"] + + # audio = audio.to(device=device, non_blocking=True) + class_label = class_label.to(device=device, non_blocking=True) + + with autocast(): + pred = model(audio, device=device) + if args.parallel_eval: + pred, class_label = lp_gather_features( + pred, class_label, args.world_size, args.horovod + ) + eval_info["pred"].append(pred) + eval_info["target"].append(class_label) + + num_samples += class_label.shape[0] + + if (i % 100) == 0: # and i != 0: + logging.info( + f"Eval Epoch: {epoch} [{num_samples} / {samples_per_val}]" + ) + + if is_master(args): + eval_info["pred"] = torch.cat(eval_info["pred"], 0).cpu() + eval_info["target"] = torch.cat(eval_info["target"], 0).cpu() + metric_dict = eval_tool.evaluate_mertics( + eval_info["pred"], eval_info["target"] + ) + metrics.update(metric_dict) + if "epoch" not in metrics.keys(): + metrics.update({"epoch": epoch}) + + if is_master(args): + if not metrics: + return metrics + + logging.info( + f"Eval Epoch: {epoch} " + + "\n".join( + ["\t".join([f"{m}: {round(metrics[m], 4):.4f}"]) for m in metrics] + ) + ) + if args.save_logs: + for name, val in metrics.items(): + if tb_writer is not None: + tb_writer.add_scalar(f"val{extra_suffix}/{name}", val, epoch) + + with open(os.path.join(args.checkpoint_path, "results.jsonl"), "a+") as f: + f.write(json.dumps(metrics)) + f.write("\n") + + if args.wandb: + assert wandb is not None, "Please install wandb." + for name, val in metrics.items(): + wandb.log({f"val{extra_suffix}/{name}": val, "epoch": epoch}) + + return metrics + else: + return metrics diff --git a/src/audioldm/clap/training/main.py b/src/audioldm/clap/training/main.py new file mode 100644 index 0000000000000000000000000000000000000000..bdfa5b73e177fa87974a807826e25d955be4d2fc --- /dev/null +++ b/src/audioldm/clap/training/main.py @@ -0,0 +1,596 @@ +from inspect import getargs +import logging +import os +import random +from datetime import datetime +import bisect +import copy +import numpy as np +import torch +import torch.backends.cudnn as cudnn +from torch import optim +from torch.cuda.amp import GradScaler +import faulthandler +import pathlib + +try: + import wandb +except ImportError: + wandb = None + +try: + import torch.utils.tensorboard as tensorboard +except ImportError: + tensorboard = None + +try: + import horovod.torch as hvd +except ImportError: + hvd = None + +from open_clip import create_model_and_transforms, trace_model, create_model +from training.data import get_data +from training.distributed import is_master, init_distributed_device, world_info_from_env +from training.logger import setup_logging +from training.params import parse_args +from training.scheduler import cosine_lr +from training.train import train_one_epoch, evaluate +from open_clip.utils import dataset_split, get_optimizer + + +def maintain_ckpts(args, startidx, all_idx_len): + for i in reversed(range(startidx, all_idx_len)): + if os.path.exists(os.path.join(args.checkpoint_path, f"epoch_top_{i}.pt")): + os.rename( + os.path.join(args.checkpoint_path, f"epoch_top_{i}.pt"), + os.path.join(args.checkpoint_path, f"epoch_top_{i+1}.pt"), + ) + if os.path.exists( + os.path.join(args.checkpoint_path, f"epoch_top_{all_idx_len}.pt") + ): + os.remove(os.path.join(args.checkpoint_path, f"epoch_top_{all_idx_len}.pt")) + return + + +def update_top_k_performance( + new_metrics_inputs, current_top_k_ckpt_metrics, args, ckpt, bignumbetter=True +): + """ + Record the top-k performance of the current epoch. + current_top_k_metrics is a dictionary of the form: {1: top_1_ckpt_measure, 2: top_2_ckpt_measure, ...} + """ + if isinstance(new_metrics_inputs, (list, tuple)): + new_metrics_inputs = np.mean(new_metrics_inputs) + return update_top_k_performance( + new_metrics_inputs, + current_top_k_ckpt_metrics, + args=args, + ckpt=ckpt, + bignumbetter=bignumbetter, + ) + elif isinstance(new_metrics_inputs, dict): + new_metrics_inputs = np.mean(list(new_metrics_inputs.values())) + return update_top_k_performance( + new_metrics_inputs, + current_top_k_ckpt_metrics, + args=args, + ckpt=ckpt, + bignumbetter=bignumbetter, + ) + elif isinstance(new_metrics_inputs, (float, int)): + update_flag = {k: False for k in current_top_k_ckpt_metrics.keys()} + sorted_keys = sorted(current_top_k_ckpt_metrics.keys()) + sorted_values = sorted( + current_top_k_ckpt_metrics.values(), reverse=bignumbetter + ) + sorted_values_ = copy.deepcopy(sorted_values) + sorted_values.append(new_metrics_inputs) + sorted_values = sorted(sorted_values, reverse=bignumbetter) + sorted_values = sorted_values[:-1] + + if sorted_values == sorted_values_: + return current_top_k_ckpt_metrics, new_metrics_inputs + else: + for i in range(len(sorted_keys)): + if current_top_k_ckpt_metrics[sorted_keys[i]] != sorted_values[i]: + current_top_k_ckpt_metrics[sorted_keys[i]] = sorted_values[i] + update_flag[sorted_keys[i]] = True + for i in range(len(update_flag)): + if update_flag[i]: + maintain_ckpts(args, i, len(sorted_keys)) + torch.save( + ckpt, + os.path.join(args.checkpoint_path, f"epoch_top_{i}.pt"), + ) + break + return current_top_k_ckpt_metrics, new_metrics_inputs + + +# def updateifNone(a, b): +# a = b if None else a +# return a + + +def is_pretrained_params(n): + return ( + n.startswith("transformer") + or n in ["positional_embedding", "text_projection"] + or n.startswith("token_embedding") + or n.startswith("ln_final") + or n.startswith("logit_scale_t") + ) + + +def random_seed(seed=42, rank=0): + torch.manual_seed(seed + rank) + np.random.seed(seed + rank) + random.seed(seed + rank) + + +def main(): + args = parse_args() + # sanitize model name for filesystem / uri use, easier if we don't use / in name as a rule? + args.amodel = args.amodel.replace("/", "-") + # download sizes.json file + + # (yusong): the below two lines are for debug + # print("setting up faulthandler") + # faulthandler.register(10) + + random.seed(args.seed) + torch.manual_seed(args.seed) + torch.cuda.manual_seed(args.seed) + torch.cuda.manual_seed_all(args.seed) + np.random.seed(args.seed) + if args.tmodel == "bert" or args.tmodel == "roberta" or args.tmodel == "bart": + assert ( + args.pretrained == "" or args.pretrained is None + ), "bert/roberta/bart text encoder does not support pretrained models." + + # get the name of the experiments + if args.name is None: + args.name = "-".join( + [ + datetime.now().strftime("%Y_%m_%d-%H_%M_%S"), + f"model_{args.amodel}", + f"lr_{args.lr}", + f"b_{args.batch_size}", + f"j_{args.workers}", + f"p_{args.precision}", + ] + ) + + # discover initial world args early so we can log properly + args.distributed = False + args.local_rank, args.rank, args.world_size = world_info_from_env() + + if args.remotedata and is_master(args): + for dataset_name in args.datasetnames: + for split in dataset_split[dataset_name]: + if not os.path.exists(f"./json_files/{dataset_name}/{split}"): + os.makedirs(f"./json_files/{dataset_name}/{split}") + os.system( + f"aws s3 cp s3://s-laion-audio/webdataset_tar/{dataset_name}/{split}/sizes.json ./json_files/{dataset_name}/{split}/sizes.json" + ) + + args.log_path = None + if is_master(args, local=args.log_local): + log_base_path = os.path.join(args.logs, args.name) + os.makedirs(log_base_path, exist_ok=True) + log_filename = f"out-{args.rank}" if args.log_local else "out.log" + args.log_path = os.path.join(log_base_path, log_filename) + if os.path.exists(args.log_path): + print( + "Error. Experiment already exists. Use --name {} to specify a new experiment." + ) + return -1 + + # Set logger + args.log_level = logging.DEBUG if args.debug else logging.INFO + setup_logging(args.log_path, args.log_level) + + # fully initialize distributed device environment + device = init_distributed_device(args) + + args.wandb = "wandb" in args.report_to or "all" in args.report_to + args.tensorboard = "tensorboard" in args.report_to or "all" in args.report_to + if is_master(args): + args.tensorboard_path = ( + os.path.join(args.logs, args.name, "tensorboard") + if args.tensorboard + else "" + ) + args.checkpoint_path = os.path.join(args.logs, args.name, "checkpoints") + for dirname in [args.tensorboard_path, args.checkpoint_path]: + if dirname: + os.makedirs(dirname, exist_ok=True) + else: + args.tensorboard_path = "" + args.checkpoint_path = "" + + if args.copy_codebase: + copy_codebase(args) + + assert args.precision in ["amp", "fp16", "fp32"] + if args.precision == "fp16": + logging.warning( + "It is recommended to use AMP mixed-precision instead of FP16. " + "FP16 support needs further verification and tuning, especially for train." + ) + + if args.horovod: + logging.info( + f"Running in horovod mode with multiple processes / nodes. Device: {args.device}." + f"Process (global: {args.rank}, local {args.local_rank}), total {args.world_size}." + ) + elif args.distributed: + logging.info( + f"Running in distributed mode with multiple processes. Device: {args.device}." + f"Process (global: {args.rank}, local {args.local_rank}), total {args.world_size}." + ) + else: + logging.info(f"Running with a single process. Device {args.device}.") + + logging.info(f"openai cache dir: {os.path.expanduser(args.openai_model_cache_dir)}") + + model, model_cfg = create_model( + args.amodel, + args.tmodel, + args.pretrained, + precision=args.precision, + device=device, + jit=args.torchscript, + force_quick_gelu=args.force_quick_gelu, + openai_model_cache_dir=os.path.expanduser(args.openai_model_cache_dir), + skip_params=True, + pretrained_audio=args.pretrained_audio, + pretrained_text=args.pretrained_text, + enable_fusion=args.enable_fusion, + fusion_type=args.fusion_type, + ) + + if args.horovod: + with torch.no_grad(): + for param in model.parameters(): + param.set_(param.contiguous()) + + if args.trace: + model = trace_model(model, batch_size=args.batch_size, device=device) + + if is_master(args): + logging.info("Model:") + logging.info(f"{str(model)}") + logging.info("Params:") + params_file = os.path.join(args.logs, args.name, "params.txt") + with open(params_file, "w") as f: + for name in sorted(vars(args)): + val = getattr(args, name) + logging.info(f" {name}: {val}") + f.write(f"{name}: {val}\n") + + if args.distributed and not args.horovod: + if args.use_bn_sync: + model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model) + ddp_args = {} + if args.ddp_static_graph: + # this doesn't exist in older PyTorch, arg only added if enabled + ddp_args["static_graph"] = True + model = torch.nn.parallel.DistributedDataParallel( + model, device_ids=[device], find_unused_parameters=True, **ddp_args + ) + + data = get_data(args, model_cfg) + assert len(data), "At least one train or eval dataset must be specified." + if args.trace: + assert "train" not in data, "Cannot train with traced model" + + exclude = ( + lambda n, p: p.ndim < 2 + or "bn" in n + or "ln" in n + or "bias" in n + or "logit_scale" in n + ) + include = lambda n, p: not exclude(n, p) + + named_parameters = list(model.named_parameters()) + + # freeze text encoder + text_freeze_parameters = [p for n, p in named_parameters if "text_branch" in n] + + if args.freeze_text: + print("Freeze Text!!!!") + for k in text_freeze_parameters: + k.requires_grad = False + + gain_or_bias_params = [ + p for n, p in named_parameters if exclude(n, p) and p.requires_grad + ] + rest_params = [p for n, p in named_parameters if include(n, p) and p.requires_grad] + + # set wd-related params to 0 if use adam optimizer + if args.optimizer == "adam": + args.wd = 0 + args.wd_pretrained = 0 + args.wd_new = 0 + + if args.train_data is None: + optimizer = None + scheduler = None + else: + total_steps = data["train"].dataloader.num_batches * args.epochs + + if args.split_opt: + for x in ["lr", "beta1", "beta2", "eps", "wd"]: + for y in ["_new", "_pretrained"]: + if getattr(args, x + y) is None: + setattr(args, x + y, getattr(args, x)) + + gain_or_bias_pretrained_params = [ + p + for n, p in named_parameters + if (exclude(n, p) and p.requires_grad) and is_pretrained_params(n) + ] + rest_pretrained_params = [ + p + for n, p in named_parameters + if (include(n, p) and p.requires_grad) and is_pretrained_params(n) + ] + gain_or_bias_new_params = [ + p + for n, p in named_parameters + if (exclude(n, p) and p.requires_grad) and (not is_pretrained_params(n)) + ] + rest_new_params = [ + p + for n, p in named_parameters + if (include(n, p) and p.requires_grad) and (not is_pretrained_params(n)) + ] + pretrained_params_optimizer = get_optimizer( + [ + {"params": gain_or_bias_pretrained_params, "weight_decay": 0.0}, + { + "params": rest_pretrained_params, + "weight_decay": args.wd_pretrained, + }, + ], + lr=args.lr_pretrained, + betas=(args.beta1_pretrained, args.beta2_pretrained), + eps=args.eps_pretrained, + momentum=args.momentum_pretrained, + optimizer_name=args.optimizer, + ) + pretrained_params_scheduler = cosine_lr( + pretrained_params_optimizer, + args.lr_pretrained, + args.warmup, + total_steps, + ) + new_params_optimizer = get_optimizer( + [ + {"params": gain_or_bias_new_params, "weight_decay": 0.0}, + {"params": rest_new_params, "weight_decay": args.wd_new}, + ], + lr=args.lr_new, + betas=(args.beta1_new, args.beta2_new), + eps=args.eps_new, + momentum=args.momentum_new, + optimizer_name=args.optimizer, + ) + + new_params_scheduler = cosine_lr( + new_params_optimizer, args.lr_new, args.warmup, total_steps + ) + + optimizer = { + "pretrained": pretrained_params_optimizer, + "new": new_params_optimizer, + } + scheduler = { + "pretrained": pretrained_params_scheduler, + "new": new_params_scheduler, + } + + if args.horovod: + pretrained_params_optimizer = hvd.DistributedOptimizer( + pretrained_params_optimizer, + named_parameters=model.named_parameters(), + ) + new_params_optimizer = hvd.DistributedOptimizer( + new_params_optimizer, named_parameters=model.named_parameters() + ) + hvd.broadcast_parameters(model.state_dict(), root_rank=0) + hvd.broadcast_optimizer_state(pretrained_params_optimizer, root_rank=0) + hvd.broadcast_optimizer_state(new_params_optimizer, root_rank=0) + else: + optimizer = get_optimizer( + [ + {"params": gain_or_bias_params, "weight_decay": 0.0}, + {"params": rest_params, "weight_decay": args.wd}, + ], + lr=args.lr, + betas=(args.beta1, args.beta2), + eps=args.eps, + momentum=args.momentum, + optimizer_name=args.optimizer, + ) + + scheduler = cosine_lr(optimizer, args.lr, args.warmup, total_steps) + + if args.horovod: + optimizer = hvd.DistributedOptimizer( + optimizer, named_parameters=model.named_parameters() + ) + hvd.broadcast_parameters(model.state_dict(), root_rank=0) + hvd.broadcast_optimizer_state(optimizer, root_rank=0) + + scaler = GradScaler() if args.precision == "amp" else None + + # optionally resume from a checkpoint + start_epoch = 0 + if args.resume is not None: + if os.path.isfile(args.resume): + checkpoint = torch.load(args.resume, map_location=device) + if "epoch" in checkpoint: + # resuming a train checkpoint w/ epoch and optimizer state + start_epoch = checkpoint["epoch"] + sd = checkpoint["state_dict"] + if not args.distributed and next(iter(sd.items()))[0].startswith( + "module" + ): + sd = {k[len("module.") :]: v for k, v in sd.items()} + model.load_state_dict(sd) + if args.split_opt: + if optimizer is not None: + for k, o_ in optimizer.items(): + o_.load_state_dict(checkpoint[k + "_" + "optimizer"]) + if optimizer is not None: + optimizer.load_state_dict(checkpoint["optimizer"]) + if scaler is not None and "scaler" in checkpoint: + scaler.load_state_dict(checkpoint["scaler"]) + logging.info( + f"=> resuming checkpoint '{args.resume}' (epoch {start_epoch})" + ) + else: + # loading a bare (model only) checkpoint for fine-tune or evaluation + model.load_state_dict(checkpoint) + logging.info( + f"=> loaded checkpoint '{args.resume}' (epoch {start_epoch})" + ) + if args.freeze_text: + print("Freeze Text!!!!") + for k in text_freeze_parameters: + k.requires_grad = False + else: + logging.info("=> no checkpoint found at '{}'".format(args.resume)) + + cudnn.benchmark = True + cudnn.deterministic = False + + # determine if this worker should save logs and checkpoints. only do so if it is rank == 0 + args.save_logs = args.logs and args.logs.lower() != "none" and is_master(args) + writer = None + if args.save_logs and args.tensorboard: + assert tensorboard is not None, "Please install tensorboard." + writer = tensorboard.SummaryWriter(args.tensorboard_path) + + if args.wandb and is_master(args): + assert wandb is not None, "Please install wandb." + logging.debug("Starting wandb.") + args.train_sz = data["train"].dataloader.num_samples + if args.val_data is not None: + args.val_sz = data["val"].dataloader.num_samples + # you will have to configure this for your project! + wandb.init( + project="clap", + notes=args.wandb_notes, + name=args.wandb_notes, + tags=[], + config=vars(args), + ) + if args.debug: + wandb.watch(model, log="all") + wandb.save(params_file) + logging.debug("Finished loading wandb.") + + if "train" not in data: + evaluate(model, data, start_epoch, args, writer) + return + elif start_epoch == 0 and "val" in data and not args.no_eval: + evaluate(model, data, 0, args, writer) + # print(f'rank {args.rank}, Start First Evaluation')# (yusong): for debug + if args.save_top_performance: + current_top_k_ckpt_metrics = { + i: 0 for i in range(args.save_top_performance) + } # initialize the top-k metric for ckpts to 0 + + # print(f'rank {args.rank}, Start Training') # (yusong): for debug + for epoch in range(start_epoch, args.epochs): + # freeze the text param after (include) args.freeze_text_after, this is -1 by default + if epoch == args.freeze_text_after: + print("Text pretrained parameters are freezed since this epoch.") + for k in text_freeze_parameters: + k.requires_grad = False + if is_master(args): + logging.info(f"Start epoch {epoch}") + + train_one_epoch(model, data, epoch, optimizer, scaler, scheduler, args, writer) + completed_epoch = epoch + 1 + + if ( + any(v in data for v in ("val", "imagenet-val", "imagenet-v2")) + and not args.no_eval + ): + metrics = evaluate(model, data, completed_epoch, args, writer) + if args.save_top_performance: + top_k_dataset = args.top_k_checkpoint_select_dataset + top_k_metric = args.top_k_checkpoint_select_metric + filtered_metrics = [ + v + for k, v in metrics.items() + if top_k_metric in k and top_k_dataset in k + ] # check all R@10 metrics (all dataset) and use it to update the ckpt + # Saving checkpoints. + if args.save_logs: + if args.split_opt: + opt_dict = { + k + "_" + "optimizer": v.state_dict() for k, v in optimizer.items() + } + else: + opt_dict = {"optimizer": optimizer.state_dict()} + checkpoint_dict = { + "epoch": completed_epoch, + "name": args.name, + "state_dict": model.state_dict(), + } + checkpoint_dict.update(opt_dict) + if scaler is not None: + checkpoint_dict["scaler"] = scaler.state_dict() + + if completed_epoch == args.epochs or ( + args.save_frequency > 0 and (completed_epoch % args.save_frequency) == 0 + ): + torch.save( + checkpoint_dict, + os.path.join(args.checkpoint_path, f"epoch_{completed_epoch}.pt"), + ) + if args.save_most_recent: + torch.save( + checkpoint_dict, + os.path.join(args.checkpoint_path, f"epoch_latest.pt"), + ) + if args.save_top_performance and not args.no_eval: + update_top_k_performance( + filtered_metrics, + current_top_k_ckpt_metrics, + args, + checkpoint_dict, + bignumbetter=True, + ) + + if args.wandb and is_master(args): + wandb.finish() + + +def copy_codebase(args): + from shutil import copytree, ignore_patterns + + new_code_path = os.path.join(args.logs, args.name, "code") + if os.path.exists(new_code_path): + print( + f"Error. Experiment already exists at {new_code_path}. Use --name to specify a new experiment." + ) + return -1 + print(f"Copying codebase to {new_code_path}") + current_code_path = os.path.realpath(__file__) + for _ in range(3): + current_code_path = os.path.dirname(current_code_path) + copytree( + current_code_path, new_code_path, ignore=ignore_patterns("log", "logs", "wandb") + ) + print("Done copying code.") + return 1 + + +if __name__ == "__main__": + main() diff --git a/src/audioldm/clap/training/params.py b/src/audioldm/clap/training/params.py new file mode 100644 index 0000000000000000000000000000000000000000..22a5167e12df7b15c42915fc9bd7055434b818e3 --- /dev/null +++ b/src/audioldm/clap/training/params.py @@ -0,0 +1,569 @@ +import argparse +import os + +CACHE_DIR = os.getenv( + "AUDIOLDM_CACHE_DIR", + "~/.cache") + + + +def get_default_params(model_name): + # Params from paper (https://arxiv.org/pdf/2103.00020.pdf) + model_name = model_name.lower() + if "vit" in model_name: + return {"lr": 5.0e-4, "beta1": 0.9, "beta2": 0.98, "eps": 1.0e-6} + else: + return {"lr": 5.0e-4, "beta1": 0.9, "beta2": 0.999, "eps": 1.0e-8} + + +def parse_args(): + parser = argparse.ArgumentParser() + parser.add_argument( + "--train-data", + type=str, + default=None, + help="Path to h5 filewith training data", + ) + parser.add_argument( + "--val-data", + type=str, + default=None, + help="Path to h5 file with validation data", + ) + parser.add_argument( + "--freeze-text", + default=False, + action="store_true", + help="if you need to freeze the text encoder, make this True", + ) + parser.add_argument( + "--freeze-text-after", + type=int, + default=-1, + help="if you need to freeze the text encoder after (include) epoch x, set this param to x. Set -1 to disable it", + ) + parser.add_argument( + "--train-ipc", + type=str, + default=None, + help="Path to npy file of the number of instance per class in training data", + ) + parser.add_argument( + "--val-ipc", + type=str, + default=None, + help="Path to npy file of the number of instance per class in validation data", + ) + parser.add_argument( + "--train-num-samples", + type=int, + default=None, + help="Number of samples in dataset. Required for webdataset if not available in info file.", + ) + parser.add_argument( + "--val-num-samples", + type=int, + default=None, + help="Number of samples in dataset. Useful for webdataset if not available in info file.", + ) + parser.add_argument( + "--dataset-type", + choices=["webdataset", "csv", "auto", "toy"], + default="auto", + help="Which type of dataset to process.", + ) + parser.add_argument( + "--csv-separator", + type=str, + default="\t", + help="For csv-like datasets, which separator to use.", + ) + parser.add_argument( + "--csv-img-key", + type=str, + default="filepath", + help="For csv-like datasets, the name of the key for the image paths.", + ) + parser.add_argument( + "--csv-caption-key", + type=str, + default="title", + help="For csv-like datasets, the name of the key for the captions.", + ) + parser.add_argument( + "--imagenet-val", + type=str, + default=None, + help="Path to imagenet val set for conducting zero shot evaluation.", + ) + parser.add_argument( + "--imagenet-v2", + type=str, + default=None, + help="Path to imagenet v2 for conducting zero shot evaluation.", + ) + parser.add_argument( + "--datasetnames", + nargs="+", + default=None, + help="If loading webdataset, spedify the dataset names to load. Can be some of these: Clotho, audioset, audiocaps, BBCSoundEffects", + ) + parser.add_argument( + "--full-train-dataset", + nargs="+", + default=None, + help="Which dataset will be trained with all the subsets. (train+test)", + ) + parser.add_argument( + "--exclude-eval-dataset", + nargs="+", + default=None, + help="Which dataset will be excluded with evaluation", + ) + parser.add_argument( + "--datasetinfos", + nargs="+", + default=None, + help="If loading webdataset, spedify the dataset types to load. Can be some of these: train, test, valid, unbalanced_train, balanced_train, eval", + ) + parser.add_argument( + "--dataset-proportion", + type=float, + default=1.0, + help="How much proportion of dataset we want to train.", + ) + parser.add_argument( + "--remotedata", + default=False, + action="store_true", + help="if the dataset is remote, set this flag", + ) + parser.add_argument( + "--class-label-path", + type=str, + default=None, + help="The path of the class label pickle or csv.", + ) + parser.add_argument( + "--datasetpath", + type=str, + default="/mnt/audio_clip/webdataset_tar", + help="The path to the dataset", + ) + parser.add_argument( + "--logs", + type=str, + default="./logs/", + help="Where to store tensorboard logs. Use None to avoid storing logs.", + ) + parser.add_argument( + "--log-local", + action="store_true", + default=False, + help="log files on local master, otherwise global master only.", + ) + parser.add_argument( + "--name", + type=str, + default=None, + help="Optional identifier for the experiment when storing logs. Otherwise use current time.", + ) + parser.add_argument( + "--workers", type=int, default=1, help="Number of workers per GPU." + ) + parser.add_argument( + "--batch-size", type=int, default=64, help="Batch size per GPU." + ) + parser.add_argument( + "--epochs", type=int, default=32, help="Number of epochs to train for." + ) + parser.add_argument("--lr", type=float, default=None, help="Learning rate.") + parser.add_argument("--beta1", type=float, default=None, help="Adam beta 1.") + parser.add_argument("--beta2", type=float, default=None, help="Adam beta 2.") + parser.add_argument("--eps", type=float, default=None, help="Adam epsilon.") + parser.add_argument("--momentum", type=float, default=None, help="SGD epsilon.") + parser.add_argument("--wd", type=float, default=0.2, help="Weight decay.") + + parser.add_argument( + "--split-opt", + action="store_true", + default=False, + help="Use this flag to skip the learning rate decay.", + ) + parser.add_argument( + "--lr-pretrained", type=float, default=None, help="Learning rate for text." + ) + parser.add_argument( + "--beta1-pretrained", type=float, default=None, help="Adam beta 1 for text." + ) + parser.add_argument( + "--beta2-pretrained", type=float, default=None, help="Adam beta 2 for text." + ) + parser.add_argument( + "--eps-pretrained", type=float, default=None, help="Adam epsilon for text." + ) + parser.add_argument( + "--wd-pretrained", type=float, default=0.2, help="Weight decay for text." + ) + parser.add_argument( + "--momentum-pretrained", type=float, default=0.9, help="Momentum for text." + ) + parser.add_argument( + "--lr-new", type=float, default=None, help="Learning rate for audio." + ) + parser.add_argument( + "--beta1-new", type=float, default=None, help="Adam beta 1 for audio." + ) + parser.add_argument( + "--beta2-new", type=float, default=None, help="Adam beta 2 for audio." + ) + parser.add_argument( + "--eps-new", type=float, default=None, help="Adam epsilon for audio." + ) + parser.add_argument( + "--wd-new", type=float, default=0.2, help="Weight decay for audio." + ) + parser.add_argument( + "--momentum-new", type=float, default=0.9, help="Momentum for audio." + ) + parser.add_argument( + "--warmup", type=int, default=10000, help="Number of steps to warmup for." + ) + parser.add_argument( + "--use-bn-sync", + default=False, + action="store_true", + help="Whether to use batch norm sync.", + ) + parser.add_argument( + "--skip-scheduler", + action="store_true", + default=False, + help="Use this flag to skip the learning rate decay.", + ) + parser.add_argument( + "--save-frequency", type=int, default=1, help="How often to save checkpoints." + ) + parser.add_argument( + "--save-top-performance", + type=int, + default=0, + help="Save the top x performance weights if the value >0", + ) + parser.add_argument( + "--save-most-recent", + action="store_true", + default=False, + help="Always save the most recent model trained to epoch_latest.pt.", + ) + parser.add_argument( + "--zeroshot-frequency", type=int, default=2, help="How often to run zero shot." + ) + parser.add_argument( + "--val-frequency", + type=int, + default=1, + help="How often to run evaluation with val data.", + ) + parser.add_argument( + "--resume", + default=None, + type=str, + help="path to latest checkpoint (default: none)", + ) + parser.add_argument( + "--precision", + choices=["amp", "fp16", "fp32"], + default="amp", + help="Floating point precision.", + ) + parser.add_argument( + "--amodel", + type=str, + default="RN50", + help="Name of the audio backbone to use.", + ) + parser.add_argument( + "--tmodel", + type=str, + default="transformer", + help="Name of the text backbone to use. Can be [transformer, bert, roberta, bart]", + ) + parser.add_argument( + "--pretrained-audio", + default="", + type=str, + help="Use a pretrained audio model weights for the audio encoder of CLAP", + ) + parser.add_argument( + "--pretrained-text", + default="", + type=str, + help="Use a pretrained text model weights for the text encoder of CLAP", + ) + parser.add_argument( + "--pretrained", + default="", + type=str, + help="Use a pretrained CLIP model weights with the specified tag or file path.", + ) + parser.add_argument( + "--pretrained-image", + default=False, + action="store_true", + help="Load imagenet pretrained weights for image tower backbone if available.", + ) + parser.add_argument( + "--lock-image", + default=False, + action="store_true", + help="Lock full image tower by disabling gradients.", + ) + parser.add_argument( + "--lock-image-unlocked-groups", + type=int, + default=0, + help="Leave last n image tower layer groups unlocked.", + ) + parser.add_argument( + "--lock-image-freeze-bn-stats", + default=False, + action="store_true", + help="Freeze BatchNorm running stats in image tower for any locked layers.", + ) + parser.add_argument( + "--local-loss", + default=False, + action="store_true", + help="calculate loss w/ local features @ global (instead of realizing full global @ global matrix)", + ) + parser.add_argument( + "--gather-with-grad", + default=False, + action="store_true", + help="enable full distributed gradient for feature gather", + ) + parser.add_argument( + "--force-quick-gelu", + default=False, + action="store_true", + help="Force use of QuickGELU activation for non-OpenAI transformer models.", + ) + parser.add_argument( + "--torchscript", + default=False, + action="store_true", + help="torch.jit.script the model, also uses jit version of OpenAI models if pretrained=='openai'", + ) + parser.add_argument( + "--trace", + default=False, + action="store_true", + help="torch.jit.trace the model for inference / eval only", + ) + # arguments for distributed training + parser.add_argument( + "--dist-url", + default="env://", + type=str, + help="url used to set up distributed training", + ) + parser.add_argument( + "--dist-backend", default="nccl", type=str, help="distributed backend" + ) + parser.add_argument( + "--report-to", + default="", + type=str, + help="Options are ['wandb', 'tensorboard', 'wandb,tensorboard']", + ) + parser.add_argument( + "--wandb-notes", default="", type=str, help="Notes if logging with wandb" + ) + parser.add_argument( + "--C", type=float, default=3.16, help="inverse regularizer for logistic reg." + ) + parser.add_argument( + "--debug", + default=False, + action="store_true", + help="If true, more information is logged.", + ) + parser.add_argument( + "--copy-codebase", + default=False, + action="store_true", + help="If true, we copy the entire base on the log diretory, and execute from there.", + ) + parser.add_argument( + "--horovod", + default=False, + action="store_true", + help="Use horovod for distributed training.", + ) + parser.add_argument( + "--ddp-static-graph", + default=False, + action="store_true", + help="Enable static graph optimization for DDP in PyTorch >= 1.11.", + ) + parser.add_argument( + "--no-set-device-rank", + default=False, + action="store_true", + help="Don't set device index from local rank (when CUDA_VISIBLE_DEVICES restricted to one per proc).", + ) + parser.add_argument("--seed", type=int, default=4242, help="Default random seed.") + + parser.add_argument( + "--top-k-checkpoint-select-dataset", + type=str, + default="all", + help="The dataset of selecting top-k checkpoint.", + ) + + # @R10, @R@5, @R1, mAP@10 + parser.add_argument( + "--top-k-checkpoint-select-metric", + type=str, + default="_R@10", + help="The metric for selecting top-k checkpoint.", + ) + parser.add_argument( + "--openai-model-cache-dir", + type=str, + default=f"{CACHE_DIR}/clip", + help="Directory to download OpenAI models.", + ) + parser.add_argument( + "--optimizer", + type=str, + default="adamw", + help="can be AdamW or SGD", + ) + parser.add_argument( + "--parallel-eval", + default=False, + action="store_true", + help="Eval in parallel (multi-GPU, multi-node).", + ) + + parser.add_argument( + "--no-eval", + default=False, + action="store_true", + help="Training without evaluation.", + ) + + parser.add_argument( + "--lp-mlp", + default=False, + action="store_true", + help="Linear Probe using MLP layer or not.", + ) + + parser.add_argument( + "--lp-freeze", + default=False, + action="store_true", + help="Linear Probe using Freeze CLAP or not", + ) + + parser.add_argument( + "--lp-act", + default="None", + type=str, + help="Options are ['relu','elu','prelu','softmax','sigmoid']", + ) + + parser.add_argument( + "--lp-loss", type=str, default="bce", help="Loss func of Linear Probe." + ) + + parser.add_argument( + "--lp-metrics", + type=str, + default="map,mauc,acc", + help="Metrics of Linear Probe.", + ) + + parser.add_argument( + "--lp-lr", type=float, default=1e-4, help="learning rate of linear probe" + ) + parser.add_argument( + "--kappa", + type=float, + default=0, + help="the kappa in the weighted contrastive loss, default is to turn off the weighted contrastive loss", + ) + + parser.add_argument( + "--data-filling", + type=str, + default="pad", + help="type of data filling when the audio length is shorter than the max length." + "Can be one of the following: repeat, repeatpad, pad", + ) + parser.add_argument( + "--data-truncating", + type=str, + default="rand_trunc", + help="type of data truncation when the audio length is longer than the max length." + "Can be one of the following: rand_trunc, fusion", + ) + + parser.add_argument( + "--clap-mlploss", + default=False, + action="store_true", + help="Using MLP loss for CLAP model or not", + ) + + parser.add_argument( + "--wandb-id", + type=str, + default=None, + help="the id of wandb experiment to restore.", + ) + + parser.add_argument( + "--sleep", type=float, default=0, help="sleep n seconds before start training" + ) + + # variable length processing + parser.add_argument( + "--enable-fusion", + default=False, + action="store_true", + help="Enable feature funsion for variable-length data", + ) + + parser.add_argument( + "--fusion-type", + type=str, + default="None", + help="Type is among ['channel_map', 'daf_1d','aff_1d','iaff_1d','daf_2d','aff_2d','iaff_2d']", + ) + + parser.add_argument( + "--mixup", + default=False, + action="store_true", + help="Enable mixup in finetuning training.", + ) + parser.add_argument( + "--text-augment-selection", + type=str, + default=None, + help="For selecting levels of augmented text. Type is among ['all', 'augment_only', 'none']", + ) + + args = parser.parse_args() + + # If some params are not passed, we use the default values based on model name. + default_params = get_default_params(args.amodel) + for name, val in default_params.items(): + if getattr(args, name) is None: + setattr(args, name, val) + + return args diff --git a/src/audioldm/clap/training/scheduler.py b/src/audioldm/clap/training/scheduler.py new file mode 100644 index 0000000000000000000000000000000000000000..87cecdb228cd2519aada596f5fa2919cb6e9feba --- /dev/null +++ b/src/audioldm/clap/training/scheduler.py @@ -0,0 +1,24 @@ +import numpy as np + + +def assign_learning_rate(optimizer, new_lr): + for param_group in optimizer.param_groups: + param_group["lr"] = new_lr + + +def _warmup_lr(base_lr, warmup_length, step): + return base_lr * (step + 1) / warmup_length + + +def cosine_lr(optimizer, base_lr, warmup_length, steps): + def _lr_adjuster(step): + if step < warmup_length: + lr = _warmup_lr(base_lr, warmup_length, step) + else: + e = step - warmup_length + es = steps - warmup_length + lr = 0.5 * (1 + np.cos(np.pi * e / es)) * base_lr + assign_learning_rate(optimizer, lr) + return lr + + return _lr_adjuster diff --git a/src/audioldm/clap/training/train.py b/src/audioldm/clap/training/train.py new file mode 100644 index 0000000000000000000000000000000000000000..b98747d56f8a8564ee327025daa76a37ce896427 --- /dev/null +++ b/src/audioldm/clap/training/train.py @@ -0,0 +1,838 @@ +import json +import logging +import math +import os +import time +from contextlib import suppress + +import numpy as np +import torch +import torch.nn.functional as F + +try: + import wandb +except ImportError: + wandb = None + +from open_clip import ClipLoss, gather_features +from .distributed import is_master +from .zero_shot import zero_shot_eval + + +class AverageMeter(object): + """Computes and stores the average and current value""" + + def __init__(self): + self.reset() + + def reset(self): + self.val = 0 + self.avg = 0 + self.sum = 0 + self.count = 0 + + def update(self, val, n=1): + self.val = val + self.sum += val * n + self.count += n + self.avg = self.sum / self.count + + +def unwrap_model(model): + if hasattr(model, "module"): + return model.module + else: + return model + + +def train_one_epoch( + model, data, epoch, optimizer, scaler, scheduler, args, tb_writer=None +): + device = torch.device(args.device) + autocast = torch.cuda.amp.autocast if args.precision == "amp" else suppress + model.train() + loss = ClipLoss( + local_loss=args.local_loss, + gather_with_grad=args.gather_with_grad, + cache_labels=True, + rank=args.rank, + world_size=args.world_size, + use_horovod=args.horovod, + mlp_loss=args.clap_mlploss, + weight_loss_kappa=args.kappa, + ) + + dataloader, sampler = data["train"].dataloader, data["train"].sampler + if args.distributed and sampler is not None: + sampler.set_epoch(epoch) + num_batches_per_epoch = dataloader.num_batches + sample_digits = math.ceil(math.log(dataloader.num_samples + 1, 10)) + + # for toy dataset + if args.dataset_type == "toy": + dataloader.dataset.generate_queue() + + loss_m = AverageMeter() + batch_time_m = AverageMeter() + data_time_m = AverageMeter() + end = time.time() + + for i, batch in enumerate(dataloader): + # logging.info(f"batch {i} of {num_batches_per_epoch}") + step = num_batches_per_epoch * epoch + i + if isinstance(scheduler, dict): + for s in scheduler.values(): + s(step) + else: + scheduler(step) + audios = batch # contains mel_spec, wavform, and longer list + texts = batch["text"] + # audios = audios.to(device=device, non_blocking=True) + # texts = texts.to(device=device, non_blocking=True) + + data_time_m.update(time.time() - end) + if isinstance(optimizer, dict): + for o_ in optimizer.values(): + o_.zero_grad() + else: + optimizer.zero_grad() + + with autocast(): + ( + audio_features, + text_features, + audio_features_mlp, + text_features_mlp, + logit_scale_a, + logit_scale_t, + ) = model(audios, texts, device) + + if args.clap_mlploss: + total_loss = loss( + audio_features=audio_features, + text_features=text_features, + logit_scale_a=logit_scale_a, + logit_scale_t=logit_scale_t, + audio_features_mlp=audio_features_mlp, + text_features_mlp=text_features_mlp, + ) + else: + total_loss = loss( + audio_features=audio_features, + text_features=text_features, + logit_scale_a=logit_scale_a, + ) + if isinstance(optimizer, dict): + if scaler is not None: + scaler.scale(total_loss).backward() + for o_ in optimizer.values(): + if args.horovod: + o_.synchronize() + scaler.unscale_(o_) + with o_.skip_synchronize(): + scaler.step(o_) + else: + scaler.step(o_) + scaler.update() + else: + total_loss.backward() + for o_ in optimizer.values(): + o_.step() + else: + if scaler is not None: + scaler.scale(total_loss).backward() + if args.horovod: + optimizer.synchronize() + scaler.unscale_(optimizer) + with optimizer.skip_synchronize(): + scaler.step(optimizer) + else: + scaler.step(optimizer) + scaler.update() + else: + total_loss.backward() + optimizer.step() + + # Note: we clamp to 4.6052 = ln(100), as in the original paper. + with torch.no_grad(): + unwrap_model(model).logit_scale_a.clamp_(0, math.log(100)) + if args.clap_mlploss: + unwrap_model(model).logit_scale_t.clamp_(0, math.log(100)) + + batch_time_m.update(time.time() - end) + end = time.time() + batch_count = i + 1 + if is_master(args) and (i % 100 == 0 or batch_count == num_batches_per_epoch): + if isinstance(audios, dict): + batch_size = len(audios["waveform"]) + else: + batch_size = len(audios) + num_samples = batch_count * batch_size * args.world_size + samples_per_epoch = dataloader.num_samples + percent_complete = 100.0 * batch_count / num_batches_per_epoch + + # NOTE loss is coarsely sampled, just master node and per log update + loss_m.update(total_loss.item(), batch_size) + logit_scale_scalar_a = logit_scale_a.item() + logit_scale_scalar_t = logit_scale_t.item() + if isinstance(optimizer, dict): + if args.clap_mlploss: + logging.info( + f"Train Epoch: {epoch} [{num_samples:>{sample_digits}}/{samples_per_epoch} ({percent_complete:.0f}%)] " + f"Loss: {loss_m.val:#.5g} ({loss_m.avg:#.4g}) " + f"Data (t): {data_time_m.avg:.3f} " + f"Batch (t): {batch_time_m.avg:.3f} " + f"LR: {[o_.param_groups[0]['lr'] for o_ in optimizer.values()]} " + f"Logit Scale Audio: {logit_scale_scalar_a:.3f}" + f"Logit Scale Text: {logit_scale_scalar_t:.3f}" + ) + log_data = { + "loss": loss_m.val, + "data_time": data_time_m.val, + "batch_time": batch_time_m.val, + "scale_audio": logit_scale_scalar_a, + "scale_text": logit_scale_scalar_t, + "lr": [o_.param_groups[0]["lr"] for o_ in optimizer.values()], + } + else: + logging.info( + f"Train Epoch: {epoch} [{num_samples:>{sample_digits}}/{samples_per_epoch} ({percent_complete:.0f}%)] " + f"Loss: {loss_m.val:#.5g} ({loss_m.avg:#.4g}) " + f"Data (t): {data_time_m.avg:.3f} " + f"Batch (t): {batch_time_m.avg:.3f} " + f"LR: {[o_.param_groups[0]['lr'] for o_ in optimizer.values()]} " + f"Logit Scale Audio: {logit_scale_scalar_a:.3f}" + ) + log_data = { + "loss": loss_m.val, + "data_time": data_time_m.val, + "batch_time": batch_time_m.val, + "scale_audio": logit_scale_scalar_a, + "lr": [o_.param_groups[0]["lr"] for o_ in optimizer.values()], + } + + else: + if args.clap_mlploss: + logging.info( + f"Train Epoch: {epoch} [{num_samples:>{sample_digits}}/{samples_per_epoch} ({percent_complete:.0f}%)] " + f"Loss: {loss_m.val:#.5g} ({loss_m.avg:#.4g}) " + f"Data (t): {data_time_m.avg:.3f} " + f"Batch (t): {batch_time_m.avg:.3f} " + f"LR: {optimizer.param_groups[0]['lr']:5f} " + f"Logit Scale Audio: {logit_scale_scalar_a:.3f}" + f"Logit Scale Text: {logit_scale_scalar_t:.3f}" + ) + + # Save train loss / etc. Using non avg meter values as loggers have their own smoothing + log_data = { + "loss": loss_m.val, + "data_time": data_time_m.val, + "batch_time": batch_time_m.val, + "scale_audio": logit_scale_scalar_a, + "scale_text": logit_scale_scalar_t, + "lr": optimizer.param_groups[0]["lr"], + } + else: + logging.info( + f"Train Epoch: {epoch} [{num_samples:>{sample_digits}}/{samples_per_epoch} ({percent_complete:.0f}%)] " + f"Loss: {loss_m.val:#.5g} ({loss_m.avg:#.4g}) " + f"Data (t): {data_time_m.avg:.3f} " + f"Batch (t): {batch_time_m.avg:.3f} " + f"LR: {optimizer.param_groups[0]['lr']:5f} " + f"Logit Scale Audio: {logit_scale_scalar_a:.3f}" + ) + + # Save train loss / etc. Using non avg meter values as loggers have their own smoothing + log_data = { + "loss": loss_m.val, + "data_time": data_time_m.val, + "batch_time": batch_time_m.val, + "scale_audio": logit_scale_scalar_a, + "lr": optimizer.param_groups[0]["lr"], + } + for name, val in log_data.items(): + name = "train/" + name + if tb_writer is not None: + tb_writer.add_scalar(name, val, step) + if args.wandb: + assert wandb is not None, "Please install wandb." + wandb.log({name: val, "step": step}) + + # resetting batch / data time meters per log window + batch_time_m.reset() + data_time_m.reset() + # end for + + +def evaluate(model, data, epoch, args, tb_writer=None): + metrics = {} + if not args.parallel_eval: + if not is_master(args): + return metrics + device = torch.device(args.device) + model.eval() + + # CHANGE + # zero_shot_metrics = zero_shot_eval(model, data, epoch, args) + # metrics.update(zero_shot_metrics) + if is_master(args): + print("Evaluating...") + autocast = torch.cuda.amp.autocast if args.precision == "amp" else suppress + if args.val_dataset_names == ["Clotho", "audiocaps"]: + # if only clotho and audiocaps are used, then we will use a different evaluation function. + # This is because in the Clotho and audiocaps valid and test set, there are 5 text for 1 audio. + if args.parallel_eval: + # (yusong): just a hack here. Don't use parallel eval when evaluating only clotho and audiocaps. + raise NotImplementedError( + "Parallel evaluation not supported for eval only Clotho and audiocaps." + ) + val_metrics_per_dataset = evaluate_clotho_audiocaps( + model, data, epoch, args, autocast, device, tb_writer + ) + for m in val_metrics_per_dataset.values(): + metrics.update(m) + if "epoch" not in metrics.keys(): + metrics.update({"epoch": epoch}) + metrics = select_top_metric_clotho_audiocaps( + metrics, val_metrics_per_dataset, args + ) + elif "val" in data and ( + args.val_frequency + and ((epoch % args.val_frequency) == 0 or epoch == args.epochs) + ): + dataloader = data["val"].dataloader + num_samples = 0 + samples_per_val = dataloader.num_samples + + # FIXME this does not scale past small eval datasets + # all_audio_features @ all_text_features will blow up memory and compute very quickly + eval_info = {} + if args.clap_mlploss: + eval_info["all"] = { + "cumulative_loss": 0.0, + "num_samples": 0, + "all_audio_features": [], + "all_text_features": [], + "all_audio_features_mlp": [], + "all_text_features_mlp": [], + } # cumulative_loss = 0.0 + else: + eval_info["all"] = { + "cumulative_loss": 0.0, + "num_samples": 0, + "all_audio_features": [], + "all_text_features": [], + } # cumu + # all_audio_features, all_text_features, all_audio_features_mlp, all_text_features_mlp = [], [], [], [] + with torch.no_grad(): + for i, batch in enumerate(dataloader): + audios = batch # contains mel_spec, wavform, and longer list + texts = batch["text"] + # audios = audios.to(device=device, non_blocking=True) + + all_names = list( + set(["-".join(b.split("/")[-3:-1]) for b in batch["__url__"]]) + ) + for name in all_names: + if name not in eval_info.keys(): + if args.clap_mlploss: + eval_info[name] = { + "cumulative_loss": 0.0, + "num_samples": 0, + "all_audio_features": [], + "all_text_features": [], + "all_audio_features_mlp": [], + "all_text_features_mlp": [], + } + else: + eval_info[name] = { + "cumulative_loss": 0.0, + "num_samples": 0, + "all_audio_features": [], + "all_text_features": [], + } + with autocast(): + ( + audio_features, + text_features, + audio_features_mlp, + text_features_mlp, + logit_scale_a, + logit_scale_t, + ) = model(audios, texts, device) + + if args.parallel_eval: + # multi-GPU eval + if args.clap_mlploss: + ( + audio_features, + text_features, + audio_features_mlp, + text_features_mlp, + ) = gather_features( + audio_features=audio_features, + text_features=text_features, + audio_features_mlp=audio_features_mlp, + text_features_mlp=text_features_mlp, + local_loss=False, + gather_with_grad=False, + rank=args.rank, + world_size=args.world_size, + use_horovod=args.horovod, + mlp_loss=args.clap_mlploss, + ) + else: + (audio_features, text_features,) = gather_features( + audio_features=audio_features, + text_features=text_features, + local_loss=False, + gather_with_grad=False, + rank=args.rank, + world_size=args.world_size, + use_horovod=args.horovod, + mlp_loss=args.clap_mlploss, + ) + + if is_master(args): + num_samples += audio_features.shape[0] + for n in [*all_names, "all"]: + if n == "all": + eval_info[n]["all_audio_features"].append( + audio_features.cpu() + ) + eval_info[n]["all_text_features"].append( + text_features.cpu() + ) + if args.clap_mlploss: + eval_info[n]["all_audio_features_mlp"].append( + audio_features_mlp.cpu() + ) + eval_info[n]["all_text_features_mlp"].append( + text_features_mlp.cpu() + ) + else: + idx = np.where( + np.array( + [ + "-".join(b.split("/")[-3:-1]) + for b in batch["__url__"] + ] + ) + == n + )[0] + eval_info[n]["all_audio_features"].append( + audio_features.cpu().index_select( + 0, torch.tensor(idx).long() + ) + ) + eval_info[n]["all_text_features"].append( + text_features.cpu().index_select( + 0, torch.tensor(idx).long() + ) + ) + if args.clap_mlploss: + eval_info[n]["all_audio_features_mlp"].append( + audio_features_mlp.cpu().index_select( + 0, torch.tensor(idx).long() + ) + ) + eval_info[n]["all_text_features_mlp"].append( + text_features_mlp.cpu().index_select( + 0, torch.tensor(idx).long() + ) + ) + # print(f'eval step {i}') # (yusong): for debug + + # cumulative_loss += total_loss * batch_size + # num_samples += batch_size + if is_master(args) and (i % 100) == 0: # and i != 0: + logging.info( + f"Eval Epoch: {epoch} [{num_samples} / {samples_per_val}]" + ) + if is_master(args): + val_metrics_per_dataset = {} + for n in eval_info.keys(): + if args.clap_mlploss: + metrics_single_dataset = get_metrics( + audio_features=torch.cat( + eval_info[n]["all_audio_features"] + ), + text_features=torch.cat(eval_info[n]["all_text_features"]), + logit_scale_a=logit_scale_a.cpu(), + audio_features_mlp=torch.cat( + eval_info[n]["all_audio_features_mlp"] + ), + text_features_mlp=torch.cat( + eval_info[n]["all_text_features_mlp"] + ), + logit_scale_t=logit_scale_t.cpu(), + mlp_loss=args.clap_mlploss, + ) + else: + metrics_single_dataset = get_metrics( + audio_features=torch.cat( + eval_info[n]["all_audio_features"] + ), + text_features=torch.cat(eval_info[n]["all_text_features"]), + logit_scale_a=logit_scale_a.cpu(), + mlp_loss=args.clap_mlploss, + ) + val_metrics_per_dataset[n] = { + n + "/" + k: v for k, v in metrics_single_dataset.items() + } + metrics.update(val_metrics_per_dataset[n]) + if "epoch" not in metrics.keys(): + metrics.update({"epoch": epoch}) + if is_master(args): + if not metrics: + return metrics + + logging.info( + f"Eval Epoch: {epoch} " + + "\n".join( + [ + "\t".join([f"{k}: {round(v, 4):.4f}" for k, v in m.items()]) + for m in val_metrics_per_dataset.values() + ] + ) + ) + + if args.save_logs: + for name, val in metrics.items(): + if tb_writer is not None: + tb_writer.add_scalar(f"val/{name}", val, epoch) + + with open(os.path.join(args.checkpoint_path, "results.jsonl"), "a+") as f: + f.write(json.dumps(metrics)) + f.write("\n") + + if args.wandb: + assert wandb is not None, "Please install wandb." + for name, val in metrics.items(): + wandb.log({f"val/{name}": val, "epoch": epoch}) + + return metrics + else: + return metrics + + +def get_metrics( + audio_features, + text_features, + logit_scale_a, + audio_features_mlp=None, + text_features_mlp=None, + logit_scale_t=None, + mlp_loss=False, +): + metrics = {} + if mlp_loss: + # Set up audio to text & text to audio similary matrice + a_logits_per_audio = ( + (logit_scale_a * audio_features @ text_features_mlp.t()).detach().cpu() + ) + a_logits_per_text = a_logits_per_audio.t().detach().cpu() + t_logits_per_audio = ( + (logit_scale_t * audio_features_mlp @ text_features.t()).detach().cpu() + ) + t_logits_per_text = t_logits_per_audio.t().detach().cpu() + + labels = torch.arange(audio_features.shape[0]).long() + # Change the loss from two terms into four terms with 2x2 combined CE loss + total_loss = ( + F.cross_entropy(a_logits_per_audio, labels) + + F.cross_entropy(a_logits_per_text, labels) + + F.cross_entropy(t_logits_per_audio, labels) + + F.cross_entropy(t_logits_per_text, labels) + ) / 4 + + metrics[f"cumulative_loss"] = total_loss.item() + metrics[f"num_samples"] = audio_features.shape[0] + + logits = { + "audio_to_text": (a_logits_per_audio + t_logits_per_audio) / 2, + "text_to_audio": (a_logits_per_text + t_logits_per_text) / 2, + } + ground_truth = torch.arange(len(text_features)).view(-1, 1) + + else: + # print("text_features", text_features) + # print("text_features.shape", text_features.shape) + logits_per_audio = ( + (logit_scale_a * audio_features @ text_features.t()).detach().cpu() + ) + logits_per_text = logits_per_audio.t().detach().cpu() + + labels = torch.arange(audio_features.shape[0]).long() + # Change the loss from two terms into four terms with 2x2 combined CE loss + total_loss = ( + F.cross_entropy(logits_per_audio, labels) + + F.cross_entropy(logits_per_text, labels) + ) / 2 + + metrics[f"cumulative_loss"] = total_loss.item() + metrics[f"num_samples"] = audio_features.shape[0] + + logits = {"audio_to_text": logits_per_audio, "text_to_audio": logits_per_text} + + ground_truth = torch.arange(len(text_features)).view(-1, 1) + + for name, logit in logits.items(): + ranking = torch.argsort(logit, descending=True) + preds = torch.where(ranking == ground_truth)[ + 1 + ] # (yusong) this line is slow because it uses single thread + preds = preds.detach().cpu().numpy() + metrics[f"{name}_mean_rank"] = preds.mean() + 1 + metrics[f"{name}_median_rank"] = np.floor(np.median(preds)) + 1 + for k in [1, 5, 10]: + metrics[f"{name}_R@{k}"] = np.mean(preds < k) + # map@10 + metrics[f"{name}_mAP@10"] = np.mean(np.where(preds < 10, 1 / (preds + 1), 0.0)) + + return metrics + + +def evaluate_clotho_audiocaps( + model, data, epoch, args, autocast, device, tb_writer=None +): + """ + Adapted from https://github.com/XinhaoMei/audio-text_retrieval/blob/main/tools/utils.py. + 1. for text-to-audio retrieval, do 5 times and average the results + 2. for R@1, R@5, R@10 in audio-to-text retrieval, take the best rank among 5 text + 3. for map@10 in audio-to-text retrieval: + 3.1: sort the rank of 5 text + 3.2: exclude the rank >=10 (0-index) + 3.3: compute the map regarding the remaining ranks: np.mean(np.arange(1, len(ranks)+1) / ranks). + (3.3) That is, take the top ranks of 5 text that is < 10, and assign the descending number as ground truth. + (3.3) E.g.: the ground truth of first rank of the 5 text should be 1, the second rank should be 2, etc. + """ + # TODO: (yusong) only support single GPU evaluation and only support non-mlp case for now. + dataloader = data["val"].dataloader + with torch.no_grad(): + eval_info = {} + for i, batch in enumerate(dataloader): + audios = batch # contains mel_spec, wavform, and longer list + + # each item in the list has 5 texts + if args.tmodel == "transformer": + from open_clip import tokenize + + texts = [tokenize(t) for t in batch["full_text"]] + texts = torch.cat(texts) + else: + from .data import tokenizer + + texts = [ + tokenizer(t) for t in batch["full_text"] + ] # 5 texts for each audio + texts = { + k: torch.cat([t[k] for t in texts]) for k in texts[0].keys() + } # 5 x batch + + # audios = audios.to(device=device, non_blocking=True) + + all_names = list( + set(["-".join(b.split("/")[-3:-1]) for b in batch["__url__"]]) + ) + for name in all_names: + if name not in eval_info.keys(): + # we will not use mlp outputs even if args.clap_mlploss=True + eval_info[name] = { + "cumulative_loss": 0.0, + "num_samples": 0, + "all_audio_features": [], + "all_text_features": [], + } + with autocast(): + audio_features = model(audios, None, device) + text_features = model(None, texts, device) + audio_features = F.normalize(audio_features, dim=-1) + text_features = F.normalize(text_features, dim=-1) + + all_names = list( + set(["-".join(b.split("/")[-3:-1]) for b in batch["__url__"]]) + ) + for n in all_names: + idx = np.where( + np.array( + ["-".join(b.split("/")[-3:-1]) for b in batch["__url__"]] + ) + == n + )[0] + eval_info[n]["all_audio_features"].append( + audio_features.cpu().index_select(0, torch.tensor(idx).long()) + ) + # (yusong) please double-check. This is for selecting 5 text features at once. + # because idx is a list of indices in size of num_samples, + # and text_features is a tensor of size (5*num_samples, dim) + # so we need to select 5 consecutive indices at once for a single index in idx. + eval_info[n]["all_text_features"].append( + text_features.cpu() + .reshape([-1, 5, text_features.shape[1]]) + .index_select(0, torch.tensor(idx).long()) + .reshape([-1, text_features.shape[1]]) + ) + + val_metrics_all = {} + + for n in eval_info.keys(): + logit_scale_a, logit_scale_t = model(None, None, device) + logit_scale_a = logit_scale_a.cpu() + + audio_features = torch.cat(eval_info[n]["all_audio_features"], dim=0) + text_features = torch.cat(eval_info[n]["all_text_features"], dim=0) + + logits_per_audio = ( + (logit_scale_a * audio_features @ text_features.t()).detach().cpu() + ) + logits_per_text = logits_per_audio.t().detach().cpu() + + # logits_per_audio shape: [num_samples, num_samples*5] + # logits_per_text shape: [num_samples*5, num_samples] + + logging.info( + f"dataset {n}, logits_per_audio shape: {logits_per_audio.shape}, " + f"logits_per_text shape: {logits_per_text.shape}" + ) + + metrics = {} + num_samples = audio_features.shape[0] + metrics[f"num_samples"] = num_samples + + # (yusong) the following code is very important, please double-check: + # logits_per_audio.reshape(num_samples, num_samples, 5)[:, :, d] + # logits_per_text.reshape(num_samples, 5, num_samples)[:, d, :] + # Those two are retrieving one of the 5 text for each audio. + labels = torch.arange(audio_features.shape[0]).long() + audio_to_text_loss = [ + F.cross_entropy( + logits_per_audio.reshape(num_samples, num_samples, 5)[:, :, d], + labels, + ) + for d in range(5) + ] + text_to_audio_loss = [ + F.cross_entropy( + logits_per_text.reshape(num_samples, 5, num_samples)[:, d, :], + labels, + ) + for d in range(5) + ] + total_loss = (np.mean(audio_to_text_loss) + np.mean(text_to_audio_loss)) / 2 + + metrics[f"cumulative_loss"] = total_loss.item() + + # text to audio: do 5 times + pred_text = [] + for d in range(5): + logit = logits_per_text.reshape(num_samples, 5, num_samples)[:, d, :] + ground_truth = torch.arange(len(logit)).view(-1, 1) + ranking = torch.argsort( + logit, descending=True + ) # [num_samples, num_samples] + preds = torch.where(ranking == ground_truth)[1] + pred_text.append(preds.detach().cpu().numpy()) + pred_text_concat = np.concatenate(pred_text, axis=0) # [5*num_samples] + metrics[f"text_to_audio_mean_rank"] = pred_text_concat.mean() + 1 + metrics[f"text_to_audio_median_rank"] = ( + np.floor(np.median(pred_text_concat)) + 1 + ) + for k in [1, 5, 10]: + metrics[f"text_to_audio_R@{k}"] = np.mean(pred_text_concat < k) + # map@10 + metrics[f"text_to_audio_mAP@10"] = np.mean( + np.where(pred_text_concat < 10, 1 / (pred_text_concat + 1), 0.0) + ) + + # audio to text: take the best result + # for audio to text map 10, sort and assign descending ground truth. + # see https://github.com/XinhaoMei/audio-text_retrieval/blob/main/tools/utils.py#L103 + # map@10 + map_all = [] + pred_audio_all = [] + for d in range(num_samples): + # logits_per_audio: [num_samples, num_samples*5] + logit_single = logits_per_audio[d, :] # [5*num_samples] + # Ground-truth index: [d*5, d*5+1, d*5+2, d*5+3, d*5+4] + ranking = torch.argsort( + logit_single, descending=True + ) # [5*num_samples] + # ranking: the index of first match, second match, ... + ground_truth = torch.arange(d * 5, d * 5 + 5)[None] + all_pred = torch.where( + torch.stack([ranking] * 5) == ground_truth.view(-1, 1) + )[1] + min_pred = torch.min(all_pred) + pred_audio_all.append(min_pred.detach().cpu().numpy()) + all_pred_filter = all_pred[all_pred < 10].detach().cpu().numpy() + # /5 because we have 5 text, so it means for the text rank >=10 we count as 0. + map_single = ( + np.sum( + (np.arange(1, len(all_pred_filter) + 1) / (all_pred_filter + 1)) + ) + / 5 + ) + map_all.append(map_single) + metrics[f"audio_to_text_mAP@10"] = np.mean(map_all) + for k in [1, 5, 10]: + metrics[f"audio_to_text_R@{k}"] = np.mean(np.array(pred_audio_all) < k) + + val_metrics_all[n] = {n + "/" + k: v for k, v in metrics.items()} + return val_metrics_all + + +def calculate_selection_performance_clotho_audiocaps(val_metrics_per_dataset): + """ + Calculate performance for Clotho+AudioCaps for model selection. + """ + selection_performance_all = [] + for n in val_metrics_per_dataset.keys(): + selection_performance = ( + val_metrics_per_dataset[n][f"{n}/audio_to_text_mAP@10"] + + val_metrics_per_dataset[n][f"{n}/text_to_audio_mAP@10"] + ) / 2 + selection_performance_all.append(selection_performance) + return np.mean(selection_performance_all) + + +def select_top_metric_clotho_audiocaps(metrics, val_metrics_per_dataset, args): + # val_metrics_per_dataset: dict, key: dataset name, value: dict, key: metric name, value: metric value + # metrics: dict, key: metric name, value: metric value + # Hack: use args to save the top performance + if not hasattr(args, "top_selection_performance"): + selection_performance = calculate_selection_performance_clotho_audiocaps( + val_metrics_per_dataset + ) + # TODO: write the if and else together + metric_update = {} + for n in val_metrics_per_dataset.keys(): + for k in val_metrics_per_dataset[n].keys(): + metric_update[ + k.split("/")[0] + "-top" + "/" + k.split("/")[1] + ] = val_metrics_per_dataset[n][k] + metric_update["top_selection_performance"] = selection_performance + metric_update["top-selection-epoch"] = metrics["epoch"] + metrics.update(metric_update) + args.top_metric = metric_update + args.top_selection_performance = selection_performance + else: + selection_performance_new = calculate_selection_performance_clotho_audiocaps( + val_metrics_per_dataset + ) + selection_performance_old = args.top_selection_performance + if selection_performance_new > selection_performance_old: + metric_update = {} + for n in val_metrics_per_dataset.keys(): + for k in val_metrics_per_dataset[n].keys(): + metric_update[ + k.split("/")[0] + "-top" + "/" + k.split("/")[1] + ] = val_metrics_per_dataset[n][k] + metric_update["top_selection_performance"] = selection_performance_new + metric_update["top-selection-epoch"] = metrics["epoch"] + metrics.update(metric_update) + args.top_metric = metric_update + args.top_selection_performance = selection_performance_new + else: + metrics.update(args.top_metric) + return metrics diff --git a/src/audioldm/clap/training/zero_shot.py b/src/audioldm/clap/training/zero_shot.py new file mode 100644 index 0000000000000000000000000000000000000000..24f0646f7375bce7e1eb0d279619603e3cd5509d --- /dev/null +++ b/src/audioldm/clap/training/zero_shot.py @@ -0,0 +1,95 @@ +# NOTE: This script is currently not supported for CLAP. +import logging +from contextlib import suppress + +import torch +import torch.nn.functional as F +from tqdm import tqdm + +from open_clip import tokenize +from .imagenet_zeroshot_data import imagenet_classnames, openai_imagenet_template + + +def zero_shot_classifier(model, classnames, templates, args): + with torch.no_grad(): + zeroshot_weights = [] + for classname in tqdm(classnames): + texts = [template(classname) for template in templates] # format with class + texts = tokenize(texts).to(args.device) # tokenize + if args.distributed and not args.horovod: + class_embeddings = model.module.encode_text(texts) + else: + class_embeddings = model.encode_text(texts) + class_embedding = F.normalize(class_embeddings, dim=-1).mean(dim=0) + class_embedding /= class_embedding.norm() + zeroshot_weights.append(class_embedding) + zeroshot_weights = torch.stack(zeroshot_weights, dim=1).to(args.device) + return zeroshot_weights + + +def accuracy(output, target, topk=(1,)): + pred = output.topk(max(topk), 1, True, True)[1].t() + correct = pred.eq(target.view(1, -1).expand_as(pred)) + return [ + float(correct[:k].reshape(-1).float().sum(0, keepdim=True).cpu().numpy()) + for k in topk + ] + + +def run(model, classifier, dataloader, args): + autocast = torch.cuda.amp.autocast if args.precision == "amp" else suppress + with torch.no_grad(): + top1, top5, n = 0.0, 0.0, 0.0 + for images, target in tqdm(dataloader, unit_scale=args.batch_size): + images = images.to(args.device) + target = target.to(args.device) + + with autocast(): + # predict + if args.distributed and not args.horovod: + image_features = model.module.encode_image(images) + else: + image_features = model.encode_image(images) + image_features = F.normalize(image_features, dim=-1) + logits = 100.0 * image_features @ classifier + + # measure accuracy + acc1, acc5 = accuracy(logits, target, topk=(1, 5)) + top1 += acc1 + top5 += acc5 + n += images.size(0) + + top1 = top1 / n + top5 = top5 / n + return top1, top5 + + +def zero_shot_eval(model, data, epoch, args): + if "imagenet-val" not in data and "imagenet-v2" not in data: + return {} + if args.zeroshot_frequency == 0: + return {} + if (epoch % args.zeroshot_frequency) != 0 and epoch != args.epochs: + return {} + + logging.info("Starting zero-shot imagenet.") + + logging.info("Building zero-shot classifier") + classifier = zero_shot_classifier( + model, imagenet_classnames, openai_imagenet_template, args + ) + + logging.info("Using classifier") + results = {} + if "imagenet-val" in data: + top1, top5 = run(model, classifier, data["imagenet-val"].dataloader, args) + results["imagenet-zeroshot-val-top1"] = top1 + results["imagenet-zeroshot-val-top5"] = top5 + if "imagenet-v2" in data: + top1, top5 = run(model, classifier, data["imagenet-v2"].dataloader, args) + results["imagenetv2-zeroshot-val-top1"] = top1 + results["imagenetv2-zeroshot-val-top5"] = top5 + + logging.info("Finished zero-shot imagenet.") + + return results diff --git a/src/audioldm/hifigan/__init__.py b/src/audioldm/hifigan/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..22627e2e9d4432ee0024d4379e998d9de7eefbe3 --- /dev/null +++ b/src/audioldm/hifigan/__init__.py @@ -0,0 +1,7 @@ +from .models import Generator + + +class AttrDict(dict): + def __init__(self, *args, **kwargs): + super(AttrDict, self).__init__(*args, **kwargs) + self.__dict__ = self diff --git a/src/audioldm/hifigan/models.py b/src/audioldm/hifigan/models.py new file mode 100644 index 0000000000000000000000000000000000000000..f11880496347e82118553b0256f403e22ae91a0d --- /dev/null +++ b/src/audioldm/hifigan/models.py @@ -0,0 +1,174 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +from torch.nn import Conv1d, ConvTranspose1d +from torch.nn.utils import weight_norm, remove_weight_norm + +LRELU_SLOPE = 0.1 + + +def init_weights(m, mean=0.0, std=0.01): + classname = m.__class__.__name__ + if classname.find("Conv") != -1: + m.weight.data.normal_(mean, std) + + +def get_padding(kernel_size, dilation=1): + return int((kernel_size * dilation - dilation) / 2) + + +class ResBlock(torch.nn.Module): + def __init__(self, h, channels, kernel_size=3, dilation=(1, 3, 5)): + super(ResBlock, self).__init__() + self.h = h + self.convs1 = nn.ModuleList( + [ + weight_norm( + Conv1d( + channels, + channels, + kernel_size, + 1, + dilation=dilation[0], + padding=get_padding(kernel_size, dilation[0]), + ) + ), + weight_norm( + Conv1d( + channels, + channels, + kernel_size, + 1, + dilation=dilation[1], + padding=get_padding(kernel_size, dilation[1]), + ) + ), + weight_norm( + Conv1d( + channels, + channels, + kernel_size, + 1, + dilation=dilation[2], + padding=get_padding(kernel_size, dilation[2]), + ) + ), + ] + ) + self.convs1.apply(init_weights) + + self.convs2 = nn.ModuleList( + [ + weight_norm( + Conv1d( + channels, + channels, + kernel_size, + 1, + dilation=1, + padding=get_padding(kernel_size, 1), + ) + ), + weight_norm( + Conv1d( + channels, + channels, + kernel_size, + 1, + dilation=1, + padding=get_padding(kernel_size, 1), + ) + ), + weight_norm( + Conv1d( + channels, + channels, + kernel_size, + 1, + dilation=1, + padding=get_padding(kernel_size, 1), + ) + ), + ] + ) + self.convs2.apply(init_weights) + + def forward(self, x): + for c1, c2 in zip(self.convs1, self.convs2): + xt = F.leaky_relu(x, LRELU_SLOPE) + xt = c1(xt) + xt = F.leaky_relu(xt, LRELU_SLOPE) + xt = c2(xt) + x = xt + x + return x + + def remove_weight_norm(self): + for l in self.convs1: + remove_weight_norm(l) + for l in self.convs2: + remove_weight_norm(l) + + +class Generator(torch.nn.Module): + def __init__(self, h): + super(Generator, self).__init__() + self.h = h + self.num_kernels = len(h.resblock_kernel_sizes) + self.num_upsamples = len(h.upsample_rates) + self.conv_pre = weight_norm( + Conv1d(h.num_mels, h.upsample_initial_channel, 7, 1, padding=3) + ) + resblock = ResBlock + + self.ups = nn.ModuleList() + for i, (u, k) in enumerate(zip(h.upsample_rates, h.upsample_kernel_sizes)): + self.ups.append( + weight_norm( + ConvTranspose1d( + h.upsample_initial_channel // (2**i), + h.upsample_initial_channel // (2 ** (i + 1)), + k, + u, + padding=(k - u) // 2, + ) + ) + ) + + self.resblocks = nn.ModuleList() + for i in range(len(self.ups)): + ch = h.upsample_initial_channel // (2 ** (i + 1)) + for j, (k, d) in enumerate( + zip(h.resblock_kernel_sizes, h.resblock_dilation_sizes) + ): + self.resblocks.append(resblock(h, ch, k, d)) + + self.conv_post = weight_norm(Conv1d(ch, 1, 7, 1, padding=3)) + self.ups.apply(init_weights) + self.conv_post.apply(init_weights) + + def forward(self, x): + x = self.conv_pre(x) + for i in range(self.num_upsamples): + x = F.leaky_relu(x, LRELU_SLOPE) + x = self.ups[i](x) + xs = None + for j in range(self.num_kernels): + if xs is None: + xs = self.resblocks[i * self.num_kernels + j](x) + else: + xs += self.resblocks[i * self.num_kernels + j](x) + x = xs / self.num_kernels + x = F.leaky_relu(x) + x = self.conv_post(x) + x = torch.tanh(x) + + return x + + def remove_weight_norm(self): + # print("Removing weight norm...") + for l in self.ups: + remove_weight_norm(l) + for l in self.resblocks: + l.remove_weight_norm() + remove_weight_norm(self.conv_pre) + remove_weight_norm(self.conv_post) diff --git a/src/audioldm/hifigan/utilities.py b/src/audioldm/hifigan/utilities.py new file mode 100644 index 0000000000000000000000000000000000000000..858578548374f774dd0386d6fe87fe423e4a2ead --- /dev/null +++ b/src/audioldm/hifigan/utilities.py @@ -0,0 +1,86 @@ +import os +import json + +import torch +import numpy as np + +import audioldm.hifigan as hifigan + +HIFIGAN_16K_64 = { + "resblock": "1", + "num_gpus": 6, + "batch_size": 16, + "learning_rate": 0.0002, + "adam_b1": 0.8, + "adam_b2": 0.99, + "lr_decay": 0.999, + "seed": 1234, + "upsample_rates": [5, 4, 2, 2, 2], + "upsample_kernel_sizes": [16, 16, 8, 4, 4], + "upsample_initial_channel": 1024, + "resblock_kernel_sizes": [3, 7, 11], + "resblock_dilation_sizes": [[1, 3, 5], [1, 3, 5], [1, 3, 5]], + "segment_size": 8192, + "num_mels": 64, + "num_freq": 1025, + "n_fft": 1024, + "hop_size": 160, + "win_size": 1024, + "sampling_rate": 16000, + "fmin": 0, + "fmax": 8000, + "fmax_for_loss": None, + "num_workers": 4, + "dist_config": { + "dist_backend": "nccl", + "dist_url": "tcp://localhost:54321", + "world_size": 1, + }, +} + + +def get_available_checkpoint_keys(model, ckpt): + print("==> Attemp to reload from %s" % ckpt) + state_dict = torch.load(ckpt)["state_dict"] + current_state_dict = model.state_dict() + new_state_dict = {} + for k in state_dict.keys(): + if ( + k in current_state_dict.keys() + and current_state_dict[k].size() == state_dict[k].size() + ): + new_state_dict[k] = state_dict[k] + else: + print("==> WARNING: Skipping %s" % k) + print( + "%s out of %s keys are matched" + % (len(new_state_dict.keys()), len(state_dict.keys())) + ) + return new_state_dict + + +def get_param_num(model): + num_param = sum(param.numel() for param in model.parameters()) + return num_param + + +def get_vocoder(config, device): + config = hifigan.AttrDict(HIFIGAN_16K_64) + vocoder = hifigan.Generator(config) + vocoder.eval() + vocoder.remove_weight_norm() + vocoder.to(device) + return vocoder + + +def vocoder_infer(mels, vocoder, lengths=None): + vocoder.eval() + with torch.no_grad(): + wavs = vocoder(mels).squeeze(1) + + wavs = (wavs.cpu().numpy() * 32768).astype("int16") + + if lengths is not None: + wavs = wavs[:, :lengths] + + return wavs diff --git a/src/audioldm/latent_diffusion/__init__.py b/src/audioldm/latent_diffusion/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/src/audioldm/latent_diffusion/attention.py b/src/audioldm/latent_diffusion/attention.py new file mode 100644 index 0000000000000000000000000000000000000000..03289eb68eed9758116641d678086932e7ea0640 --- /dev/null +++ b/src/audioldm/latent_diffusion/attention.py @@ -0,0 +1,469 @@ +from inspect import isfunction +import math +import torch +import torch.nn.functional as F +from torch import nn +from einops import rearrange + +from audioldm.latent_diffusion.util import checkpoint + + +def exists(val): + return val is not None + + +def uniq(arr): + return {el: True for el in arr}.keys() + + +def default(val, d): + if exists(val): + return val + return d() if isfunction(d) else d + + +def max_neg_value(t): + return -torch.finfo(t.dtype).max + + +def init_(tensor): + dim = tensor.shape[-1] + std = 1 / math.sqrt(dim) + tensor.uniform_(-std, std) + return tensor + + +# feedforward +class GEGLU(nn.Module): + def __init__(self, dim_in, dim_out): + super().__init__() + self.proj = nn.Linear(dim_in, dim_out * 2) + + def forward(self, x): + x, gate = self.proj(x).chunk(2, dim=-1) + return x * F.gelu(gate) + + +class FeedForward(nn.Module): + def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0.0): + super().__init__() + inner_dim = int(dim * mult) + dim_out = default(dim_out, dim) + project_in = ( + nn.Sequential(nn.Linear(dim, inner_dim), nn.GELU()) + if not glu + else GEGLU(dim, inner_dim) + ) + + self.net = nn.Sequential( + project_in, nn.Dropout(dropout), nn.Linear(inner_dim, dim_out) + ) + + def forward(self, x): + return self.net(x) + + +def zero_module(module): + """ + Zero out the parameters of a module and return it. + """ + for p in module.parameters(): + p.detach().zero_() + return module + + +def Normalize(in_channels): + return torch.nn.GroupNorm( + num_groups=32, num_channels=in_channels, eps=1e-6, affine=True + ) + + +class LinearAttention(nn.Module): + def __init__(self, dim, heads=4, dim_head=32): + super().__init__() + self.heads = heads + hidden_dim = dim_head * heads + self.to_qkv = nn.Conv2d(dim, hidden_dim * 3, 1, bias=False) + self.to_out = nn.Conv2d(hidden_dim, dim, 1) + + def forward(self, x): + b, c, h, w = x.shape + qkv = self.to_qkv(x) + q, k, v = rearrange( + qkv, "b (qkv heads c) h w -> qkv b heads c (h w)", heads=self.heads, qkv=3 + ) + k = k.softmax(dim=-1) + context = torch.einsum("bhdn,bhen->bhde", k, v) + out = torch.einsum("bhde,bhdn->bhen", context, q) + out = rearrange( + out, "b heads c (h w) -> b (heads c) h w", heads=self.heads, h=h, w=w + ) + return self.to_out(out) + + +class SpatialSelfAttention(nn.Module): + def __init__(self, in_channels): + super().__init__() + self.in_channels = in_channels + + self.norm = Normalize(in_channels) + self.q = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=1, stride=1, padding=0 + ) + self.k = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=1, stride=1, padding=0 + ) + self.v = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=1, stride=1, padding=0 + ) + self.proj_out = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=1, stride=1, padding=0 + ) + + def forward(self, x): + h_ = x + h_ = self.norm(h_) + q = self.q(h_) + k = self.k(h_) + v = self.v(h_) + + # compute attention + b, c, h, w = q.shape + q = rearrange(q, "b c h w -> b (h w) c") + k = rearrange(k, "b c h w -> b c (h w)") + w_ = torch.einsum("bij,bjk->bik", q, k) + + w_ = w_ * (int(c) ** (-0.5)) + w_ = torch.nn.functional.softmax(w_, dim=2) + + # attend to values + v = rearrange(v, "b c h w -> b c (h w)") + w_ = rearrange(w_, "b i j -> b j i") + h_ = torch.einsum("bij,bjk->bik", v, w_) + h_ = rearrange(h_, "b c (h w) -> b c h w", h=h) + h_ = self.proj_out(h_) + + return x + h_ + + +class CrossAttention(nn.Module): + """ + ### Cross Attention Layer + This falls-back to self-attention when conditional embeddings are not specified. + """ + + # use_flash_attention: bool = True + use_flash_attention: bool = False + + def __init__( + self, + query_dim, + context_dim=None, + heads=8, + dim_head=64, + dropout=0.0, + is_inplace: bool = True, + ): + # def __init__(self, d_model: int, d_cond: int, n_heads: int, d_head: int, is_inplace: bool = True): + """ + :param d_model: is the input embedding size + :param n_heads: is the number of attention heads + :param d_head: is the size of a attention head + :param d_cond: is the size of the conditional embeddings + :param is_inplace: specifies whether to perform the attention softmax computation inplace to + save memory + """ + super().__init__() + + self.is_inplace = is_inplace + self.n_heads = heads + self.d_head = dim_head + + # Attention scaling factor + self.scale = dim_head**-0.5 + + # The normal self-attention layer + if context_dim is None: + context_dim = query_dim + + # Query, key and value mappings + d_attn = dim_head * heads + self.to_q = nn.Linear(query_dim, d_attn, bias=False) + self.to_k = nn.Linear(context_dim, d_attn, bias=False) + self.to_v = nn.Linear(context_dim, d_attn, bias=False) + + # Final linear layer + self.to_out = nn.Sequential(nn.Linear(d_attn, query_dim), nn.Dropout(dropout)) + + # Setup [flash attention](https://github.com/HazyResearch/flash-attention). + # Flash attention is only used if it's installed + # and `CrossAttention.use_flash_attention` is set to `True`. + try: + # You can install flash attention by cloning their Github repo, + # [https://github.com/HazyResearch/flash-attention](https://github.com/HazyResearch/flash-attention) + # and then running `python setup.py install` + from flash_attn.flash_attention import FlashAttention + + self.flash = FlashAttention() + # Set the scale for scaled dot-product attention. + self.flash.softmax_scale = self.scale + # Set to `None` if it's not installed + except ImportError: + self.flash = None + + def forward(self, x, context=None, mask=None): + """ + :param x: are the input embeddings of shape `[batch_size, height * width, d_model]` + :param cond: is the conditional embeddings of shape `[batch_size, n_cond, d_cond]` + """ + + # If `cond` is `None` we perform self attention + has_cond = context is not None + if not has_cond: + context = x + + # Get query, key and value vectors + q = self.to_q(x) + k = self.to_k(context) + v = self.to_v(context) + + # Use flash attention if it's available and the head size is less than or equal to `128` + if ( + CrossAttention.use_flash_attention + and self.flash is not None + and not has_cond + and self.d_head <= 128 + ): + return self.flash_attention(q, k, v) + # Otherwise, fallback to normal attention + else: + return self.normal_attention(q, k, v) + + def flash_attention(self, q: torch.Tensor, k: torch.Tensor, v: torch.Tensor): + """ + #### Flash Attention + :param q: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]` + :param k: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]` + :param v: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]` + """ + + # Get batch size and number of elements along sequence axis (`width * height`) + batch_size, seq_len, _ = q.shape + + # Stack `q`, `k`, `v` vectors for flash attention, to get a single tensor of + # shape `[batch_size, seq_len, 3, n_heads * d_head]` + qkv = torch.stack((q, k, v), dim=2) + # Split the heads + qkv = qkv.view(batch_size, seq_len, 3, self.n_heads, self.d_head) + + # Flash attention works for head sizes `32`, `64` and `128`, so we have to pad the heads to + # fit this size. + if self.d_head <= 32: + pad = 32 - self.d_head + elif self.d_head <= 64: + pad = 64 - self.d_head + elif self.d_head <= 128: + pad = 128 - self.d_head + else: + raise ValueError(f"Head size ${self.d_head} too large for Flash Attention") + + # Pad the heads + if pad: + qkv = torch.cat( + (qkv, qkv.new_zeros(batch_size, seq_len, 3, self.n_heads, pad)), dim=-1 + ) + + # Compute attention + # $$\underset{seq}{softmax}\Bigg(\frac{Q K^\top}{\sqrt{d_{key}}}\Bigg)V$$ + # This gives a tensor of shape `[batch_size, seq_len, n_heads, d_padded]` + # TODO here I add the dtype changing + out, _ = self.flash(qkv.type(torch.float16)) + # Truncate the extra head size + out = out[:, :, :, : self.d_head].float() + # Reshape to `[batch_size, seq_len, n_heads * d_head]` + out = out.reshape(batch_size, seq_len, self.n_heads * self.d_head) + + # Map to `[batch_size, height * width, d_model]` with a linear layer + return self.to_out(out) + + def normal_attention(self, q: torch.Tensor, k: torch.Tensor, v: torch.Tensor): + """ + #### Normal Attention + + :param q: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]` + :param k: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]` + :param v: are the query vectors before splitting heads, of shape `[batch_size, seq, d_attn]` + """ + + # Split them to heads of shape `[batch_size, seq_len, n_heads, d_head]` + q = q.view(*q.shape[:2], self.n_heads, -1) # [bs, 64, 20, 32] + k = k.view(*k.shape[:2], self.n_heads, -1) # [bs, 1, 20, 32] + v = v.view(*v.shape[:2], self.n_heads, -1) + + # Calculate attention $\frac{Q K^\top}{\sqrt{d_{key}}}$ + attn = torch.einsum("bihd,bjhd->bhij", q, k) * self.scale + + # Compute softmax + # $$\underset{seq}{softmax}\Bigg(\frac{Q K^\top}{\sqrt{d_{key}}}\Bigg)$$ + if self.is_inplace: + half = attn.shape[0] // 2 + attn[half:] = attn[half:].softmax(dim=-1) + attn[:half] = attn[:half].softmax(dim=-1) + else: + attn = attn.softmax(dim=-1) + + # Compute attention output + # $$\underset{seq}{softmax}\Bigg(\frac{Q K^\top}{\sqrt{d_{key}}}\Bigg)V$$ + # attn: [bs, 20, 64, 1] + # v: [bs, 1, 20, 32] + out = torch.einsum("bhij,bjhd->bihd", attn, v) + # Reshape to `[batch_size, height * width, n_heads * d_head]` + out = out.reshape(*out.shape[:2], -1) + # Map to `[batch_size, height * width, d_model]` with a linear layer + return self.to_out(out) + + +# class CrossAttention(nn.Module): +# def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0.): +# super().__init__() +# inner_dim = dim_head * heads +# context_dim = default(context_dim, query_dim) + +# self.scale = dim_head ** -0.5 +# self.heads = heads + +# self.to_q = nn.Linear(query_dim, inner_dim, bias=False) +# self.to_k = nn.Linear(context_dim, inner_dim, bias=False) +# self.to_v = nn.Linear(context_dim, inner_dim, bias=False) + +# self.to_out = nn.Sequential( +# nn.Linear(inner_dim, query_dim), +# nn.Dropout(dropout) +# ) + +# def forward(self, x, context=None, mask=None): +# h = self.heads + +# q = self.to_q(x) +# context = default(context, x) +# k = self.to_k(context) +# v = self.to_v(context) + +# q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v)) + +# sim = einsum('b i d, b j d -> b i j', q, k) * self.scale + +# if exists(mask): +# mask = rearrange(mask, 'b ... -> b (...)') +# max_neg_value = -torch.finfo(sim.dtype).max +# mask = repeat(mask, 'b j -> (b h) () j', h=h) +# sim.masked_fill_(~mask, max_neg_value) + +# # attention, what we cannot get enough of +# attn = sim.softmax(dim=-1) + +# out = einsum('b i j, b j d -> b i d', attn, v) +# out = rearrange(out, '(b h) n d -> b n (h d)', h=h) +# return self.to_out(out) + + +class BasicTransformerBlock(nn.Module): + def __init__( + self, + dim, + n_heads, + d_head, + dropout=0.0, + context_dim=None, + gated_ff=True, + checkpoint=True, + ): + super().__init__() + self.attn1 = CrossAttention( + query_dim=dim, heads=n_heads, dim_head=d_head, dropout=dropout + ) # is a self-attention + self.ff = FeedForward(dim, dropout=dropout, glu=gated_ff) + self.attn2 = CrossAttention( + query_dim=dim, + context_dim=context_dim, + heads=n_heads, + dim_head=d_head, + dropout=dropout, + ) # is self-attn if context is none + self.norm1 = nn.LayerNorm(dim) + self.norm2 = nn.LayerNorm(dim) + self.norm3 = nn.LayerNorm(dim) + self.checkpoint = checkpoint + + def forward(self, x, context=None): + if context is None: + return checkpoint(self._forward, (x,), self.parameters(), self.checkpoint) + else: + return checkpoint( + self._forward, (x, context), self.parameters(), self.checkpoint + ) + + def _forward(self, x, context=None): + x = self.attn1(self.norm1(x)) + x + x = self.attn2(self.norm2(x), context=context) + x + x = self.ff(self.norm3(x)) + x + return x + + +class SpatialTransformer(nn.Module): + """ + Transformer block for image-like data. + First, project the input (aka embedding) + and reshape to b, t, d. + Then apply standard transformer action. + Finally, reshape to image + """ + + def __init__( + self, + in_channels, + n_heads, + d_head, + depth=1, + dropout=0.0, + context_dim=None, + no_context=False, + ): + super().__init__() + + if no_context: + context_dim = None + + self.in_channels = in_channels + inner_dim = n_heads * d_head + self.norm = Normalize(in_channels) + + self.proj_in = nn.Conv2d( + in_channels, inner_dim, kernel_size=1, stride=1, padding=0 + ) + + self.transformer_blocks = nn.ModuleList( + [ + BasicTransformerBlock( + inner_dim, n_heads, d_head, dropout=dropout, context_dim=context_dim + ) + for d in range(depth) + ] + ) + + self.proj_out = zero_module( + nn.Conv2d(inner_dim, in_channels, kernel_size=1, stride=1, padding=0) + ) + + def forward(self, x, context=None): + # note: if no context is given, cross-attention defaults to self-attention + b, c, h, w = x.shape + x_in = x + x = self.norm(x) + x = self.proj_in(x) + x = rearrange(x, "b c h w -> b (h w) c") + for block in self.transformer_blocks: + x = block(x, context=context) + x = rearrange(x, "b (h w) c -> b c h w", h=h, w=w) + x = self.proj_out(x) + return x + x_in diff --git a/src/audioldm/latent_diffusion/ddim.py b/src/audioldm/latent_diffusion/ddim.py new file mode 100644 index 0000000000000000000000000000000000000000..cd333d389613f12e72f333e87298e71f4e74e684 --- /dev/null +++ b/src/audioldm/latent_diffusion/ddim.py @@ -0,0 +1,377 @@ +"""SAMPLING ONLY.""" + +import torch +import numpy as np +from tqdm import tqdm + +from audioldm.latent_diffusion.util import ( + make_ddim_sampling_parameters, + make_ddim_timesteps, + noise_like, + extract_into_tensor, +) + + +class DDIMSampler(object): + def __init__(self, model, schedule="linear", **kwargs): + super().__init__() + self.model = model + self.ddpm_num_timesteps = model.num_timesteps + self.schedule = schedule + + def register_buffer(self, name, attr): + if type(attr) == torch.Tensor: + if attr.device != torch.device("cuda"): + attr = attr.to(torch.device("cuda")) + setattr(self, name, attr) + + def make_schedule( + self, ddim_num_steps, ddim_discretize="uniform", ddim_eta=0.0, verbose=True + ): + self.ddim_timesteps = make_ddim_timesteps( + ddim_discr_method=ddim_discretize, + num_ddim_timesteps=ddim_num_steps, + num_ddpm_timesteps=self.ddpm_num_timesteps, + verbose=verbose, + ) + alphas_cumprod = self.model.alphas_cumprod + assert ( + alphas_cumprod.shape[0] == self.ddpm_num_timesteps + ), "alphas have to be defined for each timestep" + to_torch = lambda x: x.clone().detach().to(torch.float32).to(self.model.device) + + self.register_buffer("betas", to_torch(self.model.betas)) + self.register_buffer("alphas_cumprod", to_torch(alphas_cumprod)) + self.register_buffer( + "alphas_cumprod_prev", to_torch(self.model.alphas_cumprod_prev) + ) + + # calculations for diffusion q(x_t | x_{t-1}) and others + self.register_buffer( + "sqrt_alphas_cumprod", to_torch(np.sqrt(alphas_cumprod.cpu())) + ) + self.register_buffer( + "sqrt_one_minus_alphas_cumprod", + to_torch(np.sqrt(1.0 - alphas_cumprod.cpu())), + ) + self.register_buffer( + "log_one_minus_alphas_cumprod", to_torch(np.log(1.0 - alphas_cumprod.cpu())) + ) + self.register_buffer( + "sqrt_recip_alphas_cumprod", to_torch(np.sqrt(1.0 / alphas_cumprod.cpu())) + ) + self.register_buffer( + "sqrt_recipm1_alphas_cumprod", + to_torch(np.sqrt(1.0 / alphas_cumprod.cpu() - 1)), + ) + + # ddim sampling parameters + ddim_sigmas, ddim_alphas, ddim_alphas_prev = make_ddim_sampling_parameters( + alphacums=alphas_cumprod.cpu(), + ddim_timesteps=self.ddim_timesteps, + eta=ddim_eta, + verbose=verbose, + ) + self.register_buffer("ddim_sigmas", ddim_sigmas) + self.register_buffer("ddim_alphas", ddim_alphas) + self.register_buffer("ddim_alphas_prev", ddim_alphas_prev) + self.register_buffer("ddim_sqrt_one_minus_alphas", np.sqrt(1.0 - ddim_alphas)) + sigmas_for_original_sampling_steps = ddim_eta * torch.sqrt( + (1 - self.alphas_cumprod_prev) + / (1 - self.alphas_cumprod) + * (1 - self.alphas_cumprod / self.alphas_cumprod_prev) + ) + self.register_buffer( + "ddim_sigmas_for_original_num_steps", sigmas_for_original_sampling_steps + ) + + @torch.no_grad() + def sample( + self, + S, + batch_size, + shape, + conditioning=None, + callback=None, + normals_sequence=None, + img_callback=None, + quantize_x0=False, + eta=0.0, + mask=None, + x0=None, + temperature=1.0, + noise_dropout=0.0, + score_corrector=None, + corrector_kwargs=None, + verbose=True, + x_T=None, + log_every_t=100, + unconditional_guidance_scale=1.0, + unconditional_conditioning=None, + # this has to come in the same format as the conditioning, # e.g. as encoded tokens, ... + **kwargs, + ): + if conditioning is not None: + if isinstance(conditioning, dict): + cbs = conditioning[list(conditioning.keys())[0]].shape[0] + if cbs != batch_size: + print( + f"Warning: Got {cbs} conditionings but batch-size is {batch_size}" + ) + else: + if conditioning.shape[0] != batch_size: + print( + f"Warning: Got {conditioning.shape[0]} conditionings but batch-size is {batch_size}" + ) + + self.make_schedule(ddim_num_steps=S, ddim_eta=eta, verbose=verbose) + # sampling + C, H, W = shape + size = (batch_size, C, H, W) + samples, intermediates = self.ddim_sampling( + conditioning, + size, + callback=callback, + img_callback=img_callback, + quantize_denoised=quantize_x0, + mask=mask, + x0=x0, + ddim_use_original_steps=False, + noise_dropout=noise_dropout, + temperature=temperature, + score_corrector=score_corrector, + corrector_kwargs=corrector_kwargs, + x_T=x_T, + log_every_t=log_every_t, + unconditional_guidance_scale=unconditional_guidance_scale, + unconditional_conditioning=unconditional_conditioning, + ) + return samples, intermediates + + @torch.no_grad() + def ddim_sampling( + self, + cond, + shape, + x_T=None, + ddim_use_original_steps=False, + callback=None, + timesteps=None, + quantize_denoised=False, + mask=None, + x0=None, + img_callback=None, + log_every_t=100, + temperature=1.0, + noise_dropout=0.0, + score_corrector=None, + corrector_kwargs=None, + unconditional_guidance_scale=1.0, + unconditional_conditioning=None, + ): + device = self.model.betas.device + b = shape[0] + if x_T is None: + img = torch.randn(shape, device=device) + else: + img = x_T + + if timesteps is None: + timesteps = ( + self.ddpm_num_timesteps + if ddim_use_original_steps + else self.ddim_timesteps + ) + elif timesteps is not None and not ddim_use_original_steps: + subset_end = ( + int( + min(timesteps / self.ddim_timesteps.shape[0], 1) + * self.ddim_timesteps.shape[0] + ) + - 1 + ) + timesteps = self.ddim_timesteps[:subset_end] + + intermediates = {"x_inter": [img], "pred_x0": [img]} + time_range = ( + reversed(range(0, timesteps)) + if ddim_use_original_steps + else np.flip(timesteps) + ) + total_steps = timesteps if ddim_use_original_steps else timesteps.shape[0] + # print(f"Running DDIM Sampling with {total_steps} timesteps") + + # iterator = gr.Progress().tqdm(time_range, desc="DDIM Sampler", total=total_steps) + iterator = tqdm(time_range, desc="DDIM Sampler", total=total_steps, leave=False) + + for i, step in enumerate(iterator): + index = total_steps - i - 1 + ts = torch.full((b,), step, device=device, dtype=torch.long) + if mask is not None: + assert x0 is not None + img_orig = self.model.q_sample( + x0, ts + ) # TODO deterministic forward pass? + img = ( + img_orig * mask + (1.0 - mask) * img + ) # In the first sampling step, img is pure gaussian noise + + outs = self.p_sample_ddim( + img, + cond, + ts, + index=index, + use_original_steps=ddim_use_original_steps, + quantize_denoised=quantize_denoised, + temperature=temperature, + noise_dropout=noise_dropout, + score_corrector=score_corrector, + corrector_kwargs=corrector_kwargs, + unconditional_guidance_scale=unconditional_guidance_scale, + unconditional_conditioning=unconditional_conditioning, + ) + img, pred_x0 = outs + if callback: + callback(i) + if img_callback: + img_callback(pred_x0, i) + + if index % log_every_t == 0 or index == total_steps - 1: + intermediates["x_inter"].append(img) + intermediates["pred_x0"].append(pred_x0) + + return img, intermediates + + @torch.no_grad() + def stochastic_encode(self, x0, t, use_original_steps=False, noise=None): + # fast, but does not allow for exact reconstruction + # t serves as an index to gather the correct alphas + if use_original_steps: + sqrt_alphas_cumprod = self.sqrt_alphas_cumprod + sqrt_one_minus_alphas_cumprod = self.sqrt_one_minus_alphas_cumprod + else: + sqrt_alphas_cumprod = torch.sqrt(self.ddim_alphas) + sqrt_one_minus_alphas_cumprod = self.ddim_sqrt_one_minus_alphas + + if noise is None: + noise = torch.randn_like(x0) + + return ( + extract_into_tensor(sqrt_alphas_cumprod, t, x0.shape) * x0 + + extract_into_tensor(sqrt_one_minus_alphas_cumprod, t, x0.shape) * noise + ) + + @torch.no_grad() + def decode( + self, + x_latent, + cond, + t_start, + unconditional_guidance_scale=1.0, + unconditional_conditioning=None, + use_original_steps=False, + ): + + timesteps = ( + np.arange(self.ddpm_num_timesteps) + if use_original_steps + else self.ddim_timesteps + ) + timesteps = timesteps[:t_start] + + time_range = np.flip(timesteps) + total_steps = timesteps.shape[0] + # print(f"Running DDIM Sampling with {total_steps} timesteps") + + # iterator = gr.Progress().tqdm(time_range, desc="Decoding image", total=total_steps) + iterator = tqdm(time_range, desc="Decoding image", total=total_steps) + x_dec = x_latent + + for i, step in enumerate(iterator): + index = total_steps - i - 1 + ts = torch.full( + (x_latent.shape[0],), step, device=x_latent.device, dtype=torch.long + ) + x_dec, _ = self.p_sample_ddim( + x_dec, + cond, + ts, + index=index, + use_original_steps=use_original_steps, + unconditional_guidance_scale=unconditional_guidance_scale, + unconditional_conditioning=unconditional_conditioning, + ) + return x_dec + + @torch.no_grad() + def p_sample_ddim( + self, + x, + c, + t, + index, + repeat_noise=False, + use_original_steps=False, + quantize_denoised=False, + temperature=1.0, + noise_dropout=0.0, + score_corrector=None, + corrector_kwargs=None, + unconditional_guidance_scale=1.0, + unconditional_conditioning=None, + ): + b, *_, device = *x.shape, x.device + + if unconditional_conditioning is None or unconditional_guidance_scale == 1.0: + e_t = self.model.apply_model(x, t, c) + else: + x_in = torch.cat([x] * 2) + t_in = torch.cat([t] * 2) + c_in = torch.cat([unconditional_conditioning, c]) + e_t_uncond, e_t = self.model.apply_model(x_in, t_in, c_in).chunk(2) + # When unconditional_guidance_scale == 1: only e_t + # When unconditional_guidance_scale == 0: only unconditional + # When unconditional_guidance_scale > 1: add more unconditional guidance + e_t = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond) + + if score_corrector is not None: + assert self.model.parameterization == "eps" + e_t = score_corrector.modify_score( + self.model, e_t, x, t, c, **corrector_kwargs + ) + + alphas = self.model.alphas_cumprod if use_original_steps else self.ddim_alphas + alphas_prev = ( + self.model.alphas_cumprod_prev + if use_original_steps + else self.ddim_alphas_prev + ) + sqrt_one_minus_alphas = ( + self.model.sqrt_one_minus_alphas_cumprod + if use_original_steps + else self.ddim_sqrt_one_minus_alphas + ) + sigmas = ( + self.model.ddim_sigmas_for_original_num_steps + if use_original_steps + else self.ddim_sigmas + ) + # select parameters corresponding to the currently considered timestep + a_t = torch.full((b, 1, 1, 1), alphas[index], device=device) + a_prev = torch.full((b, 1, 1, 1), alphas_prev[index], device=device) + sigma_t = torch.full((b, 1, 1, 1), sigmas[index], device=device) + sqrt_one_minus_at = torch.full( + (b, 1, 1, 1), sqrt_one_minus_alphas[index], device=device + ) + + # current prediction for x_0 + pred_x0 = (x - sqrt_one_minus_at * e_t) / a_t.sqrt() + if quantize_denoised: + pred_x0, _, *_ = self.model.first_stage_model.quantize(pred_x0) + # direction pointing to x_t + dir_xt = (1.0 - a_prev - sigma_t**2).sqrt() * e_t + noise = sigma_t * noise_like(x.shape, device, repeat_noise) * temperature + if noise_dropout > 0.0: + noise = torch.nn.functional.dropout(noise, p=noise_dropout) + x_prev = a_prev.sqrt() * pred_x0 + dir_xt + noise # TODO + return x_prev, pred_x0 diff --git a/src/audioldm/latent_diffusion/ddpm.py b/src/audioldm/latent_diffusion/ddpm.py new file mode 100644 index 0000000000000000000000000000000000000000..df16bff0be49c59c5ae1f9c10c33a19f4cc367b4 --- /dev/null +++ b/src/audioldm/latent_diffusion/ddpm.py @@ -0,0 +1,441 @@ +""" +wild mixture of +https://github.com/lucidrains/denoising-diffusion-pytorch/blob/7706bdfc6f527f58d33f84b7b522e61e6e3164b3/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py +https://github.com/openai/improved-diffusion/blob/e94489283bb876ac1477d5dd7709bbbd2d9902ce/improved_diffusion/gaussian_diffusion.py +https://github.com/CompVis/taming-transformers +-- merci +""" +import sys +import os + +import torch +import torch.nn as nn +import numpy as np +from contextlib import contextmanager +from functools import partial +from tqdm import tqdm + +from audioldm.utils import exists, default, count_params, instantiate_from_config +from audioldm.latent_diffusion.ema import LitEma +from audioldm.latent_diffusion.util import ( + make_beta_schedule, + extract_into_tensor, + noise_like, +) +import soundfile as sf +import os + + +__conditioning_keys__ = {"concat": "c_concat", "crossattn": "c_crossattn", "adm": "y"} + + +def disabled_train(self, mode=True): + """Overwrite model.train with this function to make sure train/eval mode + does not change anymore.""" + return self + + +def uniform_on_device(r1, r2, shape, device): + return (r1 - r2) * torch.rand(*shape, device=device) + r2 + + +class DiffusionWrapper(nn.Module): + def __init__(self, diff_model_config, conditioning_key): + super().__init__() + self.diffusion_model = instantiate_from_config(diff_model_config) + self.conditioning_key = conditioning_key + assert self.conditioning_key in [ + None, + "concat", + "crossattn", + "hybrid", + "adm", + "film", + ] + + def forward( + self, x, t, c_concat: list = None, c_crossattn: list = None, c_film: list = None + ): + x = x.contiguous() + t = t.contiguous() + + if self.conditioning_key is None: + out = self.diffusion_model(x, t) + elif self.conditioning_key == "concat": + xc = torch.cat([x] + c_concat, dim=1) + out = self.diffusion_model(xc, t) + elif self.conditioning_key == "crossattn": + cc = torch.cat(c_crossattn, 1) + out = self.diffusion_model(x, t, context=cc) + elif self.conditioning_key == "hybrid": + xc = torch.cat([x] + c_concat, dim=1) + cc = torch.cat(c_crossattn, 1) + out = self.diffusion_model(xc, t, context=cc) + elif ( + self.conditioning_key == "film" + ): # The condition is assumed to be a global token, which wil pass through a linear layer and added with the time embedding for the FILM + cc = c_film[0].squeeze(1) # only has one token + out = self.diffusion_model(x, t, y=cc) + elif self.conditioning_key == "adm": + cc = c_crossattn[0] + out = self.diffusion_model(x, t, y=cc) + else: + raise NotImplementedError() + + return out + + +class DDPM(nn.Module): + # classic DDPM with Gaussian diffusion, in image space + def __init__( + self, + unet_config, + timesteps=1000, + beta_schedule="linear", + loss_type="l2", + ckpt_path=None, + ignore_keys=[], + load_only_unet=False, + monitor="val/loss", + use_ema=True, + first_stage_key="image", + latent_t_size=256, + latent_f_size=16, + channels=3, + log_every_t=100, + clip_denoised=True, + linear_start=1e-4, + linear_end=2e-2, + cosine_s=8e-3, + given_betas=None, + original_elbo_weight=0.0, + v_posterior=0.0, # weight for choosing posterior variance as sigma = (1-v) * beta_tilde + v * beta + l_simple_weight=1.0, + conditioning_key=None, + parameterization="eps", # all assuming fixed variance schedules + scheduler_config=None, + use_positional_encodings=False, + learn_logvar=False, + logvar_init=0.0, + ): + super().__init__() + assert parameterization in [ + "eps", + "x0", + ], 'currently only supporting "eps" and "x0"' + self.parameterization = parameterization + self.state = None + # print(f"{self.__class__.__name__}: Running in {self.parameterization}-prediction mode") + self.cond_stage_model = None + self.clip_denoised = clip_denoised + self.log_every_t = log_every_t + self.first_stage_key = first_stage_key + + self.latent_t_size = latent_t_size + self.latent_f_size = latent_f_size + + self.channels = channels + self.use_positional_encodings = use_positional_encodings + self.model = DiffusionWrapper(unet_config, conditioning_key) + count_params(self.model, verbose=True) + self.use_ema = use_ema + if self.use_ema: + self.model_ema = LitEma(self.model) + # print(f"Keeping EMAs of {len(list(self.model_ema.buffers()))}.") + + self.use_scheduler = scheduler_config is not None + if self.use_scheduler: + self.scheduler_config = scheduler_config + + self.v_posterior = v_posterior + self.original_elbo_weight = original_elbo_weight + self.l_simple_weight = l_simple_weight + + if monitor is not None: + self.monitor = monitor + + self.register_schedule( + given_betas=given_betas, + beta_schedule=beta_schedule, + timesteps=timesteps, + linear_start=linear_start, + linear_end=linear_end, + cosine_s=cosine_s, + ) + + self.loss_type = loss_type + + self.learn_logvar = learn_logvar + self.logvar = torch.full(fill_value=logvar_init, size=(self.num_timesteps,)) + if self.learn_logvar: + self.logvar = nn.Parameter(self.logvar, requires_grad=True) + else: + self.logvar = nn.Parameter(self.logvar, requires_grad=False) + + self.logger_save_dir = None + self.logger_project = None + self.logger_version = None + self.label_indices_total = None + # To avoid the system cannot find metric value for checkpoint + self.metrics_buffer = { + "val/kullback_leibler_divergence_sigmoid": 15.0, + "val/kullback_leibler_divergence_softmax": 10.0, + "val/psnr": 0.0, + "val/ssim": 0.0, + "val/inception_score_mean": 1.0, + "val/inception_score_std": 0.0, + "val/kernel_inception_distance_mean": 0.0, + "val/kernel_inception_distance_std": 0.0, + "val/frechet_inception_distance": 133.0, + "val/frechet_audio_distance": 32.0, + } + self.initial_learning_rate = None + + def get_log_dir(self): + if ( + self.logger_save_dir is None + and self.logger_project is None + and self.logger_version is None + ): + return os.path.join( + self.logger.save_dir, self.logger._project, self.logger.version + ) + else: + return os.path.join( + self.logger_save_dir, self.logger_project, self.logger_version + ) + + def set_log_dir(self, save_dir, project, version): + self.logger_save_dir = save_dir + self.logger_project = project + self.logger_version = version + + def register_schedule( + self, + given_betas=None, + beta_schedule="linear", + timesteps=1000, + linear_start=1e-4, + linear_end=2e-2, + cosine_s=8e-3, + ): + if exists(given_betas): + betas = given_betas + else: + betas = make_beta_schedule( + beta_schedule, + timesteps, + linear_start=linear_start, + linear_end=linear_end, + cosine_s=cosine_s, + ) + alphas = 1.0 - betas + alphas_cumprod = np.cumprod(alphas, axis=0) + alphas_cumprod_prev = np.append(1.0, alphas_cumprod[:-1]) + + (timesteps,) = betas.shape + self.num_timesteps = int(timesteps) + self.linear_start = linear_start + self.linear_end = linear_end + assert ( + alphas_cumprod.shape[0] == self.num_timesteps + ), "alphas have to be defined for each timestep" + + to_torch = partial(torch.tensor, dtype=torch.float32) + + self.register_buffer("betas", to_torch(betas)) + self.register_buffer("alphas_cumprod", to_torch(alphas_cumprod)) + self.register_buffer("alphas_cumprod_prev", to_torch(alphas_cumprod_prev)) + + # calculations for diffusion q(x_t | x_{t-1}) and others + self.register_buffer("sqrt_alphas_cumprod", to_torch(np.sqrt(alphas_cumprod))) + self.register_buffer( + "sqrt_one_minus_alphas_cumprod", to_torch(np.sqrt(1.0 - alphas_cumprod)) + ) + self.register_buffer( + "log_one_minus_alphas_cumprod", to_torch(np.log(1.0 - alphas_cumprod)) + ) + self.register_buffer( + "sqrt_recip_alphas_cumprod", to_torch(np.sqrt(1.0 / alphas_cumprod)) + ) + self.register_buffer( + "sqrt_recipm1_alphas_cumprod", to_torch(np.sqrt(1.0 / alphas_cumprod - 1)) + ) + + # calculations for posterior q(x_{t-1} | x_t, x_0) + posterior_variance = (1 - self.v_posterior) * betas * ( + 1.0 - alphas_cumprod_prev + ) / (1.0 - alphas_cumprod) + self.v_posterior * betas + # above: equal to 1. / (1. / (1. - alpha_cumprod_tm1) + alpha_t / beta_t) + self.register_buffer("posterior_variance", to_torch(posterior_variance)) + # below: log calculation clipped because the posterior variance is 0 at the beginning of the diffusion chain + self.register_buffer( + "posterior_log_variance_clipped", + to_torch(np.log(np.maximum(posterior_variance, 1e-20))), + ) + self.register_buffer( + "posterior_mean_coef1", + to_torch(betas * np.sqrt(alphas_cumprod_prev) / (1.0 - alphas_cumprod)), + ) + self.register_buffer( + "posterior_mean_coef2", + to_torch( + (1.0 - alphas_cumprod_prev) * np.sqrt(alphas) / (1.0 - alphas_cumprod) + ), + ) + + if self.parameterization == "eps": + lvlb_weights = self.betas**2 / ( + 2 + * self.posterior_variance + * to_torch(alphas) + * (1 - self.alphas_cumprod) + ) + elif self.parameterization == "x0": + lvlb_weights = ( + 0.5 + * np.sqrt(torch.Tensor(alphas_cumprod)) + / (2.0 * 1 - torch.Tensor(alphas_cumprod)) + ) + else: + raise NotImplementedError("mu not supported") + # TODO how to choose this term + lvlb_weights[0] = lvlb_weights[1] + self.register_buffer("lvlb_weights", lvlb_weights, persistent=False) + assert not torch.isnan(self.lvlb_weights).all() + + @contextmanager + def ema_scope(self, context=None): + if self.use_ema: + self.model_ema.store(self.model.parameters()) + self.model_ema.copy_to(self.model) + if context is not None: + # print(f"{context}: Switched to EMA weights") + pass + try: + yield None + finally: + if self.use_ema: + self.model_ema.restore(self.model.parameters()) + if context is not None: + # print(f"{context}: Restored training weights") + pass + + def q_mean_variance(self, x_start, t): + """ + Get the distribution q(x_t | x_0). + :param x_start: the [N x C x ...] tensor of noiseless inputs. + :param t: the number of diffusion steps (minus 1). Here, 0 means one step. + :return: A tuple (mean, variance, log_variance), all of x_start's shape. + """ + mean = extract_into_tensor(self.sqrt_alphas_cumprod, t, x_start.shape) * x_start + variance = extract_into_tensor(1.0 - self.alphas_cumprod, t, x_start.shape) + log_variance = extract_into_tensor( + self.log_one_minus_alphas_cumprod, t, x_start.shape + ) + return mean, variance, log_variance + + def predict_start_from_noise(self, x_t, t, noise): + return ( + extract_into_tensor(self.sqrt_recip_alphas_cumprod, t, x_t.shape) * x_t + - extract_into_tensor(self.sqrt_recipm1_alphas_cumprod, t, x_t.shape) + * noise + ) + + def q_posterior(self, x_start, x_t, t): + posterior_mean = ( + extract_into_tensor(self.posterior_mean_coef1, t, x_t.shape) * x_start + + extract_into_tensor(self.posterior_mean_coef2, t, x_t.shape) * x_t + ) + posterior_variance = extract_into_tensor(self.posterior_variance, t, x_t.shape) + posterior_log_variance_clipped = extract_into_tensor( + self.posterior_log_variance_clipped, t, x_t.shape + ) + return posterior_mean, posterior_variance, posterior_log_variance_clipped + + def p_mean_variance(self, x, t, clip_denoised: bool): + model_out = self.model(x, t) + if self.parameterization == "eps": + x_recon = self.predict_start_from_noise(x, t=t, noise=model_out) + elif self.parameterization == "x0": + x_recon = model_out + if clip_denoised: + x_recon.clamp_(-1.0, 1.0) + + model_mean, posterior_variance, posterior_log_variance = self.q_posterior( + x_start=x_recon, x_t=x, t=t + ) + return model_mean, posterior_variance, posterior_log_variance + + @torch.no_grad() + def p_sample(self, x, t, clip_denoised=True, repeat_noise=False): + b, *_, device = *x.shape, x.device + model_mean, _, model_log_variance = self.p_mean_variance( + x=x, t=t, clip_denoised=clip_denoised + ) + noise = noise_like(x.shape, device, repeat_noise) + # no noise when t == 0 + nonzero_mask = ( + (1 - (t == 0).float()).reshape(b, *((1,) * (len(x.shape) - 1))).contiguous() + ) + return model_mean + nonzero_mask * (0.5 * model_log_variance).exp() * noise + + @torch.no_grad() + def p_sample_loop(self, shape, return_intermediates=False): + device = self.betas.device + b = shape[0] + img = torch.randn(shape, device=device) + intermediates = [img] + for i in tqdm( + reversed(range(0, self.num_timesteps)), + desc="Sampling t", + total=self.num_timesteps, + ): + img = self.p_sample( + img, + torch.full((b,), i, device=device, dtype=torch.long), + clip_denoised=self.clip_denoised, + ) + if i % self.log_every_t == 0 or i == self.num_timesteps - 1: + intermediates.append(img) + if return_intermediates: + return img, intermediates + return img + + @torch.no_grad() + def sample(self, batch_size=16, return_intermediates=False): + shape = (batch_size, channels, self.latent_t_size, self.latent_f_size) + channels = self.channels + return self.p_sample_loop(shape, return_intermediates=return_intermediates) + + def q_sample(self, x_start, t, noise=None): + noise = default(noise, lambda: torch.randn_like(x_start)) + return ( + extract_into_tensor(self.sqrt_alphas_cumprod, t, x_start.shape) * x_start + + extract_into_tensor(self.sqrt_one_minus_alphas_cumprod, t, x_start.shape) + * noise + ) + + def forward(self, x, *args, **kwargs): + t = torch.randint( + 0, self.num_timesteps, (x.shape[0],), device=self.device + ).long() + return self.p_losses(x, t, *args, **kwargs) + + def get_input(self, batch, k): + # fbank, log_magnitudes_stft, label_indices, fname, waveform, clip_label, text = batch + fbank, log_magnitudes_stft, label_indices, fname, waveform, text = batch + ret = {} + + ret["fbank"] = ( + fbank.unsqueeze(1).to(memory_format=torch.contiguous_format).float() + ) + ret["stft"] = log_magnitudes_stft.to( + memory_format=torch.contiguous_format + ).float() + # ret["clip_label"] = clip_label.to(memory_format=torch.contiguous_format).float() + ret["waveform"] = waveform.to(memory_format=torch.contiguous_format).float() + ret["text"] = list(text) + ret["fname"] = fname + + return ret[k] diff --git a/src/audioldm/latent_diffusion/ema.py b/src/audioldm/latent_diffusion/ema.py new file mode 100644 index 0000000000000000000000000000000000000000..26a834c3bfce205f38626ab8b19648bab2e4b295 --- /dev/null +++ b/src/audioldm/latent_diffusion/ema.py @@ -0,0 +1,82 @@ +import torch +from torch import nn + + +class LitEma(nn.Module): + def __init__(self, model, decay=0.9999, use_num_upates=True): + super().__init__() + if decay < 0.0 or decay > 1.0: + raise ValueError("Decay must be between 0 and 1") + + self.m_name2s_name = {} + self.register_buffer("decay", torch.tensor(decay, dtype=torch.float32)) + self.register_buffer( + "num_updates", + torch.tensor(0, dtype=torch.int) + if use_num_upates + else torch.tensor(-1, dtype=torch.int), + ) + + for name, p in model.named_parameters(): + if p.requires_grad: + # remove as '.'-character is not allowed in buffers + s_name = name.replace(".", "") + self.m_name2s_name.update({name: s_name}) + self.register_buffer(s_name, p.clone().detach().data) + + self.collected_params = [] + + def forward(self, model): + decay = self.decay + + if self.num_updates >= 0: + self.num_updates += 1 + decay = min(self.decay, (1 + self.num_updates) / (10 + self.num_updates)) + + one_minus_decay = 1.0 - decay + + with torch.no_grad(): + m_param = dict(model.named_parameters()) + shadow_params = dict(self.named_buffers()) + + for key in m_param: + if m_param[key].requires_grad: + sname = self.m_name2s_name[key] + shadow_params[sname] = shadow_params[sname].type_as(m_param[key]) + shadow_params[sname].sub_( + one_minus_decay * (shadow_params[sname] - m_param[key]) + ) + else: + assert not key in self.m_name2s_name + + def copy_to(self, model): + m_param = dict(model.named_parameters()) + shadow_params = dict(self.named_buffers()) + for key in m_param: + if m_param[key].requires_grad: + m_param[key].data.copy_(shadow_params[self.m_name2s_name[key]].data) + else: + assert not key in self.m_name2s_name + + def store(self, parameters): + """ + Save the current parameters for restoring later. + Args: + parameters: Iterable of `torch.nn.Parameter`; the parameters to be + temporarily stored. + """ + self.collected_params = [param.clone() for param in parameters] + + def restore(self, parameters): + """ + Restore the parameters stored with the `store` method. + Useful to validate the model with EMA parameters without affecting the + original optimization process. Store the parameters before the + `copy_to` method. After validation (or model saving), use this to + restore the former parameters. + Args: + parameters: Iterable of `torch.nn.Parameter`; the parameters to be + updated with the stored parameters. + """ + for c_param, param in zip(self.collected_params, parameters): + param.data.copy_(c_param.data) diff --git a/src/audioldm/latent_diffusion/openaimodel.py b/src/audioldm/latent_diffusion/openaimodel.py new file mode 100644 index 0000000000000000000000000000000000000000..0a23361f5d4c2d59876876e390d9275ae2a54a27 --- /dev/null +++ b/src/audioldm/latent_diffusion/openaimodel.py @@ -0,0 +1,1069 @@ +from abc import abstractmethod +import math + +import numpy as np +import torch as th +import torch.nn as nn +import torch.nn.functional as F + +from audioldm.latent_diffusion.util import ( + checkpoint, + conv_nd, + linear, + avg_pool_nd, + zero_module, + normalization, + timestep_embedding, +) +from audioldm.latent_diffusion.attention import SpatialTransformer + + +# dummy replace +def convert_module_to_f16(x): + pass + + +def convert_module_to_f32(x): + pass + + +## go +class AttentionPool2d(nn.Module): + """ + Adapted from CLIP: https://github.com/openai/CLIP/blob/main/clip/model.py + """ + + def __init__( + self, + spacial_dim: int, + embed_dim: int, + num_heads_channels: int, + output_dim: int = None, + ): + super().__init__() + self.positional_embedding = nn.Parameter( + th.randn(embed_dim, spacial_dim**2 + 1) / embed_dim**0.5 + ) + self.qkv_proj = conv_nd(1, embed_dim, 3 * embed_dim, 1) + self.c_proj = conv_nd(1, embed_dim, output_dim or embed_dim, 1) + self.num_heads = embed_dim // num_heads_channels + self.attention = QKVAttention(self.num_heads) + + def forward(self, x): + b, c, *_spatial = x.shape + x = x.reshape(b, c, -1).contiguous() # NC(HW) + x = th.cat([x.mean(dim=-1, keepdim=True), x], dim=-1) # NC(HW+1) + x = x + self.positional_embedding[None, :, :].to(x.dtype) # NC(HW+1) + x = self.qkv_proj(x) + x = self.attention(x) + x = self.c_proj(x) + return x[:, :, 0] + + +class TimestepBlock(nn.Module): + """ + Any module where forward() takes timestep embeddings as a second argument. + """ + + @abstractmethod + def forward(self, x, emb): + """ + Apply the module to `x` given `emb` timestep embeddings. + """ + + +class TimestepEmbedSequential(nn.Sequential, TimestepBlock): + """ + A sequential module that passes timestep embeddings to the children that + support it as an extra input. + """ + + def forward(self, x, emb, context=None): + for layer in self: + if isinstance(layer, TimestepBlock): + x = layer(x, emb) + elif isinstance(layer, SpatialTransformer): + x = layer(x, context) + else: + x = layer(x) + return x + + +class Upsample(nn.Module): + """ + An upsampling layer with an optional convolution. + :param channels: channels in the inputs and outputs. + :param use_conv: a bool determining if a convolution is applied. + :param dims: determines if the signal is 1D, 2D, or 3D. If 3D, then + upsampling occurs in the inner-two dimensions. + """ + + def __init__(self, channels, use_conv, dims=2, out_channels=None, padding=1): + super().__init__() + self.channels = channels + self.out_channels = out_channels or channels + self.use_conv = use_conv + self.dims = dims + if use_conv: + self.conv = conv_nd( + dims, self.channels, self.out_channels, 3, padding=padding + ) + + def forward(self, x): + assert x.shape[1] == self.channels + if self.dims == 3: + x = F.interpolate( + x, (x.shape[2], x.shape[3] * 2, x.shape[4] * 2), mode="nearest" + ) + else: + x = F.interpolate(x, scale_factor=2, mode="nearest") + if self.use_conv: + x = self.conv(x) + return x + + +class TransposedUpsample(nn.Module): + "Learned 2x upsampling without padding" + + def __init__(self, channels, out_channels=None, ks=5): + super().__init__() + self.channels = channels + self.out_channels = out_channels or channels + + self.up = nn.ConvTranspose2d( + self.channels, self.out_channels, kernel_size=ks, stride=2 + ) + + def forward(self, x): + return self.up(x) + + +class Downsample(nn.Module): + """ + A downsampling layer with an optional convolution. + :param channels: channels in the inputs and outputs. + :param use_conv: a bool determining if a convolution is applied. + :param dims: determines if the signal is 1D, 2D, or 3D. If 3D, then + downsampling occurs in the inner-two dimensions. + """ + + def __init__(self, channels, use_conv, dims=2, out_channels=None, padding=1): + super().__init__() + self.channels = channels + self.out_channels = out_channels or channels + self.use_conv = use_conv + self.dims = dims + stride = 2 if dims != 3 else (1, 2, 2) + if use_conv: + self.op = conv_nd( + dims, + self.channels, + self.out_channels, + 3, + stride=stride, + padding=padding, + ) + else: + assert self.channels == self.out_channels + self.op = avg_pool_nd(dims, kernel_size=stride, stride=stride) + + def forward(self, x): + assert x.shape[1] == self.channels + return self.op(x) + + +class ResBlock(TimestepBlock): + """ + A residual block that can optionally change the number of channels. + :param channels: the number of input channels. + :param emb_channels: the number of timestep embedding channels. + :param dropout: the rate of dropout. + :param out_channels: if specified, the number of out channels. + :param use_conv: if True and out_channels is specified, use a spatial + convolution instead of a smaller 1x1 convolution to change the + channels in the skip connection. + :param dims: determines if the signal is 1D, 2D, or 3D. + :param use_checkpoint: if True, use gradient checkpointing on this module. + :param up: if True, use this block for upsampling. + :param down: if True, use this block for downsampling. + """ + + def __init__( + self, + channels, + emb_channels, + dropout, + out_channels=None, + use_conv=False, + use_scale_shift_norm=False, + dims=2, + use_checkpoint=False, + up=False, + down=False, + ): + super().__init__() + self.channels = channels + self.emb_channels = emb_channels + self.dropout = dropout + self.out_channels = out_channels or channels + self.use_conv = use_conv + self.use_checkpoint = use_checkpoint + self.use_scale_shift_norm = use_scale_shift_norm + + self.in_layers = nn.Sequential( + normalization(channels), + nn.SiLU(), + conv_nd(dims, channels, self.out_channels, 3, padding=1), + ) + + self.updown = up or down + + if up: + self.h_upd = Upsample(channels, False, dims) + self.x_upd = Upsample(channels, False, dims) + elif down: + self.h_upd = Downsample(channels, False, dims) + self.x_upd = Downsample(channels, False, dims) + else: + self.h_upd = self.x_upd = nn.Identity() + + self.emb_layers = nn.Sequential( + nn.SiLU(), + linear( + emb_channels, + 2 * self.out_channels if use_scale_shift_norm else self.out_channels, + ), + ) + self.out_layers = nn.Sequential( + normalization(self.out_channels), + nn.SiLU(), + nn.Dropout(p=dropout), + zero_module( + conv_nd(dims, self.out_channels, self.out_channels, 3, padding=1) + ), + ) + + if self.out_channels == channels: + self.skip_connection = nn.Identity() + elif use_conv: + self.skip_connection = conv_nd( + dims, channels, self.out_channels, 3, padding=1 + ) + else: + self.skip_connection = conv_nd(dims, channels, self.out_channels, 1) + + def forward(self, x, emb): + """ + Apply the block to a Tensor, conditioned on a timestep embedding. + :param x: an [N x C x ...] Tensor of features. + :param emb: an [N x emb_channels] Tensor of timestep embeddings. + :return: an [N x C x ...] Tensor of outputs. + """ + return checkpoint( + self._forward, (x, emb), self.parameters(), self.use_checkpoint + ) + + def _forward(self, x, emb): + if self.updown: + in_rest, in_conv = self.in_layers[:-1], self.in_layers[-1] + h = in_rest(x) + h = self.h_upd(h) + x = self.x_upd(x) + h = in_conv(h) + else: + h = self.in_layers(x) + emb_out = self.emb_layers(emb).type(h.dtype) + while len(emb_out.shape) < len(h.shape): + emb_out = emb_out[..., None] + if self.use_scale_shift_norm: + out_norm, out_rest = self.out_layers[0], self.out_layers[1:] + scale, shift = th.chunk(emb_out, 2, dim=1) + h = out_norm(h) * (1 + scale) + shift + h = out_rest(h) + else: + h = h + emb_out + h = self.out_layers(h) + return self.skip_connection(x) + h + + +class AttentionBlock(nn.Module): + """ + An attention block that allows spatial positions to attend to each other. + Originally ported from here, but adapted to the N-d case. + https://github.com/hojonathanho/diffusion/blob/1e0dceb3b3495bbe19116a5e1b3596cd0706c543/diffusion_tf/models/unet.py#L66. + """ + + def __init__( + self, + channels, + num_heads=1, + num_head_channels=-1, + use_checkpoint=False, + use_new_attention_order=False, + ): + super().__init__() + self.channels = channels + if num_head_channels == -1: + self.num_heads = num_heads + else: + assert ( + channels % num_head_channels == 0 + ), f"q,k,v channels {channels} is not divisible by num_head_channels {num_head_channels}" + self.num_heads = channels // num_head_channels + self.use_checkpoint = use_checkpoint + self.norm = normalization(channels) + self.qkv = conv_nd(1, channels, channels * 3, 1) + if use_new_attention_order: + # split qkv before split heads + self.attention = QKVAttention(self.num_heads) + else: + # split heads before split qkv + self.attention = QKVAttentionLegacy(self.num_heads) + + self.proj_out = zero_module(conv_nd(1, channels, channels, 1)) + + def forward(self, x): + return checkpoint( + self._forward, (x,), self.parameters(), True + ) # TODO: check checkpoint usage, is True # TODO: fix the .half call!!! + # return pt_checkpoint(self._forward, x) # pytorch + + def _forward(self, x): + b, c, *spatial = x.shape + x = x.reshape(b, c, -1).contiguous() + qkv = self.qkv(self.norm(x)).contiguous() + h = self.attention(qkv).contiguous() + h = self.proj_out(h).contiguous() + return (x + h).reshape(b, c, *spatial).contiguous() + + +def count_flops_attn(model, _x, y): + """ + A counter for the `thop` package to count the operations in an + attention operation. + Meant to be used like: + macs, params = thop.profile( + model, + inputs=(inputs, timestamps), + custom_ops={QKVAttention: QKVAttention.count_flops}, + ) + """ + b, c, *spatial = y[0].shape + num_spatial = int(np.prod(spatial)) + # We perform two matmuls with the same number of ops. + # The first computes the weight matrix, the second computes + # the combination of the value vectors. + matmul_ops = 2 * b * (num_spatial**2) * c + model.total_ops += th.DoubleTensor([matmul_ops]) + + +class QKVAttentionLegacy(nn.Module): + """ + A module which performs QKV attention. Matches legacy QKVAttention + input/ouput heads shaping + """ + + def __init__(self, n_heads): + super().__init__() + self.n_heads = n_heads + + def forward(self, qkv): + """ + Apply QKV attention. + :param qkv: an [N x (H * 3 * C) x T] tensor of Qs, Ks, and Vs. + :return: an [N x (H * C) x T] tensor after attention. + """ + bs, width, length = qkv.shape + assert width % (3 * self.n_heads) == 0 + ch = width // (3 * self.n_heads) + q, k, v = ( + qkv.reshape(bs * self.n_heads, ch * 3, length).contiguous().split(ch, dim=1) + ) + scale = 1 / math.sqrt(math.sqrt(ch)) + weight = th.einsum( + "bct,bcs->bts", q * scale, k * scale + ) # More stable with f16 than dividing afterwards + weight = th.softmax(weight.float(), dim=-1).type(weight.dtype) + a = th.einsum("bts,bcs->bct", weight, v) + return a.reshape(bs, -1, length).contiguous() + + @staticmethod + def count_flops(model, _x, y): + return count_flops_attn(model, _x, y) + + +class QKVAttention(nn.Module): + """ + A module which performs QKV attention and splits in a different order. + """ + + def __init__(self, n_heads): + super().__init__() + self.n_heads = n_heads + + def forward(self, qkv): + """ + Apply QKV attention. + :param qkv: an [N x (3 * H * C) x T] tensor of Qs, Ks, and Vs. + :return: an [N x (H * C) x T] tensor after attention. + """ + bs, width, length = qkv.shape + assert width % (3 * self.n_heads) == 0 + ch = width // (3 * self.n_heads) + q, k, v = qkv.chunk(3, dim=1) + scale = 1 / math.sqrt(math.sqrt(ch)) + weight = th.einsum( + "bct,bcs->bts", + (q * scale).view(bs * self.n_heads, ch, length), + (k * scale).view(bs * self.n_heads, ch, length), + ) # More stable with f16 than dividing afterwards + weight = th.softmax(weight.float(), dim=-1).type(weight.dtype) + a = th.einsum( + "bts,bcs->bct", + weight, + v.reshape(bs * self.n_heads, ch, length).contiguous(), + ) + return a.reshape(bs, -1, length).contiguous() + + @staticmethod + def count_flops(model, _x, y): + return count_flops_attn(model, _x, y) + + +class UNetModel(nn.Module): + """ + The full UNet model with attention and timestep embedding. + :param in_channels: channels in the input Tensor. + :param model_channels: base channel count for the model. + :param out_channels: channels in the output Tensor. + :param num_res_blocks: number of residual blocks per downsample. + :param attention_resolutions: a collection of downsample rates at which + attention will take place. May be a set, list, or tuple. + For example, if this contains 4, then at 4x downsampling, attention + will be used. + :param dropout: the dropout probability. + :param channel_mult: channel multiplier for each level of the UNet. + :param conv_resample: if True, use learned convolutions for upsampling and + downsampling. + :param dims: determines if the signal is 1D, 2D, or 3D. + :param num_classes: if specified (as an int), then this model will be + class-conditional with `num_classes` classes. + :param use_checkpoint: use gradient checkpointing to reduce memory usage. + :param num_heads: the number of attention heads in each attention layer. + :param num_heads_channels: if specified, ignore num_heads and instead use + a fixed channel width per attention head. + :param num_heads_upsample: works with num_heads to set a different number + of heads for upsampling. Deprecated. + :param use_scale_shift_norm: use a FiLM-like conditioning mechanism. + :param resblock_updown: use residual blocks for up/downsampling. + :param use_new_attention_order: use a different attention pattern for potentially + increased efficiency. + """ + + def __init__( + self, + image_size, + in_channels, + model_channels, + out_channels, + num_res_blocks, + attention_resolutions, + dropout=0, + channel_mult=(1, 2, 4, 8), + conv_resample=True, + dims=2, + num_classes=None, + extra_film_condition_dim=None, + use_checkpoint=False, + use_fp16=False, + num_heads=-1, + num_head_channels=-1, + num_heads_upsample=-1, + use_scale_shift_norm=False, + extra_film_use_concat=False, # If true, concatenate extrafilm condition with time embedding, else addition + resblock_updown=False, + use_new_attention_order=False, + use_spatial_transformer=False, # custom transformer support + transformer_depth=1, # custom transformer support + context_dim=None, # custom transformer support + n_embed=None, # custom support for prediction of discrete ids into codebook of first stage vq model + legacy=True, + ): + super().__init__() + if num_heads_upsample == -1: + num_heads_upsample = num_heads + + if num_heads == -1: + assert ( + num_head_channels != -1 + ), "Either num_heads or num_head_channels has to be set" + + if num_head_channels == -1: + assert ( + num_heads != -1 + ), "Either num_heads or num_head_channels has to be set" + + self.image_size = image_size + self.in_channels = in_channels + self.model_channels = model_channels + self.out_channels = out_channels + self.num_res_blocks = num_res_blocks + self.attention_resolutions = attention_resolutions + self.dropout = dropout + self.channel_mult = channel_mult + self.conv_resample = conv_resample + self.num_classes = num_classes + self.extra_film_condition_dim = extra_film_condition_dim + self.use_checkpoint = use_checkpoint + self.dtype = th.float16 if use_fp16 else th.float32 + self.num_heads = num_heads + self.num_head_channels = num_head_channels + self.num_heads_upsample = num_heads_upsample + self.predict_codebook_ids = n_embed is not None + self.extra_film_use_concat = extra_film_use_concat + time_embed_dim = model_channels * 4 + self.time_embed = nn.Sequential( + linear(model_channels, time_embed_dim), + nn.SiLU(), + linear(time_embed_dim, time_embed_dim), + ) + + assert not ( + self.num_classes is not None and self.extra_film_condition_dim is not None + ), "As for the condition of theh UNet model, you can only set using class label or an extra embedding vector (such as from CLAP). You cannot set both num_classes and extra_film_condition_dim." + + if self.num_classes is not None: + self.label_emb = nn.Embedding(num_classes, time_embed_dim) + + self.use_extra_film_by_concat = ( + self.extra_film_condition_dim is not None and self.extra_film_use_concat + ) + self.use_extra_film_by_addition = ( + self.extra_film_condition_dim is not None and not self.extra_film_use_concat + ) + + if self.extra_film_condition_dim is not None: + self.film_emb = nn.Linear(self.extra_film_condition_dim, time_embed_dim) + # print("+ Use extra condition on UNet channel using Film. Extra condition dimension is %s. " % self.extra_film_condition_dim) + # if(self.use_extra_film_by_concat): + # print("\t By concatenation with time embedding") + # elif(self.use_extra_film_by_concat): + # print("\t By addition with time embedding") + + if use_spatial_transformer and ( + self.use_extra_film_by_concat or self.use_extra_film_by_addition + ): + # print("+ Spatial transformer will only be used as self-attention. Because you have choose to use film as your global condition.") + spatial_transformer_no_context = True + else: + spatial_transformer_no_context = False + + if use_spatial_transformer and not spatial_transformer_no_context: + assert ( + context_dim is not None + ), "Fool!! You forgot to include the dimension of your cross-attention conditioning..." + + if context_dim is not None and not spatial_transformer_no_context: + assert ( + use_spatial_transformer + ), "Fool!! You forgot to use the spatial transformer for your cross-attention conditioning..." + from omegaconf.listconfig import ListConfig + + if type(context_dim) == ListConfig: + context_dim = list(context_dim) + + self.input_blocks = nn.ModuleList( + [ + TimestepEmbedSequential( + conv_nd(dims, in_channels, model_channels, 3, padding=1) + ) + ] + ) + self._feature_size = model_channels + input_block_chans = [model_channels] + ch = model_channels + ds = 1 + for level, mult in enumerate(channel_mult): + for _ in range(num_res_blocks): + layers = [ + ResBlock( + ch, + time_embed_dim + if (not self.use_extra_film_by_concat) + else time_embed_dim * 2, + dropout, + out_channels=mult * model_channels, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + ) + ] + ch = mult * model_channels + if ds in attention_resolutions: + if num_head_channels == -1: + dim_head = ch // num_heads + else: + num_heads = ch // num_head_channels + dim_head = num_head_channels + if legacy: + dim_head = ( + ch // num_heads + if use_spatial_transformer + else num_head_channels + ) + layers.append( + AttentionBlock( + ch, + use_checkpoint=use_checkpoint, + num_heads=num_heads, + num_head_channels=dim_head, + use_new_attention_order=use_new_attention_order, + ) + if not use_spatial_transformer + else SpatialTransformer( + ch, + num_heads, + dim_head, + depth=transformer_depth, + context_dim=context_dim, + no_context=spatial_transformer_no_context, + ) + ) + self.input_blocks.append(TimestepEmbedSequential(*layers)) + self._feature_size += ch + input_block_chans.append(ch) + if level != len(channel_mult) - 1: + out_ch = ch + self.input_blocks.append( + TimestepEmbedSequential( + ResBlock( + ch, + time_embed_dim + if (not self.use_extra_film_by_concat) + else time_embed_dim * 2, + dropout, + out_channels=out_ch, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + down=True, + ) + if resblock_updown + else Downsample( + ch, conv_resample, dims=dims, out_channels=out_ch + ) + ) + ) + ch = out_ch + input_block_chans.append(ch) + ds *= 2 + self._feature_size += ch + + if num_head_channels == -1: + dim_head = ch // num_heads + else: + num_heads = ch // num_head_channels + dim_head = num_head_channels + if legacy: + # num_heads = 1 + dim_head = ch // num_heads if use_spatial_transformer else num_head_channels + self.middle_block = TimestepEmbedSequential( + ResBlock( + ch, + time_embed_dim + if (not self.use_extra_film_by_concat) + else time_embed_dim * 2, + dropout, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + ), + AttentionBlock( + ch, + use_checkpoint=use_checkpoint, + num_heads=num_heads, + num_head_channels=dim_head, + use_new_attention_order=use_new_attention_order, + ) + if not use_spatial_transformer + else SpatialTransformer( + ch, + num_heads, + dim_head, + depth=transformer_depth, + context_dim=context_dim, + no_context=spatial_transformer_no_context, + ), + ResBlock( + ch, + time_embed_dim + if (not self.use_extra_film_by_concat) + else time_embed_dim * 2, + dropout, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + ), + ) + self._feature_size += ch + + self.output_blocks = nn.ModuleList([]) + for level, mult in list(enumerate(channel_mult))[::-1]: + for i in range(num_res_blocks + 1): + ich = input_block_chans.pop() + layers = [ + ResBlock( + ch + ich, + time_embed_dim + if (not self.use_extra_film_by_concat) + else time_embed_dim * 2, + dropout, + out_channels=model_channels * mult, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + ) + ] + ch = model_channels * mult + if ds in attention_resolutions: + if num_head_channels == -1: + dim_head = ch // num_heads + else: + num_heads = ch // num_head_channels + dim_head = num_head_channels + if legacy: + # num_heads = 1 + dim_head = ( + ch // num_heads + if use_spatial_transformer + else num_head_channels + ) + layers.append( + AttentionBlock( + ch, + use_checkpoint=use_checkpoint, + num_heads=num_heads_upsample, + num_head_channels=dim_head, + use_new_attention_order=use_new_attention_order, + ) + if not use_spatial_transformer + else SpatialTransformer( + ch, + num_heads, + dim_head, + depth=transformer_depth, + context_dim=context_dim, + no_context=spatial_transformer_no_context, + ) + ) + if level and i == num_res_blocks: + out_ch = ch + layers.append( + ResBlock( + ch, + time_embed_dim + if (not self.use_extra_film_by_concat) + else time_embed_dim * 2, + dropout, + out_channels=out_ch, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + up=True, + ) + if resblock_updown + else Upsample(ch, conv_resample, dims=dims, out_channels=out_ch) + ) + ds //= 2 + self.output_blocks.append(TimestepEmbedSequential(*layers)) + self._feature_size += ch + + self.out = nn.Sequential( + normalization(ch), + nn.SiLU(), + zero_module(conv_nd(dims, model_channels, out_channels, 3, padding=1)), + ) + if self.predict_codebook_ids: + self.id_predictor = nn.Sequential( + normalization(ch), + conv_nd(dims, model_channels, n_embed, 1), + # nn.LogSoftmax(dim=1) # change to cross_entropy and produce non-normalized logits + ) + + self.shape_reported = False + + def convert_to_fp16(self): + """ + Convert the torso of the model to float16. + """ + self.input_blocks.apply(convert_module_to_f16) + self.middle_block.apply(convert_module_to_f16) + self.output_blocks.apply(convert_module_to_f16) + + def convert_to_fp32(self): + """ + Convert the torso of the model to float32. + """ + self.input_blocks.apply(convert_module_to_f32) + self.middle_block.apply(convert_module_to_f32) + self.output_blocks.apply(convert_module_to_f32) + + def forward(self, x, timesteps=None, context=None, y=None, **kwargs): + """ + Apply the model to an input batch. + :param x: an [N x C x ...] Tensor of inputs. + :param timesteps: a 1-D batch of timesteps. + :param context: conditioning plugged in via crossattn + :param y: an [N] Tensor of labels, if class-conditional. an [N, extra_film_condition_dim] Tensor if film-embed conditional + :return: an [N x C x ...] Tensor of outputs. + """ + if not self.shape_reported: + # print("The shape of UNet input is", x.size()) + self.shape_reported = True + + assert (y is not None) == ( + self.num_classes is not None or self.extra_film_condition_dim is not None + ), "must specify y if and only if the model is class-conditional or film embedding conditional" + hs = [] + t_emb = timestep_embedding(timesteps, self.model_channels, repeat_only=False) + emb = self.time_embed(t_emb) + + if self.num_classes is not None: + assert y.shape == (x.shape[0],) + emb = emb + self.label_emb(y) + + if self.use_extra_film_by_addition: + emb = emb + self.film_emb(y) + elif self.use_extra_film_by_concat: + emb = th.cat([emb, self.film_emb(y)], dim=-1) + + h = x.type(self.dtype) + for module in self.input_blocks: + h = module(h, emb, context) + hs.append(h) + h = self.middle_block(h, emb, context) + for module in self.output_blocks: + h = th.cat([h, hs.pop()], dim=1) + h = module(h, emb, context) + h = h.type(x.dtype) + if self.predict_codebook_ids: + return self.id_predictor(h) + else: + return self.out(h) + + +class EncoderUNetModel(nn.Module): + """ + The half UNet model with attention and timestep embedding. + For usage, see UNet. + """ + + def __init__( + self, + image_size, + in_channels, + model_channels, + out_channels, + num_res_blocks, + attention_resolutions, + dropout=0, + channel_mult=(1, 2, 4, 8), + conv_resample=True, + dims=2, + use_checkpoint=False, + use_fp16=False, + num_heads=1, + num_head_channels=-1, + num_heads_upsample=-1, + use_scale_shift_norm=False, + resblock_updown=False, + use_new_attention_order=False, + pool="adaptive", + *args, + **kwargs, + ): + super().__init__() + + if num_heads_upsample == -1: + num_heads_upsample = num_heads + + self.in_channels = in_channels + self.model_channels = model_channels + self.out_channels = out_channels + self.num_res_blocks = num_res_blocks + self.attention_resolutions = attention_resolutions + self.dropout = dropout + self.channel_mult = channel_mult + self.conv_resample = conv_resample + self.use_checkpoint = use_checkpoint + self.dtype = th.float16 if use_fp16 else th.float32 + self.num_heads = num_heads + self.num_head_channels = num_head_channels + self.num_heads_upsample = num_heads_upsample + + time_embed_dim = model_channels * 4 + self.time_embed = nn.Sequential( + linear(model_channels, time_embed_dim), + nn.SiLU(), + linear(time_embed_dim, time_embed_dim), + ) + + self.input_blocks = nn.ModuleList( + [ + TimestepEmbedSequential( + conv_nd(dims, in_channels, model_channels, 3, padding=1) + ) + ] + ) + self._feature_size = model_channels + input_block_chans = [model_channels] + ch = model_channels + ds = 1 + for level, mult in enumerate(channel_mult): + for _ in range(num_res_blocks): + layers = [ + ResBlock( + ch, + time_embed_dim, + dropout, + out_channels=mult * model_channels, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + ) + ] + ch = mult * model_channels + if ds in attention_resolutions: + layers.append( + AttentionBlock( + ch, + use_checkpoint=use_checkpoint, + num_heads=num_heads, + num_head_channels=num_head_channels, + use_new_attention_order=use_new_attention_order, + ) + ) + self.input_blocks.append(TimestepEmbedSequential(*layers)) + self._feature_size += ch + input_block_chans.append(ch) + if level != len(channel_mult) - 1: + out_ch = ch + self.input_blocks.append( + TimestepEmbedSequential( + ResBlock( + ch, + time_embed_dim, + dropout, + out_channels=out_ch, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + down=True, + ) + if resblock_updown + else Downsample( + ch, conv_resample, dims=dims, out_channels=out_ch + ) + ) + ) + ch = out_ch + input_block_chans.append(ch) + ds *= 2 + self._feature_size += ch + + self.middle_block = TimestepEmbedSequential( + ResBlock( + ch, + time_embed_dim, + dropout, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + ), + AttentionBlock( + ch, + use_checkpoint=use_checkpoint, + num_heads=num_heads, + num_head_channels=num_head_channels, + use_new_attention_order=use_new_attention_order, + ), + ResBlock( + ch, + time_embed_dim, + dropout, + dims=dims, + use_checkpoint=use_checkpoint, + use_scale_shift_norm=use_scale_shift_norm, + ), + ) + self._feature_size += ch + self.pool = pool + if pool == "adaptive": + self.out = nn.Sequential( + normalization(ch), + nn.SiLU(), + nn.AdaptiveAvgPool2d((1, 1)), + zero_module(conv_nd(dims, ch, out_channels, 1)), + nn.Flatten(), + ) + elif pool == "attention": + assert num_head_channels != -1 + self.out = nn.Sequential( + normalization(ch), + nn.SiLU(), + AttentionPool2d( + (image_size // ds), ch, num_head_channels, out_channels + ), + ) + elif pool == "spatial": + self.out = nn.Sequential( + nn.Linear(self._feature_size, 2048), + nn.ReLU(), + nn.Linear(2048, self.out_channels), + ) + elif pool == "spatial_v2": + self.out = nn.Sequential( + nn.Linear(self._feature_size, 2048), + normalization(2048), + nn.SiLU(), + nn.Linear(2048, self.out_channels), + ) + else: + raise NotImplementedError(f"Unexpected {pool} pooling") + + def convert_to_fp16(self): + """ + Convert the torso of the model to float16. + """ + self.input_blocks.apply(convert_module_to_f16) + self.middle_block.apply(convert_module_to_f16) + + def convert_to_fp32(self): + """ + Convert the torso of the model to float32. + """ + self.input_blocks.apply(convert_module_to_f32) + self.middle_block.apply(convert_module_to_f32) + + def forward(self, x, timesteps): + """ + Apply the model to an input batch. + :param x: an [N x C x ...] Tensor of inputs. + :param timesteps: a 1-D batch of timesteps. + :return: an [N x K] Tensor of outputs. + """ + emb = self.time_embed(timestep_embedding(timesteps, self.model_channels)) + + results = [] + h = x.type(self.dtype) + for module in self.input_blocks: + h = module(h, emb) + if self.pool.startswith("spatial"): + results.append(h.type(x.dtype).mean(dim=(2, 3))) + h = self.middle_block(h, emb) + if self.pool.startswith("spatial"): + results.append(h.type(x.dtype).mean(dim=(2, 3))) + h = th.cat(results, axis=-1) + return self.out(h) + else: + h = h.type(x.dtype) + return self.out(h) diff --git a/src/audioldm/latent_diffusion/util.py b/src/audioldm/latent_diffusion/util.py new file mode 100644 index 0000000000000000000000000000000000000000..a0457e523f287aef2c97f6854c89480073ab8674 --- /dev/null +++ b/src/audioldm/latent_diffusion/util.py @@ -0,0 +1,295 @@ +# adopted from +# https://github.com/openai/improved-diffusion/blob/main/improved_diffusion/gaussian_diffusion.py +# and +# https://github.com/lucidrains/denoising-diffusion-pytorch/blob/7706bdfc6f527f58d33f84b7b522e61e6e3164b3/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py +# and +# https://github.com/openai/guided-diffusion/blob/0ba878e517b276c45d1195eb29f6f5f72659a05b/guided_diffusion/nn.py +# +# thanks! + + +import os +import math +import torch +import torch.nn as nn +import numpy as np +from einops import repeat + +from audioldm.utils import instantiate_from_config + + +def make_beta_schedule( + schedule, n_timestep, linear_start=1e-4, linear_end=2e-2, cosine_s=8e-3 +): + if schedule == "linear": + betas = ( + torch.linspace( + linear_start**0.5, linear_end**0.5, n_timestep, dtype=torch.float64 + ) + ** 2 + ) + + elif schedule == "cosine": + timesteps = ( + torch.arange(n_timestep + 1, dtype=torch.float64) / n_timestep + cosine_s + ) + alphas = timesteps / (1 + cosine_s) * np.pi / 2 + alphas = torch.cos(alphas).pow(2) + alphas = alphas / alphas[0] + betas = 1 - alphas[1:] / alphas[:-1] + betas = np.clip(betas, a_min=0, a_max=0.999) + + elif schedule == "sqrt_linear": + betas = torch.linspace( + linear_start, linear_end, n_timestep, dtype=torch.float64 + ) + elif schedule == "sqrt": + betas = ( + torch.linspace(linear_start, linear_end, n_timestep, dtype=torch.float64) + ** 0.5 + ) + else: + raise ValueError(f"schedule '{schedule}' unknown.") + return betas.numpy() + + +def make_ddim_timesteps( + ddim_discr_method, num_ddim_timesteps, num_ddpm_timesteps, verbose=True +): + if ddim_discr_method == "uniform": + c = num_ddpm_timesteps // num_ddim_timesteps + ddim_timesteps = np.asarray(list(range(0, num_ddpm_timesteps, c))) + elif ddim_discr_method == "quad": + ddim_timesteps = ( + (np.linspace(0, np.sqrt(num_ddpm_timesteps * 0.8), num_ddim_timesteps)) ** 2 + ).astype(int) + else: + raise NotImplementedError( + f'There is no ddim discretization method called "{ddim_discr_method}"' + ) + + # assert ddim_timesteps.shape[0] == num_ddim_timesteps + # add one to get the final alpha values right (the ones from first scale to data during sampling) + steps_out = ddim_timesteps + 1 + if verbose: + print(f"Selected timesteps for ddim sampler: {steps_out}") + return steps_out + + +def make_ddim_sampling_parameters(alphacums, ddim_timesteps, eta, verbose=True): + # select alphas for computing the variance schedule + alphas = alphacums[ddim_timesteps] + alphas_prev = np.asarray([alphacums[0]] + alphacums[ddim_timesteps[:-1]].tolist()) + + # according the the formula provided in https://arxiv.org/abs/2010.02502 + sigmas = eta * np.sqrt( + (1 - alphas_prev) / (1 - alphas) * (1 - alphas / alphas_prev) + ) + if verbose: + print( + f"Selected alphas for ddim sampler: a_t: {alphas}; a_(t-1): {alphas_prev}" + ) + print( + f"For the chosen value of eta, which is {eta}, " + f"this results in the following sigma_t schedule for ddim sampler {sigmas}" + ) + return sigmas, alphas, alphas_prev + + +def betas_for_alpha_bar(num_diffusion_timesteps, alpha_bar, max_beta=0.999): + """ + Create a beta schedule that discretizes the given alpha_t_bar function, + which defines the cumulative product of (1-beta) over time from t = [0,1]. + :param num_diffusion_timesteps: the number of betas to produce. + :param alpha_bar: a lambda that takes an argument t from 0 to 1 and + produces the cumulative product of (1-beta) up to that + part of the diffusion process. + :param max_beta: the maximum beta to use; use values lower than 1 to + prevent singularities. + """ + betas = [] + for i in range(num_diffusion_timesteps): + t1 = i / num_diffusion_timesteps + t2 = (i + 1) / num_diffusion_timesteps + betas.append(min(1 - alpha_bar(t2) / alpha_bar(t1), max_beta)) + return np.array(betas) + + +def extract_into_tensor(a, t, x_shape): + b, *_ = t.shape + out = a.gather(-1, t).contiguous() + return out.reshape(b, *((1,) * (len(x_shape) - 1))).contiguous() + + +def checkpoint(func, inputs, params, flag): + """ + Evaluate a function without caching intermediate activations, allowing for + reduced memory at the expense of extra compute in the backward pass. + :param func: the function to evaluate. + :param inputs: the argument sequence to pass to `func`. + :param params: a sequence of parameters `func` depends on but does not + explicitly take as arguments. + :param flag: if False, disable gradient checkpointing. + """ + if flag: + args = tuple(inputs) + tuple(params) + return CheckpointFunction.apply(func, len(inputs), *args) + else: + return func(*inputs) + + +class CheckpointFunction(torch.autograd.Function): + @staticmethod + def forward(ctx, run_function, length, *args): + ctx.run_function = run_function + ctx.input_tensors = list(args[:length]) + ctx.input_params = list(args[length:]) + + with torch.no_grad(): + output_tensors = ctx.run_function(*ctx.input_tensors) + return output_tensors + + @staticmethod + def backward(ctx, *output_grads): + ctx.input_tensors = [x.detach().requires_grad_(True) for x in ctx.input_tensors] + with torch.enable_grad(): + # Fixes a bug where the first op in run_function modifies the + # Tensor storage in place, which is not allowed for detach()'d + # Tensors. + shallow_copies = [x.view_as(x) for x in ctx.input_tensors] + output_tensors = ctx.run_function(*shallow_copies) + input_grads = torch.autograd.grad( + output_tensors, + ctx.input_tensors + ctx.input_params, + output_grads, + allow_unused=True, + ) + del ctx.input_tensors + del ctx.input_params + del output_tensors + return (None, None) + input_grads + + +def timestep_embedding(timesteps, dim, max_period=10000, repeat_only=False): + """ + Create sinusoidal timestep embeddings. + :param timesteps: a 1-D Tensor of N indices, one per batch element. + These may be fractional. + :param dim: the dimension of the output. + :param max_period: controls the minimum frequency of the embeddings. + :return: an [N x dim] Tensor of positional embeddings. + """ + if not repeat_only: + half = dim // 2 + freqs = torch.exp( + -math.log(max_period) + * torch.arange(start=0, end=half, dtype=torch.float32) + / half + ).to(device=timesteps.device) + args = timesteps[:, None].float() * freqs[None] + embedding = torch.cat([torch.cos(args), torch.sin(args)], dim=-1) + if dim % 2: + embedding = torch.cat( + [embedding, torch.zeros_like(embedding[:, :1])], dim=-1 + ) + else: + embedding = repeat(timesteps, "b -> b d", d=dim) + return embedding + + +def zero_module(module): + """ + Zero out the parameters of a module and return it. + """ + for p in module.parameters(): + p.detach().zero_() + return module + + +def scale_module(module, scale): + """ + Scale the parameters of a module and return it. + """ + for p in module.parameters(): + p.detach().mul_(scale) + return module + + +def mean_flat(tensor): + """ + Take the mean over all non-batch dimensions. + """ + return tensor.mean(dim=list(range(1, len(tensor.shape)))) + + +def normalization(channels): + """ + Make a standard normalization layer. + :param channels: number of input channels. + :return: an nn.Module for normalization. + """ + return GroupNorm32(32, channels) + + +# PyTorch 1.7 has SiLU, but we support PyTorch 1.5. +class SiLU(nn.Module): + def forward(self, x): + return x * torch.sigmoid(x) + + +class GroupNorm32(nn.GroupNorm): + def forward(self, x): + return super().forward(x.float()).type(x.dtype) + + +def conv_nd(dims, *args, **kwargs): + """ + Create a 1D, 2D, or 3D convolution module. + """ + if dims == 1: + return nn.Conv1d(*args, **kwargs) + elif dims == 2: + return nn.Conv2d(*args, **kwargs) + elif dims == 3: + return nn.Conv3d(*args, **kwargs) + raise ValueError(f"unsupported dimensions: {dims}") + + +def linear(*args, **kwargs): + """ + Create a linear module. + """ + return nn.Linear(*args, **kwargs) + + +def avg_pool_nd(dims, *args, **kwargs): + """ + Create a 1D, 2D, or 3D average pooling module. + """ + if dims == 1: + return nn.AvgPool1d(*args, **kwargs) + elif dims == 2: + return nn.AvgPool2d(*args, **kwargs) + elif dims == 3: + return nn.AvgPool3d(*args, **kwargs) + raise ValueError(f"unsupported dimensions: {dims}") + + +class HybridConditioner(nn.Module): + def __init__(self, c_concat_config, c_crossattn_config): + super().__init__() + self.concat_conditioner = instantiate_from_config(c_concat_config) + self.crossattn_conditioner = instantiate_from_config(c_crossattn_config) + + def forward(self, c_concat, c_crossattn): + c_concat = self.concat_conditioner(c_concat) + c_crossattn = self.crossattn_conditioner(c_crossattn) + return {"c_concat": [c_concat], "c_crossattn": [c_crossattn]} + + +def noise_like(shape, device, repeat=False): + repeat_noise = lambda: torch.randn((1, *shape[1:]), device=device).repeat( + shape[0], *((1,) * (len(shape) - 1)) + ) + noise = lambda: torch.randn(shape, device=device) + return repeat_noise() if repeat else noise() diff --git a/src/audioldm/ldm.py b/src/audioldm/ldm.py new file mode 100644 index 0000000000000000000000000000000000000000..d293b8b7b127b91316be977ae9d6aea5752b4a4d --- /dev/null +++ b/src/audioldm/ldm.py @@ -0,0 +1,818 @@ +import os + +import torch +import numpy as np +from tqdm import tqdm +from audioldm.utils import default, instantiate_from_config, save_wave +from audioldm.latent_diffusion.ddpm import DDPM +from audioldm.variational_autoencoder.distributions import DiagonalGaussianDistribution +from audioldm.latent_diffusion.util import noise_like +from audioldm.latent_diffusion.ddim import DDIMSampler +import os + + +def disabled_train(self, mode=True): + """Overwrite model.train with this function to make sure train/eval mode + does not change anymore.""" + return self + + +class LatentDiffusion(DDPM): + """main class""" + + def __init__( + self, + device="cuda", + first_stage_config=None, + cond_stage_config=None, + num_timesteps_cond=None, + cond_stage_key="image", + cond_stage_trainable=False, + concat_mode=True, + cond_stage_forward=None, + conditioning_key=None, + scale_factor=1.0, + scale_by_std=False, + base_learning_rate=None, + *args, + **kwargs, + ): + self.device = device + self.learning_rate = base_learning_rate + self.num_timesteps_cond = default(num_timesteps_cond, 1) + self.scale_by_std = scale_by_std + assert self.num_timesteps_cond <= kwargs["timesteps"] + # for backwards compatibility after implementation of DiffusionWrapper + if conditioning_key is None: + conditioning_key = "concat" if concat_mode else "crossattn" + if cond_stage_config == "__is_unconditional__": + conditioning_key = None + ckpt_path = kwargs.pop("ckpt_path", None) + ignore_keys = kwargs.pop("ignore_keys", []) + super().__init__(conditioning_key=conditioning_key, *args, **kwargs) + self.concat_mode = concat_mode + self.cond_stage_trainable = cond_stage_trainable + self.cond_stage_key = cond_stage_key + self.cond_stage_key_orig = cond_stage_key + try: + self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1 + except: + self.num_downs = 0 + if not scale_by_std: + self.scale_factor = scale_factor + else: + self.register_buffer("scale_factor", torch.tensor(scale_factor)) + self.instantiate_first_stage(first_stage_config) + self.instantiate_cond_stage(cond_stage_config) + self.cond_stage_forward = cond_stage_forward + self.clip_denoised = False + + def make_cond_schedule( + self, + ): + self.cond_ids = torch.full( + size=(self.num_timesteps,), + fill_value=self.num_timesteps - 1, + dtype=torch.long, + ) + ids = torch.round( + torch.linspace(0, self.num_timesteps - 1, self.num_timesteps_cond) + ).long() + self.cond_ids[: self.num_timesteps_cond] = ids + + def register_schedule( + self, + given_betas=None, + beta_schedule="linear", + timesteps=1000, + linear_start=1e-4, + linear_end=2e-2, + cosine_s=8e-3, + ): + super().register_schedule( + given_betas, beta_schedule, timesteps, linear_start, linear_end, cosine_s + ) + + self.shorten_cond_schedule = self.num_timesteps_cond > 1 + if self.shorten_cond_schedule: + self.make_cond_schedule() + + def instantiate_first_stage(self, config): + model = instantiate_from_config(config) + self.first_stage_model = model.eval() + self.first_stage_model.train = disabled_train + for param in self.first_stage_model.parameters(): + param.requires_grad = False + + def instantiate_cond_stage(self, config): + if not self.cond_stage_trainable: + if config == "__is_first_stage__": + print("Using first stage also as cond stage.") + self.cond_stage_model = self.first_stage_model + elif config == "__is_unconditional__": + print(f"Training {self.__class__.__name__} as an unconditional model.") + self.cond_stage_model = None + # self.be_unconditional = True + else: + model = instantiate_from_config(config) + self.cond_stage_model = model.eval() + self.cond_stage_model.train = disabled_train + for param in self.cond_stage_model.parameters(): + param.requires_grad = False + else: + assert config != "__is_first_stage__" + assert config != "__is_unconditional__" + model = instantiate_from_config(config) + self.cond_stage_model = model + self.cond_stage_model = self.cond_stage_model.to(self.device) + + def get_first_stage_encoding(self, encoder_posterior): + if isinstance(encoder_posterior, DiagonalGaussianDistribution): + z = encoder_posterior.sample() + elif isinstance(encoder_posterior, torch.Tensor): + z = encoder_posterior + else: + raise NotImplementedError( + f"encoder_posterior of type '{type(encoder_posterior)}' not yet implemented" + ) + return self.scale_factor * z + + def get_learned_conditioning(self, c): + if self.cond_stage_forward is None: + if hasattr(self.cond_stage_model, "encode") and callable( + self.cond_stage_model.encode + ): + c = self.cond_stage_model.encode(c) + if isinstance(c, DiagonalGaussianDistribution): + c = c.mode() + else: + # Text input is list + if type(c) == list and len(c) == 1: + c = self.cond_stage_model([c[0], c[0]]) + c = c[0:1] + else: + c = self.cond_stage_model(c) + else: + assert hasattr(self.cond_stage_model, self.cond_stage_forward) + c = getattr(self.cond_stage_model, self.cond_stage_forward)(c) + return c + + @torch.no_grad() + def get_input( + self, + batch, + k, + return_first_stage_encode=True, + return_first_stage_outputs=False, + force_c_encode=False, + cond_key=None, + return_original_cond=False, + bs=None, + ): + x = super().get_input(batch, k) + + if bs is not None: + x = x[:bs] + + x = x.to(self.device) + + if return_first_stage_encode: + encoder_posterior = self.encode_first_stage(x) + z = self.get_first_stage_encoding(encoder_posterior).detach() + else: + z = None + + if self.model.conditioning_key is not None: + if cond_key is None: + cond_key = self.cond_stage_key + if cond_key != self.first_stage_key: + if cond_key in ["caption", "coordinates_bbox"]: + xc = batch[cond_key] + elif cond_key == "class_label": + xc = batch + else: + # [bs, 1, 527] + xc = super().get_input(batch, cond_key) + if type(xc) == torch.Tensor: + xc = xc.to(self.device) + else: + xc = x + if not self.cond_stage_trainable or force_c_encode: + if isinstance(xc, dict) or isinstance(xc, list): + c = self.get_learned_conditioning(xc) + else: + c = self.get_learned_conditioning(xc.to(self.device)) + else: + c = xc + + if bs is not None: + c = c[:bs] + + else: + c = None + xc = None + if self.use_positional_encodings: + pos_x, pos_y = self.compute_latent_shifts(batch) + c = {"pos_x": pos_x, "pos_y": pos_y} + out = [z, c] + if return_first_stage_outputs: + xrec = self.decode_first_stage(z) + out.extend([x, xrec]) + if return_original_cond: + out.append(xc) + return out + + @torch.no_grad() + def decode_first_stage(self, z, predict_cids=False, force_not_quantize=False): + if predict_cids: + if z.dim() == 4: + z = torch.argmax(z.exp(), dim=1).long() + z = self.first_stage_model.quantize.get_codebook_entry(z, shape=None) + z = rearrange(z, "b h w c -> b c h w").contiguous() + + z = 1.0 / self.scale_factor * z + return self.first_stage_model.decode(z) + + def mel_spectrogram_to_waveform(self, mel): + # Mel: [bs, 1, t-steps, fbins] + if len(mel.size()) == 4: + mel = mel.squeeze(1) + mel = mel.permute(0, 2, 1) + waveform = self.first_stage_model.vocoder(mel) + waveform = waveform.cpu().detach().numpy() + return waveform + + @torch.no_grad() + def encode_first_stage(self, x): + return self.first_stage_model.encode(x) + + def apply_model(self, x_noisy, t, cond, return_ids=False): + + if isinstance(cond, dict): + # hybrid case, cond is exptected to be a dict + pass + else: + if not isinstance(cond, list): + cond = [cond] + if self.model.conditioning_key == "concat": + key = "c_concat" + elif self.model.conditioning_key == "crossattn": + key = "c_crossattn" + else: + key = "c_film" + + cond = {key: cond} + + x_recon = self.model(x_noisy, t, **cond) + + if isinstance(x_recon, tuple) and not return_ids: + return x_recon[0] + else: + return x_recon + + def p_mean_variance( + self, + x, + c, + t, + clip_denoised: bool, + return_codebook_ids=False, + quantize_denoised=False, + return_x0=False, + score_corrector=None, + corrector_kwargs=None, + ): + t_in = t + model_out = self.apply_model(x, t_in, c, return_ids=return_codebook_ids) + + if score_corrector is not None: + assert self.parameterization == "eps" + model_out = score_corrector.modify_score( + self, model_out, x, t, c, **corrector_kwargs + ) + + if return_codebook_ids: + model_out, logits = model_out + + if self.parameterization == "eps": + x_recon = self.predict_start_from_noise(x, t=t, noise=model_out) + elif self.parameterization == "x0": + x_recon = model_out + else: + raise NotImplementedError() + + if clip_denoised: + x_recon.clamp_(-1.0, 1.0) + if quantize_denoised: + x_recon, _, [_, _, indices] = self.first_stage_model.quantize(x_recon) + model_mean, posterior_variance, posterior_log_variance = self.q_posterior( + x_start=x_recon, x_t=x, t=t + ) + if return_codebook_ids: + return model_mean, posterior_variance, posterior_log_variance, logits + elif return_x0: + return model_mean, posterior_variance, posterior_log_variance, x_recon + else: + return model_mean, posterior_variance, posterior_log_variance + + @torch.no_grad() + def p_sample( + self, + x, + c, + t, + clip_denoised=False, + repeat_noise=False, + return_codebook_ids=False, + quantize_denoised=False, + return_x0=False, + temperature=1.0, + noise_dropout=0.0, + score_corrector=None, + corrector_kwargs=None, + ): + b, *_, device = *x.shape, x.device + outputs = self.p_mean_variance( + x=x, + c=c, + t=t, + clip_denoised=clip_denoised, + return_codebook_ids=return_codebook_ids, + quantize_denoised=quantize_denoised, + return_x0=return_x0, + score_corrector=score_corrector, + corrector_kwargs=corrector_kwargs, + ) + if return_codebook_ids: + raise DeprecationWarning("Support dropped.") + model_mean, _, model_log_variance, logits = outputs + elif return_x0: + model_mean, _, model_log_variance, x0 = outputs + else: + model_mean, _, model_log_variance = outputs + + noise = noise_like(x.shape, device, repeat_noise) * temperature + if noise_dropout > 0.0: + noise = torch.nn.functional.dropout(noise, p=noise_dropout) + # no noise when t == 0 + nonzero_mask = ( + (1 - (t == 0).float()).reshape(b, *((1,) * (len(x.shape) - 1))).contiguous() + ) + + if return_codebook_ids: + return model_mean + nonzero_mask * ( + 0.5 * model_log_variance + ).exp() * noise, logits.argmax(dim=1) + if return_x0: + return ( + model_mean + nonzero_mask * (0.5 * model_log_variance).exp() * noise, + x0, + ) + else: + return model_mean + nonzero_mask * (0.5 * model_log_variance).exp() * noise + + @torch.no_grad() + def progressive_denoising( + self, + cond, + shape, + verbose=True, + callback=None, + quantize_denoised=False, + img_callback=None, + mask=None, + x0=None, + temperature=1.0, + noise_dropout=0.0, + score_corrector=None, + corrector_kwargs=None, + batch_size=None, + x_T=None, + start_T=None, + log_every_t=None, + ): + if not log_every_t: + log_every_t = self.log_every_t + timesteps = self.num_timesteps + if batch_size is not None: + b = batch_size if batch_size is not None else shape[0] + shape = [batch_size] + list(shape) + else: + b = batch_size = shape[0] + if x_T is None: + img = torch.randn(shape, device=self.device) + else: + img = x_T + intermediates = [] + if cond is not None: + if isinstance(cond, dict): + cond = { + key: cond[key][:batch_size] + if not isinstance(cond[key], list) + else list(map(lambda x: x[:batch_size], cond[key])) + for key in cond + } + else: + cond = ( + [c[:batch_size] for c in cond] + if isinstance(cond, list) + else cond[:batch_size] + ) + + if start_T is not None: + timesteps = min(timesteps, start_T) + iterator = ( + tqdm( + reversed(range(0, timesteps)), + desc="Progressive Generation", + total=timesteps, + ) + if verbose + else reversed(range(0, timesteps)) + ) + if type(temperature) == float: + temperature = [temperature] * timesteps + + for i in iterator: + ts = torch.full((b,), i, device=self.device, dtype=torch.long) + if self.shorten_cond_schedule: + assert self.model.conditioning_key != "hybrid" + tc = self.cond_ids[ts].to(cond.device) + cond = self.q_sample(x_start=cond, t=tc, noise=torch.randn_like(cond)) + + img, x0_partial = self.p_sample( + img, + cond, + ts, + clip_denoised=self.clip_denoised, + quantize_denoised=quantize_denoised, + return_x0=True, + temperature=temperature[i], + noise_dropout=noise_dropout, + score_corrector=score_corrector, + corrector_kwargs=corrector_kwargs, + ) + if mask is not None: + assert x0 is not None + img_orig = self.q_sample(x0, ts) + img = img_orig * mask + (1.0 - mask) * img + + if i % log_every_t == 0 or i == timesteps - 1: + intermediates.append(x0_partial) + if callback: + callback(i) + if img_callback: + img_callback(img, i) + return img, intermediates + + @torch.no_grad() + def p_sample_loop( + self, + cond, + shape, + return_intermediates=False, + x_T=None, + verbose=True, + callback=None, + timesteps=None, + quantize_denoised=False, + mask=None, + x0=None, + img_callback=None, + start_T=None, + log_every_t=None, + ): + + if not log_every_t: + log_every_t = self.log_every_t + device = self.betas.device + b = shape[0] + if x_T is None: + img = torch.randn(shape, device=device) + else: + img = x_T + + intermediates = [img] + if timesteps is None: + timesteps = self.num_timesteps + + if start_T is not None: + timesteps = min(timesteps, start_T) + iterator = ( + tqdm(reversed(range(0, timesteps)), desc="Sampling t", total=timesteps) + if verbose + else reversed(range(0, timesteps)) + ) + + if mask is not None: + assert x0 is not None + assert x0.shape[2:3] == mask.shape[2:3] # spatial size has to match + + for i in iterator: + ts = torch.full((b,), i, device=device, dtype=torch.long) + if self.shorten_cond_schedule: + assert self.model.conditioning_key != "hybrid" + tc = self.cond_ids[ts].to(cond.device) + cond = self.q_sample(x_start=cond, t=tc, noise=torch.randn_like(cond)) + + img = self.p_sample( + img, + cond, + ts, + clip_denoised=self.clip_denoised, + quantize_denoised=quantize_denoised, + ) + if mask is not None: + img_orig = self.q_sample(x0, ts) + img = img_orig * mask + (1.0 - mask) * img + + if i % log_every_t == 0 or i == timesteps - 1: + intermediates.append(img) + if callback: + callback(i) + if img_callback: + img_callback(img, i) + + if return_intermediates: + return img, intermediates + return img + + @torch.no_grad() + def sample( + self, + cond, + batch_size=16, + return_intermediates=False, + x_T=None, + verbose=True, + timesteps=None, + quantize_denoised=False, + mask=None, + x0=None, + shape=None, + **kwargs, + ): + if shape is None: + shape = (batch_size, self.channels, self.latent_t_size, self.latent_f_size) + if cond is not None: + if isinstance(cond, dict): + cond = { + key: cond[key][:batch_size] + if not isinstance(cond[key], list) + else list(map(lambda x: x[:batch_size], cond[key])) + for key in cond + } + else: + cond = ( + [c[:batch_size] for c in cond] + if isinstance(cond, list) + else cond[:batch_size] + ) + return self.p_sample_loop( + cond, + shape, + return_intermediates=return_intermediates, + x_T=x_T, + verbose=verbose, + timesteps=timesteps, + quantize_denoised=quantize_denoised, + mask=mask, + x0=x0, + **kwargs, + ) + + @torch.no_grad() + def sample_log( + self, + cond, + batch_size, + ddim, + ddim_steps, + unconditional_guidance_scale=1.0, + unconditional_conditioning=None, + use_plms=False, + mask=None, + **kwargs, + ): + + if mask is not None: + shape = (self.channels, mask.size()[-2], mask.size()[-1]) + else: + shape = (self.channels, self.latent_t_size, self.latent_f_size) + + intermediate = None + if ddim and not use_plms: + # print("Use ddim sampler") + + ddim_sampler = DDIMSampler(self) + samples, intermediates = ddim_sampler.sample( + ddim_steps, + batch_size, + shape, + cond, + verbose=False, + unconditional_guidance_scale=unconditional_guidance_scale, + unconditional_conditioning=unconditional_conditioning, + mask=mask, + **kwargs, + ) + + else: + # print("Use DDPM sampler") + samples, intermediates = self.sample( + cond=cond, + batch_size=batch_size, + return_intermediates=True, + unconditional_guidance_scale=unconditional_guidance_scale, + mask=mask, + unconditional_conditioning=unconditional_conditioning, + **kwargs, + ) + + return samples, intermediate + + @torch.no_grad() + def generate_sample( + self, + batchs, + ddim_steps=200, + ddim_eta=1.0, + x_T=None, + n_candidate_gen_per_text=1, + unconditional_guidance_scale=1.0, + unconditional_conditioning=None, + name="waveform", + use_plms=False, + save=False, + **kwargs, + ): + # Generate n_candidate_gen_per_text times and select the best + # Batch: audio, text, fnames + assert x_T is None + try: + batchs = iter(batchs) + except TypeError: + raise ValueError("The first input argument should be an iterable object") + + if use_plms: + assert ddim_steps is not None + use_ddim = ddim_steps is not None + # waveform_save_path = os.path.join(self.get_log_dir(), name) + # os.makedirs(waveform_save_path, exist_ok=True) + # print("Waveform save path: ", waveform_save_path) + + with self.ema_scope("Generate"): + for batch in batchs: + z, c = self.get_input( + batch, + self.first_stage_key, + cond_key=self.cond_stage_key, + return_first_stage_outputs=False, + force_c_encode=True, + return_original_cond=False, + bs=None, + ) + text = super().get_input(batch, "text") + + # Generate multiple samples + batch_size = z.shape[0] * n_candidate_gen_per_text + c = torch.cat([c] * n_candidate_gen_per_text, dim=0) + text = text * n_candidate_gen_per_text + + if unconditional_guidance_scale != 1.0: + unconditional_conditioning = ( + self.cond_stage_model.get_unconditional_condition(batch_size) + ) + + samples, _ = self.sample_log( + cond=c, + batch_size=batch_size, + x_T=x_T, + ddim=use_ddim, + ddim_steps=ddim_steps, + eta=ddim_eta, + unconditional_guidance_scale=unconditional_guidance_scale, + unconditional_conditioning=unconditional_conditioning, + use_plms=use_plms, + ) + + if(torch.max(torch.abs(samples)) > 1e2): + samples = torch.clip(samples, min=-10, max=10) + + mel = self.decode_first_stage(samples) + + waveform = self.mel_spectrogram_to_waveform(mel) + + if waveform.shape[0] > 1: + similarity = self.cond_stage_model.cos_similarity( + torch.FloatTensor(waveform).squeeze(1), text + ) + + best_index = [] + for i in range(z.shape[0]): + candidates = similarity[i :: z.shape[0]] + max_index = torch.argmax(candidates).item() + best_index.append(i + max_index * z.shape[0]) + + waveform = waveform[best_index] + # print("Similarity between generated audio and text", similarity) + # print("Choose the following indexes:", best_index) + + return waveform + + @torch.no_grad() + def generate_sample_masked( + self, + batchs, + ddim_steps=200, + ddim_eta=1.0, + x_T=None, + n_candidate_gen_per_text=1, + unconditional_guidance_scale=1.0, + unconditional_conditioning=None, + name="waveform", + use_plms=False, + time_mask_ratio_start_and_end=(0.25, 0.75), + freq_mask_ratio_start_and_end=(0.75, 1.0), + save=False, + **kwargs, + ): + # Generate n_candidate_gen_per_text times and select the best + # Batch: audio, text, fnames + assert x_T is None + try: + batchs = iter(batchs) + except TypeError: + raise ValueError("The first input argument should be an iterable object") + + if use_plms: + assert ddim_steps is not None + use_ddim = ddim_steps is not None + # waveform_save_path = os.path.join(self.get_log_dir(), name) + # os.makedirs(waveform_save_path, exist_ok=True) + # print("Waveform save path: ", waveform_save_path) + + with self.ema_scope("Generate"): + for batch in batchs: + z, c = self.get_input( + batch, + self.first_stage_key, + cond_key=self.cond_stage_key, + return_first_stage_outputs=False, + force_c_encode=True, + return_original_cond=False, + bs=None, + ) + text = super().get_input(batch, "text") + + # Generate multiple samples + batch_size = z.shape[0] * n_candidate_gen_per_text + + _, h, w = z.shape[0], z.shape[2], z.shape[3] + + mask = torch.ones(batch_size, h, w).to(self.device) + + mask[:, int(h * time_mask_ratio_start_and_end[0]) : int(h * time_mask_ratio_start_and_end[1]), :] = 0 + mask[:, :, int(w * freq_mask_ratio_start_and_end[0]) : int(w * freq_mask_ratio_start_and_end[1])] = 0 + mask = mask[:, None, ...] + + c = torch.cat([c] * n_candidate_gen_per_text, dim=0) + text = text * n_candidate_gen_per_text + + if unconditional_guidance_scale != 1.0: + unconditional_conditioning = ( + self.cond_stage_model.get_unconditional_condition(batch_size) + ) + + samples, _ = self.sample_log( + cond=c, + batch_size=batch_size, + x_T=x_T, + ddim=use_ddim, + ddim_steps=ddim_steps, + eta=ddim_eta, + unconditional_guidance_scale=unconditional_guidance_scale, + unconditional_conditioning=unconditional_conditioning, + use_plms=use_plms, mask=mask, x0=torch.cat([z] * n_candidate_gen_per_text) + ) + + mel = self.decode_first_stage(samples) + + waveform = self.mel_spectrogram_to_waveform(mel) + + if waveform.shape[0] > 1: + similarity = self.cond_stage_model.cos_similarity( + torch.FloatTensor(waveform).squeeze(1), text + ) + + best_index = [] + for i in range(z.shape[0]): + candidates = similarity[i :: z.shape[0]] + max_index = torch.argmax(candidates).item() + best_index.append(i + max_index * z.shape[0]) + + waveform = waveform[best_index] + # print("Similarity between generated audio and text", similarity) + # print("Choose the following indexes:", best_index) + + return waveform \ No newline at end of file diff --git a/src/audioldm/pipeline.py b/src/audioldm/pipeline.py new file mode 100644 index 0000000000000000000000000000000000000000..8a725e463466be0d84a3ab090566e2722c71366b --- /dev/null +++ b/src/audioldm/pipeline.py @@ -0,0 +1,301 @@ +import os + +import argparse +import yaml +import torch +from torch import autocast +from tqdm import tqdm, trange + +from audioldm import LatentDiffusion, seed_everything +from audioldm.utils import default_audioldm_config, get_duration, get_bit_depth, get_metadata, download_checkpoint +from audioldm.audio import wav_to_fbank, TacotronSTFT, read_wav_file +from audioldm.latent_diffusion.ddim import DDIMSampler +from einops import repeat +import os + +def make_batch_for_text_to_audio(text, waveform=None, fbank=None, batchsize=1): + text = [text] * batchsize + if batchsize < 1: + print("Warning: Batchsize must be at least 1. Batchsize is set to .") + + if(fbank is None): + fbank = torch.zeros((batchsize, 1024, 64)) # Not used, here to keep the code format + else: + fbank = torch.FloatTensor(fbank) + fbank = fbank.expand(batchsize, 1024, 64) + assert fbank.size(0) == batchsize + + stft = torch.zeros((batchsize, 1024, 512)) # Not used + + if(waveform is None): + waveform = torch.zeros((batchsize, 160000)) # Not used + else: + waveform = torch.FloatTensor(waveform) + waveform = waveform.expand(batchsize, -1) + assert waveform.size(0) == batchsize + + fname = [""] * batchsize # Not used + + batch = ( + fbank, + stft, + None, + fname, + waveform, + text, + ) + return batch + +def round_up_duration(duration): + return int(round(duration/2.5) + 1) * 2.5 + +def build_model( + ckpt_path=None, + config=None, + model_name="audioldm-s-full" +): + print("Load AudioLDM: %s", model_name) + + if(ckpt_path is None): + ckpt_path = get_metadata()[model_name]["path"] + + if(not os.path.exists(ckpt_path)): + download_checkpoint(model_name) + + if torch.cuda.is_available(): + device = torch.device("cuda:0") + else: + device = torch.device("cpu") + + if config is not None: + assert type(config) is str + config = yaml.load(open(config, "r"), Loader=yaml.FullLoader) + else: + config = default_audioldm_config(model_name) + + # Use text as condition instead of using waveform during training + config["model"]["params"]["device"] = device + config["model"]["params"]["cond_stage_key"] = "text" + + # No normalization here + latent_diffusion = LatentDiffusion(**config["model"]["params"]) + + resume_from_checkpoint = ckpt_path + + checkpoint = torch.load(resume_from_checkpoint, map_location=device) + latent_diffusion.load_state_dict(checkpoint["state_dict"]) + + latent_diffusion.eval() + latent_diffusion = latent_diffusion.to(device) + + latent_diffusion.cond_stage_model.embed_mode = "text" + return latent_diffusion + +def duration_to_latent_t_size(duration): + return int(duration * 25.6) + +def set_cond_audio(latent_diffusion): + latent_diffusion.cond_stage_key = "waveform" + latent_diffusion.cond_stage_model.embed_mode="audio" + return latent_diffusion + +def set_cond_text(latent_diffusion): + latent_diffusion.cond_stage_key = "text" + latent_diffusion.cond_stage_model.embed_mode="text" + return latent_diffusion + +def text_to_audio( + latent_diffusion, + text, + original_audio_file_path = None, + seed=42, + ddim_steps=200, + duration=10, + batchsize=1, + guidance_scale=2.5, + n_candidate_gen_per_text=3, + config=None, +): + seed_everything(int(seed)) + waveform = None + if(original_audio_file_path is not None): + waveform = read_wav_file(original_audio_file_path, int(duration * 102.4) * 160) + + batch = make_batch_for_text_to_audio(text, waveform=waveform, batchsize=batchsize) + + latent_diffusion.latent_t_size = duration_to_latent_t_size(duration) + + if(waveform is not None): + print("Generate audio that has similar content as %s" % original_audio_file_path) + latent_diffusion = set_cond_audio(latent_diffusion) + else: + print("Generate audio using text %s" % text) + latent_diffusion = set_cond_text(latent_diffusion) + + with torch.no_grad(): + waveform = latent_diffusion.generate_sample( + [batch], + unconditional_guidance_scale=guidance_scale, + ddim_steps=ddim_steps, + n_candidate_gen_per_text=n_candidate_gen_per_text, + duration=duration, + ) + return waveform + +def style_transfer( + latent_diffusion, + text, + original_audio_file_path, + transfer_strength, + seed=42, + duration=10, + batchsize=1, + guidance_scale=2.5, + ddim_steps=200, + config=None, +): + if torch.cuda.is_available(): + device = torch.device("cuda:0") + else: + device = torch.device("cpu") + + assert original_audio_file_path is not None, "You need to provide the original audio file path" + + audio_file_duration = get_duration(original_audio_file_path) + + assert get_bit_depth(original_audio_file_path) == 16, "The bit depth of the original audio file %s must be 16" % original_audio_file_path + + # if(duration > 20): + # print("Warning: The duration of the audio file %s must be less than 20 seconds. Longer duration will result in Nan in model output (we are still debugging that); Automatically set duration to 20 seconds") + # duration = 20 + + if(duration >= audio_file_duration): + print("Warning: Duration you specified %s-seconds must equal or smaller than the audio file duration %ss" % (duration, audio_file_duration)) + duration = round_up_duration(audio_file_duration) + print("Set new duration as %s-seconds" % duration) + + # duration = round_up_duration(duration) + + latent_diffusion = set_cond_text(latent_diffusion) + + if config is not None: + assert type(config) is str + config = yaml.load(open(config, "r"), Loader=yaml.FullLoader) + else: + config = default_audioldm_config() + + seed_everything(int(seed)) + # latent_diffusion.latent_t_size = duration_to_latent_t_size(duration) + latent_diffusion.cond_stage_model.embed_mode = "text" + + fn_STFT = TacotronSTFT( + config["preprocessing"]["stft"]["filter_length"], + config["preprocessing"]["stft"]["hop_length"], + config["preprocessing"]["stft"]["win_length"], + config["preprocessing"]["mel"]["n_mel_channels"], + config["preprocessing"]["audio"]["sampling_rate"], + config["preprocessing"]["mel"]["mel_fmin"], + config["preprocessing"]["mel"]["mel_fmax"], + ) + + mel, _, _ = wav_to_fbank( + original_audio_file_path, target_length=int(duration * 102.4), fn_STFT=fn_STFT + ) + mel = mel.unsqueeze(0).unsqueeze(0).to(device) + mel = repeat(mel, "1 ... -> b ...", b=batchsize) + init_latent = latent_diffusion.get_first_stage_encoding( + latent_diffusion.encode_first_stage(mel) + ) # move to latent space, encode and sample + if(torch.max(torch.abs(init_latent)) > 1e2): + init_latent = torch.clip(init_latent, min=-10, max=10) + sampler = DDIMSampler(latent_diffusion) + sampler.make_schedule(ddim_num_steps=ddim_steps, ddim_eta=1.0, verbose=False) + + t_enc = int(transfer_strength * ddim_steps) + prompts = text + + with torch.no_grad(): + with autocast("cuda"): + with latent_diffusion.ema_scope(): + uc = None + if guidance_scale != 1.0: + uc = latent_diffusion.cond_stage_model.get_unconditional_condition( + batchsize + ) + + c = latent_diffusion.get_learned_conditioning([prompts] * batchsize) + z_enc = sampler.stochastic_encode( + init_latent, torch.tensor([t_enc] * batchsize).to(device) + ) + samples = sampler.decode( + z_enc, + c, + t_enc, + unconditional_guidance_scale=guidance_scale, + unconditional_conditioning=uc, + ) + # x_samples = latent_diffusion.decode_first_stage(samples) # Will result in Nan in output + # print(torch.sum(torch.isnan(samples))) + x_samples = latent_diffusion.decode_first_stage(samples) + # print(x_samples) + x_samples = latent_diffusion.decode_first_stage(samples[:,:,:-3,:]) + # print(x_samples) + waveform = latent_diffusion.first_stage_model.decode_to_waveform( + x_samples + ) + + return waveform + +def super_resolution_and_inpainting( + latent_diffusion, + text, + original_audio_file_path = None, + seed=42, + ddim_steps=200, + duration=None, + batchsize=1, + guidance_scale=2.5, + n_candidate_gen_per_text=3, + time_mask_ratio_start_and_end=(0.10, 0.15), # regenerate the 10% to 15% of the time steps in the spectrogram + # time_mask_ratio_start_and_end=(1.0, 1.0), # no inpainting + # freq_mask_ratio_start_and_end=(0.75, 1.0), # regenerate the higher 75% to 100% mel bins + freq_mask_ratio_start_and_end=(1.0, 1.0), # no super-resolution + config=None, +): + seed_everything(int(seed)) + if config is not None: + assert type(config) is str + config = yaml.load(open(config, "r"), Loader=yaml.FullLoader) + else: + config = default_audioldm_config() + fn_STFT = TacotronSTFT( + config["preprocessing"]["stft"]["filter_length"], + config["preprocessing"]["stft"]["hop_length"], + config["preprocessing"]["stft"]["win_length"], + config["preprocessing"]["mel"]["n_mel_channels"], + config["preprocessing"]["audio"]["sampling_rate"], + config["preprocessing"]["mel"]["mel_fmin"], + config["preprocessing"]["mel"]["mel_fmax"], + ) + + # waveform = read_wav_file(original_audio_file_path, None) + mel, _, _ = wav_to_fbank( + original_audio_file_path, target_length=int(duration * 102.4), fn_STFT=fn_STFT + ) + + batch = make_batch_for_text_to_audio(text, fbank=mel[None,...], batchsize=batchsize) + + # latent_diffusion.latent_t_size = duration_to_latent_t_size(duration) + latent_diffusion = set_cond_text(latent_diffusion) + + with torch.no_grad(): + waveform = latent_diffusion.generate_sample_masked( + [batch], + unconditional_guidance_scale=guidance_scale, + ddim_steps=ddim_steps, + n_candidate_gen_per_text=n_candidate_gen_per_text, + duration=duration, + time_mask_ratio_start_and_end=time_mask_ratio_start_and_end, + freq_mask_ratio_start_and_end=freq_mask_ratio_start_and_end + ) + return waveform \ No newline at end of file diff --git a/src/audioldm/utils.py b/src/audioldm/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..ff9d28dd8cebfdb605d9e54d07a5e53ddf1afece --- /dev/null +++ b/src/audioldm/utils.py @@ -0,0 +1,282 @@ +import contextlib +import importlib + +from inspect import isfunction +import os +import soundfile as sf +import time +import wave + +import urllib.request +import progressbar + +#CACHE_DIR = os.getenv( +# "AUDIOLDM_CACHE_DIR", +# os.path.join(os.path.expanduser("~"), ".cache/audioldm")) +CACHE_DIR = "/ckptstorage/zhanghaomin/models/audioldm/AudioLDM-S-Full/" + +def get_duration(fname): + with contextlib.closing(wave.open(fname, 'r')) as f: + frames = f.getnframes() + rate = f.getframerate() + return frames / float(rate) + +def get_bit_depth(fname): + with contextlib.closing(wave.open(fname, 'r')) as f: + bit_depth = f.getsampwidth() * 8 + return bit_depth + +def get_time(): + t = time.localtime() + return time.strftime("%d_%m_%Y_%H_%M_%S", t) + +def seed_everything(seed): + import random, os + import numpy as np + import torch + + random.seed(seed) + os.environ["PYTHONHASHSEED"] = str(seed) + np.random.seed(seed) + torch.manual_seed(seed) + torch.cuda.manual_seed(seed) + torch.backends.cudnn.deterministic = True + torch.backends.cudnn.benchmark = True + + +def save_wave(waveform, savepath, name="outwav"): + if type(name) is not list: + name = [name] * waveform.shape[0] + + for i in range(waveform.shape[0]): + path = os.path.join( + savepath, + "%s_%s.wav" + % ( + os.path.basename(name[i]) + if (not ".wav" in name[i]) + else os.path.basename(name[i]).split(".")[0], + i, + ), + ) + print("Save audio to %s" % path) + sf.write(path, waveform[i, 0], samplerate=16000) + + +def exists(x): + return x is not None + + +def default(val, d): + if exists(val): + return val + return d() if isfunction(d) else d + + +def count_params(model, verbose=False): + total_params = sum(p.numel() for p in model.parameters()) + if verbose: + print(f"{model.__class__.__name__} has {total_params * 1.e-6:.2f} M params.") + return total_params + + +def get_obj_from_str(string, reload=False): + module, cls = string.rsplit(".", 1) + if reload: + module_imp = importlib.import_module(module) + importlib.reload(module_imp) + return getattr(importlib.import_module(module, package=None), cls) + + +def instantiate_from_config(config): + if not "target" in config: + if config == "__is_first_stage__": + return None + elif config == "__is_unconditional__": + return None + raise KeyError("Expected key `target` to instantiate.") + return get_obj_from_str(config["target"])(**config.get("params", dict())) + + +def default_audioldm_config(model_name="audioldm-s-full"): + basic_config = { + "wave_file_save_path": "./output", + "id": { + "version": "v1", + "name": "default", + "root": "/mnt/fast/nobackup/users/hl01486/projects/general_audio_generation/AudioLDM-python/config/default/latent_diffusion.yaml", + }, + "preprocessing": { + "audio": {"sampling_rate": 16000, "max_wav_value": 32768}, + "stft": {"filter_length": 1024, "hop_length": 160, "win_length": 1024}, + "mel": { + "n_mel_channels": 64, + "mel_fmin": 0, + "mel_fmax": 8000, + "freqm": 0, + "timem": 0, + "blur": False, + "mean": -4.63, + "std": 2.74, + "target_length": 1024, + }, + }, + "model": { + "device": "cuda", + "target": "audioldm.pipline.LatentDiffusion", + "params": { + "base_learning_rate": 5e-06, + "linear_start": 0.0015, + "linear_end": 0.0195, + "num_timesteps_cond": 1, + "log_every_t": 200, + "timesteps": 1000, + "first_stage_key": "fbank", + "cond_stage_key": "waveform", + "latent_t_size": 256, + "latent_f_size": 16, + "channels": 8, + "cond_stage_trainable": True, + "conditioning_key": "film", + "monitor": "val/loss_simple_ema", + "scale_by_std": True, + "unet_config": { + "target": "audioldm.latent_diffusion.openaimodel.UNetModel", + "params": { + "image_size": 64, + "extra_film_condition_dim": 512, + "extra_film_use_concat": True, + "in_channels": 8, + "out_channels": 8, + "model_channels": 128, + "attention_resolutions": [8, 4, 2], + "num_res_blocks": 2, + "channel_mult": [1, 2, 3, 5], + "num_head_channels": 32, + "use_spatial_transformer": True, + }, + }, + "first_stage_config": { + "base_learning_rate": 4.5e-05, + "target": "audioldm.variational_autoencoder.autoencoder.AutoencoderKL", + "params": { + "monitor": "val/rec_loss", + "image_key": "fbank", + "subband": 1, + "embed_dim": 8, + "time_shuffle": 1, + "ddconfig": { + "double_z": True, + "z_channels": 8, + "resolution": 256, + "downsample_time": False, + "in_channels": 1, + "out_ch": 1, + "ch": 128, + "ch_mult": [1, 2, 4], + "num_res_blocks": 2, + "attn_resolutions": [], + "dropout": 0.0, + }, + }, + }, + "cond_stage_config": { + "target": "audioldm.clap.encoders.CLAPAudioEmbeddingClassifierFreev2", + "params": { + "key": "waveform", + "sampling_rate": 16000, + "embed_mode": "audio", + "unconditional_prob": 0.1, + }, + }, + }, + }, + } + + if("-l-" in model_name): + basic_config["model"]["params"]["unet_config"]["params"]["model_channels"] = 256 + basic_config["model"]["params"]["unet_config"]["params"]["num_head_channels"] = 64 + elif("-m-" in model_name): + basic_config["model"]["params"]["unet_config"]["params"]["model_channels"] = 192 + basic_config["model"]["params"]["cond_stage_config"]["params"]["amodel"] = "HTSAT-base" # This model use a larger HTAST + + return basic_config + +def get_metadata(): + return { + "audioldm-s-full": { + "path": os.path.join( + CACHE_DIR, + "audioldm-s-full.ckpt", + ), + "url": "https://zenodo.org/record/7600541/files/audioldm-s-full?download=1", + }, + "audioldm-l-full": { + "path": os.path.join( + CACHE_DIR, + "audioldm-l-full.ckpt", + ), + "url": "https://zenodo.org/record/7698295/files/audioldm-full-l.ckpt?download=1", + }, + "audioldm-s-full-v2": { + "path": os.path.join( + CACHE_DIR, + "audioldm-s-full-v2.ckpt", + ), + "url": "https://zenodo.org/record/7698295/files/audioldm-full-s-v2.ckpt?download=1", + }, + "audioldm-m-text-ft": { + "path": os.path.join( + CACHE_DIR, + "audioldm-m-text-ft.ckpt", + ), + "url": "https://zenodo.org/record/7813012/files/audioldm-m-text-ft.ckpt?download=1", + }, + "audioldm-s-text-ft": { + "path": os.path.join( + CACHE_DIR, + "audioldm-s-text-ft.ckpt", + ), + "url": "https://zenodo.org/record/7813012/files/audioldm-s-text-ft.ckpt?download=1", + }, + "audioldm-m-full": { + "path": os.path.join( + CACHE_DIR, + "audioldm-m-full.ckpt", + ), + "url": "https://zenodo.org/record/7813012/files/audioldm-m-full.ckpt?download=1", + }, + } + +class MyProgressBar(): + def __init__(self): + self.pbar = None + + def __call__(self, block_num, block_size, total_size): + if not self.pbar: + self.pbar=progressbar.ProgressBar(maxval=total_size) + self.pbar.start() + + downloaded = block_num * block_size + if downloaded < total_size: + self.pbar.update(downloaded) + else: + self.pbar.finish() + +def download_checkpoint(checkpoint_name="audioldm-s-full"): + meta = get_metadata() + if(checkpoint_name not in meta.keys()): + print("The model name you provided is not supported. Please use one of the following: ", meta.keys()) + + if not os.path.exists(meta[checkpoint_name]["path"]) or os.path.getsize(meta[checkpoint_name]["path"]) < 2*10**9: + os.makedirs(os.path.dirname(meta[checkpoint_name]["path"]), exist_ok=True) + print(f"Downloading the main structure of {checkpoint_name} into {os.path.dirname(meta[checkpoint_name]['path'])}") + + urllib.request.urlretrieve(meta[checkpoint_name]["url"], meta[checkpoint_name]["path"], MyProgressBar()) + print( + "Weights downloaded in: {} Size: {}".format( + meta[checkpoint_name]["path"], + os.path.getsize(meta[checkpoint_name]["path"]), + ) + ) + \ No newline at end of file diff --git a/src/audioldm/variational_autoencoder/__init__.py b/src/audioldm/variational_autoencoder/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..08b2a9b9698e02918d7b0dd9fe0431b2847e5aa2 --- /dev/null +++ b/src/audioldm/variational_autoencoder/__init__.py @@ -0,0 +1 @@ +from .autoencoder import AutoencoderKL \ No newline at end of file diff --git a/src/audioldm/variational_autoencoder/autoencoder.py b/src/audioldm/variational_autoencoder/autoencoder.py new file mode 100644 index 0000000000000000000000000000000000000000..c21b6a19f007c5f6fb74aa44ef90f554734c0491 --- /dev/null +++ b/src/audioldm/variational_autoencoder/autoencoder.py @@ -0,0 +1,135 @@ +import torch +from audioldm.latent_diffusion.ema import * +from audioldm.variational_autoencoder.modules import Encoder, Decoder +from audioldm.variational_autoencoder.distributions import DiagonalGaussianDistribution + +from audioldm.hifigan.utilities import get_vocoder, vocoder_infer + + +class AutoencoderKL(nn.Module): + def __init__( + self, + ddconfig=None, + lossconfig=None, + image_key="fbank", + embed_dim=None, + time_shuffle=1, + subband=1, + ckpt_path=None, + reload_from_ckpt=None, + ignore_keys=[], + colorize_nlabels=None, + monitor=None, + base_learning_rate=1e-5, + scale_factor=1 + ): + super().__init__() + + self.encoder = Encoder(**ddconfig) + self.decoder = Decoder(**ddconfig) + + self.subband = int(subband) + + if self.subband > 1: + print("Use subband decomposition %s" % self.subband) + + self.quant_conv = torch.nn.Conv2d(2 * ddconfig["z_channels"], 2 * embed_dim, 1) + self.post_quant_conv = torch.nn.Conv2d(embed_dim, ddconfig["z_channels"], 1) + + self.vocoder = get_vocoder(None, "cpu") + self.embed_dim = embed_dim + + if monitor is not None: + self.monitor = monitor + + self.time_shuffle = time_shuffle + self.reload_from_ckpt = reload_from_ckpt + self.reloaded = False + self.mean, self.std = None, None + + self.scale_factor = scale_factor + + def encode(self, x): + # x = self.time_shuffle_operation(x) + x = self.freq_split_subband(x) + h = self.encoder(x) + moments = self.quant_conv(h) + posterior = DiagonalGaussianDistribution(moments) + return posterior + + def decode(self, z): + z = self.post_quant_conv(z) + dec = self.decoder(z) + dec = self.freq_merge_subband(dec) + return dec + + def decode_to_waveform(self, dec): + dec = dec.squeeze(1).permute(0, 2, 1) + wav_reconstruction = vocoder_infer(dec, self.vocoder) + return wav_reconstruction + + def forward(self, input, sample_posterior=True): + posterior = self.encode(input) + if sample_posterior: + z = posterior.sample() + else: + z = posterior.mode() + + if self.flag_first_run: + print("Latent size: ", z.size()) + self.flag_first_run = False + + dec = self.decode(z) + + return dec, posterior + + def freq_split_subband(self, fbank): + if self.subband == 1 or self.image_key != "stft": + return fbank + + bs, ch, tstep, fbins = fbank.size() + + assert fbank.size(-1) % self.subband == 0 + assert ch == 1 + + return ( + fbank.squeeze(1) + .reshape(bs, tstep, self.subband, fbins // self.subband) + .permute(0, 2, 1, 3) + ) + + def freq_merge_subband(self, subband_fbank): + if self.subband == 1 or self.image_key != "stft": + return subband_fbank + assert subband_fbank.size(1) == self.subband # Channel dimension + bs, sub_ch, tstep, fbins = subband_fbank.size() + return subband_fbank.permute(0, 2, 1, 3).reshape(bs, tstep, -1).unsqueeze(1) + + def device(self): + return next(self.parameters()).device + + @torch.no_grad() + def encode_first_stage(self, x): + return self.encode(x) + + @torch.no_grad() + def decode_first_stage(self, z, predict_cids=False, force_not_quantize=False): + if predict_cids: + if z.dim() == 4: + z = torch.argmax(z.exp(), dim=1).long() + z = self.first_stage_model.quantize.get_codebook_entry(z, shape=None) + z = rearrange(z, "b h w c -> b c h w").contiguous() + + z = 1.0 / self.scale_factor * z + return self.decode(z) + + def get_first_stage_encoding(self, encoder_posterior): + if isinstance(encoder_posterior, DiagonalGaussianDistribution): + z = encoder_posterior.sample() + elif isinstance(encoder_posterior, torch.Tensor): + z = encoder_posterior + else: + raise NotImplementedError( + f"encoder_posterior of type '{type(encoder_posterior)}' not yet implemented" + ) + return self.scale_factor * z \ No newline at end of file diff --git a/src/audioldm/variational_autoencoder/distributions.py b/src/audioldm/variational_autoencoder/distributions.py new file mode 100644 index 0000000000000000000000000000000000000000..08d0050462e11b81447630d43f861c77384fec84 --- /dev/null +++ b/src/audioldm/variational_autoencoder/distributions.py @@ -0,0 +1,102 @@ +import torch +import numpy as np + + +class AbstractDistribution: + def sample(self): + raise NotImplementedError() + + def mode(self): + raise NotImplementedError() + + +class DiracDistribution(AbstractDistribution): + def __init__(self, value): + self.value = value + + def sample(self): + return self.value + + def mode(self): + return self.value + + +class DiagonalGaussianDistribution(object): + def __init__(self, parameters, deterministic=False): + self.parameters = parameters + self.mean, self.logvar = torch.chunk(parameters, 2, dim=1) + self.logvar = torch.clamp(self.logvar, -30.0, 20.0) + self.deterministic = deterministic + self.std = torch.exp(0.5 * self.logvar) + self.var = torch.exp(self.logvar) + if self.deterministic: + self.var = self.std = torch.zeros_like(self.mean).to( + device=self.parameters.device + ) + + def sample(self): + x = self.mean + self.std * torch.randn(self.mean.shape).to( + device=self.parameters.device + ) + return x + + def kl(self, other=None): + if self.deterministic: + return torch.Tensor([0.0]) + else: + if other is None: + return 0.5 * torch.mean( + torch.pow(self.mean, 2) + self.var - 1.0 - self.logvar, + dim=[1, 2, 3], + ) + else: + return 0.5 * torch.mean( + torch.pow(self.mean - other.mean, 2) / other.var + + self.var / other.var + - 1.0 + - self.logvar + + other.logvar, + dim=[1, 2, 3], + ) + + def nll(self, sample, dims=[1, 2, 3]): + if self.deterministic: + return torch.Tensor([0.0]) + logtwopi = np.log(2.0 * np.pi) + return 0.5 * torch.sum( + logtwopi + self.logvar + torch.pow(sample - self.mean, 2) / self.var, + dim=dims, + ) + + def mode(self): + return self.mean + + +def normal_kl(mean1, logvar1, mean2, logvar2): + """ + source: https://github.com/openai/guided-diffusion/blob/27c20a8fab9cb472df5d6bdd6c8d11c8f430b924/guided_diffusion/losses.py#L12 + Compute the KL divergence between two gaussians. + Shapes are automatically broadcasted, so batches can be compared to + scalars, among other use cases. + """ + tensor = None + for obj in (mean1, logvar1, mean2, logvar2): + if isinstance(obj, torch.Tensor): + tensor = obj + break + assert tensor is not None, "at least one argument must be a Tensor" + + # Force variances to be Tensors. Broadcasting helps convert scalars to + # Tensors, but it does not work for torch.exp(). + logvar1, logvar2 = [ + x if isinstance(x, torch.Tensor) else torch.tensor(x).to(tensor) + for x in (logvar1, logvar2) + ] + + return 0.5 * ( + -1.0 + + logvar2 + - logvar1 + + torch.exp(logvar1 - logvar2) + + ((mean1 - mean2) ** 2) * torch.exp(-logvar2) + ) diff --git a/src/audioldm/variational_autoencoder/modules.py b/src/audioldm/variational_autoencoder/modules.py new file mode 100644 index 0000000000000000000000000000000000000000..a811a8b0948aebc914a6db5a8c02afbde89b32a5 --- /dev/null +++ b/src/audioldm/variational_autoencoder/modules.py @@ -0,0 +1,1066 @@ +# pytorch_diffusion + derived encoder decoder +import math +import torch +import torch.nn as nn +import numpy as np +from einops import rearrange + +from audioldm.utils import instantiate_from_config +from audioldm.latent_diffusion.attention import LinearAttention + + +def get_timestep_embedding(timesteps, embedding_dim): + """ + This matches the implementation in Denoising Diffusion Probabilistic Models: + From Fairseq. + Build sinusoidal embeddings. + This matches the implementation in tensor2tensor, but differs slightly + from the description in Section 3.5 of "Attention Is All You Need". + """ + assert len(timesteps.shape) == 1 + + half_dim = embedding_dim // 2 + emb = math.log(10000) / (half_dim - 1) + emb = torch.exp(torch.arange(half_dim, dtype=torch.float32) * -emb) + emb = emb.to(device=timesteps.device) + emb = timesteps.float()[:, None] * emb[None, :] + emb = torch.cat([torch.sin(emb), torch.cos(emb)], dim=1) + if embedding_dim % 2 == 1: # zero pad + emb = torch.nn.functional.pad(emb, (0, 1, 0, 0)) + return emb + + +def nonlinearity(x): + # swish + return x * torch.sigmoid(x) + + +def Normalize(in_channels, num_groups=32): + return torch.nn.GroupNorm( + num_groups=num_groups, num_channels=in_channels, eps=1e-6, affine=True + ) + + +class Upsample(nn.Module): + def __init__(self, in_channels, with_conv): + super().__init__() + self.with_conv = with_conv + if self.with_conv: + self.conv = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=3, stride=1, padding=1 + ) + + def forward(self, x): + x = torch.nn.functional.interpolate(x, scale_factor=2.0, mode="nearest") + if self.with_conv: + x = self.conv(x) + return x + + +class UpsampleTimeStride4(nn.Module): + def __init__(self, in_channels, with_conv): + super().__init__() + self.with_conv = with_conv + if self.with_conv: + self.conv = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=5, stride=1, padding=2 + ) + + def forward(self, x): + x = torch.nn.functional.interpolate(x, scale_factor=(4.0, 2.0), mode="nearest") + if self.with_conv: + x = self.conv(x) + return x + + +class Downsample(nn.Module): + def __init__(self, in_channels, with_conv): + super().__init__() + self.with_conv = with_conv + if self.with_conv: + # Do time downsampling here + # no asymmetric padding in torch conv, must do it ourselves + self.conv = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=3, stride=2, padding=0 + ) + + def forward(self, x): + if self.with_conv: + pad = (0, 1, 0, 1) + x = torch.nn.functional.pad(x, pad, mode="constant", value=0) + x = self.conv(x) + else: + x = torch.nn.functional.avg_pool2d(x, kernel_size=2, stride=2) + return x + + +class DownsampleTimeStride4(nn.Module): + def __init__(self, in_channels, with_conv): + super().__init__() + self.with_conv = with_conv + if self.with_conv: + # Do time downsampling here + # no asymmetric padding in torch conv, must do it ourselves + self.conv = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=5, stride=(4, 2), padding=1 + ) + + def forward(self, x): + if self.with_conv: + pad = (0, 1, 0, 1) + x = torch.nn.functional.pad(x, pad, mode="constant", value=0) + x = self.conv(x) + else: + x = torch.nn.functional.avg_pool2d(x, kernel_size=(4, 2), stride=(4, 2)) + return x + + +class ResnetBlock(nn.Module): + def __init__( + self, + *, + in_channels, + out_channels=None, + conv_shortcut=False, + dropout, + temb_channels=512, + ): + super().__init__() + self.in_channels = in_channels + out_channels = in_channels if out_channels is None else out_channels + self.out_channels = out_channels + self.use_conv_shortcut = conv_shortcut + + self.norm1 = Normalize(in_channels) + self.conv1 = torch.nn.Conv2d( + in_channels, out_channels, kernel_size=3, stride=1, padding=1 + ) + if temb_channels > 0: + self.temb_proj = torch.nn.Linear(temb_channels, out_channels) + self.norm2 = Normalize(out_channels) + self.dropout = torch.nn.Dropout(dropout) + self.conv2 = torch.nn.Conv2d( + out_channels, out_channels, kernel_size=3, stride=1, padding=1 + ) + if self.in_channels != self.out_channels: + if self.use_conv_shortcut: + self.conv_shortcut = torch.nn.Conv2d( + in_channels, out_channels, kernel_size=3, stride=1, padding=1 + ) + else: + self.nin_shortcut = torch.nn.Conv2d( + in_channels, out_channels, kernel_size=1, stride=1, padding=0 + ) + + def forward(self, x, temb): + h = x + h = self.norm1(h) + h = nonlinearity(h) + h = self.conv1(h) + + if temb is not None: + h = h + self.temb_proj(nonlinearity(temb))[:, :, None, None] + + h = self.norm2(h) + h = nonlinearity(h) + h = self.dropout(h) + h = self.conv2(h) + + if self.in_channels != self.out_channels: + if self.use_conv_shortcut: + x = self.conv_shortcut(x) + else: + x = self.nin_shortcut(x) + + return x + h + + +class LinAttnBlock(LinearAttention): + """to match AttnBlock usage""" + + def __init__(self, in_channels): + super().__init__(dim=in_channels, heads=1, dim_head=in_channels) + + +class AttnBlock(nn.Module): + def __init__(self, in_channels): + super().__init__() + self.in_channels = in_channels + + self.norm = Normalize(in_channels) + self.q = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=1, stride=1, padding=0 + ) + self.k = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=1, stride=1, padding=0 + ) + self.v = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=1, stride=1, padding=0 + ) + self.proj_out = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=1, stride=1, padding=0 + ) + + def forward(self, x): + h_ = x + h_ = self.norm(h_) + q = self.q(h_) + k = self.k(h_) + v = self.v(h_) + + # compute attention + b, c, h, w = q.shape + q = q.reshape(b, c, h * w).contiguous() + q = q.permute(0, 2, 1).contiguous() # b,hw,c + k = k.reshape(b, c, h * w).contiguous() # b,c,hw + w_ = torch.bmm(q, k).contiguous() # b,hw,hw w[b,i,j]=sum_c q[b,i,c]k[b,c,j] + w_ = w_ * (int(c) ** (-0.5)) + w_ = torch.nn.functional.softmax(w_, dim=2) + + # attend to values + v = v.reshape(b, c, h * w).contiguous() + w_ = w_.permute(0, 2, 1).contiguous() # b,hw,hw (first hw of k, second of q) + h_ = torch.bmm( + v, w_ + ).contiguous() # b, c,hw (hw of q) h_[b,c,j] = sum_i v[b,c,i] w_[b,i,j] + h_ = h_.reshape(b, c, h, w).contiguous() + + h_ = self.proj_out(h_) + + return x + h_ + + +def make_attn(in_channels, attn_type="vanilla"): + assert attn_type in ["vanilla", "linear", "none"], f"attn_type {attn_type} unknown" + # print(f"making attention of type '{attn_type}' with {in_channels} in_channels") + if attn_type == "vanilla": + return AttnBlock(in_channels) + elif attn_type == "none": + return nn.Identity(in_channels) + else: + return LinAttnBlock(in_channels) + + +class Model(nn.Module): + def __init__( + self, + *, + ch, + out_ch, + ch_mult=(1, 2, 4, 8), + num_res_blocks, + attn_resolutions, + dropout=0.0, + resamp_with_conv=True, + in_channels, + resolution, + use_timestep=True, + use_linear_attn=False, + attn_type="vanilla", + ): + super().__init__() + if use_linear_attn: + attn_type = "linear" + self.ch = ch + self.temb_ch = self.ch * 4 + self.num_resolutions = len(ch_mult) + self.num_res_blocks = num_res_blocks + self.resolution = resolution + self.in_channels = in_channels + + self.use_timestep = use_timestep + if self.use_timestep: + # timestep embedding + self.temb = nn.Module() + self.temb.dense = nn.ModuleList( + [ + torch.nn.Linear(self.ch, self.temb_ch), + torch.nn.Linear(self.temb_ch, self.temb_ch), + ] + ) + + # downsampling + self.conv_in = torch.nn.Conv2d( + in_channels, self.ch, kernel_size=3, stride=1, padding=1 + ) + + curr_res = resolution + in_ch_mult = (1,) + tuple(ch_mult) + self.down = nn.ModuleList() + for i_level in range(self.num_resolutions): + block = nn.ModuleList() + attn = nn.ModuleList() + block_in = ch * in_ch_mult[i_level] + block_out = ch * ch_mult[i_level] + for i_block in range(self.num_res_blocks): + block.append( + ResnetBlock( + in_channels=block_in, + out_channels=block_out, + temb_channels=self.temb_ch, + dropout=dropout, + ) + ) + block_in = block_out + if curr_res in attn_resolutions: + attn.append(make_attn(block_in, attn_type=attn_type)) + down = nn.Module() + down.block = block + down.attn = attn + if i_level != self.num_resolutions - 1: + down.downsample = Downsample(block_in, resamp_with_conv) + curr_res = curr_res // 2 + self.down.append(down) + + # middle + self.mid = nn.Module() + self.mid.block_1 = ResnetBlock( + in_channels=block_in, + out_channels=block_in, + temb_channels=self.temb_ch, + dropout=dropout, + ) + self.mid.attn_1 = make_attn(block_in, attn_type=attn_type) + self.mid.block_2 = ResnetBlock( + in_channels=block_in, + out_channels=block_in, + temb_channels=self.temb_ch, + dropout=dropout, + ) + + # upsampling + self.up = nn.ModuleList() + for i_level in reversed(range(self.num_resolutions)): + block = nn.ModuleList() + attn = nn.ModuleList() + block_out = ch * ch_mult[i_level] + skip_in = ch * ch_mult[i_level] + for i_block in range(self.num_res_blocks + 1): + if i_block == self.num_res_blocks: + skip_in = ch * in_ch_mult[i_level] + block.append( + ResnetBlock( + in_channels=block_in + skip_in, + out_channels=block_out, + temb_channels=self.temb_ch, + dropout=dropout, + ) + ) + block_in = block_out + if curr_res in attn_resolutions: + attn.append(make_attn(block_in, attn_type=attn_type)) + up = nn.Module() + up.block = block + up.attn = attn + if i_level != 0: + up.upsample = Upsample(block_in, resamp_with_conv) + curr_res = curr_res * 2 + self.up.insert(0, up) # prepend to get consistent order + + # end + self.norm_out = Normalize(block_in) + self.conv_out = torch.nn.Conv2d( + block_in, out_ch, kernel_size=3, stride=1, padding=1 + ) + + def forward(self, x, t=None, context=None): + # assert x.shape[2] == x.shape[3] == self.resolution + if context is not None: + # assume aligned context, cat along channel axis + x = torch.cat((x, context), dim=1) + if self.use_timestep: + # timestep embedding + assert t is not None + temb = get_timestep_embedding(t, self.ch) + temb = self.temb.dense[0](temb) + temb = nonlinearity(temb) + temb = self.temb.dense[1](temb) + else: + temb = None + + # downsampling + hs = [self.conv_in(x)] + for i_level in range(self.num_resolutions): + for i_block in range(self.num_res_blocks): + h = self.down[i_level].block[i_block](hs[-1], temb) + if len(self.down[i_level].attn) > 0: + h = self.down[i_level].attn[i_block](h) + hs.append(h) + if i_level != self.num_resolutions - 1: + hs.append(self.down[i_level].downsample(hs[-1])) + + # middle + h = hs[-1] + h = self.mid.block_1(h, temb) + h = self.mid.attn_1(h) + h = self.mid.block_2(h, temb) + + # upsampling + for i_level in reversed(range(self.num_resolutions)): + for i_block in range(self.num_res_blocks + 1): + h = self.up[i_level].block[i_block]( + torch.cat([h, hs.pop()], dim=1), temb + ) + if len(self.up[i_level].attn) > 0: + h = self.up[i_level].attn[i_block](h) + if i_level != 0: + h = self.up[i_level].upsample(h) + + # end + h = self.norm_out(h) + h = nonlinearity(h) + h = self.conv_out(h) + return h + + def get_last_layer(self): + return self.conv_out.weight + + +class Encoder(nn.Module): + def __init__( + self, + *, + ch, + out_ch, + ch_mult=(1, 2, 4, 8), + num_res_blocks, + attn_resolutions, + dropout=0.0, + resamp_with_conv=True, + in_channels, + resolution, + z_channels, + double_z=True, + use_linear_attn=False, + attn_type="vanilla", + downsample_time_stride4_levels=[], + **ignore_kwargs, + ): + super().__init__() + if use_linear_attn: + attn_type = "linear" + self.ch = ch + self.temb_ch = 0 + self.num_resolutions = len(ch_mult) + self.num_res_blocks = num_res_blocks + self.resolution = resolution + self.in_channels = in_channels + self.downsample_time_stride4_levels = downsample_time_stride4_levels + + if len(self.downsample_time_stride4_levels) > 0: + assert max(self.downsample_time_stride4_levels) < self.num_resolutions, ( + "The level to perform downsample 4 operation need to be smaller than the total resolution number %s" + % str(self.num_resolutions) + ) + + # downsampling + self.conv_in = torch.nn.Conv2d( + in_channels, self.ch, kernel_size=3, stride=1, padding=1 + ) + + curr_res = resolution + in_ch_mult = (1,) + tuple(ch_mult) + self.in_ch_mult = in_ch_mult + self.down = nn.ModuleList() + for i_level in range(self.num_resolutions): + block = nn.ModuleList() + attn = nn.ModuleList() + block_in = ch * in_ch_mult[i_level] + block_out = ch * ch_mult[i_level] + for i_block in range(self.num_res_blocks): + block.append( + ResnetBlock( + in_channels=block_in, + out_channels=block_out, + temb_channels=self.temb_ch, + dropout=dropout, + ) + ) + block_in = block_out + if curr_res in attn_resolutions: + attn.append(make_attn(block_in, attn_type=attn_type)) + down = nn.Module() + down.block = block + down.attn = attn + if i_level != self.num_resolutions - 1: + if i_level in self.downsample_time_stride4_levels: + down.downsample = DownsampleTimeStride4(block_in, resamp_with_conv) + else: + down.downsample = Downsample(block_in, resamp_with_conv) + curr_res = curr_res // 2 + self.down.append(down) + + # middle + self.mid = nn.Module() + self.mid.block_1 = ResnetBlock( + in_channels=block_in, + out_channels=block_in, + temb_channels=self.temb_ch, + dropout=dropout, + ) + self.mid.attn_1 = make_attn(block_in, attn_type=attn_type) + self.mid.block_2 = ResnetBlock( + in_channels=block_in, + out_channels=block_in, + temb_channels=self.temb_ch, + dropout=dropout, + ) + + # end + self.norm_out = Normalize(block_in) + self.conv_out = torch.nn.Conv2d( + block_in, + 2 * z_channels if double_z else z_channels, + kernel_size=3, + stride=1, + padding=1, + ) + + def forward(self, x): + # timestep embedding + temb = None + # downsampling + hs = [self.conv_in(x)] + for i_level in range(self.num_resolutions): + for i_block in range(self.num_res_blocks): + h = self.down[i_level].block[i_block](hs[-1], temb) + if len(self.down[i_level].attn) > 0: + h = self.down[i_level].attn[i_block](h) + hs.append(h) + if i_level != self.num_resolutions - 1: + hs.append(self.down[i_level].downsample(hs[-1])) + + # middle + h = hs[-1] + h = self.mid.block_1(h, temb) + h = self.mid.attn_1(h) + h = self.mid.block_2(h, temb) + + # end + h = self.norm_out(h) + h = nonlinearity(h) + h = self.conv_out(h) + return h + + +class Decoder(nn.Module): + def __init__( + self, + *, + ch, + out_ch, + ch_mult=(1, 2, 4, 8), + num_res_blocks, + attn_resolutions, + dropout=0.0, + resamp_with_conv=True, + in_channels, + resolution, + z_channels, + give_pre_end=False, + tanh_out=False, + use_linear_attn=False, + downsample_time_stride4_levels=[], + attn_type="vanilla", + **ignorekwargs, + ): + super().__init__() + if use_linear_attn: + attn_type = "linear" + self.ch = ch + self.temb_ch = 0 + self.num_resolutions = len(ch_mult) + self.num_res_blocks = num_res_blocks + self.resolution = resolution + self.in_channels = in_channels + self.give_pre_end = give_pre_end + self.tanh_out = tanh_out + self.downsample_time_stride4_levels = downsample_time_stride4_levels + + if len(self.downsample_time_stride4_levels) > 0: + assert max(self.downsample_time_stride4_levels) < self.num_resolutions, ( + "The level to perform downsample 4 operation need to be smaller than the total resolution number %s" + % str(self.num_resolutions) + ) + + # compute in_ch_mult, block_in and curr_res at lowest res + in_ch_mult = (1,) + tuple(ch_mult) + block_in = ch * ch_mult[self.num_resolutions - 1] + curr_res = resolution // 2 ** (self.num_resolutions - 1) + self.z_shape = (1, z_channels, curr_res, curr_res) + # print("Working with z of shape {} = {} dimensions.".format( + # self.z_shape, np.prod(self.z_shape))) + + # z to block_in + self.conv_in = torch.nn.Conv2d( + z_channels, block_in, kernel_size=3, stride=1, padding=1 + ) + + # middle + self.mid = nn.Module() + self.mid.block_1 = ResnetBlock( + in_channels=block_in, + out_channels=block_in, + temb_channels=self.temb_ch, + dropout=dropout, + ) + self.mid.attn_1 = make_attn(block_in, attn_type=attn_type) + self.mid.block_2 = ResnetBlock( + in_channels=block_in, + out_channels=block_in, + temb_channels=self.temb_ch, + dropout=dropout, + ) + + # upsampling + self.up = nn.ModuleList() + for i_level in reversed(range(self.num_resolutions)): + block = nn.ModuleList() + attn = nn.ModuleList() + block_out = ch * ch_mult[i_level] + for i_block in range(self.num_res_blocks + 1): + block.append( + ResnetBlock( + in_channels=block_in, + out_channels=block_out, + temb_channels=self.temb_ch, + dropout=dropout, + ) + ) + block_in = block_out + if curr_res in attn_resolutions: + attn.append(make_attn(block_in, attn_type=attn_type)) + up = nn.Module() + up.block = block + up.attn = attn + if i_level != 0: + if i_level - 1 in self.downsample_time_stride4_levels: + up.upsample = UpsampleTimeStride4(block_in, resamp_with_conv) + else: + up.upsample = Upsample(block_in, resamp_with_conv) + curr_res = curr_res * 2 + self.up.insert(0, up) # prepend to get consistent order + + # end + self.norm_out = Normalize(block_in) + self.conv_out = torch.nn.Conv2d( + block_in, out_ch, kernel_size=3, stride=1, padding=1 + ) + + def forward(self, z): + # assert z.shape[1:] == self.z_shape[1:] + self.last_z_shape = z.shape + + # timestep embedding + temb = None + + # z to block_in + h = self.conv_in(z) + + # middle + h = self.mid.block_1(h, temb) + h = self.mid.attn_1(h) + h = self.mid.block_2(h, temb) + + # upsampling + for i_level in reversed(range(self.num_resolutions)): + for i_block in range(self.num_res_blocks + 1): + h = self.up[i_level].block[i_block](h, temb) + if len(self.up[i_level].attn) > 0: + h = self.up[i_level].attn[i_block](h) + if i_level != 0: + h = self.up[i_level].upsample(h) + + # end + if self.give_pre_end: + return h + + h = self.norm_out(h) + h = nonlinearity(h) + h = self.conv_out(h) + if self.tanh_out: + h = torch.tanh(h) + return h + + +class SimpleDecoder(nn.Module): + def __init__(self, in_channels, out_channels, *args, **kwargs): + super().__init__() + self.model = nn.ModuleList( + [ + nn.Conv2d(in_channels, in_channels, 1), + ResnetBlock( + in_channels=in_channels, + out_channels=2 * in_channels, + temb_channels=0, + dropout=0.0, + ), + ResnetBlock( + in_channels=2 * in_channels, + out_channels=4 * in_channels, + temb_channels=0, + dropout=0.0, + ), + ResnetBlock( + in_channels=4 * in_channels, + out_channels=2 * in_channels, + temb_channels=0, + dropout=0.0, + ), + nn.Conv2d(2 * in_channels, in_channels, 1), + Upsample(in_channels, with_conv=True), + ] + ) + # end + self.norm_out = Normalize(in_channels) + self.conv_out = torch.nn.Conv2d( + in_channels, out_channels, kernel_size=3, stride=1, padding=1 + ) + + def forward(self, x): + for i, layer in enumerate(self.model): + if i in [1, 2, 3]: + x = layer(x, None) + else: + x = layer(x) + + h = self.norm_out(x) + h = nonlinearity(h) + x = self.conv_out(h) + return x + + +class UpsampleDecoder(nn.Module): + def __init__( + self, + in_channels, + out_channels, + ch, + num_res_blocks, + resolution, + ch_mult=(2, 2), + dropout=0.0, + ): + super().__init__() + # upsampling + self.temb_ch = 0 + self.num_resolutions = len(ch_mult) + self.num_res_blocks = num_res_blocks + block_in = in_channels + curr_res = resolution // 2 ** (self.num_resolutions - 1) + self.res_blocks = nn.ModuleList() + self.upsample_blocks = nn.ModuleList() + for i_level in range(self.num_resolutions): + res_block = [] + block_out = ch * ch_mult[i_level] + for i_block in range(self.num_res_blocks + 1): + res_block.append( + ResnetBlock( + in_channels=block_in, + out_channels=block_out, + temb_channels=self.temb_ch, + dropout=dropout, + ) + ) + block_in = block_out + self.res_blocks.append(nn.ModuleList(res_block)) + if i_level != self.num_resolutions - 1: + self.upsample_blocks.append(Upsample(block_in, True)) + curr_res = curr_res * 2 + + # end + self.norm_out = Normalize(block_in) + self.conv_out = torch.nn.Conv2d( + block_in, out_channels, kernel_size=3, stride=1, padding=1 + ) + + def forward(self, x): + # upsampling + h = x + for k, i_level in enumerate(range(self.num_resolutions)): + for i_block in range(self.num_res_blocks + 1): + h = self.res_blocks[i_level][i_block](h, None) + if i_level != self.num_resolutions - 1: + h = self.upsample_blocks[k](h) + h = self.norm_out(h) + h = nonlinearity(h) + h = self.conv_out(h) + return h + + +class LatentRescaler(nn.Module): + def __init__(self, factor, in_channels, mid_channels, out_channels, depth=2): + super().__init__() + # residual block, interpolate, residual block + self.factor = factor + self.conv_in = nn.Conv2d( + in_channels, mid_channels, kernel_size=3, stride=1, padding=1 + ) + self.res_block1 = nn.ModuleList( + [ + ResnetBlock( + in_channels=mid_channels, + out_channels=mid_channels, + temb_channels=0, + dropout=0.0, + ) + for _ in range(depth) + ] + ) + self.attn = AttnBlock(mid_channels) + self.res_block2 = nn.ModuleList( + [ + ResnetBlock( + in_channels=mid_channels, + out_channels=mid_channels, + temb_channels=0, + dropout=0.0, + ) + for _ in range(depth) + ] + ) + + self.conv_out = nn.Conv2d( + mid_channels, + out_channels, + kernel_size=1, + ) + + def forward(self, x): + x = self.conv_in(x) + for block in self.res_block1: + x = block(x, None) + x = torch.nn.functional.interpolate( + x, + size=( + int(round(x.shape[2] * self.factor)), + int(round(x.shape[3] * self.factor)), + ), + ) + x = self.attn(x).contiguous() + for block in self.res_block2: + x = block(x, None) + x = self.conv_out(x) + return x + + +class MergedRescaleEncoder(nn.Module): + def __init__( + self, + in_channels, + ch, + resolution, + out_ch, + num_res_blocks, + attn_resolutions, + dropout=0.0, + resamp_with_conv=True, + ch_mult=(1, 2, 4, 8), + rescale_factor=1.0, + rescale_module_depth=1, + ): + super().__init__() + intermediate_chn = ch * ch_mult[-1] + self.encoder = Encoder( + in_channels=in_channels, + num_res_blocks=num_res_blocks, + ch=ch, + ch_mult=ch_mult, + z_channels=intermediate_chn, + double_z=False, + resolution=resolution, + attn_resolutions=attn_resolutions, + dropout=dropout, + resamp_with_conv=resamp_with_conv, + out_ch=None, + ) + self.rescaler = LatentRescaler( + factor=rescale_factor, + in_channels=intermediate_chn, + mid_channels=intermediate_chn, + out_channels=out_ch, + depth=rescale_module_depth, + ) + + def forward(self, x): + x = self.encoder(x) + x = self.rescaler(x) + return x + + +class MergedRescaleDecoder(nn.Module): + def __init__( + self, + z_channels, + out_ch, + resolution, + num_res_blocks, + attn_resolutions, + ch, + ch_mult=(1, 2, 4, 8), + dropout=0.0, + resamp_with_conv=True, + rescale_factor=1.0, + rescale_module_depth=1, + ): + super().__init__() + tmp_chn = z_channels * ch_mult[-1] + self.decoder = Decoder( + out_ch=out_ch, + z_channels=tmp_chn, + attn_resolutions=attn_resolutions, + dropout=dropout, + resamp_with_conv=resamp_with_conv, + in_channels=None, + num_res_blocks=num_res_blocks, + ch_mult=ch_mult, + resolution=resolution, + ch=ch, + ) + self.rescaler = LatentRescaler( + factor=rescale_factor, + in_channels=z_channels, + mid_channels=tmp_chn, + out_channels=tmp_chn, + depth=rescale_module_depth, + ) + + def forward(self, x): + x = self.rescaler(x) + x = self.decoder(x) + return x + + +class Upsampler(nn.Module): + def __init__(self, in_size, out_size, in_channels, out_channels, ch_mult=2): + super().__init__() + assert out_size >= in_size + num_blocks = int(np.log2(out_size // in_size)) + 1 + factor_up = 1.0 + (out_size % in_size) + print( + f"Building {self.__class__.__name__} with in_size: {in_size} --> out_size {out_size} and factor {factor_up}" + ) + self.rescaler = LatentRescaler( + factor=factor_up, + in_channels=in_channels, + mid_channels=2 * in_channels, + out_channels=in_channels, + ) + self.decoder = Decoder( + out_ch=out_channels, + resolution=out_size, + z_channels=in_channels, + num_res_blocks=2, + attn_resolutions=[], + in_channels=None, + ch=in_channels, + ch_mult=[ch_mult for _ in range(num_blocks)], + ) + + def forward(self, x): + x = self.rescaler(x) + x = self.decoder(x) + return x + + +class Resize(nn.Module): + def __init__(self, in_channels=None, learned=False, mode="bilinear"): + super().__init__() + self.with_conv = learned + self.mode = mode + if self.with_conv: + print( + f"Note: {self.__class__.__name} uses learned downsampling and will ignore the fixed {mode} mode" + ) + raise NotImplementedError() + assert in_channels is not None + # no asymmetric padding in torch conv, must do it ourselves + self.conv = torch.nn.Conv2d( + in_channels, in_channels, kernel_size=4, stride=2, padding=1 + ) + + def forward(self, x, scale_factor=1.0): + if scale_factor == 1.0: + return x + else: + x = torch.nn.functional.interpolate( + x, mode=self.mode, align_corners=False, scale_factor=scale_factor + ) + return x + + +class FirstStagePostProcessor(nn.Module): + def __init__( + self, + ch_mult: list, + in_channels, + pretrained_model: nn.Module = None, + reshape=False, + n_channels=None, + dropout=0.0, + pretrained_config=None, + ): + super().__init__() + if pretrained_config is None: + assert ( + pretrained_model is not None + ), 'Either "pretrained_model" or "pretrained_config" must not be None' + self.pretrained_model = pretrained_model + else: + assert ( + pretrained_config is not None + ), 'Either "pretrained_model" or "pretrained_config" must not be None' + self.instantiate_pretrained(pretrained_config) + + self.do_reshape = reshape + + if n_channels is None: + n_channels = self.pretrained_model.encoder.ch + + self.proj_norm = Normalize(in_channels, num_groups=in_channels // 2) + self.proj = nn.Conv2d( + in_channels, n_channels, kernel_size=3, stride=1, padding=1 + ) + + blocks = [] + downs = [] + ch_in = n_channels + for m in ch_mult: + blocks.append( + ResnetBlock( + in_channels=ch_in, out_channels=m * n_channels, dropout=dropout + ) + ) + ch_in = m * n_channels + downs.append(Downsample(ch_in, with_conv=False)) + + self.model = nn.ModuleList(blocks) + self.downsampler = nn.ModuleList(downs) + + def instantiate_pretrained(self, config): + model = instantiate_from_config(config) + self.pretrained_model = model.eval() + # self.pretrained_model.train = False + for param in self.pretrained_model.parameters(): + param.requires_grad = False + + @torch.no_grad() + def encode_with_pretrained(self, x): + c = self.pretrained_model.encode(x) + if isinstance(c, DiagonalGaussianDistribution): + c = c.mode() + return c + + def forward(self, x): + z_fs = self.encode_with_pretrained(x) + z = self.proj_norm(z_fs) + z = self.proj(z) + z = nonlinearity(z) + + for submodel, downmodel in zip(self.model, self.downsampler): + z = submodel(z, temb=None) + z = downmodel(z) + + if self.do_reshape: + z = rearrange(z, "b c h w -> b (h w) c") + return z diff --git a/src/config.yaml b/src/config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ff423c7eb7f51ac93ced046d779de18195c3dbf2 --- /dev/null +++ b/src/config.yaml @@ -0,0 +1,16 @@ +compute_environment: LOCAL_MACHINE +distributed_type: MULTI_GPU +downcast_bf16: 'no' +gpu_ids: '1,2' +machine_rank: 0 +main_training_function: main +mixed_precision: 'no' +num_machines: 1 +num_processes: 2 +rdzv_backend: static +same_network: true +tpu_env: [] +tpu_use_cluster: false +tpu_use_sudo: false +use_cpu: false +main_process_port: 29501 \ No newline at end of file diff --git a/src/e2_tts_pytorch/__init__.py b/src/e2_tts_pytorch/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/src/e2_tts_pytorch/critic_objectives.py b/src/e2_tts_pytorch/critic_objectives.py new file mode 100644 index 0000000000000000000000000000000000000000..56e8c6876f75825a46d35bfa67c7917a8cc2f739 --- /dev/null +++ b/src/e2_tts_pytorch/critic_objectives.py @@ -0,0 +1,254 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +import numpy as np + +#################### +# Critic Model # +#################### + +# Part of the code is adapted from here: https://github.com/yaohungt/Pointwise_Dependency_Neural_Estimation + +def probabilistic_classifier_obj(f): + criterion = nn.BCEWithLogitsLoss() + + batch_size = f.shape[0] + labels = [0.]*(batch_size*batch_size) + labels[::(batch_size+1)] = [1.]*batch_size + labels = torch.tensor(labels).type_as(f) + labels = labels.view(-1,1) + + logits = f.contiguous().view(-1,1) + + Loss = -1.*criterion(logits, labels) + + return Loss + +def probabilistic_classifier_eval(f): + batch_size = f.shape[0] + joint_feat = f.contiguous().view(-1)[::(batch_size+1)] + joint_logits = torch.clamp(torch.sigmoid(joint_feat), min=1e-6, max=1-1e-6) + + MI = torch.mean(torch.log((batch_size-1)*joint_logits/(1.-joint_logits))) + # we have batch_size*(batch_size-1) product of marginal samples + # we have batch_size joint density samples + + return MI + +def infonce_lower_bound_obj(scores): + nll = scores.diag().mean() - scores.logsumexp(dim=1) + # Alternative implementation: + # nll = -tf.nn.sparse_softmax_cross_entropy_with_logits(logits=scores, labels=tf.range(batch_size)) + mi = torch.tensor(scores.size(0)).float().log() + nll + mi = mi.mean() + return mi + +def mlp(dim, hidden_dim, output_dim, layers, activation): + activation = { + 'relu': nn.ReLU, + 'tanh': nn.Tanh, + }[activation] + + seq = [nn.Linear(dim, hidden_dim), activation()] + for _ in range(layers): + seq += [nn.Linear(hidden_dim, hidden_dim), activation()] + seq += [nn.Linear(hidden_dim, output_dim)] + + return nn.Sequential(*seq) + +class SeparableCritic(nn.Module): + def __init__(self, x1_dim, x2_dim, hidden_dim, embed_dim, + layers, activation): + super(SeparableCritic, self).__init__() + self._g = mlp(x1_dim, hidden_dim, embed_dim, layers, activation) + self._h = mlp(x2_dim, hidden_dim, embed_dim, layers, activation) + + def transformed_x(self, x): + return self._g(x) + + def transformed_y(self, y): + return self._h(y) + + def forward(self, x, y): + scores = torch.matmul(self._h(y), self._g(x).t()) + return scores + + def pointwise_mi(self, x, y, estimator): + scores = torch.matmul(self._h(y), self._g(x).t()) + + if estimator == 'probabilistic_classifier': + # the prob of being a pair + # PMI = torch.sigmoid(scores.diag()) + # PMI + batch_size = scores.shape[0] + # N_pxpy / N_pxy = (batch_size - 1.) * batch_size / batch_size + PMI = scores.diag() + np.log(batch_size - 1.) + else: + raise NotImplementedError("not supporting our PMI!") + return PMI + +class ConcatCritic(nn.Module): + + def __init__(self, A_dim, B_dim, hidden_dim, layers, activation, **extra_kwargs): + super(ConcatCritic, self).__init__() + # output is scalar score + self._f = mlp(A_dim + B_dim, hidden_dim, 1, layers, activation) + + def forward(self, x, y): + batch_size = x.shape[0] + # Tile all possible combinations of x and y + x_tiled = torch.stack([x] * batch_size, dim=0) + y_tiled = torch.stack([y] * batch_size, dim=1) + # xy is [batch_size * batch_size, x_dim + y_dim] + xy_pairs = torch.reshape(torch.cat((x_tiled, y_tiled), dim=2), [batch_size * batch_size, -1]) + # Compute scores for each x_i, y_j pair. + scores = self._f(xy_pairs) + return torch.reshape(scores, [batch_size, batch_size]).t() + +# Concat critic with the InfoNCE (NCE) objective +class InfoNCECritic(nn.Module): + def __init__(self, A_dim, B_dim, hidden_dim, layers, activation, **extra_kwargs): + super(InfoNCECritic, self).__init__() + # output is scalar score + self._f = mlp(A_dim + B_dim, hidden_dim, 1, layers, activation) + + def forward(self, x_samples, y_samples): + sample_size = y_samples.shape[0] + + #x_samples = F.normalize(x_samples, dim=-1) + #y_samples = F.normalize(y_samples, dim=-1) + + x_tile = x_samples.unsqueeze(0).repeat((sample_size, 1, 1)) + y_tile = y_samples.unsqueeze(1).repeat((1, sample_size, 1)) + + T0 = self._f(torch.cat([x_samples,y_samples], dim = -1)) + T1 = self._f(torch.cat([x_tile, y_tile], dim = -1)) + + lower_bound = T0.mean() - (T1.logsumexp(dim = 1).mean() - np.log(sample_size)) + return -lower_bound + +# Concat critic with the CLUBInfoNCE (NCE-CLUB) objective +class CLUBInfoNCECritic(nn.Module): + def __init__(self, A_dim, B_dim, hidden_dim, layers, activation, **extra_kwargs): + super(CLUBInfoNCECritic, self).__init__() + + self._f = mlp(A_dim + B_dim, hidden_dim, 1, layers, activation) + + # CLUB loss + def forward(self, x_samples, y_samples): + sample_size = y_samples.shape[0] + + #x_samples = F.normalize(x_samples, dim=-1) + #y_samples = F.normalize(y_samples, dim=-1) + + x_tile = x_samples.unsqueeze(0).repeat((sample_size, 1, 1)) + y_tile = y_samples.unsqueeze(1).repeat((1, sample_size, 1)) + + T0 = self._f(torch.cat([y_samples,x_samples], dim = -1)) + T1 = self._f(torch.cat([y_tile, x_tile], dim = -1)) + + return -(T0.mean() - T1.mean()) + + # InfoNCE loss + def learning_loss(self, x_samples, y_samples): + sample_size = y_samples.shape[0] + + #x_samples = F.normalize(x_samples, dim=-1) + #y_samples = F.normalize(y_samples, dim=-1) + + x_tile = x_samples.unsqueeze(0).repeat((sample_size, 1, 1)) + y_tile = y_samples.unsqueeze(1).repeat((1, sample_size, 1)) + + T0 = self._f(torch.cat([y_samples,x_samples], dim = -1)) + T1 = self._f(torch.cat([y_tile, x_tile], dim = -1)) + + lower_bound = T0.mean() - (T1.logsumexp(dim = 1).mean() - np.log(sample_size)) + return -lower_bound + +class SupConLoss(nn.Module): + """Supervised Contrastive Learning: https://arxiv.org/pdf/2004.11362.pdf. + It also supports the unsupervised contrastive loss in SimCLR""" + def __init__(self, temperature=0.07, contrast_mode='all', + base_temperature=0.07): + super(SupConLoss, self).__init__() + self.temperature = temperature + self.contrast_mode = contrast_mode + self.base_temperature = base_temperature + + def forward(self, features, labels=None, mask=None): + """Compute loss for model. If both `labels` and `mask` are None, + it degenerates to SimCLR unsupervised loss: + https://arxiv.org/pdf/2002.05709.pdf + Args: + features: hidden vector of shape [bsz, n_views, ...]. + labels: ground truth of shape [bsz]. + mask: contrastive mask of shape [bsz, bsz], mask_{i,j}=1 if sample j + has the same class as sample i. Can be asymmetric. + Returns: + A loss scalar. + """ + device = (torch.device('cuda') + if features.is_cuda + else torch.device('cpu')) + + if len(features.shape) < 3: + raise ValueError('`features` needs to be [bsz, n_views, ...],' + 'at least 3 dimensions are required') + if len(features.shape) > 3: + features = features.view(features.shape[0], features.shape[1], -1) + + batch_size = features.shape[0] + if labels is not None and mask is not None: + raise ValueError('Cannot define both `labels` and `mask`') + elif labels is None and mask is None: + mask = torch.eye(batch_size, dtype=torch.float32).to(device) + elif labels is not None: + labels = labels.contiguous().view(-1, 1) + if labels.shape[0] != batch_size: + raise ValueError('Num of labels does not match num of features') + mask = torch.eq(labels, labels.T).float().to(device) + else: + mask = mask.float().to(device) + + contrast_count = features.shape[1] + contrast_feature = torch.cat(torch.unbind(features, dim=1), dim=0) + if self.contrast_mode == 'one': + anchor_feature = features[:, 0] + anchor_count = 1 + elif self.contrast_mode == 'all': + anchor_feature = contrast_feature + anchor_count = contrast_count + else: + raise ValueError('Unknown mode: {}'.format(self.contrast_mode)) + + # compute logits + anchor_dot_contrast = torch.div( + torch.matmul(anchor_feature, contrast_feature.T), + self.temperature) + # for numerical stability + logits_max, _ = torch.max(anchor_dot_contrast, dim=1, keepdim=True) + logits = anchor_dot_contrast - logits_max.detach() + + # tile mask + mask = mask.repeat(anchor_count, contrast_count) + # mask-out self-contrast cases + logits_mask = torch.scatter( + torch.ones_like(mask), + 1, + torch.arange(batch_size * anchor_count).view(-1, 1).to(device), + 0 + ) + mask = mask * logits_mask + + # compute log_prob + exp_logits = torch.exp(logits) * logits_mask + log_prob = logits - torch.log(exp_logits.sum(1, keepdim=True)) + + # compute mean of log-likelihood over positive + mean_log_prob_pos = (mask * log_prob).sum(1) / mask.sum(1) + + # loss + loss = - (self.temperature / self.base_temperature) * mean_log_prob_pos + loss = loss.view(anchor_count, batch_size).mean() + + return loss diff --git a/src/e2_tts_pytorch/e2_tts_crossatt.py b/src/e2_tts_pytorch/e2_tts_crossatt.py new file mode 100644 index 0000000000000000000000000000000000000000..4fddd341b14ac4e00a7e555600e82432d6831cd3 --- /dev/null +++ b/src/e2_tts_pytorch/e2_tts_crossatt.py @@ -0,0 +1,2063 @@ +""" +ein notation: +b - batch +n - sequence +nt - text sequence +nw - raw wave length +d - dimension +dt - dimension text +""" + +from __future__ import annotations + +from pathlib import Path +from random import random +from functools import partial +from itertools import zip_longest +from collections import namedtuple + +from typing import Literal, Callable + +import jaxtyping +from beartype import beartype + +import torch +import torch.nn.functional as F +from torch import nn, tensor, Tensor, from_numpy +from torch.nn import Module, ModuleList, Sequential, Linear +from torch.nn.utils.rnn import pad_sequence + +import torchaudio +from torchaudio.functional import DB_to_amplitude +from torchdiffeq import odeint + +import einx +from einops.layers.torch import Rearrange +from einops import rearrange, repeat, reduce, pack, unpack + +from x_transformers import ( + Attention, + FeedForward, + RMSNorm, + AdaptiveRMSNorm, +) + +from x_transformers.x_transformers import RotaryEmbedding + +import sys +sys.path.insert(0, "/zhanghaomin/codes3/vocos-main/") +from vocos import Vocos + +from transformers import AutoTokenizer +from transformers import T5EncoderModel +from transformers import EncodecModel, AutoProcessor + +import os +import math +import traceback +import numpy as np +from moviepy.editor import AudioFileClip, VideoFileClip +from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection +#import open_clip +from transformers import AutoImageProcessor, AutoModel +from PIL import Image +import time + +import warnings +warnings.filterwarnings("ignore") + +def normalize_wav(waveform): + waveform = waveform - torch.mean(waveform) + waveform = waveform / (torch.max(torch.abs(waveform[0, :])) + 1e-8) + return waveform * 0.5 + +def read_frames_with_moviepy(video_path, max_frame_nums=None): + try: + clip = VideoFileClip(video_path) + duration = clip.duration + print("########", duration) + CUT = False + if duration > 30.0: + duration = 30.0 + CUT = True + fps = clip.fps + frames = [] + for frame in clip.iter_frames(): + frames.append(frame) + if CUT and len(frames) >= fps*duration: + break + except: + print("Error read_frames_with_moviepy", video_path) + traceback.print_exc() + return None, None, None + if max_frame_nums is not None: + frames_idx = np.linspace(0, len(frames) - 1, max_frame_nums, dtype=int) + return np.array(frames)[frames_idx, ...], duration, fps + else: + return np.array(frames), duration, fps + +pad_sequence = partial(pad_sequence, batch_first = True) + +# constants + +class TorchTyping: + def __init__(self, abstract_dtype): + self.abstract_dtype = abstract_dtype + + def __getitem__(self, shapes: str): + return self.abstract_dtype[Tensor, shapes] + +Float = TorchTyping(jaxtyping.Float) +Int = TorchTyping(jaxtyping.Int) +Bool = TorchTyping(jaxtyping.Bool) + +# named tuples + +LossBreakdown = namedtuple('LossBreakdown', ['flow', 'velocity_consistency']) + +E2TTSReturn = namedtuple('E2TTS', ['loss', 'cond', 'pred_flow', 'pred_data', 'loss_breakdown']) + +# helpers + +def exists(v): + return v is not None + +def default(v, d): + return v if exists(v) else d + +def divisible_by(num, den): + return (num % den) == 0 + +def pack_one_with_inverse(x, pattern): + packed, packed_shape = pack([x], pattern) + + def inverse(x, inverse_pattern = None): + inverse_pattern = default(inverse_pattern, pattern) + return unpack(x, packed_shape, inverse_pattern)[0] + + return packed, inverse + +class Identity(Module): + def forward(self, x, **kwargs): + return x + +# tensor helpers + +def project(x, y): + x, inverse = pack_one_with_inverse(x, 'b *') + y, _ = pack_one_with_inverse(y, 'b *') + + dtype = x.dtype + x, y = x.double(), y.double() + unit = F.normalize(y, dim = -1) + + parallel = (x * unit).sum(dim = -1, keepdim = True) * unit + orthogonal = x - parallel + + return inverse(parallel).to(dtype), inverse(orthogonal).to(dtype) + +# simple utf-8 tokenizer, since paper went character based + +def list_str_to_tensor( + text: list[str], + padding_value = -1 +) -> Int['b nt']: + + list_tensors = [tensor([*bytes(t, 'UTF-8')]) for t in text] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + +# simple english phoneme-based tokenizer + +from g2p_en import G2p +import jieba +from pypinyin import lazy_pinyin, Style + +def get_g2p_en_encode(): + g2p = G2p() + + # used by @lucasnewman successfully here + # https://github.com/lucasnewman/e2-tts-pytorch/blob/ljspeech-test/e2_tts_pytorch/e2_tts.py + + phoneme_to_index = g2p.p2idx + num_phonemes = len(phoneme_to_index) + + extended_chars = [' ', ',', '.', '-', '!', '?', '\'', '"', '...', '..', '. .', '. . .', '. . . .', '. . . . .', '. ...', '... .', '.. ..'] + num_extended_chars = len(extended_chars) + + extended_chars_dict = {p: (num_phonemes + i) for i, p in enumerate(extended_chars)} + phoneme_to_index = {**phoneme_to_index, **extended_chars_dict} + + def encode( + text: list[str], + padding_value = -1 + ) -> Int['b nt']: + + phonemes = [g2p(t) for t in text] + list_tensors = [tensor([phoneme_to_index[p] for p in one_phoneme]) for one_phoneme in phonemes] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + + return encode, (num_phonemes + num_extended_chars) + +def all_en(word): + res = word.replace("'", "").encode('utf-8').isalpha() + return res + +def all_ch(word): + res = True + for w in word: + if not '\u4e00' <= w <= '\u9fff': + res = False + return res + +def get_g2p_zh_encode(): + puncs = ['，', '。', '？', '、'] + pinyins = ['a', 'a1', 'ai1', 'ai2', 'ai3', 'ai4', 'an1', 'an3', 'an4', 'ang1', 'ang2', 'ang4', 'ao1', 'ao2', 'ao3', 'ao4', 'ba', 'ba1', 'ba2', 'ba3', 'ba4', 'bai1', 'bai2', 'bai3', 'bai4', 'ban1', 'ban2', 'ban3', 'ban4', 'bang1', 'bang2', 'bang3', 'bang4', 'bao1', 'bao2', 'bao3', 'bao4', 'bei', 'bei1', 'bei2', 'bei3', 'bei4', 'ben1', 'ben2', 'ben3', 'ben4', 'beng1', 'beng2', 'beng4', 'bi1', 'bi2', 'bi3', 'bi4', 'bian1', 'bian2', 'bian3', 'bian4', 'biao1', 'biao2', 'biao3', 'bie1', 'bie2', 'bie3', 'bie4', 'bin1', 'bin4', 'bing1', 'bing2', 'bing3', 'bing4', 'bo', 'bo1', 'bo2', 'bo3', 'bo4', 'bu2', 'bu3', 'bu4', 'ca1', 'cai1', 'cai2', 'cai3', 'cai4', 'can1', 'can2', 'can3', 'can4', 'cang1', 'cang2', 'cao1', 'cao2', 'cao3', 'ce4', 'cen1', 'cen2', 'ceng1', 'ceng2', 'ceng4', 'cha1', 'cha2', 'cha3', 'cha4', 'chai1', 'chai2', 'chan1', 'chan2', 'chan3', 'chan4', 'chang1', 'chang2', 'chang3', 'chang4', 'chao1', 'chao2', 'chao3', 'che1', 'che2', 'che3', 'che4', 'chen1', 'chen2', 'chen3', 'chen4', 'cheng1', 'cheng2', 'cheng3', 'cheng4', 'chi1', 'chi2', 'chi3', 'chi4', 'chong1', 'chong2', 'chong3', 'chong4', 'chou1', 'chou2', 'chou3', 'chou4', 'chu1', 'chu2', 'chu3', 'chu4', 'chua1', 'chuai1', 'chuai2', 'chuai3', 'chuai4', 'chuan1', 'chuan2', 'chuan3', 'chuan4', 'chuang1', 'chuang2', 'chuang3', 'chuang4', 'chui1', 'chui2', 'chun1', 'chun2', 'chun3', 'chuo1', 'chuo4', 'ci1', 'ci2', 'ci3', 'ci4', 'cong1', 'cong2', 'cou4', 'cu1', 'cu4', 'cuan1', 'cuan2', 'cuan4', 'cui1', 'cui3', 'cui4', 'cun1', 'cun2', 'cun4', 'cuo1', 'cuo2', 'cuo4', 'da', 'da1', 'da2', 'da3', 'da4', 'dai1', 'dai3', 'dai4', 'dan1', 'dan2', 'dan3', 'dan4', 'dang1', 'dang2', 'dang3', 'dang4', 'dao1', 'dao2', 'dao3', 'dao4', 'de', 'de1', 'de2', 'dei3', 'den4', 'deng1', 'deng2', 'deng3', 'deng4', 'di1', 'di2', 'di3', 'di4', 'dia3', 'dian1', 'dian2', 'dian3', 'dian4', 'diao1', 'diao3', 'diao4', 'die1', 'die2', 'ding1', 'ding2', 'ding3', 'ding4', 'diu1', 'dong1', 'dong3', 'dong4', 'dou1', 'dou2', 'dou3', 'dou4', 'du1', 'du2', 'du3', 'du4', 'duan1', 'duan2', 'duan3', 'duan4', 'dui1', 'dui4', 'dun1', 'dun3', 'dun4', 'duo1', 'duo2', 'duo3', 'duo4', 'e1', 'e2', 'e3', 'e4', 'ei2', 'en1', 'en4', 'er', 'er2', 'er3', 'er4', 'fa1', 'fa2', 'fa3', 'fa4', 'fan1', 'fan2', 'fan3', 'fan4', 'fang1', 'fang2', 'fang3', 'fang4', 'fei1', 'fei2', 'fei3', 'fei4', 'fen1', 'fen2', 'fen3', 'fen4', 'feng1', 'feng2', 'feng3', 'feng4', 'fo2', 'fou2', 'fou3', 'fu1', 'fu2', 'fu3', 'fu4', 'ga1', 'ga2', 'ga4', 'gai1', 'gai3', 'gai4', 'gan1', 'gan2', 'gan3', 'gan4', 'gang1', 'gang2', 'gang3', 'gang4', 'gao1', 'gao2', 'gao3', 'gao4', 'ge1', 'ge2', 'ge3', 'ge4', 'gei2', 'gei3', 'gen1', 'gen2', 'gen3', 'gen4', 'geng1', 'geng3', 'geng4', 'gong1', 'gong3', 'gong4', 'gou1', 'gou2', 'gou3', 'gou4', 'gu', 'gu1', 'gu2', 'gu3', 'gu4', 'gua1', 'gua2', 'gua3', 'gua4', 'guai1', 'guai2', 'guai3', 'guai4', 'guan1', 'guan2', 'guan3', 'guan4', 'guang1', 'guang2', 'guang3', 'guang4', 'gui1', 'gui2', 'gui3', 'gui4', 'gun3', 'gun4', 'guo1', 'guo2', 'guo3', 'guo4', 'ha1', 'ha2', 'ha3', 'hai1', 'hai2', 'hai3', 'hai4', 'han1', 'han2', 'han3', 'han4', 'hang1', 'hang2', 'hang4', 'hao1', 'hao2', 'hao3', 'hao4', 'he1', 'he2', 'he4', 'hei1', 'hen2', 'hen3', 'hen4', 'heng1', 'heng2', 'heng4', 'hong1', 'hong2', 'hong3', 'hong4', 'hou1', 'hou2', 'hou3', 'hou4', 'hu1', 'hu2', 'hu3', 'hu4', 'hua1', 'hua2', 'hua4', 'huai2', 'huai4', 'huan1', 'huan2', 'huan3', 'huan4', 'huang1', 'huang2', 'huang3', 'huang4', 'hui1', 'hui2', 'hui3', 'hui4', 'hun1', 'hun2', 'hun4', 'huo', 'huo1', 'huo2', 'huo3', 'huo4', 'ji1', 'ji2', 'ji3', 'ji4', 'jia', 'jia1', 'jia2', 'jia3', 'jia4', 'jian1', 'jian2', 'jian3', 'jian4', 'jiang1', 'jiang2', 'jiang3', 'jiang4', 'jiao1', 'jiao2', 'jiao3', 'jiao4', 'jie1', 'jie2', 'jie3', 'jie4', 'jin1', 'jin2', 'jin3', 'jin4', 'jing1', 'jing2', 'jing3', 'jing4', 'jiong3', 'jiu1', 'jiu2', 'jiu3', 'jiu4', 'ju1', 'ju2', 'ju3', 'ju4', 'juan1', 'juan2', 'juan3', 'juan4', 'jue1', 'jue2', 'jue4', 'jun1', 'jun4', 'ka1', 'ka2', 'ka3', 'kai1', 'kai2', 'kai3', 'kai4', 'kan1', 'kan2', 'kan3', 'kan4', 'kang1', 'kang2', 'kang4', 'kao2', 'kao3', 'kao4', 'ke1', 'ke2', 'ke3', 'ke4', 'ken3', 'keng1', 'kong1', 'kong3', 'kong4', 'kou1', 'kou2', 'kou3', 'kou4', 'ku1', 'ku2', 'ku3', 'ku4', 'kua1', 'kua3', 'kua4', 'kuai3', 'kuai4', 'kuan1', 'kuan2', 'kuan3', 'kuang1', 'kuang2', 'kuang4', 'kui1', 'kui2', 'kui3', 'kui4', 'kun1', 'kun3', 'kun4', 'kuo4', 'la', 'la1', 'la2', 'la3', 'la4', 'lai2', 'lai4', 'lan2', 'lan3', 'lan4', 'lang1', 'lang2', 'lang3', 'lang4', 'lao1', 'lao2', 'lao3', 'lao4', 'le', 'le1', 'le4', 'lei', 'lei1', 'lei2', 'lei3', 'lei4', 'leng1', 'leng2', 'leng3', 'leng4', 'li', 'li1', 'li2', 'li3', 'li4', 'lia3', 'lian2', 'lian3', 'lian4', 'liang2', 'liang3', 'liang4', 'liao1', 'liao2', 'liao3', 'liao4', 'lie1', 'lie2', 'lie3', 'lie4', 'lin1', 'lin2', 'lin3', 'lin4', 'ling2', 'ling3', 'ling4', 'liu1', 'liu2', 'liu3', 'liu4', 'long1', 'long2', 'long3', 'long4', 'lou1', 'lou2', 'lou3', 'lou4', 'lu1', 'lu2', 'lu3', 'lu4', 'luan2', 'luan3', 'luan4', 'lun1', 'lun2', 'lun4', 'luo1', 'luo2', 'luo3', 'luo4', 'lv2', 'lv3', 'lv4', 'lve3', 'lve4', 'ma', 'ma1', 'ma2', 'ma3', 'ma4', 'mai2', 'mai3', 'mai4', 'man2', 'man3', 'man4', 'mang2', 'mang3', 'mao1', 'mao2', 'mao3', 'mao4', 'me', 'mei2', 'mei3', 'mei4', 'men', 'men1', 'men2', 'men4', 'meng1', 'meng2', 'meng3', 'meng4', 'mi1', 'mi2', 'mi3', 'mi4', 'mian2', 'mian3', 'mian4', 'miao1', 'miao2', 'miao3', 'miao4', 'mie1', 'mie4', 'min2', 'min3', 'ming2', 'ming3', 'ming4', 'miu4', 'mo1', 'mo2', 'mo3', 'mo4', 'mou1', 'mou2', 'mou3', 'mu2', 'mu3', 'mu4', 'n2', 'na1', 'na2', 'na3', 'na4', 'nai2', 'nai3', 'nai4', 'nan1', 'nan2', 'nan3', 'nan4', 'nang1', 'nang2', 'nao1', 'nao2', 'nao3', 'nao4', 'ne', 'ne2', 'ne4', 'nei3', 'nei4', 'nen4', 'neng2', 'ni1', 'ni2', 'ni3', 'ni4', 'nian1', 'nian2', 'nian3', 'nian4', 'niang2', 'niang4', 'niao2', 'niao3', 'niao4', 'nie1', 'nie4', 'nin2', 'ning2', 'ning3', 'ning4', 'niu1', 'niu2', 'niu3', 'niu4', 'nong2', 'nong4', 'nou4', 'nu2', 'nu3', 'nu4', 'nuan3', 'nuo2', 'nuo4', 'nv2', 'nv3', 'nve4', 'o1', 'o2', 'ou1', 'ou3', 'ou4', 'pa1', 'pa2', 'pa4', 'pai1', 'pai2', 'pai3', 'pai4', 'pan1', 'pan2', 'pan4', 'pang1', 'pang2', 'pang4', 'pao1', 'pao2', 'pao3', 'pao4', 'pei1', 'pei2', 'pei4', 'pen1', 'pen2', 'pen4', 'peng1', 'peng2', 'peng3', 'peng4', 'pi1', 'pi2', 'pi3', 'pi4', 'pian1', 'pian2', 'pian4', 'piao1', 'piao2', 'piao3', 'piao4', 'pie1', 'pie2', 'pie3', 'pin1', 'pin2', 'pin3', 'pin4', 'ping1', 'ping2', 'po1', 'po2', 'po3', 'po4', 'pou1', 'pu1', 'pu2', 'pu3', 'pu4', 'qi1', 'qi2', 'qi3', 'qi4', 'qia1', 'qia3', 'qia4', 'qian1', 'qian2', 'qian3', 'qian4', 'qiang1', 'qiang2', 'qiang3', 'qiang4', 'qiao1', 'qiao2', 'qiao3', 'qiao4', 'qie1', 'qie2', 'qie3', 'qie4', 'qin1', 'qin2', 'qin3', 'qin4', 'qing1', 'qing2', 'qing3', 'qing4', 'qiong1', 'qiong2', 'qiu1', 'qiu2', 'qiu3', 'qu1', 'qu2', 'qu3', 'qu4', 'quan1', 'quan2', 'quan3', 'quan4', 'que1', 'que2', 'que4', 'qun2', 'ran2', 'ran3', 'rang1', 'rang2', 'rang3', 'rang4', 'rao2', 'rao3', 'rao4', 're2', 're3', 're4', 'ren2', 'ren3', 'ren4', 'reng1', 'reng2', 'ri4', 'rong1', 'rong2', 'rong3', 'rou2', 'rou4', 'ru2', 'ru3', 'ru4', 'ruan2', 'ruan3', 'rui3', 'rui4', 'run4', 'ruo4', 'sa1', 'sa2', 'sa3', 'sa4', 'sai1', 'sai4', 'san1', 'san2', 'san3', 'san4', 'sang1', 'sang3', 'sang4', 'sao1', 'sao2', 'sao3', 'sao4', 'se4', 'sen1', 'seng1', 'sha1', 'sha2', 'sha3', 'sha4', 'shai1', 'shai2', 'shai3', 'shai4', 'shan1', 'shan3', 'shan4', 'shang', 'shang1', 'shang3', 'shang4', 'shao1', 'shao2', 'shao3', 'shao4', 'she1', 'she2', 'she3', 'she4', 'shei2', 'shen1', 'shen2', 'shen3', 'shen4', 'sheng1', 'sheng2', 'sheng3', 'sheng4', 'shi', 'shi1', 'shi2', 'shi3', 'shi4', 'shou1', 'shou2', 'shou3', 'shou4', 'shu1', 'shu2', 'shu3', 'shu4', 'shua1', 'shua2', 'shua3', 'shua4', 'shuai1', 'shuai3', 'shuai4', 'shuan1', 'shuan4', 'shuang1', 'shuang3', 'shui2', 'shui3', 'shui4', 'shun3', 'shun4', 'shuo1', 'shuo4', 'si1', 'si2', 'si3', 'si4', 'song1', 'song3', 'song4', 'sou1', 'sou3', 'sou4', 'su1', 'su2', 'su4', 'suan1', 'suan4', 'sui1', 'sui2', 'sui3', 'sui4', 'sun1', 'sun3', 'suo', 'suo1', 'suo2', 'suo3', 'ta1', 'ta3', 'ta4', 'tai1', 'tai2', 'tai4', 'tan1', 'tan2', 'tan3', 'tan4', 'tang1', 'tang2', 'tang3', 'tang4', 'tao1', 'tao2', 'tao3', 'tao4', 'te4', 'teng2', 'ti1', 'ti2', 'ti3', 'ti4', 'tian1', 'tian2', 'tian3', 'tiao1', 'tiao2', 'tiao3', 'tiao4', 'tie1', 'tie2', 'tie3', 'tie4', 'ting1', 'ting2', 'ting3', 'tong1', 'tong2', 'tong3', 'tong4', 'tou', 'tou1', 'tou2', 'tou4', 'tu1', 'tu2', 'tu3', 'tu4', 'tuan1', 'tuan2', 'tui1', 'tui2', 'tui3', 'tui4', 'tun1', 'tun2', 'tun4', 'tuo1', 'tuo2', 'tuo3', 'tuo4', 'wa', 'wa1', 'wa2', 'wa3', 'wa4', 'wai1', 'wai3', 'wai4', 'wan1', 'wan2', 'wan3', 'wan4', 'wang1', 'wang2', 'wang3', 'wang4', 'wei1', 'wei2', 'wei3', 'wei4', 'wen1', 'wen2', 'wen3', 'wen4', 'weng1', 'weng4', 'wo1', 'wo3', 'wo4', 'wu1', 'wu2', 'wu3', 'wu4', 'xi1', 'xi2', 'xi3', 'xi4', 'xia1', 'xia2', 'xia4', 'xian1', 'xian2', 'xian3', 'xian4', 'xiang1', 'xiang2', 'xiang3', 'xiang4', 'xiao1', 'xiao2', 'xiao3', 'xiao4', 'xie1', 'xie2', 'xie3', 'xie4', 'xin1', 'xin2', 'xin4', 'xing1', 'xing2', 'xing3', 'xing4', 'xiong1', 'xiong2', 'xiu1', 'xiu3', 'xiu4', 'xu', 'xu1', 'xu2', 'xu3', 'xu4', 'xuan1', 'xuan2', 'xuan3', 'xuan4', 'xue1', 'xue2', 'xue3', 'xue4', 'xun1', 'xun2', 'xun4', 'ya', 'ya1', 'ya2', 'ya3', 'ya4', 'yan1', 'yan2', 'yan3', 'yan4', 'yang1', 'yang2', 'yang3', 'yang4', 'yao1', 'yao2', 'yao3', 'yao4', 'ye1', 'ye2', 'ye3', 'ye4', 'yi1', 'yi2', 'yi3', 'yi4', 'yin1', 'yin2', 'yin3', 'yin4', 'ying1', 'ying2', 'ying3', 'ying4', 'yo1', 'yong1', 'yong3', 'yong4', 'you1', 'you2', 'you3', 'you4', 'yu1', 'yu2', 'yu3', 'yu4', 'yuan1', 'yuan2', 'yuan3', 'yuan4', 'yue1', 'yue4', 'yun1', 'yun2', 'yun3', 'yun4', 'za1', 'za2', 'za3', 'zai1', 'zai3', 'zai4', 'zan1', 'zan2', 'zan3', 'zan4', 'zang1', 'zang4', 'zao1', 'zao2', 'zao3', 'zao4', 'ze2', 'ze4', 'zei2', 'zen3', 'zeng1', 'zeng4', 'zha1', 'zha2', 'zha3', 'zha4', 'zhai1', 'zhai2', 'zhai3', 'zhai4', 'zhan1', 'zhan2', 'zhan3', 'zhan4', 'zhang1', 'zhang2', 'zhang3', 'zhang4', 'zhao1', 'zhao2', 'zhao3', 'zhao4', 'zhe', 'zhe1', 'zhe2', 'zhe3', 'zhe4', 'zhen1', 'zhen2', 'zhen3', 'zhen4', 'zheng1', 'zheng2', 'zheng3', 'zheng4', 'zhi1', 'zhi2', 'zhi3', 'zhi4', 'zhong1', 'zhong2', 'zhong3', 'zhong4', 'zhou1', 'zhou2', 'zhou3', 'zhou4', 'zhu1', 'zhu2', 'zhu3', 'zhu4', 'zhua1', 'zhua2', 'zhua3', 'zhuai1', 'zhuai3', 'zhuai4', 'zhuan1', 'zhuan2', 'zhuan3', 'zhuan4', 'zhuang1', 'zhuang4', 'zhui1', 'zhui4', 'zhun1', 'zhun2', 'zhun3', 'zhuo1', 'zhuo2', 'zi', 'zi1', 'zi2', 'zi3', 'zi4', 'zong1', 'zong2', 'zong3', 'zong4', 'zou1', 'zou2', 'zou3', 'zou4', 'zu1', 'zu2', 'zu3', 'zuan1', 'zuan3', 'zuan4', 'zui2', 'zui3', 'zui4', 'zun1', 'zuo1', 'zuo2', 'zuo3', 'zuo4'] + ens = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z', "'", ' '] + ens_U = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'] + + phoneme_to_index = {} + num_phonemes = 0 + for index, punc in enumerate(puncs): + phoneme_to_index[punc] = index + num_phonemes + num_phonemes += len(puncs) + for index, pinyin in enumerate(pinyins): + phoneme_to_index[pinyin] = index + num_phonemes + num_phonemes += len(pinyins) + for index, en in enumerate(ens): + phoneme_to_index[en] = index + num_phonemes + for index, en in enumerate(ens_U): + phoneme_to_index[en] = index + num_phonemes + num_phonemes += len(ens) + #print(num_phonemes, phoneme_to_index) # 1342 + + def encode( + text: list[str], + padding_value = -1 + ) -> Int['b nt']: + phonemes = [] + for t in text: + one_phoneme = [] + brk = False + for word in jieba.cut(t): + if all_ch(word): + seg = lazy_pinyin(word, style=Style.TONE3, tone_sandhi=True) + one_phoneme.extend(seg) + elif all_en(word): + for seg in word: + one_phoneme.append(seg) + elif word in ["，", "。", "？", "、", "'", " "]: + one_phoneme.append(word) + else: + for ch in word: + if all_ch(ch): + seg = lazy_pinyin(ch, style=Style.TONE3, tone_sandhi=True) + one_phoneme.extend(seg) + elif all_en(ch): + for seg in ch: + one_phoneme.append(seg) + else: + brk = True + break + if brk: + break + if not brk: + phonemes.append(one_phoneme) + else: + print("Error Tokenized", t, list(jieba.cut(t))) + list_tensors = [tensor([phoneme_to_index[p] for p in one_phoneme]) for one_phoneme in phonemes] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + + return encode, num_phonemes + +# tensor helpers + +def log(t, eps = 1e-5): + return t.clamp(min = eps).log() + +def lens_to_mask( + t: Int['b'], + length: int | None = None +) -> Bool['b n']: + + if not exists(length): + length = t.amax() + + seq = torch.arange(length, device = t.device) + return einx.less('n, b -> b n', seq, t) + +def mask_from_start_end_indices( + seq_len: Int['b'], + start: Int['b'], + end: Int['b'] +): + max_seq_len = seq_len.max().item() + seq = torch.arange(max_seq_len, device = start.device).long() + return einx.greater_equal('n, b -> b n', seq, start) & einx.less('n, b -> b n', seq, end) + +def mask_from_frac_lengths( + seq_len: Int['b'], + frac_lengths: Float['b'], + max_length: int | None = None, + val = False +): + lengths = (frac_lengths * seq_len).long() + max_start = seq_len - lengths + + if not val: + rand = torch.rand_like(frac_lengths) + else: + rand = torch.tensor([0.5]*frac_lengths.shape[0], device=frac_lengths.device).float() + start = (max_start * rand).long().clamp(min = 0) + end = start + lengths + + out = mask_from_start_end_indices(seq_len, start, end) + + if exists(max_length): + out = pad_to_length(out, max_length) + + return out + +def maybe_masked_mean( + t: Float['b n d'], + mask: Bool['b n'] | None = None +) -> Float['b d']: + + if not exists(mask): + return t.mean(dim = 1) + + t = einx.where('b n, b n d, -> b n d', mask, t, 0.) + num = reduce(t, 'b n d -> b d', 'sum') + den = reduce(mask.float(), 'b n -> b', 'sum') + + return einx.divide('b d, b -> b d', num, den.clamp(min = 1.)) + +def pad_to_length( + t: Tensor, + length: int, + value = None +): + seq_len = t.shape[-1] + if length > seq_len: + t = F.pad(t, (0, length - seq_len), value = value) + + return t[..., :length] + +def interpolate_1d( + x: Tensor, + length: int, + mode = 'bilinear' +): + x = rearrange(x, 'n d -> 1 d n 1') + x = F.interpolate(x, (length, 1), mode = mode) + return rearrange(x, '1 d n 1 -> n d') + +# to mel spec + +class MelSpec(Module): + def __init__( + self, + filter_length = 1024, + hop_length = 256, + win_length = 1024, + n_mel_channels = 100, + sampling_rate = 24_000, + normalize = False, + power = 1, + norm = None, + center = True, + ): + super().__init__() + self.n_mel_channels = n_mel_channels + self.sampling_rate = sampling_rate + + self.mel_stft = torchaudio.transforms.MelSpectrogram( + sample_rate = sampling_rate, + n_fft = filter_length, + win_length = win_length, + hop_length = hop_length, + n_mels = n_mel_channels, + power = power, + center = center, + normalized = normalize, + norm = norm, + ) + + self.register_buffer('dummy', tensor(0), persistent = False) + + def forward(self, inp): + if len(inp.shape) == 3: + inp = rearrange(inp, 'b 1 nw -> b nw') + + assert len(inp.shape) == 2 + + if self.dummy.device != inp.device: + self.to(inp.device) + + mel = self.mel_stft(inp) + mel = log(mel) + return mel + +class EncodecWrapper(Module): + def __init__(self, path): + super().__init__() + self.model = EncodecModel.from_pretrained(path) + self.processor = AutoProcessor.from_pretrained(path) + for param in self.model.parameters(): + param.requires_grad = False + self.model.eval() + + def forward(self, waveform): + with torch.no_grad(): + inputs = self.processor(raw_audio=waveform[0], sampling_rate=self.processor.sampling_rate, return_tensors="pt") + emb = self.model.encoder(inputs.input_values) + return emb + + def decode(self, emb): + with torch.no_grad(): + output = self.model.decoder(emb) + return output[0] + +from audioldm.audio.stft import TacotronSTFT +from audioldm.variational_autoencoder import AutoencoderKL +from audioldm.utils import default_audioldm_config, get_metadata + +def build_pretrained_models(name): + checkpoint = torch.load(get_metadata()[name]["path"], map_location="cpu") + scale_factor = checkpoint["state_dict"]["scale_factor"].item() + + vae_state_dict = {k[18:]: v for k, v in checkpoint["state_dict"].items() if "first_stage_model." in k} + + config = default_audioldm_config(name) + vae_config = config["model"]["params"]["first_stage_config"]["params"] + vae_config["scale_factor"] = scale_factor + + vae = AutoencoderKL(**vae_config) + vae.load_state_dict(vae_state_dict) + + fn_STFT = TacotronSTFT( + config["preprocessing"]["stft"]["filter_length"], + config["preprocessing"]["stft"]["hop_length"], + config["preprocessing"]["stft"]["win_length"], + config["preprocessing"]["mel"]["n_mel_channels"], + config["preprocessing"]["audio"]["sampling_rate"], + config["preprocessing"]["mel"]["mel_fmin"], + config["preprocessing"]["mel"]["mel_fmax"], + ) + + vae.eval() + fn_STFT.eval() + return vae, fn_STFT + +class VaeWrapper(Module): + def __init__(self): + super().__init__() + vae, stft = build_pretrained_models("audioldm-s-full") + vae.eval() + stft.eval() + stft = stft.cpu() + self.vae = vae + for param in self.vae.parameters(): + param.requires_grad = False + + def forward(self, waveform): + return None + + def decode(self, emb): + with torch.no_grad(): + b, d, l = emb.shape + latents = emb.transpose(1,2).reshape(b, l, 8, 16).transpose(1,2) + mel = self.vae.decode_first_stage(latents) + wave = self.vae.decode_to_waveform(mel) + return wave + +# convolutional positional generating module +# taken from https://github.com/lucidrains/voicebox-pytorch/blob/main/voicebox_pytorch/voicebox_pytorch.py#L203 + +class DepthwiseConv(Module): + def __init__( + self, + dim, + *, + kernel_size, + groups = None + ): + super().__init__() + assert not divisible_by(kernel_size, 2) + groups = default(groups, dim) # full depthwise conv by default + + self.dw_conv1d = nn.Sequential( + nn.Conv1d(dim, dim, kernel_size, groups = groups, padding = kernel_size // 2), + nn.SiLU() + ) + + def forward( + self, + x, + mask = None + ): + + if exists(mask): + x = einx.where('b n, b n d, -> b n d', mask, x, 0.) + + x = rearrange(x, 'b n c -> b c n') + x = self.dw_conv1d(x) + out = rearrange(x, 'b c n -> b n c') + + if exists(mask): + out = einx.where('b n, b n d, -> b n d', mask, out, 0.) + + return out + +# adaln zero from DiT paper + +class AdaLNZero(Module): + def __init__( + self, + dim, + dim_condition = None, + init_bias_value = -2. + ): + super().__init__() + dim_condition = default(dim_condition, dim) + self.to_gamma = nn.Linear(dim_condition, dim) + + nn.init.zeros_(self.to_gamma.weight) + nn.init.constant_(self.to_gamma.bias, init_bias_value) + + def forward(self, x, *, condition): + if condition.ndim == 2: + condition = rearrange(condition, 'b d -> b 1 d') + + gamma = self.to_gamma(condition).sigmoid() + return x * gamma + +# random projection fourier embedding + +class RandomFourierEmbed(Module): + def __init__(self, dim): + super().__init__() + assert divisible_by(dim, 2) + self.register_buffer('weights', torch.randn(dim // 2)) + + def forward(self, x): + freqs = einx.multiply('i, j -> i j', x, self.weights) * 2 * torch.pi + fourier_embed, _ = pack((x, freqs.sin(), freqs.cos()), 'b *') + return fourier_embed + +# character embedding + +class CharacterEmbed(Module): + def __init__( + self, + dim, + num_embeds = 256, + ): + super().__init__() + self.dim = dim + self.embed = nn.Embedding(num_embeds + 1, dim) # will just use 0 as the 'filler token' + + def forward( + self, + text: Int['b nt'], + max_seq_len: int, + **kwargs + ) -> Float['b n d']: + + text = text + 1 # shift all other token ids up by 1 and use 0 as filler token + + text = text[:, :max_seq_len] # just curtail if character tokens are more than the mel spec tokens, one of the edge cases the paper did not address + text = pad_to_length(text, max_seq_len, value = 0) + + return self.embed(text) + +class InterpolatedCharacterEmbed(Module): + def __init__( + self, + dim, + num_embeds = 256, + ): + super().__init__() + self.dim = dim + self.embed = nn.Embedding(num_embeds, dim) + + self.abs_pos_mlp = Sequential( + Rearrange('... -> ... 1'), + Linear(1, dim), + nn.SiLU(), + Linear(dim, dim) + ) + + def forward( + self, + text: Int['b nt'], + max_seq_len: int, + mask: Bool['b n'] | None = None + ) -> Float['b n d']: + + device = text.device + + mask = default(mask, (None,)) + + interp_embeds = [] + interp_abs_positions = [] + + for one_text, one_mask in zip_longest(text, mask): + + valid_text = one_text >= 0 + one_text = one_text[valid_text] + one_text_embed = self.embed(one_text) + + # save the absolute positions + + text_seq_len = one_text.shape[0] + + # determine audio sequence length from mask + + audio_seq_len = max_seq_len + if exists(one_mask): + audio_seq_len = one_mask.sum().long().item() + + # interpolate text embedding to audio embedding length + + interp_text_embed = interpolate_1d(one_text_embed, audio_seq_len) + interp_abs_pos = torch.linspace(0, text_seq_len, audio_seq_len, device = device) + + interp_embeds.append(interp_text_embed) + interp_abs_positions.append(interp_abs_pos) + + interp_embeds = pad_sequence(interp_embeds) + interp_abs_positions = pad_sequence(interp_abs_positions) + + interp_embeds = F.pad(interp_embeds, (0, 0, 0, max_seq_len - interp_embeds.shape[-2])) + interp_abs_positions = pad_to_length(interp_abs_positions, max_seq_len) + + # pass interp absolute positions through mlp for implicit positions + + interp_embeds = interp_embeds + self.abs_pos_mlp(interp_abs_positions) + + if exists(mask): + interp_embeds = einx.where('b n, b n d, -> b n d', mask, interp_embeds, 0.) + + return interp_embeds + +# text audio cross conditioning in multistream setup + +class TextAudioCrossCondition(Module): + def __init__( + self, + dim, + dim_text, + cond_audio_to_text = True, + ): + super().__init__() + self.text_to_audio = nn.Linear(dim_text + dim, dim, bias = False) + nn.init.zeros_(self.text_to_audio.weight) + + self.cond_audio_to_text = cond_audio_to_text + + if cond_audio_to_text: + self.audio_to_text = nn.Linear(dim + dim_text, dim_text, bias = False) + nn.init.zeros_(self.audio_to_text.weight) + + def forward( + self, + audio: Float['b n d'], + text: Float['b n dt'] + ): + audio_text, _ = pack((audio, text), 'b n *') + + text_cond = self.text_to_audio(audio_text) + audio_cond = self.audio_to_text(audio_text) if self.cond_audio_to_text else 0. + + return audio + text_cond, text + audio_cond + +# attention and transformer backbone +# for use in both e2tts as well as duration module + +class Transformer(Module): + @beartype + def __init__( + self, + *, + dim, + dim_text = None, # will default to half of audio dimension + depth = 8, + heads = 8, + dim_head = 64, + ff_mult = 4, + text_depth = None, + text_heads = None, + text_dim_head = None, + text_ff_mult = None, + cond_on_time = True, + abs_pos_emb = True, + max_seq_len = 8192, + kernel_size = 31, + dropout = 0.1, + num_registers = 32, + attn_kwargs: dict = dict( + gate_value_heads = True, + softclamp_logits = True, + ), + ff_kwargs: dict = dict(), + if_text_modules = True, + if_cross_attn = True, + if_audio_conv = True, + if_text_conv = False + ): + super().__init__() + assert divisible_by(depth, 2), 'depth needs to be even' + + # absolute positional embedding + + self.max_seq_len = max_seq_len + self.abs_pos_emb = nn.Embedding(max_seq_len, dim) if abs_pos_emb else None + + self.dim = dim + + dim_text = default(dim_text, dim // 2) + self.dim_text = dim_text + + text_heads = default(text_heads, heads) + text_dim_head = default(text_dim_head, dim_head) + text_ff_mult = default(text_ff_mult, ff_mult) + text_depth = default(text_depth, depth) + + assert 1 <= text_depth <= depth, 'must have at least 1 layer of text conditioning, but less than total number of speech layers' + + self.depth = depth + self.layers = ModuleList([]) + + # registers + + self.num_registers = num_registers + self.registers = nn.Parameter(torch.zeros(num_registers, dim)) + nn.init.normal_(self.registers, std = 0.02) + + if if_text_modules: + self.text_registers = nn.Parameter(torch.zeros(num_registers, dim_text)) + nn.init.normal_(self.text_registers, std = 0.02) + + # rotary embedding + + self.rotary_emb = RotaryEmbedding(dim_head) + self.text_rotary_emb = RotaryEmbedding(dim_head) + + # time conditioning + # will use adaptive rmsnorm + + self.cond_on_time = cond_on_time + rmsnorm_klass = RMSNorm if not cond_on_time else AdaptiveRMSNorm + postbranch_klass = Identity if not cond_on_time else partial(AdaLNZero, dim = dim) + + self.time_cond_mlp = Identity() + + if cond_on_time: + self.time_cond_mlp = Sequential( + RandomFourierEmbed(dim), + Linear(dim + 1, dim), + nn.SiLU() + ) + + for ind in range(depth): + is_later_half = ind >= (depth // 2) + has_text = ind < text_depth + + # speech related + if if_audio_conv: + speech_conv = DepthwiseConv(dim, kernel_size = kernel_size) + + attn_norm = rmsnorm_klass(dim) + attn = Attention(dim = dim, heads = heads, dim_head = dim_head, dropout = dropout, **attn_kwargs) + attn_adaln_zero = postbranch_klass() + + if if_cross_attn: + attn_norm2 = rmsnorm_klass(dim) + attn2 = Attention(dim = dim, heads = heads, dim_head = dim_head, dropout = dropout, **attn_kwargs) + attn_adaln_zero2 = postbranch_klass() + + ff_norm = rmsnorm_klass(dim) + ff = FeedForward(dim = dim, glu = True, mult = ff_mult, dropout = dropout, **ff_kwargs) + ff_adaln_zero = postbranch_klass() + + skip_proj = Linear(dim * 2, dim, bias = False) if is_later_half else None + + if if_cross_attn: + if if_audio_conv: + speech_modules = ModuleList([ + skip_proj, + speech_conv, + attn_norm, + attn, + attn_adaln_zero, + attn_norm2, + attn2, + attn_adaln_zero2, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + speech_modules = ModuleList([ + skip_proj, + attn_norm, + attn, + attn_adaln_zero, + attn_norm2, + attn2, + attn_adaln_zero2, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + if if_audio_conv: + speech_modules = ModuleList([ + skip_proj, + speech_conv, + attn_norm, + attn, + attn_adaln_zero, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + speech_modules = ModuleList([ + skip_proj, + attn_norm, + attn, + attn_adaln_zero, + ff_norm, + ff, + ff_adaln_zero, + ]) + + text_modules = None + + if has_text and if_text_modules: + # text related + if if_text_conv: + text_conv = DepthwiseConv(dim_text, kernel_size = kernel_size) + + text_attn_norm = RMSNorm(dim_text) + text_attn = Attention(dim = dim_text, heads = text_heads, dim_head = text_dim_head, dropout = dropout, **attn_kwargs) + + text_ff_norm = RMSNorm(dim_text) + text_ff = FeedForward(dim = dim_text, glu = True, mult = text_ff_mult, dropout = dropout, **ff_kwargs) + + # cross condition + + is_last = ind == (text_depth - 1) + + cross_condition = TextAudioCrossCondition(dim = dim, dim_text = dim_text, cond_audio_to_text = not is_last) + + if if_text_conv: + text_modules = ModuleList([ + text_conv, + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ]) + else: + text_modules = ModuleList([ + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ]) + + self.layers.append(ModuleList([ + speech_modules, + text_modules + ])) + + self.final_norm = RMSNorm(dim) + + self.if_cross_attn = if_cross_attn + self.if_audio_conv = if_audio_conv + self.if_text_conv = if_text_conv + + def forward( + self, + x: Float['b n d'], + times: Float['b'] | Float[''] | None = None, + mask: Bool['b n'] | None = None, + text_embed: Float['b n dt'] | None = None, + context: Float['b nc dc'] | None = None, + context_mask: Float['b nc'] | None = None + ): + batch, seq_len, device = *x.shape[:2], x.device + + assert not (exists(times) ^ self.cond_on_time), '`times` must be passed in if `cond_on_time` is set to `True` and vice versa' + + # handle absolute positions if needed + + if exists(self.abs_pos_emb): + assert seq_len <= self.max_seq_len, f'{seq_len} exceeds the set `max_seq_len` ({self.max_seq_len}) on Transformer' + seq = torch.arange(seq_len, device = device) + x = x + self.abs_pos_emb(seq) + + # handle adaptive rmsnorm kwargs + + norm_kwargs = dict() + + if exists(times): + if times.ndim == 0: + times = repeat(times, ' -> b', b = batch) + + times = self.time_cond_mlp(times) + norm_kwargs.update(condition = times) + + # register tokens + + registers = repeat(self.registers, 'r d -> b r d', b = batch) + x, registers_packed_shape = pack((registers, x), 'b * d') + + if exists(mask): + mask = F.pad(mask, (self.num_registers, 0), value = True) + + # rotary embedding + + rotary_pos_emb = self.rotary_emb.forward_from_seq_len(x.shape[-2]) + + # text related + + if exists(text_embed): + text_rotary_pos_emb = self.text_rotary_emb.forward_from_seq_len(x.shape[-2]) + + text_registers = repeat(self.text_registers, 'r d -> b r d', b = batch) + text_embed, _ = pack((text_registers, text_embed), 'b * d') + + # skip connection related stuff + + skips = [] + + # go through the layers + + for ind, (speech_modules, text_modules) in enumerate(self.layers): + layer = ind + 1 + + if self.if_cross_attn: + if self.if_audio_conv: + ( + maybe_skip_proj, + speech_conv, + attn_norm, + attn, + maybe_attn_adaln_zero, + attn_norm2, + attn2, + maybe_attn_adaln_zero2, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + ( + maybe_skip_proj, + attn_norm, + attn, + maybe_attn_adaln_zero, + attn_norm2, + attn2, + maybe_attn_adaln_zero2, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + if self.if_audio_conv: + ( + maybe_skip_proj, + speech_conv, + attn_norm, + attn, + maybe_attn_adaln_zero, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + ( + maybe_skip_proj, + attn_norm, + attn, + maybe_attn_adaln_zero, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + + # smaller text transformer + + if exists(text_embed) and exists(text_modules): + + if self.if_text_conv: + ( + text_conv, + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ) = text_modules + else: + ( + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ) = text_modules + + if self.if_text_conv: + text_embed = text_conv(text_embed, mask = mask) + text_embed + + text_embed = text_attn(text_attn_norm(text_embed), rotary_pos_emb = text_rotary_pos_emb, mask = mask) + text_embed + + text_embed = text_ff(text_ff_norm(text_embed)) + text_embed + + x, text_embed = cross_condition(x, text_embed) + + # skip connection logic + + is_first_half = layer <= (self.depth // 2) + is_later_half = not is_first_half + + if is_first_half: + skips.append(x) + + if is_later_half: + skip = skips.pop() + x = torch.cat((x, skip), dim = -1) + x = maybe_skip_proj(x) + + # position generating convolution + + if self.if_audio_conv: + x = speech_conv(x, mask = mask) + x + + # attention and feedforward blocks + + attn_out = attn(attn_norm(x, **norm_kwargs), rotary_pos_emb = rotary_pos_emb, mask = mask) + + x = x + maybe_attn_adaln_zero(attn_out, **norm_kwargs) + + if self.if_cross_attn: + attn_out = attn2(attn_norm2(x, **norm_kwargs), rotary_pos_emb = rotary_pos_emb, mask = mask, context = context, context_mask = context_mask) + + x = x + maybe_attn_adaln_zero2(attn_out, **norm_kwargs) + + ff_out = ff(ff_norm(x, **norm_kwargs)) + + x = x + maybe_ff_adaln_zero(ff_out, **norm_kwargs) + + assert len(skips) == 0 + + _, x = unpack(x, registers_packed_shape, 'b * d') + + return self.final_norm(x) + +# main classes + +class DurationPredictor(Module): + @beartype + def __init__( + self, + transformer: dict | Transformer, + num_channels = None, + mel_spec_kwargs: dict = dict(), + char_embed_kwargs: dict = dict(), + text_num_embeds = None, + tokenizer: ( + Literal['char_utf8', 'phoneme_en'] | + Callable[[list[str]], Int['b nt']] + ) = 'char_utf8' + ): + super().__init__() + + if isinstance(transformer, dict): + transformer = Transformer( + **transformer, + cond_on_time = False + ) + + # mel spec + + self.mel_spec = MelSpec(**mel_spec_kwargs) + self.num_channels = default(num_channels, self.mel_spec.n_mel_channels) + + self.transformer = transformer + + dim = transformer.dim + dim_text = transformer.dim_text + + self.dim = dim + + self.proj_in = Linear(self.num_channels, self.dim) + + # tokenizer and text embed + + if callable(tokenizer): + assert exists(text_num_embeds), '`text_num_embeds` must be given if supplying your own tokenizer encode function' + self.tokenizer = tokenizer + elif tokenizer == 'char_utf8': + text_num_embeds = 256 + self.tokenizer = list_str_to_tensor + elif tokenizer == 'phoneme_en': + self.tokenizer, text_num_embeds = get_g2p_en_encode() + elif tokenizer == 'phoneme_zh': + self.tokenizer, text_num_embeds = get_g2p_zh_encode() + else: + raise ValueError(f'unknown tokenizer string {tokenizer}') + + self.embed_text = CharacterEmbed(dim_text, num_embeds = text_num_embeds, **char_embed_kwargs) + + # to prediction + + self.to_pred = Sequential( + Linear(dim, 1, bias = False), + nn.Softplus(), + Rearrange('... 1 -> ...') + ) + + def forward( + self, + x: Float['b n d'] | Float['b nw'], + *, + text: Int['b nt'] | list[str] | None = None, + lens: Int['b'] | None = None, + return_loss = True + ): + # raw wave + + if x.ndim == 2: + x = self.mel_spec(x) + x = rearrange(x, 'b d n -> b n d') + assert x.shape[-1] == self.dim + + x = self.proj_in(x) + + batch, seq_len, device = *x.shape[:2], x.device + + # text + + text_embed = None + + if exists(text): + if isinstance(text, list): + text = list_str_to_tensor(text).to(device) + assert text.shape[0] == batch + + text_embed = self.embed_text(text, seq_len) + + # handle lengths (duration) + + if not exists(lens): + lens = torch.full((batch,), seq_len, device = device) + + mask = lens_to_mask(lens, length = seq_len) + + # if returning a loss, mask out randomly from an index and have it predict the duration + + if return_loss: + rand_frac_index = x.new_zeros(batch).uniform_(0, 1) + rand_index = (rand_frac_index * lens).long() + + seq = torch.arange(seq_len, device = device) + mask &= einx.less('n, b -> b n', seq, rand_index) + + # attending + + x = self.transformer( + x, + mask = mask, + text_embed = text_embed, + ) + + x = maybe_masked_mean(x, mask) + + pred = self.to_pred(x) + + # return the prediction if not returning loss + + if not return_loss: + return pred + + # loss + + return F.mse_loss(pred, lens.float()) + +class E2TTS(Module): + + @beartype + def __init__( + self, + transformer: dict | Transformer = None, + duration_predictor: dict | DurationPredictor | None = None, + odeint_kwargs: dict = dict( + #atol = 1e-5, + #rtol = 1e-5, + #method = 'midpoint' + method = "euler" + ), + audiocond_drop_prob = 0.30, + cond_drop_prob = 0.20, + prompt_drop_prob = 0.10, + num_channels = None, + mel_spec_module: Module | None = None, + char_embed_kwargs: dict = dict(), + mel_spec_kwargs: dict = dict(), + frac_lengths_mask: tuple[float, float] = (0.7, 1.), + audiocond_snr: tuple[float, float] | None = None, + concat_cond = False, + interpolated_text = False, + text_num_embeds: int | None = None, + tokenizer: ( + Literal['char_utf8', 'phoneme_en', 'phoneme_zh'] | + Callable[[list[str]], Int['b nt']] + ) = 'char_utf8', + use_vocos = True, + pretrained_vocos_path = 'charactr/vocos-mel-24khz', + sampling_rate: int | None = None, + frame_size: int = 320, + velocity_consistency_weight = -1e-5, + + if_cond_proj_in = True, + cond_proj_in_bias = True, + if_embed_text = True, + if_text_encoder2 = True, + if_clip_encoder = False, + video_encoder = "clip_vit" + ): + super().__init__() + + if isinstance(transformer, dict): + transformer = Transformer( + **transformer, + cond_on_time = True + ) + + if isinstance(duration_predictor, dict): + duration_predictor = DurationPredictor(**duration_predictor) + + self.transformer = transformer + + dim = transformer.dim + dim_text = transformer.dim_text + + self.dim = dim + self.dim_text = dim_text + + self.frac_lengths_mask = frac_lengths_mask + self.audiocond_snr = audiocond_snr + + self.duration_predictor = duration_predictor + + # sampling + + self.odeint_kwargs = odeint_kwargs + + # mel spec + + self.mel_spec = default(mel_spec_module, None) + num_channels = default(num_channels, None) + + self.num_channels = num_channels + self.sampling_rate = default(sampling_rate, None) + self.frame_size = frame_size + + # whether to concat condition and project rather than project both and sum + + self.concat_cond = concat_cond + + if concat_cond: + self.proj_in = nn.Linear(num_channels * 2, dim) + else: + self.proj_in = nn.Linear(num_channels, dim) + self.cond_proj_in = nn.Linear(num_channels, dim, bias=cond_proj_in_bias) if if_cond_proj_in else None + + # to prediction + + self.to_pred = Linear(dim, num_channels) + + # tokenizer and text embed + + if callable(tokenizer): + assert exists(text_num_embeds), '`text_num_embeds` must be given if supplying your own tokenizer encode function' + self.tokenizer = tokenizer + elif tokenizer == 'char_utf8': + text_num_embeds = 256 + self.tokenizer = list_str_to_tensor + elif tokenizer == 'phoneme_en': + self.tokenizer, text_num_embeds = get_g2p_en_encode() + elif tokenizer == 'phoneme_zh': + self.tokenizer, text_num_embeds = get_g2p_zh_encode() + else: + raise ValueError(f'unknown tokenizer string {tokenizer}') + + self.audiocond_drop_prob = audiocond_drop_prob + self.cond_drop_prob = cond_drop_prob + self.prompt_drop_prob = prompt_drop_prob + + # text embedding + + text_embed_klass = CharacterEmbed if not interpolated_text else InterpolatedCharacterEmbed + + self.embed_text = text_embed_klass(dim_text, num_embeds = text_num_embeds, **char_embed_kwargs) if if_embed_text else None + + # weight for velocity consistency + + self.register_buffer('zero', torch.tensor(0.), persistent = False) + self.velocity_consistency_weight = velocity_consistency_weight + + # default vocos for mel -> audio + + if pretrained_vocos_path == 'charactr/vocos-mel-24khz': + self.vocos = Vocos.from_pretrained(pretrained_vocos_path) if use_vocos else None + elif pretrained_vocos_path == 'facebook/encodec_24khz': + self.vocos = EncodecWrapper("facebook/encodec_24khz") if use_vocos else None + elif pretrained_vocos_path == 'vae': + self.vocos = VaeWrapper() if use_vocos else None + + if if_text_encoder2: + self.tokenizer2 = AutoTokenizer.from_pretrained("/ailab-train/speech/zhanghaomin/models/flan-t5-large") + self.text_encoder2 = T5EncoderModel.from_pretrained("/ailab-train/speech/zhanghaomin/models/flan-t5-large") + for param in self.text_encoder2.parameters(): + param.requires_grad = False + self.text_encoder2.eval() + + self.proj_text = None + if if_clip_encoder: + if video_encoder == "clip_vit": + ####pass + self.image_processor = CLIPImageProcessor() + #self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/IP-Adapter/", subfolder="models/image_encoder") + self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/IP-Adapter/", subfolder="sdxl_models/image_encoder") + elif video_encoder == "clip_vit2": + self.image_processor = AutoProcessor.from_pretrained("/ailab-train/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + elif video_encoder == "clip_convnext": + self.image_encoder, _, self.image_processor = open_clip.create_model_and_transforms("hf-hub:laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup") + elif video_encoder == "dinov2": + self.image_processor = AutoImageProcessor.from_pretrained("/ailab-train/speech/zhanghaomin/models/dinov2-giant/") + self.image_encoder = AutoModel.from_pretrained("/ailab-train/speech/zhanghaomin/models/dinov2-giant/") + elif video_encoder == "mixed": + pass + #self.image_processor1 = CLIPImageProcessor() + #self.image_encoder1 = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/IP-Adapter/", subfolder="sdxl_models/image_encoder") + #self.image_processor2 = AutoProcessor.from_pretrained("/ailab-train/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + #self.image_encoder2 = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + #self.image_encoder3, _, self.image_processor3 = open_clip.create_model_and_transforms("hf-hub:laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup") + #self.image_processor4 = AutoImageProcessor.from_pretrained("/ailab-train/speech/zhanghaomin/models/dinov2-giant/") + #self.image_encoder4 = AutoModel.from_pretrained("/ailab-train/speech/zhanghaomin/models/dinov2-giant/") + else: + self.image_processor = None + self.image_encoder = None + if video_encoder != "mixed": + for param in self.image_encoder.parameters(): + param.requires_grad = False + self.image_encoder.eval() + if dim_text != 1280: + self.dim_text_raw = 1280 + self.proj_text = Linear(self.dim_text_raw, dim_text) + else: + #for param in self.image_encoder1.parameters(): + # param.requires_grad = False + #self.image_encoder1.eval() + #for param in self.image_encoder2.parameters(): + # param.requires_grad = False + #self.image_encoder2.eval() + #for param in self.image_encoder3.parameters(): + # param.requires_grad = False + #self.image_encoder3.eval() + #for param in self.image_encoder4.parameters(): + # param.requires_grad = False + #self.image_encoder4.eval() + self.dim_text_raw = 4608 + self.proj_text = Linear(self.dim_text_raw, dim_text) + self.video_encoder = video_encoder + + for param in self.vocos.parameters(): + param.requires_grad = False + self.vocos.eval() + + @property + def device(self): + return next(self.parameters()).device + + def encode_text(self, prompt): + device = self.device + batch = self.tokenizer2(prompt, max_length=self.tokenizer2.model_max_length, padding=True, truncation=True, return_tensors="pt") + input_ids, attention_mask = batch.input_ids.to(device), batch.attention_mask.to(device) + + with torch.no_grad(): + encoder_hidden_states = self.text_encoder2(input_ids=input_ids, attention_mask=attention_mask)[0] + + boolean_encoder_mask = (attention_mask == 1).to(device) + return encoder_hidden_states, boolean_encoder_mask + + def encode_video(self, video_paths, l): + if self.proj_text is None: + d = self.dim_text + else: + d = self.dim_text_raw + device = self.device + b = 20 + with torch.no_grad(): + video_embeddings = [] + video_lens = [] + for video_path in video_paths: + if video_path is None: + video_embeddings.append(None) + video_lens.append(0) + continue + if isinstance(video_path, tuple): + video_path, start_sample, max_sample = video_path + else: + start_sample = 0 + max_sample = None + if video_path.startswith("/ailab-train/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = video_path.replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = video_path.replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = video_path.replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = video_path.replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = video_path.replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = video_path.replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = video_path.replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = video_path.replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = video_path.replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = video_path.replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + + if not os.path.exists(feature_path): + #print("video not exist", video_path) + frames, duration, fps = read_frames_with_moviepy(video_path, max_frame_nums=None) + if frames is None: + video_embeddings.append(None) + video_lens.append(0) + continue + ####low fps#### + ##frames = frames[0::3,...] + #ds = max(round(fps/8.0), 1) + #print("fps", fps, duration, frames.shape, ds) + #frames = frames[0::ds,...] + ####low fps#### + if self.video_encoder in ["clip_vit", "clip_vit2", "dinov2"]: + images = self.image_processor(images=frames, return_tensors="pt").to(device) + #print("images", images["pixel_values"].shape, images["pixel_values"].max(), images["pixel_values"].min(), torch.abs(images["pixel_values"]).mean()) + elif self.video_encoder in ["clip_convnext"]: + images = [] + for i in range(frames.shape[0]): + images.append(self.image_processor(Image.fromarray(frames[i])).unsqueeze(0)) + images = torch.cat(images, dim=0).to(device) + #print("images", images.shape, images.max(), images.min(), torch.abs(images).mean()) + elif self.video_encoder in ["mixed"]: + #images1 = self.image_processor1(images=frames, return_tensors="pt").to(device) + images2 = self.image_processor2(images=frames, return_tensors="pt").to(device) + images4 = self.image_processor4(images=frames, return_tensors="pt").to(device) + images3 = [] + for i in range(frames.shape[0]): + images3.append(self.image_processor3(Image.fromarray(frames[i])).unsqueeze(0)) + images3 = torch.cat(images3, dim=0).to(device) + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + image_embeddings = [] + if self.video_encoder == "clip_vit": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + elif self.video_encoder == "clip_vit2": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + elif self.video_encoder == "clip_convnext": + for i in range(math.ceil(images.shape[0] / b)): + image_embeddings.append(self.image_encoder.encode_image(images[i*b: (i+1)*b]).cpu()) + elif self.video_encoder == "dinov2": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).pooler_output.cpu()) + elif self.video_encoder == "mixed": + feature_path1 = feature_path.replace("/feature_mixed/", "/feature/") + if not os.path.exists(feature_path1): + image_embeddings1 = [] + for i in range(math.ceil(images1["pixel_values"].shape[0] / b)): + image_embeddings1.append(self.image_encoder1(pixel_values=images1["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + image_embeddings1 = torch.cat(image_embeddings1, dim=0) + #np.savez(feature_path1, image_embeddings1, duration) + else: + data1 = np.load(feature_path1) + image_embeddings1 = torch.from_numpy(data1["arr_0"]) + feature_path2 = feature_path.replace("/feature_mixed/", "/feature_clip_vit2/") + if not os.path.exists(feature_path2): + image_embeddings2 = [] + for i in range(math.ceil(images2["pixel_values"].shape[0] / b)): + image_embeddings2.append(self.image_encoder2(pixel_values=images2["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + image_embeddings2 = torch.cat(image_embeddings2, dim=0) + np.savez(feature_path2, image_embeddings2, duration) + else: + data2 = np.load(feature_path2) + image_embeddings2 = torch.from_numpy(data2["arr_0"]) + feature_path3 = feature_path.replace("/feature_mixed/", "/feature_clip_convnext/") + if not os.path.exists(feature_path3): + image_embeddings3 = [] + for i in range(math.ceil(images3.shape[0] / b)): + image_embeddings3.append(self.image_encoder3.encode_image(images3[i*b: (i+1)*b]).cpu()) + image_embeddings3 = torch.cat(image_embeddings3, dim=0) + np.savez(feature_path3, image_embeddings3, duration) + else: + data3 = np.load(feature_path3) + image_embeddings3 = torch.from_numpy(data3["arr_0"]) + feature_path4 = feature_path.replace("/feature_mixed/", "/feature_dinov2/") + if not os.path.exists(feature_path4): + image_embeddings4 = [] + for i in range(math.ceil(images4["pixel_values"].shape[0] / b)): + image_embeddings4.append(self.image_encoder4(pixel_values=images4["pixel_values"][i*b: (i+1)*b]).pooler_output.cpu()) + image_embeddings4 = torch.cat(image_embeddings4, dim=0) + np.savez(feature_path4, image_embeddings4, duration) + else: + data4 = np.load(feature_path4) + image_embeddings4 = torch.from_numpy(data4["arr_0"]) + mixed_l = min([image_embeddings1.shape[0], image_embeddings2.shape[0], image_embeddings3.shape[0], image_embeddings4.shape[0]]) + for i in range(mixed_l): + image_embeddings.append(torch.cat([image_embeddings1[i:i+1,:], image_embeddings2[i:i+1,:], image_embeddings3[i:i+1,:], image_embeddings4[i:i+1,:]], dim=1)) + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + image_embeddings = torch.cat(image_embeddings, dim=0) + #print("image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + ####low fps#### + #np.savez(feature_path, image_embeddings, duration) + np.savez(feature_path, image_embeddings, duration, fps) + ####low fps#### + else: + #print("video exist", feature_path) + data = np.load(feature_path) + image_embeddings = torch.from_numpy(data["arr_0"]) + #print("image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + duration = data["arr_1"].item() + ####low fps#### + if "arr_2" not in data: + fps = float(image_embeddings.shape[0]) / duration + ##image_embeddings = image_embeddings[0::3,...] + #ds = max(round(fps/8.0), 1) + ##print("fps", fps, duration, image_embeddings.shape, ds) + #image_embeddings = image_embeddings[0::ds,...] + else: + fps = data["arr_2"].item() + ####low fps#### + if max_sample is None: + max_sample = int(duration * self.sampling_rate) + interpolated = [] + for i in range(start_sample, max_sample, self.frame_size): + j = min(round((i+self.frame_size//2) / self.sampling_rate / (duration / (image_embeddings.shape[0] - 1))), image_embeddings.shape[0] - 1) + interpolated.append(image_embeddings[j:j+1]) + if len(interpolated) >= l: + break + interpolated = torch.cat(interpolated, dim=0) + #ll = list(range(start_sample, max_sample, self.frame_size)) + #print("encode_video l", len(ll), l, round((ll[-1]+self.frame_size//2) / self.sampling_rate / (duration / (image_embeddings.shape[0] - 1))), image_embeddings.shape[0] - 1) + #print("encode_video one", video_path, duration, image_embeddings.shape, interpolated.shape, l) + video_embeddings.append(interpolated.unsqueeze(0)) + video_lens.append(interpolated.shape[1]) + max_length = max(video_lens) + if max_length == 0: + max_length = l + else: + max_length = l + for i in range(len(video_embeddings)): + if video_embeddings[i] is None: + video_embeddings[i] = torch.zeros(1, max_length, d) + continue + if video_embeddings[i].shape[1] < max_length: + video_embeddings[i] = torch.cat([video_embeddings[i], torch.zeros(1, max_length-video_embeddings[i].shape[1], d)], 1) + video_embeddings = torch.cat(video_embeddings, 0) + #print("encode_video", l, video_embeddings.shape, video_lens) + return video_embeddings.to(device) + + def transformer_with_pred_head( + self, + x: Float['b n d'], + cond: Float['b n d'] | None = None, + times: Float['b'] | None = None, + mask: Bool['b n'] | None = None, + text: Int['b nt'] | Float['b nt dt'] | None = None, + prompt = None, + video_drop_prompt = None, + audio_drop_prompt = None, + drop_audio_cond: bool | None = None, + drop_text_cond: bool | None = None, + drop_text_prompt: bool | None = None, + return_drop_conditions = False + ): + seq_len = x.shape[-2] + bs = x.shape[0] + drop_audio_cond = [default(drop_audio_cond, self.training and random() < self.audiocond_drop_prob) for _ in range(bs)] + drop_text_cond = default(drop_text_cond, self.training and random() < self.cond_drop_prob) + drop_text_prompt = [default(drop_text_prompt, self.training and random() < self.prompt_drop_prob) for _ in range(bs)] + + if cond is not None: + for b in range(bs): + if drop_audio_cond[b]: + cond[b] = 0 + if audio_drop_prompt is not None and audio_drop_prompt[b]: + cond[b] = 0 + + if cond is not None: + if self.concat_cond: + # concat condition, given as using voicebox-like scheme + x = torch.cat((cond, x), dim = -1) + + x = self.proj_in(x) + + if cond is not None: + if not self.concat_cond: + # an alternative is to simply sum the condition + # seems to work fine + + cond = self.cond_proj_in(cond) + x = x + cond + + # whether to use a text embedding + + text_embed = None + if exists(text) and len(text.shape) == 3: + text_embed = text.clone() + if drop_text_cond: + for b in range(bs): + text_embed[b] = 0 + elif exists(text) and not drop_text_cond: + text_embed = self.embed_text(text, seq_len, mask = mask) + + context, context_mask = None, None + if prompt is not None: + #for b in range(bs): + # if drop_text_prompt[b]: + # prompt[b] = "" + if video_drop_prompt is not None: + for b in range(bs): + if video_drop_prompt[b]: + prompt[b] = "the sound of X X" + context, context_mask = self.encode_text(prompt) + for b in range(bs): + if drop_text_prompt[b]: + context[b] = 0 + if video_drop_prompt is not None and video_drop_prompt[b]: + context[b] = 0 + #print("cross attention", context.shape, context_mask.shape, x.shape, mask.shape, text_embed.shape if text_embed is not None else None, torch.mean(torch.abs(text_embed), dim=(1,2))) + #print("video_drop_prompt", prompt, video_drop_prompt, context.shape, torch.mean(torch.abs(context), dim=(1,2))) + #print("audio_drop_prompt", audio_drop_prompt, cond.shape, torch.mean(torch.abs(cond), dim=(1,2))) + + if self.proj_text is not None: + text_embed = self.proj_text(text_embed) + + # attend + + attended = self.transformer( + x, + times = times, + mask = mask, + text_embed = text_embed, + context = context, + context_mask = context_mask + ) + + pred = self.to_pred(attended) + + if not return_drop_conditions: + return pred + + return pred, drop_audio_cond, drop_text_cond, drop_text_prompt + + def cfg_transformer_with_pred_head( + self, + *args, + cfg_strength: float = 1., + remove_parallel_component: bool = True, + keep_parallel_frac: float = 0., + **kwargs, + ): + + pred = self.transformer_with_pred_head(*args, drop_audio_cond = False, drop_text_cond = False, drop_text_prompt = False, **kwargs) + + if cfg_strength < 1e-5: + return pred + + null_pred = self.transformer_with_pred_head(*args, drop_audio_cond = True, drop_text_cond = True, drop_text_prompt = True, **kwargs) + + cfg_update = pred - null_pred + + if remove_parallel_component: + # https://arxiv.org/abs/2410.02416 + parallel, orthogonal = project(cfg_update, pred) + cfg_update = orthogonal + parallel * keep_parallel_frac + + return pred + cfg_update * cfg_strength + + def add_noise(self, signal, mask, val): + if self.audiocond_snr is None: + return signal + if not val: + snr = np.random.uniform(self.audiocond_snr[0], self.audiocond_snr[1]) + else: + snr = (self.audiocond_snr[0] + self.audiocond_snr[1]) / 2.0 + #print("add_noise", self.audiocond_snr, snr, signal.shape, mask) # [True, ..., False] + noise = torch.randn_like(signal) + w = torch.abs(signal[mask]).mean() / (torch.abs(noise[mask]).mean() + 1e-6) / snr + return signal + noise * w + + @torch.no_grad() + def sample( + self, + cond: Float['b n d'] | Float['b nw'] | None = None, + *, + text: Int['b nt'] | list[str] | None = None, + lens: Int['b'] | None = None, + duration: int | Int['b'] | None = None, + steps = 32, + cfg_strength = 1., # they used a classifier free guidance strength of 1. + remove_parallel_component = True, + sway_sampling = True, + max_duration = 4096, # in case the duration predictor goes haywire + vocoder: Callable[[Float['b d n']], list[Float['_']]] | None = None, + return_raw_output: bool | None = None, + save_to_filename: str | None = None, + prompt = None, + video_drop_prompt = None, + audio_drop_prompt = None, + video_paths = None + ) -> ( + Float['b n d'], + list[Float['_']] + ): + self.eval() + + # raw wave + + if cond.ndim == 2: + cond = self.mel_spec(cond) + cond = rearrange(cond, 'b d n -> b n d') + assert cond.shape[-1] == self.num_channels + + batch, cond_seq_len, device = *cond.shape[:2], cond.device + + if not exists(lens): + lens = torch.full((batch,), cond_seq_len, device = device, dtype = torch.long) + + if video_paths is not None: + if len(video_paths) == batch: + text = self.encode_video(video_paths, cond_seq_len) + else: + text = self.encode_video(video_paths, cond_seq_len*batch) + print("clip frames", text.shape, cond.shape) + text = text.reshape(batch, -1, text.shape[-1]) + # text + elif isinstance(text, list): + text = self.tokenizer(text).to(device) + assert text.shape[0] == batch + + if exists(text): + text_lens = (text != -1).sum(dim = -1) + lens = torch.maximum(text_lens, lens) # make sure lengths are at least those of the text characters + + # duration + + cond_mask = lens_to_mask(lens) + + if exists(duration): + if isinstance(duration, int): + duration = torch.full((batch,), duration, device = device, dtype = torch.long) + + elif exists(self.duration_predictor): + duration = self.duration_predictor(cond, text = text, lens = lens, return_loss = False).long() + + duration = torch.maximum(lens, duration) # just add one token so something is generated + duration = duration.clamp(max = max_duration) + + assert duration.shape[0] == batch + + max_duration = duration.amax() + + cond = F.pad(cond, (0, 0, 0, max_duration - cond_seq_len), value = 0.) + cond_mask = F.pad(cond_mask, (0, max_duration - cond_mask.shape[-1]), value = False) + cond_mask = rearrange(cond_mask, '... -> ... 1') + + mask = lens_to_mask(duration) + #print("####", duration, mask, mask.shape, lens, cond_mask, cond_mask.shape, text) + + # neural ode + + def fn(t, x): + # at each step, conditioning is fixed + + if lens[0] == duration[0]: + print("No cond", lens, duration) + step_cond = None + else: + step_cond = torch.where(cond_mask, self.add_noise(cond, cond_mask, True), torch.zeros_like(cond)) + + # predict flow + + return self.cfg_transformer_with_pred_head( + x, + step_cond, + times = t, + text = text, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + cfg_strength = cfg_strength, + remove_parallel_component = remove_parallel_component + ) + + ####torch.manual_seed(0) + y0 = torch.randn_like(cond) + t = torch.linspace(0, 1, steps, device = self.device) + if sway_sampling: + t = t + -1.0 * (torch.cos(torch.pi / 2 * t) - 1 + t) + #print("@@@@", t) + + trajectory = odeint(fn, y0, t, **self.odeint_kwargs) + sampled = trajectory[-1] + + out = sampled + + if lens[0] != duration[0]: + out = torch.where(cond_mask, cond, out) + + # able to return raw untransformed output, if not using mel rep + + if exists(return_raw_output) and return_raw_output: + return out + + # take care of transforming mel to audio if `vocoder` is passed in, or if `use_vocos` is turned on + + if exists(vocoder): + assert not exists(self.vocos), '`use_vocos` should not be turned on if you are passing in a custom `vocoder` on sampling' + out = rearrange(out, 'b n d -> b d n') + out = vocoder(out) + + elif exists(self.vocos): + + audio = [] + for mel, one_mask in zip(out, mask): + #one_out = DB_to_amplitude(mel[one_mask], ref = 1., power = 0.5) + one_out = mel[one_mask] + + one_out = rearrange(one_out, 'n d -> 1 d n') + one_audio = self.vocos.decode(one_out) + one_audio = rearrange(one_audio, '1 nw -> nw') + audio.append(one_audio) + + out = audio + + if exists(save_to_filename): + assert exists(vocoder) or exists(self.vocos) + assert exists(self.sampling_rate) + + path = Path(save_to_filename) + parent_path = path.parents[0] + parent_path.mkdir(exist_ok = True, parents = True) + + for ind, one_audio in enumerate(out): + one_audio = rearrange(one_audio, 'nw -> 1 nw') + if len(out) == 1: + save_path = str(parent_path / f'{path.name}') + else: + save_path = str(parent_path / f'{ind + 1}.{path.name}') + torchaudio.save(save_path, one_audio.detach().cpu(), sample_rate = self.sampling_rate) + + return out + + def forward( + self, + inp: Float['b n d'] | Float['b nw'], # mel or raw wave + *, + text: Int['b nt'] | list[str] | None = None, + times: int | Int['b'] | None = None, + lens: Int['b'] | None = None, + velocity_consistency_model: E2TTS | None = None, + velocity_consistency_delta = 1e-3, + prompt = None, + video_drop_prompt=None, + audio_drop_prompt=None, + val = False, + video_paths=None + ): + need_velocity_loss = exists(velocity_consistency_model) and self.velocity_consistency_weight > 0. + + # handle raw wave + + if inp.ndim == 2: + inp = self.mel_spec(inp) + inp = rearrange(inp, 'b d n -> b n d') + assert inp.shape[-1] == self.num_channels + + batch, seq_len, dtype, device = *inp.shape[:2], inp.dtype, self.device + + if video_paths is not None: + text = self.encode_video(video_paths, seq_len) + # handle text as string + elif isinstance(text, list): + text = self.tokenizer(text).to(device) + #print("text tokenized", text[0]) + assert text.shape[0] == batch + + # lens and mask + + if not exists(lens): + lens = torch.full((batch,), seq_len, device = device) + + mask = lens_to_mask(lens, length = seq_len) + + # get a random span to mask out for training conditionally + + if not val: + if self.audiocond_drop_prob > 1.0: + frac_lengths = torch.zeros((batch,), device = self.device).float().uniform_(1.0,1.0) + else: + frac_lengths = torch.zeros((batch,), device = self.device).float().uniform_(*self.frac_lengths_mask) + else: + frac_lengths = torch.tensor([(0.7+1.0)/2.0]*batch, device = self.device).float() + rand_span_mask = mask_from_frac_lengths(lens, frac_lengths, max_length = seq_len, val = val) + + if exists(mask): + rand_span_mask &= mask + + # mel is x1 + + x1 = inp + + # main conditional flow training logic + # just ~5 loc + + # x0 is gaussian noise + + if val: + torch.manual_seed(0) + x0 = torch.randn_like(x1) + if val: + torch.manual_seed(int(time.time()*1000)) + + # t is random times from above + + if times is None: + times = torch.rand((batch,), dtype = dtype, device = self.device) + else: + times = torch.tensor((times,)*batch, dtype = dtype, device = self.device) + t = rearrange(times, 'b -> b 1 1') + + # if need velocity consistency, make sure time does not exceed 1. + + if need_velocity_loss: + t = t * (1. - velocity_consistency_delta) + + # sample xt (w in the paper) + + w = (1. - t) * x0 + t * x1 + + flow = x1 - x0 + + # only predict what is within the random mask span for infilling + + if self.audiocond_drop_prob > 1.0: + cond = None + else: + cond = einx.where( + 'b n, b n d, b n d -> b n d', + rand_span_mask, + torch.zeros_like(x1), self.add_noise(x1, ~rand_span_mask, val) + ) + + # transformer and prediction head + + if not val: + pred, did_drop_audio_cond, did_drop_text_cond, did_drop_text_prompt = self.transformer_with_pred_head( + w, + cond, + times = times, + text = text, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + return_drop_conditions = True + ) + else: + pred, did_drop_audio_cond, did_drop_text_cond, did_drop_text_prompt = self.transformer_with_pred_head( + w, + cond, + times = times, + text = text, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + drop_audio_cond = False, + drop_text_cond = False, + drop_text_prompt = False, + return_drop_conditions = True + ) + + # maybe velocity consistency loss + + velocity_loss = self.zero + + if need_velocity_loss: + + t_with_delta = t + velocity_consistency_delta + w_with_delta = (1. - t_with_delta) * x0 + t_with_delta * x1 + + with torch.no_grad(): + ema_pred = velocity_consistency_model.transformer_with_pred_head( + w_with_delta, + cond, + times = times + velocity_consistency_delta, + text = text, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + drop_audio_cond = did_drop_audio_cond, + drop_text_cond = did_drop_text_cond, + drop_text_prompt = did_drop_text_prompt + ) + + velocity_loss = F.mse_loss(pred, ema_pred, reduction = 'none') + velocity_loss = velocity_loss[rand_span_mask].mean() + + # flow matching loss + + loss = F.mse_loss(pred, flow, reduction = 'none') + + #print("loss", loss.shape, loss, "rand_span_mask", rand_span_mask.shape, rand_span_mask, "loss[rand_span_mask]", loss[rand_span_mask].shape, loss[rand_span_mask]) + loss = loss[rand_span_mask].mean() + + # total loss and get breakdown + + total_loss = loss + velocity_loss * self.velocity_consistency_weight + breakdown = LossBreakdown(loss, velocity_loss) + #print("loss", loss, velocity_loss, self.velocity_consistency_weight) + + # return total loss and bunch of intermediates + + return E2TTSReturn(total_loss, cond if cond is not None else w, pred, x0 + pred, breakdown) diff --git a/src/e2_tts_pytorch/e2_tts_crossatt3.py b/src/e2_tts_pytorch/e2_tts_crossatt3.py new file mode 100644 index 0000000000000000000000000000000000000000..86c306073a3ea1ecf6434411b414c41240c5a29c --- /dev/null +++ b/src/e2_tts_pytorch/e2_tts_crossatt3.py @@ -0,0 +1,2584 @@ +""" +ein notation: +b - batch +n - sequence +nt - text sequence +nw - raw wave length +d - dimension +dt - dimension text +""" + +from __future__ import annotations + +from pathlib import Path +from random import random +from functools import partial +from itertools import zip_longest +from collections import namedtuple + +from typing import Literal, Callable + +import jaxtyping +from beartype import beartype + +import torch +import torch.nn.functional as F +from torch import nn, tensor, Tensor, from_numpy +from torch.nn import Module, ModuleList, Sequential, Linear +from torch.nn.utils.rnn import pad_sequence + +import torchaudio +from torchaudio.functional import DB_to_amplitude +from torchdiffeq import odeint + +import einx +from einops.layers.torch import Rearrange +from einops import rearrange, repeat, reduce, pack, unpack + +from x_transformers import ( + Attention, + FeedForward, + RMSNorm, + AdaptiveRMSNorm, +) + +from x_transformers.x_transformers import RotaryEmbedding + +import sys +sys.path.insert(0, "/zhanghaomin/codes3/vocos-main/") +from vocos import Vocos + +from transformers import AutoTokenizer +from transformers import T5EncoderModel +from transformers import EncodecModel, AutoProcessor + +sys.path.insert(0, "./src/audeo/") +import Video2RollNet +import torchvision.transforms as transforms + + +transform = transforms.Compose([lambda x: x.resize((900,100)), + lambda x: np.reshape(x,(100,900,1)), + lambda x: np.transpose(x,[2,0,1]), + lambda x: x/255.]) + +####transform = transforms.Compose([lambda x: x.resize((100,900)), +#### lambda x: np.reshape(x,(900,100,1)), +#### lambda x: np.transpose(x,[2,1,0]), +#### lambda x: x/255.]) + +NOTES = 51 +NOTTE_MIN = 15 +NOTE_MAX = 65 + +####NOTES = 88 +####NOTTE_MIN = 0#15 +####NOTE_MAX = 87#72 + + +import os +import math +import traceback +import numpy as np +from moviepy.editor import AudioFileClip, VideoFileClip +from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection +#import open_clip +from transformers import AutoImageProcessor, AutoModel +from PIL import Image +import time + +import warnings +warnings.filterwarnings("ignore") + +def normalize_wav(waveform): + waveform = waveform - torch.mean(waveform) + waveform = waveform / (torch.max(torch.abs(waveform[0, :])) + 1e-8) + return waveform * 0.5 + +def read_frames_with_moviepy(video_path, max_frame_nums=None): + try: + clip = VideoFileClip(video_path) + duration = clip.duration + frames = [] + for frame in clip.iter_frames(): + frames.append(frame) + except: + print("Error read_frames_with_moviepy", video_path) + traceback.print_exc() + return None, None + if max_frame_nums is not None: + frames_idx = np.linspace(0, len(frames) - 1, max_frame_nums, dtype=int) + return np.array(frames)[frames_idx, ...], duration + else: + return np.array(frames), duration + +pad_sequence = partial(pad_sequence, batch_first = True) + +# constants + +class TorchTyping: + def __init__(self, abstract_dtype): + self.abstract_dtype = abstract_dtype + + def __getitem__(self, shapes: str): + return self.abstract_dtype[Tensor, shapes] + +Float = TorchTyping(jaxtyping.Float) +Int = TorchTyping(jaxtyping.Int) +Bool = TorchTyping(jaxtyping.Bool) + +# named tuples + +LossBreakdown = namedtuple('LossBreakdown', ['flow', 'velocity_consistency', 'a', 'b']) + +E2TTSReturn = namedtuple('E2TTS', ['loss', 'cond', 'pred_flow', 'pred_data', 'loss_breakdown']) + +# helpers + +def exists(v): + return v is not None + +def default(v, d): + return v if exists(v) else d + +def divisible_by(num, den): + return (num % den) == 0 + +def pack_one_with_inverse(x, pattern): + packed, packed_shape = pack([x], pattern) + + def inverse(x, inverse_pattern = None): + inverse_pattern = default(inverse_pattern, pattern) + return unpack(x, packed_shape, inverse_pattern)[0] + + return packed, inverse + +class Identity(Module): + def forward(self, x, **kwargs): + return x + +# tensor helpers + +def project(x, y): + x, inverse = pack_one_with_inverse(x, 'b *') + y, _ = pack_one_with_inverse(y, 'b *') + + dtype = x.dtype + x, y = x.double(), y.double() + unit = F.normalize(y, dim = -1) + + parallel = (x * unit).sum(dim = -1, keepdim = True) * unit + orthogonal = x - parallel + + return inverse(parallel).to(dtype), inverse(orthogonal).to(dtype) + +# simple utf-8 tokenizer, since paper went character based + +def list_str_to_tensor( + text: list[str], + padding_value = -1 +) -> Int['b nt']: + + list_tensors = [tensor([*bytes(t, 'UTF-8')]) for t in text] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + +# simple english phoneme-based tokenizer + +from g2p_en import G2p +import jieba +from pypinyin import lazy_pinyin, Style + +def get_g2p_en_encode(): + g2p = G2p() + + # used by @lucasnewman successfully here + # https://github.com/lucasnewman/e2-tts-pytorch/blob/ljspeech-test/e2_tts_pytorch/e2_tts.py + + phoneme_to_index = g2p.p2idx + num_phonemes = len(phoneme_to_index) + + extended_chars = [' ', ',', '.', '-', '!', '?', '\'', '"', '...', '..', '. .', '. . .', '. . . .', '. . . . .', '. ...', '... .', '.. ..'] + num_extended_chars = len(extended_chars) + + extended_chars_dict = {p: (num_phonemes + i) for i, p in enumerate(extended_chars)} + phoneme_to_index = {**phoneme_to_index, **extended_chars_dict} + + def encode( + text: list[str], + padding_value = -1 + ) -> Int['b nt']: + + phonemes = [g2p(t) for t in text] + list_tensors = [tensor([phoneme_to_index[p] for p in one_phoneme]) for one_phoneme in phonemes] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + + return encode, (num_phonemes + num_extended_chars) + +def all_en(word): + res = word.replace("'", "").encode('utf-8').isalpha() + return res + +def all_ch(word): + res = True + for w in word: + if not '\u4e00' <= w <= '\u9fff': + res = False + return res + +def get_g2p_zh_encode(): + puncs = ['，', '。', '？', '、'] + pinyins = ['a', 'a1', 'ai1', 'ai2', 'ai3', 'ai4', 'an1', 'an3', 'an4', 'ang1', 'ang2', 'ang4', 'ao1', 'ao2', 'ao3', 'ao4', 'ba', 'ba1', 'ba2', 'ba3', 'ba4', 'bai1', 'bai2', 'bai3', 'bai4', 'ban1', 'ban2', 'ban3', 'ban4', 'bang1', 'bang2', 'bang3', 'bang4', 'bao1', 'bao2', 'bao3', 'bao4', 'bei', 'bei1', 'bei2', 'bei3', 'bei4', 'ben1', 'ben2', 'ben3', 'ben4', 'beng1', 'beng2', 'beng4', 'bi1', 'bi2', 'bi3', 'bi4', 'bian1', 'bian2', 'bian3', 'bian4', 'biao1', 'biao2', 'biao3', 'bie1', 'bie2', 'bie3', 'bie4', 'bin1', 'bin4', 'bing1', 'bing2', 'bing3', 'bing4', 'bo', 'bo1', 'bo2', 'bo3', 'bo4', 'bu2', 'bu3', 'bu4', 'ca1', 'cai1', 'cai2', 'cai3', 'cai4', 'can1', 'can2', 'can3', 'can4', 'cang1', 'cang2', 'cao1', 'cao2', 'cao3', 'ce4', 'cen1', 'cen2', 'ceng1', 'ceng2', 'ceng4', 'cha1', 'cha2', 'cha3', 'cha4', 'chai1', 'chai2', 'chan1', 'chan2', 'chan3', 'chan4', 'chang1', 'chang2', 'chang3', 'chang4', 'chao1', 'chao2', 'chao3', 'che1', 'che2', 'che3', 'che4', 'chen1', 'chen2', 'chen3', 'chen4', 'cheng1', 'cheng2', 'cheng3', 'cheng4', 'chi1', 'chi2', 'chi3', 'chi4', 'chong1', 'chong2', 'chong3', 'chong4', 'chou1', 'chou2', 'chou3', 'chou4', 'chu1', 'chu2', 'chu3', 'chu4', 'chua1', 'chuai1', 'chuai2', 'chuai3', 'chuai4', 'chuan1', 'chuan2', 'chuan3', 'chuan4', 'chuang1', 'chuang2', 'chuang3', 'chuang4', 'chui1', 'chui2', 'chun1', 'chun2', 'chun3', 'chuo1', 'chuo4', 'ci1', 'ci2', 'ci3', 'ci4', 'cong1', 'cong2', 'cou4', 'cu1', 'cu4', 'cuan1', 'cuan2', 'cuan4', 'cui1', 'cui3', 'cui4', 'cun1', 'cun2', 'cun4', 'cuo1', 'cuo2', 'cuo4', 'da', 'da1', 'da2', 'da3', 'da4', 'dai1', 'dai3', 'dai4', 'dan1', 'dan2', 'dan3', 'dan4', 'dang1', 'dang2', 'dang3', 'dang4', 'dao1', 'dao2', 'dao3', 'dao4', 'de', 'de1', 'de2', 'dei3', 'den4', 'deng1', 'deng2', 'deng3', 'deng4', 'di1', 'di2', 'di3', 'di4', 'dia3', 'dian1', 'dian2', 'dian3', 'dian4', 'diao1', 'diao3', 'diao4', 'die1', 'die2', 'ding1', 'ding2', 'ding3', 'ding4', 'diu1', 'dong1', 'dong3', 'dong4', 'dou1', 'dou2', 'dou3', 'dou4', 'du1', 'du2', 'du3', 'du4', 'duan1', 'duan2', 'duan3', 'duan4', 'dui1', 'dui4', 'dun1', 'dun3', 'dun4', 'duo1', 'duo2', 'duo3', 'duo4', 'e1', 'e2', 'e3', 'e4', 'ei2', 'en1', 'en4', 'er', 'er2', 'er3', 'er4', 'fa1', 'fa2', 'fa3', 'fa4', 'fan1', 'fan2', 'fan3', 'fan4', 'fang1', 'fang2', 'fang3', 'fang4', 'fei1', 'fei2', 'fei3', 'fei4', 'fen1', 'fen2', 'fen3', 'fen4', 'feng1', 'feng2', 'feng3', 'feng4', 'fo2', 'fou2', 'fou3', 'fu1', 'fu2', 'fu3', 'fu4', 'ga1', 'ga2', 'ga4', 'gai1', 'gai3', 'gai4', 'gan1', 'gan2', 'gan3', 'gan4', 'gang1', 'gang2', 'gang3', 'gang4', 'gao1', 'gao2', 'gao3', 'gao4', 'ge1', 'ge2', 'ge3', 'ge4', 'gei2', 'gei3', 'gen1', 'gen2', 'gen3', 'gen4', 'geng1', 'geng3', 'geng4', 'gong1', 'gong3', 'gong4', 'gou1', 'gou2', 'gou3', 'gou4', 'gu', 'gu1', 'gu2', 'gu3', 'gu4', 'gua1', 'gua2', 'gua3', 'gua4', 'guai1', 'guai2', 'guai3', 'guai4', 'guan1', 'guan2', 'guan3', 'guan4', 'guang1', 'guang2', 'guang3', 'guang4', 'gui1', 'gui2', 'gui3', 'gui4', 'gun3', 'gun4', 'guo1', 'guo2', 'guo3', 'guo4', 'ha1', 'ha2', 'ha3', 'hai1', 'hai2', 'hai3', 'hai4', 'han1', 'han2', 'han3', 'han4', 'hang1', 'hang2', 'hang4', 'hao1', 'hao2', 'hao3', 'hao4', 'he1', 'he2', 'he4', 'hei1', 'hen2', 'hen3', 'hen4', 'heng1', 'heng2', 'heng4', 'hong1', 'hong2', 'hong3', 'hong4', 'hou1', 'hou2', 'hou3', 'hou4', 'hu1', 'hu2', 'hu3', 'hu4', 'hua1', 'hua2', 'hua4', 'huai2', 'huai4', 'huan1', 'huan2', 'huan3', 'huan4', 'huang1', 'huang2', 'huang3', 'huang4', 'hui1', 'hui2', 'hui3', 'hui4', 'hun1', 'hun2', 'hun4', 'huo', 'huo1', 'huo2', 'huo3', 'huo4', 'ji1', 'ji2', 'ji3', 'ji4', 'jia', 'jia1', 'jia2', 'jia3', 'jia4', 'jian1', 'jian2', 'jian3', 'jian4', 'jiang1', 'jiang2', 'jiang3', 'jiang4', 'jiao1', 'jiao2', 'jiao3', 'jiao4', 'jie1', 'jie2', 'jie3', 'jie4', 'jin1', 'jin2', 'jin3', 'jin4', 'jing1', 'jing2', 'jing3', 'jing4', 'jiong3', 'jiu1', 'jiu2', 'jiu3', 'jiu4', 'ju1', 'ju2', 'ju3', 'ju4', 'juan1', 'juan2', 'juan3', 'juan4', 'jue1', 'jue2', 'jue4', 'jun1', 'jun4', 'ka1', 'ka2', 'ka3', 'kai1', 'kai2', 'kai3', 'kai4', 'kan1', 'kan2', 'kan3', 'kan4', 'kang1', 'kang2', 'kang4', 'kao2', 'kao3', 'kao4', 'ke1', 'ke2', 'ke3', 'ke4', 'ken3', 'keng1', 'kong1', 'kong3', 'kong4', 'kou1', 'kou2', 'kou3', 'kou4', 'ku1', 'ku2', 'ku3', 'ku4', 'kua1', 'kua3', 'kua4', 'kuai3', 'kuai4', 'kuan1', 'kuan2', 'kuan3', 'kuang1', 'kuang2', 'kuang4', 'kui1', 'kui2', 'kui3', 'kui4', 'kun1', 'kun3', 'kun4', 'kuo4', 'la', 'la1', 'la2', 'la3', 'la4', 'lai2', 'lai4', 'lan2', 'lan3', 'lan4', 'lang1', 'lang2', 'lang3', 'lang4', 'lao1', 'lao2', 'lao3', 'lao4', 'le', 'le1', 'le4', 'lei', 'lei1', 'lei2', 'lei3', 'lei4', 'leng1', 'leng2', 'leng3', 'leng4', 'li', 'li1', 'li2', 'li3', 'li4', 'lia3', 'lian2', 'lian3', 'lian4', 'liang2', 'liang3', 'liang4', 'liao1', 'liao2', 'liao3', 'liao4', 'lie1', 'lie2', 'lie3', 'lie4', 'lin1', 'lin2', 'lin3', 'lin4', 'ling2', 'ling3', 'ling4', 'liu1', 'liu2', 'liu3', 'liu4', 'long1', 'long2', 'long3', 'long4', 'lou1', 'lou2', 'lou3', 'lou4', 'lu1', 'lu2', 'lu3', 'lu4', 'luan2', 'luan3', 'luan4', 'lun1', 'lun2', 'lun4', 'luo1', 'luo2', 'luo3', 'luo4', 'lv2', 'lv3', 'lv4', 'lve3', 'lve4', 'ma', 'ma1', 'ma2', 'ma3', 'ma4', 'mai2', 'mai3', 'mai4', 'man2', 'man3', 'man4', 'mang2', 'mang3', 'mao1', 'mao2', 'mao3', 'mao4', 'me', 'mei2', 'mei3', 'mei4', 'men', 'men1', 'men2', 'men4', 'meng1', 'meng2', 'meng3', 'meng4', 'mi1', 'mi2', 'mi3', 'mi4', 'mian2', 'mian3', 'mian4', 'miao1', 'miao2', 'miao3', 'miao4', 'mie1', 'mie4', 'min2', 'min3', 'ming2', 'ming3', 'ming4', 'miu4', 'mo1', 'mo2', 'mo3', 'mo4', 'mou1', 'mou2', 'mou3', 'mu2', 'mu3', 'mu4', 'n2', 'na1', 'na2', 'na3', 'na4', 'nai2', 'nai3', 'nai4', 'nan1', 'nan2', 'nan3', 'nan4', 'nang1', 'nang2', 'nao1', 'nao2', 'nao3', 'nao4', 'ne', 'ne2', 'ne4', 'nei3', 'nei4', 'nen4', 'neng2', 'ni1', 'ni2', 'ni3', 'ni4', 'nian1', 'nian2', 'nian3', 'nian4', 'niang2', 'niang4', 'niao2', 'niao3', 'niao4', 'nie1', 'nie4', 'nin2', 'ning2', 'ning3', 'ning4', 'niu1', 'niu2', 'niu3', 'niu4', 'nong2', 'nong4', 'nou4', 'nu2', 'nu3', 'nu4', 'nuan3', 'nuo2', 'nuo4', 'nv2', 'nv3', 'nve4', 'o1', 'o2', 'ou1', 'ou3', 'ou4', 'pa1', 'pa2', 'pa4', 'pai1', 'pai2', 'pai3', 'pai4', 'pan1', 'pan2', 'pan4', 'pang1', 'pang2', 'pang4', 'pao1', 'pao2', 'pao3', 'pao4', 'pei1', 'pei2', 'pei4', 'pen1', 'pen2', 'pen4', 'peng1', 'peng2', 'peng3', 'peng4', 'pi1', 'pi2', 'pi3', 'pi4', 'pian1', 'pian2', 'pian4', 'piao1', 'piao2', 'piao3', 'piao4', 'pie1', 'pie2', 'pie3', 'pin1', 'pin2', 'pin3', 'pin4', 'ping1', 'ping2', 'po1', 'po2', 'po3', 'po4', 'pou1', 'pu1', 'pu2', 'pu3', 'pu4', 'qi1', 'qi2', 'qi3', 'qi4', 'qia1', 'qia3', 'qia4', 'qian1', 'qian2', 'qian3', 'qian4', 'qiang1', 'qiang2', 'qiang3', 'qiang4', 'qiao1', 'qiao2', 'qiao3', 'qiao4', 'qie1', 'qie2', 'qie3', 'qie4', 'qin1', 'qin2', 'qin3', 'qin4', 'qing1', 'qing2', 'qing3', 'qing4', 'qiong1', 'qiong2', 'qiu1', 'qiu2', 'qiu3', 'qu1', 'qu2', 'qu3', 'qu4', 'quan1', 'quan2', 'quan3', 'quan4', 'que1', 'que2', 'que4', 'qun2', 'ran2', 'ran3', 'rang1', 'rang2', 'rang3', 'rang4', 'rao2', 'rao3', 'rao4', 're2', 're3', 're4', 'ren2', 'ren3', 'ren4', 'reng1', 'reng2', 'ri4', 'rong1', 'rong2', 'rong3', 'rou2', 'rou4', 'ru2', 'ru3', 'ru4', 'ruan2', 'ruan3', 'rui3', 'rui4', 'run4', 'ruo4', 'sa1', 'sa2', 'sa3', 'sa4', 'sai1', 'sai4', 'san1', 'san2', 'san3', 'san4', 'sang1', 'sang3', 'sang4', 'sao1', 'sao2', 'sao3', 'sao4', 'se4', 'sen1', 'seng1', 'sha1', 'sha2', 'sha3', 'sha4', 'shai1', 'shai2', 'shai3', 'shai4', 'shan1', 'shan3', 'shan4', 'shang', 'shang1', 'shang3', 'shang4', 'shao1', 'shao2', 'shao3', 'shao4', 'she1', 'she2', 'she3', 'she4', 'shei2', 'shen1', 'shen2', 'shen3', 'shen4', 'sheng1', 'sheng2', 'sheng3', 'sheng4', 'shi', 'shi1', 'shi2', 'shi3', 'shi4', 'shou1', 'shou2', 'shou3', 'shou4', 'shu1', 'shu2', 'shu3', 'shu4', 'shua1', 'shua2', 'shua3', 'shua4', 'shuai1', 'shuai3', 'shuai4', 'shuan1', 'shuan4', 'shuang1', 'shuang3', 'shui2', 'shui3', 'shui4', 'shun3', 'shun4', 'shuo1', 'shuo4', 'si1', 'si2', 'si3', 'si4', 'song1', 'song3', 'song4', 'sou1', 'sou3', 'sou4', 'su1', 'su2', 'su4', 'suan1', 'suan4', 'sui1', 'sui2', 'sui3', 'sui4', 'sun1', 'sun3', 'suo', 'suo1', 'suo2', 'suo3', 'ta1', 'ta3', 'ta4', 'tai1', 'tai2', 'tai4', 'tan1', 'tan2', 'tan3', 'tan4', 'tang1', 'tang2', 'tang3', 'tang4', 'tao1', 'tao2', 'tao3', 'tao4', 'te4', 'teng2', 'ti1', 'ti2', 'ti3', 'ti4', 'tian1', 'tian2', 'tian3', 'tiao1', 'tiao2', 'tiao3', 'tiao4', 'tie1', 'tie2', 'tie3', 'tie4', 'ting1', 'ting2', 'ting3', 'tong1', 'tong2', 'tong3', 'tong4', 'tou', 'tou1', 'tou2', 'tou4', 'tu1', 'tu2', 'tu3', 'tu4', 'tuan1', 'tuan2', 'tui1', 'tui2', 'tui3', 'tui4', 'tun1', 'tun2', 'tun4', 'tuo1', 'tuo2', 'tuo3', 'tuo4', 'wa', 'wa1', 'wa2', 'wa3', 'wa4', 'wai1', 'wai3', 'wai4', 'wan1', 'wan2', 'wan3', 'wan4', 'wang1', 'wang2', 'wang3', 'wang4', 'wei1', 'wei2', 'wei3', 'wei4', 'wen1', 'wen2', 'wen3', 'wen4', 'weng1', 'weng4', 'wo1', 'wo3', 'wo4', 'wu1', 'wu2', 'wu3', 'wu4', 'xi1', 'xi2', 'xi3', 'xi4', 'xia1', 'xia2', 'xia4', 'xian1', 'xian2', 'xian3', 'xian4', 'xiang1', 'xiang2', 'xiang3', 'xiang4', 'xiao1', 'xiao2', 'xiao3', 'xiao4', 'xie1', 'xie2', 'xie3', 'xie4', 'xin1', 'xin2', 'xin4', 'xing1', 'xing2', 'xing3', 'xing4', 'xiong1', 'xiong2', 'xiu1', 'xiu3', 'xiu4', 'xu', 'xu1', 'xu2', 'xu3', 'xu4', 'xuan1', 'xuan2', 'xuan3', 'xuan4', 'xue1', 'xue2', 'xue3', 'xue4', 'xun1', 'xun2', 'xun4', 'ya', 'ya1', 'ya2', 'ya3', 'ya4', 'yan1', 'yan2', 'yan3', 'yan4', 'yang1', 'yang2', 'yang3', 'yang4', 'yao1', 'yao2', 'yao3', 'yao4', 'ye1', 'ye2', 'ye3', 'ye4', 'yi1', 'yi2', 'yi3', 'yi4', 'yin1', 'yin2', 'yin3', 'yin4', 'ying1', 'ying2', 'ying3', 'ying4', 'yo1', 'yong1', 'yong3', 'yong4', 'you1', 'you2', 'you3', 'you4', 'yu1', 'yu2', 'yu3', 'yu4', 'yuan1', 'yuan2', 'yuan3', 'yuan4', 'yue1', 'yue4', 'yun1', 'yun2', 'yun3', 'yun4', 'za1', 'za2', 'za3', 'zai1', 'zai3', 'zai4', 'zan1', 'zan2', 'zan3', 'zan4', 'zang1', 'zang4', 'zao1', 'zao2', 'zao3', 'zao4', 'ze2', 'ze4', 'zei2', 'zen3', 'zeng1', 'zeng4', 'zha1', 'zha2', 'zha3', 'zha4', 'zhai1', 'zhai2', 'zhai3', 'zhai4', 'zhan1', 'zhan2', 'zhan3', 'zhan4', 'zhang1', 'zhang2', 'zhang3', 'zhang4', 'zhao1', 'zhao2', 'zhao3', 'zhao4', 'zhe', 'zhe1', 'zhe2', 'zhe3', 'zhe4', 'zhen1', 'zhen2', 'zhen3', 'zhen4', 'zheng1', 'zheng2', 'zheng3', 'zheng4', 'zhi1', 'zhi2', 'zhi3', 'zhi4', 'zhong1', 'zhong2', 'zhong3', 'zhong4', 'zhou1', 'zhou2', 'zhou3', 'zhou4', 'zhu1', 'zhu2', 'zhu3', 'zhu4', 'zhua1', 'zhua2', 'zhua3', 'zhuai1', 'zhuai3', 'zhuai4', 'zhuan1', 'zhuan2', 'zhuan3', 'zhuan4', 'zhuang1', 'zhuang4', 'zhui1', 'zhui4', 'zhun1', 'zhun2', 'zhun3', 'zhuo1', 'zhuo2', 'zi', 'zi1', 'zi2', 'zi3', 'zi4', 'zong1', 'zong2', 'zong3', 'zong4', 'zou1', 'zou2', 'zou3', 'zou4', 'zu1', 'zu2', 'zu3', 'zuan1', 'zuan3', 'zuan4', 'zui2', 'zui3', 'zui4', 'zun1', 'zuo1', 'zuo2', 'zuo3', 'zuo4'] + ens = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z', "'", ' '] + ens_U = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'] + + phoneme_to_index = {} + num_phonemes = 0 + for index, punc in enumerate(puncs): + phoneme_to_index[punc] = index + num_phonemes + num_phonemes += len(puncs) + for index, pinyin in enumerate(pinyins): + phoneme_to_index[pinyin] = index + num_phonemes + num_phonemes += len(pinyins) + for index, en in enumerate(ens): + phoneme_to_index[en] = index + num_phonemes + for index, en in enumerate(ens_U): + phoneme_to_index[en] = index + num_phonemes + num_phonemes += len(ens) + #print(num_phonemes, phoneme_to_index) # 1342 + + def encode( + text: list[str], + padding_value = -1 + ) -> Int['b nt']: + phonemes = [] + for t in text: + one_phoneme = [] + brk = False + for word in jieba.cut(t): + if all_ch(word): + seg = lazy_pinyin(word, style=Style.TONE3, tone_sandhi=True) + one_phoneme.extend(seg) + elif all_en(word): + for seg in word: + one_phoneme.append(seg) + elif word in ["，", "。", "？", "、", "'", " "]: + one_phoneme.append(word) + else: + for ch in word: + if all_ch(ch): + seg = lazy_pinyin(ch, style=Style.TONE3, tone_sandhi=True) + one_phoneme.extend(seg) + elif all_en(ch): + for seg in ch: + one_phoneme.append(seg) + else: + brk = True + break + if brk: + break + if not brk: + phonemes.append(one_phoneme) + else: + print("Error Tokenized", t, list(jieba.cut(t))) + list_tensors = [tensor([phoneme_to_index[p] for p in one_phoneme]) for one_phoneme in phonemes] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + + return encode, num_phonemes + +# tensor helpers + +def log(t, eps = 1e-5): + return t.clamp(min = eps).log() + +def lens_to_mask( + t: Int['b'], + length: int | None = None +) -> Bool['b n']: + + if not exists(length): + length = t.amax() + + seq = torch.arange(length, device = t.device) + return einx.less('n, b -> b n', seq, t) + +def mask_from_start_end_indices( + seq_len: Int['b'], + start: Int['b'], + end: Int['b'] +): + max_seq_len = seq_len.max().item() + seq = torch.arange(max_seq_len, device = start.device).long() + return einx.greater_equal('n, b -> b n', seq, start) & einx.less('n, b -> b n', seq, end) + +def mask_from_frac_lengths( + seq_len: Int['b'], + frac_lengths: Float['b'], + max_length: int | None = None, + val = False +): + lengths = (frac_lengths * seq_len).long() + max_start = seq_len - lengths + + if not val: + rand = torch.rand_like(frac_lengths) + else: + rand = torch.tensor([0.5]*frac_lengths.shape[0], device=frac_lengths.device).float() + start = (max_start * rand).long().clamp(min = 0) + end = start + lengths + + out = mask_from_start_end_indices(seq_len, start, end) + + if exists(max_length): + out = pad_to_length(out, max_length) + + return out + +def maybe_masked_mean( + t: Float['b n d'], + mask: Bool['b n'] | None = None +) -> Float['b d']: + + if not exists(mask): + return t.mean(dim = 1) + + t = einx.where('b n, b n d, -> b n d', mask, t, 0.) + num = reduce(t, 'b n d -> b d', 'sum') + den = reduce(mask.float(), 'b n -> b', 'sum') + + return einx.divide('b d, b -> b d', num, den.clamp(min = 1.)) + +def pad_to_length( + t: Tensor, + length: int, + value = None +): + seq_len = t.shape[-1] + if length > seq_len: + t = F.pad(t, (0, length - seq_len), value = value) + + return t[..., :length] + +def interpolate_1d( + x: Tensor, + length: int, + mode = 'bilinear' +): + x = rearrange(x, 'n d -> 1 d n 1') + x = F.interpolate(x, (length, 1), mode = mode) + return rearrange(x, '1 d n 1 -> n d') + +# to mel spec + +class MelSpec(Module): + def __init__( + self, + filter_length = 1024, + hop_length = 256, + win_length = 1024, + n_mel_channels = 100, + sampling_rate = 24_000, + normalize = False, + power = 1, + norm = None, + center = True, + ): + super().__init__() + self.n_mel_channels = n_mel_channels + self.sampling_rate = sampling_rate + + self.mel_stft = torchaudio.transforms.MelSpectrogram( + sample_rate = sampling_rate, + n_fft = filter_length, + win_length = win_length, + hop_length = hop_length, + n_mels = n_mel_channels, + power = power, + center = center, + normalized = normalize, + norm = norm, + ) + + self.register_buffer('dummy', tensor(0), persistent = False) + + def forward(self, inp): + if len(inp.shape) == 3: + inp = rearrange(inp, 'b 1 nw -> b nw') + + assert len(inp.shape) == 2 + + if self.dummy.device != inp.device: + self.to(inp.device) + + mel = self.mel_stft(inp) + mel = log(mel) + return mel + +class EncodecWrapper(Module): + def __init__(self, path): + super().__init__() + self.model = EncodecModel.from_pretrained(path) + self.processor = AutoProcessor.from_pretrained(path) + for param in self.model.parameters(): + param.requires_grad = False + self.model.eval() + + def forward(self, waveform): + with torch.no_grad(): + inputs = self.processor(raw_audio=waveform[0], sampling_rate=self.processor.sampling_rate, return_tensors="pt") + emb = self.model.encoder(inputs.input_values) + return emb + + def decode(self, emb): + with torch.no_grad(): + output = self.model.decoder(emb) + return output[0] + +from audioldm.audio.stft import TacotronSTFT +from audioldm.variational_autoencoder import AutoencoderKL +from audioldm.utils import default_audioldm_config, get_metadata + +def build_pretrained_models(name): + checkpoint = torch.load(get_metadata()[name]["path"], map_location="cpu") + scale_factor = checkpoint["state_dict"]["scale_factor"].item() + + vae_state_dict = {k[18:]: v for k, v in checkpoint["state_dict"].items() if "first_stage_model." in k} + + config = default_audioldm_config(name) + vae_config = config["model"]["params"]["first_stage_config"]["params"] + vae_config["scale_factor"] = scale_factor + + vae = AutoencoderKL(**vae_config) + vae.load_state_dict(vae_state_dict) + + fn_STFT = TacotronSTFT( + config["preprocessing"]["stft"]["filter_length"], + config["preprocessing"]["stft"]["hop_length"], + config["preprocessing"]["stft"]["win_length"], + config["preprocessing"]["mel"]["n_mel_channels"], + config["preprocessing"]["audio"]["sampling_rate"], + config["preprocessing"]["mel"]["mel_fmin"], + config["preprocessing"]["mel"]["mel_fmax"], + ) + + vae.eval() + fn_STFT.eval() + return vae, fn_STFT + +class VaeWrapper(Module): + def __init__(self): + super().__init__() + vae, stft = build_pretrained_models("audioldm-s-full") + vae.eval() + stft.eval() + stft = stft.cpu() + self.vae = vae + for param in self.vae.parameters(): + param.requires_grad = False + + def forward(self, waveform): + return None + + def decode(self, emb): + with torch.no_grad(): + b, d, l = emb.shape + latents = emb.transpose(1,2).reshape(b, l, 8, 16).transpose(1,2) + mel = self.vae.decode_first_stage(latents) + wave = self.vae.decode_to_waveform(mel) + return wave + +# convolutional positional generating module +# taken from https://github.com/lucidrains/voicebox-pytorch/blob/main/voicebox_pytorch/voicebox_pytorch.py#L203 + +class DepthwiseConv(Module): + def __init__( + self, + dim, + *, + kernel_size, + groups = None + ): + super().__init__() + assert not divisible_by(kernel_size, 2) + groups = default(groups, dim) # full depthwise conv by default + + self.dw_conv1d = nn.Sequential( + nn.Conv1d(dim, dim, kernel_size, groups = groups, padding = kernel_size // 2), + nn.SiLU() + ) + + def forward( + self, + x, + mask = None + ): + + if exists(mask): + x = einx.where('b n, b n d, -> b n d', mask, x, 0.) + + x = rearrange(x, 'b n c -> b c n') + x = self.dw_conv1d(x) + out = rearrange(x, 'b c n -> b n c') + + if exists(mask): + out = einx.where('b n, b n d, -> b n d', mask, out, 0.) + + return out + +# adaln zero from DiT paper + +class AdaLNZero(Module): + def __init__( + self, + dim, + dim_condition = None, + init_bias_value = -2. + ): + super().__init__() + dim_condition = default(dim_condition, dim) + self.to_gamma = nn.Linear(dim_condition, dim) + + nn.init.zeros_(self.to_gamma.weight) + nn.init.constant_(self.to_gamma.bias, init_bias_value) + + def forward(self, x, *, condition): + if condition.ndim == 2: + condition = rearrange(condition, 'b d -> b 1 d') + + gamma = self.to_gamma(condition).sigmoid() + return x * gamma + +# random projection fourier embedding + +class RandomFourierEmbed(Module): + def __init__(self, dim): + super().__init__() + assert divisible_by(dim, 2) + self.register_buffer('weights', torch.randn(dim // 2)) + + def forward(self, x): + freqs = einx.multiply('i, j -> i j', x, self.weights) * 2 * torch.pi + fourier_embed, _ = pack((x, freqs.sin(), freqs.cos()), 'b *') + return fourier_embed + +# character embedding + +class CharacterEmbed(Module): + def __init__( + self, + dim, + num_embeds = 256, + ): + super().__init__() + self.dim = dim + self.embed = nn.Embedding(num_embeds + 1, dim) # will just use 0 as the 'filler token' + + def forward( + self, + text: Int['b nt'], + max_seq_len: int, + **kwargs + ) -> Float['b n d']: + + text = text + 1 # shift all other token ids up by 1 and use 0 as filler token + + text = text[:, :max_seq_len] # just curtail if character tokens are more than the mel spec tokens, one of the edge cases the paper did not address + text = pad_to_length(text, max_seq_len, value = 0) + + return self.embed(text) + +class InterpolatedCharacterEmbed(Module): + def __init__( + self, + dim, + num_embeds = 256, + ): + super().__init__() + self.dim = dim + self.embed = nn.Embedding(num_embeds, dim) + + self.abs_pos_mlp = Sequential( + Rearrange('... -> ... 1'), + Linear(1, dim), + nn.SiLU(), + Linear(dim, dim) + ) + + def forward( + self, + text: Int['b nt'], + max_seq_len: int, + mask: Bool['b n'] | None = None + ) -> Float['b n d']: + + device = text.device + + mask = default(mask, (None,)) + + interp_embeds = [] + interp_abs_positions = [] + + for one_text, one_mask in zip_longest(text, mask): + + valid_text = one_text >= 0 + one_text = one_text[valid_text] + one_text_embed = self.embed(one_text) + + # save the absolute positions + + text_seq_len = one_text.shape[0] + + # determine audio sequence length from mask + + audio_seq_len = max_seq_len + if exists(one_mask): + audio_seq_len = one_mask.sum().long().item() + + # interpolate text embedding to audio embedding length + + interp_text_embed = interpolate_1d(one_text_embed, audio_seq_len) + interp_abs_pos = torch.linspace(0, text_seq_len, audio_seq_len, device = device) + + interp_embeds.append(interp_text_embed) + interp_abs_positions.append(interp_abs_pos) + + interp_embeds = pad_sequence(interp_embeds) + interp_abs_positions = pad_sequence(interp_abs_positions) + + interp_embeds = F.pad(interp_embeds, (0, 0, 0, max_seq_len - interp_embeds.shape[-2])) + interp_abs_positions = pad_to_length(interp_abs_positions, max_seq_len) + + # pass interp absolute positions through mlp for implicit positions + + interp_embeds = interp_embeds + self.abs_pos_mlp(interp_abs_positions) + + if exists(mask): + interp_embeds = einx.where('b n, b n d, -> b n d', mask, interp_embeds, 0.) + + return interp_embeds + +# text audio cross conditioning in multistream setup + +class TextAudioCrossCondition(Module): + def __init__( + self, + dim, + dim_text, + dim_frames, + cond_audio_to_text = True, + ): + super().__init__() + #self.text_to_audio = nn.Linear(dim_text + dim, dim, bias = False) + self.text_frames_to_audio = nn.Linear(dim + dim_text + dim_frames, dim, bias = False) + nn.init.zeros_(self.text_frames_to_audio.weight) + + self.cond_audio_to_text = cond_audio_to_text + + if cond_audio_to_text: + self.audio_to_text = nn.Linear(dim + dim_text, dim_text, bias = False) + nn.init.zeros_(self.audio_to_text.weight) + + self.audio_to_frames = nn.Linear(dim + dim_frames, dim_frames, bias = False) + nn.init.zeros_(self.audio_to_frames.weight) + + def forward( + self, + audio: Float['b n d'], + text: Float['b n dt'], + frames: Float['b n df'], + ): + #audio_text, _ = pack((audio, text), 'b n *') + audio_text_frames, _ = pack((audio, text, frames), 'b n *') + audio_text, _ = pack((audio, text), 'b n *') + audio_frames, _ = pack((audio, frames), 'b n *') + + #text_cond = self.text_to_audio(audio_text) + text_cond = self.text_frames_to_audio(audio_text_frames) + audio_cond = self.audio_to_text(audio_text) if self.cond_audio_to_text else 0. + audio_cond2 = self.audio_to_frames(audio_frames) if self.cond_audio_to_text else 0. + + return audio + text_cond, text + audio_cond, frames + audio_cond2 + +# attention and transformer backbone +# for use in both e2tts as well as duration module + +class Transformer(Module): + @beartype + def __init__( + self, + *, + dim, + dim_text = None, # will default to half of audio dimension + dim_frames = 512, + depth = 8, + heads = 8, + dim_head = 64, + ff_mult = 4, + text_depth = None, + text_heads = None, + text_dim_head = None, + text_ff_mult = None, + cond_on_time = True, + abs_pos_emb = True, + max_seq_len = 8192, + kernel_size = 31, + dropout = 0.1, + num_registers = 32, + attn_kwargs: dict = dict( + gate_value_heads = True, + softclamp_logits = True, + ), + ff_kwargs: dict = dict(), + if_text_modules = True, + if_cross_attn = True, + if_audio_conv = True, + if_text_conv = False + ): + super().__init__() + assert divisible_by(depth, 2), 'depth needs to be even' + + # absolute positional embedding + + self.max_seq_len = max_seq_len + self.abs_pos_emb = nn.Embedding(max_seq_len, dim) if abs_pos_emb else None + + self.dim = dim + + dim_text = default(dim_text, dim // 2) + self.dim_text = dim_text + + self.dim_frames = dim_frames + + text_heads = default(text_heads, heads) + text_dim_head = default(text_dim_head, dim_head) + text_ff_mult = default(text_ff_mult, ff_mult) + text_depth = default(text_depth, depth) + + assert 1 <= text_depth <= depth, 'must have at least 1 layer of text conditioning, but less than total number of speech layers' + + self.depth = depth + self.layers = ModuleList([]) + + # registers + + self.num_registers = num_registers + self.registers = nn.Parameter(torch.zeros(num_registers, dim)) + nn.init.normal_(self.registers, std = 0.02) + + if if_text_modules: + self.text_registers = nn.Parameter(torch.zeros(num_registers, dim_text)) + nn.init.normal_(self.text_registers, std = 0.02) + + self.frames_registers = nn.Parameter(torch.zeros(num_registers, dim_frames)) + nn.init.normal_(self.frames_registers, std = 0.02) + + # rotary embedding + + self.rotary_emb = RotaryEmbedding(dim_head) + self.text_rotary_emb = RotaryEmbedding(dim_head) + self.frames_rotary_emb = RotaryEmbedding(dim_head) + + # time conditioning + # will use adaptive rmsnorm + + self.cond_on_time = cond_on_time + rmsnorm_klass = RMSNorm if not cond_on_time else AdaptiveRMSNorm + postbranch_klass = Identity if not cond_on_time else partial(AdaLNZero, dim = dim) + + self.time_cond_mlp = Identity() + + if cond_on_time: + self.time_cond_mlp = Sequential( + RandomFourierEmbed(dim), + Linear(dim + 1, dim), + nn.SiLU() + ) + + for ind in range(depth): + is_later_half = ind >= (depth // 2) + has_text = ind < text_depth + + # speech related + if if_audio_conv: + speech_conv = DepthwiseConv(dim, kernel_size = kernel_size) + + attn_norm = rmsnorm_klass(dim) + attn = Attention(dim = dim, heads = heads, dim_head = dim_head, dropout = dropout, **attn_kwargs) + attn_adaln_zero = postbranch_klass() + + if if_cross_attn: + attn_norm2 = rmsnorm_klass(dim) + attn2 = Attention(dim = dim, heads = heads, dim_head = dim_head, dropout = dropout, **attn_kwargs) + attn_adaln_zero2 = postbranch_klass() + + ff_norm = rmsnorm_klass(dim) + ff = FeedForward(dim = dim, glu = True, mult = ff_mult, dropout = dropout, **ff_kwargs) + ff_adaln_zero = postbranch_klass() + + skip_proj = Linear(dim * 2, dim, bias = False) if is_later_half else None + + if if_cross_attn: + if if_audio_conv: + speech_modules = ModuleList([ + skip_proj, + speech_conv, + attn_norm, + attn, + attn_adaln_zero, + attn_norm2, + attn2, + attn_adaln_zero2, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + speech_modules = ModuleList([ + skip_proj, + attn_norm, + attn, + attn_adaln_zero, + attn_norm2, + attn2, + attn_adaln_zero2, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + if if_audio_conv: + speech_modules = ModuleList([ + skip_proj, + speech_conv, + attn_norm, + attn, + attn_adaln_zero, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + speech_modules = ModuleList([ + skip_proj, + attn_norm, + attn, + attn_adaln_zero, + ff_norm, + ff, + ff_adaln_zero, + ]) + + text_modules = None + + if has_text and if_text_modules: + # text related + if if_text_conv: + text_conv = DepthwiseConv(dim_text, kernel_size = kernel_size) + + text_attn_norm = RMSNorm(dim_text) + text_attn = Attention(dim = dim_text, heads = text_heads, dim_head = text_dim_head, dropout = dropout, **attn_kwargs) + + text_ff_norm = RMSNorm(dim_text) + text_ff = FeedForward(dim = dim_text, glu = True, mult = text_ff_mult, dropout = dropout, **ff_kwargs) + + # cross condition + + is_last = ind == (text_depth - 1) + + cross_condition = TextAudioCrossCondition(dim = dim, dim_text = dim_text, dim_frames = dim_frames, cond_audio_to_text = not is_last) + + if if_text_conv: + text_modules = ModuleList([ + text_conv, + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ]) + else: + text_modules = ModuleList([ + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ]) + + if True: + frames_conv = DepthwiseConv(dim_frames, kernel_size = kernel_size) + + frames_attn_norm = RMSNorm(dim_frames) + frames_attn = Attention(dim = dim_frames, heads = 8, dim_head = 64, dropout = dropout, **attn_kwargs) + + frames_ff_norm = RMSNorm(dim_frames) + frames_ff = FeedForward(dim = dim_frames, glu = True, mult = 4, dropout = dropout, **ff_kwargs) + + # cross condition + + frames_modules = ModuleList([ + frames_conv, + frames_attn_norm, + frames_attn, + frames_ff_norm, + frames_ff + ]) + + self.layers.append(ModuleList([ + speech_modules, + text_modules, + frames_modules + ])) + + self.final_norm = RMSNorm(dim) + + self.if_cross_attn = if_cross_attn + self.if_audio_conv = if_audio_conv + self.if_text_conv = if_text_conv + + def forward( + self, + x: Float['b n d'], + times: Float['b'] | Float[''] | None = None, + mask: Bool['b n'] | None = None, + text_embed: Float['b n dt'] | None = None, + frames_embed: Float['b n df'] | None = None, + context: Float['b nc dc'] | None = None, + context_mask: Float['b nc'] | None = None + ): + batch, seq_len, device = *x.shape[:2], x.device + + assert not (exists(times) ^ self.cond_on_time), '`times` must be passed in if `cond_on_time` is set to `True` and vice versa' + + # handle absolute positions if needed + + if exists(self.abs_pos_emb): + assert seq_len <= self.max_seq_len, f'{seq_len} exceeds the set `max_seq_len` ({self.max_seq_len}) on Transformer' + seq = torch.arange(seq_len, device = device) + x = x + self.abs_pos_emb(seq) + + # handle adaptive rmsnorm kwargs + + norm_kwargs = dict() + + if exists(times): + if times.ndim == 0: + times = repeat(times, ' -> b', b = batch) + + times = self.time_cond_mlp(times) + norm_kwargs.update(condition = times) + + # register tokens + + registers = repeat(self.registers, 'r d -> b r d', b = batch) + x, registers_packed_shape = pack((registers, x), 'b * d') + + if exists(mask): + mask = F.pad(mask, (self.num_registers, 0), value = True) + + # rotary embedding + + rotary_pos_emb = self.rotary_emb.forward_from_seq_len(x.shape[-2]) + + # text related + + if exists(text_embed): + text_rotary_pos_emb = self.text_rotary_emb.forward_from_seq_len(x.shape[-2]) + + text_registers = repeat(self.text_registers, 'r d -> b r d', b = batch) + text_embed, _ = pack((text_registers, text_embed), 'b * d') + + if exists(frames_embed): + frames_rotary_pos_emb = self.frames_rotary_emb.forward_from_seq_len(x.shape[-2]) + + frames_registers = repeat(self.frames_registers, 'r d -> b r d', b = batch) + frames_embed, _ = pack((frames_registers, frames_embed), 'b * d') + + # skip connection related stuff + + skips = [] + + # go through the layers + + for ind, (speech_modules, text_modules, frames_modules) in enumerate(self.layers): + layer = ind + 1 + + if self.if_cross_attn: + if self.if_audio_conv: + ( + maybe_skip_proj, + speech_conv, + attn_norm, + attn, + maybe_attn_adaln_zero, + attn_norm2, + attn2, + maybe_attn_adaln_zero2, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + ( + maybe_skip_proj, + attn_norm, + attn, + maybe_attn_adaln_zero, + attn_norm2, + attn2, + maybe_attn_adaln_zero2, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + if self.if_audio_conv: + ( + maybe_skip_proj, + speech_conv, + attn_norm, + attn, + maybe_attn_adaln_zero, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + ( + maybe_skip_proj, + attn_norm, + attn, + maybe_attn_adaln_zero, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + + # smaller text transformer + + if exists(text_embed) and exists(text_modules): + + if self.if_text_conv: + ( + text_conv, + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ) = text_modules + else: + ( + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ) = text_modules + + if self.if_text_conv: + text_embed = text_conv(text_embed, mask = mask) + text_embed + + text_embed = text_attn(text_attn_norm(text_embed), rotary_pos_emb = text_rotary_pos_emb, mask = mask) + text_embed + + text_embed = text_ff(text_ff_norm(text_embed)) + text_embed + + # frames transformer + ( + frames_conv, + frames_attn_norm, + frames_attn, + frames_ff_norm, + frames_ff + ) = frames_modules + + frames_embed = frames_conv(frames_embed, mask = mask) + frames_embed + + frames_embed = frames_attn(frames_attn_norm(frames_embed), rotary_pos_emb = frames_rotary_pos_emb, mask = mask) + frames_embed + + frames_embed = frames_ff(frames_ff_norm(frames_embed)) + frames_embed + + # cross condition + x, text_embed, frames_embed = cross_condition(x, text_embed, frames_embed) + + # skip connection logic + + is_first_half = layer <= (self.depth // 2) + is_later_half = not is_first_half + + if is_first_half: + skips.append(x) + + if is_later_half: + skip = skips.pop() + x = torch.cat((x, skip), dim = -1) + x = maybe_skip_proj(x) + + # position generating convolution + + if self.if_audio_conv: + x = speech_conv(x, mask = mask) + x + + # attention and feedforward blocks + + attn_out = attn(attn_norm(x, **norm_kwargs), rotary_pos_emb = rotary_pos_emb, mask = mask) + + x = x + maybe_attn_adaln_zero(attn_out, **norm_kwargs) + + if self.if_cross_attn: + attn_out = attn2(attn_norm2(x, **norm_kwargs), rotary_pos_emb = rotary_pos_emb, mask = mask, context = context, context_mask = context_mask) + + x = x + maybe_attn_adaln_zero2(attn_out, **norm_kwargs) + + ff_out = ff(ff_norm(x, **norm_kwargs)) + + x = x + maybe_ff_adaln_zero(ff_out, **norm_kwargs) + + assert len(skips) == 0 + + _, x = unpack(x, registers_packed_shape, 'b * d') + + return self.final_norm(x) + +# main classes + +class DurationPredictor(Module): + @beartype + def __init__( + self, + transformer: dict | Transformer, + num_channels = None, + mel_spec_kwargs: dict = dict(), + char_embed_kwargs: dict = dict(), + text_num_embeds = None, + tokenizer: ( + Literal['char_utf8', 'phoneme_en'] | + Callable[[list[str]], Int['b nt']] + ) = 'char_utf8' + ): + super().__init__() + + if isinstance(transformer, dict): + transformer = Transformer( + **transformer, + cond_on_time = False + ) + + # mel spec + + self.mel_spec = MelSpec(**mel_spec_kwargs) + self.num_channels = default(num_channels, self.mel_spec.n_mel_channels) + + self.transformer = transformer + + dim = transformer.dim + dim_text = transformer.dim_text + + self.dim = dim + + self.proj_in = Linear(self.num_channels, self.dim) + + # tokenizer and text embed + + if callable(tokenizer): + assert exists(text_num_embeds), '`text_num_embeds` must be given if supplying your own tokenizer encode function' + self.tokenizer = tokenizer + elif tokenizer == 'char_utf8': + text_num_embeds = 256 + self.tokenizer = list_str_to_tensor + elif tokenizer == 'phoneme_en': + self.tokenizer, text_num_embeds = get_g2p_en_encode() + elif tokenizer == 'phoneme_zh': + self.tokenizer, text_num_embeds = get_g2p_zh_encode() + else: + raise ValueError(f'unknown tokenizer string {tokenizer}') + + self.embed_text = CharacterEmbed(dim_text, num_embeds = text_num_embeds, **char_embed_kwargs) + + # to prediction + + self.to_pred = Sequential( + Linear(dim, 1, bias = False), + nn.Softplus(), + Rearrange('... 1 -> ...') + ) + + def forward( + self, + x: Float['b n d'] | Float['b nw'], + *, + text: Int['b nt'] | list[str] | None = None, + lens: Int['b'] | None = None, + return_loss = True + ): + # raw wave + + if x.ndim == 2: + x = self.mel_spec(x) + x = rearrange(x, 'b d n -> b n d') + assert x.shape[-1] == self.dim + + x = self.proj_in(x) + + batch, seq_len, device = *x.shape[:2], x.device + + # text + + text_embed = None + + if exists(text): + if isinstance(text, list): + text = list_str_to_tensor(text).to(device) + assert text.shape[0] == batch + + text_embed = self.embed_text(text, seq_len) + + # handle lengths (duration) + + if not exists(lens): + lens = torch.full((batch,), seq_len, device = device) + + mask = lens_to_mask(lens, length = seq_len) + + # if returning a loss, mask out randomly from an index and have it predict the duration + + if return_loss: + rand_frac_index = x.new_zeros(batch).uniform_(0, 1) + rand_index = (rand_frac_index * lens).long() + + seq = torch.arange(seq_len, device = device) + mask &= einx.less('n, b -> b n', seq, rand_index) + + # attending + + x = self.transformer( + x, + mask = mask, + text_embed = text_embed, + ) + + x = maybe_masked_mean(x, mask) + + pred = self.to_pred(x) + + # return the prediction if not returning loss + + if not return_loss: + return pred + + # loss + + return F.mse_loss(pred, lens.float()) + +class E2TTS(Module): + + @beartype + def __init__( + self, + transformer: dict | Transformer = None, + duration_predictor: dict | DurationPredictor | None = None, + odeint_kwargs: dict = dict( + #atol = 1e-5, + #rtol = 1e-5, + #method = 'midpoint' + method = "euler" + ), + audiocond_drop_prob = 0.30, + cond_drop_prob = 0.20, + prompt_drop_prob = 0.10, + num_channels = None, + mel_spec_module: Module | None = None, + char_embed_kwargs: dict = dict(), + mel_spec_kwargs: dict = dict(), + frac_lengths_mask: tuple[float, float] = (0.7, 1.), + audiocond_snr: tuple[float, float] | None = None, + concat_cond = False, + interpolated_text = False, + text_num_embeds: int | None = None, + tokenizer: ( + Literal['char_utf8', 'phoneme_en', 'phoneme_zh'] | + Callable[[list[str]], Int['b nt']] + ) = 'char_utf8', + use_vocos = True, + pretrained_vocos_path = 'charactr/vocos-mel-24khz', + sampling_rate: int | None = None, + frame_size: int = 320, + #### dpo + velocity_consistency_weight = -1e-5, + #### dpo + + if_cond_proj_in = True, + cond_proj_in_bias = True, + if_embed_text = True, + if_text_encoder2 = True, + if_clip_encoder = False, + video_encoder = "clip_vit" + ): + super().__init__() + + if isinstance(transformer, dict): + transformer = Transformer( + **transformer, + cond_on_time = True + ) + + if isinstance(duration_predictor, dict): + duration_predictor = DurationPredictor(**duration_predictor) + + self.transformer = transformer + + dim = transformer.dim + dim_text = transformer.dim_text + dim_frames = transformer.dim_frames + + self.dim = dim + self.dim_text = dim_text + + self.frac_lengths_mask = frac_lengths_mask + self.audiocond_snr = audiocond_snr + + self.duration_predictor = duration_predictor + + # sampling + + self.odeint_kwargs = odeint_kwargs + + # mel spec + + self.mel_spec = default(mel_spec_module, None) + num_channels = default(num_channels, None) + + self.num_channels = num_channels + self.sampling_rate = default(sampling_rate, None) + self.frame_size = frame_size + + # whether to concat condition and project rather than project both and sum + + self.concat_cond = concat_cond + + if concat_cond: + self.proj_in = nn.Linear(num_channels * 2, dim) + else: + self.proj_in = nn.Linear(num_channels, dim) + self.cond_proj_in = nn.Linear(num_channels, dim, bias=cond_proj_in_bias) if if_cond_proj_in else None + #self.cond_proj_in = nn.Linear(NOTES, dim, bias=cond_proj_in_bias) if if_cond_proj_in else None + + # to prediction + + self.to_pred = Linear(dim, num_channels) + + # tokenizer and text embed + + if callable(tokenizer): + assert exists(text_num_embeds), '`text_num_embeds` must be given if supplying your own tokenizer encode function' + self.tokenizer = tokenizer + elif tokenizer == 'char_utf8': + text_num_embeds = 256 + self.tokenizer = list_str_to_tensor + elif tokenizer == 'phoneme_en': + self.tokenizer, text_num_embeds = get_g2p_en_encode() + elif tokenizer == 'phoneme_zh': + self.tokenizer, text_num_embeds = get_g2p_zh_encode() + else: + raise ValueError(f'unknown tokenizer string {tokenizer}') + + self.audiocond_drop_prob = audiocond_drop_prob + self.cond_drop_prob = cond_drop_prob + self.prompt_drop_prob = prompt_drop_prob + + # text embedding + + text_embed_klass = CharacterEmbed if not interpolated_text else InterpolatedCharacterEmbed + + self.embed_text = text_embed_klass(dim_text, num_embeds = text_num_embeds, **char_embed_kwargs) if if_embed_text else None + + # weight for velocity consistency + + self.register_buffer('zero', torch.tensor(0.), persistent = False) + self.velocity_consistency_weight = velocity_consistency_weight + + # default vocos for mel -> audio + + #if pretrained_vocos_path == 'charactr/vocos-mel-24khz': + # self.vocos = Vocos.from_pretrained(pretrained_vocos_path) if use_vocos else None + #elif pretrained_vocos_path == 'facebook/encodec_24khz': + # self.vocos = EncodecWrapper("facebook/encodec_24khz") if use_vocos else None + #elif pretrained_vocos_path == 'vae': + # self.vocos = VaeWrapper() if use_vocos else None + + if if_text_encoder2: + self.tokenizer2 = AutoTokenizer.from_pretrained("./ckpts/flan-t5-large") + self.text_encoder2 = T5EncoderModel.from_pretrained("./ckpts/flan-t5-large") + for param in self.text_encoder2.parameters(): + param.requires_grad = False + self.text_encoder2.eval() + + self.proj_text = None + self.proj_frames = Linear(NOTES, dim_frames) + if if_clip_encoder: + if video_encoder == "clip_vit": + ####pass + self.image_processor = CLIPImageProcessor() + #self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train2/speech/zhanghaomin/models/IP-Adapter/", subfolder="models/image_encoder") + self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("./ckpts/IP-Adapter/", subfolder="sdxl_models/image_encoder") + elif video_encoder == "clip_vit2": + self.image_processor = AutoProcessor.from_pretrained("/ailab-train2/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train2/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + elif video_encoder == "clip_convnext": + self.image_encoder, _, self.image_processor = open_clip.create_model_and_transforms("hf-hub:laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup") + elif video_encoder == "dinov2": + self.image_processor = AutoImageProcessor.from_pretrained("/ailab-train2/speech/zhanghaomin/models/dinov2-giant/") + self.image_encoder = AutoModel.from_pretrained("/ailab-train2/speech/zhanghaomin/models/dinov2-giant/") + elif video_encoder == "mixed": + pass + #self.image_processor1 = CLIPImageProcessor() + #self.image_encoder1 = CLIPVisionModelWithProjection.from_pretrained("/ailab-train2/speech/zhanghaomin/models/IP-Adapter/", subfolder="sdxl_models/image_encoder") + #self.image_processor2 = AutoProcessor.from_pretrained("/ailab-train2/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + #self.image_encoder2 = CLIPVisionModelWithProjection.from_pretrained("/ailab-train2/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + #self.image_encoder3, _, self.image_processor3 = open_clip.create_model_and_transforms("hf-hub:laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup") + #self.image_processor4 = AutoImageProcessor.from_pretrained("/ailab-train2/speech/zhanghaomin/models/dinov2-giant/") + #self.image_encoder4 = AutoModel.from_pretrained("/ailab-train2/speech/zhanghaomin/models/dinov2-giant/") + else: + self.image_processor = None + self.image_encoder = None + if video_encoder != "mixed": + ####pass + for param in self.image_encoder.parameters(): + param.requires_grad = False + self.image_encoder.eval() + else: + #for param in self.image_encoder1.parameters(): + # param.requires_grad = False + #self.image_encoder1.eval() + #for param in self.image_encoder2.parameters(): + # param.requires_grad = False + #self.image_encoder2.eval() + #for param in self.image_encoder3.parameters(): + # param.requires_grad = False + #self.image_encoder3.eval() + #for param in self.image_encoder4.parameters(): + # param.requires_grad = False + #self.image_encoder4.eval() + self.dim_text_raw = 4608 + self.proj_text = Linear(self.dim_text_raw, dim_text) + self.video_encoder = video_encoder + + #for param in self.vocos.parameters(): + # param.requires_grad = False + #self.vocos.eval() + + ########self.conv1 = nn.Conv3d(6, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool1 = nn.Conv3d(64, 64, kernel_size=(1, 2, 2), stride=(1, 2, 2)) + ####self.conv1 = nn.Conv3d(3, 16, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.pool1 = nn.Conv3d(16, 16, kernel_size=(1, 2, 2), stride=(1, 2, 2), padding=(0,0,0)) + #### + ########self.conv2 = nn.Conv3d(64, 128, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool2 = nn.Conv3d(128, 128, kernel_size=(2, 2, 2), stride=(2, 2, 2)) + ####self.conv2 = nn.Conv3d(16, 32, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.pool2 = nn.Conv3d(32, 32, kernel_size=(2, 2, 2), stride=(1, 2, 2), padding=(0,0,0)) + #### + ########self.conv3a = nn.Conv3d(128, 256, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.conv3b = nn.Conv3d(256, 256, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool3 = nn.Conv3d(256, 256, kernel_size=(1, 2, 2), stride=(1, 2, 2)) + ####self.conv3a = nn.Conv3d(32, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.conv3b = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.pool3 = nn.Conv3d(64, 64, kernel_size=(1, 2, 2), stride=(1, 2, 2), padding=(0,0,0)) + #### + ########self.conv4a = nn.Conv3d(256, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.conv4b = nn.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool4 = nn.Conv3d(512, 512, kernel_size=(1, 2, 2), stride=(1, 2, 2)) + #####self.conv4a = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + #####self.conv4b = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ######self.pool4 = nn.Conv3d(64, 32, kernel_size=(1, 2, 2), stride=(1, 2, 2), padding=(0,0,0)) + #####self.pool4 = nn.ConvTranspose3d(64, 32, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + #### + ########self.conv5a = nn.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.conv5b = nn.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool5 = nn.ConvTranspose3d(512, 128, kernel_size=(5, 3, 3), stride=(5, 1, 1), padding=(0, 1, 1)) + ####self.conv5a = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.conv5b = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.pool5 = nn.ConvTranspose3d(64, 32, kernel_size=(3, 3, 3), stride=(3, 1, 1), padding=(0, 1, 1)) + #####self.pool5 = nn.Conv3d(256, 256, kernel_size=(1, 2, 2), stride=(1, 2, 2)) + #### + ####self.relu = nn.ReLU() + ####self.final_activation = nn.Sigmoid() + ####self.dropout = nn.Dropout(p=0.50) + ########self.fc5 = nn.Linear(51200, NOTES) + ####self.fc5 = nn.Linear(65536, 208) + ####self.fc6 = nn.Linear(208, NOTES) + #### + #####self.rnn = nn.RNN(NOTES, NOTES, 1) + #####self.fc7 = nn.Linear(NOTES, NOTES) + #### + #####self.bn1 = nn.BatchNorm3d(16) + #####self.bn2 = nn.BatchNorm3d(32) + #####self.bn3 = nn.BatchNorm3d(64) + #####self.bn4 = nn.BatchNorm3d(64) + #####self.bn5 = nn.BatchNorm3d(64) + #####self.bn6 = nn.BatchNorm3d(64) + #####self.bn7 = nn.BatchNorm1d(208) + + self.video2roll_net = Video2RollNet.resnet18(num_classes=NOTES) + + def encode_frames(self, x, l): + #print("x input", x.shape, l) # [1, 1, 251, 100, 900] + b, c, t, w, h = x.shape + assert(c == 1) + + x_all = [] + for i in range(t): + frames = [] + for j in [-2, -1, 0, 1, 2]: + f = min(max(i+j, 0), t-1) + frames.append(x[:,:,f:f+1,:,:]) + frames = torch.cat(frames, dim=2) # [b, 1, 5, w, h] + x_all.append(frames) + x = torch.cat(x_all, dim=1).reshape(b*t, 5, w, h) # [b*t, 5, w, h] + #print("x", x.shape, l) # [251, 5, 100, 900] + x = self.video2roll_net(x) + x = nn.Sigmoid()(x) + #print("x output", x.shape) # [251, 51] + ####x = x.reshape(b, t, 1, NOTES).repeat(1,1,3,1).reshape(b, t*3, NOTES) + t5 = (t*5//2)*2 + x = x.reshape(b, t, 1, NOTES).repeat(1,1,5,1).reshape(b, t*5, NOTES)[:,:t5,:].reshape(b, t5//2, 2, NOTES).mean(2) + b, d, _ = x.shape + + #print("encode_frames", x.shape, l) + if d > l: + x = x[:,:l,:] + elif d < l: + x = torch.cat((x, torch.zeros(b,l-d,NOTES,device=x.device)), 1) + return x + + return x + + ####def encode_frames(self, x, l): + #### x = x[:,:3,:,...] + #### #print("x", x.shape) # [2, 6, 301, 320, 320] # [2, 3, 251, 128, 1024] + #### x = self.conv1(x) + #### #x = self.bn1(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### #print("conv1", x.shape) # [2, 64, 301, 320, 320] # [2, 16, 251, 128, 1024] + #### x = self.pool1(x) + #### #print("pool1", x.shape) # [2, 64, 301, 160, 160] # [2, 16, 251, 64, 512] + #### + #### x = self.conv2(x) + #### #x = self.bn2(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### #print("conv2", x.shape) # [2, 128, 301, 160, 160] # [2, 32, 250, 64, 512] + #### x = self.pool2(x) + #### #x = self.relu(x) + #### #x = self.dropout(x) + #### #print("pool2", x.shape) # [2, 128, 150, 80, 80] # [2, 32, 250, 32, 256] + #### + #### x = self.conv3a(x) + #### #x = self.bn3(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### x = self.conv3b(x) + #### #x = self.bn4(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### #print("conv3", x.shape) # [2, 256, 150, 80, 80] # [2, 64, 250, 32, 256] + #### x = self.pool3(x) + #### #x = self.relu(x) + #### #x = self.dropout(x) + #### #print("pool3", x.shape) # [2, 256, 150, 40, 40] # [2, 64, 250, 16, 128] + #### + #### #x = self.conv4a(x) + #### #x = self.relu(x) + #### ##x = self.dropout(x) + #### #x = self.conv4b(x) + #### #x = self.relu(x) + #### ##x = self.dropout(x) + #### ###print("conv4", x.shape) # [2, 512, 150, 40, 40] # [2, 64, 250, 16, 128] + #### #x = self.pool4(x) + #### ##print("pool4", x.shape) # [2, 512, 150, 20, 20] # [2, 32, 250, 8, 64] + #### + #### x = self.conv5a(x) + #### #x = self.bn5(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### x = self.conv5b(x) + #### #x = self.bn6(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### #print("conv5", x.shape) # [2, 512, 150, 20, 20] # [2, 64, 250, 16, 128] + #### x = self.pool5(x) + #### #x = self.relu(x) + #### #x = self.dropout(x) + #### #print("pool5", x.shape) # [2, 128, 750, 20, 20] # [2, 32, 750/250, 16, 128] + #### + #### b, c, d, w, h = x.shape + #### x = x.permute(0,2,3,4,1).reshape(b,d,w*h*c) + #### x = self.fc5(x) + #### #x = x.reshape(b,208,d) + #### #x = self.bn7(x) + #### #x = x.reshape(b,d,208) + #### x = self.relu(x) + #### x = self.dropout(x) + #### x = self.fc6(x) + #### + #### #x = self.relu(x) + #### #x, _ = self.rnn(x) + #### #x = self.fc7(x) + #### + #### x = self.final_activation(x) + #### + #### #x = x.reshape(b,d,1,NOTES).repeat(1,1,3,1).reshape(b,d*3,NOTES) + #### #d = d * 3 + #### + #### #print("encode_frames", x.shape, l) + #### if d > l: + #### x = x[:,:l,:] + #### elif d < l: + #### x = torch.cat((x, torch.zeros(b,l-d,NOTES,device=x.device)), 1) + #### return x + + @property + def device(self): + return next(self.parameters()).device + + def encode_text(self, prompt): + device = self.device + batch = self.tokenizer2(prompt, max_length=self.tokenizer2.model_max_length, padding=True, truncation=True, return_tensors="pt") + input_ids, attention_mask = batch.input_ids.to(device), batch.attention_mask.to(device) + + with torch.no_grad(): + encoder_hidden_states = self.text_encoder2(input_ids=input_ids, attention_mask=attention_mask)[0] + + boolean_encoder_mask = (attention_mask == 1).to(device) + return encoder_hidden_states, boolean_encoder_mask + + def encode_video(self, video_paths, l): + if self.proj_text is None: + d = self.dim_text + else: + d = self.dim_text_raw + device = self.device + b = 20 + with torch.no_grad(): + video_embeddings = [] + video_lens = [] + for video_path in video_paths: + if video_path is None: + video_embeddings.append(None) + video_lens.append(0) + continue + if isinstance(video_path, tuple): + video_path, start_sample, max_sample = video_path + else: + start_sample = 0 + max_sample = None + if video_path.startswith("/ailab-train2/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = video_path.replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = video_path.replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = video_path.replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = video_path.replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = video_path.replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = video_path.replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = video_path.replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = video_path.replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = video_path.replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = video_path.replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + + if not os.path.exists(feature_path): + #print("video not exist", video_path) + frames, duration = read_frames_with_moviepy(video_path, max_frame_nums=None) + if frames is None: + video_embeddings.append(None) + video_lens.append(0) + continue + if self.video_encoder in ["clip_vit", "clip_vit2", "dinov2"]: + images = self.image_processor(images=frames, return_tensors="pt").to(device) + #print("images", images["pixel_values"].shape, images["pixel_values"].max(), images["pixel_values"].min(), torch.abs(images["pixel_values"]).mean()) + elif self.video_encoder in ["clip_convnext"]: + images = [] + for i in range(frames.shape[0]): + images.append(self.image_processor(Image.fromarray(frames[i])).unsqueeze(0)) + images = torch.cat(images, dim=0).to(device) + #print("images", images.shape, images.max(), images.min(), torch.abs(images).mean()) + elif self.video_encoder in ["mixed"]: + #images1 = self.image_processor1(images=frames, return_tensors="pt").to(device) + images2 = self.image_processor2(images=frames, return_tensors="pt").to(device) + images4 = self.image_processor4(images=frames, return_tensors="pt").to(device) + images3 = [] + for i in range(frames.shape[0]): + images3.append(self.image_processor3(Image.fromarray(frames[i])).unsqueeze(0)) + images3 = torch.cat(images3, dim=0).to(device) + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + image_embeddings = [] + if self.video_encoder == "clip_vit": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + elif self.video_encoder == "clip_vit2": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + elif self.video_encoder == "clip_convnext": + for i in range(math.ceil(images.shape[0] / b)): + image_embeddings.append(self.image_encoder.encode_image(images[i*b: (i+1)*b]).cpu()) + elif self.video_encoder == "dinov2": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).pooler_output.cpu()) + elif self.video_encoder == "mixed": + feature_path1 = feature_path.replace("/feature_mixed/", "/feature/") + if not os.path.exists(feature_path1): + image_embeddings1 = [] + for i in range(math.ceil(images1["pixel_values"].shape[0] / b)): + image_embeddings1.append(self.image_encoder1(pixel_values=images1["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + image_embeddings1 = torch.cat(image_embeddings1, dim=0) + #np.savez(feature_path1, image_embeddings1, duration) + else: + data1 = np.load(feature_path1) + image_embeddings1 = torch.from_numpy(data1["arr_0"]) + feature_path2 = feature_path.replace("/feature_mixed/", "/feature_clip_vit2/") + if not os.path.exists(feature_path2): + image_embeddings2 = [] + for i in range(math.ceil(images2["pixel_values"].shape[0] / b)): + image_embeddings2.append(self.image_encoder2(pixel_values=images2["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + image_embeddings2 = torch.cat(image_embeddings2, dim=0) + np.savez(feature_path2, image_embeddings2, duration) + else: + data2 = np.load(feature_path2) + image_embeddings2 = torch.from_numpy(data2["arr_0"]) + feature_path3 = feature_path.replace("/feature_mixed/", "/feature_clip_convnext/") + if not os.path.exists(feature_path3): + image_embeddings3 = [] + for i in range(math.ceil(images3.shape[0] / b)): + image_embeddings3.append(self.image_encoder3.encode_image(images3[i*b: (i+1)*b]).cpu()) + image_embeddings3 = torch.cat(image_embeddings3, dim=0) + np.savez(feature_path3, image_embeddings3, duration) + else: + data3 = np.load(feature_path3) + image_embeddings3 = torch.from_numpy(data3["arr_0"]) + feature_path4 = feature_path.replace("/feature_mixed/", "/feature_dinov2/") + if not os.path.exists(feature_path4): + image_embeddings4 = [] + for i in range(math.ceil(images4["pixel_values"].shape[0] / b)): + image_embeddings4.append(self.image_encoder4(pixel_values=images4["pixel_values"][i*b: (i+1)*b]).pooler_output.cpu()) + image_embeddings4 = torch.cat(image_embeddings4, dim=0) + np.savez(feature_path4, image_embeddings4, duration) + else: + data4 = np.load(feature_path4) + image_embeddings4 = torch.from_numpy(data4["arr_0"]) + mixed_l = min([image_embeddings1.shape[0], image_embeddings2.shape[0], image_embeddings3.shape[0], image_embeddings4.shape[0]]) + for i in range(mixed_l): + image_embeddings.append(torch.cat([image_embeddings1[i:i+1,:], image_embeddings2[i:i+1,:], image_embeddings3[i:i+1,:], image_embeddings4[i:i+1,:]], dim=1)) + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + image_embeddings = torch.cat(image_embeddings, dim=0) + #print("image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + np.savez(feature_path, image_embeddings, duration) + else: + #print("video exist", feature_path) + data = np.load(feature_path) + image_embeddings = torch.from_numpy(data["arr_0"]) + #print("image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + duration = data["arr_1"].item() + if max_sample is None: + max_sample = int(duration * self.sampling_rate) + interpolated = [] + for i in range(start_sample, max_sample, self.frame_size): + j = min(round((i+self.frame_size//2) / self.sampling_rate / (duration / (image_embeddings.shape[0] - 1))), image_embeddings.shape[0] - 1) + interpolated.append(image_embeddings[j:j+1]) + if len(interpolated) >= l: + break + interpolated = torch.cat(interpolated, dim=0) + #ll = list(range(start_sample, max_sample, self.frame_size)) + #print("encode_video l", len(ll), l, round((ll[-1]+self.frame_size//2) / self.sampling_rate / (duration / (image_embeddings.shape[0] - 1))), image_embeddings.shape[0] - 1) + #print("encode_video one", video_path, duration, image_embeddings.shape, interpolated.shape, l) + video_embeddings.append(interpolated.unsqueeze(0)) + video_lens.append(interpolated.shape[1]) + max_length = max(video_lens) + if max_length == 0: + max_length = l + else: + max_length = l + for i in range(len(video_embeddings)): + if video_embeddings[i] is None: + video_embeddings[i] = torch.zeros(1, max_length, d) + continue + if video_embeddings[i].shape[1] < max_length: + video_embeddings[i] = torch.cat([video_embeddings[i], torch.zeros(1, max_length-video_embeddings[i].shape[1], d)], 1) + video_embeddings = torch.cat(video_embeddings, 0) + #print("encode_video", l, video_embeddings.shape, video_lens) + return video_embeddings.to(device) + + @staticmethod + def encode_video_frames(video_paths, l): + #### skip video frames + train_video_encoder = True + if not train_video_encoder: + midi_gts = [] + for video_path in video_paths: + if video_path is None: + #midi_gts.append(None) + continue + if isinstance(video_path, tuple): + video_path, start_sample, max_sample = video_path + else: + start_sample = 0 + max_sample = None + ####if video_path.startswith("/ailab-train2/speech/zhanghaomin/scps/instruments/"): + if "/piano_2h_cropped2_cuts/" in video_path: + pass + else: + #midi_gts.append(None) + continue + ####midi_gt + midi_gt = torch.from_numpy(np.load(video_path.replace(".mp4", ".3.npy")).astype(np.float32))[:,NOTTE_MIN:NOTE_MAX+1] + #print("midi_gt", midi_gt.shape, midi_gt.max(), midi_gt.min(), torch.abs(midi_gt).mean()) + midi_gts.append(midi_gt.unsqueeze(0)) + if len(midi_gts) == 0: + return None, None + max_length = l + for i in range(len(midi_gts)): + if midi_gts[i] is None: + midi_gts[i] = torch.zeros(1, max_length, NOTES) + continue + if midi_gts[i].shape[1] < max_length: + midi_gts[i] = torch.cat([midi_gts[i], torch.zeros(1, max_length-midi_gts[i].shape[1], NOTES)], 1) + elif midi_gts[i].shape[1] > max_length: + midi_gts[i] = midi_gts[i][:, :max_length, :] + midi_gts = torch.cat(midi_gts, 0) + video_frames = 1.0 + #print("encode_video_frames", l, midi_gts.shape, midi_gts.sum()) + return video_frames, midi_gts + + video_frames = [] + video_lens = [] + midi_gts = [] + for video_path in video_paths: + if video_path is None: + #video_frames.append(None) + video_lens.append(0) + #midi_gts.append(None) + continue + if isinstance(video_path, tuple): + video_path, start_sample, max_sample = video_path + else: + start_sample = 0 + max_sample = None + + ####if video_path.startswith("/ailab-train2/speech/zhanghaomin/scps/instruments/"): + if "/piano_2h_cropped2_cuts/" in video_path: + frames_raw_path = video_path.replace(".mp4", ".generated_frames_raw.2.npz") + if not os.path.exists(frames_raw_path): + frames, duration = read_frames_with_moviepy(video_path, max_frame_nums=None) + if frames is None: + #video_frames.append(None) + video_lens.append(0) + #midi_gts.append(None) + continue + #print("raw image size", frames.shape, video_path) + frames_resized = [] + for i in range(frames.shape[0]): + ########frames_resized.append(np.asarray(Image.fromarray(frames[i]).resize((320, 320)))) + ####frames_resized.append(np.asarray(Image.fromarray(frames[i]).resize((1024, 128)))) + + input_img = Image.fromarray(frames[i]).convert('L') + binarr = np.array(input_img) + input_img = Image.fromarray(binarr.astype(np.uint8)) + frames_resized.append(transform(input_img)) + ####frames_raw = np.array(frames_resized) + frames_raw = np.concatenate(frames_resized).astype(np.float32)[...,np.newaxis] + np.savez(frames_raw_path, frames_raw, duration) + else: + data = np.load(frames_raw_path) + frames_raw = data["arr_0"] + duration = data["arr_1"].item() + ####frames_raw = frames_raw.astype(np.float32) / 255.0 + #v_frames_raw = frames_raw[1:,:,:,:] - frames_raw[:-1,:,:,:] + #v_frames_raw = np.concatenate((np.zeros((1,v_frames_raw.shape[1],v_frames_raw.shape[2],v_frames_raw.shape[3]), dtype=np.float32), v_frames_raw), axis=0) + ##print("v_frames_raw", v_frames_raw.shape, v_frames_raw.max(), v_frames_raw.min(), np.abs(v_frames_raw).mean(), np.abs(v_frames_raw[0,:,:,:]).mean()) + #frames_raw = np.concatenate((frames_raw, v_frames_raw), axis=3) + frames_raw = torch.from_numpy(frames_raw) + #print("frames_raw", frames_raw.shape, frames_raw.max(), frames_raw.min(), torch.abs(frames_raw).mean(), "image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + else: + #video_frames.append(None) + video_lens.append(0) + #midi_gts.append(None) + continue + #print("frames_raw", frames_raw.shape, l) + + if max_sample is None: + max_sample = int(duration * 24000) + + ####video_multi = 3.0 + video_multi = 2.5 + + interpolated_frames_raw = [] + frame_size_video = int(video_multi*320) + for i in range(start_sample, max_sample+frame_size_video, frame_size_video): + j = min(round(i / 24000 / (duration / (frames_raw.shape[0] - 0))), frames_raw.shape[0] - 1) + #print(j) + interpolated_frames_raw.append(frames_raw[j:j+1]) + if len(interpolated_frames_raw) >= math.floor(l/video_multi)+1: + #print("break", len(interpolated_frames_raw), l, frames_raw.shape, j) + break + interpolated_frames_raw = torch.cat(interpolated_frames_raw, dim=0) + + ####v_interpolated_frames_raw = interpolated_frames_raw[1:,:,:,:] - interpolated_frames_raw[:-1,:,:,:] + ####v_interpolated_frames_raw = torch.cat((torch.zeros(1,v_interpolated_frames_raw.shape[1],v_interpolated_frames_raw.shape[2],v_interpolated_frames_raw.shape[3]), v_interpolated_frames_raw), 0) + #####print("v_interpolated_frames_raw", v_interpolated_frames_raw.shape, v_interpolated_frames_raw.max(), v_interpolated_frames_raw.min(), torch.abs(v_interpolated_frames_raw).mean(), torch.abs(v_interpolated_frames_raw[0,:,:,:]).mean()) + ####interpolated_frames_raw = torch.cat((interpolated_frames_raw, v_interpolated_frames_raw), 3) + + video_frames.append(interpolated_frames_raw.unsqueeze(0)) + video_lens.append(interpolated_frames_raw.shape[0]) + + ####midi_gt + ####midi_gt = torch.from_numpy(np.load(video_path.replace(".mp4", ".3.npy")).astype(np.float32))[:,NOTTE_MIN:NOTE_MAX+1] + #####print("midi_gt", midi_gt.shape, midi_gt.max(), midi_gt.min(), torch.abs(midi_gt).mean()) + ####midi_gts.append(midi_gt.unsqueeze(0)) + midi_gts.append(None) + + if len(video_frames) == 0: + return None, None + + max_length = max(video_lens) + if max_length == 0: + max_length = l + else: + max_length = l + max_length_video = max(math.floor(l/video_multi)+1, max(video_lens)) + + for i in range(len(video_frames)): + if video_frames[i] is None: + ########video_frames[i] = torch.zeros(1, max_length_video, 320, 320, 6) + ####video_frames[i] = torch.zeros(1, max_length_video, 128, 1024, 6) + video_frames[i] = torch.zeros(1, max_length_video, 100, 900, 1) + continue + if video_frames[i].shape[1] < max_length_video: + ########video_frames[i] = torch.cat([video_frames[i], torch.zeros(1, max_length_video-video_frames[i].shape[1], 320, 320, 6)], 1) + ####video_frames[i] = torch.cat([video_frames[i], torch.zeros(1, max_length_video-video_frames[i].shape[1], 128, 1024, 6)], 1) + video_frames[i] = torch.cat([video_frames[i], torch.zeros(1, max_length_video-video_frames[i].shape[1], 100, 900, 1)], 1) + video_frames = torch.cat(video_frames, 0) + video_frames = video_frames.permute(0,4,1,2,3) + for i in range(len(midi_gts)): + if midi_gts[i] is None: + midi_gts[i] = torch.zeros(1, max_length, NOTES) + continue + if midi_gts[i].shape[1] < max_length: + midi_gts[i] = torch.cat([midi_gts[i], torch.zeros(1, max_length-midi_gts[i].shape[1], NOTES)], 1) + elif midi_gts[i].shape[1] > max_length: + midi_gts[i] = midi_gts[i][:, :max_length, :] + midi_gts = torch.cat(midi_gts, 0) + #print("encode_video_frames", l, video_frames.shape, video_lens, midi_gts.shape, midi_gts.sum()) + return video_frames, midi_gts + + def transformer_with_pred_head( + self, + x: Float['b n d'], + cond: Float['b n d'] | None = None, + times: Float['b'] | None = None, + mask: Bool['b n'] | None = None, + text: Int['b nt'] | Float['b nt dt'] | None = None, + frames_embed: Float['b nf df'] | None = None, + prompt = None, + video_drop_prompt = None, + audio_drop_prompt = None, + drop_audio_cond: bool | None = None, + drop_text_cond: bool | None = None, + drop_text_prompt: bool | None = None, + return_drop_conditions = False + ): + seq_len = x.shape[-2] + bs = x.shape[0] + drop_audio_cond = [default(drop_audio_cond, self.training and random() < self.audiocond_drop_prob) for _ in range(bs)] + drop_text_cond = default(drop_text_cond, self.training and random() < self.cond_drop_prob) + drop_text_prompt = [default(drop_text_prompt, self.training and random() < self.prompt_drop_prob) for _ in range(bs)] + + if cond is not None: + for b in range(bs): + if drop_audio_cond[b]: + cond[b] = 0 + if audio_drop_prompt is not None and audio_drop_prompt[b]: + cond[b] = 0 + + if cond is not None: + if self.concat_cond: + # concat condition, given as using voicebox-like scheme + x = torch.cat((cond, x), dim = -1) + + x = self.proj_in(x) + + if cond is not None: + if not self.concat_cond: + # an alternative is to simply sum the condition + # seems to work fine + + cond = self.cond_proj_in(cond) + x = x + cond + + # whether to use a text embedding + + text_embed = None + if exists(text) and len(text.shape) == 3: + text_embed = text.clone() + if drop_text_cond: + for b in range(bs): + text_embed[b] = 0 + elif exists(text) and not drop_text_cond: + text_embed = self.embed_text(text, seq_len, mask = mask) + + context, context_mask = None, None + if prompt is not None: + #for b in range(bs): + # if drop_text_prompt[b]: + # prompt[b] = "" + if video_drop_prompt is not None: + for b in range(bs): + if video_drop_prompt[b]: + prompt[b] = "the sound of X X" + context, context_mask = self.encode_text(prompt) + for b in range(bs): + if drop_text_prompt[b]: + context[b] = 0 + if video_drop_prompt is not None and video_drop_prompt[b]: + context[b] = 0 + #print("cross attention", context.shape, context_mask.shape, x.shape, mask.shape, text_embed.shape if text_embed is not None else None, torch.mean(torch.abs(text_embed), dim=(1,2))) + #print("video_drop_prompt", prompt, video_drop_prompt, context.shape, torch.mean(torch.abs(context), dim=(1,2))) + #print("audio_drop_prompt", audio_drop_prompt, cond.shape, torch.mean(torch.abs(cond), dim=(1,2))) + + if self.proj_text is not None: + text_embed = self.proj_text(text_embed) + frames_embed = self.proj_frames(frames_embed) + + # attend + + attended = self.transformer( + x, + times = times, + mask = mask, + text_embed = text_embed, + frames_embed = frames_embed, + context = context, + context_mask = context_mask + ) + + pred = self.to_pred(attended) + + if not return_drop_conditions: + return pred + + return pred, drop_audio_cond, drop_text_cond, drop_text_prompt + + def cfg_transformer_with_pred_head( + self, + *args, + cfg_strength: float = 1., + remove_parallel_component: bool = True, + keep_parallel_frac: float = 0., + **kwargs, + ): + + pred = self.transformer_with_pred_head(*args, drop_audio_cond = False, drop_text_cond = False, drop_text_prompt = False, **kwargs) + + if cfg_strength < 1e-5: + return pred + + null_pred = self.transformer_with_pred_head(*args, drop_audio_cond = True, drop_text_cond = True, drop_text_prompt = True, **kwargs) + + cfg_update = pred - null_pred + + if remove_parallel_component: + # https://arxiv.org/abs/2410.02416 + parallel, orthogonal = project(cfg_update, pred) + cfg_update = orthogonal + parallel * keep_parallel_frac + + return pred + cfg_update * cfg_strength + + def add_noise(self, signal, mask, val): + if self.audiocond_snr is None: + return signal + if not val: + snr = np.random.uniform(self.audiocond_snr[0], self.audiocond_snr[1]) + else: + snr = (self.audiocond_snr[0] + self.audiocond_snr[1]) / 2.0 + #print("add_noise", self.audiocond_snr, snr, signal.shape, mask) # [True, ..., False] + noise = torch.randn_like(signal) + w = torch.abs(signal[mask]).mean() / (torch.abs(noise[mask]).mean() + 1e-6) / snr + return signal + noise * w + + @torch.no_grad() + def sample( + self, + cond: Float['b n d'] | Float['b nw'] | None = None, + *, + text: Int['b nt'] | list[str] | None = None, + lens: Int['b'] | None = None, + duration: int | Int['b'] | None = None, + steps = 32, + cfg_strength = 1., # they used a classifier free guidance strength of 1. + remove_parallel_component = True, + sway_sampling = True, + max_duration = 4096, # in case the duration predictor goes haywire + vocoder: Callable[[Float['b d n']], list[Float['_']]] | None = None, + return_raw_output: bool | None = None, + save_to_filename: str | None = None, + prompt = None, + video_drop_prompt = None, + audio_drop_prompt = None, + video_paths = None, + frames = None, + midis = None + ) -> ( + Float['b n d'], + list[Float['_']] + ): + self.eval() + + # raw wave + + if cond.ndim == 2: + cond = self.mel_spec(cond) + cond = rearrange(cond, 'b d n -> b n d') + assert cond.shape[-1] == self.num_channels + + batch, cond_seq_len, device = *cond.shape[:2], cond.device + + if frames is None: + frames_embed = torch.zeros(batch, cond_seq_len, NOTES, device=device) + else: + #### sampling settings + train_video_encoder = True + if train_video_encoder: + frames_embed = self.encode_frames(frames, cond_seq_len) + else: + frames_embed = midis + if frames_embed.shape[1] < cond_seq_len: + frames_embed = torch.cat([frames_embed, torch.zeros(1, cond_seq_len-frames_embed.shape[1], NOTES)], 1) + elif frames_embed.shape[1] > cond_seq_len: + frames_embed = frames_embed[:, :cond_seq_len, :] + #x0 = torch.zeros(batch, cond_seq_len, 128, device=device) + print("frames_embed midis cond", frames_embed.shape if frames_embed is not None and not isinstance(frames_embed, float) else frames_embed, frames_embed.sum() if frames_embed is not None and not isinstance(frames_embed, float) else frames_embed, midis.shape if midis is not None else midis, midis.sum() if midis is not None else midis, cond.shape if cond is not None else cond, cond.sum() if cond is not None else cond) + + if not exists(lens): + lens = torch.full((batch,), cond_seq_len, device = device, dtype = torch.long) + + if video_paths is not None: + text = self.encode_video(video_paths, cond_seq_len) + # text + elif isinstance(text, list): + text = self.tokenizer(text).to(device) + assert text.shape[0] == batch + + if exists(text): + text_lens = (text != -1).sum(dim = -1) + lens = torch.maximum(text_lens, lens) # make sure lengths are at least those of the text characters + + # duration + + cond_mask = lens_to_mask(lens) + + if exists(duration): + if isinstance(duration, int): + duration = torch.full((batch,), duration, device = device, dtype = torch.long) + + elif exists(self.duration_predictor): + duration = self.duration_predictor(cond, text = text, lens = lens, return_loss = False).long() + + duration = torch.maximum(lens, duration) # just add one token so something is generated + duration = duration.clamp(max = max_duration) + + assert duration.shape[0] == batch + + max_duration = duration.amax() + + cond = F.pad(cond, (0, 0, 0, max_duration - cond_seq_len), value = 0.) + cond_mask = F.pad(cond_mask, (0, max_duration - cond_mask.shape[-1]), value = False) + cond_mask = rearrange(cond_mask, '... -> ... 1') + + mask = lens_to_mask(duration) + #print("mask", duration, mask, mask.shape, lens, cond_mask, cond_mask.shape, text) + + # neural ode + + def fn(t, x): + # at each step, conditioning is fixed + + if lens[0] == duration[0]: + print("No cond", lens, duration) + step_cond = None + else: + step_cond = torch.where(cond_mask, self.add_noise(cond, cond_mask, True), torch.zeros_like(cond)) + #step_cond = cond + + # predict flow + + return self.cfg_transformer_with_pred_head( + x, + step_cond, + times = t, + text = text, + frames_embed = frames_embed, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + cfg_strength = cfg_strength, + remove_parallel_component = remove_parallel_component + ) + + ####torch.manual_seed(0) + y0 = torch.randn_like(cond) + #y0 = torch.randn_like(x0) + t = torch.linspace(0, 1, steps, device = self.device) + if sway_sampling: + t = t + -1.0 * (torch.cos(torch.pi / 2 * t) - 1 + t) + #print("@@@@", t) + + trajectory = odeint(fn, y0, t, **self.odeint_kwargs) + sampled = trajectory[-1] + + out = sampled + + if lens[0] != duration[0]: + out = torch.where(cond_mask, cond, out) + + # able to return raw untransformed output, if not using mel rep + + if exists(return_raw_output) and return_raw_output: + return out + + # take care of transforming mel to audio if `vocoder` is passed in, or if `use_vocos` is turned on + + if exists(vocoder): + assert not exists(self.vocos), '`use_vocos` should not be turned on if you are passing in a custom `vocoder` on sampling' + out = rearrange(out, 'b n d -> b d n') + out = vocoder(out) + + elif exists(self.vocos): + + audio = [] + for mel, one_mask in zip(out, mask): + #one_out = DB_to_amplitude(mel[one_mask], ref = 1., power = 0.5) + one_out = mel[one_mask] + + one_out = rearrange(one_out, 'n d -> 1 d n') + one_audio = self.vocos.decode(one_out) + one_audio = rearrange(one_audio, '1 nw -> nw') + audio.append(one_audio) + + out = audio + + if exists(save_to_filename): + assert exists(vocoder) or exists(self.vocos) + assert exists(self.sampling_rate) + + path = Path(save_to_filename) + parent_path = path.parents[0] + parent_path.mkdir(exist_ok = True, parents = True) + + for ind, one_audio in enumerate(out): + one_audio = rearrange(one_audio, 'nw -> 1 nw') + if len(out) == 1: + save_path = str(parent_path / f'{path.name}') + else: + save_path = str(parent_path / f'{ind + 1}.{path.name}') + torchaudio.save(save_path, one_audio.detach().cpu(), sample_rate = self.sampling_rate) + + return out + + def forward( + self, + inp: Float['b n d'] | Float['b nw'], # mel or raw wave + *, + text: Int['b nt'] | list[str] | None = None, + times: int | Int['b'] | None = None, + lens: Int['b'] | None = None, + velocity_consistency_model: E2TTS | None = None, + velocity_consistency_delta = 1e-3, + prompt = None, + video_drop_prompt=None, + audio_drop_prompt=None, + val = False, + video_paths=None, + frames=None, + midis=None + ): + need_velocity_loss = exists(velocity_consistency_model) and self.velocity_consistency_weight > 0. + + # handle raw wave + + if inp.ndim == 2: + inp = self.mel_spec(inp) + inp = rearrange(inp, 'b d n -> b n d') + assert inp.shape[-1] == self.num_channels + + batch, seq_len, dtype, device = *inp.shape[:2], inp.dtype, self.device + + if video_paths is not None: + text = self.encode_video(video_paths, seq_len) + # handle text as string + elif isinstance(text, list): + text = self.tokenizer(text).to(device) + #print("text tokenized", text[0]) + assert text.shape[0] == batch + + # lens and mask + + if not exists(lens): + lens = torch.full((batch,), seq_len, device = device) + + mask = lens_to_mask(lens, length = seq_len) + + # get a random span to mask out for training conditionally + + if not val: + if self.audiocond_drop_prob > 1.0: + frac_lengths = torch.zeros((batch,), device = self.device).float().uniform_(1.0,1.0) + else: + frac_lengths = torch.zeros((batch,), device = self.device).float().uniform_(*self.frac_lengths_mask) + else: + frac_lengths = torch.tensor([(0.7+1.0)/2.0]*batch, device = self.device).float() + rand_span_mask = mask_from_frac_lengths(lens, frac_lengths, max_length = seq_len, val = val) + + if exists(mask): + rand_span_mask &= mask + + # mel is x1 + + x1 = inp + + # main conditional flow training logic + # just ~5 loc + + # x0 is gaussian noise + + if val: + torch.manual_seed(0) + x0 = torch.randn_like(x1) + if val: + torch.manual_seed(int(time.time()*1000)) + + # t is random times from above + + if times is None: + times = torch.rand((batch,), dtype = dtype, device = self.device) + else: + times = torch.tensor((times,)*batch, dtype = dtype, device = self.device) + t = rearrange(times, 'b -> b 1 1') + + # if need velocity consistency, make sure time does not exceed 1. + + if need_velocity_loss: + t = t * (1. - velocity_consistency_delta) + + # sample xt (w in the paper) + + w = (1. - t) * x0 + t * x1 + + flow = x1 - x0 + + # only predict what is within the random mask span for infilling + + if self.audiocond_drop_prob > 1.0: + cond = None + else: + cond = einx.where( + 'b n, b n d, b n d -> b n d', + rand_span_mask, + torch.zeros_like(x1), self.add_noise(x1, ~rand_span_mask, val) + ) + + #### training settings + train_video_encoder = True + train_v2a = True + use_midi_gt = False + train_video_encoder = train_video_encoder + ####train_v2a = train_v2a or val + #print("train_video_encoder", train_video_encoder, use_midi_gt, train_v2a) + + #### + if frames is None: + frames_embed = torch.zeros(batch, seq_len, NOTES, device=device) + midis = torch.zeros(batch, seq_len, NOTES, device=device) + else: + if train_video_encoder: + frames_embed = self.encode_frames(frames, seq_len) + else: + frames_embed = midis + #print("frames_embed midis cond", frames_embed.shape if frames_embed is not None and not isinstance(frames_embed, float) else frames_embed, frames_embed.sum() if frames_embed is not None and not isinstance(frames_embed, float) else frames_embed, midis.shape, midis.sum(), cond.shape if cond is not None else cond, cond.sum() if cond is not None else cond, x1.shape) + if train_video_encoder: + #lw = 1.0 + lw = torch.abs(midis-0.10) + #lw = torch.max(torch.abs(midis-0.20), torch.tensor(0.20)) + loss_midi = F.mse_loss(frames_embed, midis, reduction = 'none') * lw + #loss_midi = nn.BCELoss(reduction = 'none')(frames_embed, midis) * lw + #print("loss_midi", loss_midi.shape, mask.shape, mask, rand_span_mask.shape, rand_span_mask) + loss_midi = loss_midi[mask[-frames_embed.shape[0]:,...]].mean() + + b, t, f = frames_embed.shape + frames_embed_t = frames_embed[:,:(t//3)*3,:].reshape(b,t//3,3,f).mean(dim=2) + midis_t = midis[:,:(t//3)*3,:].reshape(b,t//3,3,f).mean(dim=2) + mask_t = mask[-frames_embed.shape[0]:,:(t//3)*3].reshape(b,t//3,3).to(torch.float32).mean(dim=2) >= 0.99 + tp = ((frames_embed_t>=0.4)*(midis_t>=0.5)).to(torch.float)[mask_t[-frames_embed_t.shape[0]:,...]].sum() + fp = ((frames_embed_t>=0.4)*(midis_t<0.5)).to(torch.float)[mask_t[-frames_embed_t.shape[0]:,...]].sum() + fn = ((frames_embed_t<0.4)*(midis_t>=0.5)).to(torch.float)[mask_t[-frames_embed_t.shape[0]:,...]].sum() + tn = ((frames_embed_t<0.4)*(midis_t<0.5)).to(torch.float)[mask_t[-frames_embed_t.shape[0]:,...]].sum() + #print("tp fp fn tn", tp, fp, fn, tn) + pre = tp / (tp + fp) if (tp + fp) != 0 else torch.tensor(0.0, device=device) + rec = tp / (tp + fn) if (tp + fn) != 0 else torch.tensor(0.0, device=device) + f1 = 2 * tp / (2 * tp + fp + fn) if (2 * tp + fp + fn) != 0 else torch.tensor(0.0, device=device) + acc = tp / (tp + fp + fn) if (tp + fp + fn) != 0 else torch.tensor(0.0, device=device) + else: + loss_midi = torch.tensor(0.0, device=device) + + tp = torch.tensor(0.0, device=device) + fp = torch.tensor(0.0, device=device) + fn = torch.tensor(0.0, device=device) + tn = torch.tensor(0.0, device=device) + pre = torch.tensor(0.0, device=device) + rec = torch.tensor(0.0, device=device) + f1 = torch.tensor(0.0, device=device) + acc = torch.tensor(0.0, device=device) + #if train_video_encoder: # loss_midi_zeros * 100.0 # 0.2131/0.1856 # 0.2819/0.2417 # 2.451/ + # loss_midi_zeros = F.mse_loss(torch.zeros_like(midis), midis, reduction = 'none') + # loss_midi_zeros = loss_midi_zeros[mask[-frames_embed.shape[0]:,...]].mean() + #else: + # loss_midi_zeros = torch.tensor(0.0, device=device) + + if train_v2a: + if use_midi_gt: + frames_embed = midis + if frames_embed.shape[0] < x1.shape[0]: + frames_embed = torch.cat((torch.zeros(x1.shape[0]-frames_embed.shape[0],frames_embed.shape[1],frames_embed.shape[2],device=frames_embed.device), frames_embed), 0) + + # transformer and prediction head + + if not val: + pred, did_drop_audio_cond, did_drop_text_cond, did_drop_text_prompt = self.transformer_with_pred_head( + w, + cond, + times = times, + text = text, + frames_embed = frames_embed, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + return_drop_conditions = True + ) + else: + pred, did_drop_audio_cond, did_drop_text_cond, did_drop_text_prompt = self.transformer_with_pred_head( + w, + cond, + times = times, + text = text, + frames_embed = frames_embed, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + drop_audio_cond = False, + drop_text_cond = False, + drop_text_prompt = False, + return_drop_conditions = True + ) + + # maybe velocity consistency loss + + velocity_loss = self.zero + + if need_velocity_loss: + + #t_with_delta = t + velocity_consistency_delta + #w_with_delta = (1. - t_with_delta) * x0 + t_with_delta * x1 + + with torch.no_grad(): + ema_pred = velocity_consistency_model.transformer_with_pred_head( + w, #w_with_delta, + cond, + times = times, #times + velocity_consistency_delta, + text = text, + frames_embed = frames_embed, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + drop_audio_cond = did_drop_audio_cond, + drop_text_cond = did_drop_text_cond, + drop_text_prompt = did_drop_text_prompt + ) + + #velocity_loss = F.mse_loss(pred, ema_pred, reduction = 'none') + velocity_loss = F.mse_loss(ema_pred, flow, reduction = 'none') + velocity_loss = (velocity_loss.mean(-1)*rand_span_mask).mean(-1) #.mean() + + ref_losses = velocity_loss[-2:, ...] + ref_losses_w, ref_losses_l = ref_losses.chunk(2) + raw_ref_loss = 0.5 * (ref_losses_w.mean() + ref_losses_l.mean()) + ref_diff = ref_losses_w - ref_losses_l + else: + ref_losses_w, ref_losses_l = 0, 0 + + # flow matching loss + + loss = F.mse_loss(pred, flow, reduction = 'none') + + #print("loss", loss.shape, loss, "rand_span_mask", rand_span_mask.shape, rand_span_mask, "loss[rand_span_mask]", loss[rand_span_mask].shape, loss[rand_span_mask]) + + #### dpo + loss = loss[rand_span_mask].mean() + loss_dpo = torch.tensor(0.0, device=device) + ####if val: + #### loss = loss[rand_span_mask].mean() + #### loss_dpo = torch.tensor(0.0, device=device) + #### model_losses_w, model_losses_l = 0, 0 + ####else: + #### loss_fm = loss[rand_span_mask].mean() + #### loss = (loss.mean(-1)*rand_span_mask).mean(-1) #.mean() + #### + #### model_losses = loss[-2:, ...] + #### model_losses_w, model_losses_l = model_losses.chunk(2) + #### raw_model_loss = 0.5 * (model_losses_w.mean() + model_losses_l.mean()) + #### model_diff = model_losses_w - model_losses_l + #### + #### scale_term = -1 + #### inside_term = scale_term * (model_diff - ref_diff) + #### loss_dpo = -1 * F.logsigmoid(inside_term).mean() + #### loss = loss_fm + #### dpo + else: + pred = torch.zeros_like(x0) + loss = torch.tensor(0.0, device=device) + + # total loss and get breakdown + + #midi_w = 100.0 + midi_w = 10.0 + #total_loss = loss + #total_loss = loss + loss_midi * midi_w + total_loss = loss + loss_midi * midi_w + loss_dpo + ####breakdown = LossBreakdown(loss, loss_midi * midi_w, pre, rec) + breakdown = LossBreakdown(pre, rec, f1, acc) + #breakdown = LossBreakdown(tp, fp, fn, tn) + #### dpo + print("loss", loss, loss_midi * midi_w) + #print("loss", loss, loss_midi * midi_w, loss_dpo, model_losses_w, model_losses_l, ref_losses_w, ref_losses_l) + #### dpo + + # return total loss and bunch of intermediates + + return E2TTSReturn(total_loss, cond if cond is not None else w, pred, x0 + pred, breakdown) diff --git a/src/e2_tts_pytorch/e2_tts_crossatt3_2.py b/src/e2_tts_pytorch/e2_tts_crossatt3_2.py new file mode 100644 index 0000000000000000000000000000000000000000..059d9f2a7cce087904daa194a4443d257f1be402 --- /dev/null +++ b/src/e2_tts_pytorch/e2_tts_crossatt3_2.py @@ -0,0 +1,2584 @@ +""" +ein notation: +b - batch +n - sequence +nt - text sequence +nw - raw wave length +d - dimension +dt - dimension text +""" + +from __future__ import annotations + +from pathlib import Path +from random import random +from functools import partial +from itertools import zip_longest +from collections import namedtuple + +from typing import Literal, Callable + +import jaxtyping +from beartype import beartype + +import torch +import torch.nn.functional as F +from torch import nn, tensor, Tensor, from_numpy +from torch.nn import Module, ModuleList, Sequential, Linear +from torch.nn.utils.rnn import pad_sequence + +import torchaudio +from torchaudio.functional import DB_to_amplitude +from torchdiffeq import odeint + +import einx +from einops.layers.torch import Rearrange +from einops import rearrange, repeat, reduce, pack, unpack + +from x_transformers import ( + Attention, + FeedForward, + RMSNorm, + AdaptiveRMSNorm, +) + +from x_transformers.x_transformers import RotaryEmbedding + +import sys +sys.path.insert(0, "/zhanghaomin/codes3/vocos-main/") +from vocos import Vocos + +from transformers import AutoTokenizer +from transformers import T5EncoderModel +from transformers import EncodecModel, AutoProcessor + +sys.path.insert(0, "./src/audeo/") +import Video2RollNet +import torchvision.transforms as transforms + + +####transform = transforms.Compose([lambda x: x.resize((900,100)), +#### lambda x: np.reshape(x,(100,900,1)), +#### lambda x: np.transpose(x,[2,0,1]), +#### lambda x: x/255.]) + +transform = transforms.Compose([lambda x: x.resize((100,900)), + lambda x: np.reshape(x,(900,100,1)), + lambda x: np.transpose(x,[2,1,0]), + lambda x: x/255.]) + +####NOTES = 51 +####NOTTE_MIN = 15 +####NOTE_MAX = 65 + +NOTES = 88 +NOTTE_MIN = 0#15 +NOTE_MAX = 87#72 + + +import os +import math +import traceback +import numpy as np +from moviepy.editor import AudioFileClip, VideoFileClip +from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection +#import open_clip +from transformers import AutoImageProcessor, AutoModel +from PIL import Image +import time + +import warnings +warnings.filterwarnings("ignore") + +def normalize_wav(waveform): + waveform = waveform - torch.mean(waveform) + waveform = waveform / (torch.max(torch.abs(waveform[0, :])) + 1e-8) + return waveform * 0.5 + +def read_frames_with_moviepy(video_path, max_frame_nums=None): + try: + clip = VideoFileClip(video_path) + duration = clip.duration + frames = [] + for frame in clip.iter_frames(): + frames.append(frame) + except: + print("Error read_frames_with_moviepy", video_path) + traceback.print_exc() + return None, None + if max_frame_nums is not None: + frames_idx = np.linspace(0, len(frames) - 1, max_frame_nums, dtype=int) + return np.array(frames)[frames_idx, ...], duration + else: + return np.array(frames), duration + +pad_sequence = partial(pad_sequence, batch_first = True) + +# constants + +class TorchTyping: + def __init__(self, abstract_dtype): + self.abstract_dtype = abstract_dtype + + def __getitem__(self, shapes: str): + return self.abstract_dtype[Tensor, shapes] + +Float = TorchTyping(jaxtyping.Float) +Int = TorchTyping(jaxtyping.Int) +Bool = TorchTyping(jaxtyping.Bool) + +# named tuples + +LossBreakdown = namedtuple('LossBreakdown', ['flow', 'velocity_consistency', 'a', 'b']) + +E2TTSReturn = namedtuple('E2TTS', ['loss', 'cond', 'pred_flow', 'pred_data', 'loss_breakdown']) + +# helpers + +def exists(v): + return v is not None + +def default(v, d): + return v if exists(v) else d + +def divisible_by(num, den): + return (num % den) == 0 + +def pack_one_with_inverse(x, pattern): + packed, packed_shape = pack([x], pattern) + + def inverse(x, inverse_pattern = None): + inverse_pattern = default(inverse_pattern, pattern) + return unpack(x, packed_shape, inverse_pattern)[0] + + return packed, inverse + +class Identity(Module): + def forward(self, x, **kwargs): + return x + +# tensor helpers + +def project(x, y): + x, inverse = pack_one_with_inverse(x, 'b *') + y, _ = pack_one_with_inverse(y, 'b *') + + dtype = x.dtype + x, y = x.double(), y.double() + unit = F.normalize(y, dim = -1) + + parallel = (x * unit).sum(dim = -1, keepdim = True) * unit + orthogonal = x - parallel + + return inverse(parallel).to(dtype), inverse(orthogonal).to(dtype) + +# simple utf-8 tokenizer, since paper went character based + +def list_str_to_tensor( + text: list[str], + padding_value = -1 +) -> Int['b nt']: + + list_tensors = [tensor([*bytes(t, 'UTF-8')]) for t in text] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + +# simple english phoneme-based tokenizer + +from g2p_en import G2p +import jieba +from pypinyin import lazy_pinyin, Style + +def get_g2p_en_encode(): + g2p = G2p() + + # used by @lucasnewman successfully here + # https://github.com/lucasnewman/e2-tts-pytorch/blob/ljspeech-test/e2_tts_pytorch/e2_tts.py + + phoneme_to_index = g2p.p2idx + num_phonemes = len(phoneme_to_index) + + extended_chars = [' ', ',', '.', '-', '!', '?', '\'', '"', '...', '..', '. .', '. . .', '. . . .', '. . . . .', '. ...', '... .', '.. ..'] + num_extended_chars = len(extended_chars) + + extended_chars_dict = {p: (num_phonemes + i) for i, p in enumerate(extended_chars)} + phoneme_to_index = {**phoneme_to_index, **extended_chars_dict} + + def encode( + text: list[str], + padding_value = -1 + ) -> Int['b nt']: + + phonemes = [g2p(t) for t in text] + list_tensors = [tensor([phoneme_to_index[p] for p in one_phoneme]) for one_phoneme in phonemes] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + + return encode, (num_phonemes + num_extended_chars) + +def all_en(word): + res = word.replace("'", "").encode('utf-8').isalpha() + return res + +def all_ch(word): + res = True + for w in word: + if not '\u4e00' <= w <= '\u9fff': + res = False + return res + +def get_g2p_zh_encode(): + puncs = ['，', '。', '？', '、'] + pinyins = ['a', 'a1', 'ai1', 'ai2', 'ai3', 'ai4', 'an1', 'an3', 'an4', 'ang1', 'ang2', 'ang4', 'ao1', 'ao2', 'ao3', 'ao4', 'ba', 'ba1', 'ba2', 'ba3', 'ba4', 'bai1', 'bai2', 'bai3', 'bai4', 'ban1', 'ban2', 'ban3', 'ban4', 'bang1', 'bang2', 'bang3', 'bang4', 'bao1', 'bao2', 'bao3', 'bao4', 'bei', 'bei1', 'bei2', 'bei3', 'bei4', 'ben1', 'ben2', 'ben3', 'ben4', 'beng1', 'beng2', 'beng4', 'bi1', 'bi2', 'bi3', 'bi4', 'bian1', 'bian2', 'bian3', 'bian4', 'biao1', 'biao2', 'biao3', 'bie1', 'bie2', 'bie3', 'bie4', 'bin1', 'bin4', 'bing1', 'bing2', 'bing3', 'bing4', 'bo', 'bo1', 'bo2', 'bo3', 'bo4', 'bu2', 'bu3', 'bu4', 'ca1', 'cai1', 'cai2', 'cai3', 'cai4', 'can1', 'can2', 'can3', 'can4', 'cang1', 'cang2', 'cao1', 'cao2', 'cao3', 'ce4', 'cen1', 'cen2', 'ceng1', 'ceng2', 'ceng4', 'cha1', 'cha2', 'cha3', 'cha4', 'chai1', 'chai2', 'chan1', 'chan2', 'chan3', 'chan4', 'chang1', 'chang2', 'chang3', 'chang4', 'chao1', 'chao2', 'chao3', 'che1', 'che2', 'che3', 'che4', 'chen1', 'chen2', 'chen3', 'chen4', 'cheng1', 'cheng2', 'cheng3', 'cheng4', 'chi1', 'chi2', 'chi3', 'chi4', 'chong1', 'chong2', 'chong3', 'chong4', 'chou1', 'chou2', 'chou3', 'chou4', 'chu1', 'chu2', 'chu3', 'chu4', 'chua1', 'chuai1', 'chuai2', 'chuai3', 'chuai4', 'chuan1', 'chuan2', 'chuan3', 'chuan4', 'chuang1', 'chuang2', 'chuang3', 'chuang4', 'chui1', 'chui2', 'chun1', 'chun2', 'chun3', 'chuo1', 'chuo4', 'ci1', 'ci2', 'ci3', 'ci4', 'cong1', 'cong2', 'cou4', 'cu1', 'cu4', 'cuan1', 'cuan2', 'cuan4', 'cui1', 'cui3', 'cui4', 'cun1', 'cun2', 'cun4', 'cuo1', 'cuo2', 'cuo4', 'da', 'da1', 'da2', 'da3', 'da4', 'dai1', 'dai3', 'dai4', 'dan1', 'dan2', 'dan3', 'dan4', 'dang1', 'dang2', 'dang3', 'dang4', 'dao1', 'dao2', 'dao3', 'dao4', 'de', 'de1', 'de2', 'dei3', 'den4', 'deng1', 'deng2', 'deng3', 'deng4', 'di1', 'di2', 'di3', 'di4', 'dia3', 'dian1', 'dian2', 'dian3', 'dian4', 'diao1', 'diao3', 'diao4', 'die1', 'die2', 'ding1', 'ding2', 'ding3', 'ding4', 'diu1', 'dong1', 'dong3', 'dong4', 'dou1', 'dou2', 'dou3', 'dou4', 'du1', 'du2', 'du3', 'du4', 'duan1', 'duan2', 'duan3', 'duan4', 'dui1', 'dui4', 'dun1', 'dun3', 'dun4', 'duo1', 'duo2', 'duo3', 'duo4', 'e1', 'e2', 'e3', 'e4', 'ei2', 'en1', 'en4', 'er', 'er2', 'er3', 'er4', 'fa1', 'fa2', 'fa3', 'fa4', 'fan1', 'fan2', 'fan3', 'fan4', 'fang1', 'fang2', 'fang3', 'fang4', 'fei1', 'fei2', 'fei3', 'fei4', 'fen1', 'fen2', 'fen3', 'fen4', 'feng1', 'feng2', 'feng3', 'feng4', 'fo2', 'fou2', 'fou3', 'fu1', 'fu2', 'fu3', 'fu4', 'ga1', 'ga2', 'ga4', 'gai1', 'gai3', 'gai4', 'gan1', 'gan2', 'gan3', 'gan4', 'gang1', 'gang2', 'gang3', 'gang4', 'gao1', 'gao2', 'gao3', 'gao4', 'ge1', 'ge2', 'ge3', 'ge4', 'gei2', 'gei3', 'gen1', 'gen2', 'gen3', 'gen4', 'geng1', 'geng3', 'geng4', 'gong1', 'gong3', 'gong4', 'gou1', 'gou2', 'gou3', 'gou4', 'gu', 'gu1', 'gu2', 'gu3', 'gu4', 'gua1', 'gua2', 'gua3', 'gua4', 'guai1', 'guai2', 'guai3', 'guai4', 'guan1', 'guan2', 'guan3', 'guan4', 'guang1', 'guang2', 'guang3', 'guang4', 'gui1', 'gui2', 'gui3', 'gui4', 'gun3', 'gun4', 'guo1', 'guo2', 'guo3', 'guo4', 'ha1', 'ha2', 'ha3', 'hai1', 'hai2', 'hai3', 'hai4', 'han1', 'han2', 'han3', 'han4', 'hang1', 'hang2', 'hang4', 'hao1', 'hao2', 'hao3', 'hao4', 'he1', 'he2', 'he4', 'hei1', 'hen2', 'hen3', 'hen4', 'heng1', 'heng2', 'heng4', 'hong1', 'hong2', 'hong3', 'hong4', 'hou1', 'hou2', 'hou3', 'hou4', 'hu1', 'hu2', 'hu3', 'hu4', 'hua1', 'hua2', 'hua4', 'huai2', 'huai4', 'huan1', 'huan2', 'huan3', 'huan4', 'huang1', 'huang2', 'huang3', 'huang4', 'hui1', 'hui2', 'hui3', 'hui4', 'hun1', 'hun2', 'hun4', 'huo', 'huo1', 'huo2', 'huo3', 'huo4', 'ji1', 'ji2', 'ji3', 'ji4', 'jia', 'jia1', 'jia2', 'jia3', 'jia4', 'jian1', 'jian2', 'jian3', 'jian4', 'jiang1', 'jiang2', 'jiang3', 'jiang4', 'jiao1', 'jiao2', 'jiao3', 'jiao4', 'jie1', 'jie2', 'jie3', 'jie4', 'jin1', 'jin2', 'jin3', 'jin4', 'jing1', 'jing2', 'jing3', 'jing4', 'jiong3', 'jiu1', 'jiu2', 'jiu3', 'jiu4', 'ju1', 'ju2', 'ju3', 'ju4', 'juan1', 'juan2', 'juan3', 'juan4', 'jue1', 'jue2', 'jue4', 'jun1', 'jun4', 'ka1', 'ka2', 'ka3', 'kai1', 'kai2', 'kai3', 'kai4', 'kan1', 'kan2', 'kan3', 'kan4', 'kang1', 'kang2', 'kang4', 'kao2', 'kao3', 'kao4', 'ke1', 'ke2', 'ke3', 'ke4', 'ken3', 'keng1', 'kong1', 'kong3', 'kong4', 'kou1', 'kou2', 'kou3', 'kou4', 'ku1', 'ku2', 'ku3', 'ku4', 'kua1', 'kua3', 'kua4', 'kuai3', 'kuai4', 'kuan1', 'kuan2', 'kuan3', 'kuang1', 'kuang2', 'kuang4', 'kui1', 'kui2', 'kui3', 'kui4', 'kun1', 'kun3', 'kun4', 'kuo4', 'la', 'la1', 'la2', 'la3', 'la4', 'lai2', 'lai4', 'lan2', 'lan3', 'lan4', 'lang1', 'lang2', 'lang3', 'lang4', 'lao1', 'lao2', 'lao3', 'lao4', 'le', 'le1', 'le4', 'lei', 'lei1', 'lei2', 'lei3', 'lei4', 'leng1', 'leng2', 'leng3', 'leng4', 'li', 'li1', 'li2', 'li3', 'li4', 'lia3', 'lian2', 'lian3', 'lian4', 'liang2', 'liang3', 'liang4', 'liao1', 'liao2', 'liao3', 'liao4', 'lie1', 'lie2', 'lie3', 'lie4', 'lin1', 'lin2', 'lin3', 'lin4', 'ling2', 'ling3', 'ling4', 'liu1', 'liu2', 'liu3', 'liu4', 'long1', 'long2', 'long3', 'long4', 'lou1', 'lou2', 'lou3', 'lou4', 'lu1', 'lu2', 'lu3', 'lu4', 'luan2', 'luan3', 'luan4', 'lun1', 'lun2', 'lun4', 'luo1', 'luo2', 'luo3', 'luo4', 'lv2', 'lv3', 'lv4', 'lve3', 'lve4', 'ma', 'ma1', 'ma2', 'ma3', 'ma4', 'mai2', 'mai3', 'mai4', 'man2', 'man3', 'man4', 'mang2', 'mang3', 'mao1', 'mao2', 'mao3', 'mao4', 'me', 'mei2', 'mei3', 'mei4', 'men', 'men1', 'men2', 'men4', 'meng1', 'meng2', 'meng3', 'meng4', 'mi1', 'mi2', 'mi3', 'mi4', 'mian2', 'mian3', 'mian4', 'miao1', 'miao2', 'miao3', 'miao4', 'mie1', 'mie4', 'min2', 'min3', 'ming2', 'ming3', 'ming4', 'miu4', 'mo1', 'mo2', 'mo3', 'mo4', 'mou1', 'mou2', 'mou3', 'mu2', 'mu3', 'mu4', 'n2', 'na1', 'na2', 'na3', 'na4', 'nai2', 'nai3', 'nai4', 'nan1', 'nan2', 'nan3', 'nan4', 'nang1', 'nang2', 'nao1', 'nao2', 'nao3', 'nao4', 'ne', 'ne2', 'ne4', 'nei3', 'nei4', 'nen4', 'neng2', 'ni1', 'ni2', 'ni3', 'ni4', 'nian1', 'nian2', 'nian3', 'nian4', 'niang2', 'niang4', 'niao2', 'niao3', 'niao4', 'nie1', 'nie4', 'nin2', 'ning2', 'ning3', 'ning4', 'niu1', 'niu2', 'niu3', 'niu4', 'nong2', 'nong4', 'nou4', 'nu2', 'nu3', 'nu4', 'nuan3', 'nuo2', 'nuo4', 'nv2', 'nv3', 'nve4', 'o1', 'o2', 'ou1', 'ou3', 'ou4', 'pa1', 'pa2', 'pa4', 'pai1', 'pai2', 'pai3', 'pai4', 'pan1', 'pan2', 'pan4', 'pang1', 'pang2', 'pang4', 'pao1', 'pao2', 'pao3', 'pao4', 'pei1', 'pei2', 'pei4', 'pen1', 'pen2', 'pen4', 'peng1', 'peng2', 'peng3', 'peng4', 'pi1', 'pi2', 'pi3', 'pi4', 'pian1', 'pian2', 'pian4', 'piao1', 'piao2', 'piao3', 'piao4', 'pie1', 'pie2', 'pie3', 'pin1', 'pin2', 'pin3', 'pin4', 'ping1', 'ping2', 'po1', 'po2', 'po3', 'po4', 'pou1', 'pu1', 'pu2', 'pu3', 'pu4', 'qi1', 'qi2', 'qi3', 'qi4', 'qia1', 'qia3', 'qia4', 'qian1', 'qian2', 'qian3', 'qian4', 'qiang1', 'qiang2', 'qiang3', 'qiang4', 'qiao1', 'qiao2', 'qiao3', 'qiao4', 'qie1', 'qie2', 'qie3', 'qie4', 'qin1', 'qin2', 'qin3', 'qin4', 'qing1', 'qing2', 'qing3', 'qing4', 'qiong1', 'qiong2', 'qiu1', 'qiu2', 'qiu3', 'qu1', 'qu2', 'qu3', 'qu4', 'quan1', 'quan2', 'quan3', 'quan4', 'que1', 'que2', 'que4', 'qun2', 'ran2', 'ran3', 'rang1', 'rang2', 'rang3', 'rang4', 'rao2', 'rao3', 'rao4', 're2', 're3', 're4', 'ren2', 'ren3', 'ren4', 'reng1', 'reng2', 'ri4', 'rong1', 'rong2', 'rong3', 'rou2', 'rou4', 'ru2', 'ru3', 'ru4', 'ruan2', 'ruan3', 'rui3', 'rui4', 'run4', 'ruo4', 'sa1', 'sa2', 'sa3', 'sa4', 'sai1', 'sai4', 'san1', 'san2', 'san3', 'san4', 'sang1', 'sang3', 'sang4', 'sao1', 'sao2', 'sao3', 'sao4', 'se4', 'sen1', 'seng1', 'sha1', 'sha2', 'sha3', 'sha4', 'shai1', 'shai2', 'shai3', 'shai4', 'shan1', 'shan3', 'shan4', 'shang', 'shang1', 'shang3', 'shang4', 'shao1', 'shao2', 'shao3', 'shao4', 'she1', 'she2', 'she3', 'she4', 'shei2', 'shen1', 'shen2', 'shen3', 'shen4', 'sheng1', 'sheng2', 'sheng3', 'sheng4', 'shi', 'shi1', 'shi2', 'shi3', 'shi4', 'shou1', 'shou2', 'shou3', 'shou4', 'shu1', 'shu2', 'shu3', 'shu4', 'shua1', 'shua2', 'shua3', 'shua4', 'shuai1', 'shuai3', 'shuai4', 'shuan1', 'shuan4', 'shuang1', 'shuang3', 'shui2', 'shui3', 'shui4', 'shun3', 'shun4', 'shuo1', 'shuo4', 'si1', 'si2', 'si3', 'si4', 'song1', 'song3', 'song4', 'sou1', 'sou3', 'sou4', 'su1', 'su2', 'su4', 'suan1', 'suan4', 'sui1', 'sui2', 'sui3', 'sui4', 'sun1', 'sun3', 'suo', 'suo1', 'suo2', 'suo3', 'ta1', 'ta3', 'ta4', 'tai1', 'tai2', 'tai4', 'tan1', 'tan2', 'tan3', 'tan4', 'tang1', 'tang2', 'tang3', 'tang4', 'tao1', 'tao2', 'tao3', 'tao4', 'te4', 'teng2', 'ti1', 'ti2', 'ti3', 'ti4', 'tian1', 'tian2', 'tian3', 'tiao1', 'tiao2', 'tiao3', 'tiao4', 'tie1', 'tie2', 'tie3', 'tie4', 'ting1', 'ting2', 'ting3', 'tong1', 'tong2', 'tong3', 'tong4', 'tou', 'tou1', 'tou2', 'tou4', 'tu1', 'tu2', 'tu3', 'tu4', 'tuan1', 'tuan2', 'tui1', 'tui2', 'tui3', 'tui4', 'tun1', 'tun2', 'tun4', 'tuo1', 'tuo2', 'tuo3', 'tuo4', 'wa', 'wa1', 'wa2', 'wa3', 'wa4', 'wai1', 'wai3', 'wai4', 'wan1', 'wan2', 'wan3', 'wan4', 'wang1', 'wang2', 'wang3', 'wang4', 'wei1', 'wei2', 'wei3', 'wei4', 'wen1', 'wen2', 'wen3', 'wen4', 'weng1', 'weng4', 'wo1', 'wo3', 'wo4', 'wu1', 'wu2', 'wu3', 'wu4', 'xi1', 'xi2', 'xi3', 'xi4', 'xia1', 'xia2', 'xia4', 'xian1', 'xian2', 'xian3', 'xian4', 'xiang1', 'xiang2', 'xiang3', 'xiang4', 'xiao1', 'xiao2', 'xiao3', 'xiao4', 'xie1', 'xie2', 'xie3', 'xie4', 'xin1', 'xin2', 'xin4', 'xing1', 'xing2', 'xing3', 'xing4', 'xiong1', 'xiong2', 'xiu1', 'xiu3', 'xiu4', 'xu', 'xu1', 'xu2', 'xu3', 'xu4', 'xuan1', 'xuan2', 'xuan3', 'xuan4', 'xue1', 'xue2', 'xue3', 'xue4', 'xun1', 'xun2', 'xun4', 'ya', 'ya1', 'ya2', 'ya3', 'ya4', 'yan1', 'yan2', 'yan3', 'yan4', 'yang1', 'yang2', 'yang3', 'yang4', 'yao1', 'yao2', 'yao3', 'yao4', 'ye1', 'ye2', 'ye3', 'ye4', 'yi1', 'yi2', 'yi3', 'yi4', 'yin1', 'yin2', 'yin3', 'yin4', 'ying1', 'ying2', 'ying3', 'ying4', 'yo1', 'yong1', 'yong3', 'yong4', 'you1', 'you2', 'you3', 'you4', 'yu1', 'yu2', 'yu3', 'yu4', 'yuan1', 'yuan2', 'yuan3', 'yuan4', 'yue1', 'yue4', 'yun1', 'yun2', 'yun3', 'yun4', 'za1', 'za2', 'za3', 'zai1', 'zai3', 'zai4', 'zan1', 'zan2', 'zan3', 'zan4', 'zang1', 'zang4', 'zao1', 'zao2', 'zao3', 'zao4', 'ze2', 'ze4', 'zei2', 'zen3', 'zeng1', 'zeng4', 'zha1', 'zha2', 'zha3', 'zha4', 'zhai1', 'zhai2', 'zhai3', 'zhai4', 'zhan1', 'zhan2', 'zhan3', 'zhan4', 'zhang1', 'zhang2', 'zhang3', 'zhang4', 'zhao1', 'zhao2', 'zhao3', 'zhao4', 'zhe', 'zhe1', 'zhe2', 'zhe3', 'zhe4', 'zhen1', 'zhen2', 'zhen3', 'zhen4', 'zheng1', 'zheng2', 'zheng3', 'zheng4', 'zhi1', 'zhi2', 'zhi3', 'zhi4', 'zhong1', 'zhong2', 'zhong3', 'zhong4', 'zhou1', 'zhou2', 'zhou3', 'zhou4', 'zhu1', 'zhu2', 'zhu3', 'zhu4', 'zhua1', 'zhua2', 'zhua3', 'zhuai1', 'zhuai3', 'zhuai4', 'zhuan1', 'zhuan2', 'zhuan3', 'zhuan4', 'zhuang1', 'zhuang4', 'zhui1', 'zhui4', 'zhun1', 'zhun2', 'zhun3', 'zhuo1', 'zhuo2', 'zi', 'zi1', 'zi2', 'zi3', 'zi4', 'zong1', 'zong2', 'zong3', 'zong4', 'zou1', 'zou2', 'zou3', 'zou4', 'zu1', 'zu2', 'zu3', 'zuan1', 'zuan3', 'zuan4', 'zui2', 'zui3', 'zui4', 'zun1', 'zuo1', 'zuo2', 'zuo3', 'zuo4'] + ens = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z', "'", ' '] + ens_U = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'] + + phoneme_to_index = {} + num_phonemes = 0 + for index, punc in enumerate(puncs): + phoneme_to_index[punc] = index + num_phonemes + num_phonemes += len(puncs) + for index, pinyin in enumerate(pinyins): + phoneme_to_index[pinyin] = index + num_phonemes + num_phonemes += len(pinyins) + for index, en in enumerate(ens): + phoneme_to_index[en] = index + num_phonemes + for index, en in enumerate(ens_U): + phoneme_to_index[en] = index + num_phonemes + num_phonemes += len(ens) + #print(num_phonemes, phoneme_to_index) # 1342 + + def encode( + text: list[str], + padding_value = -1 + ) -> Int['b nt']: + phonemes = [] + for t in text: + one_phoneme = [] + brk = False + for word in jieba.cut(t): + if all_ch(word): + seg = lazy_pinyin(word, style=Style.TONE3, tone_sandhi=True) + one_phoneme.extend(seg) + elif all_en(word): + for seg in word: + one_phoneme.append(seg) + elif word in ["，", "。", "？", "、", "'", " "]: + one_phoneme.append(word) + else: + for ch in word: + if all_ch(ch): + seg = lazy_pinyin(ch, style=Style.TONE3, tone_sandhi=True) + one_phoneme.extend(seg) + elif all_en(ch): + for seg in ch: + one_phoneme.append(seg) + else: + brk = True + break + if brk: + break + if not brk: + phonemes.append(one_phoneme) + else: + print("Error Tokenized", t, list(jieba.cut(t))) + list_tensors = [tensor([phoneme_to_index[p] for p in one_phoneme]) for one_phoneme in phonemes] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + + return encode, num_phonemes + +# tensor helpers + +def log(t, eps = 1e-5): + return t.clamp(min = eps).log() + +def lens_to_mask( + t: Int['b'], + length: int | None = None +) -> Bool['b n']: + + if not exists(length): + length = t.amax() + + seq = torch.arange(length, device = t.device) + return einx.less('n, b -> b n', seq, t) + +def mask_from_start_end_indices( + seq_len: Int['b'], + start: Int['b'], + end: Int['b'] +): + max_seq_len = seq_len.max().item() + seq = torch.arange(max_seq_len, device = start.device).long() + return einx.greater_equal('n, b -> b n', seq, start) & einx.less('n, b -> b n', seq, end) + +def mask_from_frac_lengths( + seq_len: Int['b'], + frac_lengths: Float['b'], + max_length: int | None = None, + val = False +): + lengths = (frac_lengths * seq_len).long() + max_start = seq_len - lengths + + if not val: + rand = torch.rand_like(frac_lengths) + else: + rand = torch.tensor([0.5]*frac_lengths.shape[0], device=frac_lengths.device).float() + start = (max_start * rand).long().clamp(min = 0) + end = start + lengths + + out = mask_from_start_end_indices(seq_len, start, end) + + if exists(max_length): + out = pad_to_length(out, max_length) + + return out + +def maybe_masked_mean( + t: Float['b n d'], + mask: Bool['b n'] | None = None +) -> Float['b d']: + + if not exists(mask): + return t.mean(dim = 1) + + t = einx.where('b n, b n d, -> b n d', mask, t, 0.) + num = reduce(t, 'b n d -> b d', 'sum') + den = reduce(mask.float(), 'b n -> b', 'sum') + + return einx.divide('b d, b -> b d', num, den.clamp(min = 1.)) + +def pad_to_length( + t: Tensor, + length: int, + value = None +): + seq_len = t.shape[-1] + if length > seq_len: + t = F.pad(t, (0, length - seq_len), value = value) + + return t[..., :length] + +def interpolate_1d( + x: Tensor, + length: int, + mode = 'bilinear' +): + x = rearrange(x, 'n d -> 1 d n 1') + x = F.interpolate(x, (length, 1), mode = mode) + return rearrange(x, '1 d n 1 -> n d') + +# to mel spec + +class MelSpec(Module): + def __init__( + self, + filter_length = 1024, + hop_length = 256, + win_length = 1024, + n_mel_channels = 100, + sampling_rate = 24_000, + normalize = False, + power = 1, + norm = None, + center = True, + ): + super().__init__() + self.n_mel_channels = n_mel_channels + self.sampling_rate = sampling_rate + + self.mel_stft = torchaudio.transforms.MelSpectrogram( + sample_rate = sampling_rate, + n_fft = filter_length, + win_length = win_length, + hop_length = hop_length, + n_mels = n_mel_channels, + power = power, + center = center, + normalized = normalize, + norm = norm, + ) + + self.register_buffer('dummy', tensor(0), persistent = False) + + def forward(self, inp): + if len(inp.shape) == 3: + inp = rearrange(inp, 'b 1 nw -> b nw') + + assert len(inp.shape) == 2 + + if self.dummy.device != inp.device: + self.to(inp.device) + + mel = self.mel_stft(inp) + mel = log(mel) + return mel + +class EncodecWrapper(Module): + def __init__(self, path): + super().__init__() + self.model = EncodecModel.from_pretrained(path) + self.processor = AutoProcessor.from_pretrained(path) + for param in self.model.parameters(): + param.requires_grad = False + self.model.eval() + + def forward(self, waveform): + with torch.no_grad(): + inputs = self.processor(raw_audio=waveform[0], sampling_rate=self.processor.sampling_rate, return_tensors="pt") + emb = self.model.encoder(inputs.input_values) + return emb + + def decode(self, emb): + with torch.no_grad(): + output = self.model.decoder(emb) + return output[0] + +from audioldm.audio.stft import TacotronSTFT +from audioldm.variational_autoencoder import AutoencoderKL +from audioldm.utils import default_audioldm_config, get_metadata + +def build_pretrained_models(name): + checkpoint = torch.load(get_metadata()[name]["path"], map_location="cpu") + scale_factor = checkpoint["state_dict"]["scale_factor"].item() + + vae_state_dict = {k[18:]: v for k, v in checkpoint["state_dict"].items() if "first_stage_model." in k} + + config = default_audioldm_config(name) + vae_config = config["model"]["params"]["first_stage_config"]["params"] + vae_config["scale_factor"] = scale_factor + + vae = AutoencoderKL(**vae_config) + vae.load_state_dict(vae_state_dict) + + fn_STFT = TacotronSTFT( + config["preprocessing"]["stft"]["filter_length"], + config["preprocessing"]["stft"]["hop_length"], + config["preprocessing"]["stft"]["win_length"], + config["preprocessing"]["mel"]["n_mel_channels"], + config["preprocessing"]["audio"]["sampling_rate"], + config["preprocessing"]["mel"]["mel_fmin"], + config["preprocessing"]["mel"]["mel_fmax"], + ) + + vae.eval() + fn_STFT.eval() + return vae, fn_STFT + +class VaeWrapper(Module): + def __init__(self): + super().__init__() + vae, stft = build_pretrained_models("audioldm-s-full") + vae.eval() + stft.eval() + stft = stft.cpu() + self.vae = vae + for param in self.vae.parameters(): + param.requires_grad = False + + def forward(self, waveform): + return None + + def decode(self, emb): + with torch.no_grad(): + b, d, l = emb.shape + latents = emb.transpose(1,2).reshape(b, l, 8, 16).transpose(1,2) + mel = self.vae.decode_first_stage(latents) + wave = self.vae.decode_to_waveform(mel) + return wave + +# convolutional positional generating module +# taken from https://github.com/lucidrains/voicebox-pytorch/blob/main/voicebox_pytorch/voicebox_pytorch.py#L203 + +class DepthwiseConv(Module): + def __init__( + self, + dim, + *, + kernel_size, + groups = None + ): + super().__init__() + assert not divisible_by(kernel_size, 2) + groups = default(groups, dim) # full depthwise conv by default + + self.dw_conv1d = nn.Sequential( + nn.Conv1d(dim, dim, kernel_size, groups = groups, padding = kernel_size // 2), + nn.SiLU() + ) + + def forward( + self, + x, + mask = None + ): + + if exists(mask): + x = einx.where('b n, b n d, -> b n d', mask, x, 0.) + + x = rearrange(x, 'b n c -> b c n') + x = self.dw_conv1d(x) + out = rearrange(x, 'b c n -> b n c') + + if exists(mask): + out = einx.where('b n, b n d, -> b n d', mask, out, 0.) + + return out + +# adaln zero from DiT paper + +class AdaLNZero(Module): + def __init__( + self, + dim, + dim_condition = None, + init_bias_value = -2. + ): + super().__init__() + dim_condition = default(dim_condition, dim) + self.to_gamma = nn.Linear(dim_condition, dim) + + nn.init.zeros_(self.to_gamma.weight) + nn.init.constant_(self.to_gamma.bias, init_bias_value) + + def forward(self, x, *, condition): + if condition.ndim == 2: + condition = rearrange(condition, 'b d -> b 1 d') + + gamma = self.to_gamma(condition).sigmoid() + return x * gamma + +# random projection fourier embedding + +class RandomFourierEmbed(Module): + def __init__(self, dim): + super().__init__() + assert divisible_by(dim, 2) + self.register_buffer('weights', torch.randn(dim // 2)) + + def forward(self, x): + freqs = einx.multiply('i, j -> i j', x, self.weights) * 2 * torch.pi + fourier_embed, _ = pack((x, freqs.sin(), freqs.cos()), 'b *') + return fourier_embed + +# character embedding + +class CharacterEmbed(Module): + def __init__( + self, + dim, + num_embeds = 256, + ): + super().__init__() + self.dim = dim + self.embed = nn.Embedding(num_embeds + 1, dim) # will just use 0 as the 'filler token' + + def forward( + self, + text: Int['b nt'], + max_seq_len: int, + **kwargs + ) -> Float['b n d']: + + text = text + 1 # shift all other token ids up by 1 and use 0 as filler token + + text = text[:, :max_seq_len] # just curtail if character tokens are more than the mel spec tokens, one of the edge cases the paper did not address + text = pad_to_length(text, max_seq_len, value = 0) + + return self.embed(text) + +class InterpolatedCharacterEmbed(Module): + def __init__( + self, + dim, + num_embeds = 256, + ): + super().__init__() + self.dim = dim + self.embed = nn.Embedding(num_embeds, dim) + + self.abs_pos_mlp = Sequential( + Rearrange('... -> ... 1'), + Linear(1, dim), + nn.SiLU(), + Linear(dim, dim) + ) + + def forward( + self, + text: Int['b nt'], + max_seq_len: int, + mask: Bool['b n'] | None = None + ) -> Float['b n d']: + + device = text.device + + mask = default(mask, (None,)) + + interp_embeds = [] + interp_abs_positions = [] + + for one_text, one_mask in zip_longest(text, mask): + + valid_text = one_text >= 0 + one_text = one_text[valid_text] + one_text_embed = self.embed(one_text) + + # save the absolute positions + + text_seq_len = one_text.shape[0] + + # determine audio sequence length from mask + + audio_seq_len = max_seq_len + if exists(one_mask): + audio_seq_len = one_mask.sum().long().item() + + # interpolate text embedding to audio embedding length + + interp_text_embed = interpolate_1d(one_text_embed, audio_seq_len) + interp_abs_pos = torch.linspace(0, text_seq_len, audio_seq_len, device = device) + + interp_embeds.append(interp_text_embed) + interp_abs_positions.append(interp_abs_pos) + + interp_embeds = pad_sequence(interp_embeds) + interp_abs_positions = pad_sequence(interp_abs_positions) + + interp_embeds = F.pad(interp_embeds, (0, 0, 0, max_seq_len - interp_embeds.shape[-2])) + interp_abs_positions = pad_to_length(interp_abs_positions, max_seq_len) + + # pass interp absolute positions through mlp for implicit positions + + interp_embeds = interp_embeds + self.abs_pos_mlp(interp_abs_positions) + + if exists(mask): + interp_embeds = einx.where('b n, b n d, -> b n d', mask, interp_embeds, 0.) + + return interp_embeds + +# text audio cross conditioning in multistream setup + +class TextAudioCrossCondition(Module): + def __init__( + self, + dim, + dim_text, + dim_frames, + cond_audio_to_text = True, + ): + super().__init__() + #self.text_to_audio = nn.Linear(dim_text + dim, dim, bias = False) + self.text_frames_to_audio = nn.Linear(dim + dim_text + dim_frames, dim, bias = False) + nn.init.zeros_(self.text_frames_to_audio.weight) + + self.cond_audio_to_text = cond_audio_to_text + + if cond_audio_to_text: + self.audio_to_text = nn.Linear(dim + dim_text, dim_text, bias = False) + nn.init.zeros_(self.audio_to_text.weight) + + self.audio_to_frames = nn.Linear(dim + dim_frames, dim_frames, bias = False) + nn.init.zeros_(self.audio_to_frames.weight) + + def forward( + self, + audio: Float['b n d'], + text: Float['b n dt'], + frames: Float['b n df'], + ): + #audio_text, _ = pack((audio, text), 'b n *') + audio_text_frames, _ = pack((audio, text, frames), 'b n *') + audio_text, _ = pack((audio, text), 'b n *') + audio_frames, _ = pack((audio, frames), 'b n *') + + #text_cond = self.text_to_audio(audio_text) + text_cond = self.text_frames_to_audio(audio_text_frames) + audio_cond = self.audio_to_text(audio_text) if self.cond_audio_to_text else 0. + audio_cond2 = self.audio_to_frames(audio_frames) if self.cond_audio_to_text else 0. + + return audio + text_cond, text + audio_cond, frames + audio_cond2 + +# attention and transformer backbone +# for use in both e2tts as well as duration module + +class Transformer(Module): + @beartype + def __init__( + self, + *, + dim, + dim_text = None, # will default to half of audio dimension + dim_frames = 512, + depth = 8, + heads = 8, + dim_head = 64, + ff_mult = 4, + text_depth = None, + text_heads = None, + text_dim_head = None, + text_ff_mult = None, + cond_on_time = True, + abs_pos_emb = True, + max_seq_len = 8192, + kernel_size = 31, + dropout = 0.1, + num_registers = 32, + attn_kwargs: dict = dict( + gate_value_heads = True, + softclamp_logits = True, + ), + ff_kwargs: dict = dict(), + if_text_modules = True, + if_cross_attn = True, + if_audio_conv = True, + if_text_conv = False + ): + super().__init__() + assert divisible_by(depth, 2), 'depth needs to be even' + + # absolute positional embedding + + self.max_seq_len = max_seq_len + self.abs_pos_emb = nn.Embedding(max_seq_len, dim) if abs_pos_emb else None + + self.dim = dim + + dim_text = default(dim_text, dim // 2) + self.dim_text = dim_text + + self.dim_frames = dim_frames + + text_heads = default(text_heads, heads) + text_dim_head = default(text_dim_head, dim_head) + text_ff_mult = default(text_ff_mult, ff_mult) + text_depth = default(text_depth, depth) + + assert 1 <= text_depth <= depth, 'must have at least 1 layer of text conditioning, but less than total number of speech layers' + + self.depth = depth + self.layers = ModuleList([]) + + # registers + + self.num_registers = num_registers + self.registers = nn.Parameter(torch.zeros(num_registers, dim)) + nn.init.normal_(self.registers, std = 0.02) + + if if_text_modules: + self.text_registers = nn.Parameter(torch.zeros(num_registers, dim_text)) + nn.init.normal_(self.text_registers, std = 0.02) + + self.frames_registers = nn.Parameter(torch.zeros(num_registers, dim_frames)) + nn.init.normal_(self.frames_registers, std = 0.02) + + # rotary embedding + + self.rotary_emb = RotaryEmbedding(dim_head) + self.text_rotary_emb = RotaryEmbedding(dim_head) + self.frames_rotary_emb = RotaryEmbedding(dim_head) + + # time conditioning + # will use adaptive rmsnorm + + self.cond_on_time = cond_on_time + rmsnorm_klass = RMSNorm if not cond_on_time else AdaptiveRMSNorm + postbranch_klass = Identity if not cond_on_time else partial(AdaLNZero, dim = dim) + + self.time_cond_mlp = Identity() + + if cond_on_time: + self.time_cond_mlp = Sequential( + RandomFourierEmbed(dim), + Linear(dim + 1, dim), + nn.SiLU() + ) + + for ind in range(depth): + is_later_half = ind >= (depth // 2) + has_text = ind < text_depth + + # speech related + if if_audio_conv: + speech_conv = DepthwiseConv(dim, kernel_size = kernel_size) + + attn_norm = rmsnorm_klass(dim) + attn = Attention(dim = dim, heads = heads, dim_head = dim_head, dropout = dropout, **attn_kwargs) + attn_adaln_zero = postbranch_klass() + + if if_cross_attn: + attn_norm2 = rmsnorm_klass(dim) + attn2 = Attention(dim = dim, heads = heads, dim_head = dim_head, dropout = dropout, **attn_kwargs) + attn_adaln_zero2 = postbranch_klass() + + ff_norm = rmsnorm_klass(dim) + ff = FeedForward(dim = dim, glu = True, mult = ff_mult, dropout = dropout, **ff_kwargs) + ff_adaln_zero = postbranch_klass() + + skip_proj = Linear(dim * 2, dim, bias = False) if is_later_half else None + + if if_cross_attn: + if if_audio_conv: + speech_modules = ModuleList([ + skip_proj, + speech_conv, + attn_norm, + attn, + attn_adaln_zero, + attn_norm2, + attn2, + attn_adaln_zero2, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + speech_modules = ModuleList([ + skip_proj, + attn_norm, + attn, + attn_adaln_zero, + attn_norm2, + attn2, + attn_adaln_zero2, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + if if_audio_conv: + speech_modules = ModuleList([ + skip_proj, + speech_conv, + attn_norm, + attn, + attn_adaln_zero, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + speech_modules = ModuleList([ + skip_proj, + attn_norm, + attn, + attn_adaln_zero, + ff_norm, + ff, + ff_adaln_zero, + ]) + + text_modules = None + + if has_text and if_text_modules: + # text related + if if_text_conv: + text_conv = DepthwiseConv(dim_text, kernel_size = kernel_size) + + text_attn_norm = RMSNorm(dim_text) + text_attn = Attention(dim = dim_text, heads = text_heads, dim_head = text_dim_head, dropout = dropout, **attn_kwargs) + + text_ff_norm = RMSNorm(dim_text) + text_ff = FeedForward(dim = dim_text, glu = True, mult = text_ff_mult, dropout = dropout, **ff_kwargs) + + # cross condition + + is_last = ind == (text_depth - 1) + + cross_condition = TextAudioCrossCondition(dim = dim, dim_text = dim_text, dim_frames = dim_frames, cond_audio_to_text = not is_last) + + if if_text_conv: + text_modules = ModuleList([ + text_conv, + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ]) + else: + text_modules = ModuleList([ + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ]) + + if True: + frames_conv = DepthwiseConv(dim_frames, kernel_size = kernel_size) + + frames_attn_norm = RMSNorm(dim_frames) + frames_attn = Attention(dim = dim_frames, heads = 8, dim_head = 64, dropout = dropout, **attn_kwargs) + + frames_ff_norm = RMSNorm(dim_frames) + frames_ff = FeedForward(dim = dim_frames, glu = True, mult = 4, dropout = dropout, **ff_kwargs) + + # cross condition + + frames_modules = ModuleList([ + frames_conv, + frames_attn_norm, + frames_attn, + frames_ff_norm, + frames_ff + ]) + + self.layers.append(ModuleList([ + speech_modules, + text_modules, + frames_modules + ])) + + self.final_norm = RMSNorm(dim) + + self.if_cross_attn = if_cross_attn + self.if_audio_conv = if_audio_conv + self.if_text_conv = if_text_conv + + def forward( + self, + x: Float['b n d'], + times: Float['b'] | Float[''] | None = None, + mask: Bool['b n'] | None = None, + text_embed: Float['b n dt'] | None = None, + frames_embed: Float['b n df'] | None = None, + context: Float['b nc dc'] | None = None, + context_mask: Float['b nc'] | None = None + ): + batch, seq_len, device = *x.shape[:2], x.device + + assert not (exists(times) ^ self.cond_on_time), '`times` must be passed in if `cond_on_time` is set to `True` and vice versa' + + # handle absolute positions if needed + + if exists(self.abs_pos_emb): + assert seq_len <= self.max_seq_len, f'{seq_len} exceeds the set `max_seq_len` ({self.max_seq_len}) on Transformer' + seq = torch.arange(seq_len, device = device) + x = x + self.abs_pos_emb(seq) + + # handle adaptive rmsnorm kwargs + + norm_kwargs = dict() + + if exists(times): + if times.ndim == 0: + times = repeat(times, ' -> b', b = batch) + + times = self.time_cond_mlp(times) + norm_kwargs.update(condition = times) + + # register tokens + + registers = repeat(self.registers, 'r d -> b r d', b = batch) + x, registers_packed_shape = pack((registers, x), 'b * d') + + if exists(mask): + mask = F.pad(mask, (self.num_registers, 0), value = True) + + # rotary embedding + + rotary_pos_emb = self.rotary_emb.forward_from_seq_len(x.shape[-2]) + + # text related + + if exists(text_embed): + text_rotary_pos_emb = self.text_rotary_emb.forward_from_seq_len(x.shape[-2]) + + text_registers = repeat(self.text_registers, 'r d -> b r d', b = batch) + text_embed, _ = pack((text_registers, text_embed), 'b * d') + + if exists(frames_embed): + frames_rotary_pos_emb = self.frames_rotary_emb.forward_from_seq_len(x.shape[-2]) + + frames_registers = repeat(self.frames_registers, 'r d -> b r d', b = batch) + frames_embed, _ = pack((frames_registers, frames_embed), 'b * d') + + # skip connection related stuff + + skips = [] + + # go through the layers + + for ind, (speech_modules, text_modules, frames_modules) in enumerate(self.layers): + layer = ind + 1 + + if self.if_cross_attn: + if self.if_audio_conv: + ( + maybe_skip_proj, + speech_conv, + attn_norm, + attn, + maybe_attn_adaln_zero, + attn_norm2, + attn2, + maybe_attn_adaln_zero2, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + ( + maybe_skip_proj, + attn_norm, + attn, + maybe_attn_adaln_zero, + attn_norm2, + attn2, + maybe_attn_adaln_zero2, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + if self.if_audio_conv: + ( + maybe_skip_proj, + speech_conv, + attn_norm, + attn, + maybe_attn_adaln_zero, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + ( + maybe_skip_proj, + attn_norm, + attn, + maybe_attn_adaln_zero, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + + # smaller text transformer + + if exists(text_embed) and exists(text_modules): + + if self.if_text_conv: + ( + text_conv, + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ) = text_modules + else: + ( + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ) = text_modules + + if self.if_text_conv: + text_embed = text_conv(text_embed, mask = mask) + text_embed + + text_embed = text_attn(text_attn_norm(text_embed), rotary_pos_emb = text_rotary_pos_emb, mask = mask) + text_embed + + text_embed = text_ff(text_ff_norm(text_embed)) + text_embed + + # frames transformer + ( + frames_conv, + frames_attn_norm, + frames_attn, + frames_ff_norm, + frames_ff + ) = frames_modules + + frames_embed = frames_conv(frames_embed, mask = mask) + frames_embed + + frames_embed = frames_attn(frames_attn_norm(frames_embed), rotary_pos_emb = frames_rotary_pos_emb, mask = mask) + frames_embed + + frames_embed = frames_ff(frames_ff_norm(frames_embed)) + frames_embed + + # cross condition + x, text_embed, frames_embed = cross_condition(x, text_embed, frames_embed) + + # skip connection logic + + is_first_half = layer <= (self.depth // 2) + is_later_half = not is_first_half + + if is_first_half: + skips.append(x) + + if is_later_half: + skip = skips.pop() + x = torch.cat((x, skip), dim = -1) + x = maybe_skip_proj(x) + + # position generating convolution + + if self.if_audio_conv: + x = speech_conv(x, mask = mask) + x + + # attention and feedforward blocks + + attn_out = attn(attn_norm(x, **norm_kwargs), rotary_pos_emb = rotary_pos_emb, mask = mask) + + x = x + maybe_attn_adaln_zero(attn_out, **norm_kwargs) + + if self.if_cross_attn: + attn_out = attn2(attn_norm2(x, **norm_kwargs), rotary_pos_emb = rotary_pos_emb, mask = mask, context = context, context_mask = context_mask) + + x = x + maybe_attn_adaln_zero2(attn_out, **norm_kwargs) + + ff_out = ff(ff_norm(x, **norm_kwargs)) + + x = x + maybe_ff_adaln_zero(ff_out, **norm_kwargs) + + assert len(skips) == 0 + + _, x = unpack(x, registers_packed_shape, 'b * d') + + return self.final_norm(x) + +# main classes + +class DurationPredictor(Module): + @beartype + def __init__( + self, + transformer: dict | Transformer, + num_channels = None, + mel_spec_kwargs: dict = dict(), + char_embed_kwargs: dict = dict(), + text_num_embeds = None, + tokenizer: ( + Literal['char_utf8', 'phoneme_en'] | + Callable[[list[str]], Int['b nt']] + ) = 'char_utf8' + ): + super().__init__() + + if isinstance(transformer, dict): + transformer = Transformer( + **transformer, + cond_on_time = False + ) + + # mel spec + + self.mel_spec = MelSpec(**mel_spec_kwargs) + self.num_channels = default(num_channels, self.mel_spec.n_mel_channels) + + self.transformer = transformer + + dim = transformer.dim + dim_text = transformer.dim_text + + self.dim = dim + + self.proj_in = Linear(self.num_channels, self.dim) + + # tokenizer and text embed + + if callable(tokenizer): + assert exists(text_num_embeds), '`text_num_embeds` must be given if supplying your own tokenizer encode function' + self.tokenizer = tokenizer + elif tokenizer == 'char_utf8': + text_num_embeds = 256 + self.tokenizer = list_str_to_tensor + elif tokenizer == 'phoneme_en': + self.tokenizer, text_num_embeds = get_g2p_en_encode() + elif tokenizer == 'phoneme_zh': + self.tokenizer, text_num_embeds = get_g2p_zh_encode() + else: + raise ValueError(f'unknown tokenizer string {tokenizer}') + + self.embed_text = CharacterEmbed(dim_text, num_embeds = text_num_embeds, **char_embed_kwargs) + + # to prediction + + self.to_pred = Sequential( + Linear(dim, 1, bias = False), + nn.Softplus(), + Rearrange('... 1 -> ...') + ) + + def forward( + self, + x: Float['b n d'] | Float['b nw'], + *, + text: Int['b nt'] | list[str] | None = None, + lens: Int['b'] | None = None, + return_loss = True + ): + # raw wave + + if x.ndim == 2: + x = self.mel_spec(x) + x = rearrange(x, 'b d n -> b n d') + assert x.shape[-1] == self.dim + + x = self.proj_in(x) + + batch, seq_len, device = *x.shape[:2], x.device + + # text + + text_embed = None + + if exists(text): + if isinstance(text, list): + text = list_str_to_tensor(text).to(device) + assert text.shape[0] == batch + + text_embed = self.embed_text(text, seq_len) + + # handle lengths (duration) + + if not exists(lens): + lens = torch.full((batch,), seq_len, device = device) + + mask = lens_to_mask(lens, length = seq_len) + + # if returning a loss, mask out randomly from an index and have it predict the duration + + if return_loss: + rand_frac_index = x.new_zeros(batch).uniform_(0, 1) + rand_index = (rand_frac_index * lens).long() + + seq = torch.arange(seq_len, device = device) + mask &= einx.less('n, b -> b n', seq, rand_index) + + # attending + + x = self.transformer( + x, + mask = mask, + text_embed = text_embed, + ) + + x = maybe_masked_mean(x, mask) + + pred = self.to_pred(x) + + # return the prediction if not returning loss + + if not return_loss: + return pred + + # loss + + return F.mse_loss(pred, lens.float()) + +class E2TTS(Module): + + @beartype + def __init__( + self, + transformer: dict | Transformer = None, + duration_predictor: dict | DurationPredictor | None = None, + odeint_kwargs: dict = dict( + #atol = 1e-5, + #rtol = 1e-5, + #method = 'midpoint' + method = "euler" + ), + audiocond_drop_prob = 0.30, + cond_drop_prob = 0.20, + prompt_drop_prob = 0.10, + num_channels = None, + mel_spec_module: Module | None = None, + char_embed_kwargs: dict = dict(), + mel_spec_kwargs: dict = dict(), + frac_lengths_mask: tuple[float, float] = (0.7, 1.), + audiocond_snr: tuple[float, float] | None = None, + concat_cond = False, + interpolated_text = False, + text_num_embeds: int | None = None, + tokenizer: ( + Literal['char_utf8', 'phoneme_en', 'phoneme_zh'] | + Callable[[list[str]], Int['b nt']] + ) = 'char_utf8', + use_vocos = True, + pretrained_vocos_path = 'charactr/vocos-mel-24khz', + sampling_rate: int | None = None, + frame_size: int = 320, + #### dpo + velocity_consistency_weight = -1e-5, + #### dpo + + if_cond_proj_in = True, + cond_proj_in_bias = True, + if_embed_text = True, + if_text_encoder2 = True, + if_clip_encoder = False, + video_encoder = "clip_vit" + ): + super().__init__() + + if isinstance(transformer, dict): + transformer = Transformer( + **transformer, + cond_on_time = True + ) + + if isinstance(duration_predictor, dict): + duration_predictor = DurationPredictor(**duration_predictor) + + self.transformer = transformer + + dim = transformer.dim + dim_text = transformer.dim_text + dim_frames = transformer.dim_frames + + self.dim = dim + self.dim_text = dim_text + + self.frac_lengths_mask = frac_lengths_mask + self.audiocond_snr = audiocond_snr + + self.duration_predictor = duration_predictor + + # sampling + + self.odeint_kwargs = odeint_kwargs + + # mel spec + + self.mel_spec = default(mel_spec_module, None) + num_channels = default(num_channels, None) + + self.num_channels = num_channels + self.sampling_rate = default(sampling_rate, None) + self.frame_size = frame_size + + # whether to concat condition and project rather than project both and sum + + self.concat_cond = concat_cond + + if concat_cond: + self.proj_in = nn.Linear(num_channels * 2, dim) + else: + self.proj_in = nn.Linear(num_channels, dim) + self.cond_proj_in = nn.Linear(num_channels, dim, bias=cond_proj_in_bias) if if_cond_proj_in else None + #self.cond_proj_in = nn.Linear(NOTES, dim, bias=cond_proj_in_bias) if if_cond_proj_in else None + + # to prediction + + self.to_pred = Linear(dim, num_channels) + + # tokenizer and text embed + + if callable(tokenizer): + assert exists(text_num_embeds), '`text_num_embeds` must be given if supplying your own tokenizer encode function' + self.tokenizer = tokenizer + elif tokenizer == 'char_utf8': + text_num_embeds = 256 + self.tokenizer = list_str_to_tensor + elif tokenizer == 'phoneme_en': + self.tokenizer, text_num_embeds = get_g2p_en_encode() + elif tokenizer == 'phoneme_zh': + self.tokenizer, text_num_embeds = get_g2p_zh_encode() + else: + raise ValueError(f'unknown tokenizer string {tokenizer}') + + self.audiocond_drop_prob = audiocond_drop_prob + self.cond_drop_prob = cond_drop_prob + self.prompt_drop_prob = prompt_drop_prob + + # text embedding + + text_embed_klass = CharacterEmbed if not interpolated_text else InterpolatedCharacterEmbed + + self.embed_text = text_embed_klass(dim_text, num_embeds = text_num_embeds, **char_embed_kwargs) if if_embed_text else None + + # weight for velocity consistency + + self.register_buffer('zero', torch.tensor(0.), persistent = False) + self.velocity_consistency_weight = velocity_consistency_weight + + # default vocos for mel -> audio + + #if pretrained_vocos_path == 'charactr/vocos-mel-24khz': + # self.vocos = Vocos.from_pretrained(pretrained_vocos_path) if use_vocos else None + #elif pretrained_vocos_path == 'facebook/encodec_24khz': + # self.vocos = EncodecWrapper("facebook/encodec_24khz") if use_vocos else None + #elif pretrained_vocos_path == 'vae': + # self.vocos = VaeWrapper() if use_vocos else None + + if if_text_encoder2: + self.tokenizer2 = AutoTokenizer.from_pretrained("./ckpts/flan-t5-large") + self.text_encoder2 = T5EncoderModel.from_pretrained("./ckpts/flan-t5-large") + for param in self.text_encoder2.parameters(): + param.requires_grad = False + self.text_encoder2.eval() + + self.proj_text = None + self.proj_frames = Linear(NOTES, dim_frames) + if if_clip_encoder: + if video_encoder == "clip_vit": + ####pass + self.image_processor = CLIPImageProcessor() + #self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train2/speech/zhanghaomin/models/IP-Adapter/", subfolder="models/image_encoder") + self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("./ckpts/IP-Adapter/", subfolder="sdxl_models/image_encoder") + elif video_encoder == "clip_vit2": + self.image_processor = AutoProcessor.from_pretrained("/ailab-train2/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train2/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + elif video_encoder == "clip_convnext": + self.image_encoder, _, self.image_processor = open_clip.create_model_and_transforms("hf-hub:laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup") + elif video_encoder == "dinov2": + self.image_processor = AutoImageProcessor.from_pretrained("/ailab-train2/speech/zhanghaomin/models/dinov2-giant/") + self.image_encoder = AutoModel.from_pretrained("/ailab-train2/speech/zhanghaomin/models/dinov2-giant/") + elif video_encoder == "mixed": + pass + #self.image_processor1 = CLIPImageProcessor() + #self.image_encoder1 = CLIPVisionModelWithProjection.from_pretrained("/ailab-train2/speech/zhanghaomin/models/IP-Adapter/", subfolder="sdxl_models/image_encoder") + #self.image_processor2 = AutoProcessor.from_pretrained("/ailab-train2/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + #self.image_encoder2 = CLIPVisionModelWithProjection.from_pretrained("/ailab-train2/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + #self.image_encoder3, _, self.image_processor3 = open_clip.create_model_and_transforms("hf-hub:laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup") + #self.image_processor4 = AutoImageProcessor.from_pretrained("/ailab-train2/speech/zhanghaomin/models/dinov2-giant/") + #self.image_encoder4 = AutoModel.from_pretrained("/ailab-train2/speech/zhanghaomin/models/dinov2-giant/") + else: + self.image_processor = None + self.image_encoder = None + if video_encoder != "mixed": + ####pass + for param in self.image_encoder.parameters(): + param.requires_grad = False + self.image_encoder.eval() + else: + #for param in self.image_encoder1.parameters(): + # param.requires_grad = False + #self.image_encoder1.eval() + #for param in self.image_encoder2.parameters(): + # param.requires_grad = False + #self.image_encoder2.eval() + #for param in self.image_encoder3.parameters(): + # param.requires_grad = False + #self.image_encoder3.eval() + #for param in self.image_encoder4.parameters(): + # param.requires_grad = False + #self.image_encoder4.eval() + self.dim_text_raw = 4608 + self.proj_text = Linear(self.dim_text_raw, dim_text) + self.video_encoder = video_encoder + + #for param in self.vocos.parameters(): + # param.requires_grad = False + #self.vocos.eval() + + ########self.conv1 = nn.Conv3d(6, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool1 = nn.Conv3d(64, 64, kernel_size=(1, 2, 2), stride=(1, 2, 2)) + ####self.conv1 = nn.Conv3d(3, 16, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.pool1 = nn.Conv3d(16, 16, kernel_size=(1, 2, 2), stride=(1, 2, 2), padding=(0,0,0)) + #### + ########self.conv2 = nn.Conv3d(64, 128, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool2 = nn.Conv3d(128, 128, kernel_size=(2, 2, 2), stride=(2, 2, 2)) + ####self.conv2 = nn.Conv3d(16, 32, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.pool2 = nn.Conv3d(32, 32, kernel_size=(2, 2, 2), stride=(1, 2, 2), padding=(0,0,0)) + #### + ########self.conv3a = nn.Conv3d(128, 256, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.conv3b = nn.Conv3d(256, 256, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool3 = nn.Conv3d(256, 256, kernel_size=(1, 2, 2), stride=(1, 2, 2)) + ####self.conv3a = nn.Conv3d(32, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.conv3b = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.pool3 = nn.Conv3d(64, 64, kernel_size=(1, 2, 2), stride=(1, 2, 2), padding=(0,0,0)) + #### + ########self.conv4a = nn.Conv3d(256, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.conv4b = nn.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool4 = nn.Conv3d(512, 512, kernel_size=(1, 2, 2), stride=(1, 2, 2)) + #####self.conv4a = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + #####self.conv4b = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ######self.pool4 = nn.Conv3d(64, 32, kernel_size=(1, 2, 2), stride=(1, 2, 2), padding=(0,0,0)) + #####self.pool4 = nn.ConvTranspose3d(64, 32, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + #### + ########self.conv5a = nn.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.conv5b = nn.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ########self.pool5 = nn.ConvTranspose3d(512, 128, kernel_size=(5, 3, 3), stride=(5, 1, 1), padding=(0, 1, 1)) + ####self.conv5a = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.conv5b = nn.Conv3d(64, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1)) + ####self.pool5 = nn.ConvTranspose3d(64, 32, kernel_size=(3, 3, 3), stride=(3, 1, 1), padding=(0, 1, 1)) + #####self.pool5 = nn.Conv3d(256, 256, kernel_size=(1, 2, 2), stride=(1, 2, 2)) + #### + ####self.relu = nn.ReLU() + ####self.final_activation = nn.Sigmoid() + ####self.dropout = nn.Dropout(p=0.50) + ########self.fc5 = nn.Linear(51200, NOTES) + ####self.fc5 = nn.Linear(65536, 208) + ####self.fc6 = nn.Linear(208, NOTES) + #### + #####self.rnn = nn.RNN(NOTES, NOTES, 1) + #####self.fc7 = nn.Linear(NOTES, NOTES) + #### + #####self.bn1 = nn.BatchNorm3d(16) + #####self.bn2 = nn.BatchNorm3d(32) + #####self.bn3 = nn.BatchNorm3d(64) + #####self.bn4 = nn.BatchNorm3d(64) + #####self.bn5 = nn.BatchNorm3d(64) + #####self.bn6 = nn.BatchNorm3d(64) + #####self.bn7 = nn.BatchNorm1d(208) + + self.video2roll_net = Video2RollNet.resnet18(num_classes=NOTES) + + def encode_frames(self, x, l): + #print("x input", x.shape, l) # [1, 1, 251, 100, 900] + b, c, t, w, h = x.shape + assert(c == 1) + + x_all = [] + for i in range(t): + frames = [] + for j in [-2, -1, 0, 1, 2]: + f = min(max(i+j, 0), t-1) + frames.append(x[:,:,f:f+1,:,:]) + frames = torch.cat(frames, dim=2) # [b, 1, 5, w, h] + x_all.append(frames) + x = torch.cat(x_all, dim=1).reshape(b*t, 5, w, h) # [b*t, 5, w, h] + #print("x", x.shape, l) # [251, 5, 100, 900] + x = self.video2roll_net(x) + x = nn.Sigmoid()(x) + #print("x output", x.shape) # [251, 51] + ####x = x.reshape(b, t, 1, NOTES).repeat(1,1,3,1).reshape(b, t*3, NOTES) + t5 = (t*5//2)*2 + x = x.reshape(b, t, 1, NOTES).repeat(1,1,5,1).reshape(b, t*5, NOTES)[:,:t5,:].reshape(b, t5//2, 2, NOTES).mean(2) + b, d, _ = x.shape + + #print("encode_frames", x.shape, l) + if d > l: + x = x[:,:l,:] + elif d < l: + x = torch.cat((x, torch.zeros(b,l-d,NOTES,device=x.device)), 1) + return x + + return x + + ####def encode_frames(self, x, l): + #### x = x[:,:3,:,...] + #### #print("x", x.shape) # [2, 6, 301, 320, 320] # [2, 3, 251, 128, 1024] + #### x = self.conv1(x) + #### #x = self.bn1(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### #print("conv1", x.shape) # [2, 64, 301, 320, 320] # [2, 16, 251, 128, 1024] + #### x = self.pool1(x) + #### #print("pool1", x.shape) # [2, 64, 301, 160, 160] # [2, 16, 251, 64, 512] + #### + #### x = self.conv2(x) + #### #x = self.bn2(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### #print("conv2", x.shape) # [2, 128, 301, 160, 160] # [2, 32, 250, 64, 512] + #### x = self.pool2(x) + #### #x = self.relu(x) + #### #x = self.dropout(x) + #### #print("pool2", x.shape) # [2, 128, 150, 80, 80] # [2, 32, 250, 32, 256] + #### + #### x = self.conv3a(x) + #### #x = self.bn3(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### x = self.conv3b(x) + #### #x = self.bn4(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### #print("conv3", x.shape) # [2, 256, 150, 80, 80] # [2, 64, 250, 32, 256] + #### x = self.pool3(x) + #### #x = self.relu(x) + #### #x = self.dropout(x) + #### #print("pool3", x.shape) # [2, 256, 150, 40, 40] # [2, 64, 250, 16, 128] + #### + #### #x = self.conv4a(x) + #### #x = self.relu(x) + #### ##x = self.dropout(x) + #### #x = self.conv4b(x) + #### #x = self.relu(x) + #### ##x = self.dropout(x) + #### ###print("conv4", x.shape) # [2, 512, 150, 40, 40] # [2, 64, 250, 16, 128] + #### #x = self.pool4(x) + #### ##print("pool4", x.shape) # [2, 512, 150, 20, 20] # [2, 32, 250, 8, 64] + #### + #### x = self.conv5a(x) + #### #x = self.bn5(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### x = self.conv5b(x) + #### #x = self.bn6(x) + #### x = self.relu(x) + #### x = self.dropout(x) + #### #print("conv5", x.shape) # [2, 512, 150, 20, 20] # [2, 64, 250, 16, 128] + #### x = self.pool5(x) + #### #x = self.relu(x) + #### #x = self.dropout(x) + #### #print("pool5", x.shape) # [2, 128, 750, 20, 20] # [2, 32, 750/250, 16, 128] + #### + #### b, c, d, w, h = x.shape + #### x = x.permute(0,2,3,4,1).reshape(b,d,w*h*c) + #### x = self.fc5(x) + #### #x = x.reshape(b,208,d) + #### #x = self.bn7(x) + #### #x = x.reshape(b,d,208) + #### x = self.relu(x) + #### x = self.dropout(x) + #### x = self.fc6(x) + #### + #### #x = self.relu(x) + #### #x, _ = self.rnn(x) + #### #x = self.fc7(x) + #### + #### x = self.final_activation(x) + #### + #### #x = x.reshape(b,d,1,NOTES).repeat(1,1,3,1).reshape(b,d*3,NOTES) + #### #d = d * 3 + #### + #### #print("encode_frames", x.shape, l) + #### if d > l: + #### x = x[:,:l,:] + #### elif d < l: + #### x = torch.cat((x, torch.zeros(b,l-d,NOTES,device=x.device)), 1) + #### return x + + @property + def device(self): + return next(self.parameters()).device + + def encode_text(self, prompt): + device = self.device + batch = self.tokenizer2(prompt, max_length=self.tokenizer2.model_max_length, padding=True, truncation=True, return_tensors="pt") + input_ids, attention_mask = batch.input_ids.to(device), batch.attention_mask.to(device) + + with torch.no_grad(): + encoder_hidden_states = self.text_encoder2(input_ids=input_ids, attention_mask=attention_mask)[0] + + boolean_encoder_mask = (attention_mask == 1).to(device) + return encoder_hidden_states, boolean_encoder_mask + + def encode_video(self, video_paths, l): + if self.proj_text is None: + d = self.dim_text + else: + d = self.dim_text_raw + device = self.device + b = 20 + with torch.no_grad(): + video_embeddings = [] + video_lens = [] + for video_path in video_paths: + if video_path is None: + video_embeddings.append(None) + video_lens.append(0) + continue + if isinstance(video_path, tuple): + video_path, start_sample, max_sample = video_path + else: + start_sample = 0 + max_sample = None + if video_path.startswith("/ailab-train2/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = video_path.replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = video_path.replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = video_path.replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = video_path.replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = video_path.replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = video_path.replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = video_path.replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = video_path.replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = video_path.replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = video_path.replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + + if not os.path.exists(feature_path): + #print("video not exist", video_path) + frames, duration = read_frames_with_moviepy(video_path, max_frame_nums=None) + if frames is None: + video_embeddings.append(None) + video_lens.append(0) + continue + if self.video_encoder in ["clip_vit", "clip_vit2", "dinov2"]: + images = self.image_processor(images=frames, return_tensors="pt").to(device) + #print("images", images["pixel_values"].shape, images["pixel_values"].max(), images["pixel_values"].min(), torch.abs(images["pixel_values"]).mean()) + elif self.video_encoder in ["clip_convnext"]: + images = [] + for i in range(frames.shape[0]): + images.append(self.image_processor(Image.fromarray(frames[i])).unsqueeze(0)) + images = torch.cat(images, dim=0).to(device) + #print("images", images.shape, images.max(), images.min(), torch.abs(images).mean()) + elif self.video_encoder in ["mixed"]: + #images1 = self.image_processor1(images=frames, return_tensors="pt").to(device) + images2 = self.image_processor2(images=frames, return_tensors="pt").to(device) + images4 = self.image_processor4(images=frames, return_tensors="pt").to(device) + images3 = [] + for i in range(frames.shape[0]): + images3.append(self.image_processor3(Image.fromarray(frames[i])).unsqueeze(0)) + images3 = torch.cat(images3, dim=0).to(device) + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + image_embeddings = [] + if self.video_encoder == "clip_vit": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + elif self.video_encoder == "clip_vit2": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + elif self.video_encoder == "clip_convnext": + for i in range(math.ceil(images.shape[0] / b)): + image_embeddings.append(self.image_encoder.encode_image(images[i*b: (i+1)*b]).cpu()) + elif self.video_encoder == "dinov2": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).pooler_output.cpu()) + elif self.video_encoder == "mixed": + feature_path1 = feature_path.replace("/feature_mixed/", "/feature/") + if not os.path.exists(feature_path1): + image_embeddings1 = [] + for i in range(math.ceil(images1["pixel_values"].shape[0] / b)): + image_embeddings1.append(self.image_encoder1(pixel_values=images1["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + image_embeddings1 = torch.cat(image_embeddings1, dim=0) + #np.savez(feature_path1, image_embeddings1, duration) + else: + data1 = np.load(feature_path1) + image_embeddings1 = torch.from_numpy(data1["arr_0"]) + feature_path2 = feature_path.replace("/feature_mixed/", "/feature_clip_vit2/") + if not os.path.exists(feature_path2): + image_embeddings2 = [] + for i in range(math.ceil(images2["pixel_values"].shape[0] / b)): + image_embeddings2.append(self.image_encoder2(pixel_values=images2["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + image_embeddings2 = torch.cat(image_embeddings2, dim=0) + np.savez(feature_path2, image_embeddings2, duration) + else: + data2 = np.load(feature_path2) + image_embeddings2 = torch.from_numpy(data2["arr_0"]) + feature_path3 = feature_path.replace("/feature_mixed/", "/feature_clip_convnext/") + if not os.path.exists(feature_path3): + image_embeddings3 = [] + for i in range(math.ceil(images3.shape[0] / b)): + image_embeddings3.append(self.image_encoder3.encode_image(images3[i*b: (i+1)*b]).cpu()) + image_embeddings3 = torch.cat(image_embeddings3, dim=0) + np.savez(feature_path3, image_embeddings3, duration) + else: + data3 = np.load(feature_path3) + image_embeddings3 = torch.from_numpy(data3["arr_0"]) + feature_path4 = feature_path.replace("/feature_mixed/", "/feature_dinov2/") + if not os.path.exists(feature_path4): + image_embeddings4 = [] + for i in range(math.ceil(images4["pixel_values"].shape[0] / b)): + image_embeddings4.append(self.image_encoder4(pixel_values=images4["pixel_values"][i*b: (i+1)*b]).pooler_output.cpu()) + image_embeddings4 = torch.cat(image_embeddings4, dim=0) + np.savez(feature_path4, image_embeddings4, duration) + else: + data4 = np.load(feature_path4) + image_embeddings4 = torch.from_numpy(data4["arr_0"]) + mixed_l = min([image_embeddings1.shape[0], image_embeddings2.shape[0], image_embeddings3.shape[0], image_embeddings4.shape[0]]) + for i in range(mixed_l): + image_embeddings.append(torch.cat([image_embeddings1[i:i+1,:], image_embeddings2[i:i+1,:], image_embeddings3[i:i+1,:], image_embeddings4[i:i+1,:]], dim=1)) + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + image_embeddings = torch.cat(image_embeddings, dim=0) + #print("image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + np.savez(feature_path, image_embeddings, duration) + else: + #print("video exist", feature_path) + data = np.load(feature_path) + image_embeddings = torch.from_numpy(data["arr_0"]) + #print("image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + duration = data["arr_1"].item() + if max_sample is None: + max_sample = int(duration * self.sampling_rate) + interpolated = [] + for i in range(start_sample, max_sample, self.frame_size): + j = min(round((i+self.frame_size//2) / self.sampling_rate / (duration / (image_embeddings.shape[0] - 1))), image_embeddings.shape[0] - 1) + interpolated.append(image_embeddings[j:j+1]) + if len(interpolated) >= l: + break + interpolated = torch.cat(interpolated, dim=0) + #ll = list(range(start_sample, max_sample, self.frame_size)) + #print("encode_video l", len(ll), l, round((ll[-1]+self.frame_size//2) / self.sampling_rate / (duration / (image_embeddings.shape[0] - 1))), image_embeddings.shape[0] - 1) + #print("encode_video one", video_path, duration, image_embeddings.shape, interpolated.shape, l) + video_embeddings.append(interpolated.unsqueeze(0)) + video_lens.append(interpolated.shape[1]) + max_length = max(video_lens) + if max_length == 0: + max_length = l + else: + max_length = l + for i in range(len(video_embeddings)): + if video_embeddings[i] is None: + video_embeddings[i] = torch.zeros(1, max_length, d) + continue + if video_embeddings[i].shape[1] < max_length: + video_embeddings[i] = torch.cat([video_embeddings[i], torch.zeros(1, max_length-video_embeddings[i].shape[1], d)], 1) + video_embeddings = torch.cat(video_embeddings, 0) + #print("encode_video", l, video_embeddings.shape, video_lens) + return video_embeddings.to(device) + + @staticmethod + def encode_video_frames(video_paths, l): + #### skip video frames + train_video_encoder = True + if not train_video_encoder: + midi_gts = [] + for video_path in video_paths: + if video_path is None: + #midi_gts.append(None) + continue + if isinstance(video_path, tuple): + video_path, start_sample, max_sample = video_path + else: + start_sample = 0 + max_sample = None + ####if video_path.startswith("/ailab-train2/speech/zhanghaomin/scps/instruments/"): + if "/piano_2h_cropped2_cuts/" in video_path: + pass + else: + #midi_gts.append(None) + continue + ####midi_gt + midi_gt = torch.from_numpy(np.load(video_path.replace(".mp4", ".3.npy")).astype(np.float32))[:,NOTTE_MIN:NOTE_MAX+1] + #print("midi_gt", midi_gt.shape, midi_gt.max(), midi_gt.min(), torch.abs(midi_gt).mean()) + midi_gts.append(midi_gt.unsqueeze(0)) + if len(midi_gts) == 0: + return None, None + max_length = l + for i in range(len(midi_gts)): + if midi_gts[i] is None: + midi_gts[i] = torch.zeros(1, max_length, NOTES) + continue + if midi_gts[i].shape[1] < max_length: + midi_gts[i] = torch.cat([midi_gts[i], torch.zeros(1, max_length-midi_gts[i].shape[1], NOTES)], 1) + elif midi_gts[i].shape[1] > max_length: + midi_gts[i] = midi_gts[i][:, :max_length, :] + midi_gts = torch.cat(midi_gts, 0) + video_frames = 1.0 + #print("encode_video_frames", l, midi_gts.shape, midi_gts.sum()) + return video_frames, midi_gts + + video_frames = [] + video_lens = [] + midi_gts = [] + for video_path in video_paths: + if video_path is None: + #video_frames.append(None) + video_lens.append(0) + #midi_gts.append(None) + continue + if isinstance(video_path, tuple): + video_path, start_sample, max_sample = video_path + else: + start_sample = 0 + max_sample = None + + ####if video_path.startswith("/ailab-train2/speech/zhanghaomin/scps/instruments/"): + if "/piano_2h_cropped2_cuts/" in video_path: + frames_raw_path = video_path.replace(".mp4", ".generated_frames_raw.2.npz") + if not os.path.exists(frames_raw_path): + frames, duration = read_frames_with_moviepy(video_path, max_frame_nums=None) + if frames is None: + #video_frames.append(None) + video_lens.append(0) + #midi_gts.append(None) + continue + #print("raw image size", frames.shape, video_path) + frames_resized = [] + for i in range(frames.shape[0]): + ########frames_resized.append(np.asarray(Image.fromarray(frames[i]).resize((320, 320)))) + ####frames_resized.append(np.asarray(Image.fromarray(frames[i]).resize((1024, 128)))) + + input_img = Image.fromarray(frames[i]).convert('L') + binarr = np.array(input_img) + input_img = Image.fromarray(binarr.astype(np.uint8)) + frames_resized.append(transform(input_img)) + ####frames_raw = np.array(frames_resized) + frames_raw = np.concatenate(frames_resized).astype(np.float32)[...,np.newaxis] + np.savez(frames_raw_path, frames_raw, duration) + else: + data = np.load(frames_raw_path) + frames_raw = data["arr_0"] + duration = data["arr_1"].item() + ####frames_raw = frames_raw.astype(np.float32) / 255.0 + #v_frames_raw = frames_raw[1:,:,:,:] - frames_raw[:-1,:,:,:] + #v_frames_raw = np.concatenate((np.zeros((1,v_frames_raw.shape[1],v_frames_raw.shape[2],v_frames_raw.shape[3]), dtype=np.float32), v_frames_raw), axis=0) + ##print("v_frames_raw", v_frames_raw.shape, v_frames_raw.max(), v_frames_raw.min(), np.abs(v_frames_raw).mean(), np.abs(v_frames_raw[0,:,:,:]).mean()) + #frames_raw = np.concatenate((frames_raw, v_frames_raw), axis=3) + frames_raw = torch.from_numpy(frames_raw) + #print("frames_raw", frames_raw.shape, frames_raw.max(), frames_raw.min(), torch.abs(frames_raw).mean(), "image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + else: + #video_frames.append(None) + video_lens.append(0) + #midi_gts.append(None) + continue + #print("frames_raw", frames_raw.shape, l) + + if max_sample is None: + max_sample = int(duration * 24000) + + ####video_multi = 3.0 + video_multi = 2.5 + + interpolated_frames_raw = [] + frame_size_video = int(video_multi*320) + for i in range(start_sample, max_sample+frame_size_video, frame_size_video): + j = min(round(i / 24000 / (duration / (frames_raw.shape[0] - 0))), frames_raw.shape[0] - 1) + #print(j) + interpolated_frames_raw.append(frames_raw[j:j+1]) + if len(interpolated_frames_raw) >= math.floor(l/video_multi)+1: + #print("break", len(interpolated_frames_raw), l, frames_raw.shape, j) + break + interpolated_frames_raw = torch.cat(interpolated_frames_raw, dim=0) + + ####v_interpolated_frames_raw = interpolated_frames_raw[1:,:,:,:] - interpolated_frames_raw[:-1,:,:,:] + ####v_interpolated_frames_raw = torch.cat((torch.zeros(1,v_interpolated_frames_raw.shape[1],v_interpolated_frames_raw.shape[2],v_interpolated_frames_raw.shape[3]), v_interpolated_frames_raw), 0) + #####print("v_interpolated_frames_raw", v_interpolated_frames_raw.shape, v_interpolated_frames_raw.max(), v_interpolated_frames_raw.min(), torch.abs(v_interpolated_frames_raw).mean(), torch.abs(v_interpolated_frames_raw[0,:,:,:]).mean()) + ####interpolated_frames_raw = torch.cat((interpolated_frames_raw, v_interpolated_frames_raw), 3) + + video_frames.append(interpolated_frames_raw.unsqueeze(0)) + video_lens.append(interpolated_frames_raw.shape[0]) + + ####midi_gt + ####midi_gt = torch.from_numpy(np.load(video_path.replace(".mp4", ".3.npy")).astype(np.float32))[:,NOTTE_MIN:NOTE_MAX+1] + #####print("midi_gt", midi_gt.shape, midi_gt.max(), midi_gt.min(), torch.abs(midi_gt).mean()) + ####midi_gts.append(midi_gt.unsqueeze(0)) + midi_gts.append(None) + + if len(video_frames) == 0: + return None, None + + max_length = max(video_lens) + if max_length == 0: + max_length = l + else: + max_length = l + max_length_video = max(math.floor(l/video_multi)+1, max(video_lens)) + + for i in range(len(video_frames)): + if video_frames[i] is None: + ########video_frames[i] = torch.zeros(1, max_length_video, 320, 320, 6) + ####video_frames[i] = torch.zeros(1, max_length_video, 128, 1024, 6) + video_frames[i] = torch.zeros(1, max_length_video, 100, 900, 1) + continue + if video_frames[i].shape[1] < max_length_video: + ########video_frames[i] = torch.cat([video_frames[i], torch.zeros(1, max_length_video-video_frames[i].shape[1], 320, 320, 6)], 1) + ####video_frames[i] = torch.cat([video_frames[i], torch.zeros(1, max_length_video-video_frames[i].shape[1], 128, 1024, 6)], 1) + video_frames[i] = torch.cat([video_frames[i], torch.zeros(1, max_length_video-video_frames[i].shape[1], 100, 900, 1)], 1) + video_frames = torch.cat(video_frames, 0) + video_frames = video_frames.permute(0,4,1,2,3) + for i in range(len(midi_gts)): + if midi_gts[i] is None: + midi_gts[i] = torch.zeros(1, max_length, NOTES) + continue + if midi_gts[i].shape[1] < max_length: + midi_gts[i] = torch.cat([midi_gts[i], torch.zeros(1, max_length-midi_gts[i].shape[1], NOTES)], 1) + elif midi_gts[i].shape[1] > max_length: + midi_gts[i] = midi_gts[i][:, :max_length, :] + midi_gts = torch.cat(midi_gts, 0) + #print("encode_video_frames", l, video_frames.shape, video_lens, midi_gts.shape, midi_gts.sum()) + return video_frames, midi_gts + + def transformer_with_pred_head( + self, + x: Float['b n d'], + cond: Float['b n d'] | None = None, + times: Float['b'] | None = None, + mask: Bool['b n'] | None = None, + text: Int['b nt'] | Float['b nt dt'] | None = None, + frames_embed: Float['b nf df'] | None = None, + prompt = None, + video_drop_prompt = None, + audio_drop_prompt = None, + drop_audio_cond: bool | None = None, + drop_text_cond: bool | None = None, + drop_text_prompt: bool | None = None, + return_drop_conditions = False + ): + seq_len = x.shape[-2] + bs = x.shape[0] + drop_audio_cond = [default(drop_audio_cond, self.training and random() < self.audiocond_drop_prob) for _ in range(bs)] + drop_text_cond = default(drop_text_cond, self.training and random() < self.cond_drop_prob) + drop_text_prompt = [default(drop_text_prompt, self.training and random() < self.prompt_drop_prob) for _ in range(bs)] + + if cond is not None: + for b in range(bs): + if drop_audio_cond[b]: + cond[b] = 0 + if audio_drop_prompt is not None and audio_drop_prompt[b]: + cond[b] = 0 + + if cond is not None: + if self.concat_cond: + # concat condition, given as using voicebox-like scheme + x = torch.cat((cond, x), dim = -1) + + x = self.proj_in(x) + + if cond is not None: + if not self.concat_cond: + # an alternative is to simply sum the condition + # seems to work fine + + cond = self.cond_proj_in(cond) + x = x + cond + + # whether to use a text embedding + + text_embed = None + if exists(text) and len(text.shape) == 3: + text_embed = text.clone() + if drop_text_cond: + for b in range(bs): + text_embed[b] = 0 + elif exists(text) and not drop_text_cond: + text_embed = self.embed_text(text, seq_len, mask = mask) + + context, context_mask = None, None + if prompt is not None: + #for b in range(bs): + # if drop_text_prompt[b]: + # prompt[b] = "" + if video_drop_prompt is not None: + for b in range(bs): + if video_drop_prompt[b]: + prompt[b] = "the sound of X X" + context, context_mask = self.encode_text(prompt) + for b in range(bs): + if drop_text_prompt[b]: + context[b] = 0 + if video_drop_prompt is not None and video_drop_prompt[b]: + context[b] = 0 + #print("cross attention", context.shape, context_mask.shape, x.shape, mask.shape, text_embed.shape if text_embed is not None else None, torch.mean(torch.abs(text_embed), dim=(1,2))) + #print("video_drop_prompt", prompt, video_drop_prompt, context.shape, torch.mean(torch.abs(context), dim=(1,2))) + #print("audio_drop_prompt", audio_drop_prompt, cond.shape, torch.mean(torch.abs(cond), dim=(1,2))) + + if self.proj_text is not None: + text_embed = self.proj_text(text_embed) + frames_embed = self.proj_frames(frames_embed) + + # attend + + attended = self.transformer( + x, + times = times, + mask = mask, + text_embed = text_embed, + frames_embed = frames_embed, + context = context, + context_mask = context_mask + ) + + pred = self.to_pred(attended) + + if not return_drop_conditions: + return pred + + return pred, drop_audio_cond, drop_text_cond, drop_text_prompt + + def cfg_transformer_with_pred_head( + self, + *args, + cfg_strength: float = 1., + remove_parallel_component: bool = True, + keep_parallel_frac: float = 0., + **kwargs, + ): + + pred = self.transformer_with_pred_head(*args, drop_audio_cond = False, drop_text_cond = False, drop_text_prompt = False, **kwargs) + + if cfg_strength < 1e-5: + return pred + + null_pred = self.transformer_with_pred_head(*args, drop_audio_cond = True, drop_text_cond = True, drop_text_prompt = True, **kwargs) + + cfg_update = pred - null_pred + + if remove_parallel_component: + # https://arxiv.org/abs/2410.02416 + parallel, orthogonal = project(cfg_update, pred) + cfg_update = orthogonal + parallel * keep_parallel_frac + + return pred + cfg_update * cfg_strength + + def add_noise(self, signal, mask, val): + if self.audiocond_snr is None: + return signal + if not val: + snr = np.random.uniform(self.audiocond_snr[0], self.audiocond_snr[1]) + else: + snr = (self.audiocond_snr[0] + self.audiocond_snr[1]) / 2.0 + #print("add_noise", self.audiocond_snr, snr, signal.shape, mask) # [True, ..., False] + noise = torch.randn_like(signal) + w = torch.abs(signal[mask]).mean() / (torch.abs(noise[mask]).mean() + 1e-6) / snr + return signal + noise * w + + @torch.no_grad() + def sample( + self, + cond: Float['b n d'] | Float['b nw'] | None = None, + *, + text: Int['b nt'] | list[str] | None = None, + lens: Int['b'] | None = None, + duration: int | Int['b'] | None = None, + steps = 32, + cfg_strength = 1., # they used a classifier free guidance strength of 1. + remove_parallel_component = True, + sway_sampling = True, + max_duration = 4096, # in case the duration predictor goes haywire + vocoder: Callable[[Float['b d n']], list[Float['_']]] | None = None, + return_raw_output: bool | None = None, + save_to_filename: str | None = None, + prompt = None, + video_drop_prompt = None, + audio_drop_prompt = None, + video_paths = None, + frames = None, + midis = None + ) -> ( + Float['b n d'], + list[Float['_']] + ): + self.eval() + + # raw wave + + if cond.ndim == 2: + cond = self.mel_spec(cond) + cond = rearrange(cond, 'b d n -> b n d') + assert cond.shape[-1] == self.num_channels + + batch, cond_seq_len, device = *cond.shape[:2], cond.device + + if frames is None: + frames_embed = torch.zeros(batch, cond_seq_len, NOTES, device=device) + else: + #### sampling settings + train_video_encoder = True + if train_video_encoder: + frames_embed = self.encode_frames(frames, cond_seq_len) + else: + frames_embed = midis + if frames_embed.shape[1] < cond_seq_len: + frames_embed = torch.cat([frames_embed, torch.zeros(1, cond_seq_len-frames_embed.shape[1], NOTES)], 1) + elif frames_embed.shape[1] > cond_seq_len: + frames_embed = frames_embed[:, :cond_seq_len, :] + #x0 = torch.zeros(batch, cond_seq_len, 128, device=device) + print("frames_embed midis cond", frames_embed.shape if frames_embed is not None and not isinstance(frames_embed, float) else frames_embed, frames_embed.sum() if frames_embed is not None and not isinstance(frames_embed, float) else frames_embed, midis.shape if midis is not None else midis, midis.sum() if midis is not None else midis, cond.shape if cond is not None else cond, cond.sum() if cond is not None else cond) + + if not exists(lens): + lens = torch.full((batch,), cond_seq_len, device = device, dtype = torch.long) + + if video_paths is not None: + text = self.encode_video(video_paths, cond_seq_len) + # text + elif isinstance(text, list): + text = self.tokenizer(text).to(device) + assert text.shape[0] == batch + + if exists(text): + text_lens = (text != -1).sum(dim = -1) + lens = torch.maximum(text_lens, lens) # make sure lengths are at least those of the text characters + + # duration + + cond_mask = lens_to_mask(lens) + + if exists(duration): + if isinstance(duration, int): + duration = torch.full((batch,), duration, device = device, dtype = torch.long) + + elif exists(self.duration_predictor): + duration = self.duration_predictor(cond, text = text, lens = lens, return_loss = False).long() + + duration = torch.maximum(lens, duration) # just add one token so something is generated + duration = duration.clamp(max = max_duration) + + assert duration.shape[0] == batch + + max_duration = duration.amax() + + cond = F.pad(cond, (0, 0, 0, max_duration - cond_seq_len), value = 0.) + cond_mask = F.pad(cond_mask, (0, max_duration - cond_mask.shape[-1]), value = False) + cond_mask = rearrange(cond_mask, '... -> ... 1') + + mask = lens_to_mask(duration) + #print("mask", duration, mask, mask.shape, lens, cond_mask, cond_mask.shape, text) + + # neural ode + + def fn(t, x): + # at each step, conditioning is fixed + + if lens[0] == duration[0]: + print("No cond", lens, duration) + step_cond = None + else: + step_cond = torch.where(cond_mask, self.add_noise(cond, cond_mask, True), torch.zeros_like(cond)) + #step_cond = cond + + # predict flow + + return self.cfg_transformer_with_pred_head( + x, + step_cond, + times = t, + text = text, + frames_embed = frames_embed, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + cfg_strength = cfg_strength, + remove_parallel_component = remove_parallel_component + ) + + ####torch.manual_seed(0) + y0 = torch.randn_like(cond) + #y0 = torch.randn_like(x0) + t = torch.linspace(0, 1, steps, device = self.device) + if sway_sampling: + t = t + -1.0 * (torch.cos(torch.pi / 2 * t) - 1 + t) + #print("@@@@", t) + + trajectory = odeint(fn, y0, t, **self.odeint_kwargs) + sampled = trajectory[-1] + + out = sampled + + if lens[0] != duration[0]: + out = torch.where(cond_mask, cond, out) + + # able to return raw untransformed output, if not using mel rep + + if exists(return_raw_output) and return_raw_output: + return out + + # take care of transforming mel to audio if `vocoder` is passed in, or if `use_vocos` is turned on + + if exists(vocoder): + assert not exists(self.vocos), '`use_vocos` should not be turned on if you are passing in a custom `vocoder` on sampling' + out = rearrange(out, 'b n d -> b d n') + out = vocoder(out) + + elif exists(self.vocos): + + audio = [] + for mel, one_mask in zip(out, mask): + #one_out = DB_to_amplitude(mel[one_mask], ref = 1., power = 0.5) + one_out = mel[one_mask] + + one_out = rearrange(one_out, 'n d -> 1 d n') + one_audio = self.vocos.decode(one_out) + one_audio = rearrange(one_audio, '1 nw -> nw') + audio.append(one_audio) + + out = audio + + if exists(save_to_filename): + assert exists(vocoder) or exists(self.vocos) + assert exists(self.sampling_rate) + + path = Path(save_to_filename) + parent_path = path.parents[0] + parent_path.mkdir(exist_ok = True, parents = True) + + for ind, one_audio in enumerate(out): + one_audio = rearrange(one_audio, 'nw -> 1 nw') + if len(out) == 1: + save_path = str(parent_path / f'{path.name}') + else: + save_path = str(parent_path / f'{ind + 1}.{path.name}') + torchaudio.save(save_path, one_audio.detach().cpu(), sample_rate = self.sampling_rate) + + return out + + def forward( + self, + inp: Float['b n d'] | Float['b nw'], # mel or raw wave + *, + text: Int['b nt'] | list[str] | None = None, + times: int | Int['b'] | None = None, + lens: Int['b'] | None = None, + velocity_consistency_model: E2TTS | None = None, + velocity_consistency_delta = 1e-3, + prompt = None, + video_drop_prompt=None, + audio_drop_prompt=None, + val = False, + video_paths=None, + frames=None, + midis=None + ): + need_velocity_loss = exists(velocity_consistency_model) and self.velocity_consistency_weight > 0. + + # handle raw wave + + if inp.ndim == 2: + inp = self.mel_spec(inp) + inp = rearrange(inp, 'b d n -> b n d') + assert inp.shape[-1] == self.num_channels + + batch, seq_len, dtype, device = *inp.shape[:2], inp.dtype, self.device + + if video_paths is not None: + text = self.encode_video(video_paths, seq_len) + # handle text as string + elif isinstance(text, list): + text = self.tokenizer(text).to(device) + #print("text tokenized", text[0]) + assert text.shape[0] == batch + + # lens and mask + + if not exists(lens): + lens = torch.full((batch,), seq_len, device = device) + + mask = lens_to_mask(lens, length = seq_len) + + # get a random span to mask out for training conditionally + + if not val: + if self.audiocond_drop_prob > 1.0: + frac_lengths = torch.zeros((batch,), device = self.device).float().uniform_(1.0,1.0) + else: + frac_lengths = torch.zeros((batch,), device = self.device).float().uniform_(*self.frac_lengths_mask) + else: + frac_lengths = torch.tensor([(0.7+1.0)/2.0]*batch, device = self.device).float() + rand_span_mask = mask_from_frac_lengths(lens, frac_lengths, max_length = seq_len, val = val) + + if exists(mask): + rand_span_mask &= mask + + # mel is x1 + + x1 = inp + + # main conditional flow training logic + # just ~5 loc + + # x0 is gaussian noise + + if val: + torch.manual_seed(0) + x0 = torch.randn_like(x1) + if val: + torch.manual_seed(int(time.time()*1000)) + + # t is random times from above + + if times is None: + times = torch.rand((batch,), dtype = dtype, device = self.device) + else: + times = torch.tensor((times,)*batch, dtype = dtype, device = self.device) + t = rearrange(times, 'b -> b 1 1') + + # if need velocity consistency, make sure time does not exceed 1. + + if need_velocity_loss: + t = t * (1. - velocity_consistency_delta) + + # sample xt (w in the paper) + + w = (1. - t) * x0 + t * x1 + + flow = x1 - x0 + + # only predict what is within the random mask span for infilling + + if self.audiocond_drop_prob > 1.0: + cond = None + else: + cond = einx.where( + 'b n, b n d, b n d -> b n d', + rand_span_mask, + torch.zeros_like(x1), self.add_noise(x1, ~rand_span_mask, val) + ) + + #### training settings + train_video_encoder = True + train_v2a = True + use_midi_gt = False + train_video_encoder = train_video_encoder + ####train_v2a = train_v2a or val + #print("train_video_encoder", train_video_encoder, use_midi_gt, train_v2a) + + #### + if frames is None: + frames_embed = torch.zeros(batch, seq_len, NOTES, device=device) + midis = torch.zeros(batch, seq_len, NOTES, device=device) + else: + if train_video_encoder: + frames_embed = self.encode_frames(frames, seq_len) + else: + frames_embed = midis + #print("frames_embed midis cond", frames_embed.shape if frames_embed is not None and not isinstance(frames_embed, float) else frames_embed, frames_embed.sum() if frames_embed is not None and not isinstance(frames_embed, float) else frames_embed, midis.shape, midis.sum(), cond.shape if cond is not None else cond, cond.sum() if cond is not None else cond, x1.shape) + if train_video_encoder: + #lw = 1.0 + lw = torch.abs(midis-0.10) + #lw = torch.max(torch.abs(midis-0.20), torch.tensor(0.20)) + loss_midi = F.mse_loss(frames_embed, midis, reduction = 'none') * lw + #loss_midi = nn.BCELoss(reduction = 'none')(frames_embed, midis) * lw + #print("loss_midi", loss_midi.shape, mask.shape, mask, rand_span_mask.shape, rand_span_mask) + loss_midi = loss_midi[mask[-frames_embed.shape[0]:,...]].mean() + + b, t, f = frames_embed.shape + frames_embed_t = frames_embed[:,:(t//3)*3,:].reshape(b,t//3,3,f).mean(dim=2) + midis_t = midis[:,:(t//3)*3,:].reshape(b,t//3,3,f).mean(dim=2) + mask_t = mask[-frames_embed.shape[0]:,:(t//3)*3].reshape(b,t//3,3).to(torch.float32).mean(dim=2) >= 0.99 + tp = ((frames_embed_t>=0.4)*(midis_t>=0.5)).to(torch.float)[mask_t[-frames_embed_t.shape[0]:,...]].sum() + fp = ((frames_embed_t>=0.4)*(midis_t<0.5)).to(torch.float)[mask_t[-frames_embed_t.shape[0]:,...]].sum() + fn = ((frames_embed_t<0.4)*(midis_t>=0.5)).to(torch.float)[mask_t[-frames_embed_t.shape[0]:,...]].sum() + tn = ((frames_embed_t<0.4)*(midis_t<0.5)).to(torch.float)[mask_t[-frames_embed_t.shape[0]:,...]].sum() + #print("tp fp fn tn", tp, fp, fn, tn) + pre = tp / (tp + fp) if (tp + fp) != 0 else torch.tensor(0.0, device=device) + rec = tp / (tp + fn) if (tp + fn) != 0 else torch.tensor(0.0, device=device) + f1 = 2 * tp / (2 * tp + fp + fn) if (2 * tp + fp + fn) != 0 else torch.tensor(0.0, device=device) + acc = tp / (tp + fp + fn) if (tp + fp + fn) != 0 else torch.tensor(0.0, device=device) + else: + loss_midi = torch.tensor(0.0, device=device) + + tp = torch.tensor(0.0, device=device) + fp = torch.tensor(0.0, device=device) + fn = torch.tensor(0.0, device=device) + tn = torch.tensor(0.0, device=device) + pre = torch.tensor(0.0, device=device) + rec = torch.tensor(0.0, device=device) + f1 = torch.tensor(0.0, device=device) + acc = torch.tensor(0.0, device=device) + #if train_video_encoder: # loss_midi_zeros * 100.0 # 0.2131/0.1856 # 0.2819/0.2417 # 2.451/ + # loss_midi_zeros = F.mse_loss(torch.zeros_like(midis), midis, reduction = 'none') + # loss_midi_zeros = loss_midi_zeros[mask[-frames_embed.shape[0]:,...]].mean() + #else: + # loss_midi_zeros = torch.tensor(0.0, device=device) + + if train_v2a: + if use_midi_gt: + frames_embed = midis + if frames_embed.shape[0] < x1.shape[0]: + frames_embed = torch.cat((torch.zeros(x1.shape[0]-frames_embed.shape[0],frames_embed.shape[1],frames_embed.shape[2],device=frames_embed.device), frames_embed), 0) + + # transformer and prediction head + + if not val: + pred, did_drop_audio_cond, did_drop_text_cond, did_drop_text_prompt = self.transformer_with_pred_head( + w, + cond, + times = times, + text = text, + frames_embed = frames_embed, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + return_drop_conditions = True + ) + else: + pred, did_drop_audio_cond, did_drop_text_cond, did_drop_text_prompt = self.transformer_with_pred_head( + w, + cond, + times = times, + text = text, + frames_embed = frames_embed, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + drop_audio_cond = False, + drop_text_cond = False, + drop_text_prompt = False, + return_drop_conditions = True + ) + + # maybe velocity consistency loss + + velocity_loss = self.zero + + if need_velocity_loss: + + #t_with_delta = t + velocity_consistency_delta + #w_with_delta = (1. - t_with_delta) * x0 + t_with_delta * x1 + + with torch.no_grad(): + ema_pred = velocity_consistency_model.transformer_with_pred_head( + w, #w_with_delta, + cond, + times = times, #times + velocity_consistency_delta, + text = text, + frames_embed = frames_embed, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + drop_audio_cond = did_drop_audio_cond, + drop_text_cond = did_drop_text_cond, + drop_text_prompt = did_drop_text_prompt + ) + + #velocity_loss = F.mse_loss(pred, ema_pred, reduction = 'none') + velocity_loss = F.mse_loss(ema_pred, flow, reduction = 'none') + velocity_loss = (velocity_loss.mean(-1)*rand_span_mask).mean(-1) #.mean() + + ref_losses = velocity_loss[-2:, ...] + ref_losses_w, ref_losses_l = ref_losses.chunk(2) + raw_ref_loss = 0.5 * (ref_losses_w.mean() + ref_losses_l.mean()) + ref_diff = ref_losses_w - ref_losses_l + else: + ref_losses_w, ref_losses_l = 0, 0 + + # flow matching loss + + loss = F.mse_loss(pred, flow, reduction = 'none') + + #print("loss", loss.shape, loss, "rand_span_mask", rand_span_mask.shape, rand_span_mask, "loss[rand_span_mask]", loss[rand_span_mask].shape, loss[rand_span_mask]) + + #### dpo + loss = loss[rand_span_mask].mean() + loss_dpo = torch.tensor(0.0, device=device) + ####if val: + #### loss = loss[rand_span_mask].mean() + #### loss_dpo = torch.tensor(0.0, device=device) + #### model_losses_w, model_losses_l = 0, 0 + ####else: + #### loss_fm = loss[rand_span_mask].mean() + #### loss = (loss.mean(-1)*rand_span_mask).mean(-1) #.mean() + #### + #### model_losses = loss[-2:, ...] + #### model_losses_w, model_losses_l = model_losses.chunk(2) + #### raw_model_loss = 0.5 * (model_losses_w.mean() + model_losses_l.mean()) + #### model_diff = model_losses_w - model_losses_l + #### + #### scale_term = -1 + #### inside_term = scale_term * (model_diff - ref_diff) + #### loss_dpo = -1 * F.logsigmoid(inside_term).mean() + #### loss = loss_fm + #### dpo + else: + pred = torch.zeros_like(x0) + loss = torch.tensor(0.0, device=device) + + # total loss and get breakdown + + #midi_w = 100.0 + midi_w = 10.0 + #total_loss = loss + #total_loss = loss + loss_midi * midi_w + total_loss = loss + loss_midi * midi_w + loss_dpo + ####breakdown = LossBreakdown(loss, loss_midi * midi_w, pre, rec) + breakdown = LossBreakdown(pre, rec, f1, acc) + #breakdown = LossBreakdown(tp, fp, fn, tn) + #### dpo + print("loss", loss, loss_midi * midi_w) + #print("loss", loss, loss_midi * midi_w, loss_dpo, model_losses_w, model_losses_l, ref_losses_w, ref_losses_l) + #### dpo + + # return total loss and bunch of intermediates + + return E2TTSReturn(total_loss, cond if cond is not None else w, pred, x0 + pred, breakdown) diff --git a/src/e2_tts_pytorch/e2_tts_crossatt6.py b/src/e2_tts_pytorch/e2_tts_crossatt6.py new file mode 100644 index 0000000000000000000000000000000000000000..35eae4c0a3b129ffeecba09b42b5cf23b8214230 --- /dev/null +++ b/src/e2_tts_pytorch/e2_tts_crossatt6.py @@ -0,0 +1,2186 @@ +""" +ein notation: +b - batch +n - sequence +nt - text sequence +nw - raw wave length +d - dimension +dt - dimension text +""" + +from __future__ import annotations + +from pathlib import Path +from random import random +from random import sample as random_sample +from functools import partial +from itertools import zip_longest +from collections import namedtuple + +from typing import Literal, Callable + +import jaxtyping +from beartype import beartype + +import torch +import torch.nn.functional as F +from torch import nn, tensor, Tensor, from_numpy +from torch.nn import Module, ModuleList, Sequential, Linear +from torch.nn.utils.rnn import pad_sequence + +import torchaudio +from torchaudio.functional import DB_to_amplitude +from torchdiffeq import odeint + +import einx +from einops.layers.torch import Rearrange +from einops import rearrange, repeat, reduce, pack, unpack + +from x_transformers import ( + Attention, + FeedForward, + RMSNorm, + AdaptiveRMSNorm, +) + +from x_transformers.x_transformers import RotaryEmbedding + +import sys +sys.path.insert(0, "/zhanghaomin/codes3/vocos-main/") +from vocos import Vocos + +from transformers import AutoTokenizer +from transformers import T5EncoderModel +from transformers import EncodecModel, AutoProcessor + +import os +import math +import traceback +import numpy as np +from moviepy.editor import AudioFileClip, VideoFileClip +from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection +#import open_clip +from transformers import AutoImageProcessor, AutoModel +from PIL import Image +import time + +import warnings +warnings.filterwarnings("ignore") + +def normalize_wav(waveform): + waveform = waveform - torch.mean(waveform) + waveform = waveform / (torch.max(torch.abs(waveform[0, :])) + 1e-8) + return waveform * 0.5 + +def read_frames_with_moviepy(video_path, max_frame_nums=None): + try: + clip = VideoFileClip(video_path) + duration = clip.duration + frames = [] + for frame in clip.iter_frames(): + frames.append(frame) + except: + print("Error read_frames_with_moviepy", video_path) + traceback.print_exc() + return None, None + if max_frame_nums is not None: + frames_idx = np.linspace(0, len(frames) - 1, max_frame_nums, dtype=int) + return np.array(frames)[frames_idx, ...], duration + else: + return np.array(frames), duration + +pad_sequence = partial(pad_sequence, batch_first = True) + +# constants + +class TorchTyping: + def __init__(self, abstract_dtype): + self.abstract_dtype = abstract_dtype + + def __getitem__(self, shapes: str): + return self.abstract_dtype[Tensor, shapes] + +Float = TorchTyping(jaxtyping.Float) +Int = TorchTyping(jaxtyping.Int) +Bool = TorchTyping(jaxtyping.Bool) + +# named tuples + +LossBreakdown = namedtuple('LossBreakdown', ['flow', 'velocity_consistency']) + +E2TTSReturn = namedtuple('E2TTS', ['loss', 'cond', 'pred_flow', 'pred_data', 'loss_breakdown']) + +# helpers + +def exists(v): + return v is not None + +def default(v, d): + return v if exists(v) else d + +def divisible_by(num, den): + return (num % den) == 0 + +def pack_one_with_inverse(x, pattern): + packed, packed_shape = pack([x], pattern) + + def inverse(x, inverse_pattern = None): + inverse_pattern = default(inverse_pattern, pattern) + return unpack(x, packed_shape, inverse_pattern)[0] + + return packed, inverse + +class Identity(Module): + def forward(self, x, **kwargs): + return x + +# tensor helpers + +def project(x, y): + x, inverse = pack_one_with_inverse(x, 'b *') + y, _ = pack_one_with_inverse(y, 'b *') + + dtype = x.dtype + x, y = x.double(), y.double() + unit = F.normalize(y, dim = -1) + + parallel = (x * unit).sum(dim = -1, keepdim = True) * unit + orthogonal = x - parallel + + return inverse(parallel).to(dtype), inverse(orthogonal).to(dtype) + +# simple utf-8 tokenizer, since paper went character based + +def list_str_to_tensor( + text: list[str], + padding_value = -1 +) -> Int['b nt']: + + list_tensors = [tensor([*bytes(t, 'UTF-8')]) for t in text] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + +# simple english phoneme-based tokenizer + +from g2p_en import G2p +import jieba +from pypinyin import lazy_pinyin, Style + +def get_g2p_en_encode(): + g2p = G2p() + + # used by @lucasnewman successfully here + # https://github.com/lucasnewman/e2-tts-pytorch/blob/ljspeech-test/e2_tts_pytorch/e2_tts.py + + phoneme_to_index = g2p.p2idx + num_phonemes = len(phoneme_to_index) + + extended_chars = [' ', ',', '.', '-', '!', '?', '\'', '"', '...', '..', '. .', '. . .', '. . . .', '. . . . .', '. ...', '... .', '.. ..'] + num_extended_chars = len(extended_chars) + + extended_chars_dict = {p: (num_phonemes + i) for i, p in enumerate(extended_chars)} + phoneme_to_index = {**phoneme_to_index, **extended_chars_dict} + + def encode( + text: list[str], + padding_value = -1 + ) -> Int['b nt']: + + phonemes = [g2p(t) for t in text] + list_tensors = [tensor([phoneme_to_index[p] for p in one_phoneme]) for one_phoneme in phonemes] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + + return encode, (num_phonemes + num_extended_chars) + +def all_en(word): + res = word.replace("'", "").encode('utf-8').isalpha() + return res + +def all_ch(word): + res = True + for w in word: + if not '\u4e00' <= w <= '\u9fff': + res = False + return res + +def get_g2p_zh_encode(): + puncs = ['，', '。', '？', '、'] + pinyins = ['a', 'a1', 'ai1', 'ai2', 'ai3', 'ai4', 'an1', 'an3', 'an4', 'ang1', 'ang2', 'ang4', 'ao1', 'ao2', 'ao3', 'ao4', 'ba', 'ba1', 'ba2', 'ba3', 'ba4', 'bai1', 'bai2', 'bai3', 'bai4', 'ban1', 'ban2', 'ban3', 'ban4', 'bang1', 'bang2', 'bang3', 'bang4', 'bao1', 'bao2', 'bao3', 'bao4', 'bei', 'bei1', 'bei2', 'bei3', 'bei4', 'ben1', 'ben2', 'ben3', 'ben4', 'beng1', 'beng2', 'beng4', 'bi1', 'bi2', 'bi3', 'bi4', 'bian1', 'bian2', 'bian3', 'bian4', 'biao1', 'biao2', 'biao3', 'bie1', 'bie2', 'bie3', 'bie4', 'bin1', 'bin4', 'bing1', 'bing2', 'bing3', 'bing4', 'bo', 'bo1', 'bo2', 'bo3', 'bo4', 'bu2', 'bu3', 'bu4', 'ca1', 'cai1', 'cai2', 'cai3', 'cai4', 'can1', 'can2', 'can3', 'can4', 'cang1', 'cang2', 'cao1', 'cao2', 'cao3', 'ce4', 'cen1', 'cen2', 'ceng1', 'ceng2', 'ceng4', 'cha1', 'cha2', 'cha3', 'cha4', 'chai1', 'chai2', 'chan1', 'chan2', 'chan3', 'chan4', 'chang1', 'chang2', 'chang3', 'chang4', 'chao1', 'chao2', 'chao3', 'che1', 'che2', 'che3', 'che4', 'chen1', 'chen2', 'chen3', 'chen4', 'cheng1', 'cheng2', 'cheng3', 'cheng4', 'chi1', 'chi2', 'chi3', 'chi4', 'chong1', 'chong2', 'chong3', 'chong4', 'chou1', 'chou2', 'chou3', 'chou4', 'chu1', 'chu2', 'chu3', 'chu4', 'chua1', 'chuai1', 'chuai2', 'chuai3', 'chuai4', 'chuan1', 'chuan2', 'chuan3', 'chuan4', 'chuang1', 'chuang2', 'chuang3', 'chuang4', 'chui1', 'chui2', 'chun1', 'chun2', 'chun3', 'chuo1', 'chuo4', 'ci1', 'ci2', 'ci3', 'ci4', 'cong1', 'cong2', 'cou4', 'cu1', 'cu4', 'cuan1', 'cuan2', 'cuan4', 'cui1', 'cui3', 'cui4', 'cun1', 'cun2', 'cun4', 'cuo1', 'cuo2', 'cuo4', 'da', 'da1', 'da2', 'da3', 'da4', 'dai1', 'dai3', 'dai4', 'dan1', 'dan2', 'dan3', 'dan4', 'dang1', 'dang2', 'dang3', 'dang4', 'dao1', 'dao2', 'dao3', 'dao4', 'de', 'de1', 'de2', 'dei3', 'den4', 'deng1', 'deng2', 'deng3', 'deng4', 'di1', 'di2', 'di3', 'di4', 'dia3', 'dian1', 'dian2', 'dian3', 'dian4', 'diao1', 'diao3', 'diao4', 'die1', 'die2', 'ding1', 'ding2', 'ding3', 'ding4', 'diu1', 'dong1', 'dong3', 'dong4', 'dou1', 'dou2', 'dou3', 'dou4', 'du1', 'du2', 'du3', 'du4', 'duan1', 'duan2', 'duan3', 'duan4', 'dui1', 'dui4', 'dun1', 'dun3', 'dun4', 'duo1', 'duo2', 'duo3', 'duo4', 'e1', 'e2', 'e3', 'e4', 'ei2', 'en1', 'en4', 'er', 'er2', 'er3', 'er4', 'fa1', 'fa2', 'fa3', 'fa4', 'fan1', 'fan2', 'fan3', 'fan4', 'fang1', 'fang2', 'fang3', 'fang4', 'fei1', 'fei2', 'fei3', 'fei4', 'fen1', 'fen2', 'fen3', 'fen4', 'feng1', 'feng2', 'feng3', 'feng4', 'fo2', 'fou2', 'fou3', 'fu1', 'fu2', 'fu3', 'fu4', 'ga1', 'ga2', 'ga4', 'gai1', 'gai3', 'gai4', 'gan1', 'gan2', 'gan3', 'gan4', 'gang1', 'gang2', 'gang3', 'gang4', 'gao1', 'gao2', 'gao3', 'gao4', 'ge1', 'ge2', 'ge3', 'ge4', 'gei2', 'gei3', 'gen1', 'gen2', 'gen3', 'gen4', 'geng1', 'geng3', 'geng4', 'gong1', 'gong3', 'gong4', 'gou1', 'gou2', 'gou3', 'gou4', 'gu', 'gu1', 'gu2', 'gu3', 'gu4', 'gua1', 'gua2', 'gua3', 'gua4', 'guai1', 'guai2', 'guai3', 'guai4', 'guan1', 'guan2', 'guan3', 'guan4', 'guang1', 'guang2', 'guang3', 'guang4', 'gui1', 'gui2', 'gui3', 'gui4', 'gun3', 'gun4', 'guo1', 'guo2', 'guo3', 'guo4', 'ha1', 'ha2', 'ha3', 'hai1', 'hai2', 'hai3', 'hai4', 'han1', 'han2', 'han3', 'han4', 'hang1', 'hang2', 'hang4', 'hao1', 'hao2', 'hao3', 'hao4', 'he1', 'he2', 'he4', 'hei1', 'hen2', 'hen3', 'hen4', 'heng1', 'heng2', 'heng4', 'hong1', 'hong2', 'hong3', 'hong4', 'hou1', 'hou2', 'hou3', 'hou4', 'hu1', 'hu2', 'hu3', 'hu4', 'hua1', 'hua2', 'hua4', 'huai2', 'huai4', 'huan1', 'huan2', 'huan3', 'huan4', 'huang1', 'huang2', 'huang3', 'huang4', 'hui1', 'hui2', 'hui3', 'hui4', 'hun1', 'hun2', 'hun4', 'huo', 'huo1', 'huo2', 'huo3', 'huo4', 'ji1', 'ji2', 'ji3', 'ji4', 'jia', 'jia1', 'jia2', 'jia3', 'jia4', 'jian1', 'jian2', 'jian3', 'jian4', 'jiang1', 'jiang2', 'jiang3', 'jiang4', 'jiao1', 'jiao2', 'jiao3', 'jiao4', 'jie1', 'jie2', 'jie3', 'jie4', 'jin1', 'jin2', 'jin3', 'jin4', 'jing1', 'jing2', 'jing3', 'jing4', 'jiong3', 'jiu1', 'jiu2', 'jiu3', 'jiu4', 'ju1', 'ju2', 'ju3', 'ju4', 'juan1', 'juan2', 'juan3', 'juan4', 'jue1', 'jue2', 'jue4', 'jun1', 'jun4', 'ka1', 'ka2', 'ka3', 'kai1', 'kai2', 'kai3', 'kai4', 'kan1', 'kan2', 'kan3', 'kan4', 'kang1', 'kang2', 'kang4', 'kao2', 'kao3', 'kao4', 'ke1', 'ke2', 'ke3', 'ke4', 'ken3', 'keng1', 'kong1', 'kong3', 'kong4', 'kou1', 'kou2', 'kou3', 'kou4', 'ku1', 'ku2', 'ku3', 'ku4', 'kua1', 'kua3', 'kua4', 'kuai3', 'kuai4', 'kuan1', 'kuan2', 'kuan3', 'kuang1', 'kuang2', 'kuang4', 'kui1', 'kui2', 'kui3', 'kui4', 'kun1', 'kun3', 'kun4', 'kuo4', 'la', 'la1', 'la2', 'la3', 'la4', 'lai2', 'lai4', 'lan2', 'lan3', 'lan4', 'lang1', 'lang2', 'lang3', 'lang4', 'lao1', 'lao2', 'lao3', 'lao4', 'le', 'le1', 'le4', 'lei', 'lei1', 'lei2', 'lei3', 'lei4', 'leng1', 'leng2', 'leng3', 'leng4', 'li', 'li1', 'li2', 'li3', 'li4', 'lia3', 'lian2', 'lian3', 'lian4', 'liang2', 'liang3', 'liang4', 'liao1', 'liao2', 'liao3', 'liao4', 'lie1', 'lie2', 'lie3', 'lie4', 'lin1', 'lin2', 'lin3', 'lin4', 'ling2', 'ling3', 'ling4', 'liu1', 'liu2', 'liu3', 'liu4', 'long1', 'long2', 'long3', 'long4', 'lou1', 'lou2', 'lou3', 'lou4', 'lu1', 'lu2', 'lu3', 'lu4', 'luan2', 'luan3', 'luan4', 'lun1', 'lun2', 'lun4', 'luo1', 'luo2', 'luo3', 'luo4', 'lv2', 'lv3', 'lv4', 'lve3', 'lve4', 'ma', 'ma1', 'ma2', 'ma3', 'ma4', 'mai2', 'mai3', 'mai4', 'man2', 'man3', 'man4', 'mang2', 'mang3', 'mao1', 'mao2', 'mao3', 'mao4', 'me', 'mei2', 'mei3', 'mei4', 'men', 'men1', 'men2', 'men4', 'meng1', 'meng2', 'meng3', 'meng4', 'mi1', 'mi2', 'mi3', 'mi4', 'mian2', 'mian3', 'mian4', 'miao1', 'miao2', 'miao3', 'miao4', 'mie1', 'mie4', 'min2', 'min3', 'ming2', 'ming3', 'ming4', 'miu4', 'mo1', 'mo2', 'mo3', 'mo4', 'mou1', 'mou2', 'mou3', 'mu2', 'mu3', 'mu4', 'n2', 'na1', 'na2', 'na3', 'na4', 'nai2', 'nai3', 'nai4', 'nan1', 'nan2', 'nan3', 'nan4', 'nang1', 'nang2', 'nao1', 'nao2', 'nao3', 'nao4', 'ne', 'ne2', 'ne4', 'nei3', 'nei4', 'nen4', 'neng2', 'ni1', 'ni2', 'ni3', 'ni4', 'nian1', 'nian2', 'nian3', 'nian4', 'niang2', 'niang4', 'niao2', 'niao3', 'niao4', 'nie1', 'nie4', 'nin2', 'ning2', 'ning3', 'ning4', 'niu1', 'niu2', 'niu3', 'niu4', 'nong2', 'nong4', 'nou4', 'nu2', 'nu3', 'nu4', 'nuan3', 'nuo2', 'nuo4', 'nv2', 'nv3', 'nve4', 'o1', 'o2', 'ou1', 'ou3', 'ou4', 'pa1', 'pa2', 'pa4', 'pai1', 'pai2', 'pai3', 'pai4', 'pan1', 'pan2', 'pan4', 'pang1', 'pang2', 'pang4', 'pao1', 'pao2', 'pao3', 'pao4', 'pei1', 'pei2', 'pei4', 'pen1', 'pen2', 'pen4', 'peng1', 'peng2', 'peng3', 'peng4', 'pi1', 'pi2', 'pi3', 'pi4', 'pian1', 'pian2', 'pian4', 'piao1', 'piao2', 'piao3', 'piao4', 'pie1', 'pie2', 'pie3', 'pin1', 'pin2', 'pin3', 'pin4', 'ping1', 'ping2', 'po1', 'po2', 'po3', 'po4', 'pou1', 'pu1', 'pu2', 'pu3', 'pu4', 'qi1', 'qi2', 'qi3', 'qi4', 'qia1', 'qia3', 'qia4', 'qian1', 'qian2', 'qian3', 'qian4', 'qiang1', 'qiang2', 'qiang3', 'qiang4', 'qiao1', 'qiao2', 'qiao3', 'qiao4', 'qie1', 'qie2', 'qie3', 'qie4', 'qin1', 'qin2', 'qin3', 'qin4', 'qing1', 'qing2', 'qing3', 'qing4', 'qiong1', 'qiong2', 'qiu1', 'qiu2', 'qiu3', 'qu1', 'qu2', 'qu3', 'qu4', 'quan1', 'quan2', 'quan3', 'quan4', 'que1', 'que2', 'que4', 'qun2', 'ran2', 'ran3', 'rang1', 'rang2', 'rang3', 'rang4', 'rao2', 'rao3', 'rao4', 're2', 're3', 're4', 'ren2', 'ren3', 'ren4', 'reng1', 'reng2', 'ri4', 'rong1', 'rong2', 'rong3', 'rou2', 'rou4', 'ru2', 'ru3', 'ru4', 'ruan2', 'ruan3', 'rui3', 'rui4', 'run4', 'ruo4', 'sa1', 'sa2', 'sa3', 'sa4', 'sai1', 'sai4', 'san1', 'san2', 'san3', 'san4', 'sang1', 'sang3', 'sang4', 'sao1', 'sao2', 'sao3', 'sao4', 'se4', 'sen1', 'seng1', 'sha1', 'sha2', 'sha3', 'sha4', 'shai1', 'shai2', 'shai3', 'shai4', 'shan1', 'shan3', 'shan4', 'shang', 'shang1', 'shang3', 'shang4', 'shao1', 'shao2', 'shao3', 'shao4', 'she1', 'she2', 'she3', 'she4', 'shei2', 'shen1', 'shen2', 'shen3', 'shen4', 'sheng1', 'sheng2', 'sheng3', 'sheng4', 'shi', 'shi1', 'shi2', 'shi3', 'shi4', 'shou1', 'shou2', 'shou3', 'shou4', 'shu1', 'shu2', 'shu3', 'shu4', 'shua1', 'shua2', 'shua3', 'shua4', 'shuai1', 'shuai3', 'shuai4', 'shuan1', 'shuan4', 'shuang1', 'shuang3', 'shui2', 'shui3', 'shui4', 'shun3', 'shun4', 'shuo1', 'shuo4', 'si1', 'si2', 'si3', 'si4', 'song1', 'song3', 'song4', 'sou1', 'sou3', 'sou4', 'su1', 'su2', 'su4', 'suan1', 'suan4', 'sui1', 'sui2', 'sui3', 'sui4', 'sun1', 'sun3', 'suo', 'suo1', 'suo2', 'suo3', 'ta1', 'ta3', 'ta4', 'tai1', 'tai2', 'tai4', 'tan1', 'tan2', 'tan3', 'tan4', 'tang1', 'tang2', 'tang3', 'tang4', 'tao1', 'tao2', 'tao3', 'tao4', 'te4', 'teng2', 'ti1', 'ti2', 'ti3', 'ti4', 'tian1', 'tian2', 'tian3', 'tiao1', 'tiao2', 'tiao3', 'tiao4', 'tie1', 'tie2', 'tie3', 'tie4', 'ting1', 'ting2', 'ting3', 'tong1', 'tong2', 'tong3', 'tong4', 'tou', 'tou1', 'tou2', 'tou4', 'tu1', 'tu2', 'tu3', 'tu4', 'tuan1', 'tuan2', 'tui1', 'tui2', 'tui3', 'tui4', 'tun1', 'tun2', 'tun4', 'tuo1', 'tuo2', 'tuo3', 'tuo4', 'wa', 'wa1', 'wa2', 'wa3', 'wa4', 'wai1', 'wai3', 'wai4', 'wan1', 'wan2', 'wan3', 'wan4', 'wang1', 'wang2', 'wang3', 'wang4', 'wei1', 'wei2', 'wei3', 'wei4', 'wen1', 'wen2', 'wen3', 'wen4', 'weng1', 'weng4', 'wo1', 'wo3', 'wo4', 'wu1', 'wu2', 'wu3', 'wu4', 'xi1', 'xi2', 'xi3', 'xi4', 'xia1', 'xia2', 'xia4', 'xian1', 'xian2', 'xian3', 'xian4', 'xiang1', 'xiang2', 'xiang3', 'xiang4', 'xiao1', 'xiao2', 'xiao3', 'xiao4', 'xie1', 'xie2', 'xie3', 'xie4', 'xin1', 'xin2', 'xin4', 'xing1', 'xing2', 'xing3', 'xing4', 'xiong1', 'xiong2', 'xiu1', 'xiu3', 'xiu4', 'xu', 'xu1', 'xu2', 'xu3', 'xu4', 'xuan1', 'xuan2', 'xuan3', 'xuan4', 'xue1', 'xue2', 'xue3', 'xue4', 'xun1', 'xun2', 'xun4', 'ya', 'ya1', 'ya2', 'ya3', 'ya4', 'yan1', 'yan2', 'yan3', 'yan4', 'yang1', 'yang2', 'yang3', 'yang4', 'yao1', 'yao2', 'yao3', 'yao4', 'ye1', 'ye2', 'ye3', 'ye4', 'yi1', 'yi2', 'yi3', 'yi4', 'yin1', 'yin2', 'yin3', 'yin4', 'ying1', 'ying2', 'ying3', 'ying4', 'yo1', 'yong1', 'yong3', 'yong4', 'you1', 'you2', 'you3', 'you4', 'yu1', 'yu2', 'yu3', 'yu4', 'yuan1', 'yuan2', 'yuan3', 'yuan4', 'yue1', 'yue4', 'yun1', 'yun2', 'yun3', 'yun4', 'za1', 'za2', 'za3', 'zai1', 'zai3', 'zai4', 'zan1', 'zan2', 'zan3', 'zan4', 'zang1', 'zang4', 'zao1', 'zao2', 'zao3', 'zao4', 'ze2', 'ze4', 'zei2', 'zen3', 'zeng1', 'zeng4', 'zha1', 'zha2', 'zha3', 'zha4', 'zhai1', 'zhai2', 'zhai3', 'zhai4', 'zhan1', 'zhan2', 'zhan3', 'zhan4', 'zhang1', 'zhang2', 'zhang3', 'zhang4', 'zhao1', 'zhao2', 'zhao3', 'zhao4', 'zhe', 'zhe1', 'zhe2', 'zhe3', 'zhe4', 'zhen1', 'zhen2', 'zhen3', 'zhen4', 'zheng1', 'zheng2', 'zheng3', 'zheng4', 'zhi1', 'zhi2', 'zhi3', 'zhi4', 'zhong1', 'zhong2', 'zhong3', 'zhong4', 'zhou1', 'zhou2', 'zhou3', 'zhou4', 'zhu1', 'zhu2', 'zhu3', 'zhu4', 'zhua1', 'zhua2', 'zhua3', 'zhuai1', 'zhuai3', 'zhuai4', 'zhuan1', 'zhuan2', 'zhuan3', 'zhuan4', 'zhuang1', 'zhuang4', 'zhui1', 'zhui4', 'zhun1', 'zhun2', 'zhun3', 'zhuo1', 'zhuo2', 'zi', 'zi1', 'zi2', 'zi3', 'zi4', 'zong1', 'zong2', 'zong3', 'zong4', 'zou1', 'zou2', 'zou3', 'zou4', 'zu1', 'zu2', 'zu3', 'zuan1', 'zuan3', 'zuan4', 'zui2', 'zui3', 'zui4', 'zun1', 'zuo1', 'zuo2', 'zuo3', 'zuo4'] + ens = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z', "'", ' '] + ens_U = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'] + + phoneme_to_index = {} + num_phonemes = 0 + for index, punc in enumerate(puncs): + phoneme_to_index[punc] = index + num_phonemes + num_phonemes += len(puncs) + for index, pinyin in enumerate(pinyins): + phoneme_to_index[pinyin] = index + num_phonemes + num_phonemes += len(pinyins) + for index, en in enumerate(ens): + phoneme_to_index[en] = index + num_phonemes + for index, en in enumerate(ens_U): + phoneme_to_index[en] = index + num_phonemes + num_phonemes += len(ens) + #print(num_phonemes, phoneme_to_index) # 1342 + + def encode( + text: list[str], + padding_value = -1 + ) -> Int['b nt']: + phonemes = [] + for t in text: + one_phoneme = [] + brk = False + for word in jieba.cut(t): + if all_ch(word): + seg = lazy_pinyin(word, style=Style.TONE3, tone_sandhi=True) + one_phoneme.extend(seg) + elif all_en(word): + for seg in word: + one_phoneme.append(seg) + elif word in ["，", "。", "？", "、", "'", " "]: + one_phoneme.append(word) + else: + for ch in word: + if all_ch(ch): + seg = lazy_pinyin(ch, style=Style.TONE3, tone_sandhi=True) + one_phoneme.extend(seg) + elif all_en(ch): + for seg in ch: + one_phoneme.append(seg) + else: + brk = True + break + if brk: + break + if not brk: + phonemes.append(one_phoneme) + else: + print("Error Tokenized", t, list(jieba.cut(t))) + list_tensors = [tensor([phoneme_to_index[p] for p in one_phoneme]) for one_phoneme in phonemes] + padded_tensor = pad_sequence(list_tensors, padding_value = -1) + return padded_tensor + + return encode, num_phonemes + +# tensor helpers + +def log(t, eps = 1e-5): + return t.clamp(min = eps).log() + +def lens_to_mask( + t: Int['b'], + length: int | None = None +) -> Bool['b n']: + + if not exists(length): + length = t.amax() + + seq = torch.arange(length, device = t.device) + return einx.less('n, b -> b n', seq, t) + +def mask_from_start_end_indices( + seq_len: Int['b'], + start: Int['b'], + end: Int['b'] +): + max_seq_len = seq_len.max().item() + seq = torch.arange(max_seq_len, device = start.device).long() + return einx.greater_equal('n, b -> b n', seq, start) & einx.less('n, b -> b n', seq, end) + +def mask_from_frac_lengths( + seq_len: Int['b'], + frac_lengths: Float['b'], + max_length: int | None = None, + val = False +): + lengths = (frac_lengths * seq_len).long() + max_start = seq_len - lengths + + if not val: + rand = torch.rand_like(frac_lengths) + else: + rand = torch.tensor([0.5]*frac_lengths.shape[0], device=frac_lengths.device).float() + start = (max_start * rand).long().clamp(min = 0) + end = start + lengths + + out = mask_from_start_end_indices(seq_len, start, end) + + if exists(max_length): + out = pad_to_length(out, max_length) + + return out + +def maybe_masked_mean( + t: Float['b n d'], + mask: Bool['b n'] | None = None +) -> Float['b d']: + + if not exists(mask): + return t.mean(dim = 1) + + t = einx.where('b n, b n d, -> b n d', mask, t, 0.) + num = reduce(t, 'b n d -> b d', 'sum') + den = reduce(mask.float(), 'b n -> b', 'sum') + + return einx.divide('b d, b -> b d', num, den.clamp(min = 1.)) + +def pad_to_length( + t: Tensor, + length: int, + value = None +): + seq_len = t.shape[-1] + if length > seq_len: + t = F.pad(t, (0, length - seq_len), value = value) + + return t[..., :length] + +def interpolate_1d( + x: Tensor, + length: int, + mode = 'bilinear' +): + x = rearrange(x, 'n d -> 1 d n 1') + x = F.interpolate(x, (length, 1), mode = mode) + return rearrange(x, '1 d n 1 -> n d') + +# to mel spec + +class MelSpec(Module): + def __init__( + self, + filter_length = 1024, + hop_length = 256, + win_length = 1024, + n_mel_channels = 100, + sampling_rate = 24_000, + normalize = False, + power = 1, + norm = None, + center = True, + ): + super().__init__() + self.n_mel_channels = n_mel_channels + self.sampling_rate = sampling_rate + + self.mel_stft = torchaudio.transforms.MelSpectrogram( + sample_rate = sampling_rate, + n_fft = filter_length, + win_length = win_length, + hop_length = hop_length, + n_mels = n_mel_channels, + power = power, + center = center, + normalized = normalize, + norm = norm, + ) + + self.register_buffer('dummy', tensor(0), persistent = False) + + def forward(self, inp): + if len(inp.shape) == 3: + inp = rearrange(inp, 'b 1 nw -> b nw') + + assert len(inp.shape) == 2 + + if self.dummy.device != inp.device: + self.to(inp.device) + + mel = self.mel_stft(inp) + mel = log(mel) + return mel + +class EncodecWrapper(Module): + def __init__(self, path): + super().__init__() + self.model = EncodecModel.from_pretrained(path) + self.processor = AutoProcessor.from_pretrained(path) + for param in self.model.parameters(): + param.requires_grad = False + self.model.eval() + + def forward(self, waveform): + with torch.no_grad(): + inputs = self.processor(raw_audio=waveform[0], sampling_rate=self.processor.sampling_rate, return_tensors="pt") + emb = self.model.encoder(inputs.input_values) + return emb + + def decode(self, emb): + with torch.no_grad(): + output = self.model.decoder(emb) + return output[0] + +from audioldm.audio.stft import TacotronSTFT +from audioldm.variational_autoencoder import AutoencoderKL +from audioldm.utils import default_audioldm_config, get_metadata + +def build_pretrained_models(name): + checkpoint = torch.load(get_metadata()[name]["path"], map_location="cpu") + scale_factor = checkpoint["state_dict"]["scale_factor"].item() + + vae_state_dict = {k[18:]: v for k, v in checkpoint["state_dict"].items() if "first_stage_model." in k} + + config = default_audioldm_config(name) + vae_config = config["model"]["params"]["first_stage_config"]["params"] + vae_config["scale_factor"] = scale_factor + + vae = AutoencoderKL(**vae_config) + vae.load_state_dict(vae_state_dict) + + fn_STFT = TacotronSTFT( + config["preprocessing"]["stft"]["filter_length"], + config["preprocessing"]["stft"]["hop_length"], + config["preprocessing"]["stft"]["win_length"], + config["preprocessing"]["mel"]["n_mel_channels"], + config["preprocessing"]["audio"]["sampling_rate"], + config["preprocessing"]["mel"]["mel_fmin"], + config["preprocessing"]["mel"]["mel_fmax"], + ) + + vae.eval() + fn_STFT.eval() + return vae, fn_STFT + +class VaeWrapper(Module): + def __init__(self): + super().__init__() + vae, stft = build_pretrained_models("audioldm-s-full") + vae.eval() + stft.eval() + stft = stft.cpu() + self.vae = vae + for param in self.vae.parameters(): + param.requires_grad = False + + def forward(self, waveform): + return None + + def decode(self, emb): + with torch.no_grad(): + b, d, l = emb.shape + latents = emb.transpose(1,2).reshape(b, l, 8, 16).transpose(1,2) + mel = self.vae.decode_first_stage(latents) + wave = self.vae.decode_to_waveform(mel) + return wave + +# convolutional positional generating module +# taken from https://github.com/lucidrains/voicebox-pytorch/blob/main/voicebox_pytorch/voicebox_pytorch.py#L203 + +class DepthwiseConv(Module): + def __init__( + self, + dim, + *, + kernel_size, + groups = None + ): + super().__init__() + assert not divisible_by(kernel_size, 2) + groups = default(groups, dim) # full depthwise conv by default + + self.dw_conv1d = nn.Sequential( + nn.Conv1d(dim, dim, kernel_size, groups = groups, padding = kernel_size // 2), + nn.SiLU() + ) + + def forward( + self, + x, + mask = None + ): + + if exists(mask): + x = einx.where('b n, b n d, -> b n d', mask, x, 0.) + + x = rearrange(x, 'b n c -> b c n') + x = self.dw_conv1d(x) + out = rearrange(x, 'b c n -> b n c') + + if exists(mask): + out = einx.where('b n, b n d, -> b n d', mask, out, 0.) + + return out + +# adaln zero from DiT paper + +class AdaLNZero(Module): + def __init__( + self, + dim, + dim_condition = None, + init_bias_value = -2. + ): + super().__init__() + dim_condition = default(dim_condition, dim) + self.to_gamma = nn.Linear(dim_condition, dim) + + nn.init.zeros_(self.to_gamma.weight) + nn.init.constant_(self.to_gamma.bias, init_bias_value) + + def forward(self, x, *, condition): + if condition.ndim == 2: + condition = rearrange(condition, 'b d -> b 1 d') + + gamma = self.to_gamma(condition).sigmoid() + return x * gamma + +# random projection fourier embedding + +class RandomFourierEmbed(Module): + def __init__(self, dim): + super().__init__() + assert divisible_by(dim, 2) + self.register_buffer('weights', torch.randn(dim // 2)) + + def forward(self, x): + freqs = einx.multiply('i, j -> i j', x, self.weights) * 2 * torch.pi + fourier_embed, _ = pack((x, freqs.sin(), freqs.cos()), 'b *') + return fourier_embed + +# character embedding + +class CharacterEmbed(Module): + def __init__( + self, + dim, + num_embeds = 256, + ): + super().__init__() + self.dim = dim + self.embed = nn.Embedding(num_embeds + 1, dim) # will just use 0 as the 'filler token' + + def forward( + self, + text: Int['b nt'], + max_seq_len: int, + **kwargs + ) -> Float['b n d']: + + text = text + 1 # shift all other token ids up by 1 and use 0 as filler token + + text = text[:, :max_seq_len] # just curtail if character tokens are more than the mel spec tokens, one of the edge cases the paper did not address + text = pad_to_length(text, max_seq_len, value = 0) + + return self.embed(text) + +class InterpolatedCharacterEmbed(Module): + def __init__( + self, + dim, + num_embeds = 256, + ): + super().__init__() + self.dim = dim + self.embed = nn.Embedding(num_embeds, dim) + + self.abs_pos_mlp = Sequential( + Rearrange('... -> ... 1'), + Linear(1, dim), + nn.SiLU(), + Linear(dim, dim) + ) + + def forward( + self, + text: Int['b nt'], + max_seq_len: int, + mask: Bool['b n'] | None = None + ) -> Float['b n d']: + + device = text.device + + mask = default(mask, (None,)) + + interp_embeds = [] + interp_abs_positions = [] + + for one_text, one_mask in zip_longest(text, mask): + + valid_text = one_text >= 0 + one_text = one_text[valid_text] + one_text_embed = self.embed(one_text) + + # save the absolute positions + + text_seq_len = one_text.shape[0] + + # determine audio sequence length from mask + + audio_seq_len = max_seq_len + if exists(one_mask): + audio_seq_len = one_mask.sum().long().item() + + # interpolate text embedding to audio embedding length + + interp_text_embed = interpolate_1d(one_text_embed, audio_seq_len) + interp_abs_pos = torch.linspace(0, text_seq_len, audio_seq_len, device = device) + + interp_embeds.append(interp_text_embed) + interp_abs_positions.append(interp_abs_pos) + + interp_embeds = pad_sequence(interp_embeds) + interp_abs_positions = pad_sequence(interp_abs_positions) + + interp_embeds = F.pad(interp_embeds, (0, 0, 0, max_seq_len - interp_embeds.shape[-2])) + interp_abs_positions = pad_to_length(interp_abs_positions, max_seq_len) + + # pass interp absolute positions through mlp for implicit positions + + interp_embeds = interp_embeds + self.abs_pos_mlp(interp_abs_positions) + + if exists(mask): + interp_embeds = einx.where('b n, b n d, -> b n d', mask, interp_embeds, 0.) + + return interp_embeds + +# text audio cross conditioning in multistream setup + +class TextAudioCrossCondition(Module): + def __init__( + self, + dim, + dim_text, + cond_audio_to_text = True, + ): + super().__init__() + self.text_to_audio = nn.Linear(dim_text + dim, dim, bias = False) + nn.init.zeros_(self.text_to_audio.weight) + + self.cond_audio_to_text = cond_audio_to_text + + if cond_audio_to_text: + self.audio_to_text = nn.Linear(dim + dim_text, dim_text, bias = False) + nn.init.zeros_(self.audio_to_text.weight) + + def forward( + self, + audio: Float['b n d'], + text: Float['b n dt'] + ): + audio_text, _ = pack((audio, text), 'b n *') + + text_cond = self.text_to_audio(audio_text) + audio_cond = self.audio_to_text(audio_text) if self.cond_audio_to_text else 0. + + return audio + text_cond, text + audio_cond + +# attention and transformer backbone +# for use in both e2tts as well as duration module + +class Transformer(Module): + @beartype + def __init__( + self, + *, + dim, + dim_text = None, # will default to half of audio dimension + depth = 8, + heads = 8, + dim_head = 64, + ff_mult = 4, + text_depth = None, + text_heads = None, + text_dim_head = None, + text_ff_mult = None, + cond_on_time = True, + abs_pos_emb = True, + max_seq_len = 8192, + kernel_size = 31, + dropout = 0.1, + num_registers = 32, + attn_kwargs: dict = dict( + gate_value_heads = True, + softclamp_logits = True, + ), + ff_kwargs: dict = dict(), + if_text_modules = True, + if_cross_attn = True, + if_audio_conv = True, + if_text_conv = False + ): + super().__init__() + assert divisible_by(depth, 2), 'depth needs to be even' + + # absolute positional embedding + + self.max_seq_len = max_seq_len + self.abs_pos_emb = nn.Embedding(max_seq_len, dim) if abs_pos_emb else None + + self.dim = dim + + dim_text = default(dim_text, dim // 2) + self.dim_text = dim_text + + text_heads = default(text_heads, heads) + text_dim_head = default(text_dim_head, dim_head) + text_ff_mult = default(text_ff_mult, ff_mult) + text_depth = default(text_depth, depth) + + assert 1 <= text_depth <= depth, 'must have at least 1 layer of text conditioning, but less than total number of speech layers' + + self.depth = depth + self.layers = ModuleList([]) + + # registers + + self.num_registers = num_registers + self.registers = nn.Parameter(torch.zeros(num_registers, dim)) + nn.init.normal_(self.registers, std = 0.02) + + if if_text_modules: + self.text_registers = nn.Parameter(torch.zeros(num_registers, dim_text)) + nn.init.normal_(self.text_registers, std = 0.02) + + # rotary embedding + + self.rotary_emb = RotaryEmbedding(dim_head) + self.text_rotary_emb = RotaryEmbedding(dim_head) + + # time conditioning + # will use adaptive rmsnorm + + self.cond_on_time = cond_on_time + rmsnorm_klass = RMSNorm if not cond_on_time else AdaptiveRMSNorm + postbranch_klass = Identity if not cond_on_time else partial(AdaLNZero, dim = dim) + + self.time_cond_mlp = Identity() + + if cond_on_time: + self.time_cond_mlp = Sequential( + RandomFourierEmbed(dim), + Linear(dim + 1, dim), + nn.SiLU() + ) + + for ind in range(depth): + is_later_half = ind >= (depth // 2) + has_text = ind < text_depth + + # speech related + if if_audio_conv: + speech_conv = DepthwiseConv(dim, kernel_size = kernel_size) + + attn_norm = rmsnorm_klass(dim) + attn = Attention(dim = dim, heads = heads, dim_head = dim_head, dropout = dropout, **attn_kwargs) + attn_adaln_zero = postbranch_klass() + + if if_cross_attn: + attn_norm2 = rmsnorm_klass(dim) + attn2 = Attention(dim = dim, heads = heads, dim_head = dim_head, dropout = dropout, **attn_kwargs) + attn_adaln_zero2 = postbranch_klass() + + ff_norm = rmsnorm_klass(dim) + ff = FeedForward(dim = dim, glu = True, mult = ff_mult, dropout = dropout, **ff_kwargs) + ff_adaln_zero = postbranch_klass() + + skip_proj = Linear(dim * 2, dim, bias = False) if is_later_half else None + + if if_cross_attn: + if if_audio_conv: + speech_modules = ModuleList([ + skip_proj, + speech_conv, + attn_norm, + attn, + attn_adaln_zero, + attn_norm2, + attn2, + attn_adaln_zero2, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + speech_modules = ModuleList([ + skip_proj, + attn_norm, + attn, + attn_adaln_zero, + attn_norm2, + attn2, + attn_adaln_zero2, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + if if_audio_conv: + speech_modules = ModuleList([ + skip_proj, + speech_conv, + attn_norm, + attn, + attn_adaln_zero, + ff_norm, + ff, + ff_adaln_zero, + ]) + else: + speech_modules = ModuleList([ + skip_proj, + attn_norm, + attn, + attn_adaln_zero, + ff_norm, + ff, + ff_adaln_zero, + ]) + + text_modules = None + + if has_text and if_text_modules: + # text related + if if_text_conv: + text_conv = DepthwiseConv(dim_text, kernel_size = kernel_size) + + text_attn_norm = RMSNorm(dim_text) + text_attn = Attention(dim = dim_text, heads = text_heads, dim_head = text_dim_head, dropout = dropout, **attn_kwargs) + + text_ff_norm = RMSNorm(dim_text) + text_ff = FeedForward(dim = dim_text, glu = True, mult = text_ff_mult, dropout = dropout, **ff_kwargs) + + # cross condition + + is_last = ind == (text_depth - 1) + + cross_condition = TextAudioCrossCondition(dim = dim, dim_text = dim_text, cond_audio_to_text = not is_last) + + if if_text_conv: + text_modules = ModuleList([ + text_conv, + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ]) + else: + text_modules = ModuleList([ + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ]) + + self.layers.append(ModuleList([ + speech_modules, + text_modules + ])) + + self.final_norm = RMSNorm(dim) + + self.if_cross_attn = if_cross_attn + self.if_audio_conv = if_audio_conv + self.if_text_conv = if_text_conv + + ####self.a_align = Linear(dim, 512) + ####self.v_align = Linear(dim_text, 512) + ####self.contrastive_loss = SupConLoss() + #self.contrastive_loss = FactorCLSSL(None, [1024, 1280], None) + self.contrastive_loss = FactorCLSUP(None, [1024, 1280], 6) + + def forward( + self, + x: Float['b n d'], + times: Float['b'] | Float[''] | None = None, + mask: Bool['b n'] | None = None, + text_embed: Float['b n dt'] | None = None, + context: Float['b nc dc'] | None = None, + context_mask: Float['b nc'] | None = None + ): + batch, seq_len, device = *x.shape[:2], x.device + + assert not (exists(times) ^ self.cond_on_time), '`times` must be passed in if `cond_on_time` is set to `True` and vice versa' + + # handle absolute positions if needed + + if exists(self.abs_pos_emb): + assert seq_len <= self.max_seq_len, f'{seq_len} exceeds the set `max_seq_len` ({self.max_seq_len}) on Transformer' + seq = torch.arange(seq_len, device = device) + x = x + self.abs_pos_emb(seq) + + # handle adaptive rmsnorm kwargs + + norm_kwargs = dict() + + if exists(times): + if times.ndim == 0: + times = repeat(times, ' -> b', b = batch) + + times = self.time_cond_mlp(times) + norm_kwargs.update(condition = times) + + # register tokens + + registers = repeat(self.registers, 'r d -> b r d', b = batch) + x, registers_packed_shape = pack((registers, x), 'b * d') + + if exists(mask): + mask = F.pad(mask, (self.num_registers, 0), value = True) + + # rotary embedding + + rotary_pos_emb = self.rotary_emb.forward_from_seq_len(x.shape[-2]) + + # text related + + if exists(text_embed): + text_rotary_pos_emb = self.text_rotary_emb.forward_from_seq_len(x.shape[-2]) + + text_registers = repeat(self.text_registers, 'r d -> b r d', b = batch) + text_embed, _ = pack((text_registers, text_embed), 'b * d') + + # skip connection related stuff + + skips = [] + + # go through the layers + + loss_contra = 0 + for ind, (speech_modules, text_modules) in enumerate(self.layers): + layer = ind + 1 + + if self.if_cross_attn: + if self.if_audio_conv: + ( + maybe_skip_proj, + speech_conv, + attn_norm, + attn, + maybe_attn_adaln_zero, + attn_norm2, + attn2, + maybe_attn_adaln_zero2, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + ( + maybe_skip_proj, + attn_norm, + attn, + maybe_attn_adaln_zero, + attn_norm2, + attn2, + maybe_attn_adaln_zero2, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + if self.if_audio_conv: + ( + maybe_skip_proj, + speech_conv, + attn_norm, + attn, + maybe_attn_adaln_zero, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + else: + ( + maybe_skip_proj, + attn_norm, + attn, + maybe_attn_adaln_zero, + ff_norm, + ff, + maybe_ff_adaln_zero + ) = speech_modules + + # smaller text transformer + + if exists(text_embed) and exists(text_modules): + + if self.if_text_conv: + ( + text_conv, + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ) = text_modules + else: + ( + text_attn_norm, + text_attn, + text_ff_norm, + text_ff, + cross_condition + ) = text_modules + + if self.if_text_conv: + text_embed = text_conv(text_embed, mask = mask) + text_embed + + text_embed = text_attn(text_attn_norm(text_embed), rotary_pos_emb = text_rotary_pos_emb, mask = mask) + text_embed + + text_embed = text_ff(text_ff_norm(text_embed)) + text_embed + + if x.shape[0] >= 8: + if layer in [1]: + #print("contrastive learning", x.shape, text_embed.shape) # [16, 782, 1024] [16, 782, 1280] + ####features1 = self.a_align(x) + ####features2 = self.v_align(text_embed) + features1 = x + features2 = text_embed + + #b1, b2 = random_sample(range(2,8), 2) + #t1, t2 = random_sample(range(x.shape[1]), 2) + #loss_contra = torch.cosine_similarity(x[b1,t1:t1+1,:], y[b1,t2:t2+1,:]) + torch.cosine_similarity(x[b1,t1:t1+1,:], y[b2,t1:t1+1,:]) - torch.cosine_similarity(x[b1,t1:t1+1,:], y[b1,t1:t1+1,:]) - torch.cosine_similarity(x[b2,t2:t2+1,:], y[b2,t2:t2+1,:]) + + features1 = features1[2:8,32:,:] + features2 = features2[2:8,32:,:] + if self.training: + ts = random_sample(range(features1.shape[1]), 1) + #ts = random_sample(range(features1.shape[1]), 6) + #ts = random_sample(range(features1.shape[1]), 14) + else: + ts = [350] + #ts = [100, 200, 300, 400, 500, 600] + #ts = [50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700] + features1 = features1[:,ts,:] + features2 = features2[:,ts,:] + + ####loss_contra += self.contrastive_loss(features1, features2, labels=None, mask=None) + nf = 1 + features1 = features1.reshape(6*nf, -1) + features2 = features2.reshape(6*nf, -1) + label = torch.tensor([0.0]*nf+[1.0]*nf+[2.0]*nf+[3.0]*nf+[4.0]*nf+[5.0]*nf, device=device).reshape(6*nf,1) + loss_contra += self.contrastive_loss(features1, features2, label) + + else: + loss_contra = torch.tensor(0.0, device=device) + + x, text_embed = cross_condition(x, text_embed) + + # skip connection logic + + is_first_half = layer <= (self.depth // 2) + is_later_half = not is_first_half + + if is_first_half: + skips.append(x) + + if is_later_half: + skip = skips.pop() + x = torch.cat((x, skip), dim = -1) + x = maybe_skip_proj(x) + + # position generating convolution + + if self.if_audio_conv: + x = speech_conv(x, mask = mask) + x + + # attention and feedforward blocks + + attn_out = attn(attn_norm(x, **norm_kwargs), rotary_pos_emb = rotary_pos_emb, mask = mask) + + x = x + maybe_attn_adaln_zero(attn_out, **norm_kwargs) + + if self.if_cross_attn: + attn_out = attn2(attn_norm2(x, **norm_kwargs), rotary_pos_emb = rotary_pos_emb, mask = mask, context = context, context_mask = context_mask) + + x = x + maybe_attn_adaln_zero2(attn_out, **norm_kwargs) + + ff_out = ff(ff_norm(x, **norm_kwargs)) + + x = x + maybe_ff_adaln_zero(ff_out, **norm_kwargs) + + assert len(skips) == 0 + + _, x = unpack(x, registers_packed_shape, 'b * d') + + return self.final_norm(x), loss_contra + +from .multibench_model import FactorCLSUP, FactorCLSSL + +class SupConLoss(nn.Module): + """Supervised Contrastive Learning: https://arxiv.org/pdf/2004.11362.pdf. + It also supports the unsupervised contrastive loss in SimCLR""" + def __init__(self, temperature=0.07, contrast_mode='all', + base_temperature=0.07): + super(SupConLoss, self).__init__() + self.temperature = temperature + self.contrast_mode = contrast_mode + self.base_temperature = base_temperature + + def forward(self, features, features2, labels=None, mask=None): + """Compute loss for model. If both `labels` and `mask` are None, + it degenerates to SimCLR unsupervised loss: + https://arxiv.org/pdf/2002.05709.pdf + + Args: + features: hidden vector of shape [bsz, n_views, ...]. + labels: ground truth of shape [bsz]. + mask: contrastive mask of shape [bsz, bsz], mask_{i,j}=1 if sample j + has the same class as sample i. Can be asymmetric. + Returns: + A loss scalar. + """ + features = F.normalize(features, dim=2) + features2 = F.normalize(features2, dim=2) + device = (torch.device('cuda') + if features.is_cuda + else torch.device('cpu')) + + if len(features.shape) < 3: + raise ValueError('`features` needs to be [bsz, n_views, ...],' + 'at least 3 dimensions are required') + if len(features.shape) > 3: + features = features.view(features.shape[0], features.shape[1], -1) + features2 = features2.view(features2.shape[0], features2.shape[1], -1) + + batch_size = features.shape[0] + if labels is not None and mask is not None: + raise ValueError('Cannot define both `labels` and `mask`') + elif labels is None and mask is None: + mask = torch.eye(batch_size, dtype=torch.float32).to(device) + elif labels is not None: + labels = labels.contiguous().view(-1, 1) + if labels.shape[0] != batch_size: + raise ValueError('Num of labels does not match num of features') + mask = torch.eq(labels, labels.T).float().to(device) + else: + mask = mask.float().to(device) + + contrast_count = features.shape[1] + contrast_feature = torch.cat(torch.unbind(features, dim=1), dim=0) + contrast_feature2 = torch.cat(torch.unbind(features2, dim=1), dim=0) + if self.contrast_mode == 'one': + anchor_feature = features[:, 0] + anchor_feature2 = features2[:, 0] + anchor_count = 1 + elif self.contrast_mode == 'all': + anchor_feature = contrast_feature + anchor_feature2 = contrast_feature2 + anchor_count = contrast_count + else: + raise ValueError('Unknown mode: {}'.format(self.contrast_mode)) + + # compute logits + anchor_dot_contrast = torch.div( + #torch.matmul(anchor_feature, contrast_feature.T), + torch.matmul(anchor_feature, contrast_feature2.T), + self.temperature) + # for numerical stability + logits_max, _ = torch.max(anchor_dot_contrast, dim=1, keepdim=True) + logits = anchor_dot_contrast - logits_max.detach() + + # tile mask + mask = mask.repeat(anchor_count, contrast_count) + # mask-out self-contrast cases + #logits_mask = torch.scatter( + # torch.ones_like(mask), + # 1, + # torch.arange(batch_size * anchor_count).view(-1, 1).to(device), + # 0 + #) + logits_mask = torch.ones_like(mask) + mask = mask * logits_mask + #print("logits", logits.shape, logits.min(), logits.max()) + + # compute log_prob + exp_logits = torch.exp(logits) * logits_mask + #print("exp_logits", exp_logits.shape, exp_logits.min(), exp_logits.max()) + log_prob = logits - torch.log(exp_logits.sum(1, keepdim=True)) + #print("log_prob", log_prob.shape, log_prob.min(), log_prob.max()) + + # compute mean of log-likelihood over positive + # modified to handle edge cases when there is no positive pair + # for an anchor point. + # Edge case e.g.:- + # features of shape: [4,1,...] + # labels: [0,1,1,2] + # loss before mean: [nan, ..., ..., nan] + mask_pos_pairs = mask.sum(1) + mask_pos_pairs = torch.where(mask_pos_pairs < 1e-6, 1, mask_pos_pairs) + mean_log_prob_pos = (mask * log_prob).sum(1) / mask_pos_pairs + + # loss + loss = - (self.temperature / self.base_temperature) * mean_log_prob_pos + loss = loss.view(anchor_count, batch_size).mean() + + return loss + +# main classes + +class DurationPredictor(Module): + @beartype + def __init__( + self, + transformer: dict | Transformer, + num_channels = None, + mel_spec_kwargs: dict = dict(), + char_embed_kwargs: dict = dict(), + text_num_embeds = None, + tokenizer: ( + Literal['char_utf8', 'phoneme_en'] | + Callable[[list[str]], Int['b nt']] + ) = 'char_utf8' + ): + super().__init__() + + if isinstance(transformer, dict): + transformer = Transformer( + **transformer, + cond_on_time = False + ) + + # mel spec + + self.mel_spec = MelSpec(**mel_spec_kwargs) + self.num_channels = default(num_channels, self.mel_spec.n_mel_channels) + + self.transformer = transformer + + dim = transformer.dim + dim_text = transformer.dim_text + + self.dim = dim + + self.proj_in = Linear(self.num_channels, self.dim) + + # tokenizer and text embed + + if callable(tokenizer): + assert exists(text_num_embeds), '`text_num_embeds` must be given if supplying your own tokenizer encode function' + self.tokenizer = tokenizer + elif tokenizer == 'char_utf8': + text_num_embeds = 256 + self.tokenizer = list_str_to_tensor + elif tokenizer == 'phoneme_en': + self.tokenizer, text_num_embeds = get_g2p_en_encode() + elif tokenizer == 'phoneme_zh': + self.tokenizer, text_num_embeds = get_g2p_zh_encode() + else: + raise ValueError(f'unknown tokenizer string {tokenizer}') + + self.embed_text = CharacterEmbed(dim_text, num_embeds = text_num_embeds, **char_embed_kwargs) + + # to prediction + + self.to_pred = Sequential( + Linear(dim, 1, bias = False), + nn.Softplus(), + Rearrange('... 1 -> ...') + ) + + def forward( + self, + x: Float['b n d'] | Float['b nw'], + *, + text: Int['b nt'] | list[str] | None = None, + lens: Int['b'] | None = None, + return_loss = True + ): + # raw wave + + if x.ndim == 2: + x = self.mel_spec(x) + x = rearrange(x, 'b d n -> b n d') + assert x.shape[-1] == self.dim + + x = self.proj_in(x) + + batch, seq_len, device = *x.shape[:2], x.device + + # text + + text_embed = None + + if exists(text): + if isinstance(text, list): + text = list_str_to_tensor(text).to(device) + assert text.shape[0] == batch + + text_embed = self.embed_text(text, seq_len) + + # handle lengths (duration) + + if not exists(lens): + lens = torch.full((batch,), seq_len, device = device) + + mask = lens_to_mask(lens, length = seq_len) + + # if returning a loss, mask out randomly from an index and have it predict the duration + + if return_loss: + rand_frac_index = x.new_zeros(batch).uniform_(0, 1) + rand_index = (rand_frac_index * lens).long() + + seq = torch.arange(seq_len, device = device) + mask &= einx.less('n, b -> b n', seq, rand_index) + + # attending + + x = self.transformer( + x, + mask = mask, + text_embed = text_embed, + ) + + x = maybe_masked_mean(x, mask) + + pred = self.to_pred(x) + + # return the prediction if not returning loss + + if not return_loss: + return pred + + # loss + + return F.mse_loss(pred, lens.float()) + +class E2TTS(Module): + + @beartype + def __init__( + self, + transformer: dict | Transformer = None, + duration_predictor: dict | DurationPredictor | None = None, + odeint_kwargs: dict = dict( + #atol = 1e-5, + #rtol = 1e-5, + #method = 'midpoint' + method = "euler" + ), + audiocond_drop_prob = 0.30, + cond_drop_prob = 0.20, + prompt_drop_prob = 0.10, + num_channels = None, + mel_spec_module: Module | None = None, + char_embed_kwargs: dict = dict(), + mel_spec_kwargs: dict = dict(), + frac_lengths_mask: tuple[float, float] = (0.7, 1.), + audiocond_snr: tuple[float, float] | None = None, + concat_cond = False, + interpolated_text = False, + text_num_embeds: int | None = None, + tokenizer: ( + Literal['char_utf8', 'phoneme_en', 'phoneme_zh'] | + Callable[[list[str]], Int['b nt']] + ) = 'char_utf8', + use_vocos = True, + pretrained_vocos_path = 'charactr/vocos-mel-24khz', + sampling_rate: int | None = None, + frame_size: int = 320, + velocity_consistency_weight = -1e-5, + + if_cond_proj_in = True, + cond_proj_in_bias = True, + if_embed_text = True, + if_text_encoder2 = True, + if_clip_encoder = False, + video_encoder = "clip_vit" + ): + super().__init__() + + if isinstance(transformer, dict): + transformer = Transformer( + **transformer, + cond_on_time = True + ) + + if isinstance(duration_predictor, dict): + duration_predictor = DurationPredictor(**duration_predictor) + + self.transformer = transformer + + dim = transformer.dim + dim_text = transformer.dim_text + + self.dim = dim + self.dim_text = dim_text + + self.frac_lengths_mask = frac_lengths_mask + self.audiocond_snr = audiocond_snr + + self.duration_predictor = duration_predictor + + # sampling + + self.odeint_kwargs = odeint_kwargs + + # mel spec + + self.mel_spec = default(mel_spec_module, None) + num_channels = default(num_channels, None) + + self.num_channels = num_channels + self.sampling_rate = default(sampling_rate, None) + self.frame_size = frame_size + + # whether to concat condition and project rather than project both and sum + + self.concat_cond = concat_cond + + if concat_cond: + self.proj_in = nn.Linear(num_channels * 2, dim) + else: + self.proj_in = nn.Linear(num_channels, dim) + self.cond_proj_in = nn.Linear(num_channels, dim, bias=cond_proj_in_bias) if if_cond_proj_in else None + + # to prediction + + self.to_pred = Linear(dim, num_channels) + + # tokenizer and text embed + + if callable(tokenizer): + assert exists(text_num_embeds), '`text_num_embeds` must be given if supplying your own tokenizer encode function' + self.tokenizer = tokenizer + elif tokenizer == 'char_utf8': + text_num_embeds = 256 + self.tokenizer = list_str_to_tensor + elif tokenizer == 'phoneme_en': + self.tokenizer, text_num_embeds = get_g2p_en_encode() + elif tokenizer == 'phoneme_zh': + self.tokenizer, text_num_embeds = get_g2p_zh_encode() + else: + raise ValueError(f'unknown tokenizer string {tokenizer}') + + self.audiocond_drop_prob = audiocond_drop_prob + self.cond_drop_prob = cond_drop_prob + self.prompt_drop_prob = prompt_drop_prob + + # text embedding + + text_embed_klass = CharacterEmbed if not interpolated_text else InterpolatedCharacterEmbed + + self.embed_text = text_embed_klass(dim_text, num_embeds = text_num_embeds, **char_embed_kwargs) if if_embed_text else None + + # weight for velocity consistency + + self.register_buffer('zero', torch.tensor(0.), persistent = False) + self.velocity_consistency_weight = velocity_consistency_weight + + # default vocos for mel -> audio + + if pretrained_vocos_path == 'charactr/vocos-mel-24khz': + self.vocos = Vocos.from_pretrained(pretrained_vocos_path) if use_vocos else None + elif pretrained_vocos_path == 'facebook/encodec_24khz': + self.vocos = EncodecWrapper("facebook/encodec_24khz") if use_vocos else None + elif pretrained_vocos_path == 'vae': + self.vocos = VaeWrapper() if use_vocos else None + + if if_text_encoder2: + self.tokenizer2 = AutoTokenizer.from_pretrained("/ailab-train/speech/zhanghaomin/models/flan-t5-large") + self.text_encoder2 = T5EncoderModel.from_pretrained("/ailab-train/speech/zhanghaomin/models/flan-t5-large") + for param in self.text_encoder2.parameters(): + param.requires_grad = False + self.text_encoder2.eval() + + self.proj_text = None + if if_clip_encoder: + if video_encoder == "clip_vit": + self.image_processor = CLIPImageProcessor() + #self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/IP-Adapter/", subfolder="models/image_encoder") + self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/IP-Adapter/", subfolder="sdxl_models/image_encoder") + elif video_encoder == "clip_vit2": + self.image_processor = AutoProcessor.from_pretrained("/ailab-train/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + self.image_encoder = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + elif video_encoder == "clip_convnext": + self.image_encoder, _, self.image_processor = open_clip.create_model_and_transforms("hf-hub:laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup") + elif video_encoder == "dinov2": + self.image_processor = AutoImageProcessor.from_pretrained("/ailab-train/speech/zhanghaomin/models/dinov2-giant/") + self.image_encoder = AutoModel.from_pretrained("/ailab-train/speech/zhanghaomin/models/dinov2-giant/") + elif video_encoder == "mixed": + #pass + self.image_processor1 = CLIPImageProcessor() + self.image_encoder1 = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/IP-Adapter/", subfolder="sdxl_models/image_encoder") + self.image_processor2 = AutoProcessor.from_pretrained("/ailab-train/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + self.image_encoder2 = CLIPVisionModelWithProjection.from_pretrained("/ailab-train/speech/zhanghaomin/models/clip-vit-large-patch14-336/") + self.image_encoder3, _, self.image_processor3 = open_clip.create_model_and_transforms("hf-hub:laion/CLIP-convnext_xxlarge-laion2B-s34B-b82K-augreg-soup") + self.image_processor4 = AutoImageProcessor.from_pretrained("/ailab-train/speech/zhanghaomin/models/dinov2-giant/") + self.image_encoder4 = AutoModel.from_pretrained("/ailab-train/speech/zhanghaomin/models/dinov2-giant/") + else: + self.image_processor = None + self.image_encoder = None + if video_encoder != "mixed": + for param in self.image_encoder.parameters(): + param.requires_grad = False + self.image_encoder.eval() + else: + for param in self.image_encoder1.parameters(): + param.requires_grad = False + self.image_encoder1.eval() + for param in self.image_encoder2.parameters(): + param.requires_grad = False + self.image_encoder2.eval() + for param in self.image_encoder3.parameters(): + param.requires_grad = False + self.image_encoder3.eval() + for param in self.image_encoder4.parameters(): + param.requires_grad = False + self.image_encoder4.eval() + self.dim_text_raw = 4608 + self.proj_text = Linear(self.dim_text_raw, dim_text) + self.video_encoder = video_encoder + + for param in self.vocos.parameters(): + param.requires_grad = False + self.vocos.eval() + + @property + def device(self): + return next(self.parameters()).device + + def encode_text(self, prompt): + device = self.device + batch = self.tokenizer2(prompt, max_length=self.tokenizer2.model_max_length, padding=True, truncation=True, return_tensors="pt") + input_ids, attention_mask = batch.input_ids.to(device), batch.attention_mask.to(device) + + with torch.no_grad(): + encoder_hidden_states = self.text_encoder2(input_ids=input_ids, attention_mask=attention_mask)[0] + + boolean_encoder_mask = (attention_mask == 1).to(device) + return encoder_hidden_states, boolean_encoder_mask + + def encode_video(self, video_paths, l): + if self.proj_text is None: + d = self.dim_text + else: + d = self.dim_text_raw + device = self.device + b = 20 + with torch.no_grad(): + video_embeddings = [] + video_lens = [] + for video_path in video_paths: + if video_path is None: + video_embeddings.append(None) + video_lens.append(0) + continue + if isinstance(video_path, tuple): + video_path, start_sample, max_sample = video_path + else: + start_sample = 0 + max_sample = None + if video_path.startswith("/ailab-train/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = video_path.replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = video_path.replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = video_path.replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = video_path.replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = video_path.replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = video_path.replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = video_path.replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = video_path.replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = video_path.replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = video_path.replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + + if not os.path.exists(feature_path): + #print("video not exist", video_path) + frames, duration = read_frames_with_moviepy(video_path, max_frame_nums=None) + if frames is None: + video_embeddings.append(None) + video_lens.append(0) + continue + if self.video_encoder in ["clip_vit", "clip_vit2", "dinov2"]: + images = self.image_processor(images=frames, return_tensors="pt").to(device) + #print("images", images["pixel_values"].shape, images["pixel_values"].max(), images["pixel_values"].min(), torch.abs(images["pixel_values"]).mean()) + elif self.video_encoder in ["clip_convnext"]: + images = [] + for i in range(frames.shape[0]): + images.append(self.image_processor(Image.fromarray(frames[i])).unsqueeze(0)) + images = torch.cat(images, dim=0).to(device) + #print("images", images.shape, images.max(), images.min(), torch.abs(images).mean()) + elif self.video_encoder in ["mixed"]: + #images1 = self.image_processor1(images=frames, return_tensors="pt").to(device) + images2 = self.image_processor2(images=frames, return_tensors="pt").to(device) + images4 = self.image_processor4(images=frames, return_tensors="pt").to(device) + images3 = [] + for i in range(frames.shape[0]): + images3.append(self.image_processor3(Image.fromarray(frames[i])).unsqueeze(0)) + images3 = torch.cat(images3, dim=0).to(device) + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + image_embeddings = [] + if self.video_encoder == "clip_vit": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + elif self.video_encoder == "clip_vit2": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + elif self.video_encoder == "clip_convnext": + for i in range(math.ceil(images.shape[0] / b)): + image_embeddings.append(self.image_encoder.encode_image(images[i*b: (i+1)*b]).cpu()) + elif self.video_encoder == "dinov2": + for i in range(math.ceil(images["pixel_values"].shape[0] / b)): + image_embeddings.append(self.image_encoder(pixel_values=images["pixel_values"][i*b: (i+1)*b]).pooler_output.cpu()) + elif self.video_encoder == "mixed": + feature_path1 = feature_path.replace("/feature_mixed/", "/feature/") + if not os.path.exists(feature_path1): + image_embeddings1 = [] + for i in range(math.ceil(images1["pixel_values"].shape[0] / b)): + image_embeddings1.append(self.image_encoder1(pixel_values=images1["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + image_embeddings1 = torch.cat(image_embeddings1, dim=0) + #np.savez(feature_path1, image_embeddings1, duration) + else: + data1 = np.load(feature_path1) + image_embeddings1 = torch.from_numpy(data1["arr_0"]) + feature_path2 = feature_path.replace("/feature_mixed/", "/feature_clip_vit2/") + if not os.path.exists(feature_path2): + image_embeddings2 = [] + for i in range(math.ceil(images2["pixel_values"].shape[0] / b)): + image_embeddings2.append(self.image_encoder2(pixel_values=images2["pixel_values"][i*b: (i+1)*b]).image_embeds.cpu()) + image_embeddings2 = torch.cat(image_embeddings2, dim=0) + np.savez(feature_path2, image_embeddings2, duration) + else: + data2 = np.load(feature_path2) + image_embeddings2 = torch.from_numpy(data2["arr_0"]) + feature_path3 = feature_path.replace("/feature_mixed/", "/feature_clip_convnext/") + if not os.path.exists(feature_path3): + image_embeddings3 = [] + for i in range(math.ceil(images3.shape[0] / b)): + image_embeddings3.append(self.image_encoder3.encode_image(images3[i*b: (i+1)*b]).cpu()) + image_embeddings3 = torch.cat(image_embeddings3, dim=0) + np.savez(feature_path3, image_embeddings3, duration) + else: + data3 = np.load(feature_path3) + image_embeddings3 = torch.from_numpy(data3["arr_0"]) + feature_path4 = feature_path.replace("/feature_mixed/", "/feature_dinov2/") + if not os.path.exists(feature_path4): + image_embeddings4 = [] + for i in range(math.ceil(images4["pixel_values"].shape[0] / b)): + image_embeddings4.append(self.image_encoder4(pixel_values=images4["pixel_values"][i*b: (i+1)*b]).pooler_output.cpu()) + image_embeddings4 = torch.cat(image_embeddings4, dim=0) + np.savez(feature_path4, image_embeddings4, duration) + else: + data4 = np.load(feature_path4) + image_embeddings4 = torch.from_numpy(data4["arr_0"]) + mixed_l = min([image_embeddings1.shape[0], image_embeddings2.shape[0], image_embeddings3.shape[0], image_embeddings4.shape[0]]) + for i in range(mixed_l): + image_embeddings.append(torch.cat([image_embeddings1[i:i+1,:], image_embeddings2[i:i+1,:], image_embeddings3[i:i+1,:], image_embeddings4[i:i+1,:]], dim=1)) + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + image_embeddings = torch.cat(image_embeddings, dim=0) + #print("image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + np.savez(feature_path, image_embeddings, duration) + else: + #print("video exist", feature_path) + data = np.load(feature_path) + image_embeddings = torch.from_numpy(data["arr_0"]) + #print("image_embeddings", image_embeddings.shape, image_embeddings.max(), image_embeddings.min(), torch.abs(image_embeddings).mean()) + duration = data["arr_1"].item() + if max_sample is None: + max_sample = int(duration * self.sampling_rate) + interpolated = [] + for i in range(start_sample, max_sample, self.frame_size): + j = min(round((i+self.frame_size//2) / self.sampling_rate / (duration / (image_embeddings.shape[0] - 1))), image_embeddings.shape[0] - 1) + interpolated.append(image_embeddings[j:j+1]) + if len(interpolated) >= l: + break + interpolated = torch.cat(interpolated, dim=0) + #ll = list(range(start_sample, max_sample, self.frame_size)) + #print("encode_video l", len(ll), l, round((ll[-1]+self.frame_size//2) / self.sampling_rate / (duration / (image_embeddings.shape[0] - 1))), image_embeddings.shape[0] - 1) + #print("encode_video one", video_path, duration, image_embeddings.shape, interpolated.shape, l) + video_embeddings.append(interpolated.unsqueeze(0)) + video_lens.append(interpolated.shape[1]) + max_length = max(video_lens) + if max_length == 0: + max_length = l + else: + max_length = l + for i in range(len(video_embeddings)): + if video_embeddings[i] is None: + video_embeddings[i] = torch.zeros(1, max_length, d) + continue + if video_embeddings[i].shape[1] < max_length: + video_embeddings[i] = torch.cat([video_embeddings[i], torch.zeros(1, max_length-video_embeddings[i].shape[1], d)], 1) + video_embeddings = torch.cat(video_embeddings, 0) + #print("encode_video", l, video_embeddings.shape, video_lens) + return video_embeddings.to(device) + + def transformer_with_pred_head( + self, + x: Float['b n d'], + cond: Float['b n d'] | None = None, + times: Float['b'] | None = None, + mask: Bool['b n'] | None = None, + text: Int['b nt'] | Float['b nt dt'] | None = None, + prompt = None, + video_drop_prompt = None, + audio_drop_prompt = None, + drop_audio_cond: bool | None = None, + drop_text_cond: bool | None = None, + drop_text_prompt: bool | None = None, + return_drop_conditions = False + ): + seq_len = x.shape[-2] + bs = x.shape[0] + drop_audio_cond = [default(drop_audio_cond, self.training and random() < self.audiocond_drop_prob) for _ in range(bs)] + drop_text_cond = default(drop_text_cond, self.training and random() < self.cond_drop_prob) + drop_text_prompt = [default(drop_text_prompt, self.training and random() < self.prompt_drop_prob) for _ in range(bs)] + + if cond is not None: + for b in range(bs): + if drop_audio_cond[b]: + cond[b] = 0 + if audio_drop_prompt is not None and audio_drop_prompt[b]: + cond[b] = 0 + + if cond is not None: + if self.concat_cond: + # concat condition, given as using voicebox-like scheme + x = torch.cat((cond, x), dim = -1) + + x = self.proj_in(x) + + if cond is not None: + if not self.concat_cond: + # an alternative is to simply sum the condition + # seems to work fine + + cond = self.cond_proj_in(cond) + x = x + cond + + # whether to use a text embedding + + text_embed = None + if exists(text) and len(text.shape) == 3: + text_embed = text.clone() + if drop_text_cond: + for b in range(bs): + text_embed[b] = 0 + elif exists(text) and not drop_text_cond: + text_embed = self.embed_text(text, seq_len, mask = mask) + + context, context_mask = None, None + if prompt is not None: + #for b in range(bs): + # if drop_text_prompt[b]: + # prompt[b] = "" + if video_drop_prompt is not None: + for b in range(bs): + if video_drop_prompt[b]: + prompt[b] = "the sound of X X" + context, context_mask = self.encode_text(prompt) + for b in range(bs): + if drop_text_prompt[b]: + context[b] = 0 + if video_drop_prompt is not None and video_drop_prompt[b]: + context[b] = 0 + #print("cross attention", context.shape, context_mask.shape, x.shape, mask.shape, text_embed.shape if text_embed is not None else None, torch.mean(torch.abs(text_embed), dim=(1,2))) + #print("video_drop_prompt", prompt, video_drop_prompt, context.shape, torch.mean(torch.abs(context), dim=(1,2))) + #print("audio_drop_prompt", audio_drop_prompt, cond.shape, torch.mean(torch.abs(cond), dim=(1,2))) + + if self.proj_text is not None: + text_embed = self.proj_text(text_embed) + + # attend + + attended, loss_contra = self.transformer( + x, + times = times, + mask = mask, + text_embed = text_embed, + context = context, + context_mask = context_mask + ) + + pred = self.to_pred(attended) + + if not return_drop_conditions: + return pred, loss_contra + + return pred, loss_contra, drop_audio_cond, drop_text_cond, drop_text_prompt + + def cfg_transformer_with_pred_head( + self, + *args, + cfg_strength: float = 1., + remove_parallel_component: bool = True, + keep_parallel_frac: float = 0., + **kwargs, + ): + + pred, _ = self.transformer_with_pred_head(*args, drop_audio_cond = False, drop_text_cond = False, drop_text_prompt = False, **kwargs) + + if cfg_strength < 1e-5: + return pred + + null_pred, _ = self.transformer_with_pred_head(*args, drop_audio_cond = True, drop_text_cond = True, drop_text_prompt = True, **kwargs) + + cfg_update = pred - null_pred + + if remove_parallel_component: + # https://arxiv.org/abs/2410.02416 + parallel, orthogonal = project(cfg_update, pred) + cfg_update = orthogonal + parallel * keep_parallel_frac + + return pred + cfg_update * cfg_strength + + def add_noise(self, signal, mask, val): + if self.audiocond_snr is None: + return signal + if not val: + snr = np.random.uniform(self.audiocond_snr[0], self.audiocond_snr[1]) + else: + snr = (self.audiocond_snr[0] + self.audiocond_snr[1]) / 2.0 + #print("add_noise", self.audiocond_snr, snr, signal.shape, mask) # [True, ..., False] + noise = torch.randn_like(signal) + w = torch.abs(signal[mask]).mean() / (torch.abs(noise[mask]).mean() + 1e-6) / snr + return signal + noise * w + + @torch.no_grad() + def sample( + self, + cond: Float['b n d'] | Float['b nw'] | None = None, + *, + text: Int['b nt'] | list[str] | None = None, + lens: Int['b'] | None = None, + duration: int | Int['b'] | None = None, + steps = 32, + cfg_strength = 1., # they used a classifier free guidance strength of 1. + remove_parallel_component = True, + sway_sampling = True, + max_duration = 4096, # in case the duration predictor goes haywire + vocoder: Callable[[Float['b d n']], list[Float['_']]] | None = None, + return_raw_output: bool | None = None, + save_to_filename: str | None = None, + prompt = None, + video_drop_prompt = None, + audio_drop_prompt = None, + video_paths = None + ) -> ( + Float['b n d'], + list[Float['_']] + ): + self.eval() + + # raw wave + + if cond.ndim == 2: + cond = self.mel_spec(cond) + cond = rearrange(cond, 'b d n -> b n d') + assert cond.shape[-1] == self.num_channels + + batch, cond_seq_len, device = *cond.shape[:2], cond.device + + if not exists(lens): + lens = torch.full((batch,), cond_seq_len, device = device, dtype = torch.long) + + if video_paths is not None: + text = self.encode_video(video_paths, cond_seq_len) + # text + elif isinstance(text, list): + text = self.tokenizer(text).to(device) + assert text.shape[0] == batch + + if exists(text): + text_lens = (text != -1).sum(dim = -1) + lens = torch.maximum(text_lens, lens) # make sure lengths are at least those of the text characters + + # duration + + cond_mask = lens_to_mask(lens) + + if exists(duration): + if isinstance(duration, int): + duration = torch.full((batch,), duration, device = device, dtype = torch.long) + + elif exists(self.duration_predictor): + duration = self.duration_predictor(cond, text = text, lens = lens, return_loss = False).long() + + duration = torch.maximum(lens, duration) # just add one token so something is generated + duration = duration.clamp(max = max_duration) + + assert duration.shape[0] == batch + + max_duration = duration.amax() + + cond = F.pad(cond, (0, 0, 0, max_duration - cond_seq_len), value = 0.) + cond_mask = F.pad(cond_mask, (0, max_duration - cond_mask.shape[-1]), value = False) + cond_mask = rearrange(cond_mask, '... -> ... 1') + + mask = lens_to_mask(duration) + #print("####", duration, mask, mask.shape, lens, cond_mask, cond_mask.shape, text) + + # neural ode + + def fn(t, x): + # at each step, conditioning is fixed + + if lens[0] == duration[0]: + print("No cond", lens, duration) + step_cond = None + else: + step_cond = torch.where(cond_mask, self.add_noise(cond, cond_mask, True), torch.zeros_like(cond)) + + # predict flow + + return self.cfg_transformer_with_pred_head( + x, + step_cond, + times = t, + text = text, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + cfg_strength = cfg_strength, + remove_parallel_component = remove_parallel_component + ) + + ####torch.manual_seed(0) + y0 = torch.randn_like(cond) + t = torch.linspace(0, 1, steps, device = self.device) + if sway_sampling: + t = t + -1.0 * (torch.cos(torch.pi / 2 * t) - 1 + t) + #print("@@@@", t) + + trajectory = odeint(fn, y0, t, **self.odeint_kwargs) + sampled = trajectory[-1] + + out = sampled + + if lens[0] != duration[0]: + out = torch.where(cond_mask, cond, out) + + # able to return raw untransformed output, if not using mel rep + + if exists(return_raw_output) and return_raw_output: + return out + + # take care of transforming mel to audio if `vocoder` is passed in, or if `use_vocos` is turned on + + if exists(vocoder): + assert not exists(self.vocos), '`use_vocos` should not be turned on if you are passing in a custom `vocoder` on sampling' + out = rearrange(out, 'b n d -> b d n') + out = vocoder(out) + + elif exists(self.vocos): + + audio = [] + for mel, one_mask in zip(out, mask): + #one_out = DB_to_amplitude(mel[one_mask], ref = 1., power = 0.5) + one_out = mel[one_mask] + + one_out = rearrange(one_out, 'n d -> 1 d n') + one_audio = self.vocos.decode(one_out) + one_audio = rearrange(one_audio, '1 nw -> nw') + audio.append(one_audio) + + out = audio + + if exists(save_to_filename): + assert exists(vocoder) or exists(self.vocos) + assert exists(self.sampling_rate) + + path = Path(save_to_filename) + parent_path = path.parents[0] + parent_path.mkdir(exist_ok = True, parents = True) + + for ind, one_audio in enumerate(out): + one_audio = rearrange(one_audio, 'nw -> 1 nw') + if len(out) == 1: + save_path = str(parent_path / f'{path.name}') + else: + save_path = str(parent_path / f'{ind + 1}.{path.name}') + torchaudio.save(save_path, one_audio.detach().cpu(), sample_rate = self.sampling_rate) + + return out + + def forward( + self, + inp: Float['b n d'] | Float['b nw'], # mel or raw wave + *, + text: Int['b nt'] | list[str] | None = None, + times: int | Int['b'] | None = None, + lens: Int['b'] | None = None, + velocity_consistency_model: E2TTS | None = None, + velocity_consistency_delta = 1e-3, + prompt = None, + video_drop_prompt=None, + audio_drop_prompt=None, + val = False, + video_paths=None + ): + need_velocity_loss = exists(velocity_consistency_model) and self.velocity_consistency_weight > 0. + + # handle raw wave + + if inp.ndim == 2: + inp = self.mel_spec(inp) + inp = rearrange(inp, 'b d n -> b n d') + assert inp.shape[-1] == self.num_channels + + batch, seq_len, dtype, device = *inp.shape[:2], inp.dtype, self.device + + if video_paths is not None: + text = self.encode_video(video_paths, seq_len) + # handle text as string + elif isinstance(text, list): + text = self.tokenizer(text).to(device) + #print("text tokenized", text[0]) + assert text.shape[0] == batch + + # lens and mask + + if not exists(lens): + lens = torch.full((batch,), seq_len, device = device) + + mask = lens_to_mask(lens, length = seq_len) + + # get a random span to mask out for training conditionally + + if not val: + if self.audiocond_drop_prob > 1.0: + frac_lengths = torch.zeros((batch,), device = self.device).float().uniform_(1.0,1.0) + else: + frac_lengths = torch.zeros((batch,), device = self.device).float().uniform_(*self.frac_lengths_mask) + else: + frac_lengths = torch.tensor([(0.7+1.0)/2.0]*batch, device = self.device).float() + rand_span_mask = mask_from_frac_lengths(lens, frac_lengths, max_length = seq_len, val = val) + + if exists(mask): + rand_span_mask &= mask + + # mel is x1 + + x1 = inp + + # main conditional flow training logic + # just ~5 loc + + # x0 is gaussian noise + + if val: + torch.manual_seed(0) + x0 = torch.randn_like(x1) + if val: + torch.manual_seed(int(time.time()*1000)) + + # t is random times from above + + if times is None: + times = torch.rand((batch,), dtype = dtype, device = self.device) + else: + times = torch.tensor((times,)*batch, dtype = dtype, device = self.device) + t = rearrange(times, 'b -> b 1 1') + + # if need velocity consistency, make sure time does not exceed 1. + + if need_velocity_loss: + t = t * (1. - velocity_consistency_delta) + + # sample xt (w in the paper) + + w = (1. - t) * x0 + t * x1 + + flow = x1 - x0 + + # only predict what is within the random mask span for infilling + + if self.audiocond_drop_prob > 1.0: + cond = None + else: + cond = einx.where( + 'b n, b n d, b n d -> b n d', + rand_span_mask, + torch.zeros_like(x1), self.add_noise(x1, ~rand_span_mask, val) + ) + + # transformer and prediction head + + if not val: + pred, loss_contra, did_drop_audio_cond, did_drop_text_cond, did_drop_text_prompt = self.transformer_with_pred_head( + w, + cond, + times = times, + text = text, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + return_drop_conditions = True + ) + else: + pred, loss_contra, did_drop_audio_cond, did_drop_text_cond, did_drop_text_prompt = self.transformer_with_pred_head( + w, + cond, + times = times, + text = text, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + drop_audio_cond = False, + drop_text_cond = False, + drop_text_prompt = False, + return_drop_conditions = True + ) + + # maybe velocity consistency loss + + velocity_loss = self.zero + + if need_velocity_loss: + + t_with_delta = t + velocity_consistency_delta + w_with_delta = (1. - t_with_delta) * x0 + t_with_delta * x1 + + with torch.no_grad(): + ema_pred, _ = velocity_consistency_model.transformer_with_pred_head( + w_with_delta, + cond, + times = times + velocity_consistency_delta, + text = text, + mask = mask, + prompt = prompt, + video_drop_prompt = video_drop_prompt, + audio_drop_prompt = audio_drop_prompt, + drop_audio_cond = did_drop_audio_cond, + drop_text_cond = did_drop_text_cond, + drop_text_prompt = did_drop_text_prompt + ) + + velocity_loss = F.mse_loss(pred, ema_pred, reduction = 'none') + velocity_loss = velocity_loss[rand_span_mask].mean() + + # flow matching loss + + loss = F.mse_loss(pred, flow, reduction = 'none') + + #print("loss", loss.shape, loss, "rand_span_mask", rand_span_mask.shape, rand_span_mask, "loss[rand_span_mask]", loss[rand_span_mask].shape, loss[rand_span_mask]) + loss = loss[rand_span_mask].mean() + + # total loss and get breakdown + + #total_loss = loss + velocity_loss * self.velocity_consistency_weight + #breakdown = LossBreakdown(loss, velocity_loss) + #print("loss", loss, velocity_loss, self.velocity_consistency_weight) + + ####contra_weight = 0.04 + contra_weight = 1.0 + total_loss = loss + loss_contra * contra_weight + breakdown = LossBreakdown(loss, loss_contra * contra_weight) + #print("loss", loss, loss_contra * contra_weight) + + # return total loss and bunch of intermediates + + return E2TTSReturn(total_loss, cond if cond is not None else w, pred, x0 + pred, breakdown) diff --git a/src/e2_tts_pytorch/mix.py b/src/e2_tts_pytorch/mix.py new file mode 100644 index 0000000000000000000000000000000000000000..0619c1383406849972e7a5b107cc8aa839594e75 --- /dev/null +++ b/src/e2_tts_pytorch/mix.py @@ -0,0 +1,53 @@ +import numpy as np + + +def a_weight(fs, n_fft, min_db=-80.0): + freq = np.linspace(0, fs // 2, n_fft // 2 + 1) + freq_sq = np.power(freq, 2) + freq_sq[0] = 1.0 + weight = 2.0 + 20.0 * (2 * np.log10(12194) + 2 * np.log10(freq_sq) + - np.log10(freq_sq + 12194 ** 2) + - np.log10(freq_sq + 20.6 ** 2) + - 0.5 * np.log10(freq_sq + 107.7 ** 2) + - 0.5 * np.log10(freq_sq + 737.9 ** 2)) + weight = np.maximum(weight, min_db) + + return weight + + +def compute_gain(sound, fs, min_db=-80.0, mode="A_weighting"): + if fs == 16000: + n_fft = 2048 + elif fs == 44100: + n_fft = 4096 + elif fs == 24000: + n_fft = 3072 + else: + raise Exception("Invalid fs {}".format(fs)) + stride = n_fft // 2 + + gain = [] + for i in range(0, len(sound) - n_fft + 1, stride): + if mode == "RMSE": + g = np.mean(sound[i: i + n_fft] ** 2) + elif mode == "A_weighting": + spec = np.fft.rfft(np.hanning(n_fft + 1)[:-1] * sound[i: i + n_fft]) + power_spec = np.abs(spec) ** 2 + a_weighted_spec = power_spec * np.power(10, a_weight(fs, n_fft) / 10) + g = np.sum(a_weighted_spec) + else: + raise Exception("Invalid mode {}".format(mode)) + gain.append(g) + + gain = np.array(gain) + gain = np.maximum(gain, np.power(10, min_db / 10)) + gain_db = 10 * np.log10(gain) + return gain_db + + +def mix(sound1, sound2, r, fs): + gain1 = np.max(compute_gain(sound1[0, :], fs)) # Decibel + gain2 = np.max(compute_gain(sound2[0, :], fs)) + t = 1.0 / (1 + np.power(10, (gain1 - gain2) / 20.) * (1 - r) / r) + sound = ((sound1 * t + sound2 * (1 - t)) / np.sqrt(t ** 2 + (1 - t) ** 2)) + return sound \ No newline at end of file diff --git a/src/e2_tts_pytorch/multibench_model.py b/src/e2_tts_pytorch/multibench_model.py new file mode 100644 index 0000000000000000000000000000000000000000..5a2509a5c3d6254083387c3e7293ed7fb34b4d60 --- /dev/null +++ b/src/e2_tts_pytorch/multibench_model.py @@ -0,0 +1,750 @@ +from .critic_objectives import* + +from torchvision import transforms +import torch.nn.functional as F +import torch.optim as optim +import math +import copy + + + +############################ +# Simple Augmentations # +############################ + + +def permute(x): + # shuffle the sequence order + idx = torch.randperm(x.shape[0]) + return x[idx] + +def noise(x): + noise = torch.randn(x.shape) * 0.1 + return x + noise.to(x.device) + +def drop(x): + # drop 20% of the sequences + drop_num = x.shape[0] // 5 + + x_aug = torch.clone(x) + drop_idxs = np.random.choice(x.shape[0], drop_num, replace=False) + x_aug[drop_idxs] = 0.0 + return x_aug + +def mixup(x, alpha=1.0): + indices = torch.randperm(x.shape[0]) + lam = np.random.beta(alpha, alpha) + aug_x = x * lam + x[indices] * (1 - lam) + + return aug_x + +def identity(x): + return x + + +def augment(x_batch): + v1 = x_batch + v2 = torch.clone(v1) + transforms = [permute, noise, drop, identity] + + for i in range(x_batch.shape[0]): + t_idxs = np.random.choice(4, 2, replace=False) + t1 = transforms[t_idxs[0]] + t2 = transforms[t_idxs[1]] + v1[i] = t1(v1[i]) + v2[i] = t2(v2[i]) + + return v1, v2 + +# return one augmented instance +def augment_single(x_batch): + v1 = x_batch + v2 = torch.clone(v1) + transforms = [permute, noise, drop, identity] + + for i in range(x_batch.shape[0]): + t_idxs = np.random.choice(4, 1, replace=False) + t = transforms[t_idxs[0]] + v2[i] = t(v2[i]) + + return v2 + + +def augment_embed_single(x_batch): + v1 = x_batch + v2 = torch.clone(v1) + transforms = [noise, mixup, identity] + + t_idxs = np.random.choice(3, 1, replace=False) + t = transforms[t_idxs[0]] + v2 = t(v2) + + return v2 + + +def augment_mimic(x_batch): + if x_batch.dim() == 2: + return augment_embed_single(x_batch) + else: + return augment_single(x_batch) + + + +############## +# Models # +############## + +def mlp_head(dim_in, feat_dim): + return nn.Sequential( + nn.Linear(dim_in, dim_in), + nn.ReLU(inplace=True), + nn.Linear(dim_in, feat_dim) + ) + + +class SupConModel(nn.Module): + """backbone + projection head""" + def __init__(self, temperature, encoders, dim_ins, feat_dims, use_label=False, head='mlp'): + super(SupConModel, self).__init__() + + self.use_label = use_label + self.encoders = nn.ModuleList(encoders) + if head == 'linear': + self.head1 = nn.Linear(dim_ins[0], feat_dims[0]) + self.head2 = nn.Linear(dim_ins[1], feat_dims[1]) + elif head == 'mlp': + self.head1 = nn.Sequential( + nn.Linear(dim_ins[0], dim_ins[0]), + nn.ReLU(inplace=True), + nn.Linear(dim_ins[0], feat_dims[0]) + ) + self.head2 = nn.Sequential( + nn.Linear(dim_ins[1], dim_ins[1]), + nn.ReLU(inplace=True), + nn.Linear(dim_ins[1], feat_dims[1]) + ) + + else: + raise NotImplementedError( + 'head not supported: {}'.format(head)) + self.critic = SupConLoss(temperature=temperature) + + def forward(self, x1, x2, y): + feat1 = self.encoders[0](x1) + feat1 = self.head1(feat1) + + feat2 = self.encoders[1](x2) + feat2 = self.head2(feat2) + + feat = torch.cat([feat1.unsqueeze(1), feat2.unsqueeze(1)], dim=1) + loss = self.critic(feat, y) if self.use_label else self.critic(feat) + + return loss + + def get_embedding(self, x1, x2): + return self.encoders[0](x1), self.encoders[1](x2) + + + + +class FactorCLSUP(nn.Module): + def __init__(self, encoders, feat_dims, y_ohe_dim, temperature=1, activation='relu', lr=1e-4, ratio=1): + super(FactorCLSUP, self).__init__() + self.critic_hidden_dim = 512 + self.critic_layers = 1 + self.critic_activation = 'relu' + self.lr = lr + self.ratio = ratio + self.y_ohe_dim = y_ohe_dim + self.temperature = temperature + self.feat_dims = feat_dims + + # encoder backbones + ####self.backbones = nn.ModuleList(encoders) + + # linear projection heads + ####self.linears_infonce_x1x2 = nn.ModuleList([mlp_head(self.feat_dims[i], self.feat_dims[i]) for i in range(2)]) + self.linears_club_x1x2_cond = nn.ModuleList([mlp_head(self.feat_dims[i], self.feat_dims[i]) for i in range(2)]) + + ####self.linears_infonce_x1y = mlp_head(self.feat_dims[0], self.feat_dims[0]) + ####self.linears_infonce_x2y = mlp_head(self.feat_dims[1], self.feat_dims[1]) + ####self.linears_infonce_x1x2_cond = nn.ModuleList([mlp_head(self.feat_dims[i], self.feat_dims[i]) for i in range(2)]) + ####self.linears_club_x1x2 = nn.ModuleList([mlp_head(self.feat_dims[i], self.feat_dims[i]) for i in range(2)]) + + # critics + ####self.infonce_x1x2 = InfoNCECritic(self.feat_dims[0], self.feat_dims[1], self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + self.club_x1x2_cond = CLUBInfoNCECritic(self.feat_dims[0] + self.y_ohe_dim, self.feat_dims[1] + self.y_ohe_dim, + self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + + ####self.infonce_x1y = InfoNCECritic(self.feat_dims[0], 1, self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + ####self.infonce_x2y = InfoNCECritic(self.feat_dims[1], 1, self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + ####self.infonce_x1x2_cond = InfoNCECritic(self.feat_dims[0] + self.y_ohe_dim, self.feat_dims[1] + self.y_ohe_dim, + #### self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + ####self.club_x1x2 = CLUBInfoNCECritic(self.feat_dims[0], self.feat_dims[1], self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + + + + def ohe(self, y): + N = y.shape[0] + y_ohe = torch.zeros((N, self.y_ohe_dim)) + y_ohe[torch.arange(N).long(), y.T[0].long()] = 1 + return y_ohe + + def forward(self, x1, x2, y): + # Get embeddings + ####x1_embed = self.backbones[0](x1) + ####x2_embed = self.backbones[1](x2) + x1_embed, x2_embed = x1, x2 + x1_embed = F.normalize(x1_embed, dim=-1) + x2_embed = F.normalize(x2_embed, dim=-1) + + # Get ohe label + y_ohe = self.ohe(y).cuda() + + # Compute losses + ####uncond_losses = [self.infonce_x1x2(self.linears_infonce_x1x2[0](x1_embed), self.linears_infonce_x1x2[1](x2_embed)), + #### self.club_x1x2(self.linears_club_x1x2[0](x1_embed), self.linears_club_x1x2[1](x2_embed)), + #### self.infonce_x1y(self.linears_infonce_x1y(x1_embed), y), + #### self.infonce_x2y(self.linears_infonce_x2y(x2_embed), y) + ####] + #### + ####cond_losses = [self.infonce_x1x2_cond(torch.cat([self.linears_infonce_x1x2_cond[0](x1_embed), y_ohe], dim=1), + #### torch.cat([self.linears_infonce_x1x2_cond[1](x2_embed), y_ohe], dim=1)), + #### self.club_x1x2_cond(torch.cat([self.linears_club_x1x2_cond[0](x1_embed), y_ohe], dim=1), + #### torch.cat([self.linears_club_x1x2_cond[1](x2_embed), y_ohe], dim=1)), + ####] + + cond_losses = [self.club_x1x2_cond(torch.cat([self.linears_club_x1x2_cond[0](x1_embed), y_ohe], dim=1), + torch.cat([self.linears_club_x1x2_cond[1](x2_embed), y_ohe], dim=1)), + ] + + ####return sum(uncond_losses) + sum(cond_losses) + return sum(cond_losses) + + + def learning_loss(self, x1, x2, y): + # Get embeddings + ####x1_embed = self.backbones[0](x1) + ####x2_embed = self.backbones[1](x2) + x1_embed, x2_embed = x1, x2 + x1_embed = F.normalize(x1_embed, dim=-1) + x2_embed = F.normalize(x2_embed, dim=-1) + + y_ohe = self.ohe(y).cuda() + + # Calculate InfoNCE loss for CLUB-NCE + learning_losses = [self.club_x1x2.learning_loss(self.linears_club_x1x2[0](x1_embed), self.linears_club_x1x2[1](x2_embed)), + self.club_x1x2_cond.learning_loss(torch.cat([self.linears_club_x1x2_cond[0](x1_embed), y_ohe], dim=1), + torch.cat([self.linears_club_x1x2_cond[1](x2_embed), y_ohe], dim=1)) + ] + return sum(learning_losses) + + + def get_embedding(self, x1, x2): + x1_embed = self.backbones[0](x1) + x2_embed = self.backbones[1](x2) + + x1_reps = [self.linears_infonce_x1x2[0](x1_embed), + self.linears_club_x1x2[0](x1_embed), + self.linears_infonce_x1y(x1_embed), + self.linears_infonce_x1x2_cond[0](x1_embed), + self.linears_club_x1x2_cond[0](x1_embed)] + + x2_reps = [self.linears_infonce_x1x2[1](x2_embed), + self.linears_club_x1x2[1](x2_embed), + self.linears_infonce_x2y(x2_embed), + self.linears_infonce_x1x2_cond[1](x2_embed), + self.linears_club_x1x2_cond[1](x2_embed)] + + return torch.cat(x1_reps, dim=1), torch.cat(x2_reps, dim=1) + + + def get_optims(self): + non_CLUB_params = [self.backbones.parameters(), + self.infonce_x1x2.parameters(), + self.infonce_x1y.parameters(), + self.infonce_x2y.parameters(), + self.infonce_x1x2_cond.parameters(), + self.linears_infonce_x1x2.parameters(), + self.linears_infonce_x1y.parameters(), + self.linears_infonce_x2y.parameters(), + self.linears_infonce_x1x2_cond.parameters(), + self.linears_club_x1x2_cond.parameters(), + self.linears_club_x1x2.parameters()] + + + CLUB_params = [self.club_x1x2_cond.parameters(), + self.club_x1x2.parameters()] + + non_CLUB_optims = [optim.Adam(param, lr=self.lr) for param in non_CLUB_params] + CLUB_optims = [optim.Adam(param, lr=self.lr) for param in CLUB_params] + + return non_CLUB_optims, CLUB_optims + + +class FactorCLSSL(nn.Module): + def __init__(self, encoders, feat_dims, y_ohe_dim, temperature=1, activation='relu', lr=1e-4, ratio=1): + super(FactorCLSSL, self).__init__() + self.critic_hidden_dim = 512 + self.critic_layers = 1 + self.critic_activation = 'relu' + self.lr = lr + self.ratio = ratio + self.y_ohe_dim = y_ohe_dim + self.temperature = temperature + + # encoder backbones + self.feat_dims = feat_dims + ####self.backbones = nn.ModuleList(encoders) + + # linear projection heads + self.linears_infonce_x1x2 = nn.ModuleList([mlp_head(self.feat_dims[i], self.feat_dims[i]) for i in range(2)]) + self.linears_club_x1x2_cond = nn.ModuleList([mlp_head(self.feat_dims[i], self.feat_dims[i]) for i in range(2)]) + + self.linears_infonce_x1y = mlp_head(self.feat_dims[0], self.feat_dims[0]) + self.linears_infonce_x2y = mlp_head(self.feat_dims[1], self.feat_dims[1]) + self.linears_infonce_x1x2_cond = nn.ModuleList([mlp_head(self.feat_dims[i], self.feat_dims[i]) for i in range(2)]) + self.linears_club_x1x2 = nn.ModuleList([mlp_head(self.feat_dims[i], self.feat_dims[i]) for i in range(2)]) + + # critics + self.infonce_x1x2 = InfoNCECritic(self.feat_dims[0], self.feat_dims[1], self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + self.club_x1x2_cond = CLUBInfoNCECritic(self.feat_dims[0]*2, self.feat_dims[1]*2, + self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + + self.infonce_x1y = InfoNCECritic(self.feat_dims[0], self.feat_dims[0], self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + self.infonce_x2y = InfoNCECritic(self.feat_dims[1], self.feat_dims[1], self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + self.infonce_x1x2_cond = InfoNCECritic(self.feat_dims[0]*2, self.feat_dims[1]*2, + self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + self.club_x1x2 = CLUBInfoNCECritic(self.feat_dims[0], self.feat_dims[1], self.critic_hidden_dim, self.critic_layers, activation, temperature=temperature) + + + def ohe(self, y): + N = y.shape[0] + y_ohe = torch.zeros((N, self.y_ohe_dim)) + y_ohe[torch.arange(N).long(), y.T[0].long()] = 1 + return y_ohe + + def forward(self, x1, x2, x1_aug, x2_aug): + # Get embeddings + ####x1_embed = self.backbones[0](x1) + ####x2_embed = self.backbones[1](x2) + #### + ####x1_aug_embed = self.backbones[0](x1_aug) + ####x2_aug_embed = self.backbones[1](x2_aug) + x1_embed, x2_embed, x1_aug_embed, x2_aug_embed = x1, x2, x1_aug, x2_aug + x1_embed = F.normalize(x1_embed, dim=-1) + x2_embed = F.normalize(x2_embed, dim=-1) + x1_aug_embed = F.normalize(x1_aug_embed, dim=-1) + x2_aug_embed = F.normalize(x2_aug_embed, dim=-1) + + #compute losses + uncond_losses = [self.infonce_x1x2(self.linears_infonce_x1x2[0](x1_embed), self.linears_infonce_x1x2[1](x2_embed)), + self.club_x1x2(self.linears_club_x1x2[0](x1_embed), self.linears_club_x1x2[1](x2_embed)), + self.infonce_x1y(self.linears_infonce_x1y(x1_embed), self.linears_infonce_x1y(x1_aug_embed)), + self.infonce_x2y(self.linears_infonce_x2y(x2_embed), self.linears_infonce_x2y(x2_aug_embed)) + ] + + cond_losses = [self.infonce_x1x2_cond(torch.cat([self.linears_infonce_x1x2_cond[0](x1_embed), + self.linears_infonce_x1x2_cond[0](x1_aug_embed)], dim=1), + torch.cat([self.linears_infonce_x1x2_cond[1](x2_embed), + self.linears_infonce_x1x2_cond[1](x2_aug_embed)], dim=1)), + self.club_x1x2_cond(torch.cat([self.linears_club_x1x2_cond[0](x1_embed), + self.linears_club_x1x2_cond[0](x1_aug_embed)], dim=1), + torch.cat([self.linears_club_x1x2_cond[1](x2_embed), + self.linears_club_x1x2_cond[1](x2_aug_embed)], dim=1)) + ] + + + return sum(uncond_losses) + sum(cond_losses) + + def learning_loss(self, x1, x2, x1_aug, x2_aug): + # Get embeddings + ####x1_embed = self.backbones[0](x1) + ####x2_embed = self.backbones[1](x2) + #### + ####x1_aug_embed = self.backbones[0](x1_aug) + ####x2_aug_embed = self.backbones[1](x2_aug) + x1_embed, x2_embed, x1_aug_embed, x2_aug_embed = x1, x2, x1_aug, x2_aug + x1_embed = F.normalize(x1_embed, dim=-1) + x2_embed = F.normalize(x2_embed, dim=-1) + x1_aug_embed = F.normalize(x1_aug_embed, dim=-1) + x2_aug_embed = F.normalize(x2_aug_embed, dim=-1) + + # Calculate InfoNCE loss for CLUB-NCE + learning_losses = [self.club_x1x2.learning_loss(self.linears_club_x1x2[0](x1_embed), self.linears_club_x1x2[1](x2_embed)), + self.club_x1x2_cond.learning_loss(torch.cat([self.linears_club_x1x2_cond[0](x1_embed), + self.linears_club_x1x2_cond[0](x1_aug_embed)], dim=1), + torch.cat([self.linears_club_x1x2_cond[1](x2_embed), + self.linears_club_x1x2_cond[1](x2_aug_embed)], dim=1)) + ] + return sum(learning_losses) + + def get_embedding(self, x1, x2): + x1_embed = self.backbones[0](x1) + x2_embed = self.backbones[1](x2) + + x1_reps = [self.linears_infonce_x1x2[0](x1_embed), + self.linears_club_x1x2[0](x1_embed), + self.linears_infonce_x1y(x1_embed), + self.linears_infonce_x1x2_cond[0](x1_embed), + self.linears_club_x1x2_cond[0](x1_embed)] + + x2_reps = [self.linears_infonce_x1x2[1](x2_embed), + self.linears_club_x1x2[1](x2_embed), + self.linears_infonce_x2y(x2_embed), + self.linears_infonce_x1x2_cond[1](x2_embed), + self.linears_club_x1x2_cond[1](x2_embed)] + + return torch.cat(x1_reps, dim=1), torch.cat(x2_reps, dim=1) + + + def get_optims(self): + non_CLUB_params = [self.backbones.parameters(), + self.infonce_x1x2.parameters(), + self.infonce_x1y.parameters(), + self.infonce_x2y.parameters(), + self.infonce_x1x2_cond.parameters(), + self.linears_infonce_x1x2.parameters(), + self.linears_infonce_x1y.parameters(), + self.linears_infonce_x2y.parameters(), + self.linears_infonce_x1x2_cond.parameters(), + self.linears_club_x1x2_cond.parameters(), + self.linears_club_x1x2.parameters()] + + + CLUB_params = [self.club_x1x2_cond.parameters(), + self.club_x1x2.parameters()] + + non_CLUB_optims = [optim.Adam(param, lr=self.lr) for param in non_CLUB_params] + CLUB_optims = [optim.Adam(param, lr=self.lr) for param in CLUB_params] + + return non_CLUB_optims, CLUB_optims + + + + +######################## +# Training Scripts # +######################## + + +# MOSI/MOSEI Training + +def mosi_label(y_batch): + res = copy.deepcopy(y_batch) + + res[y_batch >= 0] = 1 + res[y_batch < 0] = 0 + + return res + + +def train_supcon_mosi(model, train_loader, optimizer, modalities=[0,2], num_epoch=100): + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0][modalities[0]].float().cuda() + x2_batch = data_batch[0][modalities[1]].float().cuda() + y_batch = mosi_label(data_batch[3]).float().cuda() + + loss = model(x1_batch, x2_batch, y_batch) + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + return + + +def train_sup_mosi(model, train_loader, modalities=[0,2], num_epoch=50, num_club_iter=1): + non_CLUB_optims, CLUB_optims = model.get_optims() + losses = [] + + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0][modalities[0]].float().cuda() + x2_batch = data_batch[0][modalities[1]].float().cuda() + y_batch = mosi_label(data_batch[3]).float().cuda() + + loss = model(x1_batch, x2_batch, y_batch) + losses.append(loss.detach().cpu().numpy()) + + for optimizer in non_CLUB_optims: + optimizer.zero_grad() + + loss.backward() + + for optimizer in non_CLUB_optims: + optimizer.step() + + for _ in range(num_club_iter): + + learning_loss = model.learning_loss(x1_batch, x2_batch, y_batch) + + for optimizer in CLUB_optims: + optimizer.zero_grad() + + learning_loss.backward() + + for optimizer in CLUB_optims: + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + + return + + +def train_ssl_mosi(model, train_loader, modalities=[0,2], num_epoch=50, num_club_iter=1): + non_CLUB_optims, CLUB_optims = model.get_optims() + losses = [] + + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0][modalities[0]].float().cuda() + x2_batch = data_batch[0][modalities[1]].float().cuda() + + x1_aug = augment_single(x1_batch) + x2_aug = augment_single(x2_batch) + + loss = model(x1_batch, x2_batch, x1_aug, x2_aug) + losses.append(loss.detach().cpu().numpy()) + + for optimizer in non_CLUB_optims: + optimizer.zero_grad() + + loss.backward() + + for optimizer in non_CLUB_optims: + optimizer.step() + + for _ in range(num_club_iter): + + learning_loss = model.learning_loss(x1_batch, x2_batch, x1_aug, x2_aug) + + for optimizer in CLUB_optims: + optimizer.zero_grad() + + learning_loss.backward() + + for optimizer in CLUB_optims: + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + + return + + +# Sarcasm/Humor Training + +def sarcasm_label(y_batch): + res = copy.deepcopy(y_batch) + res[y_batch == -1] = 0 + + return res + +def train_supcon_sarcasm(model, train_loader, optimizer, modalities=[0,2], num_epoch=100): + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0][modalities[0]].float().cuda() + x2_batch = data_batch[0][modalities[1]].float().cuda() + y_batch = sarcasm_label(data_batch[3]).float().cuda() + + loss = model(x1_batch, x2_batch, y_batch) + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + return + + +def train_sup_sarcasm(model, train_loader, modalities=[0,2], num_epoch=50, num_club_iter=1): + non_CLUB_optims, CLUB_optims = model.get_optims() + losses = [] + + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0][modalities[0]].float().cuda() + x2_batch = data_batch[0][modalities[1]].float().cuda() + y_batch = sarcasm_label(data_batch[3]).float().cuda() + + #loss, losses, ts = model(x_batch, y_batch) + loss = model(x1_batch, x2_batch, y_batch) + losses.append(loss.detach().cpu().numpy()) + + for optimizer in non_CLUB_optims: + optimizer.zero_grad() + + loss.backward() + + for optimizer in non_CLUB_optims: + optimizer.step() + + for _ in range(num_club_iter): + + learning_loss = model.learning_loss(x1_batch, x2_batch, y_batch) + + for optimizer in CLUB_optims: + optimizer.zero_grad() + + learning_loss.backward() + + for optimizer in CLUB_optims: + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + + return + + +def train_ssl_sarcasm(model, train_loader, modalities=[0,2], num_epoch=50, num_club_iter=1): + non_CLUB_optims, CLUB_optims = model.get_optims() + losses = [] + + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0][modalities[0]].float().cuda() + x2_batch = data_batch[0][modalities[1]].float().cuda() + + x1_aug = augment_single(x1_batch) + x2_aug = augment_single(x2_batch) + + loss = model(x1_batch, x2_batch, x1_aug, x2_aug) + losses.append(loss.detach().cpu().numpy()) + + for optimizer in non_CLUB_optims: + optimizer.zero_grad() + + loss.backward() + + for optimizer in non_CLUB_optims: + optimizer.step() + + for _ in range(num_club_iter): + + learning_loss = model.learning_loss(x1_batch, x2_batch, x1_aug, x2_aug) + + for optimizer in CLUB_optims: + optimizer.zero_grad() + + learning_loss.backward() + + for optimizer in CLUB_optims: + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + + return + +# MIMIC Training + +def train_supcon_mimic(model, train_loader, optimizer, num_epoch=100): + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0].float().cuda() + x2_batch = data_batch[1].float().cuda() + y_batch = data_batch[2].unsqueeze(0).T.float().cuda() + + + loss = model(x1_batch, x2_batch, y_batch) + + optimizer.zero_grad() + loss.backward() + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + return + +def train_sup_mimic(model, train_loader, num_epoch=50, num_club_iter=1): + non_CLUB_optims, CLUB_optims = model.get_optims() + losses = [] + + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0].float().cuda() + x2_batch = data_batch[1].float().cuda() + y_batch = data_batch[2].unsqueeze(0).T.float().cuda() + + loss = model(x1_batch, x2_batch, y_batch) + losses.append(loss.detach().cpu().numpy()) + + for optimizer in non_CLUB_optims: + optimizer.zero_grad() + + loss.backward() + + for optimizer in non_CLUB_optims: + optimizer.step() + + for _ in range(num_club_iter): + + learning_loss = model.learning_loss(x1_batch, x2_batch, y_batch) + + for optimizer in CLUB_optims: + optimizer.zero_grad() + + learning_loss.backward() + + for optimizer in CLUB_optims: + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + + return + +def train_ssl_mimic(model, train_loader, num_epoch=50, num_club_iter=1): + non_CLUB_optims, CLUB_optims = model.get_optims() + losses = [] + + for _iter in range(num_epoch): + for i_batch, data_batch in enumerate(train_loader): + + x1_batch = data_batch[0].float().cuda() + x2_batch = data_batch[1].float().cuda() + x1_aug = augment_mimic(x1_batch) + x2_aug = augment_mimic(x2_batch) + + loss = model(x1_batch, x2_batch, x1_aug, x2_aug) + losses.append(loss.detach().cpu().numpy()) + + for optimizer in non_CLUB_optims: + optimizer.zero_grad() + + loss.backward() + + for optimizer in non_CLUB_optims: + optimizer.step() + + for _ in range(num_club_iter): + + learning_loss = model.learning_loss(x1_batch, x2_batch, x1_aug, x2_aug) + + for optimizer in CLUB_optims: + optimizer.zero_grad() + + learning_loss.backward() + + for optimizer in CLUB_optims: + optimizer.step() + + if i_batch%100 == 0: + print('iter: ', _iter, ' i_batch: ', i_batch, ' loss: ', loss.item()) + + return diff --git a/src/e2_tts_pytorch/torch_tools.py b/src/e2_tts_pytorch/torch_tools.py new file mode 100644 index 0000000000000000000000000000000000000000..b871a59168346b2f14a37bd1771ac6b002c240a8 --- /dev/null +++ b/src/e2_tts_pytorch/torch_tools.py @@ -0,0 +1,522 @@ +import torch +import torchaudio +import random +import itertools +import numpy as np +####from tools.mix import mix +from e2_tts_pytorch.mix import mix + +import time +import traceback +import os +#from datasets import load_dataset +####from transformers import ClapModel, ClapProcessor + + +####clap = ClapModel.from_pretrained("/ckptstorage/zhanghaomin/models/EnCLAP/larger_clap_general/").to("cpu") +####clap.eval() +####for param in clap.parameters(): +#### param.requires_grad = False +####clap_processor = ClapProcessor.from_pretrained("/ckptstorage/zhanghaomin/models/EnCLAP/larger_clap_general/") + + +#from msclap import CLAP +#clap_model = CLAP("/ckptstorage/zhanghaomin/models/msclap/clapcap_weights_2023.pth", version="clapcap", use_cuda=False) +#clap_model.clapcap.eval() +#for param in clap_model.clapcap.parameters(): +# param.requires_grad = False + + +#new_freq = 16000 +#hop_size = 160 +new_freq = 24000 +#hop_size = 256 +hop_size = 320 +#total_length = 1024 +#MIN_TARGET_LEN = 281 +#MAX_TARGET_LEN = 937 +total_length = 750 +MIN_TARGET_LEN = 750 +MAX_TARGET_LEN = 750 +#LEN_D = 1 +LEN_D = 0 + +clap_freq = 48000 +msclap_freq = 44100 +max_len_in_seconds = 10 +max_len_in_seconds_msclap = 7 +#period_length = 30 +period_length = 7 +cut_length = 10 + + +def normalize_wav(waveform): + waveform = waveform - torch.mean(waveform) + waveform = waveform / (torch.max(torch.abs(waveform[0, :])) + 1e-8) + return waveform * 0.5 + + +def _pad_spec(fbank, target_length=total_length): + batch, n_frames, channels = fbank.shape + p = target_length - n_frames + if p > 0: + pad = torch.zeros(batch, p, channels).to(fbank.device) + fbank = torch.cat([fbank, pad], 1) + elif p < 0: + fbank = fbank[:, :target_length, :] + + if channels % 2 != 0: + fbank = fbank[:, :, :-1] + + return fbank + + +SCORE_THRESHOLD_VAL = 0.15 +#SCORE_THRESHOLD_TRAIN = { +# "/zhanghaomin/datas/audiocaps": -np.inf, +# "/radiostorage/WavCaps": -np.inf, +# "/radiostorage/AudioGroup": -np.inf, +# "/ckptstorage/zhanghaomin/audioset": -np.inf, +# "/ckptstorage/zhanghaomin/BBCSoundEffects": -np.inf, +# "/ckptstorage/zhanghaomin/CLAP_freesound": -np.inf, +#} +SOUNDEFFECT = { + "/zhanghaomin/datas/audiocaps": False, + "/radiostorage/WavCaps": False, + "/radiostorage/AudioGroup": True, + "/ckptstorage/zhanghaomin/audioset": False, + "/ckptstorage/zhanghaomin/BBCSoundEffects": False, + "/ckptstorage/zhanghaomin/CLAP_freesound": False, + "/zhanghaomin/datas/musiccap": False, + "/ckptstorage/zhanghaomin/TangoPromptBank": False, + "/ckptstorage/zhanghaomin/audiosetsl": False, + "/ckptstorage/zhanghaomin/giantsoundeffects": True, +} +FILTER_NUM = { + "/zhanghaomin/datas/audiocaps": [0,0], + "/radiostorage/WavCaps": [0,0], + "/radiostorage/AudioGroup": [0,0], + "/ckptstorage/zhanghaomin/audioset": [0,0], + "/ckptstorage/zhanghaomin/BBCSoundEffects": [0,0], + "/ckptstorage/zhanghaomin/CLAP_freesound": [0,0], + "/zhanghaomin/datas/musiccap": [0,0], + "/ckptstorage/zhanghaomin/TangoPromptBank": [0,0], + "/ckptstorage/zhanghaomin/audiosetsl": [0,0], + "/ckptstorage/zhanghaomin/giantsoundeffects": [0,0], +} + + +TURNOFF_CLAP_FILTER_GLOBAL = False + + +def pad_wav(waveform, segment_length, text, prefix, val): + waveform_length = waveform.shape[1] + + if segment_length is None or waveform_length == segment_length: + return waveform, text + elif waveform_length > segment_length: + return waveform[:, :segment_length], text + else: + if val: + if (not SOUNDEFFECT[prefix]) or (waveform_length > segment_length / 3.0): + pad_wav = torch.zeros((waveform.shape[0], segment_length-waveform_length)).to(waveform.device) + waveform = torch.cat([waveform, pad_wav], 1) + return waveform, text + else: + min_repeats = max(int(segment_length / 3.0 // waveform_length), 2) + max_repeats = segment_length // waveform_length + if val: + repeats = (min_repeats + max_repeats) // 2 + else: + repeats = random.randint(min_repeats, max_repeats) + waveform = torch.cat([waveform]*repeats, 1) + if waveform.shape[1] < segment_length: + pad_wav = torch.zeros((waveform.shape[0], segment_length-waveform.shape[1])).to(waveform.device) + waveform = torch.cat([waveform, pad_wav], 1) + #if text[-1] in [",", "."]: + # text = text[:-1] + " repeat " + str(repeats) + " times" + text[-1] + #else: + # text = text + " repeat " + str(repeats) + " times" + return waveform, text + else: + repeats = segment_length // waveform_length + 1 + waveform = torch.cat([waveform]*repeats, 1) + assert(waveform.shape[0] == 1 and waveform.shape[1] >= segment_length) + return waveform[:, :segment_length], text + + +def msclap_generate(waveform, freq): + waveform_msclap = torchaudio.functional.resample(waveform, orig_freq=freq, new_freq=msclap_freq)[0] + start = 0 + end = waveform_msclap.shape[0] + if waveform_msclap.shape[0] > msclap_freq*max_len_in_seconds_msclap: + start = random.randint(waveform_msclap.shape[0]-msclap_freq*max_len_in_seconds_msclap) + end = start+msclap_freq*max_len_in_seconds_msclap + waveform_msclap = waveform_msclap[start: end] + if waveform_msclap.shape[0] < msclap_freq*max_len_in_seconds_msclap: + waveform_msclap = torch.cat([waveform_msclap, torch.zeros(msclap_freq*max_len_in_seconds_msclap-waveform_msclap.shape[0])]) + waveform_msclap = waveform_msclap.reshape(1,1,msclap_freq*max_len_in_seconds_msclap) + caption = clap_model.generate_caption(waveform_msclap)[0] + return caption, (start/float(msclap_freq), end/float(msclap_freq)) + + +def do_clap_filter(waveform, text, filename, val, if_clap_filter, main_process, SCORE_THRESHOLD_TRAIN): + global FILTER_NUM + + if isinstance(filename, tuple): + filename = filename[0] + if filename.startswith("/radiostorage/"): + prefix = "/".join(filename.split("/")[:3]) + else: + prefix = "/".join(filename.split("/")[:4]) + soundeffect = SOUNDEFFECT[prefix] + + if not if_clap_filter: + return np.inf, False, (None, None, soundeffect) + + score_threshold = SCORE_THRESHOLD_VAL if val else SCORE_THRESHOLD_TRAIN + if not if_clap_filter or TURNOFF_CLAP_FILTER_GLOBAL: + score_threshold = -np.inf + else: + if not val: + score_threshold = SCORE_THRESHOLD_TRAIN[prefix] + #print(prefix, score_threshold) + + resampled = torchaudio.functional.resample(waveform.reshape(1, -1), orig_freq=new_freq, new_freq=clap_freq)[0].numpy() + resampled = resampled[:clap_freq*max_len_in_seconds] + + inputs = clap_processor(text=[text], audios=[resampled], return_tensors="pt", padding=True, sampling_rate=clap_freq) + inputs = {k: v.to("cpu") for k, v in inputs.items()} + with torch.no_grad(): + outputs = clap(**inputs) + score = torch.dot(outputs.text_embeds[0,:], outputs.audio_embeds[0,:]).item() + #print("do_clap_filter:", filename, text, resampled.shape, outputs.logits_per_audio, outputs.logits_per_text, score, score < score_threshold) + if torch.any(torch.isnan(outputs.text_embeds)) or torch.any(torch.isnan(outputs.audio_embeds)): + return -np.inf, True, None + + if main_process and if_clap_filter and not TURNOFF_CLAP_FILTER_GLOBAL: + FILTER_NUM[prefix][0] += 1 + if score < score_threshold: + FILTER_NUM[prefix][1] += 1 + if FILTER_NUM[prefix][0] % 10000 == 0 or FILTER_NUM[prefix][0] == 1000: + print(prefix, FILTER_NUM[prefix][0], FILTER_NUM[prefix][1]/float(FILTER_NUM[prefix][0])) + return score, score < score_threshold, (outputs.text_embeds, outputs.audio_embeds, soundeffect) + + +def read_wav_file(filename, text, segment_length, val, if_clap_filter, main_process, SCORE_THRESHOLD_TRAIN, nch): + try: + if isinstance(filename, tuple): + if filename[0].startswith("/radiostorage/"): + prefix = "/".join(filename[0].split("/")[:3]) + else: + prefix = "/".join(filename[0].split("/")[:4]) + + #print(filename, text, segment_length, val) + wav, utt, period = filename + + #size = os.path.getsize(wav) + #if size > 200000000: + # print("Exception too large file:", filename, text, size) + # return None, None, None + + base, name = wav.rsplit("/", 1) + temp_base = "/ailab-train/speech/zhanghaomin/wav_temp/" + base.replace("/", "__") + "/" + temp_filename = temp_base + name + if os.path.exists(temp_filename): + waveform, sr = torchaudio.load(temp_filename) + else: + #start = time.time() + waveform0, sr = torchaudio.load(wav) + #end = time.time() + #print("load", end-start, wav) + waveform = torchaudio.functional.resample(waveform0, orig_freq=sr, new_freq=new_freq)[0:nch, :] + #if nch >= 2: + # waveform = torch.cat([waveform.mean(axis=0, keepdims=True), waveform], 0) + #print("resample", time.time()-end, wav) + waveform = waveform[:, new_freq*period*period_length: new_freq*(period+1)*period_length] # 0~period_length s + waveform = waveform[:, :new_freq*cut_length] + os.makedirs(temp_base, exist_ok=True) + torchaudio.save(temp_filename, waveform, new_freq) + + start = 0 + if waveform.shape[1] > new_freq*max_len_in_seconds: + if not val: + start = random.randint(0, waveform.shape[1]-new_freq*max_len_in_seconds) + waveform = waveform[:, start: start+new_freq*max_len_in_seconds] + + if val: + text_index = 0 + else: + #text_index = random.choice([0,1,2]) + #text_index = random.choice([0,1]) + text_index = 0 + text = text[text_index] + #text, timestamps = msclap_generate(waveform0[:, sr*period*period_length: sr*(period+1)*period_length], sr) + #waveform = waveform[int(timestamps[0]*new_freq): int(timestamps[1]*new_freq)] + #print(waveform.shape, text) + + score, filtered, embeddings = do_clap_filter(waveform[0, :], text, filename, val, if_clap_filter, main_process, SCORE_THRESHOLD_TRAIN) + if filtered: + print("Exception below threshold:", filename, text, score) + return None, None, None + else: + if filename.startswith("/radiostorage/"): + prefix = "/".join(filename.split("/")[:3]) + else: + prefix = "/".join(filename.split("/")[:4]) + + #size = os.path.getsize(filename) + #if size > 200000000: + # print("Exception too large file:", filename, text, size) + # return None, None, None + + base, name = filename.rsplit("/", 1) + temp_base = "/ailab-train/speech/zhanghaomin/wav_temp/" + base.replace("/", "__") + "/" + temp_filename = temp_base + name + if os.path.exists(temp_filename): + #print("wav exist", temp_filename) + waveform, sr = torchaudio.load(temp_filename) + else: + #print("wav not exist", filename) + #start = time.time() + waveform, sr = torchaudio.load(filename) # Faster!!! + #end = time.time() + #print("load", end-start, filename) + waveform = torchaudio.functional.resample(waveform, orig_freq=sr, new_freq=new_freq)[0:nch, :] + #if nch >= 2: + # waveform = torch.cat([waveform.mean(axis=0, keepdims=True), waveform], 0) + #print("resample", time.time()-end, filename) + waveform = waveform[:, :new_freq*cut_length] + os.makedirs(temp_base, exist_ok=True) + torchaudio.save(temp_filename, waveform, new_freq) + + start = 0 + if waveform.shape[1] > new_freq*max_len_in_seconds: + if not val: + start = random.randint(0, waveform.shape[1]-new_freq*max_len_in_seconds) + waveform = waveform[:, start: start+new_freq*max_len_in_seconds] + + if isinstance(text, tuple): + if val: + text_index = 0 + else: + text_index = random.choice(list(range(len(text)))) + text = text[text_index] + + score, filtered, embeddings = do_clap_filter(waveform[0, :], text, filename, val, if_clap_filter, main_process, SCORE_THRESHOLD_TRAIN) + if filtered: + print("Exception below threshold:", filename, text, score) + return None, None, None + except Exception as e: + print("Exception load:", filename, text) + traceback.print_exc() + return None, None, None + #try: + # waveform = torchaudio.functional.resample(waveform, orig_freq=sr, new_freq=new_freq)[0] + #except Exception as e: + # print("Exception resample:", waveform.shape, sr, filename, text) + # return None, None, None + if (waveform.shape[1] / float(new_freq) < 0.2) and (not SOUNDEFFECT[prefix]): + print("Exception too short wav:", waveform.shape, sr, new_freq, filename, text) + traceback.print_exc() + return None, None, None + try: + waveform = normalize_wav(waveform) + except Exception as e: + print ("Exception normalizing:", waveform.shape, sr, new_freq, filename, text) + traceback.print_exc() + #waveform = torch.ones(sample_freq*max_len_in_seconds) + return None, None, None + waveform, text = pad_wav(waveform, segment_length, text, prefix, val) + waveform = waveform / (torch.max(torch.abs(waveform[0, :])) + 1e-8) + waveform = 0.5 * waveform + #print(text) + return waveform, text, embeddings + + +def get_mel_from_wav(audio, _stft): + audio = torch.nan_to_num(torch.clip(audio, -1, 1)) + audio = torch.autograd.Variable(audio, requires_grad=False) + melspec, log_magnitudes_stft, energy = _stft.mel_spectrogram(audio) + return melspec, log_magnitudes_stft, energy + + +def argmax_lst(lst): + return max(range(len(lst)), key=lst.__getitem__) + + +def select_segment(waveform, target_length): + ch, wav_length = waveform.shape + assert(ch == 1 and wav_length == total_length * hop_size) + energy = [] + for i in range(total_length): + energy.append(torch.mean(torch.abs(waveform[:, i*hop_size: (i+1)*hop_size]))) + #sum_energy = [] + #for i in range(total_length-target_length+1): + # sum_energy.append(sum(energy[i: i+target_length])) + sum_energy = [sum(energy[:target_length])] + for i in range(1, total_length-target_length+1): + sum_energy.append(sum_energy[-1]-energy[i-1]+energy[i+target_length-1]) + + start = argmax_lst(sum_energy) + segment = waveform[:, start*hop_size: (start+target_length)*hop_size] + ch, wav_length = segment.shape + assert(ch == 1 and wav_length == target_length * hop_size) + return segment + + +def wav_to_fbank(paths, texts, num, target_length=total_length, fn_STFT=None, val=False, if_clap_filter=True, main_process=True, SCORE_THRESHOLD_TRAIN="", nch=1): + assert fn_STFT is not None + + #raw_results = [read_wav_file(path, text, target_length * hop_size, val, if_clap_filter, main_process, SCORE_THRESHOLD_TRAIN, nch) for path, text in zip(paths, texts)] + results = [] + #for result in raw_results: + # if result[0] is not None: + # results.append(result) + for path, text in zip(paths, texts): + result = read_wav_file(path, text, target_length * hop_size, val, if_clap_filter, main_process, SCORE_THRESHOLD_TRAIN, nch) + if result[0] is not None: + results.append(result) + if num > 0 and len(results) >= num: + break + if len(results) == 0: + ####return None, None, None, None, None + return None, None, None, None, None, None + + ####waveform = torch.cat([result[0] for result in results], 0) + texts = [result[1] for result in results] + embeddings = [result[2] for result in results] + + ####fbank, log_magnitudes_stft, energy = get_mel_from_wav(waveform, fn_STFT) + ####fbank = fbank.transpose(1, 2) + ####log_magnitudes_stft = log_magnitudes_stft.transpose(1, 2) + + ####fbank, log_magnitudes_stft = _pad_spec(fbank, target_length), _pad_spec( + #### log_magnitudes_stft, target_length + ####) + + ####return fbank, texts, embeddings, log_magnitudes_stft, waveform + + ####fbank = fn_STFT(waveform) + fbanks = [] + fbank_lens = [] + for result in results: + if not val: + length = random.randint(MIN_TARGET_LEN, MAX_TARGET_LEN) + else: + length = (MIN_TARGET_LEN + MAX_TARGET_LEN) // 2 + fbank_lens.append(length+LEN_D) + if not val: + waveform = select_segment(result[0], length) + else: + waveform = result[0][:, :length*hop_size] + fbank = fn_STFT(waveform).transpose(-1,-2) + #print("stft", waveform.shape, fbank.shape) + fbanks.append(fbank) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + fbank = torch.cat(fbanks, 0) + fbank_lens = torch.Tensor(fbank_lens).to(torch.int32) + #print("fbank", fbank.shape, fbank_lens) + return fbank, texts, None, None, None, fbank_lens + + +def uncapitalize(s): + if s: + return s[:1].lower() + s[1:] + else: + return "" + + +def mix_wavs_and_captions(path1, path2, caption1, caption2, target_length=total_length, main_process=True, SCORE_THRESHOLD_TRAIN="", nch=1): + sound1, caption1, embeddings1 = read_wav_file(path1, caption1, target_length * hop_size, False, False, main_process, SCORE_THRESHOLD_TRAIN, nch)#[0].numpy() + sound2, caption2, embeddings2 = read_wav_file(path2, caption2, target_length * hop_size, False, False, main_process, SCORE_THRESHOLD_TRAIN, nch)#[0].numpy() + if sound1 is not None and sound2 is not None: + mixed_sound = mix(sound1.numpy(), sound2.numpy(), 0.5, new_freq) + mixed_sound = mixed_sound.astype(np.float32) + mixed_caption = "{} and {}".format(caption1, uncapitalize(caption2)) + + #resampled = torchaudio.functional.resample(torch.from_numpy(mixed_sound).reshape(1, -1), orig_freq=new_freq, new_freq=clap_freq)[0].numpy() + #resampled = resampled[:clap_freq*max_len_in_seconds] + + #inputs = clap_processor(text=[mixed_caption], audios=[resampled], return_tensors="pt", padding=True, sampling_rate=clap_freq) + #inputs = {k: v.to("cpu") for k, v in inputs.items()} + #with torch.no_grad(): + # outputs = clap(**inputs) + if not (embeddings1[2] or embeddings2[2]): + filename = path1 + else: + filename = "/radiostorage/AudioGroup" + score, filtered, embeddings = do_clap_filter(torch.from_numpy(mixed_sound)[0, :], mixed_caption, filename, False, False, main_process, SCORE_THRESHOLD_TRAIN) + #print(score, filtered, embeddings if embeddings is None else embeddings[2], path1, path2, filename) + if filtered: + #print("Exception below threshold:", path1, path2, caption1, caption2, filename, score) + return None, None, None + + return mixed_sound, mixed_caption, embeddings + else: + return None, None, None + + +def augment(paths, texts, num_items=4, target_length=total_length, main_process=True, SCORE_THRESHOLD_TRAIN="", nch=1): + mixed_sounds, mixed_captions, mixed_embeddings = [], [], [] + combinations = list(itertools.combinations(list(range(len(texts))), 2)) + random.shuffle(combinations) + if len(combinations) < num_items: + selected_combinations = combinations + else: + selected_combinations = combinations[:num_items] + + for (i, j) in selected_combinations: + new_sound, new_caption, new_embeddings = mix_wavs_and_captions(paths[i], paths[j], texts[i], texts[j], target_length, main_process, SCORE_THRESHOLD_TRAIN, nch) + if new_sound is not None: + mixed_sounds.append(new_sound) + mixed_captions.append(new_caption) + mixed_embeddings.append(new_embeddings) + + if len(mixed_sounds) == 0: + return None, None, None + + waveform = torch.tensor(np.concatenate(mixed_sounds, 0)) + waveform = waveform / (torch.max(torch.abs(waveform[0, :])) + 1e-8) + waveform = 0.5 * waveform + + return waveform, mixed_captions, mixed_embeddings + + +def augment_wav_to_fbank(paths, texts, num_items=4, target_length=total_length, fn_STFT=None, main_process=True, SCORE_THRESHOLD_TRAIN="", nch=1): + assert fn_STFT is not None + + waveform, captions, embeddings = augment(paths, texts, num_items, target_length, main_process, SCORE_THRESHOLD_TRAIN, nch) + if waveform is None: + ####return None, None, None, None, None + return None, None, None, None, None, None + + ####fbank, log_magnitudes_stft, energy = get_mel_from_wav(waveform, fn_STFT) + ####fbank = fbank.transpose(1, 2) + ####log_magnitudes_stft = log_magnitudes_stft.transpose(1, 2) + #### + ####fbank, log_magnitudes_stft = _pad_spec(fbank, target_length), _pad_spec( + #### log_magnitudes_stft, target_length + ####) + #### + ####return fbank, log_magnitudes_stft, waveform, captions, embeddings + + ####fbank = fn_STFT(waveform) + fbanks = [] + fbank_lens = [] + for i in range(waveform.shape[0]): + length = random.randint(MIN_TARGET_LEN, MAX_TARGET_LEN) + fbank_lens.append(length+LEN_D) + ####fbank = fn_STFT(waveform[i:i+1, :length*hop_size]).transpose(-1,-2) + fbank = fn_STFT(select_segment(waveform[i:i+1, :], length)).transpose(-1,-2) + fbanks.append(fbank) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + fbank = torch.cat(fbanks, 0) + fbank_lens = torch.Tensor(fbank_lens).to(torch.int32) + return fbank, None, None, captions, None, fbank_lens \ No newline at end of file diff --git a/src/e2_tts_pytorch/trainer_multigpus_alldatas.py b/src/e2_tts_pytorch/trainer_multigpus_alldatas.py new file mode 100644 index 0000000000000000000000000000000000000000..a4a1c0acb7a948ab2b795c50abdefd0368d3d4b8 --- /dev/null +++ b/src/e2_tts_pytorch/trainer_multigpus_alldatas.py @@ -0,0 +1,1251 @@ +from __future__ import annotations + +import os +from tqdm import tqdm +import matplotlib +matplotlib.use("Agg") +import matplotlib.pylab as plt + +import torch +import torch.nn.functional as F +from torch.utils.data import DataLoader, Dataset +from torch.utils.tensorboard import SummaryWriter +from torch.optim.lr_scheduler import LinearLR, SequentialLR + +import torchaudio + +from einops import rearrange + +from accelerate import Accelerator +from accelerate.utils import DistributedDataParallelKwargs + +from ema_pytorch import EMA + +from loguru import logger + +from e2_tts_pytorch.e2_tts_crossatt import ( + E2TTS, + DurationPredictor, + MelSpec +) + +import traceback +import numpy as np +from moviepy.editor import AudioFileClip, VideoFileClip + +def exists(v): + return v is not None + +def default(v, d): + return v if exists(v) else d + +def to_numpy(t): + return t.detach().cpu().numpy() + +# plot spectrogram + +def plot_spectrogram(spectrogram): + spectrogram = to_numpy(spectrogram) + fig, ax = plt.subplots(figsize=(10, 4)) + im = ax.imshow(spectrogram.T, aspect="auto", origin="lower", interpolation="none") + plt.colorbar(im, ax=ax) + plt.xlabel("Frames") + plt.ylabel("Channels") + plt.tight_layout() + + fig.canvas.draw() + plt.close() + return fig + +# collation + +def collate_fn(batch): + mel_specs = [item['mel_spec'].squeeze(0) for item in batch] + mel_lengths = torch.LongTensor([spec.shape[-1] for spec in mel_specs]) + max_mel_length = mel_lengths.amax() + + padded_mel_specs = [] + for spec in mel_specs: + padding = (0, max_mel_length - spec.size(-1)) + padded_spec = F.pad(spec, padding, value = 0) + padded_mel_specs.append(padded_spec) + + mel_specs = torch.stack(padded_mel_specs) + + text = [item['text'] for item in batch] + text_lengths = torch.LongTensor([len(item) for item in text]) + + return dict( + mel = mel_specs, + mel_lengths = mel_lengths, + text = text, + text_lengths = text_lengths, + ) + +# dataset + +class HFDataset(Dataset): + def __init__( + self, + hf_dataset: Dataset, + target_sample_rate = 24_000, + hop_length = 256 + ): + self.data = hf_dataset + self.target_sample_rate = target_sample_rate + self.hop_length = hop_length + self.mel_spectrogram = MelSpec(sampling_rate=target_sample_rate) + + def __len__(self): + return len(self.data) + + def __getitem__(self, index): + row = self.data[index] + audio = row['audio']['array'] + + #logger.info(f"Audio shape: {audio.shape}") + + sample_rate = row['audio']['sampling_rate'] + duration = audio.shape[-1] / sample_rate + + if duration > 20 or duration < 0.3: + logger.warning(f"Skipping due to duration out of bound: {duration}") + return self.__getitem__((index + 1) % len(self.data)) + + audio_tensor = torch.from_numpy(audio).float() + + if sample_rate != self.target_sample_rate: + resampler = torchaudio.transforms.Resample(sample_rate, self.target_sample_rate) + audio_tensor = resampler(audio_tensor) + + audio_tensor = rearrange(audio_tensor, 't -> 1 t') + + mel_spec = self.mel_spectrogram(audio_tensor) + + mel_spec = rearrange(mel_spec, '1 d t -> d t') + + text = row['transcript'] + + return dict( + mel_spec = mel_spec, + text = text, + ) + +# trainer + +class E2Trainer: + def __init__( + self, + model: E2TTS, + optimizer, + num_warmup_steps=20000, + grad_accumulation_steps=1, + duration_predictor: DurationPredictor | None = None, + checkpoint_path = None, + log_file = "logs.txt", + max_grad_norm = 1.0, + sample_rate = 22050, + tensorboard_log_dir = 'runs/e2_tts_experiment', + accelerate_kwargs: dict = dict(), + ema_kwargs: dict = dict(), + use_switch_ema = False, + if_text = False, + if_prompt = False + ): + logger.add(log_file) + + ddp_kwargs = DistributedDataParallelKwargs(find_unused_parameters = True) + + self.accelerator = Accelerator( + log_with = "all", + kwargs_handlers = [ddp_kwargs], + gradient_accumulation_steps = grad_accumulation_steps, + **accelerate_kwargs + ) + self.accelerator.wait_for_everyone() + + self.target_sample_rate = sample_rate + + self.model = model + + self.need_velocity_consistent_loss = model.velocity_consistency_weight > 0. + + #self.ema_model = EMA( + # model, + # include_online_model = False, + # **ema_kwargs + #) + + self.use_switch_ema = use_switch_ema + + self.duration_predictor = duration_predictor + self.optimizer = optimizer + self.num_warmup_steps = num_warmup_steps + self.checkpoint_path = default(checkpoint_path, 'model.pth') + self.mel_spectrogram = MelSpec(sampling_rate=self.target_sample_rate) + + self.model, self.optimizer = self.accelerator.prepare( + self.model, self.optimizer + ) + #self.ema_model = self.accelerator.prepare(self.ema_model) + self.max_grad_norm = max_grad_norm + + self.writer = SummaryWriter(log_dir=tensorboard_log_dir) + self.tensorboard_log_dir = tensorboard_log_dir + self.if_text = if_text + self.if_prompt = if_prompt + + self.device_id = self.accelerator.device.index + self.num_processes = self.accelerator.num_processes + + @property + def is_main(self): + return self.accelerator.is_main_process + + def save_checkpoint(self, step, finetune=False): + self.accelerator.wait_for_everyone() + if self.is_main: + checkpoint = dict( + model_state_dict = self.accelerator.unwrap_model(self.model).state_dict(), + #optimizer_state_dict = self.accelerator.unwrap_model(self.optimizer).state_dict(), + #ema_model_state_dict = self.ema_model.state_dict(), + #scheduler_state_dict = self.scheduler.state_dict(), + #step = step, + ) + + self.accelerator.save(checkpoint, self.tensorboard_log_dir + "/" + str(step) + ".pt") + + def load_checkpoint(self): + if not exists(self.checkpoint_path) or not os.path.exists(self.checkpoint_path): + return 0 + + checkpoint = torch.load(self.checkpoint_path, map_location='cpu') + for key in list(checkpoint['model_state_dict'].keys()): + #if key.startswith('mel_spec.'): + # del checkpoint['model_state_dict'][key] + if key.startswith('transformer.text_registers'): + if checkpoint['model_state_dict'][key].shape[1] != self.accelerator.unwrap_model(self.model).transformer.text_registers.shape[1]: + print('miss match: transformer.text_registers', checkpoint['model_state_dict'][key].shape, self.accelerator.unwrap_model(self.model).transformer.text_registers.shape) + del checkpoint['model_state_dict'][key] + self.accelerator.unwrap_model(self.model).load_state_dict(checkpoint['model_state_dict'], strict=False) + #self.accelerator.unwrap_model(self.optimizer).load_state_dict(checkpoint['optimizer_state_dict']) + + #if self.is_main: + # self.ema_model.load_state_dict(checkpoint['ema_model_state_dict']) + + #if self.scheduler: + # self.scheduler.load_state_dict(checkpoint['scheduler_state_dict']) + #return checkpoint['step'] + return 0 + + def evaluate(self, eval_dataloader, epoch, epochs, global_step): + if eval_dataloader is None: + return + + total_val_loss, N, total_lossmore1, total_lossmore2 = 0, 0, 0, 0 + self.model.eval() + eval_progress_bar = tqdm(eval_dataloader, desc=f"Epoch {epoch}/{epochs}", unit="step", disable=not self.accelerator.is_local_main_process) + for step, batch in enumerate(eval_dataloader): + with self.accelerator.accumulate(self.model) and torch.no_grad(): + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt = batch + + val_loss, cond, pred, pred_data, lossmore = self.model( + mel_spec, + text=(text if self.if_text else None), + times=0.5, + lens=mel_lengths, + velocity_consistency_model=None, + prompt=(text if self.if_prompt else None), + video_drop_prompt=video_drop_prompt, + audio_drop_prompt=audio_drop_prompt, + val=True, + video_paths=video_paths + ) + a = torch.tensor(val_loss.item()*len(text), dtype=torch.float32).reshape(1).to(val_loss.device) + b = torch.tensor(len(text), dtype=torch.int32).reshape(1).to(val_loss.device) + c = torch.tensor(lossmore[0].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[0].device) + d = torch.tensor(lossmore[1].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[1].device) + val_loss_gather, N_gather, lossmore_gather1, lossmore_gather2 = self.accelerator.gather_for_metrics((a, b, c, d)) + for i in range(val_loss_gather.shape[0]): + total_val_loss += val_loss_gather[i].item() + N += N_gather[i].item() + total_lossmore1 += lossmore_gather1[i].item() + total_lossmore2 += lossmore_gather2[i].item() + eval_progress_bar.update(1) + + if self.accelerator.is_local_main_process: + total_val_loss = round(total_val_loss/float(N), 4) + total_lossmore1 = round(total_lossmore1/float(N), 4) + total_lossmore2 = round(total_lossmore2/float(N), 4) + result_string = "Epoch: {}, GlobalStep: {}, ValLoss: {}, N: {}, Lossmore1: {}, Lossmore2: {} (average loss)\n".format(epoch, global_step, total_val_loss, N, total_lossmore1, total_lossmore2) + logger.info(result_string) + + torch.cuda.empty_cache() + + def train(self, datasets, epochs, batch_size, num_workers=12, save_step=1000): + + params_d = {} + trainable_d = {} + for n, p in self.model.named_parameters(): + key = ".".join(n.split(".")[:2]) + if key not in params_d: + params_d[key] = [0, 0] + trainable_d[key] = p.requires_grad + if p.requires_grad: + params_d[key][0] += p.numel() + else: + params_d[key][1] += p.numel() + if key != "module.transformer": + assert(trainable_d[key] == p.requires_grad) + print(params_d) + print(trainable_d) + num_trainable_parameters = sum(p.numel() for p in self.model.parameters() if p.requires_grad) + print("Num trainable parameters: {}".format(num_trainable_parameters)) + + train_dataset = datasets[0] + eval_datasets = datasets[1:] + #train_dataloader = DataLoader(train_dataset, batch_size=batch_size, collate_fn=collate_fn, shuffle=True, num_workers=num_workers, pin_memory=True) + train_dataloader = DataLoader(train_dataset, shuffle=True, batch_size=batch_size*train_dataset.multi, collate_fn=train_dataset.collate_fn, num_workers=num_workers, drop_last=True, pin_memory=True) + eval_dataloaders = [DataLoader(eval_dataset, shuffle=False, batch_size=16, collate_fn=eval_dataset.collate_fn, num_workers=num_workers, drop_last=False, pin_memory=True) if eval_dataset is not None else None for eval_dataset in eval_datasets] + + total_steps = len(train_dataloader) * epochs + decay_steps = total_steps - self.num_warmup_steps + warmup_scheduler = LinearLR(self.optimizer, start_factor=1e-8, end_factor=1.0, total_iters=self.num_warmup_steps) + decay_scheduler = LinearLR(self.optimizer, start_factor=1.0, end_factor=1e-8, total_iters=decay_steps) + self.scheduler = SequentialLR(self.optimizer, + schedulers=[warmup_scheduler, decay_scheduler], + milestones=[self.num_warmup_steps]) + train_dataloader, self.scheduler = self.accelerator.prepare(train_dataloader, self.scheduler) + eval_dataloaders = [self.accelerator.prepare(eval_dataloader) for eval_dataloader in eval_dataloaders if eval_dataloader is not None] + start_step = self.load_checkpoint() + global_step = start_step + + for epoch in range(epochs): + + if epoch == 0: + [self.evaluate(eval_dataloader, 1, epochs, 0) for eval_dataloader in eval_dataloaders] + + self.model.train() + progress_bar = tqdm(train_dataloader, desc=f"Epoch {epoch+1}/{epochs}", unit="step", disable=not self.accelerator.is_local_main_process) + epoch_loss = 0.0 + + for batch in progress_bar: + with self.accelerator.accumulate(self.model): + #text_inputs = batch['text'] + #mel_spec = rearrange(batch['mel'], 'b d n -> b n d') + #mel_lengths = batch["mel_lengths"] + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt = batch + #print("batchsize", len(text)) + #print("batch", text, mel_spec.shape, video_paths, mel_lengths) + + if exists(self.duration_predictor): + dur_loss = self.duration_predictor(mel_spec, lens=batch.get('durations')) + self.writer.add_scalar('duration loss', dur_loss.detach().cpu().item(), global_step) + + velocity_consistency_model = None + #if self.need_velocity_consistent_loss and self.ema_model.initted: + # velocity_consistency_model = self.accelerator.unwrap_model(self.ema_model).ema_model + + loss, cond, pred, pred_data, lossmore = self.model( + mel_spec, + text=(text if self.if_text else None), + lens=mel_lengths, + velocity_consistency_model=velocity_consistency_model, + prompt=(text if self.if_prompt else None), + video_drop_prompt=video_drop_prompt, + audio_drop_prompt=audio_drop_prompt, + video_paths=video_paths + ) + + self.accelerator.backward(loss) + + if self.max_grad_norm > 0 and self.accelerator.sync_gradients: + self.accelerator.clip_grad_norm_(self.model.parameters(), self.max_grad_norm) + + self.optimizer.step() + self.scheduler.step() + self.optimizer.zero_grad() + + #self.accelerator.unwrap_model(self.ema_model).update() + + if self.accelerator.is_local_main_process: + logger.info(f"step {global_step+1}: loss = {loss.detach().cpu().item():.4f}") + self.writer.add_scalar('loss', loss.detach().cpu().item(), global_step) + self.writer.add_scalar("lr", self.scheduler.get_last_lr()[0], global_step) + + global_step += 1 + epoch_loss += loss.detach().cpu().item() + progress_bar.set_postfix(loss=loss.detach().cpu().item()) + + if global_step % save_step == 0: + self.save_checkpoint(global_step) + self.writer.add_figure("mel/target", plot_spectrogram(mel_spec[0,:,:]), global_step) + self.writer.add_figure("mel/mask", plot_spectrogram(cond[0,:,:]), global_step) + self.writer.add_figure("mel/prediction", plot_spectrogram(pred_data[0,:,:]), global_step) + [self.evaluate(eval_dataloader, epoch+1, epochs, global_step) for eval_dataloader in eval_dataloaders] + + #if global_step % 10 == 0: + # torch.cuda.empty_cache() + + epoch_loss /= len(train_dataloader) + if self.accelerator.is_local_main_process: + logger.info(f"epoch {epoch+1}/{epochs} - average loss = {epoch_loss:.4f}") + self.writer.add_scalar('epoch average loss', epoch_loss, epoch) + + #if self.use_switch_ema: + # self.ema_model.update_model_with_ema() + + self.writer.close() + + +import json +import random +import pandas as pd +from e2_tts_pytorch import torch_tools + +DURATION = torch_tools.total_length +#DURATION = 3000 +#beta = 1.5960 +#theta = 0.3259 +cand = 99999999 + +class Text2AudioDataset(Dataset): + def __init__(self, dataset, part, prefix, text_column, audio_column, num_examples=-1, samples=-1, stft=None, augment=-1, main_process=True, SCORE_THRESHOLD_TRAIN="", train_file="", theta=0.0, vggsound=0, video_drop_prompt=None, audio_drop_prompt=None, device_id=0, vgg_test=None, video_encoder="clip_vit", val_length=None, num_processes=8, vgg_train=None): + + #inputs = list(dataset[text_column]) + #self.inputs = [prefix + inp for inp in inputs] + #self.audios = list(dataset[audio_column]) + #self.indices = list(range(len(self.inputs))) + # + #print("audios", len(self.audios)) + #self.new_audios = [] + #for index, audio in enumerate(self.audios): + # utt, fmt = audio.split(".") + # new_audio = "/zhanghaomin/datas/audioset_sl/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/AudioSet_SL_flac/" + utt + ".flac" + # #if os.path.exists(new_audio): + # self.new_audios.append(new_audio) + #self.audios = self.new_audios + #N = len(self.audios) + #print("audios", len(self.new_audios)) + + + test_final = "/ailab-train/speech/zhanghaomin/scps/tango-master/data/test_audiocaps_subset.json" + test_utts = {} + with open(test_final, "r") as fr: + for line in fr.readlines(): + wav = json.loads(line.strip())["location"] + utt = wav.rsplit("/", 1)[-1].rsplit("_", 1)[0] + utt = "Y"+utt + assert(utt not in test_utts) + test_utts[utt] = 1 + main_process and print("test_final", len(test_utts)) + + bbc_soundeffects_utts = {} + freesound_utts = {} + + audioset_filter_labels = {"Music": 0, "Speech": 0, "Vehicle": 0, "Musical instrument": 0} + + + self.inputs = [] + self.audios = [] + self.indices = [] + N = 0 + + + audiocaps = True + if SCORE_THRESHOLD_TRAIN["/zhanghaomin/datas/audiocaps"] >= 9000.0: + audiocaps = False + + audioset_sl = True + bbc_soundeffects = True + freesound = True + soundbible = True + if SCORE_THRESHOLD_TRAIN["/radiostorage/WavCaps"] >= 9000.0: + audioset_sl = False + bbc_soundeffects = False + freesound = False + soundbible = False + + soundeffects = True + if SCORE_THRESHOLD_TRAIN["/radiostorage/AudioGroup"] >= 9000.0: + soundeffects = False + self.soundeffects = soundeffects + + audioset = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/audioset"] >= 9000.0: + audioset = False + + bbc_soundeffects2 = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/BBCSoundEffects"] >= 9000.0: + bbc_soundeffects2 = False + + freesound2 = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/CLAP_freesound"] >= 9000.0: + freesound2 = False + + musiccaps = True + if SCORE_THRESHOLD_TRAIN["/zhanghaomin/datas/musiccap"] >= 9000.0: + musiccaps = False + + tangopromptbank = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/TangoPromptBank"] >= 9000.0: + tangopromptbank = False + + audioset_sl_2ch = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/audiosetsl"] >= 9000.0: + audioset_sl_2ch = False + self.audioset_sl_2ch = audioset_sl_2ch + + boom_epic = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/giantsoundeffects"] >= 9000.0: + boom_epic = False + self.boom_epic = boom_epic + + if isinstance(part, list): + part, scp_ac, start_ac, end_ac = part + assert(part == "val_audiocaps") + else: + scp_ac = None + + if (audioset_sl and part in ["train", "train_val_audioset_sl"]) or (part == "val_audioset_sl"): + self.audioset_sl_inputs = [] + self.audioset_sl_audios = [] + self.audioset_sl_indices = [] + audioset_sl_path_train = "/zhanghaomin/codes2/tango-master/data/train_audioset_sl.json" + audioset_sl_path_val = "/zhanghaomin/codes2/tango-master/data/val_audioset_sl.json" + audioset_sl_path_train_val = "/ailab-train/speech/zhanghaomin/scps/tango-master/data/train_val_audioset_sl.json" + if part == "train": + audioset_sl_path = audioset_sl_path_train + elif part == "train_val_audioset_sl": + audioset_sl_path = audioset_sl_path_train_val + else: + audioset_sl_path = audioset_sl_path_val + FN = 0 + with open(audioset_sl_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"].rsplit(".", 1)[0] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/AudioSet_SL/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/AudioSet_SL_flac/" + utt + ".flac" + self.audioset_sl_inputs.append(caption) + self.audioset_sl_audios.append(audio) + self.audioset_sl_indices.append(N + index) + main_process and print(part, "audioset_sl", len(self.audioset_sl_audios), "filtered", FN) + self.inputs.extend(self.audioset_sl_inputs) + self.audios.extend(self.audioset_sl_audios) + self.indices.extend(self.audioset_sl_indices) + N = len(self.audios) + main_process and print(part, "audioset_sl audios", len(self.audios)) + + if (audiocaps and part in ["train", "train_val_audioset_sl"]) or (part == "val_audiocaps"): + self.audiocaps_inputs = [] + self.audiocaps_audios = [] + self.audiocaps_indices = [] + audiocaps_path_train = "/ailab-train/speech/zhanghaomin/scps/tango-master/data/audiocaps/train_audiocaps.json" + audiocaps_path_val = "/ailab-train/speech/zhanghaomin/scps/tango-master/data/audiocaps/test_audiocaps.json" + if scp_ac is not None: + audiocaps_path_val = scp_ac + if part in ["train", "train_val_audioset_sl"]: + audiocaps_path = audiocaps_path_train + else: + audiocaps_path = audiocaps_path_val + FN = 0 + with open(audiocaps_path, "r") as fr: + lines = fr.readlines() + if scp_ac is not None: + lines = lines[start_ac: end_ac] + for index, line in enumerate(lines): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = jsondata["audio"] + self.audiocaps_inputs.append(caption) + self.audiocaps_audios.append(audio) + self.audiocaps_indices.append(N + index) + main_process and print(part, "audiocaps", len(self.audiocaps_audios), "filtered", FN) + self.inputs.extend(self.audiocaps_inputs) + self.audios.extend(self.audiocaps_audios) + self.indices.extend(self.audiocaps_indices) + N = len(self.audios) + main_process and print(part, "audiocaps audios", len(self.audios)) + + if bbc_soundeffects and part in ["train", "train_val_audioset_sl"]: + self.bbc_soundeffects_inputs = [] + self.bbc_soundeffects_audios = [] + self.bbc_soundeffects_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/tango-master/data/train_bbc_sound_effects.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + bbc_soundeffects_utts[utt] = 1 + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/BBC_Sound_Effects/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/BBC_Sound_Effects_flac/" + utt + ".flac" + self.bbc_soundeffects_inputs.append(caption) + self.bbc_soundeffects_audios.append(audio) + self.bbc_soundeffects_indices.append(N + index) + main_process and print(part, "bbc_soundeffects", len(self.bbc_soundeffects_audios)) + self.inputs.extend(self.bbc_soundeffects_inputs) + self.audios.extend(self.bbc_soundeffects_audios) + self.indices.extend(self.bbc_soundeffects_indices) + N = len(self.audios) + main_process and print(part, "bbc_soundeffects audios", len(self.audios)) + + if freesound and part in ["train", "train_val_audioset_sl"]: + self.freesound_inputs = [] + self.freesound_audios = [] + self.freesound_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/tango-master/data/train_freesound.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + freesound_utts[utt] = 1 + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/FreeSound/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/FreeSound_flac/" + utt + ".flac" + self.freesound_inputs.append(caption) + self.freesound_audios.append(audio) + self.freesound_indices.append(N + index) + main_process and print(part, "freesound", len(self.freesound_audios)) + self.inputs.extend(self.freesound_inputs) + self.audios.extend(self.freesound_audios) + self.indices.extend(self.freesound_indices) + N = len(self.audios) + main_process and print(part, "freesound audios", len(self.audios)) + + if soundbible and part in ["train", "train_val_audioset_sl"]: + self.soundbible_inputs = [] + self.soundbible_audios = [] + self.soundbible_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/tango-master/data/train_soundbible.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/SoundBible/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/SoundBible_flac/" + utt + ".flac" + self.soundbible_inputs.append(caption) + self.soundbible_audios.append(audio) + self.soundbible_indices.append(N + index) + main_process and print(part, "soundbible", len(self.soundbible_audios)) + self.inputs.extend(self.soundbible_inputs) + self.audios.extend(self.soundbible_audios) + self.indices.extend(self.soundbible_indices) + N = len(self.audios) + main_process and print(part, "soundbible audios", len(self.audios)) + + if (soundeffects and part in ["train", "train_val_audioset_sl"]) or (part == "val_soundeffects"): + self.soundeffects_inputs = [] + self.soundeffects_audios = [] + self.soundeffects_indices = [] + #soundeffects_path_train = "/zhanghaomin/codes2/audiocaption/wav_all_train.scp" + #soundeffects_path_val = "/zhanghaomin/codes2/audiocaption/wav_all_val.scp" + #soundeffects_path_train = "/zhanghaomin/codes2/audiocaption/wav_msclap_all_train.scp" + soundeffects_path_train = train_file + soundeffects_path_val = "/zhanghaomin/codes2/audiocaption/wav_msclap_all_val.scp" + if part in ["train", "train_val_audioset_sl"]: + soundeffects_path = soundeffects_path_train + else: + soundeffects_path = soundeffects_path_val + with open(soundeffects_path, 'r') as fr: + for index, line in enumerate(fr.readlines()): + if soundeffects_path.endswith("msclapcap_v1.list"): + utt, wav, caption1, score = line.strip().split('"@$&#"') + caption2 = "blank" + name = "blank" + else: + utt, wav, name, caption1, caption2 = line.strip().split('"@$&#"') + wav = wav.replace("/radiostorage/AudioGroup/", "/radiostorage/AudioGroup/") + period = int(utt.split('_')[-1]) + self.soundeffects_inputs.append((caption1, caption2, name)) + self.soundeffects_audios.append((wav, utt, period)) + self.soundeffects_indices.append(N + index) + main_process and print(part, "soundeffects", len(self.soundeffects_audios)) + self.inputs.extend(self.soundeffects_inputs) + self.audios.extend(self.soundeffects_audios) + self.indices.extend(self.soundeffects_indices) + N = len(self.audios) + main_process and print(part, "soundeffects audios", len(self.audios)) + + if audioset and part in ["train", "train_val_audioset_sl"]: + self.audioset_inputs = [] + self.audioset_audios = [] + self.audioset_indices = [] + FN = 0 + FN2 = 0 + if SCORE_THRESHOLD_TRAIN["audioset"] == "af-audioset": + audioset_path = "/ailab-train/speech/zhanghaomin/scps/audioset/audioset_train_af.json" + else: + audioset_path = "/ckptstorage/zhanghaomin/audioset/audioset_train.json" + with open(audioset_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + if SCORE_THRESHOLD_TRAIN["audioset"] == "af-audioset": + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = jsondata["audio"] + else: + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + #caption = caption.replace("@", ", ") + captions = caption.split("@") + captions_new = [] + for c in captions: + if c in audioset_filter_labels: + audioset_filter_labels[c] += 1 + else: + captions_new.append(c) + if len(captions_new) == 0: + FN2 += 1 + continue + caption = "".join(captions_new) + audio = jsondata["audio"] + self.audioset_inputs.append(caption) + self.audioset_audios.append(audio) + self.audioset_indices.append(N + index) + main_process and print(part, "audioset", len(self.audioset_audios), "filtered", FN, FN2, audioset_filter_labels) + self.inputs.extend(self.audioset_inputs) + self.audios.extend(self.audioset_audios) + self.indices.extend(self.audioset_indices) + N = len(self.audios) + main_process and print(part, "audioset audios", len(self.audios)) + + if bbc_soundeffects2 and part in ["train", "train_val_audioset_sl"]: + self.bbc_soundeffects2_inputs = [] + self.bbc_soundeffects2_audios = [] + self.bbc_soundeffects2_indices = [] + FN = 0 + with open("/ckptstorage/zhanghaomin/BBCSoundEffects/bbcsoundeffects_train.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in bbc_soundeffects_utts: + FN += 1 + continue + caption = jsondata["caption"] + caption = caption.split("(")[0].strip() + audio = jsondata["audio"] + self.bbc_soundeffects2_inputs.append(caption) + self.bbc_soundeffects2_audios.append(audio) + self.bbc_soundeffects2_indices.append(N + index) + main_process and print(part, "bbc_soundeffects2", len(self.bbc_soundeffects2_audios), "filtered", FN) + self.inputs.extend(self.bbc_soundeffects2_inputs) + self.audios.extend(self.bbc_soundeffects2_audios) + self.indices.extend(self.bbc_soundeffects2_indices) + N = len(self.audios) + main_process and print(part, "bbc_soundeffects2 audios", len(self.audios)) + + if freesound2 and part in ["train", "train_val_audioset_sl"]: + self.freesound2_inputs = [] + self.freesound2_audios = [] + self.freesound2_indices = [] + FN = 0 + with open("/ckptstorage/zhanghaomin/CLAP_freesound/freesound_train.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in freesound_utts: + FN += 1 + continue + caption = jsondata["caption"] + caption = caption.split('"@$&#"') + #caption = caption[0].split("(")[0].strip() + caption = tuple([c.split("(")[0].strip() for c in caption]) + audio = jsondata["audio"] + self.freesound2_inputs.append(caption) + self.freesound2_audios.append(audio) + self.freesound2_indices.append(N + index) + main_process and print(part, "freesound2", len(self.freesound2_audios), "filtered", FN) + self.inputs.extend(self.freesound2_inputs) + self.audios.extend(self.freesound2_audios) + self.indices.extend(self.freesound2_indices) + N = len(self.audios) + main_process and print(part, "freesound2 audios", len(self.audios)) + + if tangopromptbank and part in ["train", "train_val_audioset_sl"]: + self.tangopromptbank_inputs = [] + self.tangopromptbank_audios = [] + self.tangopromptbank_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/TangoPromptBank/data.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["captions"] + audio = jsondata["location"] + self.tangopromptbank_inputs.append(caption) + self.tangopromptbank_audios.append(audio) + self.tangopromptbank_indices.append(N + index) + main_process and print(part, "tangopromptbank", len(self.tangopromptbank_audios)) + self.inputs.extend(self.tangopromptbank_inputs) + self.audios.extend(self.tangopromptbank_audios) + self.indices.extend(self.tangopromptbank_indices) + N = len(self.audios) + main_process and print(part, "tangopromptbank audios", len(self.audios)) + + if musiccaps and part in ["train", "train_val_audioset_sl"]: + self.musiccaps_inputs = [] + self.musiccaps_audios = [] + self.musiccaps_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/musiccap/musiccaps.jsonl", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.musiccaps_inputs.append(caption) + self.musiccaps_audios.append(audio) + self.musiccaps_indices.append(N + index) + main_process and print(part, "musiccaps", len(self.musiccaps_audios)) + self.inputs.extend(self.musiccaps_inputs) + self.audios.extend(self.musiccaps_audios) + self.indices.extend(self.musiccaps_indices) + N = len(self.audios) + main_process and print(part, "musiccaps audios", len(self.audios)) + + if (audioset_sl_2ch and part in ["train", "train_val_audioset_sl"]) or (part == "val_audioset_sl_2ch"): + self.audioset_sl_2ch_inputs = [] + self.audioset_sl_2ch_audios = [] + self.audioset_sl_2ch_indices = [] + audioset_sl_2ch_train = "/ckptstorage/zhanghaomin/audiosetsl/wavs/train.jsonl" + audioset_sl_2ch_val = "/ckptstorage/zhanghaomin/audiosetsl/wavs/test.jsonl" + if part in ["train", "train_val_audioset_sl"]: + audioset_sl_2ch_path = audioset_sl_2ch_train + else: + audioset_sl_2ch_path = audioset_sl_2ch_val + with open(audioset_sl_2ch_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.audioset_sl_2ch_inputs.append(caption) + self.audioset_sl_2ch_audios.append(audio) + self.audioset_sl_2ch_indices.append(N + index) + main_process and print(part, "audioset_sl_2ch", len(self.audioset_sl_2ch_audios)) + self.inputs.extend(self.audioset_sl_2ch_inputs) + self.audios.extend(self.audioset_sl_2ch_audios) + self.indices.extend(self.audioset_sl_2ch_indices) + N = len(self.audios) + main_process and print(part, "audioset_sl_2ch audios", len(self.audios)) + + if (boom_epic and part in ["train", "train_val_audioset_sl"]) or (part == "val_boom_epic"): + self.boom_epic_inputs = [] + self.boom_epic_audios = [] + self.boom_epic_indices = [] + #boom_epic_train = "/ckptstorage/zhanghaomin/giantsoundeffects/train_animals_mixture2.jsonl" + #boom_epic_val = "/ckptstorage/zhanghaomin/giantsoundeffects/test_animals_mixture2.jsonl" + boom_epic_train = "/ailab-train/speech/zhanghaomin/scps/giantsoundeffects/train.jsonl" + boom_epic_val = "/ailab-train/speech/zhanghaomin/scps/giantsoundeffects/test.jsonl" + if part in ["train", "train_val_audioset_sl"]: + boom_epic_path = boom_epic_train + else: + boom_epic_path = boom_epic_val + with open(boom_epic_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.boom_epic_inputs.append(caption) + self.boom_epic_audios.append(audio) + self.boom_epic_indices.append(N + index) + main_process and print(part, "boom_epic", len(self.boom_epic_audios)) + repeats = 1 + for _ in range(repeats): + self.inputs.extend(self.boom_epic_inputs) + self.audios.extend(self.boom_epic_audios) + self.indices.extend(self.boom_epic_indices) + N = len(self.audios) + main_process and print(part, "boom_epic audios", len(self.audios)) + self.boom_epic = boom_epic + + if vggsound: + self.inputs_vggsound = [] + self.audios_vggsound = [] + self.indices_vggsound = [] + if part in ["train", "train_val_audioset_sl"]: + #path = "/ailab-train/speech/zhanghaomin/scps/VGGSound/train.scp" + path = vgg_train + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()): + video_path, text = line.strip().split("\t") + self.inputs_vggsound.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios_vggsound.append(video_path) + self.indices_vggsound.append(index) + N = len(self.audios_vggsound) + print(part, "vggsound train audios", len(self.audios_vggsound), device_id, num_processes) + elif part == "val_vggsound": + if vgg_test is not None: + path = vgg_test[0] + start = vgg_test[1] + end = vgg_test[2] + else: + path = "/ailab-train/speech/zhanghaomin/scps/VGGSound/test.scp" + start = 0 + end = 200 + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()[start:end]): + video_path, text = line.strip().split("\t") + self.inputs.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios.append(video_path) + self.indices.append(N + index) + N = len(self.audios) + print(part, "vggsound eval audios", len(self.audios), device_id, num_processes) + self.vggsound = vggsound + self.video_drop_prompt = video_drop_prompt + self.audio_drop_prompt = audio_drop_prompt + self.device_id = device_id + self.num_processes = num_processes + self.bad_ids = {} + self.video_encoder = video_encoder + self.val_length = val_length if val_length is not None else torch_tools.MAX_TARGET_LEN + print("val_length", self.val_length) + + #self.mapper = {} + #for index, audio, text in zip(self.indices, self.audios, self.inputs): + # self.mapper[index] = [audio, text] + + if num_examples != -1: + self.inputs, self.audios = self.inputs[:num_examples], self.audios[:num_examples] + self.indices = self.indices[:num_examples] + + self.samples = samples + self.stft = stft + self.target_length = DURATION + self.augment = augment + self.part = part + self.main_process = main_process + self.SCORE_THRESHOLD_TRAIN = SCORE_THRESHOLD_TRAIN + self.theta = theta + self.multi = 4 + + def __len__(self): + return len(self.inputs) + + def get_num_instances(self): + return len(self.inputs) + + def __getitem__(self, index): + s1, s2, s3 = self.inputs[index], self.audios[index], self.indices[index] + return s1, s2, s3 + + def read_audio_from_video(self, video_path): + if video_path.startswith("/ailab-train/speech/zhanghaomin/VGGSound/"): + audio_path = video_path.replace("/video/", "/audio/").replace(".mp4", ".wav") + else: + audio_path = video_path.replace(".mp4", ".generated.wav") + if os.path.exists(audio_path): + #print("video wav exist", audio_path) + waveform, sr = torchaudio.load(audio_path) + else: + #print("video wav not exist", video_path) + try: + clip = AudioFileClip(video_path) + sound_array = np.array(list(clip.iter_frames())) + waveform = torch.from_numpy(sound_array).transpose(0,1).to(torch.float32) + waveform = waveform[0:1, :] + if clip.fps != torch_tools.new_freq: + waveform = torchaudio.functional.resample(waveform, orig_freq=clip.fps, new_freq=torch_tools.new_freq) + waveform = torch_tools.normalize_wav(waveform) + torchaudio.save(audio_path, waveform, torch_tools.new_freq) + except: + print("Error read_audio_from_video", audio_path) + traceback.print_exc() + return None + return waveform + + def collate_fn(self, data): + # 452463+1471396->452463+3430704->452463+2978587 more 452463+1037241+15973+310169 real 1183416+2000 + # theta (1183416)*0.5/(452463+1037241+15973+310169)=0.3259 + # beta (452463+1037241+15973+310169+3430704)/(452463+1037241+15973+310169+1471396)=1.5960 (452463+1037241+15973+310169+2978587)/(452463+1037241+15973+310169+1471396)=1.4585 + if self.part in ["train", "train_val_audioset_sl"]: + val = False + else: + val = True + if self.audioset_sl_2ch: + nch = 2 + else: + nch = 1 + while True: + if self.part in ["train", "train_val_audioset_sl"]: + #print("data raw", len(data), data[0]) + #data_sampled = random.sample(data, self.samples) + + if (self.soundeffects or self.boom_epic) and self.theta > 0: + data_len = len(data) + data_1 = [] + data_2 = [] + for sample in data: + if isinstance(sample[1], tuple): + if sample[1][0].startswith("/radiostorage/"): + prefix = "/".join(sample[1][0].split("/")[:3]) + else: + prefix = "/".join(sample[1][0].split("/")[:4]) + else: + if sample[1].startswith("/radiostorage/"): + prefix = "/".join(sample[1].split("/")[:3]) + else: + prefix = "/".join(sample[1].split("/")[:4]) + if torch_tools.SOUNDEFFECT[prefix]: + data_2.append(sample) + else: + data_1.append(sample) + #print("data splitted", len(data_1), len(data_2), float(len(data_1))/len(data_2)) + data_len_1 = len(data_1) + data_len_2 = len(data_2) + if data_len_1 == 0 or data_len_2 == 0: + data_1_sampled = data_1 + data_2_sampled = data_2 + else: + data_len_1_sampled = int(data_len_2 / self.theta) + data_len_2_sampled = int(data_len_1 * self.theta) + if data_len_1_sampled < data_len_1: + data_1_sampled = random.sample(data_1, data_len_1_sampled) + data_2_sampled = data_2 + else: + data_1_sampled = data_1 + data_2_sampled = random.sample(data_2, data_len_2_sampled) + #print("data sampled", len(data_1_sampled), len(data_2_sampled), float(len(data_1_sampled))/len(data_2_sampled), self.samples*cand) + data_sampled = data_1_sampled + data_sampled.extend(data_2_sampled) + data_sampled = random.sample(data_sampled, min(self.samples*cand, len(data_sampled))) + #print("data sampled", len(data_sampled)) + else: + data_sampled = random.sample(data, min(self.samples*cand, len(data))) + #print("data sampled", len(data_sampled)) + else: + data_sampled = data + dat = pd.DataFrame(data_sampled) + text, audios, indices = [dat[i].tolist() for i in dat] + + if self.vggsound and val and self.part == "val_vggsound": + #print("vggsound val", len(audios), text) + fbanks = [] + fbank_lens = [] + video_paths = [] + text_selected = [] + for audio, txt in zip(audios, text): + waveform = self.read_audio_from_video(audio) + if waveform is None: + continue + length = self.val_length + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + video_paths.append(audio) + text_selected.append(txt) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + mel = torch.cat(fbanks, 0) + mel_len = torch.Tensor(fbank_lens).to(torch.int32) + break + + if_clap_filter = False + if self.part in ["val_audiocaps", "val_audioset_sl_2ch", "val_boom_epic"]: + if_clap_filter = False + mel, text_selected, _, _, _, mel_len = torch_tools.wav_to_fbank(audios, text, self.samples, self.target_length, self.stft, val, if_clap_filter, self.main_process, self.SCORE_THRESHOLD_TRAIN, nch) + if mel is not None: + if self.part in ["train", "train_val_audioset_sl"]: + if len(text_selected) > self.samples: + mel = mel[:self.samples,...] + text_selected = text_selected[:self.samples] + #waveform = waveform[:self.samples,...] + mel_len = mel_len[:self.samples] + if self.vggsound: + video_paths = [None] * len(text_selected) + else: + video_paths = None + #print("mel", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + break + + #mel = mel.unsqueeze(1) + if self.augment != 0 and len(text_selected) > 1 and (not val): + aug_num = len(text_selected) if self.augment == -1 else self.augment + # the last batch of the training data may have only one instance + # we check the length here so that the augmentation function doesn't throw an error + mixed_mel, _, _, mixed_captions, _, mixed_mel_len = torch_tools.augment_wav_to_fbank(audios, text, aug_num, self.target_length, self.stft, self.main_process, self.SCORE_THRESHOLD_TRAIN, nch) + #print("mixed_mel", mixed_mel.shape if mixed_mel is not None else None, len(mixed_captions) if mixed_captions is not None else 0, mixed_mel_len) + if mixed_mel is not None: + if mel.shape[1] < mixed_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], mixed_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif mixed_mel.shape[1] < mel.shape[1]: + mixed_mel = torch.cat([mixed_mel, torch.zeros(mixed_mel.shape[0], mel.shape[1]-mixed_mel.shape[1], mixed_mel.shape[2])], 1) + #mixed_mel = mixed_mel.unsqueeze(1) + mel = torch.cat([mel, mixed_mel], 0) + text_selected += mixed_captions + mel_len = torch.cat([mel_len, mixed_mel_len], 0) + if self.vggsound: + video_paths.extend([None] * len(mixed_captions)) + else: + video_paths = None + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len) + + if self.vggsound and (not val): + video_paths = [None] * len(text_selected) + fbanks = [] + fbank_lens = [] + audios = [] + video_captions = [] + indices = random.sample([self.indices_vggsound[i] for i in range(self.device_id, len(self.indices_vggsound), self.num_processes)], self.vggsound*10) + indices_featured = [] + indices_nonfeatured = [] + for i in indices: + if i in self.bad_ids: + continue + if self.audios_vggsound[i].startswith("/ailab-train/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + if os.path.exists(feature_path): + indices_featured.append(i) + else: + indices_nonfeatured.append(i) + if len(indices_nonfeatured) >= self.vggsound: + break + #print(self.device_id, self.bad_ids, indices, indices_featured, indices_nonfeatured) + indices = indices_nonfeatured[:self.vggsound] + if len(indices) < self.vggsound: + indices.extend(indices_featured[:self.vggsound-len(indices)]) + for i in indices: + waveform = self.read_audio_from_video(self.audios_vggsound[i]) + if waveform is None: + print("Error audio in video", i, self.audios_vggsound[i], self.bad_ids) + self.bad_ids[i] = 1 + continue + length = random.randint(torch_tools.MIN_TARGET_LEN, torch_tools.MAX_TARGET_LEN) + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + audios.append(self.audios_vggsound[i]) + video_captions.append(self.inputs_vggsound[i]) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + video_mel = torch.cat(fbanks, 0) + video_mel_len = torch.Tensor(fbank_lens).to(torch.int32) + #print("video_mel", video_mel.shape if video_mel is not None else None, len(video_captions) if video_captions is not None else 0, video_mel_len) + if video_mel is not None: + if mel.shape[1] < video_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], video_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif video_mel.shape[1] < mel.shape[1]: + video_mel = torch.cat([video_mel, torch.zeros(video_mel.shape[0], mel.shape[1]-video_mel.shape[1], video_mel.shape[2])], 1) + #video_mel = video_mel.unsqueeze(1) + mel = torch.cat([mel, video_mel], 0) + text_selected += video_captions + mel_len = torch.cat([mel_len, video_mel_len], 0) + video_paths.extend(audios) + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + + return [text_selected, mel, video_paths, mel_len, self.video_drop_prompt, self.audio_drop_prompt] + + +class Text2SpeechDataset(Dataset): + def __init__(self, samples=-1, stft=None, val=False): + self.inputs = [] + self.audios = [] + self.indices = [] + + train_scp = "/ckptstorage/zhanghaomin/docker/ximalaya/ximalaya_process/data_scp/train.json" + test_scp = "/ckptstorage/zhanghaomin/docker/ximalaya/ximalaya_process/data_scp/test.json" + scp = train_scp if not val else test_scp + index = 0 + with open(scp, "r") as fr: + for line in fr.readlines(): + data = json.loads(line.strip()) + wav = data["wav"] + text = data["text"] + if len(text) < 2: + continue + self.inputs.append(text) + self.audios.append(wav) + self.indices.append(index) + index += 1 + print("data size", len(self.inputs), val) + self.samples = samples + self.stft = stft + self.sample_rate = 24000 + self.multi = 8 + self.val = val + + def __len__(self): + return len(self.inputs) + + def get_num_instances(self): + return len(self.inputs) + + def __getitem__(self, index): + s1, s2, s3 = self.inputs[index], self.audios[index], self.indices[index] + return s1, s2, s3 + + def collate_fn(self, data): + dat = pd.DataFrame(data) + texts, audios, indices = [dat[i].tolist() for i in dat] + + fbanks = [] + fbank_lens = [] + text_selected = [] + for text, audio in zip(texts, audios): + waveform, sr = torchaudio.load(audio) + waveform = waveform[0:1, :] + if sr != self.sample_rate: + waveform = torchaudio.functional.resample(waveform, orig_freq=sr, new_freq=self.sample_rate) + waveform = torch_tools.normalize_wav(waveform) + fbank = self.stft(waveform).transpose(-1,-2) + #print("stft", waveform.shape, fbank.shape) + if self.val: + if waveform.shape[1] / float(self.sample_rate) < 2.0 or waveform.shape[1] / float(self.sample_rate) > 15.0: + continue + else: + if waveform.shape[1] / float(self.sample_rate) < 1.0 or waveform.shape[1] / float(self.sample_rate) > 20.0: + continue + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + text_selected.append(text) + if self.samples > 0 and len(text_selected) >= self.samples: + break + if self.samples > 0 and len(text_selected) > self.samples: + fbanks = fbanks[:self.samples] + fbank_lens = fbank_lens[:self.samples] + text_selected = text_selected[:self.samples] + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + mel = torch.cat(fbanks, 0) + mel_len = torch.Tensor(fbank_lens).to(torch.int32) + return [text_selected, mel, None, mel_len, None] + diff --git a/src/e2_tts_pytorch/trainer_multigpus_alldatas3.py b/src/e2_tts_pytorch/trainer_multigpus_alldatas3.py new file mode 100644 index 0000000000000000000000000000000000000000..4133a10991fecbeea7b4304a43996e40c67240de --- /dev/null +++ b/src/e2_tts_pytorch/trainer_multigpus_alldatas3.py @@ -0,0 +1,1456 @@ +from __future__ import annotations + +import os +from tqdm import tqdm +import matplotlib +matplotlib.use("Agg") +import matplotlib.pylab as plt + +import torch +import torch.nn.functional as F +from torch.utils.data import DataLoader, Dataset +from torch.utils.tensorboard import SummaryWriter +from torch.optim.lr_scheduler import LinearLR, SequentialLR + +import torchaudio + +from einops import rearrange + +from accelerate import Accelerator +from accelerate.utils import DistributedDataParallelKwargs + +from ema_pytorch import EMA + +from loguru import logger + +from e2_tts_pytorch.e2_tts_crossatt3 import ( + E2TTS, + DurationPredictor, + MelSpec +) + +import traceback +import numpy as np +from moviepy.editor import AudioFileClip, VideoFileClip + +def exists(v): + return v is not None + +def default(v, d): + return v if exists(v) else d + +def to_numpy(t): + return t.detach().cpu().numpy() + +# plot spectrogram + +def plot_spectrogram(spectrogram): + spectrogram = to_numpy(spectrogram) + fig, ax = plt.subplots(figsize=(10, 4)) + im = ax.imshow(spectrogram.T, aspect="auto", origin="lower", interpolation="none") + plt.colorbar(im, ax=ax) + plt.xlabel("Frames") + plt.ylabel("Channels") + plt.tight_layout() + + fig.canvas.draw() + plt.close() + return fig + +# collation + +def collate_fn(batch): + mel_specs = [item['mel_spec'].squeeze(0) for item in batch] + mel_lengths = torch.LongTensor([spec.shape[-1] for spec in mel_specs]) + max_mel_length = mel_lengths.amax() + + padded_mel_specs = [] + for spec in mel_specs: + padding = (0, max_mel_length - spec.size(-1)) + padded_spec = F.pad(spec, padding, value = 0) + padded_mel_specs.append(padded_spec) + + mel_specs = torch.stack(padded_mel_specs) + + text = [item['text'] for item in batch] + text_lengths = torch.LongTensor([len(item) for item in text]) + + return dict( + mel = mel_specs, + mel_lengths = mel_lengths, + text = text, + text_lengths = text_lengths, + ) + +# dataset + +class HFDataset(Dataset): + def __init__( + self, + hf_dataset: Dataset, + target_sample_rate = 24_000, + hop_length = 256 + ): + self.data = hf_dataset + self.target_sample_rate = target_sample_rate + self.hop_length = hop_length + self.mel_spectrogram = MelSpec(sampling_rate=target_sample_rate) + + def __len__(self): + return len(self.data) + + def __getitem__(self, index): + row = self.data[index] + audio = row['audio']['array'] + + #logger.info(f"Audio shape: {audio.shape}") + + sample_rate = row['audio']['sampling_rate'] + duration = audio.shape[-1] / sample_rate + + if duration > 20 or duration < 0.3: + logger.warning(f"Skipping due to duration out of bound: {duration}") + return self.__getitem__((index + 1) % len(self.data)) + + audio_tensor = torch.from_numpy(audio).float() + + if sample_rate != self.target_sample_rate: + resampler = torchaudio.transforms.Resample(sample_rate, self.target_sample_rate) + audio_tensor = resampler(audio_tensor) + + audio_tensor = rearrange(audio_tensor, 't -> 1 t') + + mel_spec = self.mel_spectrogram(audio_tensor) + + mel_spec = rearrange(mel_spec, '1 d t -> d t') + + text = row['transcript'] + + return dict( + mel_spec = mel_spec, + text = text, + ) + +# trainer + +class E2Trainer: + def __init__( + self, + model: E2TTS, + optimizer, + num_warmup_steps=20000, + grad_accumulation_steps=1, + duration_predictor: DurationPredictor | None = None, + checkpoint_path = None, + log_file = "logs.txt", + max_grad_norm = 1.0, + sample_rate = 22050, + tensorboard_log_dir = 'runs/e2_tts_experiment', + accelerate_kwargs: dict = dict(), + ema_kwargs: dict = dict(), + use_switch_ema = False, + if_text = False, + if_prompt = False + ): + logger.add(log_file) + + ddp_kwargs = DistributedDataParallelKwargs(find_unused_parameters = True) + + self.accelerator = Accelerator( + log_with = "all", + kwargs_handlers = [ddp_kwargs], + gradient_accumulation_steps = grad_accumulation_steps, + **accelerate_kwargs + ) + self.accelerator.wait_for_everyone() + + self.target_sample_rate = sample_rate + + self.model = model + + self.need_velocity_consistent_loss = model.velocity_consistency_weight > 0. + + #self.ema_model = EMA( + # model, + # include_online_model = False, + # **ema_kwargs + #) + + self.use_switch_ema = use_switch_ema + + self.duration_predictor = duration_predictor + self.optimizer = optimizer + self.num_warmup_steps = num_warmup_steps + self.checkpoint_path = default(checkpoint_path, 'model.pth') + self.mel_spectrogram = MelSpec(sampling_rate=self.target_sample_rate) + + self.model, self.optimizer = self.accelerator.prepare( + self.model, self.optimizer + ) + #self.ema_model = self.accelerator.prepare(self.ema_model) + self.max_grad_norm = max_grad_norm + + self.writer = SummaryWriter(log_dir=tensorboard_log_dir) + self.tensorboard_log_dir = tensorboard_log_dir + self.if_text = if_text + self.if_prompt = if_prompt + + self.device_id = self.accelerator.device.index + self.num_processes = self.accelerator.num_processes + + @property + def is_main(self): + return self.accelerator.is_main_process + + def save_checkpoint(self, step, finetune=False): + self.accelerator.wait_for_everyone() + if self.is_main: + checkpoint = dict( + model_state_dict = self.accelerator.unwrap_model(self.model).state_dict(), + #optimizer_state_dict = self.accelerator.unwrap_model(self.optimizer).state_dict(), + #ema_model_state_dict = self.ema_model.state_dict(), + #scheduler_state_dict = self.scheduler.state_dict(), + #step = step, + ) + + self.accelerator.save(checkpoint, self.tensorboard_log_dir + "/" + str(step) + ".pt") + + def load_checkpoint(self): + if not exists(self.checkpoint_path) or not os.path.exists(self.checkpoint_path): + return 0 + + checkpoint = torch.load(self.checkpoint_path, map_location='cpu') + for key in list(checkpoint['model_state_dict'].keys()): + #if key.startswith('mel_spec.'): + # del checkpoint['model_state_dict'][key] + if key.startswith('transformer.text_registers'): + if checkpoint['model_state_dict'][key].shape[1] != self.accelerator.unwrap_model(self.model).transformer.text_registers.shape[1]: + print('miss match: transformer.text_registers', checkpoint['model_state_dict'][key].shape, self.accelerator.unwrap_model(self.model).transformer.text_registers.shape) + del checkpoint['model_state_dict'][key] + #### + #if key.startswith("conv") or key.startswith("pool"): + # print('del video encoder', key, checkpoint['model_state_dict'][key].shape) + # del checkpoint['model_state_dict'][key] + self.accelerator.unwrap_model(self.model).load_state_dict(checkpoint['model_state_dict'], strict=False) + #self.accelerator.unwrap_model(self.optimizer).load_state_dict(checkpoint['optimizer_state_dict']) + + if self.is_main: + model0 = {} + for key in list(checkpoint['model_state_dict'].keys()): + model0[key] = checkpoint['model_state_dict'][key].shape + model1 = {} + for key, param in self.accelerator.unwrap_model(self.model).state_dict().items(): + model1[key] = param.shape + #print("model0", model0) + #print("model1", model1) + for key in model0.keys(): + if key not in model1: + pass + #print("Missing key found", key, model0[key]) + else: + if model0[key] != model1[key]: + pass + #print("Miss match", key, model0[key], model1[key]) + for key in model1.keys(): + if key not in model0: + pass + #print("New key found", key, model1[key]) + else: + if model0[key] != model1[key]: + pass + #print("Miss match", key, model0[key], model1[key]) + + #if self.is_main: + # self.ema_model.load_state_dict(checkpoint['ema_model_state_dict']) + + #if self.scheduler: + # self.scheduler.load_state_dict(checkpoint['scheduler_state_dict']) + #return checkpoint['step'] + return 0 + + def evaluate(self, eval_dataloader, epoch, epochs, global_step): + if eval_dataloader is None: + return + + total_val_loss, N, total_lossmore1, total_lossmore2, total_lossmore3, total_lossmore4 = 0, 0, 0, 0, 0, 0 + self.model.eval() + eval_progress_bar = tqdm(eval_dataloader, desc=f"Epoch {epoch}/{epochs}", unit="step", disable=not self.accelerator.is_local_main_process) + for step, batch in enumerate(eval_dataloader): + with self.accelerator.accumulate(self.model) and torch.no_grad(): + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt, frames, midis = batch + + val_loss, cond, pred, pred_data, lossmore = self.model( + mel_spec, + text=(text if self.if_text else None), + times=0.5, + lens=mel_lengths, + velocity_consistency_model=None, + prompt=(text if self.if_prompt else None), + video_drop_prompt=video_drop_prompt, + audio_drop_prompt=audio_drop_prompt, + val=True, + video_paths=video_paths, + frames=frames, + midis=midis + ) + a = torch.tensor(val_loss.item()*len(text), dtype=torch.float32).reshape(1).to(val_loss.device) + b = torch.tensor(len(text), dtype=torch.int32).reshape(1).to(val_loss.device) + c = torch.tensor(lossmore[0].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[0].device) + d = torch.tensor(lossmore[1].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[1].device) + e = torch.tensor(lossmore[2].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[2].device) + f = torch.tensor(lossmore[3].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[3].device) + val_loss_gather, N_gather, lossmore_gather1, lossmore_gather2, lossmore_gather3, lossmore_gather4 = self.accelerator.gather_for_metrics((a, b, c, d, e, f)) + for i in range(val_loss_gather.shape[0]): + total_val_loss += val_loss_gather[i].item() + N += N_gather[i].item() + total_lossmore1 += lossmore_gather1[i].item() + total_lossmore2 += lossmore_gather2[i].item() + total_lossmore3 += lossmore_gather3[i].item() + total_lossmore4 += lossmore_gather4[i].item() + eval_progress_bar.update(1) + + if self.accelerator.is_local_main_process: + total_val_loss = round(total_val_loss/float(N), 4) + total_lossmore1 = round(total_lossmore1/float(N), 4) + total_lossmore2 = round(total_lossmore2/float(N), 4) + total_lossmore3 = round(total_lossmore3/float(N), 4) + total_lossmore4 = round(total_lossmore4/float(N), 4) + result_string = "Epoch: {}, GlobalStep: {}, ValLoss: {}, N: {}, Lossmore1: {}, Lossmore2: {}, Lossmore3: {}, Lossmore4: {} (average loss)\n".format(epoch, global_step, total_val_loss, N, total_lossmore1, total_lossmore2, total_lossmore3, total_lossmore4) + #tp, fp, fn, tn = total_lossmore1, total_lossmore2, total_lossmore3, total_lossmore4 + #result_string = "Epoch: {}, GlobalStep: {}, ValLoss: {}, N: {}, Lossmore1: {}, Lossmore2: {}, Lossmore3: {}, Lossmore4: {} (average loss)\n".format(epoch, global_step, total_val_loss, N, tp / (tp + fp) if (tp + fp) != 0 else 0, tp / (tp + fn) if (tp + fn) != 0 else 0, 2 * tp / (2 * tp + fp + fn) if (2 * tp + fp + fn) != 0 else 0, tp / (tp + fp + fn) if (tp + fp + fn) != 0 else 0) + logger.info(result_string) + + torch.cuda.empty_cache() + self.model.train() + + def train(self, datasets, epochs, batch_size, num_workers=12, save_step=1000): + + params_d = {} + trainable_d = {} + for n, p in self.model.named_parameters(): + key = ".".join(n.split(".")[:2]) + if key not in params_d: + params_d[key] = [0, 0] + trainable_d[key] = p.requires_grad + if p.requires_grad: + params_d[key][0] += p.numel() + else: + params_d[key][1] += p.numel() + if key != "module.transformer": + assert(trainable_d[key] == p.requires_grad) + print(params_d) + print(trainable_d) + num_trainable_parameters = sum(p.numel() for p in self.model.parameters() if p.requires_grad) + print("Num trainable parameters: {}".format(num_trainable_parameters)) + + train_dataset = datasets[0] + eval_datasets = datasets[1:] + #train_dataloader = DataLoader(train_dataset, batch_size=batch_size, collate_fn=collate_fn, shuffle=True, num_workers=num_workers, pin_memory=True) + train_dataloader = DataLoader(train_dataset, shuffle=True, batch_size=batch_size*train_dataset.multi, collate_fn=train_dataset.collate_fn, num_workers=num_workers, drop_last=True, pin_memory=True) + eval_dataloaders = [DataLoader(eval_dataset, shuffle=False, batch_size=(len(eval_dataset.video_drop_prompt) if eval_dataset.video_drop_prompt is not None else 16), collate_fn=eval_dataset.collate_fn, num_workers=num_workers, drop_last=False, pin_memory=True) if eval_dataset is not None else None for eval_dataset in eval_datasets] + print("eval_datasets batch_size", [(len(eval_dataset.video_drop_prompt) if eval_dataset.video_drop_prompt is not None else 16) if eval_dataset is not None else None for eval_dataset in eval_datasets]) + + total_steps = len(train_dataloader) * epochs + decay_steps = total_steps - self.num_warmup_steps + warmup_scheduler = LinearLR(self.optimizer, start_factor=1e-8, end_factor=1.0, total_iters=self.num_warmup_steps) + decay_scheduler = LinearLR(self.optimizer, start_factor=1.0, end_factor=1e-8, total_iters=decay_steps) + self.scheduler = SequentialLR(self.optimizer, + schedulers=[warmup_scheduler, decay_scheduler], + milestones=[self.num_warmup_steps]) + train_dataloader, self.scheduler = self.accelerator.prepare(train_dataloader, self.scheduler) + eval_dataloaders = [self.accelerator.prepare(eval_dataloader) for eval_dataloader in eval_dataloaders if eval_dataloader is not None] + start_step = self.load_checkpoint() + global_step = start_step + + #### dpo + velocity_consistency_model = None + ####velocity_consistency_model = self.accelerator.unwrap_model(self.model) + #### dpo + for epoch in range(epochs): + + if epoch == 0: + [self.evaluate(eval_dataloader, 1, epochs, 0) for eval_dataloader in eval_dataloaders] + + self.model.train() + progress_bar = tqdm(train_dataloader, desc=f"Epoch {epoch+1}/{epochs}", unit="step", disable=not self.accelerator.is_local_main_process) + epoch_loss = 0.0 + + for batch in progress_bar: + with self.accelerator.accumulate(self.model): + #text_inputs = batch['text'] + #mel_spec = rearrange(batch['mel'], 'b d n -> b n d') + #mel_lengths = batch["mel_lengths"] + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt, frames, midis = batch + #print("batchsize", len(text)) + for i, video_path in enumerate(video_paths): + if video_path is not None: + if random.random() >= 0.5: + video_drop_prompt[i] = True + else: + video_drop_prompt[i] = False + #print("batch", text, mel_spec.shape, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt, frames.shape if frames is not None and not isinstance(frames, float) else frames, midis.shape) + + if exists(self.duration_predictor): + dur_loss = self.duration_predictor(mel_spec, lens=batch.get('durations')) + self.writer.add_scalar('duration loss', dur_loss.detach().cpu().item(), global_step) + + #velocity_consistency_model = None + #if self.need_velocity_consistent_loss and self.ema_model.initted: + # velocity_consistency_model = self.accelerator.unwrap_model(self.ema_model).ema_model + + loss, cond, pred, pred_data, lossmore = self.model( + mel_spec, + text=(text if self.if_text else None), + lens=mel_lengths, + velocity_consistency_model=velocity_consistency_model, + prompt=(text if self.if_prompt else None), + video_drop_prompt=video_drop_prompt, + audio_drop_prompt=audio_drop_prompt, + video_paths=video_paths, + frames=frames, + midis=midis + ) + + self.accelerator.backward(loss) + + if self.max_grad_norm > 0 and self.accelerator.sync_gradients: + self.accelerator.clip_grad_norm_(self.model.parameters(), self.max_grad_norm) + + self.optimizer.step() + self.scheduler.step() + self.optimizer.zero_grad() + + #self.accelerator.unwrap_model(self.ema_model).update() + + if self.accelerator.is_local_main_process: + logger.info(f"step {global_step+1}: loss = {loss.detach().cpu().item():.4f}") + self.writer.add_scalar('loss', loss.detach().cpu().item(), global_step) + self.writer.add_scalar("lr", self.scheduler.get_last_lr()[0], global_step) + + global_step += 1 + epoch_loss += loss.detach().cpu().item() + progress_bar.set_postfix(loss=loss.detach().cpu().item()) + + if global_step % save_step == 0: + self.save_checkpoint(global_step) + self.writer.add_figure("mel/target", plot_spectrogram(mel_spec[0,:,:]), global_step) + self.writer.add_figure("mel/mask", plot_spectrogram(cond[0,:,:]), global_step) + self.writer.add_figure("mel/prediction", plot_spectrogram(pred_data[0,:,:]), global_step) + [self.evaluate(eval_dataloader, epoch+1, epochs, global_step) for eval_dataloader in eval_dataloaders] + + #if global_step % 10 == 0: + # torch.cuda.empty_cache() + + epoch_loss /= len(train_dataloader) + if self.accelerator.is_local_main_process: + logger.info(f"epoch {epoch+1}/{epochs} - average loss = {epoch_loss:.4f}") + self.writer.add_scalar('epoch average loss', epoch_loss, epoch) + + #if self.use_switch_ema: + # self.ema_model.update_model_with_ema() + + self.writer.close() + + +import json +import random +import pandas as pd +from e2_tts_pytorch import torch_tools + +DURATION = torch_tools.total_length +#DURATION = 3000 +#beta = 1.5960 +#theta = 0.3259 +cand = 99999999 + +class Text2AudioDataset(Dataset): + def __init__(self, dataset, part, prefix, text_column, audio_column, num_examples=-1, samples=-1, stft=None, augment=-1, main_process=True, SCORE_THRESHOLD_TRAIN="", train_file="", theta=0.0, vggsound=0, instruments=0, video_drop_prompt=None, audio_drop_prompt=None, device_id=0, vgg_test=None, video_encoder="clip_vit", val_length=None, num_processes=8): + + #inputs = list(dataset[text_column]) + #self.inputs = [prefix + inp for inp in inputs] + #self.audios = list(dataset[audio_column]) + #self.indices = list(range(len(self.inputs))) + # + #print("audios", len(self.audios)) + #self.new_audios = [] + #for index, audio in enumerate(self.audios): + # utt, fmt = audio.split(".") + # new_audio = "/zhanghaomin/datas/audioset_sl/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/AudioSet_SL_flac/" + utt + ".flac" + # #if os.path.exists(new_audio): + # self.new_audios.append(new_audio) + #self.audios = self.new_audios + #N = len(self.audios) + #print("audios", len(self.new_audios)) + + + test_final = "./tests/scps/tango-master/data/test_audiocaps_subset.json" + test_utts = {} + with open(test_final, "r") as fr: + for line in fr.readlines(): + wav = json.loads(line.strip())["location"] + utt = wav.rsplit("/", 1)[-1].rsplit("_", 1)[0] + utt = "Y"+utt + assert(utt not in test_utts) + test_utts[utt] = 1 + main_process and print("test_final", len(test_utts)) + + bbc_soundeffects_utts = {} + freesound_utts = {} + + audioset_filter_labels = {"Music": 0, "Speech": 0, "Vehicle": 0, "Musical instrument": 0} + + + self.inputs = [] + self.audios = [] + self.indices = [] + N = 0 + + + audiocaps = True + if SCORE_THRESHOLD_TRAIN["/zhanghaomin/datas/audiocaps"] >= 9000.0: + audiocaps = False + + audioset_sl = True + bbc_soundeffects = True + freesound = True + soundbible = True + if SCORE_THRESHOLD_TRAIN["/radiostorage/WavCaps"] >= 9000.0: + audioset_sl = False + bbc_soundeffects = False + freesound = False + soundbible = False + + soundeffects = True + if SCORE_THRESHOLD_TRAIN["/radiostorage/AudioGroup"] >= 9000.0: + soundeffects = False + self.soundeffects = soundeffects + + audioset = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/audioset"] >= 9000.0: + audioset = False + + bbc_soundeffects2 = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/BBCSoundEffects"] >= 9000.0: + bbc_soundeffects2 = False + + freesound2 = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/CLAP_freesound"] >= 9000.0: + freesound2 = False + + musiccaps = True + if SCORE_THRESHOLD_TRAIN["/zhanghaomin/datas/musiccap"] >= 9000.0: + musiccaps = False + + tangopromptbank = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/TangoPromptBank"] >= 9000.0: + tangopromptbank = False + + audioset_sl_2ch = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/audiosetsl"] >= 9000.0: + audioset_sl_2ch = False + self.audioset_sl_2ch = audioset_sl_2ch + + boom_epic = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/giantsoundeffects"] >= 9000.0: + boom_epic = False + self.boom_epic = boom_epic + + if isinstance(part, list): + part, scp_ac, start_ac, end_ac = part + assert(part == "val_audiocaps") + else: + scp_ac = None + + if (audioset_sl and part in ["train", "train_val_audioset_sl"]) or (part == "val_audioset_sl"): + self.audioset_sl_inputs = [] + self.audioset_sl_audios = [] + self.audioset_sl_indices = [] + audioset_sl_path_train = "/zhanghaomin/codes2/tango-master/data/train_audioset_sl.json" + audioset_sl_path_val = "/zhanghaomin/codes2/tango-master/data/val_audioset_sl.json" + audioset_sl_path_train_val = "./tests/scps/tango-master/data/train_val_audioset_sl.json" + if part == "train": + audioset_sl_path = audioset_sl_path_train + elif part == "train_val_audioset_sl": + audioset_sl_path = audioset_sl_path_train_val + else: + audioset_sl_path = audioset_sl_path_val + FN = 0 + with open(audioset_sl_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"].rsplit(".", 1)[0] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/AudioSet_SL/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/AudioSet_SL_flac/" + utt + ".flac" + self.audioset_sl_inputs.append(caption) + self.audioset_sl_audios.append(audio) + self.audioset_sl_indices.append(N + index) + main_process and print(part, "audioset_sl", len(self.audioset_sl_audios), "filtered", FN) + self.inputs.extend(self.audioset_sl_inputs) + self.audios.extend(self.audioset_sl_audios) + self.indices.extend(self.audioset_sl_indices) + N = len(self.audios) + main_process and print(part, "audioset_sl audios", len(self.audios)) + + if (audiocaps and part in ["train", "train_val_audioset_sl"]) or (part == "val_audiocaps"): + self.audiocaps_inputs = [] + self.audiocaps_audios = [] + self.audiocaps_indices = [] + audiocaps_path_train = "./tests/scps/tango-master/data/audiocaps/train_audiocaps.json" + audiocaps_path_val = "./tests/scps/tango-master/data/audiocaps/test_audiocaps.json" + if scp_ac is not None: + audiocaps_path_val = scp_ac + if part in ["train", "train_val_audioset_sl"]: + audiocaps_path = audiocaps_path_train + else: + audiocaps_path = audiocaps_path_val + FN = 0 + with open(audiocaps_path, "r") as fr: + lines = fr.readlines() + if scp_ac is not None: + lines = lines[start_ac: end_ac] + for index, line in enumerate(lines): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = jsondata["audio"] + self.audiocaps_inputs.append(caption) + self.audiocaps_audios.append(audio) + self.audiocaps_indices.append(N + index) + main_process and print(part, "audiocaps", len(self.audiocaps_audios), "filtered", FN) + self.inputs.extend(self.audiocaps_inputs) + self.audios.extend(self.audiocaps_audios) + self.indices.extend(self.audiocaps_indices) + N = len(self.audios) + main_process and print(part, "audiocaps audios", len(self.audios)) + + if bbc_soundeffects and part in ["train", "train_val_audioset_sl"]: + self.bbc_soundeffects_inputs = [] + self.bbc_soundeffects_audios = [] + self.bbc_soundeffects_indices = [] + with open("./tests/scps/tango-master/data/train_bbc_sound_effects.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + bbc_soundeffects_utts[utt] = 1 + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/BBC_Sound_Effects/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/BBC_Sound_Effects_flac/" + utt + ".flac" + self.bbc_soundeffects_inputs.append(caption) + self.bbc_soundeffects_audios.append(audio) + self.bbc_soundeffects_indices.append(N + index) + main_process and print(part, "bbc_soundeffects", len(self.bbc_soundeffects_audios)) + self.inputs.extend(self.bbc_soundeffects_inputs) + self.audios.extend(self.bbc_soundeffects_audios) + self.indices.extend(self.bbc_soundeffects_indices) + N = len(self.audios) + main_process and print(part, "bbc_soundeffects audios", len(self.audios)) + + if freesound and part in ["train", "train_val_audioset_sl"]: + self.freesound_inputs = [] + self.freesound_audios = [] + self.freesound_indices = [] + with open("./tests/scps/tango-master/data/train_freesound.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + freesound_utts[utt] = 1 + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/FreeSound/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/FreeSound_flac/" + utt + ".flac" + self.freesound_inputs.append(caption) + self.freesound_audios.append(audio) + self.freesound_indices.append(N + index) + main_process and print(part, "freesound", len(self.freesound_audios)) + self.inputs.extend(self.freesound_inputs) + self.audios.extend(self.freesound_audios) + self.indices.extend(self.freesound_indices) + N = len(self.audios) + main_process and print(part, "freesound audios", len(self.audios)) + + if soundbible and part in ["train", "train_val_audioset_sl"]: + self.soundbible_inputs = [] + self.soundbible_audios = [] + self.soundbible_indices = [] + with open("./tests/scps/tango-master/data/train_soundbible.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/SoundBible/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/SoundBible_flac/" + utt + ".flac" + self.soundbible_inputs.append(caption) + self.soundbible_audios.append(audio) + self.soundbible_indices.append(N + index) + main_process and print(part, "soundbible", len(self.soundbible_audios)) + self.inputs.extend(self.soundbible_inputs) + self.audios.extend(self.soundbible_audios) + self.indices.extend(self.soundbible_indices) + N = len(self.audios) + main_process and print(part, "soundbible audios", len(self.audios)) + + if (soundeffects and part in ["train", "train_val_audioset_sl"]) or (part == "val_soundeffects"): + self.soundeffects_inputs = [] + self.soundeffects_audios = [] + self.soundeffects_indices = [] + #soundeffects_path_train = "/zhanghaomin/codes2/audiocaption/wav_all_train.scp" + #soundeffects_path_val = "/zhanghaomin/codes2/audiocaption/wav_all_val.scp" + #soundeffects_path_train = "/zhanghaomin/codes2/audiocaption/wav_msclap_all_train.scp" + soundeffects_path_train = train_file + soundeffects_path_val = "/zhanghaomin/codes2/audiocaption/wav_msclap_all_val.scp" + if part in ["train", "train_val_audioset_sl"]: + soundeffects_path = soundeffects_path_train + else: + soundeffects_path = soundeffects_path_val + with open(soundeffects_path, 'r') as fr: + for index, line in enumerate(fr.readlines()): + if soundeffects_path.endswith("msclapcap_v1.list"): + utt, wav, caption1, score = line.strip().split('"@$&#"') + caption2 = "blank" + name = "blank" + else: + utt, wav, name, caption1, caption2 = line.strip().split('"@$&#"') + wav = wav.replace("/radiostorage/AudioGroup/", "/radiostorage/AudioGroup/") + period = int(utt.split('_')[-1]) + self.soundeffects_inputs.append((caption1, caption2, name)) + self.soundeffects_audios.append((wav, utt, period)) + self.soundeffects_indices.append(N + index) + main_process and print(part, "soundeffects", len(self.soundeffects_audios)) + self.inputs.extend(self.soundeffects_inputs) + self.audios.extend(self.soundeffects_audios) + self.indices.extend(self.soundeffects_indices) + N = len(self.audios) + main_process and print(part, "soundeffects audios", len(self.audios)) + + if audioset and part in ["train", "train_val_audioset_sl"]: + self.audioset_inputs = [] + self.audioset_audios = [] + self.audioset_indices = [] + FN = 0 + FN2 = 0 + if SCORE_THRESHOLD_TRAIN["audioset"] == "af-audioset": + audioset_path = "./tests/scps/audioset/audioset_train_af.json" + else: + audioset_path = "/ckptstorage/zhanghaomin/audioset/audioset_train.json" + with open(audioset_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + if SCORE_THRESHOLD_TRAIN["audioset"] == "af-audioset": + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = jsondata["audio"] + else: + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + #caption = caption.replace("@", ", ") + captions = caption.split("@") + captions_new = [] + for c in captions: + if c in audioset_filter_labels: + audioset_filter_labels[c] += 1 + else: + captions_new.append(c) + if len(captions_new) == 0: + FN2 += 1 + continue + caption = "".join(captions_new) + audio = jsondata["audio"] + self.audioset_inputs.append(caption) + self.audioset_audios.append(audio) + self.audioset_indices.append(N + index) + main_process and print(part, "audioset", len(self.audioset_audios), "filtered", FN, FN2, audioset_filter_labels) + self.inputs.extend(self.audioset_inputs) + self.audios.extend(self.audioset_audios) + self.indices.extend(self.audioset_indices) + N = len(self.audios) + main_process and print(part, "audioset audios", len(self.audios)) + + if bbc_soundeffects2 and part in ["train", "train_val_audioset_sl"]: + self.bbc_soundeffects2_inputs = [] + self.bbc_soundeffects2_audios = [] + self.bbc_soundeffects2_indices = [] + FN = 0 + with open("/ckptstorage/zhanghaomin/BBCSoundEffects/bbcsoundeffects_train.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in bbc_soundeffects_utts: + FN += 1 + continue + caption = jsondata["caption"] + caption = caption.split("(")[0].strip() + audio = jsondata["audio"] + self.bbc_soundeffects2_inputs.append(caption) + self.bbc_soundeffects2_audios.append(audio) + self.bbc_soundeffects2_indices.append(N + index) + main_process and print(part, "bbc_soundeffects2", len(self.bbc_soundeffects2_audios), "filtered", FN) + self.inputs.extend(self.bbc_soundeffects2_inputs) + self.audios.extend(self.bbc_soundeffects2_audios) + self.indices.extend(self.bbc_soundeffects2_indices) + N = len(self.audios) + main_process and print(part, "bbc_soundeffects2 audios", len(self.audios)) + + if freesound2 and part in ["train", "train_val_audioset_sl"]: + self.freesound2_inputs = [] + self.freesound2_audios = [] + self.freesound2_indices = [] + FN = 0 + with open("/ckptstorage/zhanghaomin/CLAP_freesound/freesound_train.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in freesound_utts: + FN += 1 + continue + caption = jsondata["caption"] + caption = caption.split('"@$&#"') + #caption = caption[0].split("(")[0].strip() + caption = tuple([c.split("(")[0].strip() for c in caption]) + audio = jsondata["audio"] + self.freesound2_inputs.append(caption) + self.freesound2_audios.append(audio) + self.freesound2_indices.append(N + index) + main_process and print(part, "freesound2", len(self.freesound2_audios), "filtered", FN) + self.inputs.extend(self.freesound2_inputs) + self.audios.extend(self.freesound2_audios) + self.indices.extend(self.freesound2_indices) + N = len(self.audios) + main_process and print(part, "freesound2 audios", len(self.audios)) + + if tangopromptbank and part in ["train", "train_val_audioset_sl"]: + self.tangopromptbank_inputs = [] + self.tangopromptbank_audios = [] + self.tangopromptbank_indices = [] + with open("./tests/scps/TangoPromptBank/data.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["captions"] + audio = jsondata["location"] + self.tangopromptbank_inputs.append(caption) + self.tangopromptbank_audios.append(audio) + self.tangopromptbank_indices.append(N + index) + main_process and print(part, "tangopromptbank", len(self.tangopromptbank_audios)) + self.inputs.extend(self.tangopromptbank_inputs) + self.audios.extend(self.tangopromptbank_audios) + self.indices.extend(self.tangopromptbank_indices) + N = len(self.audios) + main_process and print(part, "tangopromptbank audios", len(self.audios)) + + if musiccaps and part in ["train", "train_val_audioset_sl"]: + self.musiccaps_inputs = [] + self.musiccaps_audios = [] + self.musiccaps_indices = [] + with open("./tests/scps/musiccap/musiccaps.jsonl", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.musiccaps_inputs.append(caption) + self.musiccaps_audios.append(audio) + self.musiccaps_indices.append(N + index) + main_process and print(part, "musiccaps", len(self.musiccaps_audios)) + self.inputs.extend(self.musiccaps_inputs) + self.audios.extend(self.musiccaps_audios) + self.indices.extend(self.musiccaps_indices) + N = len(self.audios) + main_process and print(part, "musiccaps audios", len(self.audios)) + + if (audioset_sl_2ch and part in ["train", "train_val_audioset_sl"]) or (part == "val_audioset_sl_2ch"): + self.audioset_sl_2ch_inputs = [] + self.audioset_sl_2ch_audios = [] + self.audioset_sl_2ch_indices = [] + audioset_sl_2ch_train = "/ckptstorage/zhanghaomin/audiosetsl/wavs/train.jsonl" + audioset_sl_2ch_val = "/ckptstorage/zhanghaomin/audiosetsl/wavs/test.jsonl" + if part in ["train", "train_val_audioset_sl"]: + audioset_sl_2ch_path = audioset_sl_2ch_train + else: + audioset_sl_2ch_path = audioset_sl_2ch_val + with open(audioset_sl_2ch_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.audioset_sl_2ch_inputs.append(caption) + self.audioset_sl_2ch_audios.append(audio) + self.audioset_sl_2ch_indices.append(N + index) + main_process and print(part, "audioset_sl_2ch", len(self.audioset_sl_2ch_audios)) + self.inputs.extend(self.audioset_sl_2ch_inputs) + self.audios.extend(self.audioset_sl_2ch_audios) + self.indices.extend(self.audioset_sl_2ch_indices) + N = len(self.audios) + main_process and print(part, "audioset_sl_2ch audios", len(self.audios)) + + if (boom_epic and part in ["train", "train_val_audioset_sl"]) or (part == "val_boom_epic"): + self.boom_epic_inputs = [] + self.boom_epic_audios = [] + self.boom_epic_indices = [] + #boom_epic_train = "/ckptstorage/zhanghaomin/giantsoundeffects/train_animals_mixture2.jsonl" + #boom_epic_val = "/ckptstorage/zhanghaomin/giantsoundeffects/test_animals_mixture2.jsonl" + boom_epic_train = "./tests/scps/giantsoundeffects/train.jsonl" + boom_epic_val = "./tests/scps/giantsoundeffects/test.jsonl" + if part in ["train", "train_val_audioset_sl"]: + boom_epic_path = boom_epic_train + else: + boom_epic_path = boom_epic_val + with open(boom_epic_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.boom_epic_inputs.append(caption) + self.boom_epic_audios.append(audio) + self.boom_epic_indices.append(N + index) + main_process and print(part, "boom_epic", len(self.boom_epic_audios)) + repeats = 1 + for _ in range(repeats): + self.inputs.extend(self.boom_epic_inputs) + self.audios.extend(self.boom_epic_audios) + self.indices.extend(self.boom_epic_indices) + N = len(self.audios) + main_process and print(part, "boom_epic audios", len(self.audios)) + self.boom_epic = boom_epic + + if vggsound: + self.inputs_vggsound = [] + self.audios_vggsound = [] + self.indices_vggsound = [] + if part in ["train", "train_val_audioset_sl"]: + path = "./tests/scps/VGGSound/train.scp" + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()): + video_path, text = line.strip().split("\t") + self.inputs_vggsound.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios_vggsound.append(video_path) + self.indices_vggsound.append(index) + N = len(self.audios_vggsound) + print(part, "vggsound train audios", len(self.audios_vggsound), device_id, num_processes) + elif part == "val_vggsound": + if vgg_test is not None: + path = vgg_test[0] + start = vgg_test[1] + end = vgg_test[2] + step = vgg_test[3] + else: + path = "./tests/scps/VGGSound/test.scp" + start = 0 + end = 200 + step = 1 + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()[start:end:step]): + video_path, text = line.strip().split("\t") + self.inputs.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios.append(video_path) + self.indices.append(N + index) + N = len(self.audios) + print(part, "vggsound eval audios", len(self.audios), device_id, num_processes) + + if instruments: + self.inputs_instruments = [] + self.audios_instruments = [] + self.indices_instruments = [] + if part in ["train", "train_val_audioset_sl"]: + ####path = "./tests/scps/instruments/train.scp" + path = "./tests/scps/instruments/piano_2h/train.scp" + ####path = "./tests/scps/instruments/piano_20h/v2a_giant_piano2/train.scp" + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()): + video_path, text = line.strip().split("\t") + self.inputs_instruments.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios_instruments.append(video_path) + self.indices_instruments.append(index) + N = len(self.audios_instruments) + print(part, "instruments train audios", len(self.audios_instruments), device_id, num_processes) + elif part == "val_instruments": + if vgg_test is not None: + path = vgg_test[0] + start = vgg_test[1] + end = vgg_test[2] + step = vgg_test[3] + else: + ####path = "./tests/scps/instruments/test.scp" + path = "./tests/scps/instruments/piano_2h/test.scp" + ####path = "./tests/scps/instruments/piano_20h/v2a_giant_piano2/test.scp" + start = 0 + end = 200 + step = 1 + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()[start:end:step]): + video_path, text = line.strip().split("\t") + self.inputs.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios.append(video_path) + self.indices.append(N + index) + N = len(self.audios) + print(part, "instruments eval audios", len(self.audios), device_id, num_processes) + + self.vggsound = vggsound + self.instruments = instruments + self.video_drop_prompt = video_drop_prompt + self.audio_drop_prompt = audio_drop_prompt + self.device_id = device_id + self.num_processes = num_processes + self.bad_ids = {} + self.bad_ids_instruments = {} + self.video_encoder = video_encoder + self.val_length = val_length if val_length is not None else torch_tools.MAX_TARGET_LEN + print("val_length", self.val_length) + + #self.mapper = {} + #for index, audio, text in zip(self.indices, self.audios, self.inputs): + # self.mapper[index] = [audio, text] + + if num_examples != -1: + self.inputs, self.audios = self.inputs[:num_examples], self.audios[:num_examples] + self.indices = self.indices[:num_examples] + + self.samples = samples + self.stft = stft + self.target_length = DURATION + self.augment = augment + self.part = part + self.main_process = main_process + self.SCORE_THRESHOLD_TRAIN = SCORE_THRESHOLD_TRAIN + self.theta = theta + self.multi = 4 + + def __len__(self): + return len(self.inputs) + + def get_num_instances(self): + return len(self.inputs) + + def __getitem__(self, index): + s1, s2, s3 = self.inputs[index], self.audios[index], self.indices[index] + return s1, s2, s3 + + def read_audio_from_video(self, video_path): + if video_path.startswith("/ailab-train2/speech/zhanghaomin/VGGSound/"): + audio_path = video_path.replace("/video/", "/audio/").replace(".mp4", ".wav") + else: + audio_path = video_path.replace(".mp4", ".generated.wav") + if os.path.exists(audio_path): + #print("video wav exist", audio_path) + waveform, sr = torchaudio.load(audio_path) + else: + #print("video wav not exist", video_path) + try: + clip = AudioFileClip(video_path) + sound_array = np.array(list(clip.iter_frames())) + waveform = torch.from_numpy(sound_array).transpose(0,1).to(torch.float32) + waveform = waveform[0:1, :] + if clip.fps != torch_tools.new_freq: + waveform = torchaudio.functional.resample(waveform, orig_freq=clip.fps, new_freq=torch_tools.new_freq) + waveform = torch_tools.normalize_wav(waveform) + torchaudio.save(audio_path, waveform, torch_tools.new_freq) + except: + print("Error read_audio_from_video", audio_path) + traceback.print_exc() + return None + return waveform + + def collate_fn(self, data): + # 452463+1471396->452463+3430704->452463+2978587 more 452463+1037241+15973+310169 real 1183416+2000 + # theta (1183416)*0.5/(452463+1037241+15973+310169)=0.3259 + # beta (452463+1037241+15973+310169+3430704)/(452463+1037241+15973+310169+1471396)=1.5960 (452463+1037241+15973+310169+2978587)/(452463+1037241+15973+310169+1471396)=1.4585 + if self.part in ["train", "train_val_audioset_sl"]: + val = False + else: + val = True + if self.audioset_sl_2ch: + nch = 2 + else: + nch = 1 + while True: + if self.part in ["train", "train_val_audioset_sl"]: + #print("data raw", len(data), data[0]) + #data_sampled = random.sample(data, self.samples) + + if (self.soundeffects or self.boom_epic) and self.theta > 0: + data_len = len(data) + data_1 = [] + data_2 = [] + for sample in data: + if isinstance(sample[1], tuple): + if sample[1][0].startswith("/radiostorage/"): + prefix = "/".join(sample[1][0].split("/")[:3]) + else: + prefix = "/".join(sample[1][0].split("/")[:4]) + else: + if sample[1].startswith("/radiostorage/"): + prefix = "/".join(sample[1].split("/")[:3]) + else: + prefix = "/".join(sample[1].split("/")[:4]) + if torch_tools.SOUNDEFFECT[prefix]: + data_2.append(sample) + else: + data_1.append(sample) + #print("data splitted", len(data_1), len(data_2), float(len(data_1))/len(data_2)) + data_len_1 = len(data_1) + data_len_2 = len(data_2) + if data_len_1 == 0 or data_len_2 == 0: + data_1_sampled = data_1 + data_2_sampled = data_2 + else: + data_len_1_sampled = int(data_len_2 / self.theta) + data_len_2_sampled = int(data_len_1 * self.theta) + if data_len_1_sampled < data_len_1: + data_1_sampled = random.sample(data_1, data_len_1_sampled) + data_2_sampled = data_2 + else: + data_1_sampled = data_1 + data_2_sampled = random.sample(data_2, data_len_2_sampled) + #print("data sampled", len(data_1_sampled), len(data_2_sampled), float(len(data_1_sampled))/len(data_2_sampled), self.samples*cand) + data_sampled = data_1_sampled + data_sampled.extend(data_2_sampled) + data_sampled = random.sample(data_sampled, min(self.samples*cand, len(data_sampled))) + #print("data sampled", len(data_sampled)) + else: + data_sampled = random.sample(data, min(self.samples*cand, len(data))) + #print("data sampled", len(data_sampled)) + else: + data_sampled = data + dat = pd.DataFrame(data_sampled) + text, audios, indices = [dat[i].tolist() for i in dat] + + if self.vggsound and val and self.part in ["val_vggsound", "val_instruments"]: + #print("vggsound val", len(audios), text) + fbanks = [] + fbank_lens = [] + video_paths = [] + text_selected = [] + for audio, txt in zip(audios, text): + waveform = self.read_audio_from_video(audio) + if waveform is None: + continue + length = self.val_length + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + video_paths.append(audio) + text_selected.append(txt) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + mel = torch.cat(fbanks, 0) + mel_len = torch.Tensor(fbank_lens).to(torch.int32) + break + + if_clap_filter = False + if self.part in ["val_audiocaps", "val_audioset_sl_2ch", "val_boom_epic"]: + if_clap_filter = False + mel, text_selected, _, _, _, mel_len = torch_tools.wav_to_fbank(audios, text, self.samples, self.target_length, self.stft, val, if_clap_filter, self.main_process, self.SCORE_THRESHOLD_TRAIN, nch) + if mel is not None: + if self.part in ["train", "train_val_audioset_sl"]: + if len(text_selected) > self.samples: + mel = mel[:self.samples,...] + text_selected = text_selected[:self.samples] + #waveform = waveform[:self.samples,...] + mel_len = mel_len[:self.samples] + if self.vggsound: + video_paths = [None] * len(text_selected) + else: + video_paths = None + #print("mel", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + break + + #mel = mel.unsqueeze(1) + if self.augment != 0 and len(text_selected) > 1 and (not val): + aug_num = len(text_selected) if self.augment == -1 else self.augment + # the last batch of the training data may have only one instance + # we check the length here so that the augmentation function doesn't throw an error + mixed_mel, _, _, mixed_captions, _, mixed_mel_len = torch_tools.augment_wav_to_fbank(audios, text, aug_num, self.target_length, self.stft, self.main_process, self.SCORE_THRESHOLD_TRAIN, nch) + #print("mixed_mel", mixed_mel.shape if mixed_mel is not None else None, len(mixed_captions) if mixed_captions is not None else 0, mixed_mel_len) + if mixed_mel is not None: + if mel.shape[1] < mixed_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], mixed_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif mixed_mel.shape[1] < mel.shape[1]: + mixed_mel = torch.cat([mixed_mel, torch.zeros(mixed_mel.shape[0], mel.shape[1]-mixed_mel.shape[1], mixed_mel.shape[2])], 1) + #mixed_mel = mixed_mel.unsqueeze(1) + mel = torch.cat([mel, mixed_mel], 0) + text_selected += mixed_captions + mel_len = torch.cat([mel_len, mixed_mel_len], 0) + if self.vggsound: + video_paths.extend([None] * len(mixed_captions)) + else: + video_paths = None + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len) + + if self.vggsound and (not val): + video_paths = [None] * len(text_selected) + fbanks = [] + fbank_lens = [] + audios = [] + video_captions = [] + indices = random.sample([self.indices_vggsound[i] for i in range(self.device_id, len(self.indices_vggsound), self.num_processes)], self.vggsound*10) + indices_featured = [] + indices_nonfeatured = [] + for i in indices: + if i in self.bad_ids: + continue + if self.audios_vggsound[i].startswith("/ailab-train2/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + if os.path.exists(feature_path): + indices_featured.append(i) + else: + indices_nonfeatured.append(i) + if len(indices_nonfeatured) >= self.vggsound: + break + #print(self.device_id, self.bad_ids, indices, indices_featured, indices_nonfeatured) + indices = indices_nonfeatured[:self.vggsound] + if len(indices) < self.vggsound: + indices.extend(indices_featured[:self.vggsound-len(indices)]) + for i in indices: + waveform = self.read_audio_from_video(self.audios_vggsound[i]) + if waveform is None: + print("Error audio in video", i, self.audios_vggsound[i], self.bad_ids) + self.bad_ids[i] = 1 + continue + length = random.randint(torch_tools.MIN_TARGET_LEN, torch_tools.MAX_TARGET_LEN) + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + audios.append(self.audios_vggsound[i]) + video_captions.append(self.inputs_vggsound[i]) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + video_mel = torch.cat(fbanks, 0) + video_mel_len = torch.Tensor(fbank_lens).to(torch.int32) + #print("video_mel", video_mel.shape if video_mel is not None else None, len(video_captions) if video_captions is not None else 0, video_mel_len) + if video_mel is not None: + if mel.shape[1] < video_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], video_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif video_mel.shape[1] < mel.shape[1]: + video_mel = torch.cat([video_mel, torch.zeros(video_mel.shape[0], mel.shape[1]-video_mel.shape[1], video_mel.shape[2])], 1) + #video_mel = video_mel.unsqueeze(1) + mel = torch.cat([mel, video_mel], 0) + text_selected += video_captions + mel_len = torch.cat([mel_len, video_mel_len], 0) + video_paths.extend(audios) + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + + if self.instruments and (not val): + fbanks = [] + fbank_lens = [] + audios = [] + video_captions = [] + indices = random.sample([self.indices_instruments[i] for i in range(self.device_id, len(self.indices_instruments), self.num_processes)], self.instruments*10) + indices_featured = [] + indices_nonfeatured = [] + for i in indices: + if i in self.bad_ids_instruments: + continue + if self.audios_instruments[i].startswith("/ailab-train2/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = self.audios_instruments[i].replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_instruments[i].replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_instruments[i].replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_instruments[i].replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_instruments[i].replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + if os.path.exists(feature_path): + indices_featured.append(i) + else: + indices_nonfeatured.append(i) + if len(indices_nonfeatured) >= self.instruments: + break + #print(self.device_id, self.bad_ids_instruments, indices, indices_featured, indices_nonfeatured) + indices = indices_nonfeatured[:self.instruments] + if len(indices) < self.instruments: + indices.extend(indices_featured[:self.instruments-len(indices)]) + #### dpo + ####a_indices = [] + ####b_indices = [] + ####for i in indices[:len(indices)//2]: + #### path, name = self.audios_instruments[i].rsplit("/", 1) + #### assert(name[0] in ["a", "b"]) + #### for j, p in enumerate(self.audios_instruments): + #### if p == path + "/a" + name[1:]: + #### a_indices.append(j) + #### elif p == path + "/b" + name[1:]: + #### b_indices.append(j) + ####indices = a_indices + b_indices + #### dpo + for i in indices: + waveform = self.read_audio_from_video(self.audios_instruments[i]) + if waveform is None: + print("Error audio in video instruments", i, self.audios_instruments[i], self.bad_ids_instruments) + self.bad_ids_instruments[i] = 1 + continue + length = random.randint(torch_tools.MIN_TARGET_LEN, torch_tools.MAX_TARGET_LEN) + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + audios.append(self.audios_instruments[i]) + video_captions.append(self.inputs_instruments[i]) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + video_mel = torch.cat(fbanks, 0) + video_mel_len = torch.Tensor(fbank_lens).to(torch.int32) + #print("video_mel", video_mel.shape if video_mel is not None else None, len(video_captions) if video_captions is not None else 0, video_mel_len) + if video_mel is not None: + if mel.shape[1] < video_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], video_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif video_mel.shape[1] < mel.shape[1]: + video_mel = torch.cat([video_mel, torch.zeros(video_mel.shape[0], mel.shape[1]-video_mel.shape[1], video_mel.shape[2])], 1) + #video_mel = video_mel.unsqueeze(1) + mel = torch.cat([mel, video_mel], 0) + text_selected += video_captions + mel_len = torch.cat([mel_len, video_mel_len], 0) + video_paths.extend(audios) + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + + #### + text_selected = [" ".join(text.split(" ")[:20]) for text in text_selected] + + #### + if not val: + ####T = 8 + T = 5 + ####T = 2 + text_selected = text_selected[-T:] + mel = mel[-T:,...] + video_paths = video_paths[-T:] + mel_len = mel_len[-T:,...] + self.video_drop_prompt = self.video_drop_prompt[-T:] + self.audio_drop_prompt = self.audio_drop_prompt[-T:] if self.audio_drop_prompt is not None else None + + frames, midis = E2TTS.encode_video_frames(video_paths, mel.shape[1]) + return [text_selected, mel, video_paths, mel_len, self.video_drop_prompt, self.audio_drop_prompt, frames, midis] + + +class Text2SpeechDataset(Dataset): + def __init__(self, samples=-1, stft=None, val=False): + self.inputs = [] + self.audios = [] + self.indices = [] + + train_scp = "/ckptstorage/zhanghaomin/docker/ximalaya/ximalaya_process/data_scp/train.json" + test_scp = "/ckptstorage/zhanghaomin/docker/ximalaya/ximalaya_process/data_scp/test.json" + scp = train_scp if not val else test_scp + index = 0 + with open(scp, "r") as fr: + for line in fr.readlines(): + data = json.loads(line.strip()) + wav = data["wav"] + text = data["text"] + if len(text) < 2: + continue + self.inputs.append(text) + self.audios.append(wav) + self.indices.append(index) + index += 1 + print("data size", len(self.inputs), val) + self.samples = samples + self.stft = stft + self.sample_rate = 24000 + self.multi = 8 + self.val = val + + def __len__(self): + return len(self.inputs) + + def get_num_instances(self): + return len(self.inputs) + + def __getitem__(self, index): + s1, s2, s3 = self.inputs[index], self.audios[index], self.indices[index] + return s1, s2, s3 + + def collate_fn(self, data): + dat = pd.DataFrame(data) + texts, audios, indices = [dat[i].tolist() for i in dat] + + fbanks = [] + fbank_lens = [] + text_selected = [] + for text, audio in zip(texts, audios): + waveform, sr = torchaudio.load(audio) + waveform = waveform[0:1, :] + if sr != self.sample_rate: + waveform = torchaudio.functional.resample(waveform, orig_freq=sr, new_freq=self.sample_rate) + waveform = torch_tools.normalize_wav(waveform) + fbank = self.stft(waveform).transpose(-1,-2) + #print("stft", waveform.shape, fbank.shape) + if self.val: + if waveform.shape[1] / float(self.sample_rate) < 2.0 or waveform.shape[1] / float(self.sample_rate) > 15.0: + continue + else: + if waveform.shape[1] / float(self.sample_rate) < 1.0 or waveform.shape[1] / float(self.sample_rate) > 20.0: + continue + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + text_selected.append(text) + if self.samples > 0 and len(text_selected) >= self.samples: + break + if self.samples > 0 and len(text_selected) > self.samples: + fbanks = fbanks[:self.samples] + fbank_lens = fbank_lens[:self.samples] + text_selected = text_selected[:self.samples] + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + mel = torch.cat(fbanks, 0) + mel_len = torch.Tensor(fbank_lens).to(torch.int32) + return [text_selected, mel, None, mel_len, None] + diff --git a/src/e2_tts_pytorch/trainer_multigpus_alldatas3_2.py b/src/e2_tts_pytorch/trainer_multigpus_alldatas3_2.py new file mode 100644 index 0000000000000000000000000000000000000000..6352ea7d86def5ebe077a965621c361ffe2856cd --- /dev/null +++ b/src/e2_tts_pytorch/trainer_multigpus_alldatas3_2.py @@ -0,0 +1,1456 @@ +from __future__ import annotations + +import os +from tqdm import tqdm +import matplotlib +matplotlib.use("Agg") +import matplotlib.pylab as plt + +import torch +import torch.nn.functional as F +from torch.utils.data import DataLoader, Dataset +from torch.utils.tensorboard import SummaryWriter +from torch.optim.lr_scheduler import LinearLR, SequentialLR + +import torchaudio + +from einops import rearrange + +from accelerate import Accelerator +from accelerate.utils import DistributedDataParallelKwargs + +from ema_pytorch import EMA + +from loguru import logger + +from e2_tts_pytorch.e2_tts_crossatt3_2 import ( + E2TTS, + DurationPredictor, + MelSpec +) + +import traceback +import numpy as np +from moviepy.editor import AudioFileClip, VideoFileClip + +def exists(v): + return v is not None + +def default(v, d): + return v if exists(v) else d + +def to_numpy(t): + return t.detach().cpu().numpy() + +# plot spectrogram + +def plot_spectrogram(spectrogram): + spectrogram = to_numpy(spectrogram) + fig, ax = plt.subplots(figsize=(10, 4)) + im = ax.imshow(spectrogram.T, aspect="auto", origin="lower", interpolation="none") + plt.colorbar(im, ax=ax) + plt.xlabel("Frames") + plt.ylabel("Channels") + plt.tight_layout() + + fig.canvas.draw() + plt.close() + return fig + +# collation + +def collate_fn(batch): + mel_specs = [item['mel_spec'].squeeze(0) for item in batch] + mel_lengths = torch.LongTensor([spec.shape[-1] for spec in mel_specs]) + max_mel_length = mel_lengths.amax() + + padded_mel_specs = [] + for spec in mel_specs: + padding = (0, max_mel_length - spec.size(-1)) + padded_spec = F.pad(spec, padding, value = 0) + padded_mel_specs.append(padded_spec) + + mel_specs = torch.stack(padded_mel_specs) + + text = [item['text'] for item in batch] + text_lengths = torch.LongTensor([len(item) for item in text]) + + return dict( + mel = mel_specs, + mel_lengths = mel_lengths, + text = text, + text_lengths = text_lengths, + ) + +# dataset + +class HFDataset(Dataset): + def __init__( + self, + hf_dataset: Dataset, + target_sample_rate = 24_000, + hop_length = 256 + ): + self.data = hf_dataset + self.target_sample_rate = target_sample_rate + self.hop_length = hop_length + self.mel_spectrogram = MelSpec(sampling_rate=target_sample_rate) + + def __len__(self): + return len(self.data) + + def __getitem__(self, index): + row = self.data[index] + audio = row['audio']['array'] + + #logger.info(f"Audio shape: {audio.shape}") + + sample_rate = row['audio']['sampling_rate'] + duration = audio.shape[-1] / sample_rate + + if duration > 20 or duration < 0.3: + logger.warning(f"Skipping due to duration out of bound: {duration}") + return self.__getitem__((index + 1) % len(self.data)) + + audio_tensor = torch.from_numpy(audio).float() + + if sample_rate != self.target_sample_rate: + resampler = torchaudio.transforms.Resample(sample_rate, self.target_sample_rate) + audio_tensor = resampler(audio_tensor) + + audio_tensor = rearrange(audio_tensor, 't -> 1 t') + + mel_spec = self.mel_spectrogram(audio_tensor) + + mel_spec = rearrange(mel_spec, '1 d t -> d t') + + text = row['transcript'] + + return dict( + mel_spec = mel_spec, + text = text, + ) + +# trainer + +class E2Trainer: + def __init__( + self, + model: E2TTS, + optimizer, + num_warmup_steps=20000, + grad_accumulation_steps=1, + duration_predictor: DurationPredictor | None = None, + checkpoint_path = None, + log_file = "logs.txt", + max_grad_norm = 1.0, + sample_rate = 22050, + tensorboard_log_dir = 'runs/e2_tts_experiment', + accelerate_kwargs: dict = dict(), + ema_kwargs: dict = dict(), + use_switch_ema = False, + if_text = False, + if_prompt = False + ): + logger.add(log_file) + + ddp_kwargs = DistributedDataParallelKwargs(find_unused_parameters = True) + + self.accelerator = Accelerator( + log_with = "all", + kwargs_handlers = [ddp_kwargs], + gradient_accumulation_steps = grad_accumulation_steps, + **accelerate_kwargs + ) + self.accelerator.wait_for_everyone() + + self.target_sample_rate = sample_rate + + self.model = model + + self.need_velocity_consistent_loss = model.velocity_consistency_weight > 0. + + #self.ema_model = EMA( + # model, + # include_online_model = False, + # **ema_kwargs + #) + + self.use_switch_ema = use_switch_ema + + self.duration_predictor = duration_predictor + self.optimizer = optimizer + self.num_warmup_steps = num_warmup_steps + self.checkpoint_path = default(checkpoint_path, 'model.pth') + self.mel_spectrogram = MelSpec(sampling_rate=self.target_sample_rate) + + self.model, self.optimizer = self.accelerator.prepare( + self.model, self.optimizer + ) + #self.ema_model = self.accelerator.prepare(self.ema_model) + self.max_grad_norm = max_grad_norm + + self.writer = SummaryWriter(log_dir=tensorboard_log_dir) + self.tensorboard_log_dir = tensorboard_log_dir + self.if_text = if_text + self.if_prompt = if_prompt + + self.device_id = self.accelerator.device.index + self.num_processes = self.accelerator.num_processes + + @property + def is_main(self): + return self.accelerator.is_main_process + + def save_checkpoint(self, step, finetune=False): + self.accelerator.wait_for_everyone() + if self.is_main: + checkpoint = dict( + model_state_dict = self.accelerator.unwrap_model(self.model).state_dict(), + #optimizer_state_dict = self.accelerator.unwrap_model(self.optimizer).state_dict(), + #ema_model_state_dict = self.ema_model.state_dict(), + #scheduler_state_dict = self.scheduler.state_dict(), + #step = step, + ) + + self.accelerator.save(checkpoint, self.tensorboard_log_dir + "/" + str(step) + ".pt") + + def load_checkpoint(self): + if not exists(self.checkpoint_path) or not os.path.exists(self.checkpoint_path): + return 0 + + checkpoint = torch.load(self.checkpoint_path, map_location='cpu') + for key in list(checkpoint['model_state_dict'].keys()): + #if key.startswith('mel_spec.'): + # del checkpoint['model_state_dict'][key] + if key.startswith('transformer.text_registers'): + if checkpoint['model_state_dict'][key].shape[1] != self.accelerator.unwrap_model(self.model).transformer.text_registers.shape[1]: + print('miss match: transformer.text_registers', checkpoint['model_state_dict'][key].shape, self.accelerator.unwrap_model(self.model).transformer.text_registers.shape) + del checkpoint['model_state_dict'][key] + #### + #if key.startswith("conv") or key.startswith("pool"): + # print('del video encoder', key, checkpoint['model_state_dict'][key].shape) + # del checkpoint['model_state_dict'][key] + self.accelerator.unwrap_model(self.model).load_state_dict(checkpoint['model_state_dict'], strict=False) + #self.accelerator.unwrap_model(self.optimizer).load_state_dict(checkpoint['optimizer_state_dict']) + + if self.is_main: + model0 = {} + for key in list(checkpoint['model_state_dict'].keys()): + model0[key] = checkpoint['model_state_dict'][key].shape + model1 = {} + for key, param in self.accelerator.unwrap_model(self.model).state_dict().items(): + model1[key] = param.shape + #print("model0", model0) + #print("model1", model1) + for key in model0.keys(): + if key not in model1: + pass + #print("Missing key found", key, model0[key]) + else: + if model0[key] != model1[key]: + pass + #print("Miss match", key, model0[key], model1[key]) + for key in model1.keys(): + if key not in model0: + pass + #print("New key found", key, model1[key]) + else: + if model0[key] != model1[key]: + pass + #print("Miss match", key, model0[key], model1[key]) + + #if self.is_main: + # self.ema_model.load_state_dict(checkpoint['ema_model_state_dict']) + + #if self.scheduler: + # self.scheduler.load_state_dict(checkpoint['scheduler_state_dict']) + #return checkpoint['step'] + return 0 + + def evaluate(self, eval_dataloader, epoch, epochs, global_step): + if eval_dataloader is None: + return + + total_val_loss, N, total_lossmore1, total_lossmore2, total_lossmore3, total_lossmore4 = 0, 0, 0, 0, 0, 0 + self.model.eval() + eval_progress_bar = tqdm(eval_dataloader, desc=f"Epoch {epoch}/{epochs}", unit="step", disable=not self.accelerator.is_local_main_process) + for step, batch in enumerate(eval_dataloader): + with self.accelerator.accumulate(self.model) and torch.no_grad(): + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt, frames, midis = batch + + val_loss, cond, pred, pred_data, lossmore = self.model( + mel_spec, + text=(text if self.if_text else None), + times=0.5, + lens=mel_lengths, + velocity_consistency_model=None, + prompt=(text if self.if_prompt else None), + video_drop_prompt=video_drop_prompt, + audio_drop_prompt=audio_drop_prompt, + val=True, + video_paths=video_paths, + frames=frames, + midis=midis + ) + a = torch.tensor(val_loss.item()*len(text), dtype=torch.float32).reshape(1).to(val_loss.device) + b = torch.tensor(len(text), dtype=torch.int32).reshape(1).to(val_loss.device) + c = torch.tensor(lossmore[0].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[0].device) + d = torch.tensor(lossmore[1].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[1].device) + e = torch.tensor(lossmore[2].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[2].device) + f = torch.tensor(lossmore[3].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[3].device) + val_loss_gather, N_gather, lossmore_gather1, lossmore_gather2, lossmore_gather3, lossmore_gather4 = self.accelerator.gather_for_metrics((a, b, c, d, e, f)) + for i in range(val_loss_gather.shape[0]): + total_val_loss += val_loss_gather[i].item() + N += N_gather[i].item() + total_lossmore1 += lossmore_gather1[i].item() + total_lossmore2 += lossmore_gather2[i].item() + total_lossmore3 += lossmore_gather3[i].item() + total_lossmore4 += lossmore_gather4[i].item() + eval_progress_bar.update(1) + + if self.accelerator.is_local_main_process: + total_val_loss = round(total_val_loss/float(N), 4) + total_lossmore1 = round(total_lossmore1/float(N), 4) + total_lossmore2 = round(total_lossmore2/float(N), 4) + total_lossmore3 = round(total_lossmore3/float(N), 4) + total_lossmore4 = round(total_lossmore4/float(N), 4) + result_string = "Epoch: {}, GlobalStep: {}, ValLoss: {}, N: {}, Lossmore1: {}, Lossmore2: {}, Lossmore3: {}, Lossmore4: {} (average loss)\n".format(epoch, global_step, total_val_loss, N, total_lossmore1, total_lossmore2, total_lossmore3, total_lossmore4) + #tp, fp, fn, tn = total_lossmore1, total_lossmore2, total_lossmore3, total_lossmore4 + #result_string = "Epoch: {}, GlobalStep: {}, ValLoss: {}, N: {}, Lossmore1: {}, Lossmore2: {}, Lossmore3: {}, Lossmore4: {} (average loss)\n".format(epoch, global_step, total_val_loss, N, tp / (tp + fp) if (tp + fp) != 0 else 0, tp / (tp + fn) if (tp + fn) != 0 else 0, 2 * tp / (2 * tp + fp + fn) if (2 * tp + fp + fn) != 0 else 0, tp / (tp + fp + fn) if (tp + fp + fn) != 0 else 0) + logger.info(result_string) + + torch.cuda.empty_cache() + self.model.train() + + def train(self, datasets, epochs, batch_size, num_workers=12, save_step=1000): + + params_d = {} + trainable_d = {} + for n, p in self.model.named_parameters(): + key = ".".join(n.split(".")[:2]) + if key not in params_d: + params_d[key] = [0, 0] + trainable_d[key] = p.requires_grad + if p.requires_grad: + params_d[key][0] += p.numel() + else: + params_d[key][1] += p.numel() + if key != "module.transformer": + assert(trainable_d[key] == p.requires_grad) + print(params_d) + print(trainable_d) + num_trainable_parameters = sum(p.numel() for p in self.model.parameters() if p.requires_grad) + print("Num trainable parameters: {}".format(num_trainable_parameters)) + + train_dataset = datasets[0] + eval_datasets = datasets[1:] + #train_dataloader = DataLoader(train_dataset, batch_size=batch_size, collate_fn=collate_fn, shuffle=True, num_workers=num_workers, pin_memory=True) + train_dataloader = DataLoader(train_dataset, shuffle=True, batch_size=batch_size*train_dataset.multi, collate_fn=train_dataset.collate_fn, num_workers=num_workers, drop_last=True, pin_memory=True) + eval_dataloaders = [DataLoader(eval_dataset, shuffle=False, batch_size=(len(eval_dataset.video_drop_prompt) if eval_dataset.video_drop_prompt is not None else 16), collate_fn=eval_dataset.collate_fn, num_workers=num_workers, drop_last=False, pin_memory=True) if eval_dataset is not None else None for eval_dataset in eval_datasets] + print("eval_datasets batch_size", [(len(eval_dataset.video_drop_prompt) if eval_dataset.video_drop_prompt is not None else 16) if eval_dataset is not None else None for eval_dataset in eval_datasets]) + + total_steps = len(train_dataloader) * epochs + decay_steps = total_steps - self.num_warmup_steps + warmup_scheduler = LinearLR(self.optimizer, start_factor=1e-8, end_factor=1.0, total_iters=self.num_warmup_steps) + decay_scheduler = LinearLR(self.optimizer, start_factor=1.0, end_factor=1e-8, total_iters=decay_steps) + self.scheduler = SequentialLR(self.optimizer, + schedulers=[warmup_scheduler, decay_scheduler], + milestones=[self.num_warmup_steps]) + train_dataloader, self.scheduler = self.accelerator.prepare(train_dataloader, self.scheduler) + eval_dataloaders = [self.accelerator.prepare(eval_dataloader) for eval_dataloader in eval_dataloaders if eval_dataloader is not None] + start_step = self.load_checkpoint() + global_step = start_step + + #### dpo + velocity_consistency_model = None + ####velocity_consistency_model = self.accelerator.unwrap_model(self.model) + #### dpo + for epoch in range(epochs): + + if epoch == 0: + [self.evaluate(eval_dataloader, 1, epochs, 0) for eval_dataloader in eval_dataloaders] + + self.model.train() + progress_bar = tqdm(train_dataloader, desc=f"Epoch {epoch+1}/{epochs}", unit="step", disable=not self.accelerator.is_local_main_process) + epoch_loss = 0.0 + + for batch in progress_bar: + with self.accelerator.accumulate(self.model): + #text_inputs = batch['text'] + #mel_spec = rearrange(batch['mel'], 'b d n -> b n d') + #mel_lengths = batch["mel_lengths"] + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt, frames, midis = batch + #print("batchsize", len(text)) + for i, video_path in enumerate(video_paths): + if video_path is not None: + if random.random() >= 0.5: + video_drop_prompt[i] = True + else: + video_drop_prompt[i] = False + #print("batch", text, mel_spec.shape, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt, frames.shape if frames is not None and not isinstance(frames, float) else frames, midis.shape) + + if exists(self.duration_predictor): + dur_loss = self.duration_predictor(mel_spec, lens=batch.get('durations')) + self.writer.add_scalar('duration loss', dur_loss.detach().cpu().item(), global_step) + + #velocity_consistency_model = None + #if self.need_velocity_consistent_loss and self.ema_model.initted: + # velocity_consistency_model = self.accelerator.unwrap_model(self.ema_model).ema_model + + loss, cond, pred, pred_data, lossmore = self.model( + mel_spec, + text=(text if self.if_text else None), + lens=mel_lengths, + velocity_consistency_model=velocity_consistency_model, + prompt=(text if self.if_prompt else None), + video_drop_prompt=video_drop_prompt, + audio_drop_prompt=audio_drop_prompt, + video_paths=video_paths, + frames=frames, + midis=midis + ) + + self.accelerator.backward(loss) + + if self.max_grad_norm > 0 and self.accelerator.sync_gradients: + self.accelerator.clip_grad_norm_(self.model.parameters(), self.max_grad_norm) + + self.optimizer.step() + self.scheduler.step() + self.optimizer.zero_grad() + + #self.accelerator.unwrap_model(self.ema_model).update() + + if self.accelerator.is_local_main_process: + logger.info(f"step {global_step+1}: loss = {loss.detach().cpu().item():.4f}") + self.writer.add_scalar('loss', loss.detach().cpu().item(), global_step) + self.writer.add_scalar("lr", self.scheduler.get_last_lr()[0], global_step) + + global_step += 1 + epoch_loss += loss.detach().cpu().item() + progress_bar.set_postfix(loss=loss.detach().cpu().item()) + + if global_step % save_step == 0: + self.save_checkpoint(global_step) + self.writer.add_figure("mel/target", plot_spectrogram(mel_spec[0,:,:]), global_step) + self.writer.add_figure("mel/mask", plot_spectrogram(cond[0,:,:]), global_step) + self.writer.add_figure("mel/prediction", plot_spectrogram(pred_data[0,:,:]), global_step) + [self.evaluate(eval_dataloader, epoch+1, epochs, global_step) for eval_dataloader in eval_dataloaders] + + #if global_step % 10 == 0: + # torch.cuda.empty_cache() + + epoch_loss /= len(train_dataloader) + if self.accelerator.is_local_main_process: + logger.info(f"epoch {epoch+1}/{epochs} - average loss = {epoch_loss:.4f}") + self.writer.add_scalar('epoch average loss', epoch_loss, epoch) + + #if self.use_switch_ema: + # self.ema_model.update_model_with_ema() + + self.writer.close() + + +import json +import random +import pandas as pd +from e2_tts_pytorch import torch_tools + +DURATION = torch_tools.total_length +#DURATION = 3000 +#beta = 1.5960 +#theta = 0.3259 +cand = 99999999 + +class Text2AudioDataset(Dataset): + def __init__(self, dataset, part, prefix, text_column, audio_column, num_examples=-1, samples=-1, stft=None, augment=-1, main_process=True, SCORE_THRESHOLD_TRAIN="", train_file="", theta=0.0, vggsound=0, instruments=0, video_drop_prompt=None, audio_drop_prompt=None, device_id=0, vgg_test=None, video_encoder="clip_vit", val_length=None, num_processes=8): + + #inputs = list(dataset[text_column]) + #self.inputs = [prefix + inp for inp in inputs] + #self.audios = list(dataset[audio_column]) + #self.indices = list(range(len(self.inputs))) + # + #print("audios", len(self.audios)) + #self.new_audios = [] + #for index, audio in enumerate(self.audios): + # utt, fmt = audio.split(".") + # new_audio = "/zhanghaomin/datas/audioset_sl/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/AudioSet_SL_flac/" + utt + ".flac" + # #if os.path.exists(new_audio): + # self.new_audios.append(new_audio) + #self.audios = self.new_audios + #N = len(self.audios) + #print("audios", len(self.new_audios)) + + + test_final = "./tests/scps/tango-master/data/test_audiocaps_subset.json" + test_utts = {} + with open(test_final, "r") as fr: + for line in fr.readlines(): + wav = json.loads(line.strip())["location"] + utt = wav.rsplit("/", 1)[-1].rsplit("_", 1)[0] + utt = "Y"+utt + assert(utt not in test_utts) + test_utts[utt] = 1 + main_process and print("test_final", len(test_utts)) + + bbc_soundeffects_utts = {} + freesound_utts = {} + + audioset_filter_labels = {"Music": 0, "Speech": 0, "Vehicle": 0, "Musical instrument": 0} + + + self.inputs = [] + self.audios = [] + self.indices = [] + N = 0 + + + audiocaps = True + if SCORE_THRESHOLD_TRAIN["/zhanghaomin/datas/audiocaps"] >= 9000.0: + audiocaps = False + + audioset_sl = True + bbc_soundeffects = True + freesound = True + soundbible = True + if SCORE_THRESHOLD_TRAIN["/radiostorage/WavCaps"] >= 9000.0: + audioset_sl = False + bbc_soundeffects = False + freesound = False + soundbible = False + + soundeffects = True + if SCORE_THRESHOLD_TRAIN["/radiostorage/AudioGroup"] >= 9000.0: + soundeffects = False + self.soundeffects = soundeffects + + audioset = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/audioset"] >= 9000.0: + audioset = False + + bbc_soundeffects2 = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/BBCSoundEffects"] >= 9000.0: + bbc_soundeffects2 = False + + freesound2 = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/CLAP_freesound"] >= 9000.0: + freesound2 = False + + musiccaps = True + if SCORE_THRESHOLD_TRAIN["/zhanghaomin/datas/musiccap"] >= 9000.0: + musiccaps = False + + tangopromptbank = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/TangoPromptBank"] >= 9000.0: + tangopromptbank = False + + audioset_sl_2ch = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/audiosetsl"] >= 9000.0: + audioset_sl_2ch = False + self.audioset_sl_2ch = audioset_sl_2ch + + boom_epic = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/giantsoundeffects"] >= 9000.0: + boom_epic = False + self.boom_epic = boom_epic + + if isinstance(part, list): + part, scp_ac, start_ac, end_ac = part + assert(part == "val_audiocaps") + else: + scp_ac = None + + if (audioset_sl and part in ["train", "train_val_audioset_sl"]) or (part == "val_audioset_sl"): + self.audioset_sl_inputs = [] + self.audioset_sl_audios = [] + self.audioset_sl_indices = [] + audioset_sl_path_train = "/zhanghaomin/codes2/tango-master/data/train_audioset_sl.json" + audioset_sl_path_val = "/zhanghaomin/codes2/tango-master/data/val_audioset_sl.json" + audioset_sl_path_train_val = "./tests/scps/tango-master/data/train_val_audioset_sl.json" + if part == "train": + audioset_sl_path = audioset_sl_path_train + elif part == "train_val_audioset_sl": + audioset_sl_path = audioset_sl_path_train_val + else: + audioset_sl_path = audioset_sl_path_val + FN = 0 + with open(audioset_sl_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"].rsplit(".", 1)[0] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/AudioSet_SL/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/AudioSet_SL_flac/" + utt + ".flac" + self.audioset_sl_inputs.append(caption) + self.audioset_sl_audios.append(audio) + self.audioset_sl_indices.append(N + index) + main_process and print(part, "audioset_sl", len(self.audioset_sl_audios), "filtered", FN) + self.inputs.extend(self.audioset_sl_inputs) + self.audios.extend(self.audioset_sl_audios) + self.indices.extend(self.audioset_sl_indices) + N = len(self.audios) + main_process and print(part, "audioset_sl audios", len(self.audios)) + + if (audiocaps and part in ["train", "train_val_audioset_sl"]) or (part == "val_audiocaps"): + self.audiocaps_inputs = [] + self.audiocaps_audios = [] + self.audiocaps_indices = [] + audiocaps_path_train = "./tests/scps/tango-master/data/audiocaps/train_audiocaps.json" + audiocaps_path_val = "./tests/scps/tango-master/data/audiocaps/test_audiocaps.json" + if scp_ac is not None: + audiocaps_path_val = scp_ac + if part in ["train", "train_val_audioset_sl"]: + audiocaps_path = audiocaps_path_train + else: + audiocaps_path = audiocaps_path_val + FN = 0 + with open(audiocaps_path, "r") as fr: + lines = fr.readlines() + if scp_ac is not None: + lines = lines[start_ac: end_ac] + for index, line in enumerate(lines): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = jsondata["audio"] + self.audiocaps_inputs.append(caption) + self.audiocaps_audios.append(audio) + self.audiocaps_indices.append(N + index) + main_process and print(part, "audiocaps", len(self.audiocaps_audios), "filtered", FN) + self.inputs.extend(self.audiocaps_inputs) + self.audios.extend(self.audiocaps_audios) + self.indices.extend(self.audiocaps_indices) + N = len(self.audios) + main_process and print(part, "audiocaps audios", len(self.audios)) + + if bbc_soundeffects and part in ["train", "train_val_audioset_sl"]: + self.bbc_soundeffects_inputs = [] + self.bbc_soundeffects_audios = [] + self.bbc_soundeffects_indices = [] + with open("./tests/scps/tango-master/data/train_bbc_sound_effects.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + bbc_soundeffects_utts[utt] = 1 + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/BBC_Sound_Effects/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/BBC_Sound_Effects_flac/" + utt + ".flac" + self.bbc_soundeffects_inputs.append(caption) + self.bbc_soundeffects_audios.append(audio) + self.bbc_soundeffects_indices.append(N + index) + main_process and print(part, "bbc_soundeffects", len(self.bbc_soundeffects_audios)) + self.inputs.extend(self.bbc_soundeffects_inputs) + self.audios.extend(self.bbc_soundeffects_audios) + self.indices.extend(self.bbc_soundeffects_indices) + N = len(self.audios) + main_process and print(part, "bbc_soundeffects audios", len(self.audios)) + + if freesound and part in ["train", "train_val_audioset_sl"]: + self.freesound_inputs = [] + self.freesound_audios = [] + self.freesound_indices = [] + with open("./tests/scps/tango-master/data/train_freesound.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + freesound_utts[utt] = 1 + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/FreeSound/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/FreeSound_flac/" + utt + ".flac" + self.freesound_inputs.append(caption) + self.freesound_audios.append(audio) + self.freesound_indices.append(N + index) + main_process and print(part, "freesound", len(self.freesound_audios)) + self.inputs.extend(self.freesound_inputs) + self.audios.extend(self.freesound_audios) + self.indices.extend(self.freesound_indices) + N = len(self.audios) + main_process and print(part, "freesound audios", len(self.audios)) + + if soundbible and part in ["train", "train_val_audioset_sl"]: + self.soundbible_inputs = [] + self.soundbible_audios = [] + self.soundbible_indices = [] + with open("./tests/scps/tango-master/data/train_soundbible.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/SoundBible/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/SoundBible_flac/" + utt + ".flac" + self.soundbible_inputs.append(caption) + self.soundbible_audios.append(audio) + self.soundbible_indices.append(N + index) + main_process and print(part, "soundbible", len(self.soundbible_audios)) + self.inputs.extend(self.soundbible_inputs) + self.audios.extend(self.soundbible_audios) + self.indices.extend(self.soundbible_indices) + N = len(self.audios) + main_process and print(part, "soundbible audios", len(self.audios)) + + if (soundeffects and part in ["train", "train_val_audioset_sl"]) or (part == "val_soundeffects"): + self.soundeffects_inputs = [] + self.soundeffects_audios = [] + self.soundeffects_indices = [] + #soundeffects_path_train = "/zhanghaomin/codes2/audiocaption/wav_all_train.scp" + #soundeffects_path_val = "/zhanghaomin/codes2/audiocaption/wav_all_val.scp" + #soundeffects_path_train = "/zhanghaomin/codes2/audiocaption/wav_msclap_all_train.scp" + soundeffects_path_train = train_file + soundeffects_path_val = "/zhanghaomin/codes2/audiocaption/wav_msclap_all_val.scp" + if part in ["train", "train_val_audioset_sl"]: + soundeffects_path = soundeffects_path_train + else: + soundeffects_path = soundeffects_path_val + with open(soundeffects_path, 'r') as fr: + for index, line in enumerate(fr.readlines()): + if soundeffects_path.endswith("msclapcap_v1.list"): + utt, wav, caption1, score = line.strip().split('"@$&#"') + caption2 = "blank" + name = "blank" + else: + utt, wav, name, caption1, caption2 = line.strip().split('"@$&#"') + wav = wav.replace("/radiostorage/AudioGroup/", "/radiostorage/AudioGroup/") + period = int(utt.split('_')[-1]) + self.soundeffects_inputs.append((caption1, caption2, name)) + self.soundeffects_audios.append((wav, utt, period)) + self.soundeffects_indices.append(N + index) + main_process and print(part, "soundeffects", len(self.soundeffects_audios)) + self.inputs.extend(self.soundeffects_inputs) + self.audios.extend(self.soundeffects_audios) + self.indices.extend(self.soundeffects_indices) + N = len(self.audios) + main_process and print(part, "soundeffects audios", len(self.audios)) + + if audioset and part in ["train", "train_val_audioset_sl"]: + self.audioset_inputs = [] + self.audioset_audios = [] + self.audioset_indices = [] + FN = 0 + FN2 = 0 + if SCORE_THRESHOLD_TRAIN["audioset"] == "af-audioset": + audioset_path = "./tests/scps/audioset/audioset_train_af.json" + else: + audioset_path = "/ckptstorage/zhanghaomin/audioset/audioset_train.json" + with open(audioset_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + if SCORE_THRESHOLD_TRAIN["audioset"] == "af-audioset": + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = jsondata["audio"] + else: + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + #caption = caption.replace("@", ", ") + captions = caption.split("@") + captions_new = [] + for c in captions: + if c in audioset_filter_labels: + audioset_filter_labels[c] += 1 + else: + captions_new.append(c) + if len(captions_new) == 0: + FN2 += 1 + continue + caption = "".join(captions_new) + audio = jsondata["audio"] + self.audioset_inputs.append(caption) + self.audioset_audios.append(audio) + self.audioset_indices.append(N + index) + main_process and print(part, "audioset", len(self.audioset_audios), "filtered", FN, FN2, audioset_filter_labels) + self.inputs.extend(self.audioset_inputs) + self.audios.extend(self.audioset_audios) + self.indices.extend(self.audioset_indices) + N = len(self.audios) + main_process and print(part, "audioset audios", len(self.audios)) + + if bbc_soundeffects2 and part in ["train", "train_val_audioset_sl"]: + self.bbc_soundeffects2_inputs = [] + self.bbc_soundeffects2_audios = [] + self.bbc_soundeffects2_indices = [] + FN = 0 + with open("/ckptstorage/zhanghaomin/BBCSoundEffects/bbcsoundeffects_train.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in bbc_soundeffects_utts: + FN += 1 + continue + caption = jsondata["caption"] + caption = caption.split("(")[0].strip() + audio = jsondata["audio"] + self.bbc_soundeffects2_inputs.append(caption) + self.bbc_soundeffects2_audios.append(audio) + self.bbc_soundeffects2_indices.append(N + index) + main_process and print(part, "bbc_soundeffects2", len(self.bbc_soundeffects2_audios), "filtered", FN) + self.inputs.extend(self.bbc_soundeffects2_inputs) + self.audios.extend(self.bbc_soundeffects2_audios) + self.indices.extend(self.bbc_soundeffects2_indices) + N = len(self.audios) + main_process and print(part, "bbc_soundeffects2 audios", len(self.audios)) + + if freesound2 and part in ["train", "train_val_audioset_sl"]: + self.freesound2_inputs = [] + self.freesound2_audios = [] + self.freesound2_indices = [] + FN = 0 + with open("/ckptstorage/zhanghaomin/CLAP_freesound/freesound_train.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in freesound_utts: + FN += 1 + continue + caption = jsondata["caption"] + caption = caption.split('"@$&#"') + #caption = caption[0].split("(")[0].strip() + caption = tuple([c.split("(")[0].strip() for c in caption]) + audio = jsondata["audio"] + self.freesound2_inputs.append(caption) + self.freesound2_audios.append(audio) + self.freesound2_indices.append(N + index) + main_process and print(part, "freesound2", len(self.freesound2_audios), "filtered", FN) + self.inputs.extend(self.freesound2_inputs) + self.audios.extend(self.freesound2_audios) + self.indices.extend(self.freesound2_indices) + N = len(self.audios) + main_process and print(part, "freesound2 audios", len(self.audios)) + + if tangopromptbank and part in ["train", "train_val_audioset_sl"]: + self.tangopromptbank_inputs = [] + self.tangopromptbank_audios = [] + self.tangopromptbank_indices = [] + with open("./tests/scps/TangoPromptBank/data.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["captions"] + audio = jsondata["location"] + self.tangopromptbank_inputs.append(caption) + self.tangopromptbank_audios.append(audio) + self.tangopromptbank_indices.append(N + index) + main_process and print(part, "tangopromptbank", len(self.tangopromptbank_audios)) + self.inputs.extend(self.tangopromptbank_inputs) + self.audios.extend(self.tangopromptbank_audios) + self.indices.extend(self.tangopromptbank_indices) + N = len(self.audios) + main_process and print(part, "tangopromptbank audios", len(self.audios)) + + if musiccaps and part in ["train", "train_val_audioset_sl"]: + self.musiccaps_inputs = [] + self.musiccaps_audios = [] + self.musiccaps_indices = [] + with open("./tests/scps/musiccap/musiccaps.jsonl", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.musiccaps_inputs.append(caption) + self.musiccaps_audios.append(audio) + self.musiccaps_indices.append(N + index) + main_process and print(part, "musiccaps", len(self.musiccaps_audios)) + self.inputs.extend(self.musiccaps_inputs) + self.audios.extend(self.musiccaps_audios) + self.indices.extend(self.musiccaps_indices) + N = len(self.audios) + main_process and print(part, "musiccaps audios", len(self.audios)) + + if (audioset_sl_2ch and part in ["train", "train_val_audioset_sl"]) or (part == "val_audioset_sl_2ch"): + self.audioset_sl_2ch_inputs = [] + self.audioset_sl_2ch_audios = [] + self.audioset_sl_2ch_indices = [] + audioset_sl_2ch_train = "/ckptstorage/zhanghaomin/audiosetsl/wavs/train.jsonl" + audioset_sl_2ch_val = "/ckptstorage/zhanghaomin/audiosetsl/wavs/test.jsonl" + if part in ["train", "train_val_audioset_sl"]: + audioset_sl_2ch_path = audioset_sl_2ch_train + else: + audioset_sl_2ch_path = audioset_sl_2ch_val + with open(audioset_sl_2ch_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.audioset_sl_2ch_inputs.append(caption) + self.audioset_sl_2ch_audios.append(audio) + self.audioset_sl_2ch_indices.append(N + index) + main_process and print(part, "audioset_sl_2ch", len(self.audioset_sl_2ch_audios)) + self.inputs.extend(self.audioset_sl_2ch_inputs) + self.audios.extend(self.audioset_sl_2ch_audios) + self.indices.extend(self.audioset_sl_2ch_indices) + N = len(self.audios) + main_process and print(part, "audioset_sl_2ch audios", len(self.audios)) + + if (boom_epic and part in ["train", "train_val_audioset_sl"]) or (part == "val_boom_epic"): + self.boom_epic_inputs = [] + self.boom_epic_audios = [] + self.boom_epic_indices = [] + #boom_epic_train = "/ckptstorage/zhanghaomin/giantsoundeffects/train_animals_mixture2.jsonl" + #boom_epic_val = "/ckptstorage/zhanghaomin/giantsoundeffects/test_animals_mixture2.jsonl" + boom_epic_train = "./tests/scps/giantsoundeffects/train.jsonl" + boom_epic_val = "./tests/scps/giantsoundeffects/test.jsonl" + if part in ["train", "train_val_audioset_sl"]: + boom_epic_path = boom_epic_train + else: + boom_epic_path = boom_epic_val + with open(boom_epic_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.boom_epic_inputs.append(caption) + self.boom_epic_audios.append(audio) + self.boom_epic_indices.append(N + index) + main_process and print(part, "boom_epic", len(self.boom_epic_audios)) + repeats = 1 + for _ in range(repeats): + self.inputs.extend(self.boom_epic_inputs) + self.audios.extend(self.boom_epic_audios) + self.indices.extend(self.boom_epic_indices) + N = len(self.audios) + main_process and print(part, "boom_epic audios", len(self.audios)) + self.boom_epic = boom_epic + + if vggsound: + self.inputs_vggsound = [] + self.audios_vggsound = [] + self.indices_vggsound = [] + if part in ["train", "train_val_audioset_sl"]: + path = "./tests/scps/VGGSound/train.scp" + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()): + video_path, text = line.strip().split("\t") + self.inputs_vggsound.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios_vggsound.append(video_path) + self.indices_vggsound.append(index) + N = len(self.audios_vggsound) + print(part, "vggsound train audios", len(self.audios_vggsound), device_id, num_processes) + elif part == "val_vggsound": + if vgg_test is not None: + path = vgg_test[0] + start = vgg_test[1] + end = vgg_test[2] + step = vgg_test[3] + else: + path = "./tests/scps/VGGSound/test.scp" + start = 0 + end = 200 + step = 1 + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()[start:end:step]): + video_path, text = line.strip().split("\t") + self.inputs.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios.append(video_path) + self.indices.append(N + index) + N = len(self.audios) + print(part, "vggsound eval audios", len(self.audios), device_id, num_processes) + + if instruments: + self.inputs_instruments = [] + self.audios_instruments = [] + self.indices_instruments = [] + if part in ["train", "train_val_audioset_sl"]: + ####path = "./tests/scps/instruments/train.scp" + ####path = "./tests/scps/instruments/piano_2h/train.scp" + path = "./tests/scps/instruments/piano_20h/v2a_giant_piano2/train.scp" + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()): + video_path, text = line.strip().split("\t") + self.inputs_instruments.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios_instruments.append(video_path) + self.indices_instruments.append(index) + N = len(self.audios_instruments) + print(part, "instruments train audios", len(self.audios_instruments), device_id, num_processes) + elif part == "val_instruments": + if vgg_test is not None: + path = vgg_test[0] + start = vgg_test[1] + end = vgg_test[2] + step = vgg_test[3] + else: + ####path = "./tests/scps/instruments/test.scp" + ####path = "./tests/scps/instruments/piano_2h/test.scp" + path = "./tests/scps/instruments/piano_20h/v2a_giant_piano2/test.scp" + start = 0 + end = 200 + step = 1 + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()[start:end:step]): + video_path, text = line.strip().split("\t") + self.inputs.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios.append(video_path) + self.indices.append(N + index) + N = len(self.audios) + print(part, "instruments eval audios", len(self.audios), device_id, num_processes) + + self.vggsound = vggsound + self.instruments = instruments + self.video_drop_prompt = video_drop_prompt + self.audio_drop_prompt = audio_drop_prompt + self.device_id = device_id + self.num_processes = num_processes + self.bad_ids = {} + self.bad_ids_instruments = {} + self.video_encoder = video_encoder + self.val_length = val_length if val_length is not None else torch_tools.MAX_TARGET_LEN + print("val_length", self.val_length) + + #self.mapper = {} + #for index, audio, text in zip(self.indices, self.audios, self.inputs): + # self.mapper[index] = [audio, text] + + if num_examples != -1: + self.inputs, self.audios = self.inputs[:num_examples], self.audios[:num_examples] + self.indices = self.indices[:num_examples] + + self.samples = samples + self.stft = stft + self.target_length = DURATION + self.augment = augment + self.part = part + self.main_process = main_process + self.SCORE_THRESHOLD_TRAIN = SCORE_THRESHOLD_TRAIN + self.theta = theta + self.multi = 4 + + def __len__(self): + return len(self.inputs) + + def get_num_instances(self): + return len(self.inputs) + + def __getitem__(self, index): + s1, s2, s3 = self.inputs[index], self.audios[index], self.indices[index] + return s1, s2, s3 + + def read_audio_from_video(self, video_path): + if video_path.startswith("/ailab-train2/speech/zhanghaomin/VGGSound/"): + audio_path = video_path.replace("/video/", "/audio/").replace(".mp4", ".wav") + else: + audio_path = video_path.replace(".mp4", ".generated.wav") + if os.path.exists(audio_path): + #print("video wav exist", audio_path) + waveform, sr = torchaudio.load(audio_path) + else: + #print("video wav not exist", video_path) + try: + clip = AudioFileClip(video_path) + sound_array = np.array(list(clip.iter_frames())) + waveform = torch.from_numpy(sound_array).transpose(0,1).to(torch.float32) + waveform = waveform[0:1, :] + if clip.fps != torch_tools.new_freq: + waveform = torchaudio.functional.resample(waveform, orig_freq=clip.fps, new_freq=torch_tools.new_freq) + waveform = torch_tools.normalize_wav(waveform) + torchaudio.save(audio_path, waveform, torch_tools.new_freq) + except: + print("Error read_audio_from_video", audio_path) + traceback.print_exc() + return None + return waveform + + def collate_fn(self, data): + # 452463+1471396->452463+3430704->452463+2978587 more 452463+1037241+15973+310169 real 1183416+2000 + # theta (1183416)*0.5/(452463+1037241+15973+310169)=0.3259 + # beta (452463+1037241+15973+310169+3430704)/(452463+1037241+15973+310169+1471396)=1.5960 (452463+1037241+15973+310169+2978587)/(452463+1037241+15973+310169+1471396)=1.4585 + if self.part in ["train", "train_val_audioset_sl"]: + val = False + else: + val = True + if self.audioset_sl_2ch: + nch = 2 + else: + nch = 1 + while True: + if self.part in ["train", "train_val_audioset_sl"]: + #print("data raw", len(data), data[0]) + #data_sampled = random.sample(data, self.samples) + + if (self.soundeffects or self.boom_epic) and self.theta > 0: + data_len = len(data) + data_1 = [] + data_2 = [] + for sample in data: + if isinstance(sample[1], tuple): + if sample[1][0].startswith("/radiostorage/"): + prefix = "/".join(sample[1][0].split("/")[:3]) + else: + prefix = "/".join(sample[1][0].split("/")[:4]) + else: + if sample[1].startswith("/radiostorage/"): + prefix = "/".join(sample[1].split("/")[:3]) + else: + prefix = "/".join(sample[1].split("/")[:4]) + if torch_tools.SOUNDEFFECT[prefix]: + data_2.append(sample) + else: + data_1.append(sample) + #print("data splitted", len(data_1), len(data_2), float(len(data_1))/len(data_2)) + data_len_1 = len(data_1) + data_len_2 = len(data_2) + if data_len_1 == 0 or data_len_2 == 0: + data_1_sampled = data_1 + data_2_sampled = data_2 + else: + data_len_1_sampled = int(data_len_2 / self.theta) + data_len_2_sampled = int(data_len_1 * self.theta) + if data_len_1_sampled < data_len_1: + data_1_sampled = random.sample(data_1, data_len_1_sampled) + data_2_sampled = data_2 + else: + data_1_sampled = data_1 + data_2_sampled = random.sample(data_2, data_len_2_sampled) + #print("data sampled", len(data_1_sampled), len(data_2_sampled), float(len(data_1_sampled))/len(data_2_sampled), self.samples*cand) + data_sampled = data_1_sampled + data_sampled.extend(data_2_sampled) + data_sampled = random.sample(data_sampled, min(self.samples*cand, len(data_sampled))) + #print("data sampled", len(data_sampled)) + else: + data_sampled = random.sample(data, min(self.samples*cand, len(data))) + #print("data sampled", len(data_sampled)) + else: + data_sampled = data + dat = pd.DataFrame(data_sampled) + text, audios, indices = [dat[i].tolist() for i in dat] + + if self.vggsound and val and self.part in ["val_vggsound", "val_instruments"]: + #print("vggsound val", len(audios), text) + fbanks = [] + fbank_lens = [] + video_paths = [] + text_selected = [] + for audio, txt in zip(audios, text): + waveform = self.read_audio_from_video(audio) + if waveform is None: + continue + length = self.val_length + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + video_paths.append(audio) + text_selected.append(txt) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + mel = torch.cat(fbanks, 0) + mel_len = torch.Tensor(fbank_lens).to(torch.int32) + break + + if_clap_filter = False + if self.part in ["val_audiocaps", "val_audioset_sl_2ch", "val_boom_epic"]: + if_clap_filter = False + mel, text_selected, _, _, _, mel_len = torch_tools.wav_to_fbank(audios, text, self.samples, self.target_length, self.stft, val, if_clap_filter, self.main_process, self.SCORE_THRESHOLD_TRAIN, nch) + if mel is not None: + if self.part in ["train", "train_val_audioset_sl"]: + if len(text_selected) > self.samples: + mel = mel[:self.samples,...] + text_selected = text_selected[:self.samples] + #waveform = waveform[:self.samples,...] + mel_len = mel_len[:self.samples] + if self.vggsound: + video_paths = [None] * len(text_selected) + else: + video_paths = None + #print("mel", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + break + + #mel = mel.unsqueeze(1) + if self.augment != 0 and len(text_selected) > 1 and (not val): + aug_num = len(text_selected) if self.augment == -1 else self.augment + # the last batch of the training data may have only one instance + # we check the length here so that the augmentation function doesn't throw an error + mixed_mel, _, _, mixed_captions, _, mixed_mel_len = torch_tools.augment_wav_to_fbank(audios, text, aug_num, self.target_length, self.stft, self.main_process, self.SCORE_THRESHOLD_TRAIN, nch) + #print("mixed_mel", mixed_mel.shape if mixed_mel is not None else None, len(mixed_captions) if mixed_captions is not None else 0, mixed_mel_len) + if mixed_mel is not None: + if mel.shape[1] < mixed_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], mixed_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif mixed_mel.shape[1] < mel.shape[1]: + mixed_mel = torch.cat([mixed_mel, torch.zeros(mixed_mel.shape[0], mel.shape[1]-mixed_mel.shape[1], mixed_mel.shape[2])], 1) + #mixed_mel = mixed_mel.unsqueeze(1) + mel = torch.cat([mel, mixed_mel], 0) + text_selected += mixed_captions + mel_len = torch.cat([mel_len, mixed_mel_len], 0) + if self.vggsound: + video_paths.extend([None] * len(mixed_captions)) + else: + video_paths = None + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len) + + if self.vggsound and (not val): + video_paths = [None] * len(text_selected) + fbanks = [] + fbank_lens = [] + audios = [] + video_captions = [] + indices = random.sample([self.indices_vggsound[i] for i in range(self.device_id, len(self.indices_vggsound), self.num_processes)], self.vggsound*10) + indices_featured = [] + indices_nonfeatured = [] + for i in indices: + if i in self.bad_ids: + continue + if self.audios_vggsound[i].startswith("/ailab-train2/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + if os.path.exists(feature_path): + indices_featured.append(i) + else: + indices_nonfeatured.append(i) + if len(indices_nonfeatured) >= self.vggsound: + break + #print(self.device_id, self.bad_ids, indices, indices_featured, indices_nonfeatured) + indices = indices_nonfeatured[:self.vggsound] + if len(indices) < self.vggsound: + indices.extend(indices_featured[:self.vggsound-len(indices)]) + for i in indices: + waveform = self.read_audio_from_video(self.audios_vggsound[i]) + if waveform is None: + print("Error audio in video", i, self.audios_vggsound[i], self.bad_ids) + self.bad_ids[i] = 1 + continue + length = random.randint(torch_tools.MIN_TARGET_LEN, torch_tools.MAX_TARGET_LEN) + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + audios.append(self.audios_vggsound[i]) + video_captions.append(self.inputs_vggsound[i]) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + video_mel = torch.cat(fbanks, 0) + video_mel_len = torch.Tensor(fbank_lens).to(torch.int32) + #print("video_mel", video_mel.shape if video_mel is not None else None, len(video_captions) if video_captions is not None else 0, video_mel_len) + if video_mel is not None: + if mel.shape[1] < video_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], video_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif video_mel.shape[1] < mel.shape[1]: + video_mel = torch.cat([video_mel, torch.zeros(video_mel.shape[0], mel.shape[1]-video_mel.shape[1], video_mel.shape[2])], 1) + #video_mel = video_mel.unsqueeze(1) + mel = torch.cat([mel, video_mel], 0) + text_selected += video_captions + mel_len = torch.cat([mel_len, video_mel_len], 0) + video_paths.extend(audios) + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + + if self.instruments and (not val): + fbanks = [] + fbank_lens = [] + audios = [] + video_captions = [] + indices = random.sample([self.indices_instruments[i] for i in range(self.device_id, len(self.indices_instruments), self.num_processes)], self.instruments*10) + indices_featured = [] + indices_nonfeatured = [] + for i in indices: + if i in self.bad_ids_instruments: + continue + if self.audios_instruments[i].startswith("/ailab-train2/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = self.audios_instruments[i].replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_instruments[i].replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_instruments[i].replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_instruments[i].replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_instruments[i].replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_instruments[i].replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + if os.path.exists(feature_path): + indices_featured.append(i) + else: + indices_nonfeatured.append(i) + if len(indices_nonfeatured) >= self.instruments: + break + #print(self.device_id, self.bad_ids_instruments, indices, indices_featured, indices_nonfeatured) + indices = indices_nonfeatured[:self.instruments] + if len(indices) < self.instruments: + indices.extend(indices_featured[:self.instruments-len(indices)]) + #### dpo + ####a_indices = [] + ####b_indices = [] + ####for i in indices[:len(indices)//2]: + #### path, name = self.audios_instruments[i].rsplit("/", 1) + #### assert(name[0] in ["a", "b"]) + #### for j, p in enumerate(self.audios_instruments): + #### if p == path + "/a" + name[1:]: + #### a_indices.append(j) + #### elif p == path + "/b" + name[1:]: + #### b_indices.append(j) + ####indices = a_indices + b_indices + #### dpo + for i in indices: + waveform = self.read_audio_from_video(self.audios_instruments[i]) + if waveform is None: + print("Error audio in video instruments", i, self.audios_instruments[i], self.bad_ids_instruments) + self.bad_ids_instruments[i] = 1 + continue + length = random.randint(torch_tools.MIN_TARGET_LEN, torch_tools.MAX_TARGET_LEN) + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + audios.append(self.audios_instruments[i]) + video_captions.append(self.inputs_instruments[i]) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + video_mel = torch.cat(fbanks, 0) + video_mel_len = torch.Tensor(fbank_lens).to(torch.int32) + #print("video_mel", video_mel.shape if video_mel is not None else None, len(video_captions) if video_captions is not None else 0, video_mel_len) + if video_mel is not None: + if mel.shape[1] < video_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], video_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif video_mel.shape[1] < mel.shape[1]: + video_mel = torch.cat([video_mel, torch.zeros(video_mel.shape[0], mel.shape[1]-video_mel.shape[1], video_mel.shape[2])], 1) + #video_mel = video_mel.unsqueeze(1) + mel = torch.cat([mel, video_mel], 0) + text_selected += video_captions + mel_len = torch.cat([mel_len, video_mel_len], 0) + video_paths.extend(audios) + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + + #### + text_selected = [" ".join(text.split(" ")[:20]) for text in text_selected] + + #### + if not val: + ####T = 8 + T = 5 + ####T = 2 + text_selected = text_selected[-T:] + mel = mel[-T:,...] + video_paths = video_paths[-T:] + mel_len = mel_len[-T:,...] + self.video_drop_prompt = self.video_drop_prompt[-T:] + self.audio_drop_prompt = self.audio_drop_prompt[-T:] if self.audio_drop_prompt is not None else None + + frames, midis = E2TTS.encode_video_frames(video_paths, mel.shape[1]) + return [text_selected, mel, video_paths, mel_len, self.video_drop_prompt, self.audio_drop_prompt, frames, midis] + + +class Text2SpeechDataset(Dataset): + def __init__(self, samples=-1, stft=None, val=False): + self.inputs = [] + self.audios = [] + self.indices = [] + + train_scp = "/ckptstorage/zhanghaomin/docker/ximalaya/ximalaya_process/data_scp/train.json" + test_scp = "/ckptstorage/zhanghaomin/docker/ximalaya/ximalaya_process/data_scp/test.json" + scp = train_scp if not val else test_scp + index = 0 + with open(scp, "r") as fr: + for line in fr.readlines(): + data = json.loads(line.strip()) + wav = data["wav"] + text = data["text"] + if len(text) < 2: + continue + self.inputs.append(text) + self.audios.append(wav) + self.indices.append(index) + index += 1 + print("data size", len(self.inputs), val) + self.samples = samples + self.stft = stft + self.sample_rate = 24000 + self.multi = 8 + self.val = val + + def __len__(self): + return len(self.inputs) + + def get_num_instances(self): + return len(self.inputs) + + def __getitem__(self, index): + s1, s2, s3 = self.inputs[index], self.audios[index], self.indices[index] + return s1, s2, s3 + + def collate_fn(self, data): + dat = pd.DataFrame(data) + texts, audios, indices = [dat[i].tolist() for i in dat] + + fbanks = [] + fbank_lens = [] + text_selected = [] + for text, audio in zip(texts, audios): + waveform, sr = torchaudio.load(audio) + waveform = waveform[0:1, :] + if sr != self.sample_rate: + waveform = torchaudio.functional.resample(waveform, orig_freq=sr, new_freq=self.sample_rate) + waveform = torch_tools.normalize_wav(waveform) + fbank = self.stft(waveform).transpose(-1,-2) + #print("stft", waveform.shape, fbank.shape) + if self.val: + if waveform.shape[1] / float(self.sample_rate) < 2.0 or waveform.shape[1] / float(self.sample_rate) > 15.0: + continue + else: + if waveform.shape[1] / float(self.sample_rate) < 1.0 or waveform.shape[1] / float(self.sample_rate) > 20.0: + continue + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + text_selected.append(text) + if self.samples > 0 and len(text_selected) >= self.samples: + break + if self.samples > 0 and len(text_selected) > self.samples: + fbanks = fbanks[:self.samples] + fbank_lens = fbank_lens[:self.samples] + text_selected = text_selected[:self.samples] + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + mel = torch.cat(fbanks, 0) + mel_len = torch.Tensor(fbank_lens).to(torch.int32) + return [text_selected, mel, None, mel_len, None] + diff --git a/src/e2_tts_pytorch/trainer_multigpus_alldatas6.py b/src/e2_tts_pytorch/trainer_multigpus_alldatas6.py new file mode 100644 index 0000000000000000000000000000000000000000..8fe9367622f642904c19ff392543cd1dc3fa1ea9 --- /dev/null +++ b/src/e2_tts_pytorch/trainer_multigpus_alldatas6.py @@ -0,0 +1,1246 @@ +from __future__ import annotations + +import os +from tqdm import tqdm +import matplotlib +matplotlib.use("Agg") +import matplotlib.pylab as plt + +import torch +import torch.nn.functional as F +from torch.utils.data import DataLoader, Dataset +from torch.utils.tensorboard import SummaryWriter +from torch.optim.lr_scheduler import LinearLR, SequentialLR + +import torchaudio + +from einops import rearrange + +from accelerate import Accelerator +from accelerate.utils import DistributedDataParallelKwargs + +from ema_pytorch import EMA + +from loguru import logger + +from e2_tts_pytorch.e2_tts_crossatt6 import ( + E2TTS, + DurationPredictor, + MelSpec +) + +import traceback +import numpy as np +from moviepy.editor import AudioFileClip, VideoFileClip + +def exists(v): + return v is not None + +def default(v, d): + return v if exists(v) else d + +def to_numpy(t): + return t.detach().cpu().numpy() + +# plot spectrogram + +def plot_spectrogram(spectrogram): + spectrogram = to_numpy(spectrogram) + fig, ax = plt.subplots(figsize=(10, 4)) + im = ax.imshow(spectrogram.T, aspect="auto", origin="lower", interpolation="none") + plt.colorbar(im, ax=ax) + plt.xlabel("Frames") + plt.ylabel("Channels") + plt.tight_layout() + + fig.canvas.draw() + plt.close() + return fig + +# collation + +def collate_fn(batch): + mel_specs = [item['mel_spec'].squeeze(0) for item in batch] + mel_lengths = torch.LongTensor([spec.shape[-1] for spec in mel_specs]) + max_mel_length = mel_lengths.amax() + + padded_mel_specs = [] + for spec in mel_specs: + padding = (0, max_mel_length - spec.size(-1)) + padded_spec = F.pad(spec, padding, value = 0) + padded_mel_specs.append(padded_spec) + + mel_specs = torch.stack(padded_mel_specs) + + text = [item['text'] for item in batch] + text_lengths = torch.LongTensor([len(item) for item in text]) + + return dict( + mel = mel_specs, + mel_lengths = mel_lengths, + text = text, + text_lengths = text_lengths, + ) + +# dataset + +class HFDataset(Dataset): + def __init__( + self, + hf_dataset: Dataset, + target_sample_rate = 24_000, + hop_length = 256 + ): + self.data = hf_dataset + self.target_sample_rate = target_sample_rate + self.hop_length = hop_length + self.mel_spectrogram = MelSpec(sampling_rate=target_sample_rate) + + def __len__(self): + return len(self.data) + + def __getitem__(self, index): + row = self.data[index] + audio = row['audio']['array'] + + #logger.info(f"Audio shape: {audio.shape}") + + sample_rate = row['audio']['sampling_rate'] + duration = audio.shape[-1] / sample_rate + + if duration > 20 or duration < 0.3: + logger.warning(f"Skipping due to duration out of bound: {duration}") + return self.__getitem__((index + 1) % len(self.data)) + + audio_tensor = torch.from_numpy(audio).float() + + if sample_rate != self.target_sample_rate: + resampler = torchaudio.transforms.Resample(sample_rate, self.target_sample_rate) + audio_tensor = resampler(audio_tensor) + + audio_tensor = rearrange(audio_tensor, 't -> 1 t') + + mel_spec = self.mel_spectrogram(audio_tensor) + + mel_spec = rearrange(mel_spec, '1 d t -> d t') + + text = row['transcript'] + + return dict( + mel_spec = mel_spec, + text = text, + ) + +# trainer + +class E2Trainer: + def __init__( + self, + model: E2TTS, + optimizer, + num_warmup_steps=20000, + grad_accumulation_steps=1, + duration_predictor: DurationPredictor | None = None, + checkpoint_path = None, + log_file = "logs.txt", + max_grad_norm = 1.0, + sample_rate = 22050, + tensorboard_log_dir = 'runs/e2_tts_experiment', + accelerate_kwargs: dict = dict(), + ema_kwargs: dict = dict(), + use_switch_ema = False, + if_text = False, + if_prompt = False + ): + logger.add(log_file) + + ddp_kwargs = DistributedDataParallelKwargs(find_unused_parameters = True) + + self.accelerator = Accelerator( + log_with = "all", + kwargs_handlers = [ddp_kwargs], + gradient_accumulation_steps = grad_accumulation_steps, + **accelerate_kwargs + ) + self.accelerator.wait_for_everyone() + + self.target_sample_rate = sample_rate + + self.model = model + + self.need_velocity_consistent_loss = model.velocity_consistency_weight > 0. + + #self.ema_model = EMA( + # model, + # include_online_model = False, + # **ema_kwargs + #) + + self.use_switch_ema = use_switch_ema + + self.duration_predictor = duration_predictor + self.optimizer = optimizer + self.num_warmup_steps = num_warmup_steps + self.checkpoint_path = default(checkpoint_path, 'model.pth') + self.mel_spectrogram = MelSpec(sampling_rate=self.target_sample_rate) + + self.model, self.optimizer = self.accelerator.prepare( + self.model, self.optimizer + ) + #self.ema_model = self.accelerator.prepare(self.ema_model) + self.max_grad_norm = max_grad_norm + + self.writer = SummaryWriter(log_dir=tensorboard_log_dir) + self.tensorboard_log_dir = tensorboard_log_dir + self.if_text = if_text + self.if_prompt = if_prompt + + self.device_id = self.accelerator.device.index + self.num_processes = self.accelerator.num_processes + + @property + def is_main(self): + return self.accelerator.is_main_process + + def save_checkpoint(self, step, finetune=False): + self.accelerator.wait_for_everyone() + if self.is_main: + checkpoint = dict( + model_state_dict = self.accelerator.unwrap_model(self.model).state_dict(), + #optimizer_state_dict = self.accelerator.unwrap_model(self.optimizer).state_dict(), + #ema_model_state_dict = self.ema_model.state_dict(), + #scheduler_state_dict = self.scheduler.state_dict(), + #step = step, + ) + + self.accelerator.save(checkpoint, self.tensorboard_log_dir + "/" + str(step) + ".pt") + + def load_checkpoint(self): + if not exists(self.checkpoint_path) or not os.path.exists(self.checkpoint_path): + return 0 + + checkpoint = torch.load(self.checkpoint_path, map_location='cpu') + for key in list(checkpoint['model_state_dict'].keys()): + #if key.startswith('mel_spec.'): + # del checkpoint['model_state_dict'][key] + if key.startswith('transformer.text_registers'): + if checkpoint['model_state_dict'][key].shape[1] != self.accelerator.unwrap_model(self.model).transformer.text_registers.shape[1]: + print('miss match: transformer.text_registers', checkpoint['model_state_dict'][key].shape, self.accelerator.unwrap_model(self.model).transformer.text_registers.shape) + del checkpoint['model_state_dict'][key] + self.accelerator.unwrap_model(self.model).load_state_dict(checkpoint['model_state_dict'], strict=False) + #self.accelerator.unwrap_model(self.optimizer).load_state_dict(checkpoint['optimizer_state_dict']) + + #if self.is_main: + # self.ema_model.load_state_dict(checkpoint['ema_model_state_dict']) + + #if self.scheduler: + # self.scheduler.load_state_dict(checkpoint['scheduler_state_dict']) + #return checkpoint['step'] + return 0 + + def evaluate(self, eval_dataloader, epoch, epochs, global_step): + if eval_dataloader is None: + return + + total_val_loss, N, total_lossmore1, total_lossmore2 = 0, 0, 0, 0 + self.model.eval() + eval_progress_bar = tqdm(eval_dataloader, desc=f"Epoch {epoch}/{epochs}", unit="step", disable=not self.accelerator.is_local_main_process) + for step, batch in enumerate(eval_dataloader): + with self.accelerator.accumulate(self.model) and torch.no_grad(): + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt = batch + + val_loss, cond, pred, pred_data, lossmore = self.model( + mel_spec, + text=(text if self.if_text else None), + times=0.5, + lens=mel_lengths, + velocity_consistency_model=None, + prompt=(text if self.if_prompt else None), + video_drop_prompt=video_drop_prompt, + audio_drop_prompt=audio_drop_prompt, + val=True, + video_paths=video_paths + ) + a = torch.tensor(val_loss.item()*len(text), dtype=torch.float32).reshape(1).to(val_loss.device) + b = torch.tensor(len(text), dtype=torch.int32).reshape(1).to(val_loss.device) + c = torch.tensor(lossmore[0].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[0].device) + d = torch.tensor(lossmore[1].item()*len(text), dtype=torch.float32).reshape(1).to(lossmore[1].device) + val_loss_gather, N_gather, lossmore_gather1, lossmore_gather2 = self.accelerator.gather_for_metrics((a, b, c, d)) + for i in range(val_loss_gather.shape[0]): + total_val_loss += val_loss_gather[i].item() + N += N_gather[i].item() + total_lossmore1 += lossmore_gather1[i].item() + total_lossmore2 += lossmore_gather2[i].item() + eval_progress_bar.update(1) + + if self.accelerator.is_local_main_process: + total_val_loss = round(total_val_loss/float(N), 4) + total_lossmore1 = round(total_lossmore1/float(N), 4) + total_lossmore2 = round(total_lossmore2/float(N), 4) + result_string = "Epoch: {}, GlobalStep: {}, ValLoss: {}, N: {}, Lossmore1: {}, Lossmore2: {} (average loss)\n".format(epoch, global_step, total_val_loss, N, total_lossmore1, total_lossmore2) + logger.info(result_string) + + torch.cuda.empty_cache() + + def train(self, datasets, epochs, batch_size, num_workers=12, save_step=1000): + + params_d = {} + trainable_d = {} + for n, p in self.model.named_parameters(): + key = ".".join(n.split(".")[:2]) + if key not in params_d: + params_d[key] = 0 + trainable_d[key] = p.requires_grad + params_d[key] += p.numel() + assert(trainable_d[key] == p.requires_grad) + print(params_d) + print(trainable_d) + num_trainable_parameters = sum(p.numel() for p in self.model.parameters() if p.requires_grad) + print("Num trainable parameters: {}".format(num_trainable_parameters)) + + train_dataset = datasets[0] + eval_datasets = datasets[1:] + #train_dataloader = DataLoader(train_dataset, batch_size=batch_size, collate_fn=collate_fn, shuffle=True, num_workers=num_workers, pin_memory=True) + train_dataloader = DataLoader(train_dataset, shuffle=True, batch_size=batch_size*train_dataset.multi, collate_fn=train_dataset.collate_fn, num_workers=num_workers, drop_last=True, pin_memory=True) + eval_dataloaders = [DataLoader(eval_dataset, shuffle=False, batch_size=16, collate_fn=eval_dataset.collate_fn, num_workers=num_workers, drop_last=False, pin_memory=True) if eval_dataset is not None else None for eval_dataset in eval_datasets] + + total_steps = len(train_dataloader) * epochs + decay_steps = total_steps - self.num_warmup_steps + warmup_scheduler = LinearLR(self.optimizer, start_factor=1e-8, end_factor=1.0, total_iters=self.num_warmup_steps) + decay_scheduler = LinearLR(self.optimizer, start_factor=1.0, end_factor=1e-8, total_iters=decay_steps) + self.scheduler = SequentialLR(self.optimizer, + schedulers=[warmup_scheduler, decay_scheduler], + milestones=[self.num_warmup_steps]) + train_dataloader, self.scheduler = self.accelerator.prepare(train_dataloader, self.scheduler) + eval_dataloaders = [self.accelerator.prepare(eval_dataloader) for eval_dataloader in eval_dataloaders if eval_dataloader is not None] + start_step = self.load_checkpoint() + global_step = start_step + + for epoch in range(epochs): + + if epoch == 0: + [self.evaluate(eval_dataloader, 1, epochs, 0) for eval_dataloader in eval_dataloaders] + + self.model.train() + progress_bar = tqdm(train_dataloader, desc=f"Epoch {epoch+1}/{epochs}", unit="step", disable=not self.accelerator.is_local_main_process) + epoch_loss = 0.0 + + for batch in progress_bar: + with self.accelerator.accumulate(self.model): + #text_inputs = batch['text'] + #mel_spec = rearrange(batch['mel'], 'b d n -> b n d') + #mel_lengths = batch["mel_lengths"] + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt = batch + #print("batchsize", len(text)) + #print("batch", text, mel_spec.shape, video_paths, mel_lengths) + + if exists(self.duration_predictor): + dur_loss = self.duration_predictor(mel_spec, lens=batch.get('durations')) + self.writer.add_scalar('duration loss', dur_loss.detach().cpu().item(), global_step) + + velocity_consistency_model = None + #if self.need_velocity_consistent_loss and self.ema_model.initted: + # velocity_consistency_model = self.accelerator.unwrap_model(self.ema_model).ema_model + + loss, cond, pred, pred_data, lossmore = self.model( + mel_spec, + text=(text if self.if_text else None), + lens=mel_lengths, + velocity_consistency_model=velocity_consistency_model, + prompt=(text if self.if_prompt else None), + video_drop_prompt=video_drop_prompt, + audio_drop_prompt=audio_drop_prompt, + video_paths=video_paths + ) + + self.accelerator.backward(loss) + + if self.max_grad_norm > 0 and self.accelerator.sync_gradients: + self.accelerator.clip_grad_norm_(self.model.parameters(), self.max_grad_norm) + + self.optimizer.step() + self.scheduler.step() + self.optimizer.zero_grad() + + #self.accelerator.unwrap_model(self.ema_model).update() + + if self.accelerator.is_local_main_process: + logger.info(f"step {global_step+1}: loss = {loss.detach().cpu().item():.4f}") + self.writer.add_scalar('loss', loss.detach().cpu().item(), global_step) + self.writer.add_scalar("lr", self.scheduler.get_last_lr()[0], global_step) + + global_step += 1 + epoch_loss += loss.detach().cpu().item() + progress_bar.set_postfix(loss=loss.detach().cpu().item()) + + if global_step % save_step == 0: + self.save_checkpoint(global_step) + self.writer.add_figure("mel/target", plot_spectrogram(mel_spec[0,:,:]), global_step) + self.writer.add_figure("mel/mask", plot_spectrogram(cond[0,:,:]), global_step) + self.writer.add_figure("mel/prediction", plot_spectrogram(pred_data[0,:,:]), global_step) + [self.evaluate(eval_dataloader, epoch+1, epochs, global_step) for eval_dataloader in eval_dataloaders] + + #if global_step % 10 == 0: + # torch.cuda.empty_cache() + + epoch_loss /= len(train_dataloader) + if self.accelerator.is_local_main_process: + logger.info(f"epoch {epoch+1}/{epochs} - average loss = {epoch_loss:.4f}") + self.writer.add_scalar('epoch average loss', epoch_loss, epoch) + + #if self.use_switch_ema: + # self.ema_model.update_model_with_ema() + + self.writer.close() + + +import json +import random +import pandas as pd +from e2_tts_pytorch import torch_tools + +DURATION = torch_tools.total_length +#DURATION = 3000 +#beta = 1.5960 +#theta = 0.3259 +cand = 99999999 + +class Text2AudioDataset(Dataset): + def __init__(self, dataset, part, prefix, text_column, audio_column, num_examples=-1, samples=-1, stft=None, augment=-1, main_process=True, SCORE_THRESHOLD_TRAIN="", train_file="", theta=0.0, vggsound=0, video_drop_prompt=None, audio_drop_prompt=None, device_id=0, vgg_test=None, video_encoder="clip_vit", val_length=None, num_processes=8): + + #inputs = list(dataset[text_column]) + #self.inputs = [prefix + inp for inp in inputs] + #self.audios = list(dataset[audio_column]) + #self.indices = list(range(len(self.inputs))) + # + #print("audios", len(self.audios)) + #self.new_audios = [] + #for index, audio in enumerate(self.audios): + # utt, fmt = audio.split(".") + # new_audio = "/zhanghaomin/datas/audioset_sl/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/AudioSet_SL_flac/" + utt + ".flac" + # #if os.path.exists(new_audio): + # self.new_audios.append(new_audio) + #self.audios = self.new_audios + #N = len(self.audios) + #print("audios", len(self.new_audios)) + + + test_final = "/ailab-train/speech/zhanghaomin/scps/tango-master/data/test_audiocaps_subset.json" + test_utts = {} + with open(test_final, "r") as fr: + for line in fr.readlines(): + wav = json.loads(line.strip())["location"] + utt = wav.rsplit("/", 1)[-1].rsplit("_", 1)[0] + utt = "Y"+utt + assert(utt not in test_utts) + test_utts[utt] = 1 + main_process and print("test_final", len(test_utts)) + + bbc_soundeffects_utts = {} + freesound_utts = {} + + audioset_filter_labels = {"Music": 0, "Speech": 0, "Vehicle": 0, "Musical instrument": 0} + + + self.inputs = [] + self.audios = [] + self.indices = [] + N = 0 + + + audiocaps = True + if SCORE_THRESHOLD_TRAIN["/zhanghaomin/datas/audiocaps"] >= 9000.0: + audiocaps = False + + audioset_sl = True + bbc_soundeffects = True + freesound = True + soundbible = True + if SCORE_THRESHOLD_TRAIN["/radiostorage/WavCaps"] >= 9000.0: + audioset_sl = False + bbc_soundeffects = False + freesound = False + soundbible = False + + soundeffects = True + if SCORE_THRESHOLD_TRAIN["/radiostorage/AudioGroup"] >= 9000.0: + soundeffects = False + self.soundeffects = soundeffects + + audioset = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/audioset"] >= 9000.0: + audioset = False + + bbc_soundeffects2 = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/BBCSoundEffects"] >= 9000.0: + bbc_soundeffects2 = False + + freesound2 = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/CLAP_freesound"] >= 9000.0: + freesound2 = False + + musiccaps = True + if SCORE_THRESHOLD_TRAIN["/zhanghaomin/datas/musiccap"] >= 9000.0: + musiccaps = False + + tangopromptbank = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/TangoPromptBank"] >= 9000.0: + tangopromptbank = False + + audioset_sl_2ch = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/audiosetsl"] >= 9000.0: + audioset_sl_2ch = False + self.audioset_sl_2ch = audioset_sl_2ch + + boom_epic = True + if SCORE_THRESHOLD_TRAIN["/ckptstorage/zhanghaomin/giantsoundeffects"] >= 9000.0: + boom_epic = False + self.boom_epic = boom_epic + + if isinstance(part, list): + part, scp_ac, start_ac, end_ac = part + assert(part == "val_audiocaps") + else: + scp_ac = None + + if (audioset_sl and part in ["train", "train_val_audioset_sl"]) or (part == "val_audioset_sl"): + self.audioset_sl_inputs = [] + self.audioset_sl_audios = [] + self.audioset_sl_indices = [] + audioset_sl_path_train = "/zhanghaomin/codes2/tango-master/data/train_audioset_sl.json" + audioset_sl_path_val = "/zhanghaomin/codes2/tango-master/data/val_audioset_sl.json" + audioset_sl_path_train_val = "/ailab-train/speech/zhanghaomin/scps/tango-master/data/train_val_audioset_sl.json" + if part == "train": + audioset_sl_path = audioset_sl_path_train + elif part == "train_val_audioset_sl": + audioset_sl_path = audioset_sl_path_train_val + else: + audioset_sl_path = audioset_sl_path_val + FN = 0 + with open(audioset_sl_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"].rsplit(".", 1)[0] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/AudioSet_SL/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/AudioSet_SL_flac/" + utt + ".flac" + self.audioset_sl_inputs.append(caption) + self.audioset_sl_audios.append(audio) + self.audioset_sl_indices.append(N + index) + main_process and print(part, "audioset_sl", len(self.audioset_sl_audios), "filtered", FN) + self.inputs.extend(self.audioset_sl_inputs) + self.audios.extend(self.audioset_sl_audios) + self.indices.extend(self.audioset_sl_indices) + N = len(self.audios) + main_process and print(part, "audioset_sl audios", len(self.audios)) + + if (audiocaps and part in ["train", "train_val_audioset_sl"]) or (part == "val_audiocaps"): + self.audiocaps_inputs = [] + self.audiocaps_audios = [] + self.audiocaps_indices = [] + audiocaps_path_train = "/ailab-train/speech/zhanghaomin/scps/tango-master/data/audiocaps/train_audiocaps.json" + audiocaps_path_val = "/ailab-train/speech/zhanghaomin/scps/tango-master/data/audiocaps/test_audiocaps.json" + if scp_ac is not None: + audiocaps_path_val = scp_ac + if part in ["train", "train_val_audioset_sl"]: + audiocaps_path = audiocaps_path_train + else: + audiocaps_path = audiocaps_path_val + FN = 0 + with open(audiocaps_path, "r") as fr: + lines = fr.readlines() + if scp_ac is not None: + lines = lines[start_ac: end_ac] + for index, line in enumerate(lines): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = jsondata["audio"] + self.audiocaps_inputs.append(caption) + self.audiocaps_audios.append(audio) + self.audiocaps_indices.append(N + index) + main_process and print(part, "audiocaps", len(self.audiocaps_audios), "filtered", FN) + self.inputs.extend(self.audiocaps_inputs) + self.audios.extend(self.audiocaps_audios) + self.indices.extend(self.audiocaps_indices) + N = len(self.audios) + main_process and print(part, "audiocaps audios", len(self.audios)) + + if bbc_soundeffects and part in ["train", "train_val_audioset_sl"]: + self.bbc_soundeffects_inputs = [] + self.bbc_soundeffects_audios = [] + self.bbc_soundeffects_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/tango-master/data/train_bbc_sound_effects.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + bbc_soundeffects_utts[utt] = 1 + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/BBC_Sound_Effects/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/BBC_Sound_Effects_flac/" + utt + ".flac" + self.bbc_soundeffects_inputs.append(caption) + self.bbc_soundeffects_audios.append(audio) + self.bbc_soundeffects_indices.append(N + index) + main_process and print(part, "bbc_soundeffects", len(self.bbc_soundeffects_audios)) + self.inputs.extend(self.bbc_soundeffects_inputs) + self.audios.extend(self.bbc_soundeffects_audios) + self.indices.extend(self.bbc_soundeffects_indices) + N = len(self.audios) + main_process and print(part, "bbc_soundeffects audios", len(self.audios)) + + if freesound and part in ["train", "train_val_audioset_sl"]: + self.freesound_inputs = [] + self.freesound_audios = [] + self.freesound_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/tango-master/data/train_freesound.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + freesound_utts[utt] = 1 + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/FreeSound/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/FreeSound_flac/" + utt + ".flac" + self.freesound_inputs.append(caption) + self.freesound_audios.append(audio) + self.freesound_indices.append(N + index) + main_process and print(part, "freesound", len(self.freesound_audios)) + self.inputs.extend(self.freesound_inputs) + self.audios.extend(self.freesound_audios) + self.indices.extend(self.freesound_indices) + N = len(self.audios) + main_process and print(part, "freesound audios", len(self.audios)) + + if soundbible and part in ["train", "train_val_audioset_sl"]: + self.soundbible_inputs = [] + self.soundbible_audios = [] + self.soundbible_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/tango-master/data/train_soundbible.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + caption = jsondata["caption"] + audio = "/radiostorage/WavCaps/Zip_files/SoundBible/mnt/fast/nobackup/scratch4weeks/xm00178/WavCaps/data/waveforms/SoundBible_flac/" + utt + ".flac" + self.soundbible_inputs.append(caption) + self.soundbible_audios.append(audio) + self.soundbible_indices.append(N + index) + main_process and print(part, "soundbible", len(self.soundbible_audios)) + self.inputs.extend(self.soundbible_inputs) + self.audios.extend(self.soundbible_audios) + self.indices.extend(self.soundbible_indices) + N = len(self.audios) + main_process and print(part, "soundbible audios", len(self.audios)) + + if (soundeffects and part in ["train", "train_val_audioset_sl"]) or (part == "val_soundeffects"): + self.soundeffects_inputs = [] + self.soundeffects_audios = [] + self.soundeffects_indices = [] + #soundeffects_path_train = "/zhanghaomin/codes2/audiocaption/wav_all_train.scp" + #soundeffects_path_val = "/zhanghaomin/codes2/audiocaption/wav_all_val.scp" + #soundeffects_path_train = "/zhanghaomin/codes2/audiocaption/wav_msclap_all_train.scp" + soundeffects_path_train = train_file + soundeffects_path_val = "/zhanghaomin/codes2/audiocaption/wav_msclap_all_val.scp" + if part in ["train", "train_val_audioset_sl"]: + soundeffects_path = soundeffects_path_train + else: + soundeffects_path = soundeffects_path_val + with open(soundeffects_path, 'r') as fr: + for index, line in enumerate(fr.readlines()): + if soundeffects_path.endswith("msclapcap_v1.list"): + utt, wav, caption1, score = line.strip().split('"@$&#"') + caption2 = "blank" + name = "blank" + else: + utt, wav, name, caption1, caption2 = line.strip().split('"@$&#"') + wav = wav.replace("/radiostorage/AudioGroup/", "/radiostorage/AudioGroup/") + period = int(utt.split('_')[-1]) + self.soundeffects_inputs.append((caption1, caption2, name)) + self.soundeffects_audios.append((wav, utt, period)) + self.soundeffects_indices.append(N + index) + main_process and print(part, "soundeffects", len(self.soundeffects_audios)) + self.inputs.extend(self.soundeffects_inputs) + self.audios.extend(self.soundeffects_audios) + self.indices.extend(self.soundeffects_indices) + N = len(self.audios) + main_process and print(part, "soundeffects audios", len(self.audios)) + + if audioset and part in ["train", "train_val_audioset_sl"]: + self.audioset_inputs = [] + self.audioset_audios = [] + self.audioset_indices = [] + FN = 0 + FN2 = 0 + if SCORE_THRESHOLD_TRAIN["audioset"] == "af-audioset": + audioset_path = "/ailab-train/speech/zhanghaomin/scps/audioset/audioset_train_af.json" + else: + audioset_path = "/ckptstorage/zhanghaomin/audioset/audioset_train.json" + with open(audioset_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + if SCORE_THRESHOLD_TRAIN["audioset"] == "af-audioset": + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + audio = jsondata["audio"] + else: + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in test_utts: + FN += 1 + continue + caption = jsondata["caption"] + #caption = caption.replace("@", ", ") + captions = caption.split("@") + captions_new = [] + for c in captions: + if c in audioset_filter_labels: + audioset_filter_labels[c] += 1 + else: + captions_new.append(c) + if len(captions_new) == 0: + FN2 += 1 + continue + caption = "".join(captions_new) + audio = jsondata["audio"] + self.audioset_inputs.append(caption) + self.audioset_audios.append(audio) + self.audioset_indices.append(N + index) + main_process and print(part, "audioset", len(self.audioset_audios), "filtered", FN, FN2, audioset_filter_labels) + self.inputs.extend(self.audioset_inputs) + self.audios.extend(self.audioset_audios) + self.indices.extend(self.audioset_indices) + N = len(self.audios) + main_process and print(part, "audioset audios", len(self.audios)) + + if bbc_soundeffects2 and part in ["train", "train_val_audioset_sl"]: + self.bbc_soundeffects2_inputs = [] + self.bbc_soundeffects2_audios = [] + self.bbc_soundeffects2_indices = [] + FN = 0 + with open("/ckptstorage/zhanghaomin/BBCSoundEffects/bbcsoundeffects_train.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in bbc_soundeffects_utts: + FN += 1 + continue + caption = jsondata["caption"] + caption = caption.split("(")[0].strip() + audio = jsondata["audio"] + self.bbc_soundeffects2_inputs.append(caption) + self.bbc_soundeffects2_audios.append(audio) + self.bbc_soundeffects2_indices.append(N + index) + main_process and print(part, "bbc_soundeffects2", len(self.bbc_soundeffects2_audios), "filtered", FN) + self.inputs.extend(self.bbc_soundeffects2_inputs) + self.audios.extend(self.bbc_soundeffects2_audios) + self.indices.extend(self.bbc_soundeffects2_indices) + N = len(self.audios) + main_process and print(part, "bbc_soundeffects2 audios", len(self.audios)) + + if freesound2 and part in ["train", "train_val_audioset_sl"]: + self.freesound2_inputs = [] + self.freesound2_audios = [] + self.freesound2_indices = [] + FN = 0 + with open("/ckptstorage/zhanghaomin/CLAP_freesound/freesound_train.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + utt = jsondata["id"] + if part in ["train", "train_val_audioset_sl"] and utt in freesound_utts: + FN += 1 + continue + caption = jsondata["caption"] + caption = caption.split('"@$&#"') + #caption = caption[0].split("(")[0].strip() + caption = tuple([c.split("(")[0].strip() for c in caption]) + audio = jsondata["audio"] + self.freesound2_inputs.append(caption) + self.freesound2_audios.append(audio) + self.freesound2_indices.append(N + index) + main_process and print(part, "freesound2", len(self.freesound2_audios), "filtered", FN) + self.inputs.extend(self.freesound2_inputs) + self.audios.extend(self.freesound2_audios) + self.indices.extend(self.freesound2_indices) + N = len(self.audios) + main_process and print(part, "freesound2 audios", len(self.audios)) + + if tangopromptbank and part in ["train", "train_val_audioset_sl"]: + self.tangopromptbank_inputs = [] + self.tangopromptbank_audios = [] + self.tangopromptbank_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/TangoPromptBank/data.json", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["captions"] + audio = jsondata["location"] + self.tangopromptbank_inputs.append(caption) + self.tangopromptbank_audios.append(audio) + self.tangopromptbank_indices.append(N + index) + main_process and print(part, "tangopromptbank", len(self.tangopromptbank_audios)) + self.inputs.extend(self.tangopromptbank_inputs) + self.audios.extend(self.tangopromptbank_audios) + self.indices.extend(self.tangopromptbank_indices) + N = len(self.audios) + main_process and print(part, "tangopromptbank audios", len(self.audios)) + + if musiccaps and part in ["train", "train_val_audioset_sl"]: + self.musiccaps_inputs = [] + self.musiccaps_audios = [] + self.musiccaps_indices = [] + with open("/ailab-train/speech/zhanghaomin/scps/musiccap/musiccaps.jsonl", "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.musiccaps_inputs.append(caption) + self.musiccaps_audios.append(audio) + self.musiccaps_indices.append(N + index) + main_process and print(part, "musiccaps", len(self.musiccaps_audios)) + self.inputs.extend(self.musiccaps_inputs) + self.audios.extend(self.musiccaps_audios) + self.indices.extend(self.musiccaps_indices) + N = len(self.audios) + main_process and print(part, "musiccaps audios", len(self.audios)) + + if (audioset_sl_2ch and part in ["train", "train_val_audioset_sl"]) or (part == "val_audioset_sl_2ch"): + self.audioset_sl_2ch_inputs = [] + self.audioset_sl_2ch_audios = [] + self.audioset_sl_2ch_indices = [] + audioset_sl_2ch_train = "/ckptstorage/zhanghaomin/audiosetsl/wavs/train.jsonl" + audioset_sl_2ch_val = "/ckptstorage/zhanghaomin/audiosetsl/wavs/test.jsonl" + if part in ["train", "train_val_audioset_sl"]: + audioset_sl_2ch_path = audioset_sl_2ch_train + else: + audioset_sl_2ch_path = audioset_sl_2ch_val + with open(audioset_sl_2ch_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.audioset_sl_2ch_inputs.append(caption) + self.audioset_sl_2ch_audios.append(audio) + self.audioset_sl_2ch_indices.append(N + index) + main_process and print(part, "audioset_sl_2ch", len(self.audioset_sl_2ch_audios)) + self.inputs.extend(self.audioset_sl_2ch_inputs) + self.audios.extend(self.audioset_sl_2ch_audios) + self.indices.extend(self.audioset_sl_2ch_indices) + N = len(self.audios) + main_process and print(part, "audioset_sl_2ch audios", len(self.audios)) + + if (boom_epic and part in ["train", "train_val_audioset_sl"]) or (part == "val_boom_epic"): + self.boom_epic_inputs = [] + self.boom_epic_audios = [] + self.boom_epic_indices = [] + #boom_epic_train = "/ckptstorage/zhanghaomin/giantsoundeffects/train_animals_mixture2.jsonl" + #boom_epic_val = "/ckptstorage/zhanghaomin/giantsoundeffects/test_animals_mixture2.jsonl" + boom_epic_train = "/ailab-train/speech/zhanghaomin/scps/giantsoundeffects/train.jsonl" + boom_epic_val = "/ailab-train/speech/zhanghaomin/scps/giantsoundeffects/test.jsonl" + if part in ["train", "train_val_audioset_sl"]: + boom_epic_path = boom_epic_train + else: + boom_epic_path = boom_epic_val + with open(boom_epic_path, "r") as fr: + for index, line in enumerate(fr.readlines()): + jsondata = json.loads(line.strip()) + caption = jsondata["caption"] + audio = jsondata["audio"] + self.boom_epic_inputs.append(caption) + self.boom_epic_audios.append(audio) + self.boom_epic_indices.append(N + index) + main_process and print(part, "boom_epic", len(self.boom_epic_audios)) + repeats = 1 + for _ in range(repeats): + self.inputs.extend(self.boom_epic_inputs) + self.audios.extend(self.boom_epic_audios) + self.indices.extend(self.boom_epic_indices) + N = len(self.audios) + main_process and print(part, "boom_epic audios", len(self.audios)) + self.boom_epic = boom_epic + + if vggsound: + self.inputs_vggsound = [] + self.audios_vggsound = [] + self.indices_vggsound = [] + if part in ["train", "train_val_audioset_sl"]: + path = "/ailab-train/speech/zhanghaomin/scps/VGGSound/train.scp" + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()): + video_path, text = line.strip().split("\t") + self.inputs_vggsound.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios_vggsound.append(video_path) + self.indices_vggsound.append(index) + N = len(self.audios_vggsound) + print(part, "vggsound train audios", len(self.audios_vggsound), device_id, num_processes) + elif part == "val_vggsound": + if vgg_test is not None: + path = vgg_test[0] + start = vgg_test[1] + end = vgg_test[2] + else: + path = "/ailab-train/speech/zhanghaomin/scps/VGGSound/test.scp" + start = 0 + end = 200 + with open(path, "r") as fr: + for index, line in enumerate(fr.readlines()[start:end]): + video_path, text = line.strip().split("\t") + self.inputs.append("the sound of " + text.strip().replace("(", "").replace(")", "")) + self.audios.append(video_path) + self.indices.append(N + index) + N = len(self.audios) + print(part, "vggsound eval audios", len(self.audios), device_id, num_processes) + self.vggsound = vggsound + self.video_drop_prompt = video_drop_prompt + self.audio_drop_prompt = audio_drop_prompt + self.device_id = device_id + self.num_processes = num_processes + self.bad_ids = {} + self.video_encoder = video_encoder + self.val_length = val_length if val_length is not None else torch_tools.MAX_TARGET_LEN + print("val_length", self.val_length) + + #self.mapper = {} + #for index, audio, text in zip(self.indices, self.audios, self.inputs): + # self.mapper[index] = [audio, text] + + if num_examples != -1: + self.inputs, self.audios = self.inputs[:num_examples], self.audios[:num_examples] + self.indices = self.indices[:num_examples] + + self.samples = samples + self.stft = stft + self.target_length = DURATION + self.augment = augment + self.part = part + self.main_process = main_process + self.SCORE_THRESHOLD_TRAIN = SCORE_THRESHOLD_TRAIN + self.theta = theta + self.multi = 4 + + def __len__(self): + return len(self.inputs) + + def get_num_instances(self): + return len(self.inputs) + + def __getitem__(self, index): + s1, s2, s3 = self.inputs[index], self.audios[index], self.indices[index] + return s1, s2, s3 + + def read_audio_from_video(self, video_path): + if video_path.startswith("/ailab-train/speech/zhanghaomin/VGGSound/"): + audio_path = video_path.replace("/video/", "/audio/").replace(".mp4", ".wav") + else: + audio_path = video_path.replace(".mp4", ".generated.wav") + if os.path.exists(audio_path): + #print("video wav exist", audio_path) + waveform, sr = torchaudio.load(audio_path) + else: + #print("video wav not exist", video_path) + try: + clip = AudioFileClip(video_path) + sound_array = np.array(list(clip.iter_frames())) + waveform = torch.from_numpy(sound_array).transpose(0,1).to(torch.float32) + waveform = waveform[0:1, :] + if clip.fps != torch_tools.new_freq: + waveform = torchaudio.functional.resample(waveform, orig_freq=clip.fps, new_freq=torch_tools.new_freq) + waveform = torch_tools.normalize_wav(waveform) + torchaudio.save(audio_path, waveform, torch_tools.new_freq) + except: + print("Error read_audio_from_video", audio_path) + traceback.print_exc() + return None + return waveform + + def collate_fn(self, data): + # 452463+1471396->452463+3430704->452463+2978587 more 452463+1037241+15973+310169 real 1183416+2000 + # theta (1183416)*0.5/(452463+1037241+15973+310169)=0.3259 + # beta (452463+1037241+15973+310169+3430704)/(452463+1037241+15973+310169+1471396)=1.5960 (452463+1037241+15973+310169+2978587)/(452463+1037241+15973+310169+1471396)=1.4585 + if self.part in ["train", "train_val_audioset_sl"]: + val = False + else: + val = True + if self.audioset_sl_2ch: + nch = 2 + else: + nch = 1 + while True: + if self.part in ["train", "train_val_audioset_sl"]: + #print("data raw", len(data), data[0]) + #data_sampled = random.sample(data, self.samples) + + if (self.soundeffects or self.boom_epic) and self.theta > 0: + data_len = len(data) + data_1 = [] + data_2 = [] + for sample in data: + if isinstance(sample[1], tuple): + if sample[1][0].startswith("/radiostorage/"): + prefix = "/".join(sample[1][0].split("/")[:3]) + else: + prefix = "/".join(sample[1][0].split("/")[:4]) + else: + if sample[1].startswith("/radiostorage/"): + prefix = "/".join(sample[1].split("/")[:3]) + else: + prefix = "/".join(sample[1].split("/")[:4]) + if torch_tools.SOUNDEFFECT[prefix]: + data_2.append(sample) + else: + data_1.append(sample) + #print("data splitted", len(data_1), len(data_2), float(len(data_1))/len(data_2)) + data_len_1 = len(data_1) + data_len_2 = len(data_2) + if data_len_1 == 0 or data_len_2 == 0: + data_1_sampled = data_1 + data_2_sampled = data_2 + else: + data_len_1_sampled = int(data_len_2 / self.theta) + data_len_2_sampled = int(data_len_1 * self.theta) + if data_len_1_sampled < data_len_1: + data_1_sampled = random.sample(data_1, data_len_1_sampled) + data_2_sampled = data_2 + else: + data_1_sampled = data_1 + data_2_sampled = random.sample(data_2, data_len_2_sampled) + #print("data sampled", len(data_1_sampled), len(data_2_sampled), float(len(data_1_sampled))/len(data_2_sampled), self.samples*cand) + data_sampled = data_1_sampled + data_sampled.extend(data_2_sampled) + data_sampled = random.sample(data_sampled, min(self.samples*cand, len(data_sampled))) + #print("data sampled", len(data_sampled)) + else: + data_sampled = random.sample(data, min(self.samples*cand, len(data))) + #print("data sampled", len(data_sampled)) + else: + data_sampled = data + dat = pd.DataFrame(data_sampled) + text, audios, indices = [dat[i].tolist() for i in dat] + + if self.vggsound and val and self.part == "val_vggsound": + #print("vggsound val", len(audios), text) + fbanks = [] + fbank_lens = [] + video_paths = [] + text_selected = [] + for audio, txt in zip(audios, text): + waveform = self.read_audio_from_video(audio) + if waveform is None: + continue + length = self.val_length + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + video_paths.append(audio) + text_selected.append(txt) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + mel = torch.cat(fbanks, 0) + mel_len = torch.Tensor(fbank_lens).to(torch.int32) + break + + if_clap_filter = False + if self.part in ["val_audiocaps", "val_audioset_sl_2ch", "val_boom_epic"]: + if_clap_filter = False + mel, text_selected, _, _, _, mel_len = torch_tools.wav_to_fbank(audios, text, self.samples, self.target_length, self.stft, val, if_clap_filter, self.main_process, self.SCORE_THRESHOLD_TRAIN, nch) + if mel is not None: + if self.part in ["train", "train_val_audioset_sl"]: + if len(text_selected) > self.samples: + mel = mel[:self.samples,...] + text_selected = text_selected[:self.samples] + #waveform = waveform[:self.samples,...] + mel_len = mel_len[:self.samples] + if self.vggsound: + video_paths = [None] * len(text_selected) + else: + video_paths = None + #print("mel", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + break + + #mel = mel.unsqueeze(1) + if self.augment != 0 and len(text_selected) > 1 and (not val): + aug_num = len(text_selected) if self.augment == -1 else self.augment + # the last batch of the training data may have only one instance + # we check the length here so that the augmentation function doesn't throw an error + mixed_mel, _, _, mixed_captions, _, mixed_mel_len = torch_tools.augment_wav_to_fbank(audios, text, aug_num, self.target_length, self.stft, self.main_process, self.SCORE_THRESHOLD_TRAIN, nch) + #print("mixed_mel", mixed_mel.shape if mixed_mel is not None else None, len(mixed_captions) if mixed_captions is not None else 0, mixed_mel_len) + if mixed_mel is not None: + if mel.shape[1] < mixed_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], mixed_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif mixed_mel.shape[1] < mel.shape[1]: + mixed_mel = torch.cat([mixed_mel, torch.zeros(mixed_mel.shape[0], mel.shape[1]-mixed_mel.shape[1], mixed_mel.shape[2])], 1) + #mixed_mel = mixed_mel.unsqueeze(1) + mel = torch.cat([mel, mixed_mel], 0) + text_selected += mixed_captions + mel_len = torch.cat([mel_len, mixed_mel_len], 0) + if self.vggsound: + video_paths.extend([None] * len(mixed_captions)) + else: + video_paths = None + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len) + + if self.vggsound and (not val): + video_paths = [None] * len(text_selected) + fbanks = [] + fbank_lens = [] + audios = [] + video_captions = [] + indices = random.sample([self.indices_vggsound[i] for i in range(self.device_id, len(self.indices_vggsound), self.num_processes)], self.vggsound*10) + indices_featured = [] + indices_nonfeatured = [] + for i in indices: + if i in self.bad_ids: + continue + if self.audios_vggsound[i].startswith("/ailab-train/speech/zhanghaomin/VGGSound/"): + if self.video_encoder == "clip_vit": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_clip_vit2/").replace(".mp4", ".npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_clip_convnext/").replace(".mp4", ".npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_dinov2/").replace(".mp4", ".npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_vggsound[i].replace("/video/", "/feature_mixed/").replace(".mp4", ".npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + else: + if self.video_encoder == "clip_vit": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.npz") + elif self.video_encoder == "clip_vit2": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.clip_vit2.npz") + elif self.video_encoder == "clip_convnext": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.clip_convnext.npz") + elif self.video_encoder == "dinov2": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.dinov2.npz") + elif self.video_encoder == "mixed": + feature_path = self.audios_vggsound[i].replace(".mp4", ".generated.mixed.npz") + else: + raise Exception("Invalid video_encoder " + self.video_encoder) + if os.path.exists(feature_path): + indices_featured.append(i) + else: + indices_nonfeatured.append(i) + if len(indices_nonfeatured) >= self.vggsound: + break + #print(self.device_id, self.bad_ids, indices, indices_featured, indices_nonfeatured) + indices = indices_nonfeatured[:self.vggsound] + if len(indices) < self.vggsound: + indices.extend(indices_featured[:self.vggsound-len(indices)]) + for i in indices: + waveform = self.read_audio_from_video(self.audios_vggsound[i]) + if waveform is None: + print("Error audio in video", i, self.audios_vggsound[i], self.bad_ids) + self.bad_ids[i] = 1 + continue + length = random.randint(torch_tools.MIN_TARGET_LEN, torch_tools.MAX_TARGET_LEN) + waveform = waveform[:, :length*torch_tools.hop_size] + fbank = self.stft(waveform).transpose(-1,-2) + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + audios.append(self.audios_vggsound[i]) + video_captions.append(self.inputs_vggsound[i]) + #print("stft", waveform.shape, fbank.shape) + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + video_mel = torch.cat(fbanks, 0) + video_mel_len = torch.Tensor(fbank_lens).to(torch.int32) + #print("video_mel", video_mel.shape if video_mel is not None else None, len(video_captions) if video_captions is not None else 0, video_mel_len) + if video_mel is not None: + if mel.shape[1] < video_mel.shape[1]: + mel = torch.cat([mel, torch.zeros(mel.shape[0], video_mel.shape[1]-mel.shape[1], mel.shape[2])], 1) + elif video_mel.shape[1] < mel.shape[1]: + video_mel = torch.cat([video_mel, torch.zeros(video_mel.shape[0], mel.shape[1]-video_mel.shape[1], video_mel.shape[2])], 1) + #video_mel = video_mel.unsqueeze(1) + mel = torch.cat([mel, video_mel], 0) + text_selected += video_captions + mel_len = torch.cat([mel_len, video_mel_len], 0) + video_paths.extend(audios) + #print("mel_final", mel.shape if mel is not None else None, len(text_selected) if text_selected is not None else 0, mel_len, video_paths) + + return [text_selected, mel, video_paths, mel_len, self.video_drop_prompt, self.audio_drop_prompt] + + +class Text2SpeechDataset(Dataset): + def __init__(self, samples=-1, stft=None, val=False): + self.inputs = [] + self.audios = [] + self.indices = [] + + train_scp = "/ckptstorage/zhanghaomin/docker/ximalaya/ximalaya_process/data_scp/train.json" + test_scp = "/ckptstorage/zhanghaomin/docker/ximalaya/ximalaya_process/data_scp/test.json" + scp = train_scp if not val else test_scp + index = 0 + with open(scp, "r") as fr: + for line in fr.readlines(): + data = json.loads(line.strip()) + wav = data["wav"] + text = data["text"] + if len(text) < 2: + continue + self.inputs.append(text) + self.audios.append(wav) + self.indices.append(index) + index += 1 + print("data size", len(self.inputs), val) + self.samples = samples + self.stft = stft + self.sample_rate = 24000 + self.multi = 8 + self.val = val + + def __len__(self): + return len(self.inputs) + + def get_num_instances(self): + return len(self.inputs) + + def __getitem__(self, index): + s1, s2, s3 = self.inputs[index], self.audios[index], self.indices[index] + return s1, s2, s3 + + def collate_fn(self, data): + dat = pd.DataFrame(data) + texts, audios, indices = [dat[i].tolist() for i in dat] + + fbanks = [] + fbank_lens = [] + text_selected = [] + for text, audio in zip(texts, audios): + waveform, sr = torchaudio.load(audio) + waveform = waveform[0:1, :] + if sr != self.sample_rate: + waveform = torchaudio.functional.resample(waveform, orig_freq=sr, new_freq=self.sample_rate) + waveform = torch_tools.normalize_wav(waveform) + fbank = self.stft(waveform).transpose(-1,-2) + #print("stft", waveform.shape, fbank.shape) + if self.val: + if waveform.shape[1] / float(self.sample_rate) < 2.0 or waveform.shape[1] / float(self.sample_rate) > 15.0: + continue + else: + if waveform.shape[1] / float(self.sample_rate) < 1.0 or waveform.shape[1] / float(self.sample_rate) > 20.0: + continue + fbanks.append(fbank) + fbank_lens.append(fbank.shape[1]) + text_selected.append(text) + if self.samples > 0 and len(text_selected) >= self.samples: + break + if self.samples > 0 and len(text_selected) > self.samples: + fbanks = fbanks[:self.samples] + fbank_lens = fbank_lens[:self.samples] + text_selected = text_selected[:self.samples] + max_length = max(fbank_lens) + for i in range(len(fbanks)): + if fbanks[i].shape[1] < max_length: + fbanks[i] = torch.cat([fbanks[i], torch.zeros(fbanks[i].shape[0], max_length-fbanks[i].shape[1], fbanks[i].shape[2])], 1) + mel = torch.cat(fbanks, 0) + mel_len = torch.Tensor(fbank_lens).to(torch.int32) + return [text_selected, mel, None, mel_len, None] + diff --git a/src/inference_v2a.py b/src/inference_v2a.py new file mode 100644 index 0000000000000000000000000000000000000000..3f447e7b90951532f5357091bcb54a2c108ab441 --- /dev/null +++ b/src/inference_v2a.py @@ -0,0 +1,222 @@ +import sys + +if len(sys.argv) >= 6: + ckpt = sys.argv[1] + drop_prompt = bool(int(sys.argv[2])) + test_scp = sys.argv[3] + start = int(sys.argv[4]) + end = int(sys.argv[5]) + step = 1 + out_dir = sys.argv[6] + print("inference", ckpt, drop_prompt, test_scp, start, end, out_dir) +else: + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more/98500.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more/190000.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more/315000.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more_more/60000.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more_more_piano5/4_2_8000.pt" + ckpt = "./ckpts/piano5_4_2_8000.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more_more_piano6/dpo_100.pt" + drop_prompt = False + test_scp = "/ailab-train/speech/zhanghaomin/scps/VGGSound/test.scp" + #test_scp = "./tests/vgg_test.scp" + ####test_scp = "/ailab-train/speech/zhanghaomin/scps/instruments/test.scp" + ####test_scp = "/ailab-train/speech/zhanghaomin/scps/instruments/piano_2h/test.scp" + ####test_scp = "/ailab-train/speech/zhanghaomin/scps/instruments/piano_20h/v2a_giant_piano2/test.scp" + start = 0 + end = 2 + step = 1 + out_dir = "./outputs_vgg/" + ####out_dir = "./outputs_piano/" + #####out_dir = "./outputs2t_20h_dpo/" + + +import torch +from e2_tts_pytorch.e2_tts_crossatt3 import E2TTS, DurationPredictor +from e2_tts_pytorch.e2_tts_crossatt3 import MelSpec, EncodecWrapper + +from torch.optim import Adam +from torch.utils.data import DataLoader, Dataset +from datasets import load_dataset + +from e2_tts_pytorch.trainer_multigpus_alldatas3 import HFDataset, Text2AudioDataset + +from einops import einsum, rearrange, repeat, reduce, pack, unpack +import torchaudio + +from datetime import datetime +import json +import numpy as np +import os +from moviepy.editor import VideoFileClip, AudioFileClip +import traceback + + +audiocond_drop_prob = 1.1 +#audiocond_drop_prob = 0.3 +#cond_proj_in_bias = True +#cond_drop_prob = 1.1 +cond_drop_prob = -0.1 +prompt_drop_prob = -0.1 +#prompt_drop_prob = 1.1 +video_text = True + + +def main(): + #duration_predictor = DurationPredictor( + # transformer = dict( + # dim = 512, + # depth = 6, + # ) + #) + duration_predictor = None + + e2tts = E2TTS( + duration_predictor = duration_predictor, + transformer = dict( + #depth = 12, + #dim = 512, + #heads = 8, + #dim_head = 64, + depth = 12, + dim = 1024, + dim_text = 1280, + heads = 16, + dim_head = 64, + if_text_modules = (cond_drop_prob < 1.0), + if_cross_attn = (prompt_drop_prob < 1.0), + if_audio_conv = True, + if_text_conv = True, + ), + #tokenizer = 'char_utf8', + tokenizer = 'phoneme_zh', + audiocond_drop_prob = audiocond_drop_prob, + cond_drop_prob = cond_drop_prob, + prompt_drop_prob = prompt_drop_prob, + frac_lengths_mask = (0.7, 1.0), + #audiocond_snr = None, + #audiocond_snr = (5.0, 10.0), + + if_cond_proj_in = (audiocond_drop_prob < 1.0), + #cond_proj_in_bias = cond_proj_in_bias, + if_embed_text = (cond_drop_prob < 1.0) and (not video_text), + if_text_encoder2 = (prompt_drop_prob < 1.0), + if_clip_encoder = video_text, + video_encoder = "clip_vit", + + pretrained_vocos_path = 'facebook/encodec_24khz', + num_channels = 128, + sampling_rate = 24000, + ) + e2tts = e2tts.to("cuda") + + #checkpoint = torch.load("/ckptstorage/zhanghaomin/e2/e2_tts_experiment_v2a_encodec/3000.pt", map_location="cpu") + #checkpoint = torch.load("/ckptstorage/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more/500.pt", map_location="cpu") + #checkpoint = torch.load("/ckptstorage/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more/98500.pt", map_location="cpu") + #checkpoint = torch.load("/ckptstorage/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more/190000.pt", map_location="cpu") + checkpoint = torch.load(ckpt, map_location="cpu") + + #for key in list(checkpoint['model_state_dict'].keys()): + # if key.startswith('mel_spec.'): + # del checkpoint['model_state_dict'][key] + # if key.startswith('transformer.text_registers'): + # del checkpoint['model_state_dict'][key] + e2tts.load_state_dict(checkpoint['model_state_dict'], strict=False) + + e2tts.vocos = EncodecWrapper("facebook/encodec_24khz") + for param in e2tts.vocos.parameters(): + param.requires_grad = False + e2tts.vocos.eval() + e2tts.vocos.to("cuda") + + #dataset = HFDataset(load_dataset("parquet", data_files={"test": "/ckptstorage/zhanghaomin/tts/GLOBE/data/test-*.parquet"})["test"]) + #sample = dataset[1] + #mel_spec_raw = sample["mel_spec"].unsqueeze(0) + #mel_spec = rearrange(mel_spec_raw, 'b d n -> b n d') + #print(mel_spec.shape, sample["text"]) + + #out_dir = "/user-fs/zhanghaomin/v2a_generated/v2a_190000_tests/" + #out_dir = "/user-fs/zhanghaomin/v2a_generated/tv2a_98500_clips/" + if not os.path.exists(out_dir): + os.makedirs(out_dir) + + #bs = list(range(10)) + [14,16] + bs = None + + SCORE_THRESHOLD_TRAIN = '{"/zhanghaomin/datas/audiocaps": -9999.0, "/radiostorage/WavCaps": -9999.0, "/radiostorage/AudioGroup": 9999.0, "/ckptstorage/zhanghaomin/audioset": -9999.0, "/ckptstorage/zhanghaomin/BBCSoundEffects": 9999.0, "/ckptstorage/zhanghaomin/CLAP_freesound": 9999.0, "/zhanghaomin/datas/musiccap": -9999.0, "/ckptstorage/zhanghaomin/TangoPromptBank": -9999.0, "audioset": "af-audioset", "/ckptstorage/zhanghaomin/audiosetsl": 9999.0, "/ckptstorage/zhanghaomin/giantsoundeffects": -9999.0}' # /root/datasets/ /radiostorage/ + SCORE_THRESHOLD_TRAIN = json.loads(SCORE_THRESHOLD_TRAIN) + for key in SCORE_THRESHOLD_TRAIN: + if key == "audioset": + continue + if SCORE_THRESHOLD_TRAIN[key] <= -9000.0: + SCORE_THRESHOLD_TRAIN[key] = -np.inf + print("SCORE_THRESHOLD_TRAIN", SCORE_THRESHOLD_TRAIN) + stft = EncodecWrapper("facebook/encodec_24khz") + ####eval_dataset = Text2AudioDataset(None, "val_instruments", None, None, None, -1, -1, stft, 0, True, SCORE_THRESHOLD_TRAIN, "/zhanghaomin/codes2/audiocaption/msclapcap_v1.list", -1.0, 1, 1, [drop_prompt], None, 0, vgg_test=[test_scp, start, end, step], video_encoder="clip_vit") + eval_dataset = Text2AudioDataset(None, "val_vggsound", None, None, None, -1, -1, stft, 0, True, SCORE_THRESHOLD_TRAIN, "/zhanghaomin/codes2/audiocaption/msclapcap_v1.list", -1.0, 1, 1, [drop_prompt], None, 0, vgg_test=[test_scp, start, end, step], video_encoder="clip_vit") + eval_dataloader = DataLoader(eval_dataset, shuffle=False, batch_size=1, collate_fn=eval_dataset.collate_fn, num_workers=1, drop_last=False, pin_memory=True) + i = 0 + for b, batch in enumerate(eval_dataloader): + if (bs is not None) and (b not in bs): + continue + #text, mel_spec, _, mel_lengths = batch + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt, frames, midis = batch + print(mel_spec.shape, mel_lengths, text, video_paths, video_drop_prompt, audio_drop_prompt, frames.shape if frames is not None and not isinstance(frames, float) else frames, midis.shape if midis is not None else midis, midis.sum() if midis is not None else midis) + text = text[i:i+1] + mel_spec = mel_spec[i:i+1, 0:mel_lengths[i], :] + mel_lengths = mel_lengths[i:i+1] + video_paths = video_paths[i:i+1] + video_path = out_dir + video_paths[0].replace("/", "__") + audio_path = video_path.replace(".mp4", ".wav") + + name = video_paths[0].rsplit("/", 1)[1].rsplit(".", 1)[0] + + num = 1 + + l = mel_lengths[0] + #cond = mel_spec.repeat(num, 1, 1) + cond = torch.randn(num, l, e2tts.num_channels) + duration = torch.tensor([l]*num, dtype=torch.int32) + lens = torch.tensor([l]*num, dtype=torch.int32) + print(datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3], "start") + #e2tts.sample(text=[""]*num, duration=duration.to("cuda"), lens=lens.to("cuda"), cond=cond.to("cuda"), save_to_filename="test.wav", steps=16, cfg_strength=3.0, remove_parallel_component=False, sway_sampling=True) + e2tts.sample(text=None, duration=duration.to("cuda"), lens=lens.to("cuda"), cond=cond.to("cuda"), save_to_filename=audio_path, steps=64, prompt=text*num, video_drop_prompt=video_drop_prompt, audio_drop_prompt=audio_drop_prompt, cfg_strength=2.0, remove_parallel_component=False, sway_sampling=True, video_paths=video_paths, frames=(frames if frames is None or isinstance(frames, float) else frames.to("cuda")), midis=(midis if midis is None else midis.to("cuda"))) + print(datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3], "sample") + #one_audio = e2tts.vocos.decode(mel_spec_raw.to("cuda")) + #one_audio = e2tts.vocos.decode(cond.transpose(-1,-2).to("cuda")) + #print(datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3], "vocoder") + #torchaudio.save("ref.wav", one_audio.detach().cpu(), sample_rate = e2tts.sampling_rate) + + try: + os.system("cp \"" + video_paths[0] + "\" \"" + video_path + "\"") + video = VideoFileClip(video_path) + audio = AudioFileClip(audio_path) + print("duration", video.duration, audio.duration) + if video.duration >= audio.duration: + video = video.subclip(0, audio.duration) + else: + audio = audio.subclip(0, video.duration) + final_video = video.set_audio(audio) + final_video.write_videofile(video_path.replace(".mp4", ".v2a.mp4"), codec="libx264", audio_codec="aac") + print("\"" + video_path.replace(".mp4", ".v2a.mp4") + "\"") + except Exception as e: + print("Exception write_videofile:", video_path.replace(".mp4", ".v2a.mp4")) + traceback.print_exc() + + if False: + if not os.path.exists(out_dir+"groundtruth/"): + os.makedirs(out_dir+"groundtruth/") + if not os.path.exists(out_dir+"generated/"): + os.makedirs(out_dir+"generated/") + duration_gt = video.duration + duration_gr = final_video.duration + duration = min(duration_gt, duration_gr) + audio_gt = video.audio.subclip(0, duration) + audio_gr = final_video.audio.subclip(0, duration) + audio_gt.write_audiofile(out_dir+"groundtruth/"+name+".wav", fps=24000) + audio_gr.write_audiofile(out_dir+"generated/"+name+".wav", fps=24000) + + +if __name__ == "__main__": + main() + diff --git a/src/inference_v2p.py b/src/inference_v2p.py new file mode 100644 index 0000000000000000000000000000000000000000..a23cdaa093a8c2e8fa6ef6759d4d9e8a754b4ce2 --- /dev/null +++ b/src/inference_v2p.py @@ -0,0 +1,222 @@ +import sys + +if len(sys.argv) >= 6: + ckpt = sys.argv[1] + drop_prompt = bool(int(sys.argv[2])) + test_scp = sys.argv[3] + start = int(sys.argv[4]) + end = int(sys.argv[5]) + step = 1 + out_dir = sys.argv[6] + print("inference", ckpt, drop_prompt, test_scp, start, end, out_dir) +else: + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more/98500.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more/190000.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more/315000.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more_more/60000.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more_more_piano5/4_2_8000.pt" + ckpt = "./ckpts/piano5_4_2_8000.pt" + #ckpt = "/ailab-train/speech/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more_more_piano6/dpo_100.pt" + drop_prompt = False + ####test_scp = "/ailab-train/speech/zhanghaomin/scps/VGGSound/test.scp" + #test_scp = "/ailab-train/speech/zhanghaomin/scps/instruments/test.scp" + #test_scp = "/ailab-train/speech/zhanghaomin/scps/instruments/piano_2h/test.scp" + test_scp = "./tests/piano_2h_test.scp" + #test_scp = "/ailab-train/speech/zhanghaomin/scps/instruments/piano_20h/v2a_giant_piano2/test.scp" + start = 0 + end = 2 + step = 1 + ####out_dir = "./outputs_vgg/" + out_dir = "./outputs_piano/" + #out_dir = "./outputs2t_20h_dpo/" + + +import torch +from e2_tts_pytorch.e2_tts_crossatt3 import E2TTS, DurationPredictor +from e2_tts_pytorch.e2_tts_crossatt3 import MelSpec, EncodecWrapper + +from torch.optim import Adam +from torch.utils.data import DataLoader, Dataset +from datasets import load_dataset + +from e2_tts_pytorch.trainer_multigpus_alldatas3 import HFDataset, Text2AudioDataset + +from einops import einsum, rearrange, repeat, reduce, pack, unpack +import torchaudio + +from datetime import datetime +import json +import numpy as np +import os +from moviepy.editor import VideoFileClip, AudioFileClip +import traceback + + +audiocond_drop_prob = 1.1 +#audiocond_drop_prob = 0.3 +#cond_proj_in_bias = True +#cond_drop_prob = 1.1 +cond_drop_prob = -0.1 +prompt_drop_prob = -0.1 +#prompt_drop_prob = 1.1 +video_text = True + + +def main(): + #duration_predictor = DurationPredictor( + # transformer = dict( + # dim = 512, + # depth = 6, + # ) + #) + duration_predictor = None + + e2tts = E2TTS( + duration_predictor = duration_predictor, + transformer = dict( + #depth = 12, + #dim = 512, + #heads = 8, + #dim_head = 64, + depth = 12, + dim = 1024, + dim_text = 1280, + heads = 16, + dim_head = 64, + if_text_modules = (cond_drop_prob < 1.0), + if_cross_attn = (prompt_drop_prob < 1.0), + if_audio_conv = True, + if_text_conv = True, + ), + #tokenizer = 'char_utf8', + tokenizer = 'phoneme_zh', + audiocond_drop_prob = audiocond_drop_prob, + cond_drop_prob = cond_drop_prob, + prompt_drop_prob = prompt_drop_prob, + frac_lengths_mask = (0.7, 1.0), + #audiocond_snr = None, + #audiocond_snr = (5.0, 10.0), + + if_cond_proj_in = (audiocond_drop_prob < 1.0), + #cond_proj_in_bias = cond_proj_in_bias, + if_embed_text = (cond_drop_prob < 1.0) and (not video_text), + if_text_encoder2 = (prompt_drop_prob < 1.0), + if_clip_encoder = video_text, + video_encoder = "clip_vit", + + pretrained_vocos_path = 'facebook/encodec_24khz', + num_channels = 128, + sampling_rate = 24000, + ) + e2tts = e2tts.to("cuda") + + #checkpoint = torch.load("/ckptstorage/zhanghaomin/e2/e2_tts_experiment_v2a_encodec/3000.pt", map_location="cpu") + #checkpoint = torch.load("/ckptstorage/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more/500.pt", map_location="cpu") + #checkpoint = torch.load("/ckptstorage/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more/98500.pt", map_location="cpu") + #checkpoint = torch.load("/ckptstorage/zhanghaomin/e2/e2_tts_experiment_v2a_encodec_more_more_more/190000.pt", map_location="cpu") + checkpoint = torch.load(ckpt, map_location="cpu") + + #for key in list(checkpoint['model_state_dict'].keys()): + # if key.startswith('mel_spec.'): + # del checkpoint['model_state_dict'][key] + # if key.startswith('transformer.text_registers'): + # del checkpoint['model_state_dict'][key] + e2tts.load_state_dict(checkpoint['model_state_dict'], strict=False) + + e2tts.vocos = EncodecWrapper("facebook/encodec_24khz") + for param in e2tts.vocos.parameters(): + param.requires_grad = False + e2tts.vocos.eval() + e2tts.vocos.to("cuda") + + #dataset = HFDataset(load_dataset("parquet", data_files={"test": "/ckptstorage/zhanghaomin/tts/GLOBE/data/test-*.parquet"})["test"]) + #sample = dataset[1] + #mel_spec_raw = sample["mel_spec"].unsqueeze(0) + #mel_spec = rearrange(mel_spec_raw, 'b d n -> b n d') + #print(mel_spec.shape, sample["text"]) + + #out_dir = "/user-fs/zhanghaomin/v2a_generated/v2a_190000_tests/" + #out_dir = "/user-fs/zhanghaomin/v2a_generated/tv2a_98500_clips/" + if not os.path.exists(out_dir): + os.makedirs(out_dir) + + #bs = list(range(10)) + [14,16] + bs = None + + SCORE_THRESHOLD_TRAIN = '{"/zhanghaomin/datas/audiocaps": -9999.0, "/radiostorage/WavCaps": -9999.0, "/radiostorage/AudioGroup": 9999.0, "/ckptstorage/zhanghaomin/audioset": -9999.0, "/ckptstorage/zhanghaomin/BBCSoundEffects": 9999.0, "/ckptstorage/zhanghaomin/CLAP_freesound": 9999.0, "/zhanghaomin/datas/musiccap": -9999.0, "/ckptstorage/zhanghaomin/TangoPromptBank": -9999.0, "audioset": "af-audioset", "/ckptstorage/zhanghaomin/audiosetsl": 9999.0, "/ckptstorage/zhanghaomin/giantsoundeffects": -9999.0}' # /root/datasets/ /radiostorage/ + SCORE_THRESHOLD_TRAIN = json.loads(SCORE_THRESHOLD_TRAIN) + for key in SCORE_THRESHOLD_TRAIN: + if key == "audioset": + continue + if SCORE_THRESHOLD_TRAIN[key] <= -9000.0: + SCORE_THRESHOLD_TRAIN[key] = -np.inf + print("SCORE_THRESHOLD_TRAIN", SCORE_THRESHOLD_TRAIN) + stft = EncodecWrapper("facebook/encodec_24khz") + eval_dataset = Text2AudioDataset(None, "val_instruments", None, None, None, -1, -1, stft, 0, True, SCORE_THRESHOLD_TRAIN, "/zhanghaomin/codes2/audiocaption/msclapcap_v1.list", -1.0, 1, 1, [drop_prompt], None, 0, vgg_test=[test_scp, start, end, step], video_encoder="clip_vit") + ####eval_dataset = Text2AudioDataset(None, "val_vggsound", None, None, None, -1, -1, stft, 0, True, SCORE_THRESHOLD_TRAIN, "/zhanghaomin/codes2/audiocaption/msclapcap_v1.list", -1.0, 1, 1, [drop_prompt], None, 0, vgg_test=[test_scp, start, end, step], video_encoder="clip_vit") + eval_dataloader = DataLoader(eval_dataset, shuffle=False, batch_size=1, collate_fn=eval_dataset.collate_fn, num_workers=1, drop_last=False, pin_memory=True) + i = 0 + for b, batch in enumerate(eval_dataloader): + if (bs is not None) and (b not in bs): + continue + #text, mel_spec, _, mel_lengths = batch + text, mel_spec, video_paths, mel_lengths, video_drop_prompt, audio_drop_prompt, frames, midis = batch + print(mel_spec.shape, mel_lengths, text, video_paths, video_drop_prompt, audio_drop_prompt, frames.shape if frames is not None and not isinstance(frames, float) else frames, midis.shape if midis is not None else midis, midis.sum() if midis is not None else midis) + text = text[i:i+1] + mel_spec = mel_spec[i:i+1, 0:mel_lengths[i], :] + mel_lengths = mel_lengths[i:i+1] + video_paths = video_paths[i:i+1] + video_path = out_dir + video_paths[0].replace("/", "__") + audio_path = video_path.replace(".mp4", ".wav") + + name = video_paths[0].rsplit("/", 1)[1].rsplit(".", 1)[0] + + num = 1 + + l = mel_lengths[0] + #cond = mel_spec.repeat(num, 1, 1) + cond = torch.randn(num, l, e2tts.num_channels) + duration = torch.tensor([l]*num, dtype=torch.int32) + lens = torch.tensor([l]*num, dtype=torch.int32) + print(datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3], "start") + #e2tts.sample(text=[""]*num, duration=duration.to("cuda"), lens=lens.to("cuda"), cond=cond.to("cuda"), save_to_filename="test.wav", steps=16, cfg_strength=3.0, remove_parallel_component=False, sway_sampling=True) + e2tts.sample(text=None, duration=duration.to("cuda"), lens=lens.to("cuda"), cond=cond.to("cuda"), save_to_filename=audio_path, steps=64, prompt=text*num, video_drop_prompt=video_drop_prompt, audio_drop_prompt=audio_drop_prompt, cfg_strength=2.0, remove_parallel_component=False, sway_sampling=True, video_paths=video_paths, frames=(frames if frames is None or isinstance(frames, float) else frames.to("cuda")), midis=(midis if midis is None else midis.to("cuda"))) + print(datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3], "sample") + #one_audio = e2tts.vocos.decode(mel_spec_raw.to("cuda")) + #one_audio = e2tts.vocos.decode(cond.transpose(-1,-2).to("cuda")) + #print(datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3], "vocoder") + #torchaudio.save("ref.wav", one_audio.detach().cpu(), sample_rate = e2tts.sampling_rate) + + try: + os.system("cp \"" + video_paths[0] + "\" \"" + video_path + "\"") + video = VideoFileClip(video_path) + audio = AudioFileClip(audio_path) + print("duration", video.duration, audio.duration) + if video.duration >= audio.duration: + video = video.subclip(0, audio.duration) + else: + audio = audio.subclip(0, video.duration) + final_video = video.set_audio(audio) + final_video.write_videofile(video_path.replace(".mp4", ".v2a.mp4"), codec="libx264", audio_codec="aac") + print("\"" + video_path.replace(".mp4", ".v2a.mp4") + "\"") + except Exception as e: + print("Exception write_videofile:", video_path.replace(".mp4", ".v2a.mp4")) + traceback.print_exc() + + if False: + if not os.path.exists(out_dir+"groundtruth/"): + os.makedirs(out_dir+"groundtruth/") + if not os.path.exists(out_dir+"generated/"): + os.makedirs(out_dir+"generated/") + duration_gt = video.duration + duration_gr = final_video.duration + duration = min(duration_gt, duration_gr) + audio_gt = video.audio.subclip(0, duration) + audio_gr = final_video.audio.subclip(0, duration) + audio_gt.write_audiofile(out_dir+"groundtruth/"+name+".wav", fps=24000) + audio_gr.write_audiofile(out_dir+"generated/"+name+".wav", fps=24000) + + +if __name__ == "__main__": + main() + diff --git a/src/merge_wavs.py b/src/merge_wavs.py new file mode 100644 index 0000000000000000000000000000000000000000..77cc912d3c3415904157caa91aaded7eeb228cb6 --- /dev/null +++ b/src/merge_wavs.py @@ -0,0 +1,119 @@ +import os + + +if False: + prefix = "__ailab-train__speech__zhanghaomin__scps__instruments__piano_2h__piano_2h_cropped2_cuts__" + + + #path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_4_4000/" + #new_path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_4_4000_20s/" + #new_path2 = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_4_4000_10s/" + + + #path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_4_2_8000/" + #new_path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_4_2_8000_20s/" + #new_path2 = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_4_2_8000_10s/" + + + path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_ab/" + new_path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_ab_20s/" + new_path2 = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_ab_10s/" + + + os.mkdir(new_path) + os.mkdir(new_path2) + + + utt = "nwwHuxHMIpc" + + for index in range(13): + os.system("sox %s %s %s"%(path+prefix+utt+"."+str(index*2).zfill(8)+".wav", path+prefix+utt+"."+str(index*2+1).zfill(8)+".wav", new_path+utt+"."+str(index+1)+".wav")) + + for index in range(27): + os.system("cp %s %s"%(path+prefix+utt+"."+str(index).zfill(8)+".wav", new_path2+utt+"."+str(index+1)+".wav")) + + + utt = "ra1jf2nzJPg" + + for index in range(12): + os.system("sox %s %s %s"%(path+prefix+utt+"."+str(index*2).zfill(8)+".wav", path+prefix+utt+"."+str(index*2+1).zfill(8)+".wav", new_path+utt+"."+str(index+1)+".wav")) + + for index in range(24): + os.system("cp %s %s"%(path+prefix+utt+"."+str(index).zfill(8)+".wav", new_path2+utt+"."+str(index+1)+".wav")) + + + utt = "u5nBBJndN3I" + + for index in range(12): + os.system("sox %s %s %s"%(path+prefix+utt+"."+str(index*2).zfill(8)+".wav", path+prefix+utt+"."+str(index*2+1).zfill(8)+".wav", new_path+utt+"."+str(index+1)+".wav")) + + for index in range(25): + os.system("cp %s %s"%(path+prefix+utt+"."+str(index).zfill(8)+".wav", new_path2+utt+"."+str(index+1)+".wav")) + + + + +if True: + from moviepy.editor import VideoFileClip, AudioFileClip + + + prefix = "__ailab-train__speech__zhanghaomin__scps__instruments__piano_20h__v2a_giant_piano2__" + + + #path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_20h_base/" + #new_path2 = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_20h_base_10s/" + + #path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_20h_vel/" + #new_path2 = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_20h_vel_10s/" + + path = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_20h_dpo/" + new_path2 = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/outputs2t_20h_dpo_10s/" + + #path_gt = "/ailab-train/speech/zhanghaomin/codes3/e2-tts-pytorch-main/gt_20h_cut10/" + + + os.mkdir(new_path2) + + #os.mkdir(path_gt) + + + utt = "amazing_grace__aamazing_arace" + + for index in range(8): + if not os.path.exists(path+prefix+utt+"_"+str(index+1)+".wav"): + continue + os.system("cp %s %s"%(path+prefix+utt+"_"+str(index+1)+".wav", new_path2+utt+"."+str(index+1)+".wav")) + + #audio = AudioFileClip(path+prefix+utt+"_"+str(index+1)+".mp4") + #if audio.duration > 10.0: + # audio = audio.subclip(0, 10.0) + #audio.write_audiofile(path_gt+utt+"."+str(index+1)+".wav", fps=24000, ffmpeg_params=["-ac", "1"]) + + + utt = "Mad_World__amad_world" + + for index in range(24): + if not os.path.exists(path+prefix+utt+"_"+str(index+1)+".wav"): + continue + os.system("cp %s %s"%(path+prefix+utt+"_"+str(index+1)+".wav", new_path2+utt+"."+str(index+1)+".wav")) + + #audio = AudioFileClip(path+prefix+utt+"_"+str(index+1)+".mp4") + #if audio.duration > 10.0: + # audio = audio.subclip(0, 10.0) + #audio.write_audiofile(path_gt+utt+"."+str(index+1)+".wav", fps=24000, ffmpeg_params=["-ac", "1"]) + + + utt = "Minuet_In_G_Minor__aminuet_in_g_minor" + + for index in range(14): + if not os.path.exists(path+prefix+utt+"_"+str(index+1)+".wav"): + continue + os.system("cp %s %s"%(path+prefix+utt+"_"+str(index+1)+".wav", new_path2+utt+"."+str(index+1)+".wav")) + + #audio = AudioFileClip(path+prefix+utt+"_"+str(index+1)+".mp4") + #if audio.duration > 10.0: + # audio = audio.subclip(0, 10.0) + #audio.write_audiofile(path_gt+utt+"."+str(index+1)+".wav", fps=24000, ffmpeg_params=["-ac", "1"]) + + + diff --git a/tests/VGGSound/video/1u1orBeV4xI_000428.mp4 b/tests/VGGSound/video/1u1orBeV4xI_000428.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..6db79c137abeb903f334e67f9807702b95bf738c --- /dev/null +++ b/tests/VGGSound/video/1u1orBeV4xI_000428.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7126d4c3d0a3c1d7a9b9f83284864ef672d8d413c04dd15d505b874e1efec900 +size 4165561 diff --git a/tests/VGGSound/video/1uCzQCdCC1U_000170.mp4 b/tests/VGGSound/video/1uCzQCdCC1U_000170.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..7ccd8991cf343efdf522daaace1d833abdfe9dae --- /dev/null +++ b/tests/VGGSound/video/1uCzQCdCC1U_000170.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2db37c8eabdaeee87d7ae24d9b570936bd44338e6d881ea9d1427c39b3380ae5 +size 2258372 diff --git a/tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000000.mp4 b/tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000000.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..45e267ff7ef2ee18337aa5a637cb2366e79bc08a --- /dev/null +++ b/tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000000.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:00b02e3805a9213a1d5a871b38e5cfe992fd5378e09ecff084706b99935aab25 +size 614113 diff --git a/tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000001.mp4 b/tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000001.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..e845c16284c1ba28b545ab9949db6a6bd6e3e29b --- /dev/null +++ b/tests/piano_2h_cropped2_cuts/nwwHuxHMIpc.00000001.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3826b8d19e99126024330d6405a82974c9bdd8edf19d4ba7368bbc5725440d14 +size 670256 diff --git a/tests/piano_2h_test.scp b/tests/piano_2h_test.scp new file mode 100644 index 0000000000000000000000000000000000000000..cea1049cb30df7c6f1a99c59e4e39730c8094ae5 --- /dev/null +++ b/tests/piano_2h_test.scp @@ -0,0 +1,76 @@ 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+/ailab-train/speech/zhanghaomin/VGGSound/video/zZnDRrwcbTE_000021.mp4 mosquito buzzing +/ailab-train/speech/zhanghaomin/VGGSound/video/zZsetnYA5RM_000001.mp4 cuckoo bird calling +/ailab-train/speech/zhanghaomin/VGGSound/video/z_WasI8m3iM_000012.mp4 cat growling +/ailab-train/speech/zhanghaomin/VGGSound/video/zayC5mUo7sY_000100.mp4 playing drum kit +/ailab-train/speech/zhanghaomin/VGGSound/video/zbiJEml563w_000030.mp4 police car (siren) +/ailab-train/speech/zhanghaomin/VGGSound/video/zcPFRKqTD9I_000470.mp4 cricket chirping +/ailab-train/speech/zhanghaomin/VGGSound/video/zcrQlstpqUI_000131.mp4 playing castanets +/ailab-train/speech/zhanghaomin/VGGSound/video/zd3SKCVbaWg_000001.mp4 people eating crisps +/ailab-train/speech/zhanghaomin/VGGSound/video/zdFS8K0fJJI_000297.mp4 bouncing on trampoline +/ailab-train/speech/zhanghaomin/VGGSound/video/zdZstaYr9hY_000200.mp4 playing sitar +/ailab-train/speech/zhanghaomin/VGGSound/video/zdktzavoISw_000104.mp4 people marching +/ailab-train/speech/zhanghaomin/VGGSound/video/zdktzavoISw_000167.mp4 people marching +/ailab-train/speech/zhanghaomin/VGGSound/video/zdtVT2xwrHU_000030.mp4 male speech, man speaking +/ailab-train/speech/zhanghaomin/VGGSound/video/ze1hFgnTcdE_000140.mp4 playing double bass +/ailab-train/speech/zhanghaomin/VGGSound/video/zexkXRiD9zk_000050.mp4 sailing +/ailab-train/speech/zhanghaomin/VGGSound/video/zey5f-NjbtE_000002.mp4 people giggling +/ailab-train/speech/zhanghaomin/VGGSound/video/zey5f-NjbtE_000201.mp4 people giggling +/ailab-train/speech/zhanghaomin/VGGSound/video/zfUTuz6G6R8_000229.mp4 people eating apple +/ailab-train/speech/zhanghaomin/VGGSound/video/zfWvVJbYaiU_000120.mp4 electric shaver, electric razor shaving +/ailab-train/speech/zhanghaomin/VGGSound/video/zg6UfeKCtr4_000075.mp4 playing table tennis +/ailab-train/speech/zhanghaomin/VGGSound/video/zgI-Lr6Pbcs_000030.mp4 playing theremin +/ailab-train/speech/zhanghaomin/VGGSound/video/zgM0pD0JIqc_000000.mp4 train whistling +/ailab-train/speech/zhanghaomin/VGGSound/video/zgM0pD0JIqc_000015.mp4 train whistling +/ailab-train/speech/zhanghaomin/VGGSound/video/zgR4fR2nPvM_000139.mp4 tractor digging +/ailab-train/speech/zhanghaomin/VGGSound/video/zglG6Kx2eSw_000032.mp4 otter growling +/ailab-train/speech/zhanghaomin/VGGSound/video/zgmAvQF1ojQ_000049.mp4 cow lowing +/ailab-train/speech/zhanghaomin/VGGSound/video/zguk_hYrBY4_000041.mp4 cat growling +/ailab-train/speech/zhanghaomin/VGGSound/video/zh4tznWde1M_000330.mp4 cat purring +/ailab-train/speech/zhanghaomin/VGGSound/video/zhFzDzfOCik_000111.mp4 volcano explosion +/ailab-train/speech/zhanghaomin/VGGSound/video/zhOI8JLAO8Q_001073.mp4 swimming +/ailab-train/speech/zhanghaomin/VGGSound/video/zi5NCXyuLMI_000230.mp4 gibbon howling +/ailab-train/speech/zhanghaomin/VGGSound/video/ziPit3oAWwo_000049.mp4 whale calling +/ailab-train/speech/zhanghaomin/VGGSound/video/zj5JwVSZJJ4_000222.mp4 hail +/ailab-train/speech/zhanghaomin/VGGSound/video/zjDpx3YU7mU_000270.mp4 shot football +/ailab-train/speech/zhanghaomin/VGGSound/video/zjRqBIxxdrg_000362.mp4 playing bass drum +/ailab-train/speech/zhanghaomin/VGGSound/video/zk1GeJP6Y00_000000.mp4 sea lion barking +/ailab-train/speech/zhanghaomin/VGGSound/video/zk4YZ_mbx2c_000012.mp4 playing tennis +/ailab-train/speech/zhanghaomin/VGGSound/video/zkcM-cg52is_000008.mp4 ferret dooking +/ailab-train/speech/zhanghaomin/VGGSound/video/zktc6NQrZ_8_000130.mp4 playing flute +/ailab-train/speech/zhanghaomin/VGGSound/video/zlH9KxAhP5Q_000110.mp4 dog growling +/ailab-train/speech/zhanghaomin/VGGSound/video/zmNfxr_2Rdw_000160.mp4 playing guiro +/ailab-train/speech/zhanghaomin/VGGSound/video/zmVhTFChkWI_000072.mp4 disc scratching +/ailab-train/speech/zhanghaomin/VGGSound/video/zml4ewtfjbA_000117.mp4 planing timber +/ailab-train/speech/zhanghaomin/VGGSound/video/zml4ewtfjbA_000242.mp4 planing timber +/ailab-train/speech/zhanghaomin/VGGSound/video/znKsInR4DN0_000183.mp4 playing djembe +/ailab-train/speech/zhanghaomin/VGGSound/video/zoo7FpCz7F0_000332.mp4 playing snare drum +/ailab-train/speech/zhanghaomin/VGGSound/video/zpWuikVorYg_000032.mp4 elk bugling +/ailab-train/speech/zhanghaomin/VGGSound/video/zr88Jqze7_U_000034.mp4 chimpanzee pant-hooting +/ailab-train/speech/zhanghaomin/VGGSound/video/zra3SOgAsyg_000031.mp4 chicken clucking +/ailab-train/speech/zhanghaomin/VGGSound/video/zrd5rRF4Jkg_000011.mp4 pig oinking +/ailab-train/speech/zhanghaomin/VGGSound/video/zrklTYnpE80_000098.mp4 popping popcorn +/ailab-train/speech/zhanghaomin/VGGSound/video/zrrM6Qg2Dwg_000030.mp4 playing steelpan +/ailab-train/speech/zhanghaomin/VGGSound/video/zsSLTyIhuf0_000000.mp4 playing tennis +/ailab-train/speech/zhanghaomin/VGGSound/video/zsZr_xJ7ECQ_000029.mp4 baby laughter +/ailab-train/speech/zhanghaomin/VGGSound/video/zt-j0_ZVzxg_000480.mp4 telephone bell ringing +/ailab-train/speech/zhanghaomin/VGGSound/video/ztTsKk1Fxgg_000041.mp4 skiing +/ailab-train/speech/zhanghaomin/VGGSound/video/ztfegVzqeCI_000030.mp4 playing theremin +/ailab-train/speech/zhanghaomin/VGGSound/video/ztlvu_7eQIE_000164.mp4 electric grinder grinding +/ailab-train/speech/zhanghaomin/VGGSound/video/ztn3BA42BO0_000017.mp4 orchestra +/ailab-train/speech/zhanghaomin/VGGSound/video/zu2LE5amQ5g_000026.mp4 smoke detector beeping +/ailab-train/speech/zhanghaomin/VGGSound/video/zuqaQqmtzXs_000095.mp4 playing tuning fork +/ailab-train/speech/zhanghaomin/VGGSound/video/zvKOi8N1_Dg_000122.mp4 popping popcorn +/ailab-train/speech/zhanghaomin/VGGSound/video/zw4X8p5zVZE_000023.mp4 missile launch +/ailab-train/speech/zhanghaomin/VGGSound/video/zwBmiXviAAM_000202.mp4 missile launch +/ailab-train/speech/zhanghaomin/VGGSound/video/zwjAqa7-Nv8_000008.mp4 playing darts +/ailab-train/speech/zhanghaomin/VGGSound/video/zxPbEuAVEZU_000000.mp4 playing gong +/ailab-train/speech/zhanghaomin/VGGSound/video/zx_vcwOsDO4_000050.mp4 tapping guitar +/ailab-train/speech/zhanghaomin/VGGSound/video/zxd98l89Prk_000036.mp4 lions roaring +/ailab-train/speech/zhanghaomin/VGGSound/video/zxpo56cpUBU_000007.mp4 people booing +/ailab-train/speech/zhanghaomin/VGGSound/video/zxxWGaZIxD0_000289.mp4 alarm clock ringing +/ailab-train/speech/zhanghaomin/VGGSound/video/zyJ9oIWMEBQ_000110.mp4 shot football +/ailab-train/speech/zhanghaomin/VGGSound/video/zyMH_BNFQfA_000032.mp4 cheetah chirrup +/ailab-train/speech/zhanghaomin/VGGSound/video/zywjuHhWmF8_000003.mp4 striking bowling +/ailab-train/speech/zhanghaomin/VGGSound/video/zz0fdUGTHWo_000045.mp4 chimpanzee pant-hooting +/ailab-train/speech/zhanghaomin/VGGSound/video/zzFdhaiG_Hk_000095.mp4 popping popcorn +/ailab-train/speech/zhanghaomin/VGGSound/video/zzbTaK7CXJY_000030.mp4 wind noise +/ailab-train/speech/zhanghaomin/VGGSound/video/zzqrZOq928w_000055.mp4 train horning +/ailab-train/speech/zhanghaomin/VGGSound/video/zzvCPtdNxNo_000068.mp4 civil defense siren diff --git a/tests/scps/musiccap/musiccaps.jsonl b/tests/scps/musiccap/musiccaps.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4bdebfdc762dc771ed7be369abee2e606e227ebd --- /dev/null +++ b/tests/scps/musiccap/musiccaps.jsonl @@ -0,0 +1,5521 @@ +{"id": "-0Gj8-vB1q4", "caption": "The low quality recording features a ballad song that contains sustained strings, mellow piano melody and soft female vocal singing over it. It sounds sad and soulful, like something you would hear at Sunday services.", "audio": "/zhanghaomin/datas/musiccap/music_data/-0Gj8-vB1q4.wav"} +{"id": "-0SdAVK79lg", "caption": "This song features an electric guitar as the main instrument. The guitar plays a descending run in the beginning then plays an arpeggiated chord followed by a double stop hammer on to a higher note and a descending slide followed by a descending chord run. The percussion plays a simple beat using rim shots. The percussion plays in common time. The bass plays only one note on the first count of each bar. The piano plays backing chords. There are no voices in this song. The mood of this song is relaxing. This song can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/-0SdAVK79lg.wav"} +{"id": "-0vPFx-wRRI", "caption": "a male voice is singing a melody with changing tempos while snipping his fingers rhythmically. The recording sounds like it has been recorded in an empty room. This song may be playing, practicing snipping and singing along.", "audio": "/zhanghaomin/datas/musiccap/music_data/-0vPFx-wRRI.wav"} +{"id": "-0xzrMun0Rs", "caption": "This song contains digital drums playing a simple groove along with two guitars. One strumming chords along with the snare the other one playing a melody on top. An e-bass is playing the footnote while a piano is playing a major and minor chord progression. A trumpet is playing a loud melody alongside the guitar. All the instruments sound flat and are being played by a keyboard. There are little bongo hits in the background panned to the left side of the speakers. Apart from the music you can hear eating sounds and a stomach rumbling. This song may be playing for an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/-0xzrMun0Rs.wav"} +{"id": "-1LrH01Ei1w", "caption": "This song features a rubber instrument being played. The strumming is fast. The melody is played on one fretted string and other open strings. The melody is played on the lower octave and is later repeated on the higher octave. This song can be played at a folk party.", "audio": "/zhanghaomin/datas/musiccap/music_data/-1LrH01Ei1w.wav"} +{"id": "-1OlgJWehn8", "caption": "This clip is three tracks playing consecutively. The first one is an electric guitar lead harmony with a groovy bass line, followed by white noise and then a female vocalisation to a vivacious melody with a keyboard harmony, slick drumming, funky bass lines and male backup. The three songs are unrelated and unsynced.", "audio": "/zhanghaomin/datas/musiccap/music_data/-1OlgJWehn8.wav"} +{"id": "-1UWSisR2zo", "caption": "A male singer sings this groovy melody. The song is a techno dance song with a groovy bass line, strong drumming rhythm and a keyboard accompaniment. The song is so groovy and serves as a dance track for the dancing children. The audio quality is very poor with high gains and hissing noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/-1UWSisR2zo.wav"} +{"id": "-3Kv4fdm7Uk", "caption": "someone is playing a high pitched melody on a steel drum. The file is of poor audio-quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/-3Kv4fdm7Uk.wav"} +{"id": "-4NLarMj4xU", "caption": "The Pop song features a soft female vocal singing over sustained pulsating synth lead, mellow piano melody, sustained synth brass, punchy kick, claps. tinny wide hi hats and high pitched female vocal melody. It sounds emotional, sad, passionate and like something you would hear on a radio.", "audio": "/zhanghaomin/datas/musiccap/music_data/-4NLarMj4xU.wav"} +{"id": "-4SYC2YgzL8", "caption": "low fidelity audio from a live performance featuring a solo direct input acoustic guitar strumming airy, suspended open chords. Also present are occasional ambient sounds, perhaps papers being shuffled.", "audio": "/zhanghaomin/datas/musiccap/music_data/-4SYC2YgzL8.wav"} +{"id": "-5FoeegAgvU", "caption": "The instrumental music features an ensemble that resembles the orchestra. The melody is being played by a brass section while strings provide harmonic accompaniment. At the end of the music excerpt one can hear a double bass playing a long note and then a percussive noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/-5FoeegAgvU.wav"} +{"id": "-5f6hjZf9Yw", "caption": "This folk song features a male voice singing the main melody in an emotional mood. This is accompanied by an accordion playing fills in the background. A violin plays a droning melody. There is no percussion in this song. This song can be played at a Central Asian classical concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/-5f6hjZf9Yw.wav"} +{"id": "-5xOcMJpTUk", "caption": "A male guitarist plays the guitar and speaks about technique in this online video tutorial. The male voice is strong and commanding, along with guitar string twang sounds, clearly demonstrating the technique. The audio quality is mediocre.", "audio": "/zhanghaomin/datas/musiccap/music_data/-5xOcMJpTUk.wav"} +{"id": "-6HBGg1cAI0", "caption": "This middle eastern folk song features a male voice. This is accompanied by a string instrument called the oud playing the melody in between lines. A variety of middle-eastern percussion instruments are played in the background. A tambourine is played on every count. A darbuka plays a simple beat. This folk song can be played in a movie scene set in a Moroccan market.", "audio": "/zhanghaomin/datas/musiccap/music_data/-6HBGg1cAI0.wav"} +{"id": "-6QGvxvaTkI", "caption": "The low quality recording features a live performance of a traditional song and it consists of an echoing male vocal singing over acoustic strings melody, plucked strings melody and wooden percussion. There is a crowd chattering noise in the background. The recording is a bit noisy and it sounds passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/-6QGvxvaTkI.wav"} +{"id": "-6pcgdLfb_A", "caption": "This is an R&B/soul music piece. There is a male vocalist singing melodically and in a sensual manner over multiple tracks. The melody of the beat is provided by a string sample. There is a strong bass sound in the piece. The rhythm is provided by a groovy electronic drum beat. There is an urban feel to this piece. It could be used in the soundtrack of a TV series where two characters are sharing intimate moments.", "audio": "/zhanghaomin/datas/musiccap/music_data/-6pcgdLfb_A.wav"} +{"id": "-7B9tPuIP-w", "caption": "A male voice narrates a monologue to the rhythm of a song in the background. The song is fast tempo with enthusiastic drumming, groovy bass lines,cymbal ride, keyboard accompaniment ,electric guitar and animated vocals. The song plays softly in the background as the narrator speaks and burgeons when he stops. The song is a classic Rock and Roll and the narration is a Documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/-7B9tPuIP-w.wav"} +{"id": "-7wUQP6G5EQ", "caption": "The low quality recording features a renaissance music that consists of soft wooden percussion and mellow, harmonized flute melody playing on top of it. The recording is a bit noisy, but it also sounds soulful, mellow, passionate, emotional and vintage - It really puts the listener in a period of renaissance.", "audio": "/zhanghaomin/datas/musiccap/music_data/-7wUQP6G5EQ.wav"} +{"id": "-88me9bBzrk", "caption": "Someone is playing a fast melody on a low bansuri flute along with someone playing tablas and a shrutibox in the background. This song may be playing at a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/-88me9bBzrk.wav"} +{"id": "-8C-gydUbR8", "caption": "A children\u2019s choir sings this devotional melody. The song is medium tempo with a steady bass line, drumming rhythm and clapping percussion. The song is black gospel choral music played in front of a live congregation. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/-8C-gydUbR8.wav"} +{"id": "-8cgbhIR_pw", "caption": "The low quality recording features a cover of a ballad song that consists of passionate, muddy male vocal singing over arpeggiated acoustic guitar melody. It sounds noisy, muddy and messy, as the frequencies are clashing, but it is also emotional and raw.", "audio": "/zhanghaomin/datas/musiccap/music_data/-8cgbhIR_pw.wav"} +{"id": "-BHPu-dPmWQ", "caption": "The Alternative/Indie song features an intimate, widely spread, mixed vocals singing over noisy snare, punchy kick, wide tinny hi hats, electric guitar melody, synth lead melody and groovy bass guitar. At the end of the loop there is a short snare roll and some claps. It sounds easygoing and melancholic thanks to those vocals.", "audio": "/zhanghaomin/datas/musiccap/music_data/-BHPu-dPmWQ.wav"} +{"id": "-BIMKnb3tlo", "caption": "This is a Hindustani classical music piece. There is a harmonium playing the main tune. A bansuri joins in to play, supporting a melody every now and then. The rhythmic background consists of the tabla percussion and the electronic drums. The atmosphere of the piece is joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/-BIMKnb3tlo.wav"} +{"id": "-Bu7YaslRW0", "caption": "A synth pad is playing a drone sound in the lower mid range. Cymbals are creating atmosphere while a flute/string/brass sound is playing a melody. The whole recording is full of reverb. This song may be playing in a forest documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/-Bu7YaslRW0.wav"} +{"id": "-ByoSbgzr4M", "caption": "This clip is an electronic guitar instrumental. The tempo is fast with a vigorous, lively electric guitar lead without any instrumentation. The music is rapid,controlled, intense and vigorous with immense control and dexterity with the instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/-ByoSbgzr4M.wav"} +{"id": "-CUp_Tmg2Y0", "caption": "The low quality recording features a drum solo that consists of a double pedal kick, punchy snare, shimmering cymbals and boomy toms. It sounds energetic and manic, thanks to that kick pattern. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/-CUp_Tmg2Y0.wav"} +{"id": "-DeAdhYKbGE", "caption": "A bagpipe ensemble playing a quick melody in unison, employing trills to ornament it.", "audio": "/zhanghaomin/datas/musiccap/music_data/-DeAdhYKbGE.wav"} +{"id": "-Dtir74TiUM", "caption": "This is a drum & bass music piece. There is a constantly repeating hollering sample accompanied by rapid turntable scratching. A synth sound can be heard playing an ominous tune. The rhythmic background consists of a fast-tempo electronic drum beat. The atmosphere is energetic. This piece could be used in the soundtrack of a car racing game. It could also be playing at nightclubs during early-2000s themed parties.", "audio": "/zhanghaomin/datas/musiccap/music_data/-Dtir74TiUM.wav"} +{"id": "-EVRXQpt1-8", "caption": "Someone is playing a guitar-like instrument in a tremolo fashion along with someone playing a melody on a harp along with a bass playing the root note. A male voice is singing, sounding sad and sensitive. A backing voice that seems to be female is singing along, providing harmonies. This song may be playing in a dance performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/-EVRXQpt1-8.wav"} +{"id": "-FEPOSP7ay0", "caption": "The low quality recording features loud bells and metallic squeaking sounds. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/-FEPOSP7ay0.wav"} +{"id": "-FFx68qSAuY", "caption": "This is a punk rock music piece. There are male vocals singing in a grunt-like manner. The melody is being played by an electric guitar while a bass guitar plays in the background. The rhythm consists of a slightly fast-paced rock acoustic drum beat. The piece has an aggressive atmosphere. It could be used in the soundtrack of an action-filled video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/-FFx68qSAuY.wav"} +{"id": "-FlvaZQOr2I", "caption": "The song is an instrumental. The song is medium tempo, with a horn and string section and a drum section playing to a crescendo, followed by a low frequency thumping rhythm. The song is an instrumental soundtrack for an animated show. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/-FlvaZQOr2I.wav"} +{"id": "-Gf4Ihv1zwc", "caption": "This is a Christmas music piece with heavy influences from Celtic music. There is a female vocalist singing melodically as the lead. The melodic background is provided by the strings and the piano and at the same time Celtic instruments that resemble a harp and a dulcimer. There is a calming and positive aura to this piece. It could be playing in the background at a Christmas party. It could also be used in Christmas-themed shows or social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/-Gf4Ihv1zwc.wav"} +{"id": "-IZbvEO9wzU", "caption": "This is a heavily edited version of a birthday song. The track has been transposed to make the original vocal sound like a little girl which resulted in a chipmunk vocal effect. The piano playing the melody and the electronic drum beat is at an irritatingly higher pitch than normal. This creates a bizarre atmosphere. It could be used in nightmare sequences in video games or TV shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/-IZbvEO9wzU.wav"} +{"id": "-JVWfFPBl84", "caption": "This audio clip features the sound produced at a particular frequency by a Tibetan singing bowl. This produces a continuous ringing sound. Toward the end of the clip, some other animal sounds can be heard. There are no other instruments in this song. This song can be played at a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/-JVWfFPBl84.wav"} +{"id": "-JvB5AL59fM", "caption": "An acoustic drum is playing a simple rock groove with some drum fills on the toms and snare along with a distorted e-bass and e-guitar playing the same line. Panned to the right side of the speaker you can hear a piano sound playing a little melody. A female voice is singing a happy sounding melody while male backing voices are supporting her. This song may be playing sitting in your room enjoying being at home alone.", "audio": "/zhanghaomin/datas/musiccap/music_data/-JvB5AL59fM.wav"} +{"id": "-M-6VinyMiY", "caption": "The low quality recording features a rock song that consists of flat male vocal singing over sustained and arpeggiated electric guitar melodies, followed by snappy rimshots, soft kick, shimmering hi hats and groovy bass guitar. It sounds emotional and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/-M-6VinyMiY.wav"} +{"id": "-M6K3QoHh40", "caption": "The low quality recording features a R&B song playing on a speaker, judging by the reverberant and boomy sound of it. The song consists of passionate male vocal singing over shimmering hi hats, claps, groovy bass and \"4 on the floor\" kick pattern, It sounds passionate, like something you would dance to with your partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/-M6K3QoHh40.wav"} +{"id": "-NmjCyqIavI", "caption": "This is an amateur recording of a female voice beatboxing. It is a funny recording. It could be playing in the background of comedic social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/-NmjCyqIavI.wav"} +{"id": "-O9mnfC61Ac", "caption": "This is a country music piece. There is a fiddle playing the main melody. The acoustic guitar and the electric guitar are playing gently in the background. The song has a slow tempo. The atmosphere is sentimental. This piece can be used in the soundtrack of an American drama movie, especially during the scenes where the feeling of longing is emphasized.", "audio": "/zhanghaomin/datas/musiccap/music_data/-O9mnfC61Ac.wav"} +{"id": "-OAyRsvFGgc", "caption": "The low quality recording features a cover of a rock song that consists of an electric guitar solo melody played over playback instrumental. The instrumental features a punchy kick and snare hits, soft cymbals and smooth bass. It sounds passionate, even though the recording is muffled and noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/-OAyRsvFGgc.wav"} +{"id": "-OUIEnuNd1I", "caption": "This is a classical music piece belonging to the baroque period. The piece is being performed with a harp. There is a catchy tune being played with a positive aura. This piece could suit well as wedding music. It could be used in the soundtrack of a documentary. It could also be playing in the background of a classy restaurant or a museum.", "audio": "/zhanghaomin/datas/musiccap/music_data/-OUIEnuNd1I.wav"} +{"id": "-Q9MTRXS4bE", "caption": "This music is a spirited instrumental. The tempo is fast with an animated Piano harmony, synthesiser arrangements, synthesised violins, rhythmic digital drums, funky bass lines and electronic sounds. The music is superimposed over sounds of tapping and rhythmic beeping. The music is happy, perky, upbeat, enthusiastic, lively and spirited.", "audio": "/zhanghaomin/datas/musiccap/music_data/-Q9MTRXS4bE.wav"} +{"id": "-QuWdnmn-kM", "caption": "This is a lullaby that features a main melody made with a xylophone that has a bright sound. A sustained piano synth creates a dreamy and sleepy ambience sound. A subtle cello plays single chords that bounce from one beat to the next. This is a song a baby could fall asleep to.", "audio": "/zhanghaomin/datas/musiccap/music_data/-QuWdnmn-kM.wav"} +{"id": "-R0267o4lLk", "caption": "You can hear two people playing various percussive instruments. One is holding the same beat playing on congas while the other is playing a solo changing rhythms and percussive sounds in a complex manner. This song may be playing live demonstrating a solo run.", "audio": "/zhanghaomin/datas/musiccap/music_data/-R0267o4lLk.wav"} +{"id": "-RYtUAsNhF0", "caption": "This is a poor quality instrumental piece played in the background of a sign language video. There is an optimistic sounding tune being played by the strings, the piano and the acoustic guitar. The atmosphere is mellow and gentle. Samples from this piece could be lifted to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/-RYtUAsNhF0.wav"} +{"id": "-SD43H5B5hE", "caption": "There is a low sound that reminds of a heartbeat rising in tempo before a splash-like metallic sound with reverb comes in and breaks the atmosphere in half. This audio may be used for a movie scene. This audio is in poor quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/-SD43H5B5hE.wav"} +{"id": "-SWaCArvQug", "caption": "Ambient sound still in the room with a mild background music playing. A male singer sings a passionate melody with subtle background music. The audio quality is very poor with drawer sliding sound and general noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/-SWaCArvQug.wav"} +{"id": "-T4GeTHKtJQ", "caption": "The low quality recording features a compilation of rock songs and it consists of punchy kicks, wide electric guitar melodies, distorted bass guitar, energetic crash cymbals, shimmering hi hats and harmonizing male vocals singing over it. It sounds energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/-T4GeTHKtJQ.wav"} +{"id": "-U16iKiXGuY", "caption": "The low quality recording features a live performance of a R&B song that consists of a mellow piano melody and an emotional female vocal singing over it. There are some noises in the recording, alongside lip smack noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/-U16iKiXGuY.wav"} +{"id": "-Umconw-CRE", "caption": "The low quality recording features a cover of a rock song with a rock instrumental playback playing in the background and electric guitar solo melody playing on top of it. It sounds muffled and noisy, as it was probably recorded with a low quality microphone, but it is still passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/-Umconw-CRE.wav"} +{"id": "-UuEBhule84", "caption": "The low quality recording features a flat male vocal singing over acoustic rhythm guitar chords, after which that same vocal is talking. The song sounds passionate, while the recording, overall, is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/-UuEBhule84.wav"} +{"id": "-VI2IRq17rs", "caption": "In this clip, a large bell is rung and left to ring. We can hear the resonance in the room as the bell rings. There is then the faint sound of a male speaking in the background. It's a live recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/-VI2IRq17rs.wav"} +{"id": "-VclCul6FrI", "caption": "The low quality recording features a jazzy organ keys melody. The recording is in mono, noisy, muffled and slightly distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/-VclCul6FrI.wav"} +{"id": "-Vo4CAMX26U", "caption": "The low quality recording features a low windpipe vocal sound played in nature, surrounded by flowing water and chirping birds sound effects. Sounds a bit harsh and loud, as the tone of the windpipe is constantly changing.", "audio": "/zhanghaomin/datas/musiccap/music_data/-Vo4CAMX26U.wav"} +{"id": "-W5c6CeUMPE", "caption": "This is a Swiss folk music piece. There is a male vocal and there is a female vocal. They are yodeling as a duet. The melody in the background is being played by a melodeon. There is a pastoral feel to it. This piece could be used in the soundtrack of a movie that takes place in the Alps region.", "audio": "/zhanghaomin/datas/musiccap/music_data/-W5c6CeUMPE.wav"} +{"id": "-WvVG0wHcTc", "caption": "The low quality recording features a classical live performance of sustained violin melody, shimmering hi hats, electric guitar melody, theremin solo melody and subtle female vocals at the end of the loop. There are some crowd clapping sounds in the background. It is noisy, in mono and it sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/-WvVG0wHcTc.wav"} +{"id": "-XN0NtrnfMY", "caption": "The low quality recording features a rock song instrumental that consists of shimmering hi hats, punchy snare, groovy bass guitar, acoustic rhythm guitar in the left channel and electric guitar chord progression in the right channel of the stereo image. It sounds energetic and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/-XN0NtrnfMY.wav"} +{"id": "-XkbErI_7EU", "caption": "This slow jazz song features male voices singing the main melody in harmony. This is accompanied by percussion playing a simple beat. The double bass plays the root notes of the chords. Trumpets play a fill in harmony in between lines. A piano plays an arpeggiated chord at the end of the first line. This song has a romantic mood. This song can be played in a classic romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/-XkbErI_7EU.wav"} +{"id": "-YATTKBtmRA", "caption": "This is a hip-hop music piece. There is a crisp synth sound playing the melody. The piece has a strong bass sound. There is a melodic pad with beat repeat effect that uses a piano sample. The rhythmic background is provided by a loud electronic drum beat. The piece is energetic and modern sounding. It could be used in the soundtrack of a sci-fi movie where there is a lot of action going on.", "audio": "/zhanghaomin/datas/musiccap/music_data/-YATTKBtmRA.wav"} +{"id": "-YIT4HBM__g", "caption": "A female vocalist sings this mellifluous song.The tempo is slow with the vocalist singing a soprano, with alto choral harmony. There are sounds of rustling, whirring,scuttling and people talking in the background. The vocals are beautiful, mellifluous,and ethereal.", "audio": "/zhanghaomin/datas/musiccap/music_data/-YIT4HBM__g.wav"} +{"id": "-ZHpNr_KRXU", "caption": "Someone is playing a percussive instrument that reminds a little bit of a tabla while someone else is playing a fast melody on an accordion. A male voice is singing at a higher pitch. This song may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/-ZHpNr_KRXU.wav"} +{"id": "-_6RxZyi30Q", "caption": "This is an amateur recording of a dance performance over a latin dance music piece in the style of zumba. There is a female dance instructor shouting directions to the dancers. There is a male vocalist singing melodically in the background piece. A strong bass and a loud electronic drum beat can be heard very distinctly. The atmosphere is energetic. The quality of the recording is quite poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/-_6RxZyi30Q.wav"} +{"id": "-_OzT7Xyvok", "caption": "Amateur recording of two nylon string guitars playing in flamenco style. The playing is technically challenging yet sloppy.", "audio": "/zhanghaomin/datas/musiccap/music_data/-_OzT7Xyvok.wav"} +{"id": "-bgHkxwoliw", "caption": "Digital drums are playing a four on the floor rhythm with a kick on every beat along with a bassline and a keyboard sound playing short rhythmic chords and a e-guitar playing a simple melody along. A male voice is singing in a higher key. This song may be playing at a folkfest.", "audio": "/zhanghaomin/datas/musiccap/music_data/-bgHkxwoliw.wav"} +{"id": "-cLzki-B06o", "caption": "This is a Kurdish folk music piece. The main melody is first played by the baglama and then by the zurna. The rhythmic background consists of an electronic drum beat and supportive percussive elements. The atmosphere is lively. This piece could be used as an accompaniment piece for a folk dance course such as the halay dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/-cLzki-B06o.wav"} +{"id": "-cQ-jUTEgck", "caption": "This is a live performance of a southern rock piece. There is an electric guitar playing a blues solo. There is a bass guitar playing in the background. The rhythm is being played by the acoustic drums. The atmosphere is groovy. This piece could be playing in the background at a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/-cQ-jUTEgck.wav"} +{"id": "-dVgUSrR8g4", "caption": "This song is a vigorous metal instrumental. The tempo is fast with intense drumming, fiery electric guitar riff, amplified guitar rhythms and energetic keyboard accompaniment. The music is energetic, aggressive, youthful, spirited, goth, intense,psychedelic and trance like. This instrumental is Hard Rock/Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/-dVgUSrR8g4.wav"} +{"id": "-e4wXAy1iVo", "caption": "Two female voices are singing in harmony to a ukulele strumming chords. One of the voices is deeper and the other one higher. This song may be jamming together at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/-e4wXAy1iVo.wav"} +{"id": "-eDAoheZrY8", "caption": "The song is an instrumental. The song is slow tempo with building crescendo , string section harmony, horn section, drums playing steadily and piano accompaniment. The song is suspenseful and builds anticipation. The song is a movie soundtrack and has an average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/-eDAoheZrY8.wav"} +{"id": "-f1DNyngKVY", "caption": "This is an instrumental sitar music piece. The sitar is being played at a medium-to-high range. There is a calming and relaxing atmosphere to this piece. This piece can be used in the background of a meditation video. It could also be played during a meditation session at a course.", "audio": "/zhanghaomin/datas/musiccap/music_data/-f1DNyngKVY.wav"} +{"id": "-f6s6kQEHFY", "caption": "This slow ballad features a female voice singing the main melody. This is accompanied by a repetitive piano melody. The bass plays the root notes of the chords in staccato style in eighth note patterns. Synth horns play in the background at different pitches. The song has an ambient and ethereal feel. The mood of the song is haunting. This song can be played in a sad scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/-f6s6kQEHFY.wav"} +{"id": "-fxh7jAJR8U", "caption": "Male singers sing this vocal harmony. The tempo is medium with a steady drumming rhythm, various percussion tones, keyboard accompaniment, steady bass line and tambourine percussion. The song is soothing and romantic. The song is a retro pop hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/-fxh7jAJR8U.wav"} +{"id": "-hSMzrWZCAE", "caption": "The pop rock music features a male voice singing. An electric guitar with a distortion effect on plays plays two chords every two measures. The drums play a strong rhythm and together with a synth bass drive the pulse of the music.", "audio": "/zhanghaomin/datas/musiccap/music_data/-hSMzrWZCAE.wav"} +{"id": "-hYRFCQdbLg", "caption": "The Low quality recording features an upbeat instrumental playing in the background on some kind of speaker, while a loud marimba melody is played over it. It kind of sounds off beat, also the sound is mostly located in the left channel of the stereo image, which makes the recording imbalanced and low in quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/-hYRFCQdbLg.wav"} +{"id": "-i9gpG3vPwA", "caption": "This audio clip is an electronic instrumental of two different tracks with medium fast tempo. The first tempo has an amplified piano playing an emphatic harmony along with digital drums. The second track has emphatic digital drums and electronic /synthesised music arrangement. Both the tracks are melodious, pleasant, harmonic, futuristic, captivating and engaging with a dance groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/-i9gpG3vPwA.wav"} +{"id": "-i9uQMysy_A", "caption": "This audio clip is of a male vocalist beat boxing. The tempo is fast with the vocalist mimicking vigorous drumming, drum machine rhythms, turn table and other percussions.the rhythm is vigorous, energetic and tireless.", "audio": "/zhanghaomin/datas/musiccap/music_data/-i9uQMysy_A.wav"} +{"id": "-jpbCWcz2pk", "caption": "This is a comedic hip-hop music piece. There is a male vocal rapping in the lead. The melody in the beat is being played by the piano and the electric guitar while a bass guitar plays in the background. The rhythm is provided by an electronic drum beat. The piece has an amusing aura to it. It could be used in the background of funny social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/-jpbCWcz2pk.wav"} +{"id": "-kpR93atgd8", "caption": "An acoustic drum is playing along with a bassline giving the song a ska/reggae feeling. The e-guitar strumming on the offbeat supports that feeling while a keyboard is playing a bell-sounding chord. Bongos are setting little accents at the end. A saxophone is playing a melody along. This song may be playing at a festival outside while the sun is shining.", "audio": "/zhanghaomin/datas/musiccap/music_data/-kpR93atgd8.wav"} +{"id": "-lPXTBXa0tE", "caption": "The song is an instrumental. The song is medium tempo played by a solo guitarist on a vintage super tone with an exquisite tone. The song is emotional and passionate. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/-lPXTBXa0tE.wav"} +{"id": "-m5ZlWziIeA", "caption": "This amateur recording features a vinyl scratch being played on a DJ console. This is accompanied by programmed percussion playing a simple beat at a fast tempo. The hi-hat is struck in eighth notes. The snare and kick are played in a unique pattern. A synth plays a two-note lick at different intervals. Other instruments are not audible as the audio quality is low.", "audio": "/zhanghaomin/datas/musiccap/music_data/-m5ZlWziIeA.wav"} +{"id": "-m9pH0WXQto", "caption": "The Electro Pop song features a flat female vocal, occasionally supported by wide background female doubling vocals, singing over quiet drums, groovy and boomy bass, arpeggiated synth melody and some sound effects of the airplane and the explosion. In the second part, the drums cut through the mix more, therefore they are more audible, while the new elements appear, including shimmering bells and simple hi hats. Sounds like a low quality recording, especially because of that first part of the loop.", "audio": "/zhanghaomin/datas/musiccap/music_data/-m9pH0WXQto.wav"} +{"id": "-mA_bqD1tgU", "caption": "The low quality recording features a folk song that consists of a wooden percussion, groovy bass, breathy flute melody, groovy piano melody, shimmering shakers and sustained strings melody. It sounds passionate, joyful and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/-mA_bqD1tgU.wav"} +{"id": "-mB_XLq6g1g", "caption": "This audio contains an acoustic drum playing a groove along with a simple bassline. Trumpets are playing a melody that sounds out of tune and all over the place while a kids voice is streaming and you can hear some aggressive clicking sounds. This song may be playing for a parody video.", "audio": "/zhanghaomin/datas/musiccap/music_data/-mB_XLq6g1g.wav"} +{"id": "-nlkWWphiaM", "caption": "The low quality recording features a live performance that consists of fruity male vocal singing over accordion melody, acoustic rhythm guitar chords and shimmering bells. It sounds emotional and hopeful. The recording is a bit noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/-nlkWWphiaM.wav"} +{"id": "-o0ZtQIkM60", "caption": "This is a video game theme. There is a cinematic string sound playing the melody while the wind sound effect implies there is a snowstorm. A male choir starts singing alongside orchestral percussive elements. There is an epic atmosphere. This piece could fit well in the soundtrack of a thriller video game where there is a face-off about to happen.", "audio": "/zhanghaomin/datas/musiccap/music_data/-o0ZtQIkM60.wav"} +{"id": "-oP-XX28B0s", "caption": "A male singer sings this cool hip hop love song with backup singers in vocal harmony. The tempo is medium with keyboard accompaniment, piano accompaniment, steady drumming rhythm, clapping percussion and other sonic effects. The song is emotional and romantic with a cool dance groove,", "audio": "/zhanghaomin/datas/musiccap/music_data/-oP-XX28B0s.wav"} +{"id": "-pUfYFcsgG4", "caption": "This recording contains environmental sounds such as birds singing. Then bells start playing a melody with a long release time. This is an amateur recording. This song may be playing outside in a park at a fixed time.", "audio": "/zhanghaomin/datas/musiccap/music_data/-pUfYFcsgG4.wav"} +{"id": "-qcTD2o6I9s", "caption": "The kick is playing on every beat along with a fast paced high hat and a snare sound. The digital bass is adding some spice and sounds overdriven. Pad sounds can be heard in the background while a synth lead sound is playing a simple repetitive melody. A male voice is rapping/singing. A lot of backing vocals with delay are adding energy to the mix. This song may be playing in a car.", "audio": "/zhanghaomin/datas/musiccap/music_data/-qcTD2o6I9s.wav"} +{"id": "-r2-9oyIzkQ", "caption": "The Romance song features an electric guitar lick, low toms roll and soft crash cymbal, followed by emotional piano chord progression and wide background crowd screams, as the passionate male vocal sings over it. Judging by the crowd sound effect, it seems that this is a live performance. Sounds emotional, passionate, heartfelt and romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/-r2-9oyIzkQ.wav"} +{"id": "-r7iz-9v9bA", "caption": "This song features a female voice singing in opera style using only vocables and no words. This is accompanied by violins playing eighth note patterns that change according to the chords being played. The bass follows the root notes of the chords. A muted guitar or string instrument plays arpeggiated chords. This song can be played in a fantasy game.", "audio": "/zhanghaomin/datas/musiccap/music_data/-r7iz-9v9bA.wav"} +{"id": "-rAhS48FkYw", "caption": "The low quality recording features a pop song that consists of a passionate male vocal singing over mellow kick hits, shimmering hi hats, wide electric guitar melody, syncopated snare and wooden percussion. The first half of the loop does not consist of the vocal, snare and hi hats. It sounds happy, fun and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/-rAhS48FkYw.wav"} +{"id": "-sRFfU8k0Zs", "caption": "This is an Arabic movie music piece. It is an instrumental piece. There is a clarinet playing a vague melody. The sound of knives being rubbed against one another can be heard. There is an ominous, terrifying atmosphere. This piece could be used in the soundtrack of a horror movie to imply the feeling of hopelessness.", "audio": "/zhanghaomin/datas/musiccap/music_data/-sRFfU8k0Zs.wav"} +{"id": "-sevczF5etI", "caption": "The Folk song features a passionately played sitar guitar, groovy bass and short offbeat accordion chords, followed by metallic percussive elements and punchy kick. The recording is a bit lower in quality due to loud clicky keys sounds. It sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/-sevczF5etI.wav"} +{"id": "-tKZOl4q1Kw", "caption": "The clip just contains a high pitched synth melody. The motif keeps going higher in pitch, and then eventually a riser comes in. The combination of these two factors creates a sense of build-up to a climactic moment.", "audio": "/zhanghaomin/datas/musiccap/music_data/-tKZOl4q1Kw.wav"} +{"id": "-taO6N-rxv4", "caption": "This is a rock music piece playing in the background of a tutorial video. There is an electric guitar playing a simple tune as the lead while another provides a rhythmic backing by playing the same note repeatedly in rapid procession. There is an acoustic drum beat playing. There are water sound effects related to the video. The piece has a generic feeling. It does not evoke much excitement. It could be used as a jingle for an advertisement or in the background of an instructive video.", "audio": "/zhanghaomin/datas/musiccap/music_data/-taO6N-rxv4.wav"} +{"id": "-tmY1GEH3_Y", "caption": "The low quality recording features a pop song that consists of an echoing male vocal singing over punchy kick and snare hits, shimmering hi hats, metallic percussions, synth lead melody, synth pad chords and groovy synth bass. It sounds energetic, nostalgic and exciting - like something you would hear in clubs during the 80s.", "audio": "/zhanghaomin/datas/musiccap/music_data/-tmY1GEH3_Y.wav"} +{"id": "-tpq_bzSKes", "caption": "This composition contains an upright bass playing softly along to a harp and strings playing a melody while a male deep voice is softly singing a melody sounding like telling a story. The song sounds like it was made for Christmas. This song may be playing at home having dinner with the whole family.", "audio": "/zhanghaomin/datas/musiccap/music_data/-tpq_bzSKes.wav"} +{"id": "-uaTK8sa5Ms", "caption": "An acoustic drum set is playing a 16th note rhythm using the edge of his snare and a hihat sound opening and closing. A banjo is playing a fast melody along with a violin/viola playing the same melody. An upright bass is playing a walking bassline. This song may be playing in a funny tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/-uaTK8sa5Ms.wav"} +{"id": "-v5hgCh3M2w", "caption": "The Soft Rock song features a passionate female vocalist singing over a wide electric guitar melody, punchy snare, soft kick hits, groovy bass guitar and shimmering hi-hats. It sounds sad, emotional and passionate - like something you would listen to on a day you are feeling down.", "audio": "/zhanghaomin/datas/musiccap/music_data/-v5hgCh3M2w.wav"} +{"id": "-w12aSkQ9No", "caption": "A female vocalist sings this soprano solo. The tempo is slow with a classic orchestral accompaniment of violin harmony, an intense incessant cello melody, brass instrument and organ. The song is an intense, emotional, beseeching, sad, and imploring classic opera .", "audio": "/zhanghaomin/datas/musiccap/music_data/-w12aSkQ9No.wav"} +{"id": "-w4HLksto_k", "caption": "The low quality recording features a flat male vocal singing over digital piano melody and wooden percussion. The recording is noisy, in mono, loud and distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/-w4HLksto_k.wav"} +{"id": "-w8maIWtnUk", "caption": "This is an instrumental jam recording of a gear showcase. There is an electric guitar with a clear sound being played with an echo pedal. It gives the recording a dreamy feeling. This track can be used to lift guitar samples with effect for a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/-w8maIWtnUk.wav"} +{"id": "-wVWjl9Kq6U", "caption": "This music is a melodic instrumental. The tempo is medium with a captivating electric guitar lead, rhythmic acoustic guitar, funky bass line, keyboard accompaniment, steady drumming and trumpets. The music is soothing, atmospheric, euphonious, youthful, and soulful. This instrumental is a Soft Rock/Funk pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/-wVWjl9Kq6U.wav"} +{"id": "-wymN80CiYU", "caption": "A male singer sings this beautiful melody with backup singers in vocal harmony. The song is medium tempo with a percussive string section, strong bass line, guitar lead, steady drumming rhythm , keyboard accompaniment and various percussion clicks. The song is emotional and romantic. The song is of poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/-wymN80CiYU.wav"} +{"id": "-zA6LL78KYU", "caption": "The low quality recording features a folk song that consists of a passionate female vocal singing over harmonica solo, groovy bass, shimmering hi hats, punchy snare, boomy kicks, groovy electric guitar melody and some claps. It sounds passionate and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/-zA6LL78KYU.wav"} +{"id": "-zOybsEdM5E", "caption": "This is a calm type of song which features a flute being intricately played on top of the various instruments. There is a violin creating a sustained tone underneath. The music feels mystical and enchanting.", "audio": "/zhanghaomin/datas/musiccap/music_data/-zOybsEdM5E.wav"} +{"id": "0-7PyzhzuYQ", "caption": "This is a bluegrass music piece. There is a mandolin playing the main tune as the lead while a banjo and an acoustic guitar are supporting it in the melodic background. There is a joyful feeling to this piece. It could be used in the soundtrack of a movie or a TV show with a rural setting. It could also be used in the background of pastoral social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/0-7PyzhzuYQ.wav"} +{"id": "00M9FhCet6s", "caption": "This children's song features a male voice singing the main melody. There are other voices singing backing vocals. This is accompanied by percussion playing a simple beat. A guitar strums the chords accenting the strums in between lines. The bass plays the root notes of the chords with a reggae feel. The keyboards play chords in the background. This song can be played at a children's party.", "audio": "/zhanghaomin/datas/musiccap/music_data/00M9FhCet6s.wav"} +{"id": "01PzcPKT3_E", "caption": "The Jazz song features a saxophone solo melody played over shimmering shakers, tinny metallic percussions and mellow sustained brass melody. It sounds passionate, emotional and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/01PzcPKT3_E.wav"} +{"id": "01hjVJN9xCg", "caption": "A low fidelity recording of a gospel choir with group vocals, a female singer, a male rapper, piano, a busy kick pattern, finger snaps and a slow tempo. The mood is hopeful and spiritual.", "audio": "/zhanghaomin/datas/musiccap/music_data/01hjVJN9xCg.wav"} +{"id": "0298WjE3_tk", "caption": "A female singer sings and chants with Emily. The tempo is fast with a quick drumming rhythm, percussive bass line, strong drumming rhythm and keyboard accompaniment. The song is exciting and energetic. The song is an anime show soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/0298WjE3_tk.wav"} +{"id": "02Qntw26enM", "caption": "This audio contains a theremin playing a melody in the higher register along to an acoustic piano recording in the background. This song may be practicing theremin playing along with a backing track.", "audio": "/zhanghaomin/datas/musiccap/music_data/02Qntw26enM.wav"} +{"id": "03frQGyrgQ4", "caption": "The song is an instrumental. The song is in slow tempo with a theremin playing a melancholic melody with a guitar accompaniment. The song is emotional and lilting. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/03frQGyrgQ4.wav"} +{"id": "03z0rpIkm5g", "caption": "The low quality recording features a reggae/dub song that consists of a flat male vocal singing over punchy 808 bass, punchy snare, shimmering hi hats and groovy piano chords. It sounds energetic, groovy and the recording is noisy and in mono - due to the fact that the sound is coming from the right channel only.", "audio": "/zhanghaomin/datas/musiccap/music_data/03z0rpIkm5g.wav"} +{"id": "04NjXsLyCl4", "caption": "A loud cymbal sound is opening the space for a digital drum playing a simple groove when an e-guitar-like sound comes in and plays a melody on top. This is an amateur recording. This song may be playing in a sensual movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/04NjXsLyCl4.wav"} +{"id": "05JAmKFVy44", "caption": "The low quality recording features a kids song played through some kind of toy, and it consists of low male vocal singing over some key chords. It sounds distorted and crushed. The recording is noisy and in mono, as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/05JAmKFVy44.wav"} +{"id": "05OJDYeHLMc", "caption": "This audio contains very strong deep percussive hits and a e-guitar sound also serving as bass. A male voice is singing with a little bit of reverb on his voice. In-between the breaks male voices are singing a melody. This song may be playing in an action movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/05OJDYeHLMc.wav"} +{"id": "06Brdf83RZE", "caption": "This is a teen pop music piece. There is a teen female vocalist singing melodically. The main tune is being played by the acoustic guitar. There is a bass guitar playing in the background. The electronic drums provide the rhythmic background. The piece has an easygoing atmosphere. This piece could be an opening theme for a teenage drama movie/TV show. It could also be playing in the background at a clothing store.", "audio": "/zhanghaomin/datas/musiccap/music_data/06Brdf83RZE.wav"} +{"id": "06IU9WsEp3s", "caption": "A male vocalist sings this enthusiastic latin melody. The tempo is medium with keyboard harmony, rhythmic Spanish guitar,percussive congas, bongos and guiro with tambourine beats. There is a loud siren-like sound superimposed over the song. The song is lively, simple,emotional, youthful, rhythmic, catchy with a latin dance grove.", "audio": "/zhanghaomin/datas/musiccap/music_data/06IU9WsEp3s.wav"} +{"id": "07-3grCQ8EU", "caption": "This is a Polish folk music piece meant to be played at weddings. This is an instrumental piece. The melody is played by a Polish fiddle, while there are occasional notes that can be heard from the background of an instrument that sounds like a mandolin. The rhythmic background is probably from the Polish percussive instrument baraban. There is a joyful atmosphere. This piece could be played at Polish weddings or it could be used in the soundtrack of a historical movie or a TV show that takes place in an Eastern European town.", "audio": "/zhanghaomin/datas/musiccap/music_data/07-3grCQ8EU.wav"} +{"id": "07-vpXo91XM", "caption": "Low fidelity recording of a live concert. The crowd noise is very loud and the audience is screaming. The audio is distorting. Amidst the crowd noise, beat boxing can be heard performing a house music style beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/07-vpXo91XM.wav"} +{"id": "07FxCXxknY4", "caption": "This audio contains an acoustic guitar. The piece is played in fingerstyle. Meaning that the chords and the melody are played at the same time. The guitar has some reverb on it. This song may be playing live at an art gallery.", "audio": "/zhanghaomin/datas/musiccap/music_data/07FxCXxknY4.wav"} +{"id": "07mS0mSTDjY", "caption": "This is an amateur recording of an Afro-cuban dance music performance. There are male vocals singing joyfully. There is a percussion orchestra made up of diverse elements such as the conga, the bongo and the timbales are playing in the rhythmic background. The atmosphere is lively and vibrant. Although the audio quality is not that great, this piece can still be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/07mS0mSTDjY.wav"} +{"id": "07xGXxIHOL4", "caption": "A male vocalist sings this soft love song. The tempo is slow with a romantic piano accompaniment, groovy bass line, steady drumming and ambient saxophone harmony. The song is a romantic, emotional, mellow, sentimental, proposal or wedding song. This song is a R&B/Soul song.", "audio": "/zhanghaomin/datas/musiccap/music_data/07xGXxIHOL4.wav"} +{"id": "08mf5GxT820", "caption": "A digital drum is playing a simple rhythm along with a synth bassline. A very pregnant synth lead i s playing a catchy and repeating melody in the higher register. In the background you can hear feet stumping noises. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/08mf5GxT820.wav"} +{"id": "08u-jdwjM74", "caption": "This pop song features a male voice singing the main melody. This is accompanied by programmed percussion playing a simple beat. The snare is struck on alternate counts. The bass plays the root notes of the chords. A synth plays chords on the first count of every bar. A shaker plays a pattern in the background. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/08u-jdwjM74.wav"} +{"id": "09lQmg2wvsY", "caption": "Someone is playing a bunch of different digital sounds that are arpeggiated and rising in pitch with dissonant harmonies. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/09lQmg2wvsY.wav"} +{"id": "0ADP-O_V3vA", "caption": "This song is a lively Ukrainian duet. The tempo is fast and upbeat with a bright keyboard harmony, infectious drumming , groovy bass line and rhythmic acoustic guitar. The music is energetic, enthusiastic, lively, high-spirited , cheerful, happy, warm, buoyant and catchy with a simple melody. This song is a Ukrainian Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/0ADP-O_V3vA.wav"} +{"id": "0AGHo8V8HpM", "caption": "This music is instrumental. The tempo is fast with a spirited cello and harpsichord accompaniment. The music is lively, intense, rich, complex , exquisite and engaging. This music a Western Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/0AGHo8V8HpM.wav"} +{"id": "0AhX-ReXovI", "caption": "Someone is playing a simple groove on tablas. In the background you can hear a backing track playing a flute melody along with synth pads, shaker/chime sounds and a tambourine. This song may be playing practicing tablas at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/0AhX-ReXovI.wav"} +{"id": "0BFauf6TGGU", "caption": "This is an Indian dance music piece. The piece opens with a bansuri note. Then, the harmonium starts playing a repeated melody. The rhythmic background is provided by the manjira. The atmosphere is vibrant and lively. This piece is the perfect accompaniment piece for a modern dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/0BFauf6TGGU.wav"} +{"id": "0DYH0sqDXB8", "caption": "The low quality recording features synth pad chords and synth keys chords played over punchy snare, heartbeat kick and shimmering hi hats. It sounds easygoing, chill and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/0DYH0sqDXB8.wav"} +{"id": "0DizopdPMBw", "caption": "The female voice sings in the mid range. The drums is playing a fast rock/hiphop groove along with an acoustic bass breaking along with it into another part of the song. One of the e-guitars is playing some chords running through a strong tremolo effect. While the other guitar sounds distorted and takes the lead. One is panned to the left, the other to the right side of the speakers. This song may be playing at a birthday party.", "audio": "/zhanghaomin/datas/musiccap/music_data/0DizopdPMBw.wav"} +{"id": "0EOQco76eXQ", "caption": "The song is an instrumental. The song is slow tempo with gentle drum brushes, percussion, bass guitar solo, and piano accompaniment gently. The song is groovy and emotional. The song is possibly a Christian worship song or a smooth jazz song. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/0EOQco76eXQ.wav"} +{"id": "0EvpBtracsk", "caption": "The first song starts with a hihat, e-guitar playing a melody and a bassline. Then the song changes after some radio noise sounds into a pop song containing a piano; male backing voices; synth lead sound and a female singer. These songs may be playing for an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/0EvpBtracsk.wav"} +{"id": "0EzWmAPwoTs", "caption": "The Rock song features an energetic male vocal singing over repetitive electric guitar melody, groovy bass, punchy kick and snare, shimmering hi hats and energetic crash cymbal. There is a short drum roll that represents a variation in a repetitive loop. It sounds energetic and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/0EzWmAPwoTs.wav"} +{"id": "0F-Z0zF1504", "caption": "A male vocalist sings this soft Korean Melody. The tempo is medium with a romantic piano accompaniment, steady drumming, simple bass lines, chimes, synthesiser arrangements and male vocal backup. The song is a soft, mellow, romantic, emotional, sentimental, dulcet, melodic love song. This song is a Korean Soft Pop/K-pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/0F-Z0zF1504.wav"} +{"id": "0Gxn9FtaJFc", "caption": "This is a rock music piece with a male vocal. The synth and the piano are playing the main melody in a minor scale while the bass guitar is supporting them in the background. The rhythm is played by acoustic drums although it is rather slow. The song has a sad atmosphere. It could be played in the background of emotional online content.", "audio": "/zhanghaomin/datas/musiccap/music_data/0Gxn9FtaJFc.wav"} +{"id": "0H3FAoDgzhI", "caption": "A female voice is singing in a higher pitch sounding melancholic. A digital drum is playing an unusual rhythm along with a soft sub bass and loud repeating digital industrial noises. This song may be playing in a post-apocalyptic video game-sequence.", "audio": "/zhanghaomin/datas/musiccap/music_data/0H3FAoDgzhI.wav"} +{"id": "0HXYdGGKV2k", "caption": "The song is an instrumental. The song is medium tempo with a groovy rhythm and fast fingers playing this banjo solo. The song is entertaining and exciting. The song is of poor audio quality and a live performance video.", "audio": "/zhanghaomin/datas/musiccap/music_data/0HXYdGGKV2k.wav"} +{"id": "0ISHZQJdeSw", "caption": "A male vocalist sings this Rap. The tempo is slow with enthusiastic drumming, syncopated piano harmony, digital beats ,keyboard arrangements with vocal backup and a catchy vocal riff. The rap is catchy, youthful, insightful, enthusiastic, intense, passionate, emotional and persuasive. This song is contemporary Rap/Hip-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/0ISHZQJdeSw.wav"} +{"id": "0J_2K1Gvruk", "caption": "This song features two cellos playing a melody in harmony. This is accompanied by hand claps on every alternate count of the bars. The bass plays the root notes of the chords. The kick drum is played at the intro. There are no voices in this song. This is an instrumental song with a happy feel. This song can be played in a luxury advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/0J_2K1Gvruk.wav"} +{"id": "0J_TdiZ3TKA", "caption": "A male vocalist sings this sweet animated song in a foreign language.The tempo is fast with an equally animated and cheerful piano accompaniment. The song is simple, sweet, adorable,catchy, lovable, catchy, upbeat, cute, engaging, winsome and charming. This song is a Children\u2019s song from an animated series.", "audio": "/zhanghaomin/datas/musiccap/music_data/0J_TdiZ3TKA.wav"} +{"id": "0JbGxIR8JTk", "caption": "Afrobeat inspired music with an island flavor. Fingerpicked acoustic-electric nylon string guitar carries the harmony, while a male singer sings freely. syncopated electric bass and drumset meld with various African percussion.", "audio": "/zhanghaomin/datas/musiccap/music_data/0JbGxIR8JTk.wav"} +{"id": "0K-zyeLuKho", "caption": "The low quality recording features a guitar tutorial that consists of a flat male vocal talking and counting the rhythm over an arpeggiated acoustic guitar melody. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/0K-zyeLuKho.wav"} +{"id": "0KCVgexi4yU", "caption": "This song contains a female voice singing along to a digital drum playing a four on the floor beat with a kick on every beat and a hi hat on the backbeat. A digital bass and long digital pad sounds are creating an atmosphere. This song may be playing on a tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/0KCVgexi4yU.wav"} +{"id": "0L2ndtt60Q8", "caption": "This is a parody of an electronic music song with a chipmunk vocal effect. There is an edited version of the original track playing in the background that is transposed to a very high pitch.", "audio": "/zhanghaomin/datas/musiccap/music_data/0L2ndtt60Q8.wav"} +{"id": "0L3vcdzQPPU", "caption": "This is a recording of an acapella piece by multiple vocalists. The women sing in a high pitched, whistle-like tone while the men sing in lower tones and harmonise with the women. The melody is rapid and progressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/0L3vcdzQPPU.wav"} +{"id": "0LE6Ll1rVlg", "caption": "The Rock song features a passionate male vocal, alongside harmonizing male vocals, singing over wide electric guitar melody, groovy bass guitar, punchy kick and snare hits and some shimmering cymbals. It sounds energetic and kind of addictive thanks to those harmonizing vocals - like something you would hear on a radio during the 00s.", "audio": "/zhanghaomin/datas/musiccap/music_data/0LE6Ll1rVlg.wav"} +{"id": "0LLlcPiatiU", "caption": "The song is mostly instrumental with a faint male vocal. The song is medium tempo with a slick drumming rhythm , booming bass line, siren tones and a keyboard playing arpeggiated tones. The song is followed by camera flash and click tones. The song is exciting with a lot of fanfare. The song is fading with the end credits superimposed with camera flash tones.", "audio": "/zhanghaomin/datas/musiccap/music_data/0LLlcPiatiU.wav"} +{"id": "0M7nETLOsKQ", "caption": "The Pop song features a passionate male vocal singing over mellow piano chords. It sounds passionate, emotional, mellow and soft.", "audio": "/zhanghaomin/datas/musiccap/music_data/0M7nETLOsKQ.wav"} +{"id": "0MzrXd8CUCg", "caption": "The low quality recording features a wide resonating woodwind melody. The recording is loud, noisy with some crackles and it sounds harsh.", "audio": "/zhanghaomin/datas/musiccap/music_data/0MzrXd8CUCg.wav"} +{"id": "0NTzOtVmoiU", "caption": "The song is an instrumental. The song is fast in tempo, with a bagpiper playing a Solo melody accompanied by a drum rhythm and people cheering and clapping wildly. The song is rousing in spirit and fervour. The song has a bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/0NTzOtVmoiU.wav"} +{"id": "0NZY0GHQBP0", "caption": "This amateur recording features a classic song. This is an instrumental song featuring a violin solo. This is accompanied by percussion playing a simple beat. A keyboard plays chords in the background with fills in between bars. The bass plays the root note and the lower fifth of the chord. There are no voices in this song. Due to the low quality of sound, the other instruments are unclear. This song can be played in a classic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/0NZY0GHQBP0.wav"} +{"id": "0ONdm4sW47c", "caption": "This is a classical music piece that is being performed on the acoustic guitar. The acoustic guitar is being played in a gentle manner. The tune is in major key which gives the piece an optimistic aura. There is a tender atmosphere to the piece. This piece could be playing in the background at a classy restaurant. It could also be used in the soundtrack of a feelgood movie, especially during the scenes in which the characters are finding pleasure in simple things.", "audio": "/zhanghaomin/datas/musiccap/music_data/0ONdm4sW47c.wav"} +{"id": "0OY8XXZ98rw", "caption": "The Metal song features a distorted flat male vocal singing over wide aggressive electric guitar riffs, distorted bass guitar, punchy snare, double pedal kick and shimmering cymbals. It sounds energetic, aggressive and manic - like something you would go into a mosh pit for.", "audio": "/zhanghaomin/datas/musiccap/music_data/0OY8XXZ98rw.wav"} +{"id": "0OYlHvyfNk4", "caption": "This song sounds lightly uplifting. An e-bass is playing a repeating melody along with a guitar playing an almost melody at a higher key. Another acoustic guitar is strumming chords. The male voice is singing almost rapping/talking while backing voices are singing repeating the melody and phrases. This song may be playing outside on a bike on a sunny day.", "audio": "/zhanghaomin/datas/musiccap/music_data/0OYlHvyfNk4.wav"} +{"id": "0OhtODbKajw", "caption": "This audio contains people playing a melody in the higher register using violins and a viola. Some are playing the melody upwards while others are playing downwards. A cello or upright bass is providing a melody line in the lower register. This song may be playing during a classical concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/0OhtODbKajw.wav"} +{"id": "0Olm321vgk8", "caption": "The Low Quality recording features r&b/soul songs sung by passionate male vocalists over fat bass guitar, punchy kick and snare hits and arpeggiated electric guitar melody. There are also some chattering voices in the background, it sounds like it is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/0Olm321vgk8.wav"} +{"id": "0PMFAO4TIU4", "caption": "A digital drum is playing a simple beat along with some percussive sounds. A bass is playing the same melody as the accordion-like instrument. A male voice is shouting little phrases. This song may be playing a country having a traditional dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/0PMFAO4TIU4.wav"} +{"id": "0Q1JLNfm8oU", "caption": "This song contains two pianos panned to both sides of the speakers playing melodies in the mid to upper range. A female voice, maybe a child sings a melody in a very high pitch. THis song may be playing as part of a movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/0Q1JLNfm8oU.wav"} +{"id": "0QAaln-hjPw", "caption": "This song contains digital drums playing along with a synth bass line creating the foundation of this song. Some drum elements are panned to both sides of the speakers. A synth lead sound is playing a high pitched melody and a male voice sample is used as a loop to create a melody. This song may be playing for a youtube video.", "audio": "/zhanghaomin/datas/musiccap/music_data/0QAaln-hjPw.wav"} +{"id": "0QYNC7J05XI", "caption": "This pop song features a male voice singing the main melody using vocables. This is accompanied by an acoustic guitar strumming chords. The piano fills at a higher register and also plays chords. The bass guitar plays the root notes of the chords without any flourishes. A shaker is used in the background which acts as the percussion. Hand claps are played at every alternate count. Bells are played on the first count of the first two bars of each phrase. The melody is happy and upbeat. This song can be played in a movie scene featuring a family on a road trip.", "audio": "/zhanghaomin/datas/musiccap/music_data/0QYNC7J05XI.wav"} +{"id": "0RDz0rLakwc", "caption": "A male vocalist sings this trippy Electronic song. The tempo is slow with synthesiser arrangement, digital drums and electronically articulated music. The song is catchy, youthful, enthusiastic, trippy, psychedelic , new age, and groovy. This song is an Electro -Hop/ Hip-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/0RDz0rLakwc.wav"} +{"id": "0RcMzUdXDRQ", "caption": "This is a song for children. The song is in major key as is usual with almost all kids songs. There is a female vocalist in the lead. The melody is being played by an acoustic guitar while a bass guitar plays a simple bass line. The electric guitar is playing delayed notes for texture. The acoustic drums are playing a basic medium tempo beat in the rhythmic background. The atmosphere is easygoing. This piece could be used during activities in a kindergarten.", "audio": "/zhanghaomin/datas/musiccap/music_data/0RcMzUdXDRQ.wav"} +{"id": "0RgGrVklaao", "caption": "This clip is an instrumental of two separate tracks. The tempo is medium with the first clip of ambient nature sounds during a rainfall like, thunder, lightning and water flowing followed by a rhythmic clanging of metal. The second clip is sinister music on the synthesiser followed by the buzzing of an electric circuit. The audio is dark, sinister, anticipatory, scary, suspenseful and spooky.", "audio": "/zhanghaomin/datas/musiccap/music_data/0RgGrVklaao.wav"} +{"id": "0RpkkfkUBRU", "caption": "This audio contains a cinematic composition with evolving synth drone sounds. Higher pitched pads, noise sounds panning to both sides of the speakers and arpeggiated short percussive pluck sounds. Some synth strings are playing a dissonant harmony creating more tension. A marimba hit is being played with a lot of reverb. This song may be playing for a movie-scene full of tension.", "audio": "/zhanghaomin/datas/musiccap/music_data/0RpkkfkUBRU.wav"} +{"id": "0S5zWt91Bwo", "caption": "This song contains acoustic guitars being strummed fast, a mandolin playing the lead melody in a higher pitch and an upright bass providing an almost walking bassline. This song may be playing in the countryside while having a BBQ.", "audio": "/zhanghaomin/datas/musiccap/music_data/0S5zWt91Bwo.wav"} +{"id": "0SNhAKyXtC8", "caption": "Someone is playing a harp making use of the full register. A bassline, a melody is the mid range and high repetitive note. The whole composition sounds oriental due to a lot of half notes. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/0SNhAKyXtC8.wav"} +{"id": "0SnjS2w_c80", "caption": "This is an alternative music piece used as an outro jingle for a food channel. The vocals are being sung with a vocoder. There is a keyboard playing in the melodic background. A simple acoustic drum beat can be heard playing the rhythm. The atmosphere is trippy.", "audio": "/zhanghaomin/datas/musiccap/music_data/0SnjS2w_c80.wav"} +{"id": "0TV9zvfwFhs", "caption": "The R&B music features a male voice singing and being backed by similar male voices from time to time. An electric piano accompanies the singer with long-note chords. The drums play a light rhythm and dictate the flow of the music. Towards the end of the music excerpt a bass guitar starts to play. In the beginning of the passage one can hear a tubular bell being struck once. This sound is very similar to a church bell.", "audio": "/zhanghaomin/datas/musiccap/music_data/0TV9zvfwFhs.wav"} +{"id": "0TiEO149Ydc", "caption": "The low quality recording features a live performance of an Alternative/Indie song and it consists of passionate female vocal singing over acoustic guitar strummed chord and wooden percussive element. The recording is noisy and the vocal is slightly moving throughout the stereo image making it unbalanced. It sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/0TiEO149Ydc.wav"} +{"id": "0Ubu4BqSWmU", "caption": "A male vocalist sings this mellow rap. The tempo is medium with a groovy bass line, keyboard harmony , slick drumming and vocal backup. The song is youthful, story telling, passionate, impactful, compelling and engaging. This song is contemporary Hip-Hop/Rap.", "audio": "/zhanghaomin/datas/musiccap/music_data/0Ubu4BqSWmU.wav"} +{"id": "0VjPCd62oKg", "caption": "This music is a clip of the end of the song. There is no music nor vocals. The audio clip begins with the sound of splashing water followed by ducks quacking before it fades and stops. This song sounds like a Children\u2019s Nursery rhyme about ducks or animals , animal sounds or swimming. It intends to make learning fun and simple.", "audio": "/zhanghaomin/datas/musiccap/music_data/0VjPCd62oKg.wav"} +{"id": "0VsjSa1X7iA", "caption": "The low quality recording features a live performance of a gospel song and it consists of passionate male vocal singing over harmonizing mixed choir in the background. The recording is a bit noisy and it has some footsteps sounds in it, but overall it sounds passionate, emotional and soulful - as every gospel song should sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/0VsjSa1X7iA.wav"} +{"id": "0VwX92X3iPc", "caption": "This audio contains a female voice speaking in a relaxed and sensual sounding way while you can hear the sound of scratching on a surface.", "audio": "/zhanghaomin/datas/musiccap/music_data/0VwX92X3iPc.wav"} +{"id": "0Wdh45yt7tY", "caption": "The song is an instrumental. The song is medium tempo with an accordion accompaniment, violin solo and a flute melody. The song is beautiful and nostalgic. The audio quality is poor. The song has an old gypsy soul to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/0Wdh45yt7tY.wav"} +{"id": "0XxinBtKouQ", "caption": "A group of male vocalists sing this happy, upbeat country /bluegrass song. The tempo is fast with vigorous and animated acoustic guitar, banjo, mandolin and auto harp lead and harmony. The song is a live performance with ambient sounds of clapping, cheering and people talking. This song is a cheerful Country Pop/Bluegrass song.", "audio": "/zhanghaomin/datas/musiccap/music_data/0XxinBtKouQ.wav"} +{"id": "0ZNFJz-eZTU", "caption": "The low quality recording features a jazz song cover that consists of a passionate saxophone melody played over soft hi hats and kick hits, snappy rimshots, smooth bass, organ keys chords and mellow piano chords. It sounds emotional, passionate and reverberant - as it was probably recorded in a medium size room.", "audio": "/zhanghaomin/datas/musiccap/music_data/0ZNFJz-eZTU.wav"} +{"id": "0ZXWSO_Y2C0", "caption": "This is a melodic death metal music piece. There is a male vocal singing using the pig squeal technique in the lead. The electric guitar with heavy distortion is playing a hard-hitting riff. There is a bass guitar playing in the background. The acoustic drums are playing a loud but simple beat. The atmosphere of the piece is violent. It could be used in the soundtrack of a horror movie or a horror video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/0ZXWSO_Y2C0.wav"} +{"id": "0_QcatLmg7c", "caption": "The low quality recording features a pop song performed by passionate male vocalists, followed by acoustic guitar arpeggiated melody and mellow piano melody. It sounds heartfelt and emotional. There are some crowd noises in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/0_QcatLmg7c.wav"} +{"id": "0_XItMAYkwc", "caption": "This song contains a simple acoustic drum groove with a cowbell sound. Two e-guitars and an e-bass are all playing the same melody spread across the speakers. Another e-guitar is strumming dissonant chords in the background panned to the left side of the speakers. Male voices are singing in a higher key. This song may be playing while cooking with joy.", "audio": "/zhanghaomin/datas/musiccap/music_data/0_XItMAYkwc.wav"} +{"id": "0_hH79HnEdo", "caption": "This heavy metal song features a female voice rapping the main vocals. The voice is aggressive and high pitched. This is accompanied by distortion guitars playing aggressive riffs. The distortion guitars play using muted power chords lending a heavy tone to the rhythm section. The bass follows the same riffs as the guitars. The percussion plays an aggressive rock beat using double kicks in parts, following the guitar riffs. This song has a rebellious mood. This song can be played in a Transformers-style machine movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/0_hH79HnEdo.wav"} +{"id": "0a6uLBmqZgA", "caption": "This amateur recording clip features the bagpipes playing a melody. This tune is played at a fast tempo and at a high pitch. There are no other instruments in this song. There are no voices in this song. This song is an instrumental. This song can be played in a village fair. The sound of the crowd cheering is heard throughout the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/0a6uLBmqZgA.wav"} +{"id": "0a91szM1Ivw", "caption": "The low quality recording features a live performance of traditional folk song and it consists of distorted, passionate female vocal singing over subtle sitar melody. The recording is noisy and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/0a91szM1Ivw.wav"} +{"id": "0abzD7hBTRk", "caption": "This music clip is of a male vocalist doing a beat box. The tempo is medium fast with the vocalist imitating the digital drums, turntable and Dj mixer to a perfection. This vocal percussion is lively, rhythmic, youthful and engaging.", "audio": "/zhanghaomin/datas/musiccap/music_data/0abzD7hBTRk.wav"} +{"id": "0bP2MH3LqvI", "caption": "This song features a piano melody being played. It is played on an ascending scale. The sound of a plane propeller is played on top of this music. At the end; a male voice is heard in a narrating tone. There are no other instruments in this song and no vocal melody is sung in this clip. This music can be played in a classic silent movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/0bP2MH3LqvI.wav"} +{"id": "0bRUkLsttto", "caption": "This is a hip-hop piece. There is a male vocal rapping at the forefront while other male vocals can be heard singing ad-libs. A repeated theme is being played by a keyboard. A synth bass with low-to-mid characteristics can be heard playing in the background. The rhythmic background consists of a hard-hitting electronic drum beat. The atmosphere is groovy. This piece could be played at nightclubs. It would also suit well with a sports venue setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/0bRUkLsttto.wav"} +{"id": "0bvPjMQ_WbE", "caption": "The low quality recording features a live performance of loud steel pans melody over playback instrumental that consists of shimmering hi hats, open hats and \"4 on the floor\" kick pattern. There are some crowd talking noises in the background. It sounds exotic and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/0bvPjMQ_WbE.wav"} +{"id": "0c1YU_VtFRE", "caption": "This recording is full of environmental sounds like wind and other sounds. Then at the end a beep tone comes and an acoustic piano is playing an arpeggio melody with reverb on it. This is an amateur recording. This song may be used as an outro or intro in an amateur video.", "audio": "/zhanghaomin/datas/musiccap/music_data/0c1YU_VtFRE.wav"} +{"id": "0cNYPgD6cEA", "caption": "The male mid to high range voice sings loudly and full of emotions pouring out of his soul while strumming some minor chords on the guitar. This recording is of poor quality. This song may be played in an open mic, poetry bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/0cNYPgD6cEA.wav"} +{"id": "0dPx94RPy2M", "caption": "This is a jingle piece played in the background of an advertisement video. There are sounds coming from a drill. The piece in the background is an instrumental rock music piece. There is a keyboard and an electric guitar playing the melody while an acoustic sounding drum beat provides the rhythm. The sounds are bland and generic. The piece could be of some use as an advertisement jingle or it could be playing in the background of an instructive/tutorial video.", "audio": "/zhanghaomin/datas/musiccap/music_data/0dPx94RPy2M.wav"} +{"id": "0ewQiU3q5jM", "caption": "This file contains audio playing a high pitched melody on a music box. The melody sounds a little freighting and is full of reverb. From the recording you can hear a little bit of white noise. This song may be playing in a horror movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/0ewQiU3q5jM.wav"} +{"id": "0ewWspUqB6Y", "caption": "This is a Romanian folk music piece. It is a live performance. In the background, there is a contrabass and a cimbalom playing. The main melody is being played by the violin and the accordion. The atmosphere is vibrant and cheerful. This piece could be used in the soundtrack of a comedy movie that takes place in eastern Europe or the Balkans, especially during an escape scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/0ewWspUqB6Y.wav"} +{"id": "0fCpAuxrQ_I", "caption": "This song is a Rock instrumental. The tempo is medium fast with an aggressive electric guitar harmony, steady drumming, keyboard accompaniment, groovy bass lines. The audio quality is inferior so the finer aspects; are hard to detect. Overall the vibe of the song is intense,dangerous, sinister, spooky, goth, threatening and suspenseful. This song is Hard Rock/Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/0fCpAuxrQ_I.wav"} +{"id": "0fiOM---7QI", "caption": "This is a traditional, cultural South Asian song. It is upbeat, vibrant, cheerful. The lead singer sings in a fast paced and rhythmic way, connecting many words within a short span of musical time. The rest of the performers are clapping their hands, playing the tabla. This is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/0fiOM---7QI.wav"} +{"id": "0fqtA_ZBn_8", "caption": "The low quality recording features a live performance of a traditional song that consists of fruity male vocals, alongside harmonizing boy background vocals, singing over subtle strings melody and wooden percussion. It sounds passionate, soulful and emotional, even though the recording is really noisy, as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/0fqtA_ZBn_8.wav"} +{"id": "0hfU27A6tus", "caption": "This is the performance of an Irish folk song using a banjo and a mandolin. The singer is elderly and the guitars are layered. The banjo is used to play a simple motif that revolves around two chords.", "audio": "/zhanghaomin/datas/musiccap/music_data/0hfU27A6tus.wav"} +{"id": "0hw_BB4QN34", "caption": "This audio contains someone playing a snare like instrument with a flat sounding kick. The snare hits are complex and fast. There is some reverb involved in the recording. This is an amateur recording. This may be playing in a traditional entry for a song.", "audio": "/zhanghaomin/datas/musiccap/music_data/0hw_BB4QN34.wav"} +{"id": "0i8VM_EooCs", "caption": "This is a finnish techno pop piece with polka influences. There is a female vocalist in the lead singing rapidly in a manner that resembles yodeling. A male vocalist occasionally joins her at a lower pitch while singing the melody. The melodic background consists of a keyboard tune and a simple bass line. The rhythmic background is provided by an electronic disco drum beat. The atmosphere is playful and danceable. This piece could be used in the background of a comedic social media content. It could also be played at children's events.", "audio": "/zhanghaomin/datas/musiccap/music_data/0i8VM_EooCs.wav"} +{"id": "0jFQ21A6GRA", "caption": "This is a Christian gospel music piece. There is a male vocalist singing melodically at the forefront. The simple tune is being played by a mellow acoustic guitar. The piece has a deep and passionate atmosphere. It could be used in Christian religious events and gatherings. It could also be used in the background of Christian social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/0jFQ21A6GRA.wav"} +{"id": "0kQD1P0_KUs", "caption": "The song is an instrumental with male vocalists cheering enthusiastically . The tempo is medium fast with a trombone and trumpet playing percussively and an Indian dhol playing percussively. The song is cheerful and energetic. The song is a traditional Indian folk style called Punjabi Bhangra music. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/0kQD1P0_KUs.wav"} +{"id": "0kQjfwXjFuY", "caption": "This is an instructive recording of a male vocalist singing in an erotic manner. A backwards reverb effect is applied to the vocal which gives the track a feeling of anticipation. This track could be used to exemplify the use of the backwards reverb effect in sound design courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/0kQjfwXjFuY.wav"} +{"id": "0khKvVDyYV4", "caption": "The low quality recording features an in-game audio recording that features an echoing female exhale sound, shimmering hi hats, claps, shimmering bells melody and groovy bass guitar. In the second half of the loop, the song changes and there is a sweet female vocal humming a melody. It sounds exciting, happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/0khKvVDyYV4.wav"} +{"id": "0lIETNZ_7sg", "caption": "The low quality recording features a Christmas song that consists of a widely spread, groovy piano melody, followed by synth choir keys. It sounds happy, joyful, fun and euphoric - as any Christmas song should sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/0lIETNZ_7sg.wav"} +{"id": "0m9-5BkL4Mc", "caption": "The music features a timid boy voice singing a melody. Right in the opening of the music excerpt, before the boy starts to sing, an accordion can be heard playing a short melody. A band that consists of drums, bass guitar and electric guitar is accompanying the boy. Listening to the electric guitar, I get country music vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/0m9-5BkL4Mc.wav"} +{"id": "0nNmbkU8GBI", "caption": "This is an ambient music piece. There is a granular synth playing at a medium-to-high pitch. The piece has a hypnotic atmosphere. It could be used in the background of meditation videos.", "audio": "/zhanghaomin/datas/musiccap/music_data/0nNmbkU8GBI.wav"} +{"id": "0nk7utNkHOY", "caption": "This music is a western classical instrumental. The tempo is slow with a cello solo. The music is soft, rich, deep, mellow, euphonious, pensive, melancholic, emotional and sentimental.", "audio": "/zhanghaomin/datas/musiccap/music_data/0nk7utNkHOY.wav"} +{"id": "0oIFGARD9xE", "caption": "A female vocalist sings this Gospel song. The tempo is medium with groovy bass lines, keyboard accompaniment, electric guitar and acoustic guitar rhythm,tambourine beats and choral harmony. The song is a spirited,emotional,fervent, earnest and devotional Christian Worship Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/0oIFGARD9xE.wav"} +{"id": "0pewITE1550", "caption": "The song is an instrumental. The song is medium tempo with various marching band drums playing in sync. The song is highly energetic and spirited. The song is bad in audio quality. The song is a college marching band playing enthusiastically.", "audio": "/zhanghaomin/datas/musiccap/music_data/0pewITE1550.wav"} +{"id": "0q-80dzp6PU", "caption": "The low quality recording features an electro pop song that consists of an echoing passionate male vocal singing over groovy synth keys chord progression, punchy snare hits, followed by snare roll, wide laser synths and reversed crash riser. It sounds exciting and energetic - like a build up section of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/0q-80dzp6PU.wav"} +{"id": "0qtbbK5HVMw", "caption": "The song is instrumental. The tempo is fast with violins playing in harmony showing exemplary technique. The song is emotional, spirited and passionate. The song is a western classical music hit. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/0qtbbK5HVMw.wav"} +{"id": "0rNr_qnoPQ4", "caption": "The low quality recording features a passionate male vocal, alongside passionate female vocal, singing over shimmering tambourine, shimmering hi hats and mellow piano chords. It sounds soft, emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/0rNr_qnoPQ4.wav"} +{"id": "0s0Uy0-zBa0", "caption": "This music is instrumental. There is no harmony, just an incessant dissonant beep, loud explosive sound and static in the background. The sounds are of those in a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/0s0Uy0-zBa0.wav"} +{"id": "0sPVAP17w2U", "caption": "This instrumental song features a Chinese fiddle. The song has an oriental feel. The fiddle is accompanied by a bass playing the root notes of the chords. Another medium pitched instrument plays chords in the background. Bells and chimes are played to add more melody to this song. There is no percussion in this song. There are no voices in this song. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/0sPVAP17w2U.wav"} +{"id": "0soVCtJgDTk", "caption": "The low quality recording features an advertisement that consists of camera shuttering effects and high pitched down sweeps, followed by arpeggiated strings melody, orchestra percussions and synth sound effects playing in the background. It sounds exciting and epic.", "audio": "/zhanghaomin/datas/musiccap/music_data/0soVCtJgDTk.wav"} +{"id": "0trWdhSvab4", "caption": "Male singers sing this vocal harmony. The song is medium fast tempo with a groovy bass line, steady drumming rhythm, piano accompaniment and guitar rhythm. The song is devotional and congregational. The song is a classic Christian praise hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/0trWdhSvab4.wav"} +{"id": "0u1sk49gAU0", "caption": "The low quality recording features a flat male vocal talking and playing a groovy accordion melody, before which a male and a female laugh. It sounds passionate and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/0u1sk49gAU0.wav"} +{"id": "0u4gY1bBUwQ", "caption": "This music is a lively instrumental. The tempo is fast with a drum beat introduction, saxophone solo, piano solo, followed with lively harmony of the tenor sax and march like drumming. This piece is the song introduction. It is a lively, cheerful, happy, celebratory and youthful Western Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/0u4gY1bBUwQ.wav"} +{"id": "0u5-WiBKam8", "caption": "The low quality recording features a reverberant breathy flute melody with an inhale sound in-between. It sounds mystical, passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/0u5-WiBKam8.wav"} +{"id": "0vFPs6XsU_Q", "caption": "A male and female child singers sing this vocal duet in harmony. The song is medium tempo with keyboard accompaniment , groovy bass line and an enthusiastic drumming rhythm. The song is passionate and loving. The song is a retro tv show tune and in poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/0vFPs6XsU_Q.wav"} +{"id": "0wYi8B9PXDY", "caption": "This is a video game theme being hummed by a male vocal. It is in the low-to-medium range. It conveys a feeling of idleness. Vocal samples can be lifted from this track to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/0wYi8B9PXDY.wav"} +{"id": "0wzsE67O5tE", "caption": "The song is an instrumental. The tempo is medium with an acoustic guitar playing lead, electric guitar accompaniment and a groovy bass line and no percussion instruments. The song is spirited and energetic. The audio quality is quite poor and the song has rock music influences.", "audio": "/zhanghaomin/datas/musiccap/music_data/0wzsE67O5tE.wav"} +{"id": "0x6chChxzV0", "caption": "This rock song features a male voice singing the main melody. The melody has a repetitive pattern. Another voice sings 'ooh' in the background. This is accompanied by percussion playing a simple rock beat in common time. The bass plays a note and slides to the higher octave and comes back to the original note. The guitar strums the chords of this song. This song has a hippie feel. This song can be played in a movie based on a drug cartel.", "audio": "/zhanghaomin/datas/musiccap/music_data/0x6chChxzV0.wav"} +{"id": "0zolXzR9Oi4", "caption": "This is a classical music piece from the baroque era. The piece is being performed by a harpsichord. There is a mysterious atmosphere and a medieval feel to this piece. The music could fit very well in the soundtrack of a gothic horror movie, especially where we are witnessing a scene of exposition.", "audio": "/zhanghaomin/datas/musiccap/music_data/0zolXzR9Oi4.wav"} +{"id": "1-Y9kafYuqQ", "caption": "The low quality recording features a DJ scratching his vinyl track that consists of a boomy 808 bass, low male vocal, laser synth lead melody, soft white noise, low synth down sweep and wide short snare roll. There is some widely spread snare roll at the end of the first section of the loop. It sounds energetic and a bit chaotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/1-Y9kafYuqQ.wav"} +{"id": "10dur7jhFQM", "caption": "This techno song features programmed percussion. The kick is played on every count of the beat. A cymbal or shaker is played in sixteenth note patterns. This is accompanied by a synth playing a repetitive sequence. Another synth sound is played in bursts which has a warped sound effect. This song is an instrumental and has no voices. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/10dur7jhFQM.wav"} +{"id": "11D0JdB7_4k", "caption": "This song features a didgeridoo being played using the vibration produced by blowing the lips on the instrument. This produces a droning sound. The droning sound alternates with the bass sound of the didgeridoo in a pattern. There are no other instruments in this song. There are no voices in this song. This is an instrumental song. This song can be played in a movie scene when a man lost in a forest approaches a tribal settlement.", "audio": "/zhanghaomin/datas/musiccap/music_data/11D0JdB7_4k.wav"} +{"id": "11FeId69WOk", "caption": "A male vocalist sings this retro classic melody. The tempo is slow with a melodious electric guitar lead, soft acoustic guitar accompaniment and subtle bass complimenting the soft vocals and backup. The song is mellow, melancholic, pensive, insightful, euphonious, dulcet and soothing. There is a sound of static in the background. This song is classic Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/11FeId69WOk.wav"} +{"id": "11fNNN95_og", "caption": "This is an analog sounding video game theme. The melodic structure consists of a keyboard, a synth brass and a synth strings sound. The atmosphere is action-filled and ominous. There is an arcade feel to it. This piece could be used in the soundtrack of an action video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/11fNNN95_og.wav"} +{"id": "13n6n6nKMhI", "caption": "The low quality recording features echoing sleep drone sound effects. It sounds weird and cool at the same time. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/13n6n6nKMhI.wav"} +{"id": "14hTDUjCr_g", "caption": "The music features a male voice singing a melody while being backed at times by other male vocals. A piano accompanies the singer by playing a combination of chords and melody. For the most part a marimba plays in unison with the singer. In the low register, a synth bass plays long notes. The drummer makes use of only the hi-hat and China cymbal.", "audio": "/zhanghaomin/datas/musiccap/music_data/14hTDUjCr_g.wav"} +{"id": "15CZ2h5VL-A", "caption": "This amateur recording features a shaker being played continuously. A cajon is played. After about two bars, the sound of the cajon changes to a more open sound. This video is an instrumental. There are no voices in this song. This song can be played as an instruction for cajon players.", "audio": "/zhanghaomin/datas/musiccap/music_data/15CZ2h5VL-A.wav"} +{"id": "15Mw2jyyHk0", "caption": "This song is an instrumental. The tempo is fast and vigorous, with the musician playing a very rapid harmony on the Spanish guitar with an acoustic guitar accompaniment; the song is energetic, vibrant, enthusiastic, and shows a lot of dexterity with the instrument. This song is an instrumental Pop rock song.", "audio": "/zhanghaomin/datas/musiccap/music_data/15Mw2jyyHk0.wav"} +{"id": "15z-gbPxdXg", "caption": "The low quality recording features a finger style acoustic guitar melody. The recording is in mono, noisy and it sounds soulful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/15z-gbPxdXg.wav"} +{"id": "16F5fdORzSo", "caption": "This song contains an acoustic piano playing a minor chord composition with some soft strings in the background playing in a higher key. An e-bass is playing the footnote of the piano. A female voice is singing loud and clear with a voice that sounds melancholic/sad. This song may be playing with headphones while feeling sad.", "audio": "/zhanghaomin/datas/musiccap/music_data/16F5fdORzSo.wav"} +{"id": "16TsDMjHzYU", "caption": "The low quality recording features a, what it seems like, karaoke cover of a muffled pop song that consists of some guitar melodies and rock-ish drums, over which an emotional female vocal is singing. There are some laughing and chattering crowd sound effects in the background too. It sounds fun and emotional, but also noisy and kind of chaotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/16TsDMjHzYU.wav"} +{"id": "17AtKbQ7glU", "caption": "The song is an instrumental soundtrack. The tempo is medium with a string section harmony, horn section, flutes playing , violins playing and lower harmony played judiciously. The song is haunting and full of suspense. The song is a vintage suspense movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/17AtKbQ7glU.wav"} +{"id": "18mS4cLPOb8", "caption": "This piece is a parody of an ad theme. There are female vocals singing at a high-pitch in the major scale, resulting in an epic atmosphere resembling an anthem. The resolution is interrupted by an implied bear attack, breaking the seriousness of the piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/18mS4cLPOb8.wav"} +{"id": "19-GI2LzOtc", "caption": "The low quality recording features a wide choir singing over widely spread strings and brass melody, followed by a sizzling triangle. It sounds epic, powerful and passionate. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/19-GI2LzOtc.wav"} +{"id": "19Pp9QEw17U", "caption": "This is the recording of a slide guitar lesson. There is a male instructor playing blues on the steel guitar while speaking and breathing over his performance at the same time.", "audio": "/zhanghaomin/datas/musiccap/music_data/19Pp9QEw17U.wav"} +{"id": "1ACn3u5UnBw", "caption": "An organ is playing chords and melodies while a male voice is singing soulfully with a lot of reverb and delay in his voice. This is an amateur recording. This song may be playing proposing to someone.", "audio": "/zhanghaomin/datas/musiccap/music_data/1ACn3u5UnBw.wav"} +{"id": "1AOe82obwcY", "caption": "This is a sound that is calm and soothing and would be suitable for any kind of relaxation, meditation or spa. We hear a flute melody with long notes being played over a low frequency buzzing tone.", "audio": "/zhanghaomin/datas/musiccap/music_data/1AOe82obwcY.wav"} +{"id": "1ArUx6UCxe4", "caption": "The song is an instrumental with a devilish voice laughing. The tempo is fast with a fast paced drumming rhythm with strong cymbal crashes. The song is probably an adult animated show designed to scare.", "audio": "/zhanghaomin/datas/musiccap/music_data/1ArUx6UCxe4.wav"} +{"id": "1BVSYfNCcv0", "caption": "This is a Malaysian alternative rock music piece. There is a male vocalist singing melodically at the forefront. The main melody is played by the acoustic guitar with the backing of a mellow electric guitar and a simple bass line on the bass guitar. The rhythmic background consists of a basic rock acoustic drum beat. There is a sentimental and easygoing atmosphere to this piece. It could be used in the soundtrack of a drama/romance movie or TV series that takes place in Malaysia.", "audio": "/zhanghaomin/datas/musiccap/music_data/1BVSYfNCcv0.wav"} +{"id": "1Ccis4FDGwY", "caption": "The low quality recording features an electric guitar melody playing in the left channel only in the first half of the loop. At the very end of the loop, the second electric guitar melody appears in the right channel of the stereo image, which makes the stereo image more balanced. It sounds mellow, soft and passionate. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/1Ccis4FDGwY.wav"} +{"id": "1DNoynuGLV4", "caption": "This song starts with a glitter sound and the drums hitting a soft crash. Followed by piano chords and a higher pitched melody accompanied by a stringlike synthesizer sound repeating a simple melody. The drums sound repetitive and programmed accompanied by some bongos and a bass giving the song a funky groove. There is a beeping sound that sounds like it's not part of the song. This song may be playing while stuck on the telephone-line.", "audio": "/zhanghaomin/datas/musiccap/music_data/1DNoynuGLV4.wav"} +{"id": "1FU5odlgLmo", "caption": "This music is a pensive instrumental.The tempo is medium with a melancholic cello, rhythmic ukulele and a percussion instrument. The song is pensive, contemplative, meditative, melancholic ,solemn and dreamy.", "audio": "/zhanghaomin/datas/musiccap/music_data/1FU5odlgLmo.wav"} +{"id": "1FnA3w94zXI", "caption": "This low quality amateur recording features a guitar solo being played on a distortion guitar. The solo is played up the neck on the higher register. The guitarist plays with very fast picking techniques. This song starts off with string bending which is followed by fast picking on descending licks.", "audio": "/zhanghaomin/datas/musiccap/music_data/1FnA3w94zXI.wav"} +{"id": "1FnT0RrfMEA", "caption": "This music is a mellow, dulcet instrumental. The tempo is slow with a beautiful violin harmony, piano accompaniment and steady bassline with synthesiser arrangements. The music is serene, calming,soothing, sentimental,emotional, wistful,poignant,melancholic and euphonious. This song is an exquisite middle eastern instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/1FnT0RrfMEA.wav"} +{"id": "1GCOnj53QYM", "caption": "This music is two separate tracks. The first track is electronic music with turn table scratching. The second track is a soft, romantic, mellow, harmonious melody with keyboard harmony, electric guitar, groovy bass and steady drumming with a man talking at the end. The two tracks are unrelated.", "audio": "/zhanghaomin/datas/musiccap/music_data/1GCOnj53QYM.wav"} +{"id": "1IK4OeOqAEo", "caption": "A female vocalist sings this melancholic melody in a foreign language.The tempo is slow with a romantic piano accompaniment. The song is soft, mellow, poignant, emotional,sentimental, romantic, melancholic , sad, lonely,and wistful. This song is a Pop/ Love song.", "audio": "/zhanghaomin/datas/musiccap/music_data/1IK4OeOqAEo.wav"} +{"id": "1ILLsA6gqHE", "caption": "Someone is playing various singing bowls. From low sounding ones to high sounding ones creating a melody. This song may be playing in a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/1ILLsA6gqHE.wav"} +{"id": "1IMi7yfZVVM", "caption": "The low quality recording features a groovy buzzy synth bass with a filter effect on it, followed by punchy \"4 on the floor\" kick pattern, shimmering hi hats, wide mellow high pitched sound effect and echoing male vocal singing over it. It sounds energetic and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/1IMi7yfZVVM.wav"} +{"id": "1Is1xfDjZrw", "caption": "A deeper male voice is talking for a moment before changing to another male voice talking about something. In the background you can hear a professional recording containing an e-bass playing single long notes along with an organ and an acoustic piano playing chords in the midrange. An acoustic drum is holding a simple beat in the background. This song may be playing in a gospel church band.", "audio": "/zhanghaomin/datas/musiccap/music_data/1Is1xfDjZrw.wav"} +{"id": "1JpeDWbgUO8", "caption": "A male vocalist sings this energetic pop song. The tempo is fast with an animated keyboard harmony, vigorous drumming, punchy bass lines, vibrant tambourine beats and an enthusiastic vocal backup riff. The song is a remix of an old song. It is vibrant, peppy, punchy, vibrant, vociferous. This song is Pop Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/1JpeDWbgUO8.wav"} +{"id": "1JqNiV03kog", "caption": "This is a Carnatic classical music piece. There is a female vocalist singing melodically while shifting her voice in a veena-like manner. The sitar is playing the melody and the tabla is playing the rhythm. There is a sentimental and dreamy atmosphere to this piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/1JqNiV03kog.wav"} +{"id": "1JwoLPCIGhs", "caption": "The low quality recording features a cover of a blues song and it consists of subtly strummed, acoustic rhythm guitar, followed by electric guitar solo melody. It sounds passionate, easygoing and cool - like something you would hear in high end bars or blues clubs. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/1JwoLPCIGhs.wav"} +{"id": "1KN3GrwhY8c", "caption": "This disco song features a male voice singing the main melody. This is accompanied by programmed percussion playing a disco beat. The kick is played at every count of the bar. The synth changes chords after two bars to a higher pitch chord, then after one bar to a higher pitch chord, then after one more bar to a higher pitch chord and finally after one more bar to a suspended fourth chord. The instruments pause for 3 counts of the bar while the voice continues to sing. The bass plays the root notes of the chords. The mood of this song is romantic. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/1KN3GrwhY8c.wav"} +{"id": "1KmsVHx7E2c", "caption": "This is a movie music piece. The music starts playing with a film reel effect. A strings section with cinematic characteristics are playing a dramatic tune while percussive elements resembling a timpani and a big cymbal are playing accentuated hits to put emphasis on this feeling. The atmosphere is epic. There is the aura of a story about to be told in this piece. It could be used in the soundtrack of a documentary, an action or a thriller movie. It could also be used in the soundtrack of a thriller video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/1KmsVHx7E2c.wav"} +{"id": "1LA64TXatWk", "caption": "This audio contains someone scratching to a backing drumtrack. This song may be playing at home demonstrating an app to someone.", "audio": "/zhanghaomin/datas/musiccap/music_data/1LA64TXatWk.wav"} +{"id": "1MwaXCfUvX8", "caption": "An acoustic drum and a bass are repeating the same pattern along with two e-guitars playing along with the melody while a male voice sings slightly soulful and loud. In the background a crowd is sheering. The recording is of very poor audio quality. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/1MwaXCfUvX8.wav"} +{"id": "1O4LpU7HggY", "caption": "This clip features a male voice narrating about guitars. In the background, an acoustic guitar is strumming chords and picking notes used as fills. The mood of the song is happy and uptempo. There are no other instruments in this song. This song can be played in a romantic mood. This audio can be used in a guitar promotional video.", "audio": "/zhanghaomin/datas/musiccap/music_data/1O4LpU7HggY.wav"} +{"id": "1OIfQHKnAcw", "caption": "A male singer sings this emotional melody. The song is medium tempo with a piano accompaniment and a strong bass drum kick . The song is emotional and romantic. The song is a home music video .", "audio": "/zhanghaomin/datas/musiccap/music_data/1OIfQHKnAcw.wav"} +{"id": "1PKxdTlquCA", "caption": "The Pop song features a flat female vocal, supported by wide harmonizing background vocals, singing over groovy acoustic rhythm guitar, offbeat shimmering open hats, claps, offbeat synth keys chords and a simple \"4 on the floor\" kick pattern that perfectly complements the groovy bass. Sounds energetic and uptempo, like something you would hear in clubs, or on a radio.", "audio": "/zhanghaomin/datas/musiccap/music_data/1PKxdTlquCA.wav"} +{"id": "1PN-bfs2EhY", "caption": "The low quality recording features a girl with a sweet voice singing over pop songs played on playback. The recording is in mono, very noisy and it sounds muffled, but also happy, fun and innocent.", "audio": "/zhanghaomin/datas/musiccap/music_data/1PN-bfs2EhY.wav"} +{"id": "1PSzSTilu_s", "caption": "The low quality recording features a southern rock song that consists of flat male vocal singing over wide acoustic rhythm guitars, short electric guitar lick, smooth bass guitar, punchy snare, simple kick pattern and shimmering hi-hats. It sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/1PSzSTilu_s.wav"} +{"id": "1Q9DXhXMSFI", "caption": "The Low Quality recording features a regional Mexican song sung by reverberant male vocals over acoustic guitar chords, punchy snare and kick hits, groovy bass and funky piano chords. There is a short snare roll at one point that serves as a transition to the next section of the song. Sounds a bit muffled, as it is a live performance, but also energetic and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/1Q9DXhXMSFI.wav"} +{"id": "1QFli7KSXAQ", "caption": "The Rock song features a passionate male vocalist singing over wide electric guitar melodies, groovy bass guitar, shimmering cymbals, groovy toms, punchy snare and kick hits. It sounds energetic, passionate, emotional and loud.", "audio": "/zhanghaomin/datas/musiccap/music_data/1QFli7KSXAQ.wav"} +{"id": "1QSD-dzEv7Y", "caption": "This audio contains someone playing a bansuri flute in the mid-to high register. A piano is playing a repeating melody along with an e-bass. The flute is full of reverb. This song may be playing flute at home with a backing track.", "audio": "/zhanghaomin/datas/musiccap/music_data/1QSD-dzEv7Y.wav"} +{"id": "1RRGInmOhTQ", "caption": "This music is a lively instrumental. The tempo is fast with an infectious accordion harmony, rhythmic acoustic guitar, violin harmony and keyboard accompaniment. The music is pleasant, happy, cheerful, warm, sprightly, romantic, carefree, upbeat and genial. This music sounds like a movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/1RRGInmOhTQ.wav"} +{"id": "1Rd1w7Ty1ak", "caption": "The low quality recording features a pop song that contains a soft male vocal singing over soft crash cymbals, claps, punchy kick, shimmering shakers, groovy bass, piano melody and electric guitar melody. It sounds easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/1Rd1w7Ty1ak.wav"} +{"id": "1RhYdQnZ_hw", "caption": "This is an amateur vocal cover of a pop music piece. There is a teen female vocalist singing melodically. On the backing track, an acoustic guitar is heard playing the main theme while an acoustic sounding drum track is playing the rhythmic background. The atmosphere is melancholic.", "audio": "/zhanghaomin/datas/musiccap/music_data/1RhYdQnZ_hw.wav"} +{"id": "1RwhRTe-OKk", "caption": "The song is an instrumental. The song is medium tempo with three guitars playing in harmony, guitar accompaniment, guitar harmony, guitar lead and a strong bass line. The song is emotional and spirited. The song has an average audio quality and is played in front of a live audience.", "audio": "/zhanghaomin/datas/musiccap/music_data/1RwhRTe-OKk.wav"} +{"id": "1SO5RJLWKAs", "caption": "This is an electric guitar jam being performed by a 9 year-old. It is an amateur recording, so there is a constant feedback noise coming from the amp. The electric guitar has a clean sound. The tunes are mostly simple with a lot of muted strokes. The recording has an easygoing atmosphere. If the feedback noise can be bypassed, the tunes from this recording can be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/1SO5RJLWKAs.wav"} +{"id": "1SqihV_DnEg", "caption": "The track is a lullaby song that features a mellow male vocal with a mellow voice. A soft xylophone plays a melody on the foreground while a deep bass guitar adds a certain bounciness to the song's rhythm. The atmosphere is calmed and dreamy.", "audio": "/zhanghaomin/datas/musiccap/music_data/1SqihV_DnEg.wav"} +{"id": "1ToIyrmWFjw", "caption": "This is a Turkish arabesque rap music piece. There is a female vocalist singing in a melancholic manner in the Turkish language. The beat has a string sample and a flute sample in the melody. There is a very loud electronic drum beat in the rhythmic background. The song has a depressive atmosphere. This piece could be used in the background of sad Turkish social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/1ToIyrmWFjw.wav"} +{"id": "1TyOPtg0Yfk", "caption": "The clip includes a male singer singing in a traditional hindustani style of singing called Aakar. There is a tabla for percussion, and some kind of woodwind instrument. There are elderly background male vocalists who chant phrases in unison.", "audio": "/zhanghaomin/datas/musiccap/music_data/1TyOPtg0Yfk.wav"} +{"id": "1V7ReAk9k-4", "caption": "The hip-hop music excerpt features what sounds to be a doubled boy voice rapping. A typical hip-hop drum beat drives the pulse of the music. A sampled string sound is playing arpeggios as accompaniment. Other synth sounds can be heard playing short repeating melodies. The atmosphere is slightly tense.", "audio": "/zhanghaomin/datas/musiccap/music_data/1V7ReAk9k-4.wav"} +{"id": "1VKSpjXZvKo", "caption": "Solo horn with reverb performing a triad based melody. A male voice over can be heard in the beginning.", "audio": "/zhanghaomin/datas/musiccap/music_data/1VKSpjXZvKo.wav"} +{"id": "1W2Cz2Jj76Q", "caption": "The low quality recording features a muffled male vocal talking, after which he starts playing breathy flute melody. It is noisy, in mono and it sounds muffled and distorted, as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/1W2Cz2Jj76Q.wav"} +{"id": "1W2FOzSXsxs", "caption": "This low quality audio clip features a female voice singing the main melody. This is accompanied by a piano. There are no other instruments in this song. This song has a story-telling mood and is at a slow tempo. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/1W2FOzSXsxs.wav"} +{"id": "1WlvXneu6oY", "caption": "The song is instrumental music. The song is medium tempo with just a piano playing pensively and no other instrumentation. The song is emotional and poignant. The song is a western classical masterpiece, but with bad audio quality issues.", "audio": "/zhanghaomin/datas/musiccap/music_data/1WlvXneu6oY.wav"} +{"id": "1Xtkou9dtyA", "caption": "The Alternative/Indie song features layered punchy kicks, energetic crash cymbals, groovy bass and synth key chords, followed by electric guitar licks. It sounds haunting and energetic, almost like a halloween themed song.", "audio": "/zhanghaomin/datas/musiccap/music_data/1Xtkou9dtyA.wav"} +{"id": "1YPYQP6yupA", "caption": "The low quality recording features a passionate male vocal singing over mellow piano chords, shimmering hi hats, snappy rimshots, punchy kick and soft bass. It sounds emotional, passionate and heartfelt.", "audio": "/zhanghaomin/datas/musiccap/music_data/1YPYQP6yupA.wav"} +{"id": "1ZaxqZMs21M", "caption": "A male vocalist sings this spirited rock and rock song. The tempo is fast with bright drumming, intense electric guitar feedback, keyboard harmony and rhythmic acoustic guitar with vocal backup. The song is upbeat, spirited, enthusiastic, vibrant, vivacious, buoyant and youthful with a dance groove. The sound quality is inferior making it difficult to understand the lyrics or the finer elements of this Rock and Roll song.", "audio": "/zhanghaomin/datas/musiccap/music_data/1ZaxqZMs21M.wav"} +{"id": "1Ziku4FLka4", "caption": "This is an educational kids song. There is a female vocalist singing playfully. The piano and the xylophone are playing a simple melody. The rhythm is a basic acoustic drum beat. The atmosphere is joyful. This piece can be used in the soundtrack of a kids TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/1Ziku4FLka4.wav"} +{"id": "1_YHHL_t2GI", "caption": "The low quality recording features clapping and shoe tapping sounds over rock songs played on playback. The song consists of a passionate male vocal that sings over punchy kick and snare hits, shimmering hi hats, electric guitar melody and groovy bass guitar. The recording is in mono and a bit noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/1_YHHL_t2GI.wav"} +{"id": "1a_nvi4sW64", "caption": "The low quality recording features a disco song that consists of passionate female vocals and wide harmonizing female vocals singing over funky bass guitar, mellow synth keys chords, funky electric guitar chords, shimmering hi hats, clapping and \"4 on the floor\" kick pattern. It sounds funky and energetic, but also thin and hollow, due to the bad mixing.", "audio": "/zhanghaomin/datas/musiccap/music_data/1a_nvi4sW64.wav"} +{"id": "1bSP4wLfMpA", "caption": "A cello section is playing a short stroke melody with the bow while other strings, probably violins are playing a one note drone in a high key. Timpani hits and rolls are adding depth to the musical scenario. In the background you can hear sound effects opening up the soundscape for a deeper male voice screaming/crying along to a chainsaw sound. This song may be playing in a movie scene where someone is getting tortured.", "audio": "/zhanghaomin/datas/musiccap/music_data/1bSP4wLfMpA.wav"} +{"id": "1cqcTbDxsHM", "caption": "The low quality recording features a pulsating theremin synth lead and haunting synth lead playing in the background. It sounds low, analog, spooky and spacey, almost like outer space communication.", "audio": "/zhanghaomin/datas/musiccap/music_data/1cqcTbDxsHM.wav"} +{"id": "1cwGW0cBdRs", "caption": "The low quality recording features a cover of a rock song and it contains sad theremin lead melody played over playback instrumental that consists arpeggiated electric guitar melody and mellow rimshots in the right channel of the stereo image, smooth bass guitar that leans towards the left channel and shimmering cymbals. It sounds emotional, sad and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/1cwGW0cBdRs.wav"} +{"id": "1dt9eL2rmSY", "caption": "The soundtrack features various aquatic animals like whales and dolphins making sounds. The keyboard plays synth tones with organ sounds with the grunting, squeaking and growling tones. The sound quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/1dt9eL2rmSY.wav"} +{"id": "1gDNqOQFopY", "caption": "This clip is of an amateur recording. It features a male voice. He starts off the song by singing a quacking melody followed by yodeling. There are no words in this song. This voice is accompanied by a piano playing chords. There are no other instruments in this song. This song has a comedic feel to it. This song can be played at a house party.", "audio": "/zhanghaomin/datas/musiccap/music_data/1gDNqOQFopY.wav"} +{"id": "1h2sb2xeCt8", "caption": "The low quality recording features a ballad that consists of a soft female vocal singing over a mellow piano melody and shimmering bells at the end of the loop. The recording is noisy and it sounds passionate, emotional and mystical, almost like a lullaby.", "audio": "/zhanghaomin/datas/musiccap/music_data/1h2sb2xeCt8.wav"} +{"id": "1hABzqBHh7w", "caption": "A male vocalist sings this spirited song. The tempo is fast with trumpets, keyboard harmony, steady drumming and simple bass lines along with vocal backup. The song is happy, energetic, enthusiastic, popular, peppy, vivacious and celebratory. There are sounds in the background of people talking, hooting, cheering and scuttling and rustling. This is a popular Folk/Regional song.", "audio": "/zhanghaomin/datas/musiccap/music_data/1hABzqBHh7w.wav"} +{"id": "1hWAOReJehw", "caption": "This song contains an accordion playing a fast melody along with a female voice singing her own melody with a lot of vibrato and sliding down tones. A tabla is playing a rhythm. Everybody seems to make their own thing. So this can be considered a complex composition. This song may be playing live with people listening and sitting on the floor.", "audio": "/zhanghaomin/datas/musiccap/music_data/1hWAOReJehw.wav"} +{"id": "1heMbyumHAo", "caption": "This is a remix of an R&B soul piece. There is a male vocal singing in a laid-back manner joined by an auto-tuned male vocal. The keyboard provides the melody with a gentle bass guitar playing in the background. The rhythmic structure is composed of the acoustic drums and the percussion playing a medium tempo beat. The atmosphere of the piece is groovy and there is a feelgood aura to it. This piece could be used in the soundtrack of a sitcom.", "audio": "/zhanghaomin/datas/musiccap/music_data/1heMbyumHAo.wav"} +{"id": "1i1sbQOILb0", "caption": "The low quality recording features a live performance of traditional music and it consists of harmonizing female vocals singing over shimmering hi hats and tambourine hits, fat snare, boomy kick, groovy bass and short strings melody. The stereo image is unbalanced as the vocals are leaning towards the right channel of the stereo image. It sounds soulful and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/1i1sbQOILb0.wav"} +{"id": "1j13NdQiw8c", "caption": "This music is instrumental. The tempo is fast with a lively keyboard harmony, steady drumming, groovy bass lines and harmonica melodic. The song is fresh, groovy, sunny, happy; vivacious and spirited. The song is a live performance outdoors as there are ambient nature sounds like the breeze,and sound of people talking.", "audio": "/zhanghaomin/datas/musiccap/music_data/1j13NdQiw8c.wav"} +{"id": "1j3pXUr8R4M", "caption": "This instrumental song features a harp melody being played. There are no other instruments in this song. There are no voices in this song.. The mood of this song is dreamy. This song can be played in a dream sequence in an animated film.", "audio": "/zhanghaomin/datas/musiccap/music_data/1j3pXUr8R4M.wav"} +{"id": "1j4rFfU5XKQ", "caption": "This song contains several drum hits and percussive instruments playing a fast paced rhythm that motivates dancing along. An e-bass is bringing the low end supporting the drums. Cuatro guitars are strumming chords as a rhythmic addition. Trumpets are playing a loud and catchy melody. Some of the musical elements are slightly panned to the left and right side of the speakers. This song may be playing at a cheerful event.", "audio": "/zhanghaomin/datas/musiccap/music_data/1j4rFfU5XKQ.wav"} +{"id": "1jATjKL2vAE", "caption": "This music is instrumental. The tempo is fast with a rhythmic guitar lead. There is minimal instrumentation and the music is an upbeat, energetic and catchy riff.", "audio": "/zhanghaomin/datas/musiccap/music_data/1jATjKL2vAE.wav"} +{"id": "1jptuEjuTig", "caption": "The low quality recording features a live performance that consists of reverberant wooden percussion over an electro song, followed by crowd talking and public announcement vocals in the background. The song consists of groovy bass, haunting synth lead, soft \"4 on the floor\" kick pattern and shimmering shakers. It sounds like it was recorded somewhere outdoors, judging by the public announcement vocal and crowd noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/1jptuEjuTig.wav"} +{"id": "1kYDbl5Y9Sg", "caption": "This is the live performance of a Paraguayan folk music piece. There is no singer. There is a Paraguayan harp playing a vibrant yet melancholic tune. The atmosphere is heart-touching. This piece could be used in the soundtrack of a drama movie during a scene of serenity or mourning.", "audio": "/zhanghaomin/datas/musiccap/music_data/1kYDbl5Y9Sg.wav"} +{"id": "1l7BjFDQLUM", "caption": "This is a jingle piece. There is no singer in this piece. There is an organ and a keyboard playing the main melody while bells and other percussive elements provide the rhythmic background. The atmosphere is cheerful. This piece could be used as an advertisement jingle. It could also be used at a festive event setting such as Christmas or Thanksgiving.", "audio": "/zhanghaomin/datas/musiccap/music_data/1l7BjFDQLUM.wav"} +{"id": "1lgqqW5TsJk", "caption": "This song contains digital drums with a deep low kick sound, a sharp hi hat and a loud bellsound with its own rhythm. A synthesizer is playing a lead sound in the mid range before jumping up an octave after a male scratched vocal sample is being played. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/1lgqqW5TsJk.wav"} +{"id": "1ls3ectO1F4", "caption": "This song contains acoustic drums with reverb and a bassline playing to the kick. Someone is playing a slow evolving melody on a distorted e-guitar. In the background you can hear voices. This song may be playing live at a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/1ls3ectO1F4.wav"} +{"id": "1mB_cboJR8s", "caption": "This meditation music features a male voice in a low tone chanting words in a melodic tone. There are no other instruments in this song. The mood of this song is relaxing. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/1mB_cboJR8s.wav"} +{"id": "1nUqhH8bAPk", "caption": "A country-song with guitar, acoustic drums and a almost walking bassline is playing along with a high pitched baby voice singing along to some sound effects/noise samples of some ribbon. This recording is in very poor quality. This song may be playing as a joke to pull off on someone.", "audio": "/zhanghaomin/datas/musiccap/music_data/1nUqhH8bAPk.wav"} +{"id": "1o7iTDLNTFk", "caption": "This clip features a guitar chord being strummed in the beginning. This is followed by a male voice narrating a song. There are no other instruments in this song. There is no vocal melody in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/1o7iTDLNTFk.wav"} +{"id": "1pR0SgbqP3M", "caption": "A male vocalist sings this lively pop. The tempo is fast and peppy with animated trumpets, groovy saxophone, slick drumming, funky bass line, keyboard harmony, synthesiser arrangements and electronic sounds. The song is upbeat, energetic, enthusiastic, youthful, vibrant, effervescent; passionate and electrifying. This song is Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/1pR0SgbqP3M.wav"} +{"id": "1rhsnmWLeGw", "caption": "A female vocalist sings this pleasant melody. The tempo is slow with a melodic piano accompaniment. There is minimal instrumentation with emphasis on vocals. The song is soft, mellow, soothing, calming, mellifluous, pleasant, and dreamy. This song is a love song, children\u2019s song or a lullaby.", "audio": "/zhanghaomin/datas/musiccap/music_data/1rhsnmWLeGw.wav"} +{"id": "1tNkAc29aPE", "caption": "This song is an instrumental. The tempo is medium with an upbeat electric guitar harmony. The music is minimal with no other instrument as accompaniment. It is Loud, sharp, intense, youthful and rhythmic. The vibrations of the music can be heard even after it stops playing. This music is Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/1tNkAc29aPE.wav"} +{"id": "1tz4xNRRR4M", "caption": "This lullaby features a fruity male vocal talking over a haunting bell melody. At the end of the loop, there is a sustained string swell. It sounds creepy, haunting, mystical and like a theme song for a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/1tz4xNRRR4M.wav"} +{"id": "1uHF1-8TcEk", "caption": "The clip features a choir singing a hymnal type of song. This was recorded live. There's a piano accompanying the choir. They are humming in a gentle and angelic way.", "audio": "/zhanghaomin/datas/musiccap/music_data/1uHF1-8TcEk.wav"} +{"id": "1xhwyUVSRQk", "caption": "A female singer sings this cool pop melody with backup singers in vocal harmony. The song is medium tempo with a groovy bass line, steady drumming rhythm, and keyboard accompaniment . The song is exciting and youthful. The audio quality with a lot of ambient crowd noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/1xhwyUVSRQk.wav"} +{"id": "1y1lEOGBcWM", "caption": "The low quality recording features a suspenseful piano melody played over mellow synth pad chords. It sounds intense, mystical, but also passionate, as something you would hear in movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/1y1lEOGBcWM.wav"} +{"id": "1yGWdegJjA4", "caption": "Instrumental electro music with a half time feel in the kick and busy drums. The bass is constantly busy, with resonant filter sweeps for dramatic effect. There are multiple overlapping high synth melodies with big sounding reverb throughout. Perfect for a large outdoor or stadium EDM festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/1yGWdegJjA4.wav"} +{"id": "1yWGmdevTuM", "caption": "This tribal music is played on a didgeridoo. It is played by vibrating the lips over the instrument using breathing techniques. The song has a continuous droning sound and inter spread with low pitch bass sounds. There are no voices in this song. This audio can be used in a movie where the protagonist is trapped in a forest.", "audio": "/zhanghaomin/datas/musiccap/music_data/1yWGmdevTuM.wav"} +{"id": "1ypKEH2kd7g", "caption": "The song is an instrumental jazz tune. The tempo is medium with steady drumming with drum brushes and other percussive hits, piano accompaniment, guitar accompaniment, groovy bass line and a muted trumpet playing a cool solo. The song is a jazz improvisation of a romantic melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/1ypKEH2kd7g.wav"} +{"id": "2-K-7T8ZIWA", "caption": "This music is an instrumental of the Christmas Carol \u201cYou Better Watch Out\u2019. The tempo is medium with the lead harmony on the theremin and piano accompaniment. The music is haunting, ethereal, lilting, mesmerising and captivating. This music is a Theremin Instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/2-K-7T8ZIWA.wav"} +{"id": "20QZS9L5WeA", "caption": "The low quality recording features a mellow arpeggiated piano melody playing in the background, while the breathy flute melody is playing over it. It sounds passionate, emotional and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/20QZS9L5WeA.wav"} +{"id": "20Vh6z6Ie0E", "caption": "The recording features a live performance of a pop song that consists of passionate female vocal singing over groovy piano melody, sustained strings melody, smooth bass, widely spread shimmering shaker, snaps and snappy rimshots. It sounds euphoric, as it brings a Christmassy vibe, and is also happy and nostalgic.", "audio": "/zhanghaomin/datas/musiccap/music_data/20Vh6z6Ie0E.wav"} +{"id": "21MgIcLN8Ow", "caption": "The low quality recording features a didgeridoo melody being played. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/21MgIcLN8Ow.wav"} +{"id": "23xC7lTBikU", "caption": "This is the live recording of a didgeridoo concert. The didgeridoo is being played at a wide variety of frequency ranges. There is a raw feel to this piece. The sound has tribal characteristics. The sounds from this recording could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/23xC7lTBikU.wav"} +{"id": "244y56-vLWE", "caption": "A male singer sings this exciting Latin dance melody. The tempo is medium fast with a saxophone solo, percussive bass line, guitar accompaniment, latin percussion, steady drumming rhythm, and cymbal crashes. The song is exciting with the crowds going crazy. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/244y56-vLWE.wav"} +{"id": "24cmo2fEQo8", "caption": "The low quality recording features an echoing tom, snappy rimshots and echoing, repetitive arpeggiated harp melody playing, after which there is a punchy kick hit. It sounds groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/24cmo2fEQo8.wav"} +{"id": "25Ccp8usBtE", "caption": "The low quality recording features a harmonizing female vocal melody singing over a groovy piano melody. It sounds happy, joyful and fun, even though the recording is very noisy - to the point that the audio is distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/25Ccp8usBtE.wav"} +{"id": "25RWrqQol7Y", "caption": "These are various sound effects compiled into a track. There is an electronic music/dubstep influence on the sounds. A strong bass synth can be heard playing. The sounds of glass shattering and ice breaking were used to create a dramatic effect. The atmosphere of the track is aggressive. This track could be used as an opening theme to a gaming/sports/gym Youtube channel. Samples of this track could also be used in the sound effects of an action movie or a video game. It could also fit well in an advertisement targeted at a male audience.", "audio": "/zhanghaomin/datas/musiccap/music_data/25RWrqQol7Y.wav"} +{"id": "26HLgXWF-Co", "caption": "This audio contains someone playing a classical melody on an acoustic guitar using fingerstyle. This audio is full of reverb. This song may be playing at a talent show.", "audio": "/zhanghaomin/datas/musiccap/music_data/26HLgXWF-Co.wav"} +{"id": "26IOFykrJrc", "caption": "This is a jazz music piece with a saxophone solo as the lead. There is a clean-toned synth bass in the background creating an epic atmosphere. It would fit perfectly in a movie/TV show setting as a soundtrack opening.", "audio": "/zhanghaomin/datas/musiccap/music_data/26IOFykrJrc.wav"} +{"id": "26jTWRMRoxY", "caption": "The song is an instrumental with separate audio tracks. The tempos are medium with female vocals, backup singers, groovy drum rhythms, keyboard harmony, guitar accompaniment and various percussive hits. The song is energetic and exciting. The song is an ad jingle for a software product. The audio quality is poor with hissing tones.", "audio": "/zhanghaomin/datas/musiccap/music_data/26jTWRMRoxY.wav"} +{"id": "28pkN4m1x6I", "caption": "This is an electro swing/funk music piece. It is an instrumental piece. There is a brass section making up the most of the melody with the saxophone as the lead. The bass line is being played by the tuba. There is also a piano adding texture to the melody. The rhythmic background is provided by an electronic drum beat. The atmosphere is upbeat and eccentric. This piece could be playing at a nightclub or a dance club. It could also work well in the soundtrack of a comedy animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/28pkN4m1x6I.wav"} +{"id": "28wBrNjHXOM", "caption": "This is a meditation music piece. There is a didgeridoo playing a vague melody at the forefront while repetitive shamanic drum hits can be heard in the background. The atmosphere is profound and calming. This piece can be used in the background of meditation videos. It can be used during sessions at yoga centers.", "audio": "/zhanghaomin/datas/musiccap/music_data/28wBrNjHXOM.wav"} +{"id": "298Q_pSLflU", "caption": "This song contains a lot of different synthesizer sounds. One is playing a lead melody in a higher register while two others are playing a rhythmic repeating melody in the mid and low register. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/298Q_pSLflU.wav"} +{"id": "2ATMQxWVpXk", "caption": "A male singer screams and laughs loudly. The song is medium tempo with steady rock drumming, groovy bass line and electric guitar rhythm. The song is energetic and haunting. The song is a modern punk rock song.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ATMQxWVpXk.wav"} +{"id": "2BBAUwC1BI4", "caption": "The low quality recording features an arpeggiated electric guitar melody performance. The recording is noisy and in mono, as it was probably recorded with a phone. It sounds mystical and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/2BBAUwC1BI4.wav"} +{"id": "2BGzxAuetOA", "caption": "A male vocalist sings this song. The tempo is slow, with intense drumming; keyboard harmony, groovy bass lines and electric guitar harmony in the background. The vocalist is singing a dissonant tune along with syncopated music over the melodious and rhythmic background. This is probably karaoke.", "audio": "/zhanghaomin/datas/musiccap/music_data/2BGzxAuetOA.wav"} +{"id": "2CzfBZ1mYBs", "caption": "This song is full of rhythmic elements and an e-bass that supports the mood for dancing. A rhodes/organ is playing a simple melody along with a trumped playing its own melody. The recording is full of synth pad sound and crash hits. This song may be playing on a portable speaker while riding a bike with friends during summer.", "audio": "/zhanghaomin/datas/musiccap/music_data/2CzfBZ1mYBs.wav"} +{"id": "2FQKfGCwjSE", "caption": "The song has different music tracks played in succession. The song has guitar accompaniment and a groovy bass followed by female singer singing vocal chants with male backup singer in vocal harmony, on a groovy drum rhythm and keyboard harmony with white noise added. The song is probably an ad jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/2FQKfGCwjSE.wav"} +{"id": "2G4lyzAZ1vk", "caption": "A female voice is singing soulfully, sounding a little airy and sensual. Someone is playing neo-soul chords on an e-guitar. This song may be playing at home singing along to a karaoke song. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/2G4lyzAZ1vk.wav"} +{"id": "2G5bSYHcJSM", "caption": "The low quality recording features a weird repetitive, funny male vocal singing over a weird instrumental that consists of punchy kick and rimshots, tinny percussion, some synth lead melody and filter modulated bass. It sounds funny and it is in mono - almost like a prank song.", "audio": "/zhanghaomin/datas/musiccap/music_data/2G5bSYHcJSM.wav"} +{"id": "2GWkKVHxGRM", "caption": "This music is a live instrumental.The music is medium tempo with a dominant piano accompaniment, keyboard harmony, bright drumming, funky bass line, congas rhythm and tambourine beats. The music is a live performance as there are ambient background sounds of people talking and laughing.", "audio": "/zhanghaomin/datas/musiccap/music_data/2GWkKVHxGRM.wav"} +{"id": "2GepmcbNlJY", "caption": "The recording is of poor quality. A male voice is singing soulfully along to a backing instrumental sounding like coming out of some speakers. There is a piano playing and you can hear electric drums. This song may be playing at home practicing singing.", "audio": "/zhanghaomin/datas/musiccap/music_data/2GepmcbNlJY.wav"} +{"id": "2Gja9wBkz6U", "caption": "The low quality recording features a theremin solo melody. It sounds spacey and weird, as the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/2Gja9wBkz6U.wav"} +{"id": "2I6pPRWKsCQ", "caption": "The low quality recording features a live performance of a R&B song that consists of muffled male vocal singing over groovy bass guitar, mellow synth keys melody and energetic drums. There are some crowd noises in the background. The recording is noisy, as it was probably recorded with a phone, but it sounds energetic, passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/2I6pPRWKsCQ.wav"} +{"id": "2Ic1zm9mBjk", "caption": "The song is an instrumental. The song is medium tempo with a sitar playing solo, tabla playing percussively and other Indian percussion instruments. The song is emotional and poignant. The audio quality is very ordinary.", "audio": "/zhanghaomin/datas/musiccap/music_data/2Ic1zm9mBjk.wav"} +{"id": "2IpapScfsT4", "caption": "This instrumental song features a run played on a piano followed by an ascending progression on the French horn. The horn plays descending notes and the piano repeats the same melody using arpeggiated chords. This is followed by two ascending notes on the horn. There are no other instruments in this song. This song has a relaxing feel. This song can be played in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/2IpapScfsT4.wav"} +{"id": "2JNY2SaMk7s", "caption": "This reggae song features a male voice making an announcement in the beginning. A female voice sings a one-line melody. This is accompanied by the main male voice singing vocables in the background. Until this part, only a keyboard and guitar are playing a reggae rhythm. This is followed by the main male voice singing the main melody in a reggae style. This is accompanied by a kick driven percussion playing a simple beat. There are voices singing vocables in the background. The mood of this song is happy. This song can be played in a movie with a holiday theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/2JNY2SaMk7s.wav"} +{"id": "2JnlmS1zzls", "caption": "A male chorus sings this passionate song in a foreign language which sounds like Greek. The song is medium tempo with hand percussion like drums, small hand drum, tambourine and a beat with sticks. The vocals are emphatic and sung in lively parts. The song is passionate, emotional, sentimental, and sounds like an anthem or a love song for the Country or a Leader.", "audio": "/zhanghaomin/datas/musiccap/music_data/2JnlmS1zzls.wav"} +{"id": "2JuMYUPMGGM", "caption": "This is an electronic piece played in an instructive video. A sine wave synth sound is used both in the chords and the lead section. It is in medium-to-high range. There is a bizarre feeling in this piece. Although the piece is interrupted in the original, parts of it can be lifted to be used as samples in the soundtrack of an outer space sci-fi movie/video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/2JuMYUPMGGM.wav"} +{"id": "2KGnpMYHBGI", "caption": "The excerpt features for most part atmospheric sounds like whispers, a string being strummed, and electronic sounds. Some of the sounds kind of imitate the sounds dolphins make. The atmosphere is somewhat quiet.", "audio": "/zhanghaomin/datas/musiccap/music_data/2KGnpMYHBGI.wav"} +{"id": "2KkNk9Ao7G4", "caption": "The low quality recording features a punchy kick and snare hits, followed by shimmering hi hats, buzzy synth bass and 8 bit synth lead melody. It sounds groovy, weird and like something you would hear as background music in games.", "audio": "/zhanghaomin/datas/musiccap/music_data/2KkNk9Ao7G4.wav"} +{"id": "2KwSyaLT_mw", "caption": "Someone is playing a clean e-guitar with a chorus and tremolo effect. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/2KwSyaLT_mw.wav"} +{"id": "2M-CFCo-rkY", "caption": "This is an emotional Japanese pop ballad. The singer has a light, airy and gentle voice that she uses to sing over the deep and full piano arpeggios. The song has a calming and emotional effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/2M-CFCo-rkY.wav"} +{"id": "2MZUbxulAI4", "caption": "This is the behind-the-scenes video of a movie soundtrack. There are male voices talking to each other and singing under footage. There is a faint backing track in the video. A bansuri flute is playing a melody while the tabla percussion is playing the rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/2MZUbxulAI4.wav"} +{"id": "2MpzHv5KNZU", "caption": "This is an instrumental classical music performance. There is a gentle tune being played with the piano sound. Ambient sounds such as birds singing can be heard in the recording. The atmosphere is soothing and relaxing. This is a perfect piece for a sleep music playlist. It could also work well as an advertisement jingle. It could be playing in the background at a nursery.", "audio": "/zhanghaomin/datas/musiccap/music_data/2MpzHv5KNZU.wav"} +{"id": "2OI4QeokeRQ", "caption": "This is a country music piece. There is a female vocalist singing melodically as the lead at a medium-to-high range. A mandolin is playing the main theme while being backed by a bass guitar. The rhythmic background consists of a simple 4/4 acoustic drum beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/2OI4QeokeRQ.wav"} +{"id": "2Q20hVyYjBM", "caption": "A male vocalist sings this passionate song in Dutch. The tempo is slow with vocal emphasis and an accordion harmony. The song is a simple, narrative, slow Folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/2Q20hVyYjBM.wav"} +{"id": "2RMOegT2Jn8", "caption": "hip hop music featuring a young male rapper over a minimalist beat with only percussion such as cowbell, kick drum, shaker, and triangle.", "audio": "/zhanghaomin/datas/musiccap/music_data/2RMOegT2Jn8.wav"} +{"id": "2RU4CSDzS-g", "caption": "This slow pop song features a male voice singing the main melody. This is accompanied by an acoustic guitar plucking chords. Another acoustic guitar plays in harmony with the first guitar. The mood of this song is romantic. The voice is calming and the song is relaxing. The bass notes are accented and toward the end, the bass notes slide to the next note. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/2RU4CSDzS-g.wav"} +{"id": "2SI_uNBcSyw", "caption": "This is the nightcore version of a rock music piece. There is a distorted electric guitar sound playing the main melody and a bass guitar in the background. The rhythm consists of a slightly fast-paced and hard-hitting rock acoustic drum beat. The atmosphere is rebellious. This piece could be used in the soundtrack of an anime.", "audio": "/zhanghaomin/datas/musiccap/music_data/2SI_uNBcSyw.wav"} +{"id": "2SQxfaWAJJg", "caption": "This audio contains fast paced digital drums changing the beat from halftime into a four on the floor with a kick on every beat along with a synth bassline. Other synth sounds are playing a lead sound and an arpeggiolike melody along with a distorted e-guitar. A female voice is singing in a high pitch accompanied by another female backing voice creating a harmony. This song may be playing as an entry for a fast paced action series.", "audio": "/zhanghaomin/datas/musiccap/music_data/2SQxfaWAJJg.wav"} +{"id": "2SenLjPbGzU", "caption": "The low quality recording features a pop song that consists of a passionate male vocal, alongside background male vocals, singing over punchy 808 bass, claps, shimmering hi hats, wide tinny percussion, repetitive synth lead melody and groovy synth keys melody. It sounds groovy, addictive and exciting - like something you would hear in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/2SenLjPbGzU.wav"} +{"id": "2ShO1jZYZeA", "caption": "This techno song features programmed percussion playing at a fast tempo. After two bars, the percussion plays a crash cymbal and pauses. There are layers of synth sounds. One layer is playing a high pitched repetitive melody. Another layer is playing the lower octaves of the same melody but the sound is different. Another synth is playing the bass parts using the same melody. This is an instrumental song with a techno feel. This song can be used in an advertisement for a luxury item.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ShO1jZYZeA.wav"} +{"id": "2T1P9ovsl4A", "caption": "The low quality recording features an emotional electric guitar melody, shimmering hi hats, soft kick hits and punchy snare in the left channel and arpeggiated electric guitar melody and simple bass guitar in the right channel of the stereo image. Due to this unconventional panning, the stereo image sounds a bit unbalanced. It is still emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/2T1P9ovsl4A.wav"} +{"id": "2U8Dvh7nwFI", "caption": "This is a pop music piece. The words are being sung by two vocals: one male and one female which lead to a duet for the chorus. There is a banjo and an electric guitar playing the melody while a simple electronic drum beat provides the rhythmic background for the song. It is a slightly melodic and emotional song. This piece could be used in the soundtrack of a romantic drama during a flashback scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/2U8Dvh7nwFI.wav"} +{"id": "2UY_-oF1vqo", "caption": "This song contains a digital drum playing a simple pattern with a kick and a snare sound. Synthesizers are playing a repeating melody in the higher register. Another synth sound is playing a more aggressive lead sound with a countermelody. A string sample is being used to create a short hit. This song may be playing during a car ride.", "audio": "/zhanghaomin/datas/musiccap/music_data/2UY_-oF1vqo.wav"} +{"id": "2Ui85-AOLyo", "caption": "This is a live recording of a DJ doing deck scratching on a hip hop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/2Ui85-AOLyo.wav"} +{"id": "2UnlMwW8nyI", "caption": "This children's song features an accordion playing chords. This is accompanied by percussion playing a simple beat. The bass plays the root notes of the chords. An instrument like the xylophone plays the main melody on the low frequencies. There are no voices in this song. This song is an instrumental. The mood of this song is happy. This song can be played in a children's animation series.", "audio": "/zhanghaomin/datas/musiccap/music_data/2UnlMwW8nyI.wav"} +{"id": "2VFVe0RCn7g", "caption": "Someone is playing a distorted e-guitar. Finger-tapping a classical music piece. This is an amateur recording and not of the best sound-quality. This song may be playing at home showing off your skills to a friend.", "audio": "/zhanghaomin/datas/musiccap/music_data/2VFVe0RCn7g.wav"} +{"id": "2WxUIkF2zEw", "caption": "In the forefront you can hear water running while a jazz piece is playing in the background. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/2WxUIkF2zEw.wav"} +{"id": "2YAyM0aHFRU", "caption": "This song has a traditional African Arabic feel to it. There is an accordion, an upbeat vibe, and an ethnic vocal performance by the male vocalist. It is a live recording and the audio quality is not professional.", "audio": "/zhanghaomin/datas/musiccap/music_data/2YAyM0aHFRU.wav"} +{"id": "2YQPwRLB1s0", "caption": "The low quality recording features a jungle track that consists of bouncy snare, soft kick, shimmering shakers, energetic ride cymbal, claps and groovy bass. There are some zipping sound effects, alongside energetic female vocal phrases. It sounds energetic, but yet smooth. Sounds like a soundtrack for a commercial.", "audio": "/zhanghaomin/datas/musiccap/music_data/2YQPwRLB1s0.wav"} +{"id": "2ZB7DUGOdZw", "caption": "The song is an instrumental. The song is fast tempo with distorted guitars playing in rhythm. The song is energetic and an amateurish performance. The song is of very poor quality with audio noise and hissing sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ZB7DUGOdZw.wav"} +{"id": "2ZYzviKuq9w", "caption": "This is a hip-hop music piece. There is a female vocalist singing in a rap-like manner. There is a strong bass in the background. For the rhythm, there is a simple electronic drum beat with heavy use of claps. The keyboard is playing occasional tunes. The atmosphere is groovy. This piece could be playing in the background at a nightclub or at a dance club.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ZYzviKuq9w.wav"} +{"id": "2ZfthfWQowE", "caption": "The song is an instrumental. The song is medium fast tempo with African folk drumming rhythm, string section, violins playing, horns and woodwinds playing in harmony. The song is adventurous and exciting. The song is an advertisement jingle for a DSLR camera complete with camera click tones. The audio is of poor quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ZfthfWQowE.wav"} +{"id": "2ZgEbNi--8Q", "caption": "A male singer sings this aggressive vocal. The song is medium tempo with a slick drumming rhythm, groovy bass line, sonic tones, keyboard harmony and various percussive hits. The song is a modern electronic dance music with trance influences. The song has bad quality audio issues.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ZgEbNi--8Q.wav"} +{"id": "2ZogsGp-T4o", "caption": "This song is a mandolin instrumental. The tempo is medium with a lively melody on the mandolin. The music is minimalist without any other instruments. The music is high pitched, melodious and charming. This audio ends abruptly indicating that this could be a mandolin tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ZogsGp-T4o.wav"} +{"id": "2ZrqWkdwVzo", "caption": "The low quality recording features a harpsichord melody being played. The recording is extremely noisy and it sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ZrqWkdwVzo.wav"} +{"id": "2_Vk3tmqz-0", "caption": "The clip sounds like a live performance of Hawaiian Luau music. The song has a generally positive and uplifting effect - it can put you into a good mood. There are several layers of guitars. There's also a main string instrument that plays arpeggiated notes.", "audio": "/zhanghaomin/datas/musiccap/music_data/2_Vk3tmqz-0.wav"} +{"id": "2_kLD3IbF2c", "caption": "This song contains background noises such as a goat sound, wind blowing and very low horns blowing one note. Then the music comes in with a string section playing a short stroke melody. This song may be playing in a war/adventure video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/2_kLD3IbF2c.wav"} +{"id": "2_mFg42LlUI", "caption": "The low quality recording features a huge church organ chord progression, followed by shimmering cymbals, played in a huge reverberant space - most likely a church. It sounds epic and powerful.", "audio": "/zhanghaomin/datas/musiccap/music_data/2_mFg42LlUI.wav"} +{"id": "2aPVOidHLXI", "caption": "The low quality recording features a wide, soft whispering male vocals singing over a wide electric guitar melody, shimmering cymbals and drum roll. In the second part of the loop there is an energetic male vocal singing over more energetic electric guitar chords, distorted bass, punchy kick and snare hits and shimmering cymbals. It sounds energetic, aggressive, but also messy and kind of chaotic, since the mix is dirty.", "audio": "/zhanghaomin/datas/musiccap/music_data/2aPVOidHLXI.wav"} +{"id": "2bCuw7U_Rac", "caption": "This low quality recording features a male voice singing the main melody in a foreign language. This is accompanied by percussion playing a simple beat with a Latin feel. The bass is played on a double bass. The double bass plays a groovy bassline. Flute fills are played in the background. An accordion plays melodies in harmony with the voice. This song has romantic overtones. This song can be played at the end credits of a mafia romance movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/2bCuw7U_Rac.wav"} +{"id": "2bcnAoZbptI", "caption": "This is a live performance of a pop music piece. There is a male vocalist singing melodically in the lead. There is a catchy tune that is being performed on a keyboard with a piano sound.The atmosphere is sentimental. This piece could be used in the soundtrack of a romantic comedy movie, especially during the scenes where the characters are starting to fall in love with each other.", "audio": "/zhanghaomin/datas/musiccap/music_data/2bcnAoZbptI.wav"} +{"id": "2ctgUIqyaBk", "caption": "This pop song features a male voice singing the main melody in a foreign language. The melody is repetitive. This is accompanied by percussion playing a simple beat. The bass plays the root notes of the chords. A guitar plays arpeggiated chords using a chorus effect. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/2ctgUIqyaBk.wav"} +{"id": "2cxs73i3l1M", "caption": "The low quality recording features a passionate female vocal, alongside harmonizing background vocals, singing over wide wooden percussion, groovy bass and shimmering shakers. It sounds joyful, emotional and passionate. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/2cxs73i3l1M.wav"} +{"id": "2cxvYC9QZac", "caption": "A male singer sings this passionate melody. The song is medium tempo with Latin percussion, guiro percussions, guitar rhythm, piano accompaniment and guitar rhythm. The song is romantic and spirited. The song is a Latin dance song with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/2cxvYC9QZac.wav"} +{"id": "2dyEnOo3yJ8", "caption": "The low quality recording features a traditional song that consists of passionate female vocal singing over wooden percussive elements, strings and flute melody. It sounds passionate, emotional and soulful and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/2dyEnOo3yJ8.wav"} +{"id": "2dyxjGTXSpA", "caption": "A male vocalist sings this intense melody in a foreign language.The tempo is slow with a keyboard and organ accompaniment that is burgeoning as the song progresses. The vocals are eloquent, emphatic, persuasive and lilting and the vibe of the song is mellow, persuasive, passionate, emotional and appealing.", "audio": "/zhanghaomin/datas/musiccap/music_data/2dyxjGTXSpA.wav"} +{"id": "2f1UXGix_Cw", "caption": "The low quality recording features a techno song that consists of a compilation of sounds. The first version is thin and crushed, as it was played on a speaker and recorded with a poor microphone. The second version is the actual song being played, which consists of a \"4 on the floor\" kick patter, wide percussive elements and shimmering open hats. The final, third version is crushed, distorted and heavy as it consists of very loud kick punches.", "audio": "/zhanghaomin/datas/musiccap/music_data/2f1UXGix_Cw.wav"} +{"id": "2f7NnTVQzR0", "caption": "The low quality recording features a cover of a pop song. It is sung by passionate female vocalists over pop instrumental playing in the background. It is noisy and it sounds roomy as it is probably recorded with a phone or a camera microphone, but it is also emotional, passionate and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/2f7NnTVQzR0.wav"} +{"id": "2gc1L3g1itU", "caption": "This audio contains someone playing blues on an e-piano. This audio is in poor audio quality, you can hear white noise from the recording. This song may be playing piano at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/2gc1L3g1itU.wav"} +{"id": "2gvyOxKuQPY", "caption": "The song is an instrumental. The tempo is medium, featuring a drum solo with no other instrumentation, featuring a lot of stops, cymbals crashes and drum rolls. The song serves as a dance track for a group of dancers. The audio quality is deteriorated and generally poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/2gvyOxKuQPY.wav"} +{"id": "2hgvuYGc95o", "caption": "The low quality recording features a beatboxing over harmonica solo melody. It sounds groovy and the recording is groovy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/2hgvuYGc95o.wav"} +{"id": "2i4UNf8tjvU", "caption": "This folk song features a male voice singing the main melody in a southern accent. The voice falls in the bass category. This is accompanied by an acoustic guitar strumming chords. The recording is of low quality and there is a lot of white noise drowning the other sounds. A basic percussion instrument is played. The voice is emotional. This song can be played in a retro style movie where a family goes to meet their grandparents out in the countryside.", "audio": "/zhanghaomin/datas/musiccap/music_data/2i4UNf8tjvU.wav"} +{"id": "2iFgXSXdqLo", "caption": "This clip features some heavy and overdriven solo electric guitar playing. The phrases are energetic, gritty and full of rock flavour. You'd hear this kind of playing at a rock concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/2iFgXSXdqLo.wav"} +{"id": "2juYRZnhF3g", "caption": "Two voices can be heard singing a Christmas song accompanied by a piano or guitar playing along chords. The sounds seem to come out of a box rather than being sung live. The recording is of very poor audio quality. This song may be playing at Christmas time.", "audio": "/zhanghaomin/datas/musiccap/music_data/2juYRZnhF3g.wav"} +{"id": "2kORDnISun4", "caption": "A choral harmony consisting of four parts sings this ethereal harmony. The song is medium tempo with a church organ and orchestra accompaniment. The song is heavenly and innocent. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/2kORDnISun4.wav"} +{"id": "2kY_ZG78V-g", "caption": "This is low quality audio and all instruments are not heard clearly. The main melody is played on a marimba. This is accompanied by a timpani. Another drum set is used to play percussion with the focus on the snare and hi-hat. After the marimbas pause, one marimba plays a soft melody. This song does not feature any vocals. This song can be played in a fantasy sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/2kY_ZG78V-g.wav"} +{"id": "2kcSUBkFbaQ", "caption": "The Low Quality Hip Hop song features a dry, flat male vocal rapping over punchy kick layered with shimmering open hats, punchy kick, simple hi hats, claps, syncopated snare hits, wide arpeggiated synth melody and stuttering synth chords. It sounds energetic and kind of unnatural, since the vocal is so detached from the instrumental due to the bad mixing of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/2kcSUBkFbaQ.wav"} +{"id": "2lBZ6yPW9WU", "caption": "The low quality, noisy recording features a wooden rubbing sound effect, followed by a short exhale blow. The recording has wide natural sounds, including birds chirping, as it was recorded outdoors.", "audio": "/zhanghaomin/datas/musiccap/music_data/2lBZ6yPW9WU.wav"} +{"id": "2nsZhXxes68", "caption": "An acoustic drum is playing a groove with crash hits and a double-bass drum along with the e-bass and an e-guitar playing bass notes along with the complex kickdrum. A oriental sounding string and brass-section is playing a melody. The male voice sounds very aggressive, screaming with full force. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/2nsZhXxes68.wav"} +{"id": "2o1p83UjJFA", "caption": "This is the live performance of an orchestral rock piece. There is a male vocalist singing melodically in the lead. The piano is gently playing the main tune of the song. The tempo of the piece is slow. There is a profound, melancholic atmosphere. This piece could be used in the soundtrack of a drama movie/TV series. It could also be playing in the background at a rock/metal bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/2o1p83UjJFA.wav"} +{"id": "2pTnwe3DzCs", "caption": "This is the recording of a keyboard lesson. There is a male instructor that plays the notes on the keyboard first and then describes the placement of the fingers and the notes that are being played. The audio quality of the lesson is not that great.", "audio": "/zhanghaomin/datas/musiccap/music_data/2pTnwe3DzCs.wav"} +{"id": "2qO-OQtOBK0", "caption": "This is a percussion music piece. There is a medium pitched conga sound providing the rhythm. Clicking sounds related to a video game can be heard. Parts of this piece are suitable for a video game.soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/2qO-OQtOBK0.wav"} +{"id": "2sIfE3KOi5s", "caption": "This music is instrumental. The tempo is fast with trumpet harmony, keyboard accompaniment, infectious drumming, syncopated, funky bass lines, lively piano and electric and acoustic guitar riffs. The music is upbeat, groovy, complex harmony, ambient, soulful and funky. This song is Funk Soul;", "audio": "/zhanghaomin/datas/musiccap/music_data/2sIfE3KOi5s.wav"} +{"id": "2uagA3ujRtM", "caption": "This clip features purring sounds as the main sound. This is accompanied by violins playing a lullaby melody in the background. The sounds of crickets chirping are also played in the background. This clip does not contain any voices or any other musical instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/2uagA3ujRtM.wav"} +{"id": "2umjh27MkjU", "caption": "This song features a male voice singing the main melody. This is accompanied by other male voices singing backing vocals in harmony. The bass plays the root notes of the chords. A synth plays a melody similar to the backing voices and continues to play even when the main voice sings. The synth has an accordion voice. This is accompanied by programmed percussion playing a Latin dance beat. The mood of this song is romantic. This song can be played in a dance party.", "audio": "/zhanghaomin/datas/musiccap/music_data/2umjh27MkjU.wav"} +{"id": "2unse6chkMU", "caption": "This is a piece that would be suitable as calming study music or music for sleeping. It features a relaxing and soothing motif on the piano, being backed by a distant, high pitched and sustained violin.", "audio": "/zhanghaomin/datas/musiccap/music_data/2unse6chkMU.wav"} +{"id": "2uvHgwAljPA", "caption": "The song is an instrumental. The song is medium tempo with a groovy drum rhythm, vinyl disc scratching tones and a percussive bass line. The song is energetic and groovy. The audio quality is very poor with a lot of hissing noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/2uvHgwAljPA.wav"} +{"id": "2vQTq4QLP8U", "caption": "This is a eurodance/latin dance music piece. The words are sung in the Spanish language by a female vocalist in a seductive manner. The main theme is played by the accordion while elements such as the keyboard and the bass guitar make up the melodic background. The rhythmic background consists of a basic 4/4 electronic drum beat and latin percussive elements. There is a sensual and erotic feel to this piece. It could be playing at latin dance nights at dance clubs. It could also work well as an accompaniment piece at a latin dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/2vQTq4QLP8U.wav"} +{"id": "2wGkbHl3IUE", "caption": "The low quality recording features a bagpipes melody playing while a dog is howling. It sounds emotional and passionate, even though the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/2wGkbHl3IUE.wav"} +{"id": "2wZCoeq9Ppc", "caption": "The low quality recording features a harmonizing woodwinds melody playing. The recording is noisy, in mono and it sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/2wZCoeq9Ppc.wav"} +{"id": "2x4694ExyCU", "caption": "The low quality recording features an electro song that consists of a widely spread stuttering synth melody, buzzy synth bass and distorted electric guitar melody. It sounds distorted, loud, suspenseful and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/2x4694ExyCU.wav"} +{"id": "2x9735gU01s", "caption": "The low quality recording features an arpeggiated acoustic guitar. It sounds mellow, soft, emotional and sad.", "audio": "/zhanghaomin/datas/musiccap/music_data/2x9735gU01s.wav"} +{"id": "2xATintzaj4", "caption": "The song is an instrumental. The song is medium tempo with an electric guitar playing chords and strumming rhythm with no other instrumentation. The song is emotional and interesting. The song is probably a demo of a guitar or guitar amplifier. The audio is average quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/2xATintzaj4.wav"} +{"id": "2xGRCsW6-Bk", "caption": "The low quality recording features a Champeta song that consists of wooden percussive elements, electric guitar solo melody, funky electric rhythm guitar chords, shimmering shakers and hi hats and smooth bass guitar. It sounds funky and like something you would dance to in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/2xGRCsW6-Bk.wav"} +{"id": "2xQuWif8axE", "caption": "This is a live recording of an instrumental progressive metal piece. A solo is being played on the electric guitar at a very fast pace using the technique of shredding. Rapid jumps from medium to high range notes can be heard. The atmosphere is aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/2xQuWif8axE.wav"} +{"id": "2xtOqrNKH5s", "caption": "This song is an electronic instrumental. The tempo is fast with booming bass lines, synthesiser arrangement, table turner and digital drums. The music is vibrant, upbeat, pulsating, loud, punchy, buoyant, youthful and has a dance groove. This music is EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/2xtOqrNKH5s.wav"} +{"id": "2y1QnNBaxAU", "caption": "This is an emotional, melodic piano piece. It brings about sombre and reflective feelings. It has a slow tempo, and it is not intricate but it is captivating. The empty spaces between the motifs allows for thoughts to flow.", "audio": "/zhanghaomin/datas/musiccap/music_data/2y1QnNBaxAU.wav"} +{"id": "2z1elo4ucis", "caption": "This is an amateur recording of a latin dance music piece. The audio quality is not that great. There is a male vocalist singing loudly. A bass guitar is playing a groovy bass line while an electric guitar is strumming chords in a syncopated manner. The rhythmic background is provided by a barely heard latin acoustic drum beat. The atmosphere is cheerful. This piece could be sampled for use in the making of a latin influenced hip-hop beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/2z1elo4ucis.wav"} +{"id": "2zjtZYqg3Ow", "caption": "The Drum & Bass song features wide piano chords layered with wide synth pad chords, followed by echoing vocal melody at the beginning, double pedal kick, punchy snare and manically played hi hats. Right before the beat drops, there is a wide reverberant riser that lifts the energy of the track, preparing the listener for it. It sounds energetic, uptempo and manic - like something you would hear on commercials.", "audio": "/zhanghaomin/datas/musiccap/music_data/2zjtZYqg3Ow.wav"} +{"id": "2zo5z1I0CeM", "caption": "This pop song is sung by a female children's choir. The voices are soprano and alto. The soprano voice sings high pitch notes in vocals. The alto voices sing the words in parts. This is accompanied by the bass playing the root notes of the chords. A piano plays arpeggiated chords. The mood of this song is sad. This song can be played in a movie scene about reminiscing the past.", "audio": "/zhanghaomin/datas/musiccap/music_data/2zo5z1I0CeM.wav"} +{"id": "2zpITTJiw7Q", "caption": "This low quality audio features a melody played on the piano. This is followed by a melody on two different synth voices. This is accompanied by percussion playing a simple melody. The bass plays the root notes of the chords. The other instruments are not clearly heard because of the low quality of audio. There are no voices in this song. This song can be played in an anime video.", "audio": "/zhanghaomin/datas/musiccap/music_data/2zpITTJiw7Q.wav"} +{"id": "2zrPFxxT1VM", "caption": "This song starts with a male narrator speaking a line. This is followed by a female voice singing the main melody and each line is repeated by male and female voices. This song has a repetitive melody. This song has a call and response pattern. This is accompanied by an acoustic guitar playing chords and riffs at the end of lines. The percussion is played on a tabla. This song has a religious chant feel. This song can be played in a religious gathering.", "audio": "/zhanghaomin/datas/musiccap/music_data/2zrPFxxT1VM.wav"} +{"id": "3-_QS346VWo", "caption": "This is a new-age music piece. There is no singer in this piece. The acoustic guitar is playing the main melody. The piano is playing the chords of the piece while in the background a faint synth string sound can be heard. The atmosphere is relaxing and soothing. This piece would make the perfect background music for a meditation video. It could also be playing in the background at a spa or a wellness center.", "audio": "/zhanghaomin/datas/musiccap/music_data/3-_QS346VWo.wav"} +{"id": "30tNWUyJCog", "caption": "This reggae song features a male voice singing the main melody. The vocal melody is repetitive. This is accompanied by programmed percussion playing a reggae beat. Hand claps are played at regular intervals. The bass plays a groovy bassline. A saxophone plays fills in between lines. This song has a reggae feel. This song can be played in a Caribbean style party.", "audio": "/zhanghaomin/datas/musiccap/music_data/30tNWUyJCog.wav"} +{"id": "31DNFoW3NAw", "caption": "A keyboard is playing chords with a string sound along with something that sounds like a cembalo or another keyboard playing chords and a melody in the mid to higher register. A male voice is singing in an upper key sounding soulful and sensitive. This song may be playing for a sensual music video.", "audio": "/zhanghaomin/datas/musiccap/music_data/31DNFoW3NAw.wav"} +{"id": "31O2j4aAgYU", "caption": "This song features an electric guitar. The guitar plays a blues progression by first descending three chords and then ending the song on a higher register. The guitar tone has a lot of added reverb. There are no other instruments in this audio. This is an instrumental song with no voices.", "audio": "/zhanghaomin/datas/musiccap/music_data/31O2j4aAgYU.wav"} +{"id": "31iD2VPLMxQ", "caption": "The song is an instrumental. The tempo is slow with a poignant violin solo, keyboard accompaniment, percussion drums, strong bass line and a guitar accompaniment. The song is emotional and has a sense of grief and awe. The song is a documentary soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/31iD2VPLMxQ.wav"} +{"id": "32C6w8V7TX8", "caption": "The pop music features a female voice singing and being accompanied by other female voices. The drums and bass guitar play a simple and repetitive groove and drive the pulsation of the music. An electric guitar is playing a funky accompaniment. A group of strings play a repetitive melody that ascends in pitch with each repetition.", "audio": "/zhanghaomin/datas/musiccap/music_data/32C6w8V7TX8.wav"} +{"id": "32iayLTRmxg", "caption": "This song contains a digital drum with a soft subbass. A male voice is rapping along to a repeating male and also female voice sample. The male voice sample uses a harmonizer effect. A riser is preparing the next part of the song. A metallophone/marimba melody is repeating itself through the duration of the whole song. This song may be playing in an urban bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/32iayLTRmxg.wav"} +{"id": "338iZ76huSQ", "caption": "This new age song features a guitar solo being played. This is accompanied by a tabla on the percussion. The bass plays the root notes of the chord with no flourishes and embellishments. An angelic voice sings vocables in the background. The voice does not sing any lyrics. The mood of this song is relaxing. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/338iZ76huSQ.wav"} +{"id": "33LJ36nAozM", "caption": "A handicapped musician plays the guitar with his feet and sings and jokes about. The song is medium tempo and retro pop with just a guitar strumming and no other instrumentation. The song is inspiring and relaxing. The song audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/33LJ36nAozM.wav"} +{"id": "33dCbb1MyYU", "caption": "A female vocalist sings this spirited pop. The tempo is fast with a spirited, upbeat acoustic guitar accompaniment, synthesiser arrangements, slick drumming, digital drum rhythm, boomy bass drop , added reverb and auto tune for better effects.The song is young, fresh, upbeat, bouncy, punchy, and has a dance groove.this song is a synth pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/33dCbb1MyYU.wav"} +{"id": "35b9UHjagaI", "caption": "This is a TV series theme. It is an instrumental piece. There is a melody being played on an acoustic guitar. There are various percussive elements in this piece. The piece is mostly rhythmic and there is an eccentric feel to it. This piece could be used as an accompaniment piece in a latin dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/35b9UHjagaI.wav"} +{"id": "36ToDxW_hns", "caption": "The low quality recording features a cover of a rock and it consists of passionately played solo acoustic guitar melody over staccato strings melody playing in the background on playback. Even though the recording is noisy, it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/36ToDxW_hns.wav"} +{"id": "374R7te0ra0", "caption": "The Hip Hop song features a flat male vocal rapping over repetitive, echoing piano melody, claps and punchy kick hits. At the very beginning of the loop, there are stuttering hi hats, sustained synth bass and filtered, pitched up female chant playing. It sounds groovy and addictive - thanks to the way rappers are rapping.", "audio": "/zhanghaomin/datas/musiccap/music_data/374R7te0ra0.wav"} +{"id": "38R9Vnwt890", "caption": "The music features an orchestra playing a fast tempo piece. Since the song is purely instrumental there is no voice singing. The trombones and the trumpets stand out the most. The music is epic and can work pretty well for a movie, especially a chasing scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/38R9Vnwt890.wav"} +{"id": "390At7lW4iw", "caption": "Mostly ambient sounds of a rotary phone ringing and someone picking up the phone. In the background there is an ethereal sounding high, gliding synth melody and muffled autotuned vocals. Sounds like an intro to a hip hop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/390At7lW4iw.wav"} +{"id": "39MksqVeLdY", "caption": "The low quality recording features a live performance where a DJ is playing his set. There are crowd noises in the background. The recording is noisy and it sounds manic, aggressive, distorted and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/39MksqVeLdY.wav"} +{"id": "3B-YYTbpFZE", "caption": "The low quality recording features a flat male vocal narrating over flame sounds and wooden surface scratching sounds, after which there is a cut to a shimmering shaker and wooden percussion playing. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/3B-YYTbpFZE.wav"} +{"id": "3C-5_z01Olc", "caption": "This is an indie rock music piece. There is a male vocalist singing melodically in the lead. There is an electric guitar playing a simple tune with a strong reverb effect. The bass guitar is playing the root notes. The rhythmic background consists of a basic acoustic drum beat. The atmosphere is easygoing. This piece could be used in the soundtrack of a teenage drama TV series as the opening theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/3C-5_z01Olc.wav"} +{"id": "3ClbaJYWVO4", "caption": "This is a gear showcase jam. There is a clean sounding electric guitar with an echo effect being played in a gentle manner. The recording has a dreamy, trippy atmosphere. Parts of this recording can be lifted as samples to be used in beat-making. An advertisement jingle could also be derived from this piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/3ClbaJYWVO4.wav"} +{"id": "3EXXs3x4Ius", "caption": "The low quality recording features a children's song that consists of a flat male vocal singing over groovy piano melody, simple bass, simple hi hats, punchy snare, soft kick hits, synth lead melody, electric guitar melody and bells melody. It sounds happy, fun and joyful - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/3EXXs3x4Ius.wav"} +{"id": "3EtbIWF_ynU", "caption": "The low quality recording features a plucked arpeggiated Zheng melody. The recording is in mono and it is noisy and it gives off sentimental vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/3EtbIWF_ynU.wav"} +{"id": "3FJFcgaa0oE", "caption": "This funk song features a male voice singing the main melody. The melody is repetitive. This is accompanied by percussion that does not play any cymbals. A trumpet plays a repetitive melody of staccato notes. There are other quirky instruments playing in the background adding to the percussion. The mood of this song is upbeat. This song can be played in a bank robbery movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/3FJFcgaa0oE.wav"} +{"id": "3Gyi7AvDLzc", "caption": "A male vocalist sings an animated song. The song is fast tempo with acoustic guitar, mandolin and resonator rhythms, cello accompaniment and vocal backup. The audio quality is inferior and muddled making it almost impossible to understand the lyrics. The melody and instrumentation sounds like Country music.", "audio": "/zhanghaomin/datas/musiccap/music_data/3Gyi7AvDLzc.wav"} +{"id": "3HtfWSbmuAc", "caption": "Someone is playing a neo-soul chord progression on a fender rhodes piano with vibration tremolo effect. This song may be playing at a live concert opening the stage.", "audio": "/zhanghaomin/datas/musiccap/music_data/3HtfWSbmuAc.wav"} +{"id": "3IYd8cCmUkQ", "caption": "The low quality recording features a R&B song that consists of passionate male vocals, alongside background harmonizing male vocals, singing over tinny bells melody, synth strings melody, tinny high pitched synth lead melody, shimmering hi hats, gliding bass, punchy kick and claps. It sounds passionate and emotional, even though the mix of the song is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/3IYd8cCmUkQ.wav"} +{"id": "3JYQgXudiH8", "caption": "A digital drum is playing a groove that motivates to dance with a kick on every beat along with a shaker. Male backing voices are singing a melody in harmony and adlips that are panned to the right side of the speakers. A piano is playing a simple repeating melody and a soft bass sound is rounding the recording up. On top of that a male voice is singing phrases. This song may be playing at home dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/3JYQgXudiH8.wav"} +{"id": "3KQy3Cajo4E", "caption": "A male singer sings this popular country hit with backup singers in vocal harmony. The song is in medium tempo with a walking bass , acoustic guitar strumming rhythmically, autoharp accompaniment and steady drumming rhythm. The song is an emotional and nostalgic country hit. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/3KQy3Cajo4E.wav"} +{"id": "3KdyWJ6wTOw", "caption": "This song features a male voice rapping the lyrics. Female voices sing vocables in the background. This is accompanied by programmed percussion playing a trap beat. The bass plays a groovy bassline by sliding to notes rather than pausing in between notes. A synth plays a repetitive melody in the background. This song can be played in a gangster movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/3KdyWJ6wTOw.wav"} +{"id": "3NAqH9LYDyU", "caption": "This is a soca music piece. There is a male vocalist singing with autotune. A repeating hollering sample can be heard. The tune is being played by a melodic pad. The rhythm is provided by an electronic drum beat. The atmosphere is danceable. This piece could be playing in the background at a Caribbean nightclub.", "audio": "/zhanghaomin/datas/musiccap/music_data/3NAqH9LYDyU.wav"} +{"id": "3Nwsd439zmU", "caption": "The low quality recording features a live performance of a folk song and it consists of harmonica melodies played over groovy double bass and shimmering hi-hats. The recording is noisy and fairly wide.", "audio": "/zhanghaomin/datas/musiccap/music_data/3Nwsd439zmU.wav"} +{"id": "3OLeJZF4oI0", "caption": "This guitar instruction audio features an acoustic guitar. This starts off with a male voice giving instructions on how to play the guitar. The bass note is played on the open string and the chord is strummed once. This is the Hendrix chord being played on the acoustic guitar. There are no other instruments in this song. There is no vocal melody in this song. This audio can be used in a guitar instruction video.", "audio": "/zhanghaomin/datas/musiccap/music_data/3OLeJZF4oI0.wav"} +{"id": "3OUNEL8XaR0", "caption": "This music is a soothing instrumental. The tempo is slow with a beautiful violin symphony, romantic piano accompaniment, harp melody, a wind instrument and shakers. The music is mellifluous, gentle,pensive, nostalgic, poignant, melancholic,\nromantic, enthralling, enigmatic, dreamy, calming and ethereal.", "audio": "/zhanghaomin/datas/musiccap/music_data/3OUNEL8XaR0.wav"} +{"id": "3OWArQGgmm0", "caption": "The low quality recording features an electric guitar melody, with echoing wobble effect on, that occasionally distorts. It sounds like the player is trying out an effect for his guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/3OWArQGgmm0.wav"} +{"id": "3PoC1-xd4Yw", "caption": "This song features a synth playing the rhythm section using a piano tone. The shofar plays a tremulous note. There is no percussion in this song. The mood of this song is melancholic. There are no other instruments in this song. There is no voice in this song. This song can be used in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/3PoC1-xd4Yw.wav"} +{"id": "3PuzzYmTDA4", "caption": "The low quality recording features a classical song that consists of a soft wide strings melody, followed by mellow woodwinds melody and low brass melody. There is a short snippet of a cymbal riser at the very end of the loop. It sounds passionate, emotional and suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/3PuzzYmTDA4.wav"} +{"id": "3PwR0D7CuwM", "caption": "The low quality recording features a wide harpsichord melody. It sounds passionate, emotional and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/3PwR0D7CuwM.wav"} +{"id": "3QNFY4MKTy4", "caption": "This is a Hungarian pop music piece. There is a female vocalist singing melodically. The main tune is being played by a piano while there is a bass guitar playing in the background. A slow tempo acoustic drum beat provides the rhythm. The atmosphere is emotional. This piece could be used in the soundtrack of a romance/drama movie that takes place in Hungary.", "audio": "/zhanghaomin/datas/musiccap/music_data/3QNFY4MKTy4.wav"} +{"id": "3QqVP0odOw4", "caption": "The low quality recording features a commercial music that consists of a funny processed male vocal, after which there is a harmonizing female vocal singing over punchy kick, brass melody, wooden percussion and echoing brass melody. It sounds addictive - like every commercial music should sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/3QqVP0odOw4.wav"} +{"id": "3R8xDvhJk54", "caption": "The low quality recording features a tutorial on how to tune an acoustic guitar, string by string. The recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/3R8xDvhJk54.wav"} +{"id": "3TO4C7SiC7I", "caption": "A female voice or voices is/are singing loud and in a high register with a lot of quarter and half steps. The voices are full or reverb. They are accompanied by dry percussion playing a counter rhythm. A pad sound, rich in harmonies, is underlining the song with long chords that are being played in the mid to lower register. This song may be playing while meditating.", "audio": "/zhanghaomin/datas/musiccap/music_data/3TO4C7SiC7I.wav"} +{"id": "3TP1itJqv-E", "caption": "Harsh, grating sound of a solo bagpipe with audience sounds in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/3TP1itJqv-E.wav"} +{"id": "3TQmts_MxyQ", "caption": "This is an instrumental backing track of a jazz music piece. There is no singer in this version of the piece. The piano is playing the chords in the minor key while a bass guitar can be heard playing a walking bass line. The rhythmic background consists of acoustic drums playing a jazz swing beat. The atmosphere is delicate. This piece could be playing in the background at a coffee shop. It could be used in the soundtrack of a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/3TQmts_MxyQ.wav"} +{"id": "3UHHjbO0ThM", "caption": "This audio contains an acoustic drum set playing fast snare rolls and then adding in a kick on every beat along with some crash hits. A synthesizer is playing a fast lead melody in the upper register. Then the song breaks into the next part and a brass/string section is playing a melody changing note on every beat together with the kick. This song may be playing for a fast paced video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/3UHHjbO0ThM.wav"} +{"id": "3VEMHWnewuc", "caption": "This song is an instrumental. The tempo is fast with an enthusiastic acoustic guitar melody, keyboard accompaniment and a mellifluous female vocalisation with choral harmony. The music is rhythmic, youthful, simple,beautiful, charming, soothing, pleasant, charming, and tranquil.", "audio": "/zhanghaomin/datas/musiccap/music_data/3VEMHWnewuc.wav"} +{"id": "3VTinB14Pmw", "caption": "The low quality recording features an ambient scraping synth lead playing. It sounds muddy, muffled, but also spacey and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/3VTinB14Pmw.wav"} +{"id": "3Wdxjm-h36w", "caption": "This song contains a synth melody that sounds a little in the background slowly coming more into focus. This sound is full of reverb. Other synth sounds are playing pads and experimental pluck sounds. A glass sound is being played as a hi hat and a noise snare sound takes a lot of space with sounds panned to the left and right side of the speakers. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/3Wdxjm-h36w.wav"} +{"id": "3XL825fK6UM", "caption": "This clip is a vocalisation of the Om Mantra. The tempo is slow with a droning melody and repetitive chanting of the word Om. It is meditative, calming, soothing, spiritual, lulling, hypnotic and trance like. This is Mantra Meditation music.", "audio": "/zhanghaomin/datas/musiccap/music_data/3XL825fK6UM.wav"} +{"id": "3XRjrSOVBnQ", "caption": "This song contains a male voice talking over a synth drone pad along to some soft sounding kick hits and a simple synth arpeggio. Then the recording stops and a new one rises with a drum stick sound and a e-bass sliding up in pitch. This song may be playing in a wildlife documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/3XRjrSOVBnQ.wav"} +{"id": "3XeMR8lX0dg", "caption": "A cappella choir is singing a melody with a deep male bass voice. Midrange female and male singers and high female voices. Then two female voices start singing two different arpeggio-melodies. The voices are spread across the left and right speaker. You can hear the sound of water. This song may be playing in a live presentation.", "audio": "/zhanghaomin/datas/musiccap/music_data/3XeMR8lX0dg.wav"} +{"id": "3Xoz87_SUdw", "caption": "The low quality recording features a flat male vocal speaking over suspenseful orchestra music. It sounds intense and dramatic and as soon as the male vocal stops speaking, the volume of the music goes up - which makes it dynamic overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/3Xoz87_SUdw.wav"} +{"id": "3Yc7_n6mDsI", "caption": "The low quality recording features a drum solo that consists of punchy snare hits and occasional snare roll, punchy kick and shimmering hi-hats. It sounds energetic and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/3Yc7_n6mDsI.wav"} +{"id": "3YuO2UOYKRk", "caption": "A digital drum is playing a groove along with a stabbing synth sound. They have some fast repeating pattern effect that gives the composition more rhythmic elements along with a loud long and noisy snare sound. The digital bass sounds liquid and synth-pads are swelling up slowly coming into focus. This song may be playing in a lock and pop dance battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/3YuO2UOYKRk.wav"} +{"id": "3Z74i_FWs3o", "caption": "This is a shuffle music piece. It opens with a dissolving sound effect that signals that a drop is about to start. The dialing sound effects of a buttoned telephone can be heard. It mostly consists of electronic sounds that could be influenced by drum & bass.", "audio": "/zhanghaomin/datas/musiccap/music_data/3Z74i_FWs3o.wav"} +{"id": "3ZhyXbwFQAM", "caption": "The low quality recording features a wide punchy toms, wide aggressive electric guitars, sustained synth lead, distorted filtered bass and tinny hi hats. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/3ZhyXbwFQAM.wav"} +{"id": "3ZyuBJEbmJM", "caption": "A sparse house music beat with just drums. The kick plays a four on the floor pattern, while the hi-hats play on the off beats and the bass part plays a syncopated dotted rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/3ZyuBJEbmJM.wav"} +{"id": "3_M9ZMo5TiU", "caption": "Someone is playing a long high pitched note that is rising up in pitch and is leaving a kick-like sound while repeating itself. This sound may be playing at home testing out a synthesizer and its possibilities.", "audio": "/zhanghaomin/datas/musiccap/music_data/3_M9ZMo5TiU.wav"} +{"id": "3b3s0TvjGwA", "caption": "A drone sound is playing in the lower to mid range as an intro before the song starts with a high pitched bell sound with a very long release time and acoustic drums that sounds like playing behind a closed door. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/3b3s0TvjGwA.wav"} +{"id": "3bg0iy-ypcw", "caption": "The Hip Hip songs live performance consists of repetitive male vocal singing over repetitive piano melody, smooth bass, shimmering hi hats and soft kick and snare hits. It sounds jazzy and warm.", "audio": "/zhanghaomin/datas/musiccap/music_data/3bg0iy-ypcw.wav"} +{"id": "3cEQfNZ_F1w", "caption": "This is a jazzy instrumental that sounds upbeat, cheery and vibrant. This would be suitable for some swing dancing. It's got an electric guitarist playing licks, a punchy piano, and groovy intricate drum pattern. The piece is in four over four time signature.", "audio": "/zhanghaomin/datas/musiccap/music_data/3cEQfNZ_F1w.wav"} +{"id": "3dUo62RsD00", "caption": "This song is a hard rock instrumental. The tempo is fast with bright electric guitars playing lead, steady bass line, punchy drumming and upbeat keyboard harmony The music is energetic, upbeat, youthful, engaging, buoyant, peppy, and groovy.it is a crowd pleaser ,as clapping, cheering , chatter and hooting can be heard in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/3dUo62RsD00.wav"} +{"id": "3dzR3ZWOe8Y", "caption": "This song contains acoustic drums playing a complex rhythm along with a e-bass playing a walking bassline and a piano playing jazz chords in the mid range. A baritone saxophone is playing the main melody accompanied by other brass instruments. This song may be playing during a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/3dzR3ZWOe8Y.wav"} +{"id": "3e6GleQ9sl0", "caption": "This song contains someone playing a gentle and warm sounding melody on a violin accompanied by a harp. This song may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/3e6GleQ9sl0.wav"} +{"id": "3fqWosszpnE", "caption": "A male vocalist sings this upbeat pop song. The tempo is medium fast with thumping drum beats, percussion instruments, ukulele melody, keyboard accompaniment and rhythmic guitar. The audio is muddled making it difficult to hear the finer elements of the song. The song is energetic, enthusiastic, happy, fresh, peppy, perky , groovy. There is background chatter, clapping, cheering and rustling. The song is a Pop Rock/Alternative Indie.", "audio": "/zhanghaomin/datas/musiccap/music_data/3fqWosszpnE.wav"} +{"id": "3gh1oldZ7Zc", "caption": "This song features a female voice singing the main melody. This is accompanied by a guitar playing arpeggiated chords. A wind instrument plays fills in between lines. There is no percussion in this song. This song has a romantic mood. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/3gh1oldZ7Zc.wav"} +{"id": "3jLef5eHgzU", "caption": "This audio contains someone playing a distorted e-guitar solo in a higher register along with acoustic drums with cymbal hits and a half open hit. An e-bass is underlining the rhythm. There are digital comedic noises and laughter that seem not to be part of the musical composition. This song may be playing in a comedic tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/3jLef5eHgzU.wav"} +{"id": "3kSQNjfJnN8", "caption": "The song is an instrumental. The song is slow tempo with a Chinese string instrument playing a lilting melody along with tones of the string instrument being plucked like a harp. The song is emotional and melancholic. The song is a live performance with ambient room noise and generally poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/3kSQNjfJnN8.wav"} +{"id": "3kXukXBvDQQ", "caption": "This song is a lively Indian instrumental. The tempo is fast with lively brass bands playing harmony, energetic drums ,Nagpada and dhol and other Indian percussion and synthesiser with digital arrangements. There is a dialogue of a man and woman superimposed over the music, with sighing and giggling in the background. The music is typical Indian Baarat music. It is happy, cheerful, vivacious, energetic, youthful, vigorous and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/3kXukXBvDQQ.wav"} +{"id": "3m-a805cVl0", "caption": "The low quality recording features a simple acoustic guitar melody. It sounds like a tutorial and it gives off happy and fun vibes. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/3m-a805cVl0.wav"} +{"id": "3m4QSVVBMss", "caption": "The low quality recording features a pop song that consists of seductive female vocal singing over arpeggiated synth lead melody, pulsating synth keys, sustained synth melody, punchy kick, claps, simple hi hats and groovy bass that glues everything together. It sounds a bit muffled, probably because of the quality of the mix.", "audio": "/zhanghaomin/datas/musiccap/music_data/3m4QSVVBMss.wav"} +{"id": "3mNOJpN_qOQ", "caption": "An acoustic guitar is playing single notes of a minor chord progression alongside an acoustic piano playing a melody on itself. Then a string-section comes in for a moment elevating the emotional piece giving it a beauty and soft sadness. The instruments are slightly panned to the left and right side of the speakers. The female voice is softly singing with a little bit of reverb on her voice. This song may be playing at a theater-performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/3mNOJpN_qOQ.wav"} +{"id": "3mStyfCbL68", "caption": "The drum is playing a four on the floor groove with little fill-ins on the snare crash. A synthesizer is playing a 2000s pad sounding lead melody. The distorted e-guitar that is playing underlining the melody with some long sounding chords. This song may be played at an event to animate and pump up the people.", "audio": "/zhanghaomin/datas/musiccap/music_data/3mStyfCbL68.wav"} +{"id": "3nbB3F-OdSM", "caption": "A male vocalist sings this vigorous Rock song. The tempo is fast with enthusiastic electric guitar lead and harmonies, electric bass guitar and hard hitting drumming with cymbal rides. The song is passionate, youthful, enthusiastic, intense, compelling, boisterous and vigorous. This song is a Hard Rock/Heavy Metal song.", "audio": "/zhanghaomin/datas/musiccap/music_data/3nbB3F-OdSM.wav"} +{"id": "3nfiGGQykxk", "caption": "This audio contains a shofar horn getting blown in a higher register. The high tone is loud and drops in pitch at the end. This song may be playing live in a village calling for a traditional ceremony.", "audio": "/zhanghaomin/datas/musiccap/music_data/3nfiGGQykxk.wav"} +{"id": "3noh9LiQNrs", "caption": "This is the recording of a guitar lesson. The instructor at first plays the chords on a clean sounding electric guitar and then describes the nature of the chord that he is playing. The chords that were strummed could be used as clean electric guitar samples in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/3noh9LiQNrs.wav"} +{"id": "3obJKn19jTE", "caption": "This is a grunge rock music piece. A distorted electric guitar playing power chords leads the tune with a bass guitar in the background. Loud acoustic drums provide the rhythmic background while also playing a lot of fills. There is also a male vocal. The music has a rebellious atmosphere mixed with a rough sound that is characteristic of the grunge scene. This piece could be used as a soundtrack in college drama movies/TV series. It could also be used in advertisements targeted at teenagers.", "audio": "/zhanghaomin/datas/musiccap/music_data/3obJKn19jTE.wav"} +{"id": "3otUlQ4wvLY", "caption": "This amateur recording features a male voice. This is accompanied by an electric guitar. The notes of the chords are first plucked and the chord is struck once. There is no percussion and no other instruments in this song. This is a slow tempo song. The mood of this song is romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/3otUlQ4wvLY.wav"} +{"id": "3pU34vUoO9g", "caption": "This religious song features the main melody first sung by male voices in harmony followed by female voices in harmony. The voices sing in a hall environment giving a reverb effect. There are no instruments in this song. This song gives a holy feel. This song can be played in a church.", "audio": "/zhanghaomin/datas/musiccap/music_data/3pU34vUoO9g.wav"} +{"id": "3q9K2PgA2-U", "caption": "This is a live performance of a polka music piece. It is being performed by a wind orchestra. The main melody is being performed by the tuba. There is a lively, cheerful atmosphere to this piece. It could be used as an accompaniment piece for a European folk dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/3q9K2PgA2-U.wav"} +{"id": "3rbWoeUg9yo", "caption": "The low quality recording features a regional Mexican song that consists of harmonizing male vocals singing over wide, bouncy wooden percussion, wide acoustic rhythm guitar, groovy bass, punchy kick and strings melody. It sounds passionate, energetic and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/3rbWoeUg9yo.wav"} +{"id": "3rvqiSZB4pA", "caption": "This is an electronic funk/disco music piece from the 80s. There is a female vocalist singing melodically. The repeated main theme is being played by the keyboard. There is a synth bass playing a groovy bass line. There is an acoustic drum beat in the rhythmic background. The atmosphere is sensual. This piece can be used in the soundtrack of a retro-themed movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/3rvqiSZB4pA.wav"} +{"id": "3sIlpn9nvKU", "caption": "The rock music features a male voice singing a repeating melody and being backed by other male vocals. The electric guitar plays fast chords with a distortion effect on and the bass guitar follows with the same speed. The drums play a fast repeating rhythm. The quality of the audio is really low and so this leads me to believe this is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/3sIlpn9nvKU.wav"} +{"id": "3sRO6iwfUxo", "caption": "A digital drum is playing a simple groove along with a melodic short sample. A saxophone sample is playing a long note in the background. A male voice is rapping with a lot of energetic/aggressive energy. In the background you can hear a male voice shouting for a moment. This song may be playing in a car.", "audio": "/zhanghaomin/datas/musiccap/music_data/3sRO6iwfUxo.wav"} +{"id": "3tK7PpCo0PQ", "caption": "A male singer-songwriter accompanied by a strummed acoustic guitar and singing passionately a heartfelt folk song. The recording is somewhat low fidelity and live.", "audio": "/zhanghaomin/datas/musiccap/music_data/3tK7PpCo0PQ.wav"} +{"id": "3tSPMzvuQpk", "caption": "A male voice is singing a Christmas song supported by a piano playing chords. The audio is of poorer quality and seems to be coming out of a jukebox rather than being sung live. This song may be playing at Christmas time.", "audio": "/zhanghaomin/datas/musiccap/music_data/3tSPMzvuQpk.wav"} +{"id": "3tbFP_JKzXw", "caption": "The low quality recording features a harmonizing throaty male vocal singing over dissonant strings melody in the background. It sounds traditional and hopeful.", "audio": "/zhanghaomin/datas/musiccap/music_data/3tbFP_JKzXw.wav"} +{"id": "3tlaELkmRqs", "caption": "This song is an amateur recording of a person strumming an acoustic guitar. A group of adults and children sing the main melody using vocables and no lyrics. The melody is repetitive. There are no other instruments in this song. The song has a happy mood. This is a party song.", "audio": "/zhanghaomin/datas/musiccap/music_data/3tlaELkmRqs.wav"} +{"id": "3tyb0cXoX2g", "caption": "A male singer sings this high energy EDM. The tempo fast with the song starts with a slow female vocalisation, soft piano accompaniment and takes off to an upbeat groove. The song is groovy, youthful, buoyant, vivacious;punchy and vibrant with atmospheric synthesiser, hard hitting drumming, funky bass line, spirited electric guitar harmony along with enthusiastic vocals. The vocals are auto tuned and the use of heavy electronic instrumentation make it an ultimate EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/3tyb0cXoX2g.wav"} +{"id": "3u9OO9Og0Gc", "caption": "This is a live performance of an R&B music piece. There is a female vocalist singing melodically in the lead. Three female supporting vocals can be heard singing in the back. The melody is being played by the piano while the bass guitar plays a groovy bass line. The rhythm is provided by an acoustic drum beat. The atmosphere is sentimental. This piece can be used in the soundtrack of a romance movie involving a couple in a long distance relationship.", "audio": "/zhanghaomin/datas/musiccap/music_data/3u9OO9Og0Gc.wav"} +{"id": "3ujGrObyefA", "caption": "This music is instrumental. The tempo is fast with an upbeat keyboard harmony, bright drumming, energetic electric guitar and synthesiser and digital drum arrangements. There is an interaction between two men superimposed over the music. The music is lively, cheerful, happy, positive, upbeat, warm and heartening. This is the background score for an Interview or documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/3ujGrObyefA.wav"} +{"id": "3uz_ZrGsIaA", "caption": "The low quality recording features a clean electric guitar melody with a beautiful reverb effect on it. The recording is a bit noisy and in mono, and it sounds like a player is practicing his melodies.", "audio": "/zhanghaomin/datas/musiccap/music_data/3uz_ZrGsIaA.wav"} +{"id": "3vEsFxolnFs", "caption": "This clip is an instrumental with a female voice speaking. The tempo is medium with a banjo riff. This is a Banjo lesson on chord progression for country dance music. It is clear and crisp.", "audio": "/zhanghaomin/datas/musiccap/music_data/3vEsFxolnFs.wav"} +{"id": "3w3fD54bNvU", "caption": "The song is an instrumental. The song is medium tempo with a guitar playing lead and several guitarists playing harmony and accompaniment and a pick scratching guitar strings producing a percussive line. The song is immersive and has a classic country gun fight duel vibe to it. The song has ambient room noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/3w3fD54bNvU.wav"} +{"id": "3w4nFQrUQ8k", "caption": "This music is instrumental. The tempo is fast with atmospheric synthesiser, percussions like a boomy bass drum, enthusiastic steel pan and snare. The music is loud, resounding,intense, sinister, grim, suspenseful, burgeoning and boomy. This is a Percussion Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/3w4nFQrUQ8k.wav"} +{"id": "3w_LsKl-3Pk", "caption": "The low quality recording features a traditional song that consists of a passionate woodwind melody played over wooden percussive elements. It sounds soulful, passionate and emotional, even though the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/3w_LsKl-3Pk.wav"} +{"id": "3zIQTDfS4Hk", "caption": "The low quality recording features a tropical steel drum melody playing over background percussive instrumental. It is noisy, but it sounds tropical, exotic and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/3zIQTDfS4Hk.wav"} +{"id": "3zPvfVmL0nE", "caption": "This audio contains someone playing a drum with a big kick drum and snare sound playing cymbals along with a tambourine. In the background you can hear an electric organ playing long minor chords while a distorted e-guitar is playing a solo sounding as someone singing. This song may be playing live at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/3zPvfVmL0nE.wav"} +{"id": "3zT0aiN2E70", "caption": "This music is an upbeat instrumental. The tempo is fast with vigorous digital drumming, synthesiser arrangements and DJ mixer effects. The music is electrifying, pulsating, buoyant, punchy, groovy, youthful and high-spirited. This music is an outdoor live performance with ambient sounds. There are sounds of hysterical fans cheering, clapping and singing along. This music is Futuritic Electronic Pop/ Techno Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/3zT0aiN2E70.wav"} +{"id": "3zntWbS9XeI", "caption": "This audio clip features the end of an instrument with a lot of reverb. This additional reverb gives the ending an epic feel. At the end of the clip, a guitar chord is struck. There are no other instruments in this song. There are no voices in this song. This song can be used to promote a reverb pedal.", "audio": "/zhanghaomin/datas/musiccap/music_data/3zntWbS9XeI.wav"} +{"id": "4--05CAaDsg", "caption": "The song is an instrumental with a baby making noises while paddling in a pool. The song is medium tempo with steady drumming, latin percussion, guitar accompaniment, trumpets playing in harmony and keyboard accompaniment. The song is a soundtrack for a home video and the audio quality is bad due to varying noise levels.", "audio": "/zhanghaomin/datas/musiccap/music_data/4--05CAaDsg.wav"} +{"id": "40D4L5Ndi6k", "caption": "A male vocalist sings this animated song in a foreign language. The tempo is fast with a bright applied violin accompaniment, lively drumming, groovy bass line, tambourine beats, rhythmic mandolin and acoustic guitar accompany net. The song is lively, energetic, vibrant, happy, vivacious and merry with a dance groove. This song is a Folk Pop/Regional Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/40D4L5Ndi6k.wav"} +{"id": "40i3_JH6FYw", "caption": "This is a recording of an instrumental jam. There is a blues type solo being performed on an overdriven electric guitar. The guitar has an 80s sound. This recording could be sampled for use in beat-making or as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/40i3_JH6FYw.wav"} +{"id": "40kbMyL2Wgo", "caption": "This audio contains digital drums playing along to a male voice singing in a higher key while a synth bass sound and a lead sound are supporting the epic atmosphere. Then another male voice starts rapping with a lot of confidence and a little aggression in his voice. A male voice is providing backing vocals panned to both sides of the speakers. This song may be playing as a motivational mood enhancer.", "audio": "/zhanghaomin/datas/musiccap/music_data/40kbMyL2Wgo.wav"} +{"id": "40sAH2ZB0Pg", "caption": "Someone is playing an acoustic guitar strumming chords on the backbeat along with a banjo doing the same. A slide guitar is playing a melody along. An upright bass is playing a simple bassline. Two female voices are singing as a duo. The second one creates harmony in the higher register. This song is an amateur recording. This song may be playing at a local event.", "audio": "/zhanghaomin/datas/musiccap/music_data/40sAH2ZB0Pg.wav"} +{"id": "40vmsGsFBsw", "caption": "The song is an instrumental. The song is medium tempo with a string section accompaniment, timpani playing and other percussion instruments. There are other funny sounds like ball bouncing and other percussion tones. The song is an ad jingle soundtrack. The audio track is of poor quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/40vmsGsFBsw.wav"} +{"id": "40xkia7fwEM", "caption": "A male vocalist sings this mellow country song. The tempo is medium with fiddle, cello and viola harmony with acoustic guitar rhythm.The song is mellow, soft, dulcet,emotional , melancholic and nostalgic . This song is Country Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/40xkia7fwEM.wav"} +{"id": "42QgE4mM55I", "caption": "A background song is being played containing a female voice singing along to a synthesizer pluck melody and a digital drum with a big deep kick sound. Kids are singing along and laughing when a male voice starts singing along in a higher key. This song may be playing while enjoying time with your family.", "audio": "/zhanghaomin/datas/musiccap/music_data/42QgE4mM55I.wav"} +{"id": "42xehaGoJbc", "caption": "This is a live recording. The audio quality is poor. We hear a string section with layers of violins that are playing a motif which sounds exciting, suspenseful, and thrilling. It immediately gets you feeling on edge.", "audio": "/zhanghaomin/datas/musiccap/music_data/42xehaGoJbc.wav"} +{"id": "44sbWBFswUY", "caption": "Spirited Christmas music with a fast four on the floor dance beat. There is a high pitched 'chipmunk' style vocal singing a well-known tune accompanied by syncopated synth chord stabs, a drum machine and a drum fill.", "audio": "/zhanghaomin/datas/musiccap/music_data/44sbWBFswUY.wav"} +{"id": "45iNSkfzOwM", "caption": "The song is an instrumental. The tempo is medium with a piano accompaniment, music box tones and percussion tones with a metal grinding instrument making noise. The song is tense and anticipatory. The song is a soundtrack for a documentary film.", "audio": "/zhanghaomin/datas/musiccap/music_data/45iNSkfzOwM.wav"} +{"id": "46WpyRUqwXU", "caption": "The low quality recording features a pop song that contains a passionate female vocal, alongside wide harmonizing male vocals, singing over wide brass melody, electric guitar chords, straight piano melody, punchy snare and smooth bass guitar. It sounds groovy, addictive and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/46WpyRUqwXU.wav"} +{"id": "476vNb6thyM", "caption": "The low quality recording features a jazzy electric guitar melody. The recording is noisy and it is in mono - regardless, it sounds calming and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/476vNb6thyM.wav"} +{"id": "49nqh7uI9fw", "caption": "This recording contains male voice samples that seem to be pitched down and strongly processed with effects, also reverb and delay. One is panned to the right side of the speakers. A lot of white noise is running through a filter and an LFO. A synthesizer is playing a simple melody for a moment before fading away. This song may be playing in-between two songs of a DJ-set.", "audio": "/zhanghaomin/datas/musiccap/music_data/49nqh7uI9fw.wav"} +{"id": "4AejyFDHP_k", "caption": "An acoustic guitar almost fully panned to the left side of the speakers is strumming a single chord as a rhythmic element while an upright-bass is playing a walking bassline. The other acoustic guitar is adding a little melody at the end of the phrase of the singers. The female duo is singing a melody together. One a little deeper and the other a little higher creating a harmony. This song may be playing in the countryside of a Latin country.", "audio": "/zhanghaomin/datas/musiccap/music_data/4AejyFDHP_k.wav"} +{"id": "4AfykLGm0j8", "caption": "This is a compilation of various different music pieces all in one recording to advertise a radio software. The pieces are generic in nature. There is a rock music piece with an electric guitar playing. After a static sound effect, it switches to a pop music piece. There is a female vocalist singing over a keyboard and electronic drum beat background. There is a random feeling to this track.", "audio": "/zhanghaomin/datas/musiccap/music_data/4AfykLGm0j8.wav"} +{"id": "4BIIFU_b6BY", "caption": "An acoustic drum is playing a rock groove with a big emphasis on the ride and silent hits on the crash. Along with the drums a electric bass is playing a bluesy line and so does the guitar. Another e-guitar is strumming chords. The whole song sounds fast and may be playing at a local festival where people are dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/4BIIFU_b6BY.wav"} +{"id": "4Bc9OoagYmo", "caption": "The song has a laid-back, unfussy feel to it. There are various instruments layered to form a smooth, groovy, yet mellow song. The song would be categorized as pop rock, owing to the electric guitar lick and prominent electric guitar chord plucking. There's also an organ and an electric piano. The singer sounds soulful but relaxed.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Bc9OoagYmo.wav"} +{"id": "4CkJjhuYRmY", "caption": "The song is an instrumental. The tempo is medium with a horn playing melody accompanied, by a string section, horn section and a rhythm section and led by a conductor. The song is exciting and regal. The song is a classical western tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/4CkJjhuYRmY.wav"} +{"id": "4CkZqT26Vb0", "caption": "This song features a flute playing the main melody. This is accompanied by percussion playing a nomadic beat. A stringed instrument plucks notes in the background. Ambient synth sounds are played to give fullness to the song. This song has a middle-eastern influence and is dreamy. It can be played in the intro lobby of a game.", "audio": "/zhanghaomin/datas/musiccap/music_data/4CkZqT26Vb0.wav"} +{"id": "4CrPPlHN9_s", "caption": "The low quality recording features a cover of a pop song and it consists of passionate male vocals, alongside harmonizing background vocals, singing over wide, arpeggiated electric guitar melody and simple bass guitar. The recording is a bit noisy, but it is barely audible, especially when you take into account that it sounds very emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/4CrPPlHN9_s.wav"} +{"id": "4EwWBI-tHLk", "caption": "This music is a lively harmony of the brass and wind instruments. The tempo is fast with lively tuba, trombone, trumpet, clarinet with mandolin and resonator accompaniment and busking percussion that sounds like scratching. His music is loud, vibrant, perky, engaging and animated street busking.", "audio": "/zhanghaomin/datas/musiccap/music_data/4EwWBI-tHLk.wav"} +{"id": "4GlH0-KhInI", "caption": "This song contains digital drums playing a kick on every beat together with a digital synth bass playing a simple almost monotone bassline. A male voice is singing in a deeper key. This song is running through some filters opening up and with a lot of reverb. This song may be playing while having a car ride.", "audio": "/zhanghaomin/datas/musiccap/music_data/4GlH0-KhInI.wav"} +{"id": "4Gow6qZcNZI", "caption": "The low quality recording features a tutorial where a flat male vocalist is talking, after which a groovy bass guitar is playing. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Gow6qZcNZI.wav"} +{"id": "4H1nc2Xv2Hg", "caption": "The song is an instrumental. The tempo is slow and unsure, with a guitarist attempting to play a minor scale and gets the scale wrong. The song has poor audio quality with ambient traffic noise in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/4H1nc2Xv2Hg.wav"} +{"id": "4HfU5OQUqq0", "caption": "A male artist talks and makes drilling noises. The song is a modern hip hop song with male rap vocals, hip hop drumming rhythm, heavy bass drops and keyboard harmony. The track has ambient room noises and the music track is very faint. The audio quality is very average.", "audio": "/zhanghaomin/datas/musiccap/music_data/4HfU5OQUqq0.wav"} +{"id": "4HhJneiP-hY", "caption": "There is an orchestra composed of the winds section and the timpani playing a dramatic tune with a rising melody. Afterwards, a thunder sound effect can be heard. Sounds from this piece can be sampled for use in advertisement jingles or in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/4HhJneiP-hY.wav"} +{"id": "4JYJRqwqWGM", "caption": "This audio contains a melodic bell ringing. In the background you can hear birds chirping. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/4JYJRqwqWGM.wav"} +{"id": "4KqSdK5KM-I", "caption": "A banjo is playing chords while an upright bass is playing a bassline. These two form the rhythmic section. On top of that a mandolin is playing a fast and complex solo. In the background you can hear the crowd cheering and clapping hands. This is an amateur recording. This song may be playing in a big pub.", "audio": "/zhanghaomin/datas/musiccap/music_data/4KqSdK5KM-I.wav"} +{"id": "4L9KyVVsQOc", "caption": "The low quality recording features an echoing electric guitar playing rock solo melody. The recording is noisy and in mono. It sounds passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/4L9KyVVsQOc.wav"} +{"id": "4LZSSya3ZZQ", "caption": "The low quality recording features a flat male vocal talking over an acoustic guitar solo melody playing in the background. It sounds like a tutorial and the recording is in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/4LZSSya3ZZQ.wav"} +{"id": "4Lk8pUeLCwQ", "caption": "A male singer sings this reggae melody with backup singers in vocal harmony. The song is medium fast tempo with a groovy drum drumming rhythm, keyboard accompaniment, percussive bass line and various percussive effects. The song is groovy and enthusiastic with a reggae influence.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Lk8pUeLCwQ.wav"} +{"id": "4M0njWKFsME", "caption": "Here we have a powerful rock ballad instrumental in a minor key. The guitar is grungy and overdriven, and the piano is clean and plays the same chords as the guitar at the same time.", "audio": "/zhanghaomin/datas/musiccap/music_data/4M0njWKFsME.wav"} +{"id": "4M_k01zIbVM", "caption": "The low quality recording features a cover of a soft rock song and it consists of strummed electric guitar and mellow electric guitar melody played over playback that has groovy bass, reverberant rimshots, shimmering cymbals and sizzling high pitched synth pad. It sounds emotional, funky and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/4M_k01zIbVM.wav"} +{"id": "4Mm5mBgktG0", "caption": "The song is an instrumental. The song is medium tempo with a groovy bass line, grunge keyboard tones, synth trumpet lead and techno drumming rhythm. The song is entertaining and energetic. The song is an electronic dance song with average quality recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Mm5mBgktG0.wav"} +{"id": "4Mo7tdV2LZk", "caption": "A oud is being played fast while a choir is singing a melody slowly moving down the scale. This song may be playing at a music reunion. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Mo7tdV2LZk.wav"} +{"id": "4PGzlwvXMnE", "caption": "The low quality recording features a trap song that consists of flat male vocals, alongside wide harmonizing male vocals, singing over punchy 808 bass and repetitive synth lead melody in the background. There is a high pitched riser at the end of the loop. It sounds groovy and addictive thanks to that cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/4PGzlwvXMnE.wav"} +{"id": "4PNPgaLKFlc", "caption": "The track is a Kids Music song. A female voice with appealing vocals sings an easygoing melody. A piano with a bright sound plays a jazzy melody. A jazz drum kit plays a smooth beat. In the background there are trumpets playing a melody that matches the positive and fun atmosphere of the track.", "audio": "/zhanghaomin/datas/musiccap/music_data/4PNPgaLKFlc.wav"} +{"id": "4Psj5jYa7a4", "caption": "Someone is playing a didgeridoo using circular breathing to continue airflow. A percussive stick sound can be heard and in the background you can hear waves of water. This song may be playing at the beach practicing didgeridoo by yourself.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Psj5jYa7a4.wav"} +{"id": "4Psyk_xyBl0", "caption": "The track features an electric guitar with a chorus pedal effect. The guitar alternates between riff to melody. The sound is space-like and almost psychedelic. The atmosphere is sweet and dreamy.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Psyk_xyBl0.wav"} +{"id": "4QES-SJ7mP0", "caption": "A four chord modern hip hop/ R&B production featuring synthesizer pads, electronic drums, a female vocalist in a minor key.", "audio": "/zhanghaomin/datas/musiccap/music_data/4QES-SJ7mP0.wav"} +{"id": "4QJktFv916o", "caption": "The low quality recording features a metal song that consists of female opera vocal singing over double pedal kick, punchy snare, energetic cymbals, wide electric guitar melody and groovy bass guitar. It sounds aggressive, energetic and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/4QJktFv916o.wav"} +{"id": "4S4NDnNTptY", "caption": "The low quality recording features an orchestra that contains a wide string section, aggressive triangle cymbal and woodwind section dynamically playing an addictive melody. It is very noisy, uptempo, energetic and dynamic.", "audio": "/zhanghaomin/datas/musiccap/music_data/4S4NDnNTptY.wav"} +{"id": "4T2KBwRxi_g", "caption": "This is a live recording of a didgeridoo being played. The musician takes a deep breath intermittently while playing the deep, bellowing tone of the instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/4T2KBwRxi_g.wav"} +{"id": "4TDtUHo5cSE", "caption": "The low quality recording features a jazz song that consists of shimmering hi hats and ride cymbals, soft kick and snare hits, groovy walking bass and smooth organ keys melody. It sounds easygoing, groovy and warm - almost like a theme song for some old cartoon.", "audio": "/zhanghaomin/datas/musiccap/music_data/4TDtUHo5cSE.wav"} +{"id": "4TXy2i036LU", "caption": "This song contains drums with a deep and strong but jet soft kick sound with a snare that sounds muted. An upright bass or e-bass is playing a line along. A e-guitar is strumming a chord progression along with a piano. A male voice is singing in the midrange sounding sensitive and honest. Panned to both sides of the speakers two trumpets are playing a melody in the lower to mid-range. This song may be playing in a beautiful romantic art video.", "audio": "/zhanghaomin/datas/musiccap/music_data/4TXy2i036LU.wav"} +{"id": "4T_5clu_0OM", "caption": "Male singers engage in a conversation at the beginning of the song. The song is medium tempo with a guitar playing rhythm, steady drumming rhythm, tambourine percussion, kick drum percussion and keyboard accompaniment. The song is romantic and spirited. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/4T_5clu_0OM.wav"} +{"id": "4Ua6i_VDYU4", "caption": "This audio contains a digital drum with a kick on every beat. An e-bass is playing a slightly funky groove. A synthesizer is playing a short fast melody. Another synth sound is playing a string/pad sound rising up into focus. A female voice is singing, then another female voice takes over singing. The crowd is cheering loudly. This song may be playing during a live show.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Ua6i_VDYU4.wav"} +{"id": "4Udqs0trpMw", "caption": "This audio contains an orchestral composition. A brass section is playing an uplifting melody with a horn playing a bassline. Cymbals are playing a 8th notes rhythm and flutes and a trombone are playing a countermelody. On top of that a xylophone is playing a melody in a higher pitch on top. This song may be playing during a cheerful cultural event such as Christmas.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Udqs0trpMw.wav"} +{"id": "4VbXYuCz4M0", "caption": "The low quality recording features a live performance that consists of harmonica solo melody played over acoustic rhythm guitar chords. The recording is noisy, in mono and it sounds happy and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/4VbXYuCz4M0.wav"} +{"id": "4Vg0PQuHTk0", "caption": "This is a groovy, electro-funk track which works well for dancing. A song like this would be heard in the eighties. It is soulful and upbeat. There are synth stabs and a trumpety synth motif in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Vg0PQuHTk0.wav"} +{"id": "4W3Ql8JbEN8", "caption": "The low quality recording features short repetitive synth hits located in the right channel, buzzy sounds in the left channel of the stereo image and deep synth hits in the middle. It sounds intense and suspenseful, like background music for a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/4W3Ql8JbEN8.wav"} +{"id": "4W8BYc8ZMaE", "caption": "The music features a female voice singing while being backed by another female voice. The instrumental consists of only one acoustic guitar that strums chords. At one point the crowd is screaming/cheering. The sound of the recording plus the cheering crowd makes me think that this was recorded at a live event.", "audio": "/zhanghaomin/datas/musiccap/music_data/4W8BYc8ZMaE.wav"} +{"id": "4W8IZxn3nEI", "caption": "A male vocalist sings this animated song. The tempo is medium fast with keyboard harmony, acoustic guitar , steady drumming and simple bass lines. The song is simple, catchy, funny, spirited, animated and easy to sing along. The lyrics are funny.", "audio": "/zhanghaomin/datas/musiccap/music_data/4W8IZxn3nEI.wav"} +{"id": "4X2aUZFZlzc", "caption": "A digital drum is playing a monotone beat with a kick on every beat along with a repeating voice sample. In the next song a wide synth pad is playing a string sound while a female voice sample is singing a melody. These songs may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/4X2aUZFZlzc.wav"} +{"id": "4Y5VcH7iK3Q", "caption": "Instrumental surf rock with a lead electric guitar playing the melody and a rhythm electric guitar strumming chords. Ride cymbals are loud in the mix and spring reverb is used as an effect. The electric bass is playing a walking pattern.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Y5VcH7iK3Q.wav"} +{"id": "4Yc71_dU3m4", "caption": "This music is a lively instrumental of the Indian Classical instruments. The tempo is fast with a lead Veena harmony, spirited tabla and tanpura rhythm and melodic flute accompaniment. The music is euphoric, mellifluous, dulcet, lively, high spirited and rich. This music is a Indian Classical Veena instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/4Yc71_dU3m4.wav"} +{"id": "4ZwGxgOwBUc", "caption": "This music is a lively violin composition. The tempo is fast with a spirited violin harmony and vivacious viola and cello accompaniment. The music is upbeat, happy, cheerful, playful, fresh and captivating with the voice of a woman superimposed on it with static and ambient outdoor sounds. This instrumental is a background music to a live presentation happening outdoors.", "audio": "/zhanghaomin/datas/musiccap/music_data/4ZwGxgOwBUc.wav"} +{"id": "4_s5vHgfxnw", "caption": "This audio contains someone playing bagpipes with something that sounds like a traditional piece. Someone is also playing a side drum snare along. This song may be playing on the street performed by buskers.", "audio": "/zhanghaomin/datas/musiccap/music_data/4_s5vHgfxnw.wav"} +{"id": "4a1a-lmDVaY", "caption": "This funk song features a male voice singing the main melody. Other voices sing backing vocals in harmony. A saxophone plays a repetitive melody. This is accompanied by percussion playing a funk beat. The bass plays a funky bassline. A guitar plays muted chords using a tron effect. This song is upbeat and has a happy mood. This song can be played at a retro style disco.", "audio": "/zhanghaomin/datas/musiccap/music_data/4a1a-lmDVaY.wav"} +{"id": "4b8gTARnmVE", "caption": "This is a salsa music piece. There is a male vocal in the lead joined by another as a back vocal. All the vocals are singing joyfully. There is a piano playing the main melody while a bass guitar is playing in the background. In the rhythmic background, there is an acoustic latin drum beat with percussion playing syncopations all over. There is a lively, upbeat atmosphere. This piece could be played at dance clubs and it could also be used as an accompaniment piece for latin dance courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/4b8gTARnmVE.wav"} +{"id": "4bXb6GLm6zg", "caption": "This is the live performance of a blues music piece. It is an instrumental performance. The lead electric guitar is playing a blues solo while another electric guitar and a bass guitar are playing in the background. The rhythmic background consists of a slow tempo blues acoustic drum beat. There is a groovy atmosphere to this performance. This piece could be playing in the background at a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/4bXb6GLm6zg.wav"} +{"id": "4cg3MsrvJqw", "caption": "This is a traditional Chinese folk band playing a variety of traditional chinese instruments. The erhu, which sounds much like a violin, is being played in harmony with the guqin to create a melody which the performers also sing. The percussion is done on a bongo-sounding drum. This is a live performance, and we hear people speaking in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/4cg3MsrvJqw.wav"} +{"id": "4dilYyxYLmM", "caption": "This song contains a digital drum with a shaker panned to the left side of the speaker. There are other rhythmic sound effects panned to the right side of the speakers. A digital bass playing a repeating melody is the center of this song. This song may be playing in a dance battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/4dilYyxYLmM.wav"} +{"id": "4ezo771lGts", "caption": "Sounds of explosions and jet airplanes over a synthesized orchestral string pad playing a four chord progression and electronic drums playing a subdued, mellow backbeat rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/4ezo771lGts.wav"} +{"id": "4gEmWJCPZGo", "caption": "The song is primarily an instrumental with male voices chanting prayers. The song is fast tempo with tabla percussions and harmonium playing accompaniment. The song is spirited and devotional with a trance like feel to it. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/4gEmWJCPZGo.wav"} +{"id": "4hulNRgH6cI", "caption": "This music is instrumental.the tempo is slow with a boomy, menacing bass and synthesiser arrangements. The music is deliberate, menacing, precarious,threatening, scary, sinister and grim. This music is Hard Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/4hulNRgH6cI.wav"} +{"id": "4i11P4OCRfk", "caption": "This recording contains a dulcimer playing a melody along with loud tablas playing a lot of deep hits that are overloading the recording speakers. At the end a string sound comes underlining with long pad notes. This song may be playing in a live event.", "audio": "/zhanghaomin/datas/musiccap/music_data/4i11P4OCRfk.wav"} +{"id": "4i1aizhCnfg", "caption": "A male vocalist sings this mellow pop. The tempo is slow in contrast to the enthusiastic introductory bit in this section. The song is soft, mellow, emotional, repetitive, melancholic, nostalgic and passionate with a soft acoustic guitar accompaniment. This could be a song fade. This song is a Korean Pop/K-Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/4i1aizhCnfg.wav"} +{"id": "4i9DgH80kDg", "caption": "This music is instrumental. The tempo is medium with an animated Banjo lead harmony. There is minimal instrumentation with cheerful ,popping vibrations of this beautiful instrument. It is lively ,spirited, cheerful and adds a beautiful layer to Country and Folk Songs.", "audio": "/zhanghaomin/datas/musiccap/music_data/4i9DgH80kDg.wav"} +{"id": "4jzr88nEdCM", "caption": "A male vocalist sings this upbeat pop. The tempo is fast with synthesiser arrangements, hard hitting drums, groovy bass, tambourine beats ,keyboard harmony and choral harmony. The song is an upbeat, catchy , compelling, persuasive, enthusiastic and youthful Indie Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/4jzr88nEdCM.wav"} +{"id": "4kKVGPDCIK8", "caption": "This song contains a male voice chanting a melody in the midrange while a synth is playing a drone full of overtones. Other synth pads are overlaying in a higher register while again other synth pluck sounds are playing a melody in a high key. This song may be playing in a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/4kKVGPDCIK8.wav"} +{"id": "4kZ0EZg5JRU", "caption": "The low quality recording features a ballad that contains a flat male vocal, alongside mellow harmonizing, reverberant female vocals, singing over acoustic rhythm guitar located in the left channel, electric guitar melody in the right channel of the stereo image, groovy bass, shimmering hi hats, soft rimshots, soft kick hits and mellow keys melody. It sounds mellow, emotional, passionate and heartfelt.", "audio": "/zhanghaomin/datas/musiccap/music_data/4kZ0EZg5JRU.wav"} +{"id": "4kyWH8eWP8M", "caption": "church bells ringing together slowly.", "audio": "/zhanghaomin/datas/musiccap/music_data/4kyWH8eWP8M.wav"} +{"id": "4l441DdEJfU", "caption": "The low quality recording features fruity male vocals, alongside background crowd noise, talking, after which a trap song, that consists of passionate male vocal and addictive synth brass lead melody, starts playing. It sounds exciting and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/4l441DdEJfU.wav"} +{"id": "4lcZkOMhKv8", "caption": "This house music clip features a male voice in the beginning followed by a male voice that has been heavily processed. This is accompanied by programmed percussion with a booming kick played on every count. After two bars, the snare is also played with the kick. Staccato synth notes are played on the 'one and' and the third count of each bar. The mood of this song is upbeat. This song can be played in a trance club.", "audio": "/zhanghaomin/datas/musiccap/music_data/4lcZkOMhKv8.wav"} +{"id": "4ls_8xIjBzM", "caption": "This music is instrumental. The tempo is medium with an electric guitar riff and the voice of a man giving instructions on electric guitar techniques. The music is loud, clear, amplified, vivid, emphatic and powerful. This is a tutorial/ lesson on electric guitar techniques.", "audio": "/zhanghaomin/datas/musiccap/music_data/4ls_8xIjBzM.wav"} +{"id": "4mC6K77Y_Ho", "caption": "This song features the sound of a shofar being played. The shofar plays a high pitch note and plays some broken notes in between. This song is an instrumental and has no voices. This instrument is played ar Jewish religious functions.", "audio": "/zhanghaomin/datas/musiccap/music_data/4mC6K77Y_Ho.wav"} +{"id": "4mtfOkzOvBI", "caption": "The low quality recording features a live performance of folk songs played by flute, strings and energetic drums. The recording is noisy and in mono, as the audio is crackling and it sounds energetic and kind of addictive thanks to that flute and strings melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/4mtfOkzOvBI.wav"} +{"id": "4o0bARRMYQ8", "caption": "The Gospel song features a harmonized mixed choir vocals singing over mellow piano melody, smooth bass, soft kick, snare and cymbals hits and sustained strings melody. It sounds passionate, emotional, powerful and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/4o0bARRMYQ8.wav"} +{"id": "4q-eGdrqiIw", "caption": "The low quality recording features flat male vocals talking over rock songs playing in the background. It sounds like a documentary about music. The recording is muffled, noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/4q-eGdrqiIw.wav"} +{"id": "4q6e_ZDFOZI", "caption": "This is a Christmas themed jingle piece. There is a little girl singing sentimentally at a medium-to-high pitch. In the melodic background, treble strings play the tune while the cello holds the bass notes with rhythm. There is also a passing section of wind chimes. A male voice makes a brief comment over the girl's singing. This could be used in Christmas themed social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/4q6e_ZDFOZI.wav"} +{"id": "4refolVb_uQ", "caption": "The low quality recording features a rock song that consists of reverberant male vocal singing over groovy bass, short electric guitar chords, punchy snare, soft kick hits, shimmering hi hats and soft crash cymbals. The reverb of the vocal is located in the right channel of the stereo image, which makes it sound interesting. It is easygoing and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/4refolVb_uQ.wav"} +{"id": "4sD0Bvt3FKk", "caption": "A blues rock song is being played. Containing drums that are playing a simple groove along with a blues bassline that is supported by an e-guitar playing the same melody. So does a piano just in a higher pitch adding harmony. The female voices are singing together. Then an e-guitar starts playing a little solo-melody. There are some airy background noises that seem not to belong to the recording. This song may be playing at a local car workshop.", "audio": "/zhanghaomin/datas/musiccap/music_data/4sD0Bvt3FKk.wav"} +{"id": "4tF0Lt9VEp8", "caption": "This song features a male voice beatboxing. At the beginning of the song, he beatboxes a simple beat. Post that, the beatboxing is done in layers where the beat is one layer, the cymbals is another layer, a bass slide is another layer and a deep voice is the fourth layer. This is all done using the human voice and no instruments. This song is at a moderate tempo. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/4tF0Lt9VEp8.wav"} +{"id": "4tH9knHaTd0", "caption": "The low quality recording features sustained french horn tones played, while there is a low female vocal and flat male vocal talking, followed by some laughs, shoe squeaking and woodwind melody played in the background. The recording is a bit noisy and it sounds like the musicians are rehearsing.", "audio": "/zhanghaomin/datas/musiccap/music_data/4tH9knHaTd0.wav"} +{"id": "4ueN2gGsH5Y", "caption": "This instrumental song features an acoustic guitar being played. The strings are raked followed by a bend to a higher note. This is followed by a descending run using three notes. This song has a blues feel. There are no other instruments in this song. There are no voices in this song. This song can be played in a Wild West movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/4ueN2gGsH5Y.wav"} +{"id": "4ufDENm_ECk", "caption": "This amateur recording features low quality audio. The audio is of music played from a toy. It is a children's song. A child is singing the main melody. This is accompanied by percussion playing a simple beat. There are other instruments playing fills in between lines. The voice of the instruments is not distinguishable. There is a giggling sound of a girl that is heard in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/4ufDENm_ECk.wav"} +{"id": "4vGLTrW04UE", "caption": "This song elicits feelings of mystery, exploration and curiosity. It's a classical piece including violins, violas, cellos and a recorder or alto-flute. The end section builds tension and suspense - as if in a movie scene when a character is peaking curiously around new terrain.", "audio": "/zhanghaomin/datas/musiccap/music_data/4vGLTrW04UE.wav"} +{"id": "4vWChPYkuwA", "caption": "A male vocalist sings this Pop song. The tempo is slow with a melodic and emphatic piano accompaniment. This bit has minimal instrumentation as it is the introduction. The music is burgeoning with a cymbal crash introduced at the end of this clip. The song is slow, sad, poignant, reflective and nostalgic. This song is a hit Pop Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/4vWChPYkuwA.wav"} +{"id": "4vsI0Kwn8jY", "caption": "The song is an instrumental. The song is a medium tempo with a mandolin player playing a cheerful melody with no other instrumentation. The song is positive and has a delightful dance rhythm. The song has an average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/4vsI0Kwn8jY.wav"} +{"id": "4yJZ4VX8XQI", "caption": "This song features synth pads playing in the background. Shimmering notes are played in this song. These notes are played three times. There are no voices in this song. There are no other instruments in this song. This instrumental song has a dreamy feel. This song can be played in a relaxation room or meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/4yJZ4VX8XQI.wav"} +{"id": "4ymXDU-48EE", "caption": "A female singer leads other backup singers in a vocal harmony. The song is medium tempo with just mouth and body percussion. The song is groovy and played with a lot of ambient crowd noises. The song is a movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/4ymXDU-48EE.wav"} +{"id": "4zZiWBp0b08", "caption": "This is a comedy music piece. There is a male vocalist singing in a funny manner in the Filipino language. The keyboard is playing a goofy tune with the bass guitar playing in the background. The rhythm is being played by a simple electronic drum beat. There is an amusing atmosphere. This piece could be used in the soundtrack of a comedy movie that takes place in the Philippines.", "audio": "/zhanghaomin/datas/musiccap/music_data/4zZiWBp0b08.wav"} +{"id": "5-aS_pyXesM", "caption": "A male vocalist sings this enthralling Arabic song. The tempo is medium with mizwiz lead melody , rhythmic oud accompaniment,, goblet drum, tambourine keyboard harmony along with more Arabian percussive instruments. The song is melodic, charming, pleasant, engaging, ambient and soulful. This song is an Arabic Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/5-aS_pyXesM.wav"} +{"id": "5-tx4Fgqetc", "caption": "This clip features a didgeridoo being played. The sound it produces is a droning sound alternating with a bass sound. There are no voices in this clip. This is an instrumental clip of only a didgeridoo. There are no other instruments in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/5-tx4Fgqetc.wav"} +{"id": "50QEapyTPD4", "caption": "The track is a video game soundtrack. A scary sounding synth sustains a dissonant chord that indicates danger. What seems to be an infant is sampled, the sound has reverb and distortion. There's a tension atmosphere.The overall vibe of the track is dark.", "audio": "/zhanghaomin/datas/musiccap/music_data/50QEapyTPD4.wav"} +{"id": "50fuQm8B2Yg", "caption": "This jazz song features a saxophone playing the main melody. This is accompanied by percussion playing a jazz beat. A piano plays jazz chords. The double bass plays the root notes with flourishes and fills. This song is the outro of a song and abruptly pauses. The mood of this song is happy. There are no voices in this song. This is an instrumental song. This song can be played in a luxury bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/50fuQm8B2Yg.wav"} +{"id": "51bsCRv6kI0", "caption": "The low quality recording features a flat male vocal talking, after which a jazz live performance recording starts playing. It sounds like an interview and the recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/51bsCRv6kI0.wav"} +{"id": "52GYcHTcCgs", "caption": "The male voice is singing/talking over an electric bass playing a harmonic bassline while the acoustic drums is playing a light groove almost just on the lightly open hi hat and some kick hits. This song may be playing at a musician's bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/52GYcHTcCgs.wav"} +{"id": "52odOK7G2kg", "caption": "This song features a distortion guitar. This is an instructional video. The song features an open note followed by the octave. Then a descending pattern is played on the distortion guitar. The voice gives instructions on how to play the pattern. There is no percussion in this song. There are no other instruments in this song. There is no vocal melody in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/52odOK7G2kg.wav"} +{"id": "53UF6F7D284", "caption": "The low quality recording features a southern rock song that consists of a fruity male vocal singing over groovy bass guitar, low toms and wide electric guitar melody. It sounds emotional and nostalgic.", "audio": "/zhanghaomin/datas/musiccap/music_data/53UF6F7D284.wav"} +{"id": "54yI3In3DrU", "caption": "The low quality recording features a classical song that consists of an arpeggiated strings melody and mellow woodwind melody playing in the background. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/54yI3In3DrU.wav"} +{"id": "55qucu8Zs_I", "caption": "The low quality recording features a passionate female vocal, alongside harmonizing vocals, singing over wooden percussion, playing as the background music, while there are birds chirping, cows mooing and metallic impacts sounds. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/55qucu8Zs_I.wav"} +{"id": "55vMO5LzMHM", "caption": "There is an ambient synth playing at a low-to-medium range. A door creaking sound can be heard. There is an eerie and ominous atmosphere to this track. It could be sampled to be used in the soundtrack of a mystery/horror video game as a sound effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/55vMO5LzMHM.wav"} +{"id": "56Cm1AkbfbU", "caption": "The low quality recording features a live performance of a pop song that consists of harmonizing male vocals singing, while there are crowd cheering noises in the background. It sounds passionate, heartfelt and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/56Cm1AkbfbU.wav"} +{"id": "577NM64YL18", "caption": "This is a live recording with low audio quality. It seems like the kind of music that would feature in a sombre, mysterious, and perhaps haunting movie. The instruments are layers of sustained, high-pitched synths.", "audio": "/zhanghaomin/datas/musiccap/music_data/577NM64YL18.wav"} +{"id": "588osm3C4bw", "caption": "The low quality recording features a live performance of a jazz song that consists of a clarinet solo melody played over groovy piano, mellow brass melody, shimmering hi hats and mellow kick hits. It sounds emotional, easygoing and chill.", "audio": "/zhanghaomin/datas/musiccap/music_data/588osm3C4bw.wav"} +{"id": "58JwiVM8bYM", "caption": "This song contains acoustic drums playing a repetitive groove along with a bassline. A e-guitar with a chorus effect is playing a repeating melody. In the background you can hear shouting sounds and goose noises. This song may be playing while playing video-games.", "audio": "/zhanghaomin/datas/musiccap/music_data/58JwiVM8bYM.wav"} +{"id": "58f4AsxOYhU", "caption": "This song features the sound of the watch machine gears moving. It is the sound of the watch click. It is accompanied by the sound of a synth which swells till the end. A bass sound is played once after the first watch click and then once in between the fourth and fifth click. Thereafter, the bass sound is repeated after every two clicks. This song has no voices. This sound can be played in a movie where a bank robber is about to steal from a large bank.", "audio": "/zhanghaomin/datas/musiccap/music_data/58f4AsxOYhU.wav"} +{"id": "59Mt7J_0KT4", "caption": "This is an intro to a YouTube video. Initially, there is a turntable scratching sound with a shouting sample. Then an upbeat jazz music piece starts playing. There is a piano and a flute playing the melody while a bass guitar plays in the background. The jazz acoustic drum beat provides the rhythm. There is a car engine sound coming from a video gameplay. It is a whole mashup of different sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/59Mt7J_0KT4.wav"} +{"id": "5AdeNHlPnvs", "caption": "The low quality recording features a traditional song that consists of a passionate male vocal singing over breathy flute melody, shimmering tambourine, claps, wooden percussion and strings melody. It sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/5AdeNHlPnvs.wav"} +{"id": "5BEVY0vaygg", "caption": "This song contains someone playing a hybrid of a guitar/harp. In the background you can hear drums and e-bass playing along while a male voice is singing sounding relaxed in the midrange.", "audio": "/zhanghaomin/datas/musiccap/music_data/5BEVY0vaygg.wav"} +{"id": "5C70IZwHA5g", "caption": "This song features a male voice and a female voice singing together. This is accompanied by percussion playing a simple beat. A shaker is played once on the count and twice on the end of each count. The bass plays a melody using a fuzzy tone. A synth holds chords in the background. The mood of the singers is narrative. This song can be played in a mystery movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/5C70IZwHA5g.wav"} +{"id": "5CtvEcPtknI", "caption": "This song is an alternative rock song which features a male vocalist whispering the lyrics. The guitarist plays arpeggios of the chords while there is a screeching distorted sound in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/5CtvEcPtknI.wav"} +{"id": "5D4siJjh1j0", "caption": "The low quality recording features a high pitched female vocal singing over snare roll, repetitive synth keys chords and echoing crash cymbals all impacted by filter modulation that slowly opens up. It sounds exciting and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/5D4siJjh1j0.wav"} +{"id": "5DDg2CzAmgE", "caption": "This is a fast tempo song. The audio quality is inferior so the vocals are muddled making it difficult to comprehend if the vocalist is a male or female. The music is incoherent too but it is possible to identify synth arrangements, intense drumming, boomy bass lines,and keyboard harmony with spirited vocals. The song is upbeat and has a dance groove. It is a pop rock/ synth rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/5DDg2CzAmgE.wav"} +{"id": "5DNl3DX4rr0", "caption": "This is a heavy metal music piece from a video game soundtrack. The piece is being performed in the style of a military march. There are speech sounds that resemble the speech of a fascist dictator. The main theme is being played by the distorted electric guitar with the bass guitar playing in the background. The rhythmic background is provided by the acoustic drums. There is an aggressive and militaristic atmosphere. This piece could be playing in the soundtrack of a video game or a movie that has a war setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/5DNl3DX4rr0.wav"} +{"id": "5F8zpfwFKl0", "caption": "This is an Uzbek folk music piece. There is a female vocalist singing melodically. The main tune is being played by the garmon while the rhythmic background consists of the doors and the clapping of the dancers. There is a vibrant atmosphere in this piece. It could be used as an accompaniment piece for an Uzbek folk dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/5F8zpfwFKl0.wav"} +{"id": "5FbQu7QTme0", "caption": "A female vocalist sings this lilting Folk song in a foreign language. The tempo is slow with an Oud accompaniment, violin harmony, tabla and dhol rhythm. The performance is live with ambient sounds. The song is simple, sweet, charming and lilting.", "audio": "/zhanghaomin/datas/musiccap/music_data/5FbQu7QTme0.wav"} +{"id": "5FlNBuS7YgM", "caption": "This is an Italian folk music piece. It is a live performance recording. There is a mandolin playing the main tune of the piece while an acoustic guitar plays in the melodic background. The atmosphere of the piece is lively. This piece could be used in the soundtrack of a documentary taking place in the Mediterranean region. It could also be used in tourism agency advertisements. Another possible use is as an accompaniment piece for Italian folk dance courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/5FlNBuS7YgM.wav"} +{"id": "5J6CjNc8Njo", "caption": "This is a Tunisian folk music piece. There is an orchestra playing the main tune with the dominant sound of the strings section and the oud. There is a choir singing in the background. The atmosphere is vibrant and sentimental. This piece could be in the soundtrack of a Middle Eastern/North African soap opera.", "audio": "/zhanghaomin/datas/musiccap/music_data/5J6CjNc8Njo.wav"} +{"id": "5JQIsqc8HBc", "caption": "A female voice is singing in a higher pitch with a lot of quarter and half steps. A string section and plucked strings are playing along with the melody adding little accents here and there. percussion instruments are holding a rhythm with little elements. This song sounds like it is from a part of India. The sound quality is not the best. This song may be playing in a documenta.", "audio": "/zhanghaomin/datas/musiccap/music_data/5JQIsqc8HBc.wav"} +{"id": "5JRvGMTjEzQ", "caption": "This is an acoustic performance of a Vietnamese ballad music piece. There is a male vocalist singing gently while playing a mellow tune on the acoustic guitar. The atmosphere is sentimental and melancholic. This piece could be playing in the background at a Vietnamese coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/5JRvGMTjEzQ.wav"} +{"id": "5JkPsWsq3E8", "caption": "The Indian traditional music is purely instrumental, there is no voice. All instruments used are from Indian culture. A sitar one-note harmonic pedal can be heard throughout the music excerpt. The atmosphere is somewhat calming, meditating.", "audio": "/zhanghaomin/datas/musiccap/music_data/5JkPsWsq3E8.wav"} +{"id": "5JqTvKNXzOw", "caption": "This is a dance-pop music piece. There are two female vocalists singing melodically and rapping. The keyboard is playing the main tune while there is a bass guitar playing in the background. The rhythm consists of an electronic drum beat. There is a hip atmosphere. This piece could be used in the soundtrack of a teenage drama TV series as an opening theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/5JqTvKNXzOw.wav"} +{"id": "5KvjUzQbMT4", "caption": "Here we get to hear a hardcore metal piece. This is characterised, in part, by the rapid action on the kick drum - with notes being played at a rate of sixteenth notes on the kick. The drummer also frequents the ride cymbal. The guitar is grungy, gritty, fuzzy, heavy, deep, hardcore.", "audio": "/zhanghaomin/datas/musiccap/music_data/5KvjUzQbMT4.wav"} +{"id": "5LX2Unga1p4", "caption": "A digital drum with a strong snare that sounds like a slap is playing along with an e-bass that is being slapped, playing a funky bassline. A e-guitar is strumming two funky chords along. A female voice is rapping with a lot of confidence in the attitude and then another female voice is singing accompanied by female backing voices. The file is of poorer audio-quality. This song may be playing in a disco.", "audio": "/zhanghaomin/datas/musiccap/music_data/5LX2Unga1p4.wav"} +{"id": "5MAX6bUSf4s", "caption": "The low quality recording features a breathy flute melody playing over playback that consists of snare roll and shimmering bells. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/5MAX6bUSf4s.wav"} +{"id": "5MOJnA715fA", "caption": "A female vocalist sings this pop song. The tempo is fast with vigorous percussion in the background , funky bass line, an incessant keyboard harmony and guitar. The vocals and instrumentation are incoherent as the audio quality is bad. The is sound of static, murmuring, buzzing,hissing and scuffling indicating that this is a recording of a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/5MOJnA715fA.wav"} +{"id": "5NCUtndrsHg", "caption": "An acoustic drum is holding the groove together with an upright bass and an acoustic guitar playing rhythmic chords on the backbeat. A trumpet and trombone are playing a melody before the male voice starts to sing being backed up by other male voices singing along. This song may be playing during a live event.", "audio": "/zhanghaomin/datas/musiccap/music_data/5NCUtndrsHg.wav"} +{"id": "5P5XAclO8ko", "caption": "This is a pop rock piece. There is a female vocalist singing melodically at the forefront. The melody is being played by a wide-sounding strings section and an acoustic guitar. The bass guitar is playing the root notes in the background. The rhythmic structure is provided by a simple acoustic drum beat. The song is in minor key. The atmosphere is sentimental and filled with longing. This piece could be included in the soundtrack of a teenage drama movie or TV series.", "audio": "/zhanghaomin/datas/musiccap/music_data/5P5XAclO8ko.wav"} +{"id": "5QtjEBcZR6M", "caption": "This is a very distorted tape recording of a gospel song. A choir with a male lead vocal can be heard singing passionately. The loud volume of electric guitar and the acoustic drums can be heard in the track. This track could be used in a nightmare sequence in the soundtrack of a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/5QtjEBcZR6M.wav"} +{"id": "5Tq56BN8PCQ", "caption": "A female singer sings this lilting melody. The song is medium tempo with an acoustic guitar accompaniment, strong bass line, steady rhythm and piano accompaniment. The song has a bad audio quality. The song is emotional and nostalgic in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/5Tq56BN8PCQ.wav"} +{"id": "5UXnulANF8g", "caption": "A soft male singer with a vocal double effect accompanied by plucked string sounds, a synth pad and an oboe. The genre is soft rock with no drums.", "audio": "/zhanghaomin/datas/musiccap/music_data/5UXnulANF8g.wav"} +{"id": "5UmoK5WAW8Y", "caption": "A male vocalist sings this enthusiastic song in a foreign language. The tempo is fast with infectious drumming and an animated button accordion melody. The song is a fusion of hip-hop with folk music making it unique,unconventional and experimental. It is youthful, buoyant, catchy, engaging and funky with electronic beats. This song is a fusion of Hip-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/5UmoK5WAW8Y.wav"} +{"id": "5XNalwqtkFg", "caption": "This is an instrumental meditation music piece. The only instrument being played is the Tibetan singing bowl. The bowl is being rung repeatedly at varying accentuations. Then, the mallet is being rubbed outside the bowl to interrupt the resonant sound. There is a calming and soothing atmosphere to this recording. It could be used in the background of a meditation video. It could also be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/5XNalwqtkFg.wav"} +{"id": "5XXAeSybGK0", "caption": "The low quality recording features a cover of a song sung by passionate girl vocalists over acoustic guitar melody and smooth bass. The recording is very noisy and crackly. Judging by the quality of it, the vocalist is singing on a very cheap sounding microphone - which makes the sound quality even worse.", "audio": "/zhanghaomin/datas/musiccap/music_data/5XXAeSybGK0.wav"} +{"id": "5Y_mT93tkvQ", "caption": "This music is a percussion instrumental. The tempo is fast with an energetic drum machine rhythm.no other instrument has been used.It is vibrant, enthusiastic, bright, simple, energetic, and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/5Y_mT93tkvQ.wav"} +{"id": "5ZX1-GAb7IM", "caption": "The low quality recording features a live performance of a traditional song that consists of a strings melody played over wooden percussion. The recording is in mono, a bit noisy and it sounds passionate, emotional and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/5ZX1-GAb7IM.wav"} +{"id": "5ZX9Ig7XXsw", "caption": "The Soul/R&B song features a passionate male vocal singing over shimmering hi hats, energetic crash cymbals, wide acoustic rhythm guitar melody, shimmering shakers, snappy snare, piano chords and mellow bass. It sounds passionate and romantic - like something you would sing to your partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/5ZX9Ig7XXsw.wav"} +{"id": "5ZpVhmhVYoI", "caption": "An acoustic drum is playing along with a tambourine playing together with the snare. An e-bass is playing along with the kick of the drums. E-guitars are strumming chords as a duo while a male voice sings in a higher register. In the background you can hear male voices providing harmonies. This song may be playing live in a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/5ZpVhmhVYoI.wav"} +{"id": "5_orEetudIA", "caption": "The low quality recording features a manically played piano melody over punchy kick and snare hits, followed by uptempo hi hats and shimmering open hats. It sounds aggressive, mani and thin, as it lacks low frequencies.", "audio": "/zhanghaomin/datas/musiccap/music_data/5_orEetudIA.wav"} +{"id": "5aCDam9_Ps4", "caption": "This is a traditional south asian dance song with a cheerful affect. We have a group of female singers singing in unison - a melody that matches with the one being played on the sitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/5aCDam9_Ps4.wav"} +{"id": "5a_Qxd4ECTo", "caption": "This music is an intense instrumental; the tempo is fast with atmospheric synthesiser,non-tertian harmonies , distal reverb and electronic sounds. The music is tense, sinister, suspenseful, futuristic, psychedelic and alien. This music is Futurepop.", "audio": "/zhanghaomin/datas/musiccap/music_data/5a_Qxd4ECTo.wav"} +{"id": "5at69yM1PoU", "caption": "The low quality recording features a sustained didgeridoo melody played over quiet, shimmering shakers and wooden percussion. It sounds intense and suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/5at69yM1PoU.wav"} +{"id": "5blPLHS0Cko", "caption": "This ambient song features a main melody played on a flute. It is accompanied by percussion playing beats on the bass drum only. A tambourine is played on one count in every bar. There are the sounds of chirping birds in the background. This song also has layers of synth playing tribal-style instruments. The mood is meditative. This song can be used in meditation or in a yoga session.", "audio": "/zhanghaomin/datas/musiccap/music_data/5blPLHS0Cko.wav"} +{"id": "5bn7PPKcqSA", "caption": "This music is an Electronic instrumental. The tempo is slow with synthesiser arrangements and digitally arranged sounds. The music is dark, futuristic,intense, sinister, and scary with a gothic ambiance. This music is futuristic techno pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/5bn7PPKcqSA.wav"} +{"id": "5bsUYmXIgMA", "caption": "The low quality recording features a traditional song that consists of wooden percussive elements and addictive strings melody playing together. It sounds haunting, suspenseful and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/5bsUYmXIgMA.wav"} +{"id": "5dG1oPahyto", "caption": "The Jazz song features a passionate saxophone melody, followed by an arpeggiated string melody and wide synth pad chords. It sounds passionate, mellow, soft, relaxing and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/5dG1oPahyto.wav"} +{"id": "5fPxUI0Fl-4", "caption": "This song contains two acoustic guitars picking a melody. A digital drum is playing a simple groove when a male voice starts to sing in a higher register with backing vocals. Then the melody drops one octave. The guitars are panned to the left and right side of the speakers. This song may be playing on a road trip with friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/5fPxUI0Fl-4.wav"} +{"id": "5gh5H0QqJl0", "caption": "Here we have a pop R&B song with a piano arpeggio and guitar strumming as the lead melodic components in the instrumental. A rapper then utters a few words in his raspy and strong voice. We then hear subtle soulful backing vocals. The song is emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/5gh5H0QqJl0.wav"} +{"id": "5gyMt0YzPQ0", "caption": "This is a broken beat music piece with jazz funk influences. There is a repeating hollering female vocal sample. There is a keyboard and a synth bass playing the melody. In the background, there is an electronic drum beat and percussive elements. This piece has a groovy atmosphere. It is danceable. It could be playing in the background of a nightclub at earlier hours or at a coffee house.", "audio": "/zhanghaomin/datas/musiccap/music_data/5gyMt0YzPQ0.wav"} +{"id": "5h5NdW6cYY0", "caption": "This slow pop song features a male voice singing the main melody. The voice is emotional. This is accompanied by a piano playing chords in the background. A synth plays a repetitive two note phrase in this song. There is no percussion in this song. The mood of this song is romantic. There are no other instruments in this song. This song can be played in a dreamy sequence in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/5h5NdW6cYY0.wav"} +{"id": "5hEt87nd7os", "caption": "This music is instrumental. The tempo is fast with a vigorous banjo harmony, infectious drumming, auto harp, mandolin and tambourine accompaniment. The music is an upbeat, high-spirited, energetic,enthusiastic ,effervescent Country Music instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/5hEt87nd7os.wav"} +{"id": "5hyRWertUbI", "caption": "A trashy, lo-fi sounding experimental techno track with a steady tempo and shrill, metallic sounds. The mood is cold and distant. Everything sounds a little broken.", "audio": "/zhanghaomin/datas/musiccap/music_data/5hyRWertUbI.wav"} +{"id": "5i0zq91Ocz0", "caption": "This is a psychedelic rock music piece. There is a male vocalist singing melodically in the lead. The main melody is being played by the keyboard with the backing of the electric guitar and the bass guitar. The rhythmic background consists of a rock acoustic drum beat. The atmosphere is chill and trippy. This piece could be used in the soundtrack of a drama movie or a TV series that has scenes of hallucinogenic trip sequences. It could also be playing in the background at a hippie coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/5i0zq91Ocz0.wav"} +{"id": "5iPTcL50mvw", "caption": "The low quality recording features a chiptune remix of a pop song and it consists of high pitched female vocal singing over repetitive synth melody, punchy \"4 on the floor\" kick pattern and shimmering bells melody at the very beginning of the loop. It sounds kind of addictive, fun and happy. The audio sounds like it was stretched.", "audio": "/zhanghaomin/datas/musiccap/music_data/5iPTcL50mvw.wav"} +{"id": "5iUwBOf4yek", "caption": "This song features a synth lead in the beginning. This is accompanied by Indian percussion. A synth choir is playing chords in the background. The synth lead pauses along with the other instruments. A techno beat is played using only bass and kick. This song can be played at a DJ party.", "audio": "/zhanghaomin/datas/musiccap/music_data/5iUwBOf4yek.wav"} +{"id": "5ieMy-PAKA0", "caption": "This is an advertisement jingle music piece. It is an instrumental piece. The main theme is being played by the piano while there is a synth string sound in the melodic background. There is an emotional, heart-touching atmosphere. This piece could be used in the soundtrack of a drama movie during scenes of tragedy. It could also work well as an advertisement jingle where there is an attempted appeal to emotion.", "audio": "/zhanghaomin/datas/musiccap/music_data/5ieMy-PAKA0.wav"} +{"id": "5jQIuYPAODg", "caption": "This is an amateur recording. There are two famous actors singing melodically but with a lot of mistakes on the words. The piano is playing a simple tune. The recording is a bit dated, so the quality is quite low.", "audio": "/zhanghaomin/datas/musiccap/music_data/5jQIuYPAODg.wav"} +{"id": "5jT_i7S9QSM", "caption": "someone is playing an acoustic guitar. Two chordshapes mostly played as single notes with some little hammering while a male voice sings. This song may be playing at a poetry open mic night.", "audio": "/zhanghaomin/datas/musiccap/music_data/5jT_i7S9QSM.wav"} +{"id": "5keRbrVx-G4", "caption": "A male vocalist sings this enthusiastic Rock song. The tempo is fast with bright drumming, enthusiastic electric guitar harmony, keyboard accompaniment , groovy bass line. The song is youthful, enthusiastic, energetic, vital, vigorous and passionate rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/5keRbrVx-G4.wav"} +{"id": "5lZFGZXH20E", "caption": "This clip features a singular marimba being played. It is a low-quality recording of a performance wherein the performer plays some off-key notes. We hear applause after the performer stops playing.", "audio": "/zhanghaomin/datas/musiccap/music_data/5lZFGZXH20E.wav"} +{"id": "5mLYN-F2Oek", "caption": "The low quality recording features a R&B song that consists of echoing harmonizing vocals, alongside passionate male vocal singing over noisy percussion, punchy snare and kick hits, pulsating synth melody, synth pad chord, shimmering shakers and sizzling triangle. It sounds romantic, passionate and emotional - like something you would slow dance to with your partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/5mLYN-F2Oek.wav"} +{"id": "5mmUQUwr6tI", "caption": "This music is instrumental. The tempo is fast with an animated piano harmony of Jingle Bells. The music is upbeat, cheerful, happy, fun, joyful and vivacious.", "audio": "/zhanghaomin/datas/musiccap/music_data/5mmUQUwr6tI.wav"} +{"id": "5n8I-br2n1U", "caption": "a female voice is singing to a digital drum set along with a bass and old disco synthesizer sounds. The singer gets backed by a male singer and the crowd is singing along. There is clapping from the crowd. This song may be playing live at a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/5n8I-br2n1U.wav"} +{"id": "5nJr7iar6ZM", "caption": "This is a classic music piece belonging to the baroque era. There is a soprano male vocal singing at an extraordinarily high pitch. The melody is being played by the violin and the cello. There is an emotional atmosphere to this piece. It could be playing in the background at a classy restaurant. It could also work well in the soundtrack of an art movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/5nJr7iar6ZM.wav"} +{"id": "5pIdH6p3kuo", "caption": "The low quality recording features a raw innocent girl vocal singing over sloppy acoustic rhythm guitar chords. It sounds passionate and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/5pIdH6p3kuo.wav"} +{"id": "5qVc9y3TNnY", "caption": "This is a Pamiri folk song. The female vocalist is singing melodically accompanied by a choir of both male and female back vocals. A keyboard is playing the main tune while a mixture of loud electronic drums and percussion provide the rhythmic background. This piece has a playful atmosphere. It could be used in a dancing course that involves folk dances of the region.", "audio": "/zhanghaomin/datas/musiccap/music_data/5qVc9y3TNnY.wav"} +{"id": "5r4jLwjj_Ik", "caption": "This is a jazz music piece. There is a saxophone playing a solo in the lead. A tuba is playing the bass line. There is an electric guitar strumming chords. The rhythm is being played on the ride cymbal by the acoustic drums. The instrumentals have a sophisticated feel. This piece could be playing in the background at a classy restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/5r4jLwjj_Ik.wav"} +{"id": "5rjQU4vOIlw", "caption": "Here we have a live recording of a musician playing the harmonica in a bluesy style. The tone is warm and rich and the mood is reminiscent of a country western film.", "audio": "/zhanghaomin/datas/musiccap/music_data/5rjQU4vOIlw.wav"} +{"id": "5rsQHo-6DI4", "caption": "Mellow rock with a slow drum beat, acoustic strumming guitar, male and female vocalists singing in octaves.", "audio": "/zhanghaomin/datas/musiccap/music_data/5rsQHo-6DI4.wav"} +{"id": "5s0yPPrQWxs", "caption": "This is a British hip-hop music piece. There is a male vocal rapping in the lead. The beat in the background has its main melody being played by the acoustic guitar. A faint bass sound can be heard in the background. The rhythm is provided by an electronic drum beat. The atmosphere is hip and the sound is urban. This piece could be used in the soundtrack of a teenage drama movie that takes place in Great Britain.", "audio": "/zhanghaomin/datas/musiccap/music_data/5s0yPPrQWxs.wav"} +{"id": "5tNOauvQWQQ", "caption": "The low quality recording features a wide synth lead melody, synth pad chords and a bell impact at the very end, which slowly fades out. It sounds modern and kind of weird, due to the sudden bell impact.", "audio": "/zhanghaomin/datas/musiccap/music_data/5tNOauvQWQQ.wav"} +{"id": "5tRNPTLRZqI", "caption": "This is the live performance of a wedding music piece on the steel drum percussion. There is a unique feel to it. The recording has a gain issue that makes the drums give a peak noise during accented notes. If that could be resolved, it would make perfect wedding music in a tropical setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/5tRNPTLRZqI.wav"} +{"id": "5tt_GKV13G0", "caption": "This music is an instrumental with a groovy rhythm. The audio is of inferior quality making the sound muddled and difficult to comprehend. There is a steady rhythm in the background with the sound of a turn table, scratching , a catchy riff on the electric guitar and some sound caused by disturbance in electrical energy.", "audio": "/zhanghaomin/datas/musiccap/music_data/5tt_GKV13G0.wav"} +{"id": "5w3s2T0VBug", "caption": "The Ambient song features soft shimmering bells, mellow sustained strings, sustained low woodwinds and subtle wooden percussive elements, while there are birds chirping sounds in the background. It sounds relaxing and calming - like something that would put you in a zen mode.", "audio": "/zhanghaomin/datas/musiccap/music_data/5w3s2T0VBug.wav"} +{"id": "5xAzHL8Zlcs", "caption": "This audio contains a male voice talking. Then a short section of an orchestra is playing with a brass section and a lot of percussive hits. It instantly changes to someone playing a long note on a horn in a higher key. This is an amateur recording and may be playing during a documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/5xAzHL8Zlcs.wav"} +{"id": "5xBfKiQcMZQ", "caption": "A male vocalist sings this enthusiastic song. The tempo is fast with infectious drumming, groovy bass lines, funky electric guitar harmony and an energetic keyboard accompaniment with vocal backup. The song is energetic, high-spirited, youthful, infectious, pulsating and vigorous. This song is a popular Alternative Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/5xBfKiQcMZQ.wav"} +{"id": "5xIBQGMjiX4", "caption": "The low quality recording features harmonized male vocals singing over shimmering shakers, repetitive cowbell hits and acoustic rhythm guitar chord progressions. It is a bit noisy and loud, as it was probably recorded with the phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/5xIBQGMjiX4.wav"} +{"id": "5y2M_K3bUcQ", "caption": "The low quality recording features a groovy didgeridoo melody playing over wooden percussion. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/5y2M_K3bUcQ.wav"} +{"id": "5z60cbPEEaY", "caption": "This audio contains someone walking up and down the scales with a trumpet. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/5z60cbPEEaY.wav"} +{"id": "6-CMq6xw0fg", "caption": "The low quality recording features a pop song that consists of harmonizing male vocals singing over groovy bass, shimmering cymbals, \"4 on the floor\" kick pattern, claps, addictive synth brass melody and distorted, buzzy synth lead. It sounds energetic, happy and fun - like something you would hear on TV commercials.", "audio": "/zhanghaomin/datas/musiccap/music_data/6-CMq6xw0fg.wav"} +{"id": "6-MdbipzKS0", "caption": "This song is a lively duet by two male voices. The tempo is fast with amplified piano, infectious drumming; tambourine beats and synthesiser arrangements. The song is youthful,fun, happy, groovy, energetic, buoyant, and high spirited. This song is called Deep House.", "audio": "/zhanghaomin/datas/musiccap/music_data/6-MdbipzKS0.wav"} +{"id": "6-XEA0zqo8M", "caption": "The song is an instrumental piece. The song is medium tempo with a steady rhythm, groovy bass line, retro keyboard tones. The song is dance-like and entertaining. The song is a hip hop tune and an amateur production.", "audio": "/zhanghaomin/datas/musiccap/music_data/6-XEA0zqo8M.wav"} +{"id": "60OIHit4Q-M", "caption": "This is an Indian pop music piece. The female vocalist is singing in a heart-touching manner. The electric guitar is playing a gentle melody. The bass guitar is supporting the melodic background. The electronic drums and the electronic percussion provide a mid tempo rhythmic background. The overall atmosphere of the piece is sentimental. It could be used in the soundtrack of a Bollywood drama.", "audio": "/zhanghaomin/datas/musiccap/music_data/60OIHit4Q-M.wav"} +{"id": "60uuoSycuWE", "caption": "low fidelity recording of a child singing quietly while being accompanied by ukelele strumming a syncopated pattern and a loud woodblock playing a steady click on the backbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/60uuoSycuWE.wav"} +{"id": "60y9j_Dc-Xs", "caption": "This music is instrumental. The tempo is medium with a sharp melody of the xylophone. It is melodic, reverberating, minimalist with a festive ring to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/60y9j_Dc-Xs.wav"} +{"id": "614LdgrE13A", "caption": "This song features the sound of glass being shattered. There are no voices in this clip. A synth plays a backing sound and holds the chord for the duration of the clip. Toward the end, the sound of wind is played. There are no other instruments in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/614LdgrE13A.wav"} +{"id": "62C6TngDeXI", "caption": "Someone is playing fast paced traditional Irish song on a accordion while stomping his foot. This song may be playing live on a traditional event.", "audio": "/zhanghaomin/datas/musiccap/music_data/62C6TngDeXI.wav"} +{"id": "62L5kn1qFeY", "caption": "The low quality recording features a cover of a rock song and it consists of an arpeggiated acoustic guitar melody over which there is a soft female vocal singing. The recording is noisy, in mono and it sounds emotional, soft and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/62L5kn1qFeY.wav"} +{"id": "63jbksEqycQ", "caption": "This song is an operatic harmony. The tempo is slow with a soft piano accompaniment and choral vocal harmony. The song is soft, melodic, enigmatic, ethereal, mystical, magical, dreamy and enchanting. This music is a Choral Symphony.", "audio": "/zhanghaomin/datas/musiccap/music_data/63jbksEqycQ.wav"} +{"id": "63rqIYPHvlc", "caption": "Someone is beatboxing while doing a bassline with his voice. Finger snipping can be heard supporting the beat. This song may be playing at a talent show.", "audio": "/zhanghaomin/datas/musiccap/music_data/63rqIYPHvlc.wav"} +{"id": "64auWicQqZY", "caption": "This is a song that's led by the deep bellowing hum of the didgeridoo. We hear a wooden percussion instrument keeping a consistent timing in four over four tempo throughout the whole clip on each beat. There are two other percussion instruments, one deep and one in a higher register, and those play a rhythm intermittently throughout the clip. This kind of music is suitable for meditation or any kind of spiritual south asian experience.", "audio": "/zhanghaomin/datas/musiccap/music_data/64auWicQqZY.wav"} +{"id": "65KYS3lIRII", "caption": "This music is instrumental. The tempo is fast with electronic beats and rhythm on a DJ mixer. The music is youthful, hypnotic, groovy; burgeoning and trance .", "audio": "/zhanghaomin/datas/musiccap/music_data/65KYS3lIRII.wav"} +{"id": "669Fk7afszw", "caption": "An acoustic guitar is strumming chords while a banjo is playing a fast melody over it. In the background you can hear an upright bass playing a fast walking bassline. Also in the background noises of people speaking can be heard. This song may be playing live on the streets performed by buskers.", "audio": "/zhanghaomin/datas/musiccap/music_data/669Fk7afszw.wav"} +{"id": "66B46E_hrrk", "caption": "The song is an instrumental. The tempo is medium with a groovy drumming rhythm, percussive bass line, keyboard accompaniment and various percussive and sonic effects. The song is youthful and exciting with a trance element. The song is a modern tench pop dance tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/66B46E_hrrk.wav"} +{"id": "67S7s_jFXhc", "caption": "A male singer sings this hip hop melody with backup singers in vocal harmony. The song is medium tempo with a groovy drum rhythm, steady bass line and a grunge keyboard harmony. The song is exciting and energetic. The song has average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/67S7s_jFXhc.wav"} +{"id": "6807299U5eg", "caption": "The low quality recording features a traditional song that consists of a passionate female vocal singing over breathy flute melody, wooden percussion, keys chords and acoustic guitar chords. It sounds soulful, passionate and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/6807299U5eg.wav"} +{"id": "682ODyTqKyw", "caption": "The clip has a relaxing, chill, mellow vibe. It is a live recording outdoors, and features various sounds of skateboarders doing tricks. The song itself is a hip hop song that's relaxing and chill. There's an electric guitar riff, and a high pitched soulful vocal refrain.", "audio": "/zhanghaomin/datas/musiccap/music_data/682ODyTqKyw.wav"} +{"id": "68DacKw1hlE", "caption": "This is a pop/funk music piece. There is a male vocalist singing melodically in the lead. The main melody is being played by the keyboard while the bass guitar is playing a groovy bass line in the background. The rhythm consists of an electronic drum beat. The atmosphere is groovy. This piece could be used in the soundtrack of a crime/comedy movie, especially during the scenes where a character is trying hard to appear as a villain.", "audio": "/zhanghaomin/datas/musiccap/music_data/68DacKw1hlE.wav"} +{"id": "68XchGI6H-4", "caption": "A male vocalist sings this spirited Latin song. The tempo is fast with a syncopated piano harmony, spanish guitar accompaniment ,Congas and bongos percussion, pandeira beats , keyboard harmony and vocal backup. The music is a lively, energetic, enthusiastic, passionate, spirited and vital Latin Pop with a dance groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/68XchGI6H-4.wav"} +{"id": "69oU6LfyQ_4", "caption": "A female singer sings this live cover version of a famous song. The song is medium tempo with guitar accompaniment, crowds cheering and whistling and cameras clicking. The song has a poor audio quality and has a lot of ambient crowd noises,", "audio": "/zhanghaomin/datas/musiccap/music_data/69oU6LfyQ_4.wav"} +{"id": "6AC84nr6ckM", "caption": "This is an afro-cuban folk music compilation. There are male vocals singing in an energetic manner. There are acoustic guitars playing the main themes while upright bass is used for the lower range. The rhythmic background is provided by a variety of latin percussive instruments. There is a vibrant atmosphere. Parts of this recording can be used in latin dance courses as accompaniment pieces.", "audio": "/zhanghaomin/datas/musiccap/music_data/6AC84nr6ckM.wav"} +{"id": "6BitLl5Bnxw", "caption": "This instrumental song starts off with a repetitive synth melody and percussion. The percussion pauses and the sound of water splash is heard. The bass note continues to ring. During this pause, a three-note high pitched game sound is played. After the pause, the synth melody continues to play and a piano melody is played on top of that. The bass plays the root notes of the chords. The percussion plays a simple beat in common time.", "audio": "/zhanghaomin/datas/musiccap/music_data/6BitLl5Bnxw.wav"} +{"id": "6C0HoQe4Y-Y", "caption": "A child singer sings this passionate Latin melody. The song is slow tempo with steady drumming, tambourine percussions, a strong bass line and brass instruments playing countermelody. The song is spirited and passionate. The song has poor audio quality and has ambient crowd noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/6C0HoQe4Y-Y.wav"} +{"id": "6CaZAITdAsk", "caption": "The low quality recording features a wide arpeggiated piano melody, sustained strings melody, mellow woodwind melody and shimmering bells over which the passionate male vocalist is singing at the very end of the loop. There is also the sound of walking on concrete. It sounds mellow, soft and sad. There is also the sound of walking on concrete.", "audio": "/zhanghaomin/datas/musiccap/music_data/6CaZAITdAsk.wav"} +{"id": "6EwEo0JQkTg", "caption": "This is the live recording of a DJ performance. The DJ is modifying a hip-hop beat with the use of a turntable through the scratching technique. A repeated sitar sample can be heard in the beat. There is a strong and groovy bass line in the background. The rhythmic structure consists of a slightly fast-paced hip-hop electronic drum beat. There is a modern sounding, urban feel to it. This piece could be playing in the background at a sportswear shop. It could also be played at sports venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/6EwEo0JQkTg.wav"} +{"id": "6F8qv0JBWkE", "caption": "This piece is full of orchestra instruments playing a sequence full of rapid changes with a little darker emotions. Sounding gigantic, dangerous and heroic. This song may be playing at a live concert or for a scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/6F8qv0JBWkE.wav"} +{"id": "6FQ1nQ0FvgQ", "caption": "This audio contains male voices singing together an opera in a higher pitch creating harmonies. In the background you can hear strings playing. This song may be playing live in a theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/6FQ1nQ0FvgQ.wav"} +{"id": "6HQqly6duac", "caption": "The low quality recording features a live performance of guitar percussion. It sounds shimmering and groovy. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/6HQqly6duac.wav"} +{"id": "6II4JGJDyZo", "caption": "The low quality recording features a compilation of recordings where the first recording in the loop is a live performance that's distorted, loud and in mono. The second part of the recording is very noisy and it features bright bells, some resonating sounds and it sounds weird.", "audio": "/zhanghaomin/datas/musiccap/music_data/6II4JGJDyZo.wav"} +{"id": "6Ig6zwBn4b4", "caption": "The main element of the clip is an electric guitar with reverb and a tube screamer pedal. The guitarist plays an intricate lick and there seems to be some kind of piano or harpsichord as the backing instrument. There is also a synth pad which made the song feel a little transcendental.", "audio": "/zhanghaomin/datas/musiccap/music_data/6Ig6zwBn4b4.wav"} +{"id": "6J3X0whM_-4", "caption": "The low quality recording features a steel pans melody, shimmering hi hats, syncopated snare and \"4 on the floor\" kick pattern. It is a bit reverberant as it was played in a concert hall. There are some crowd cheering and applause sounds. It sounds exotic, fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/6J3X0whM_-4.wav"} +{"id": "6JJMlY3Go9s", "caption": "A male vocalist sings this emphatic rock. The tempo is medium with vigorous electric guitar, synthesiser arrangement, groovy bass line and intense drumming. The vocals are soft ,sad, lonely, poignant, mellow, and melodic in contrast to the intense instrumentation. This song is Blues-Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/6JJMlY3Go9s.wav"} +{"id": "6KXd7l5pThg", "caption": "This audio contains someone playing a didgeridoo using circular breathing for a continuous sound. This is an amateur recording. In the background you can hear birds chirping. This song may be playing live during a traditional performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/6KXd7l5pThg.wav"} +{"id": "6Kb0q9J8lPA", "caption": "A lot of male voices are chanting a mantra. Their voices reach from the low register up to the mid range. A drone pad sound is panned to the right side of the speakers along with a pluck playing single notes on top. The voices are also spread along the speakers and the whole recording is full of big reverb and a little bit of reverb. This song may be played while meditating or in an epic, heroic movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/6Kb0q9J8lPA.wav"} +{"id": "6KqFiP_ux5U", "caption": "The low quality recording features a soul song that consists of a passionate male vocal, alongside wide harmonizing female vocals, singing over smooth piano melody, wide sustained strings and subtle, arpeggiated electric guitar melody. It sounds heartfelt, emotional and uplifting - like something you would hear in church.", "audio": "/zhanghaomin/datas/musiccap/music_data/6KqFiP_ux5U.wav"} +{"id": "6L8066DGqcA", "caption": "This is a hip-hop beat. There is a turntable scratching sound and a hollering sample constantly repeated in the beat. Later on, a synth sound can be heard taking part in the melodic structure. The rhythm is provided by an electronic drum beat. The atmosphere is hip and aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/6L8066DGqcA.wav"} +{"id": "6N1LWG4aztA", "caption": "The music features a female voice singing an ascending melody. The rhythm section consists of a bass guitar, a pair of congas and a ride cymbal. An electric piano accompanies the singer with chords. In the background an electric guitar plays an accompaniment that combines melody and chords. Right at the end of the music excerpt a China cymbal can be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/6N1LWG4aztA.wav"} +{"id": "6OVb3rjcB3Q", "caption": "This clip features an electric guitar played through a distortion effects pedal. At the beginning, the sound is open. The guitar plays a power chord using down strokes. After changing settings on the pedal, a chord is strummed and then arpeggiated notes are played. This produces a 'closed' sound. There are no voices in this song. There are no other instruments in this clip. This clip can be played in a demo video of the distortion effect pedal.", "audio": "/zhanghaomin/datas/musiccap/music_data/6OVb3rjcB3Q.wav"} +{"id": "6OcoDIrbMtY", "caption": "This is a country/Americana music piece. There is a male vocalist with a gravelly voice singing in the lead. An acoustic guitar is playing a simple tune. There is a faint percussive element that can be heard in the background that resembles pinched harmonics coming from a guitar. The atmosphere is melancholic. This piece could be used in the soundtrack of a drama movie or a TV show during a scene of introspection where a character is experiencing dark thoughts.", "audio": "/zhanghaomin/datas/musiccap/music_data/6OcoDIrbMtY.wav"} +{"id": "6PWiDlWmPs0", "caption": "A male vocalist sings this romantic song. The tempo is medium fast with keyboard harmony, infectious drumming, steady bass lines and electronic guitar. The song is simple, mellow, tender, sentimental, emotional and mellow. This is a Romantic Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/6PWiDlWmPs0.wav"} +{"id": "6PquRVe1Wa4", "caption": "The low quality recording features a traditional song sung by flat male vocals over wooden, boomy percussion. The recording is in mono, a bit noisy and it sounds muddy, as the bass frequencies are overwhelming.", "audio": "/zhanghaomin/datas/musiccap/music_data/6PquRVe1Wa4.wav"} +{"id": "6Q5N1DfzGj0", "caption": "A lot of marimbas are being played with the same melody. Along with a bass marimba playing low notes as bassline. Maracas are providing the rhythm. This is an amateur recording. The audio-quality is not the best. This song may be playing for a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/6Q5N1DfzGj0.wav"} +{"id": "6QAZJ4H_5rA", "caption": "This audio contains a male voice talking rather than playing an e-guitar with a chorus effect. This audio may be playing for a sound tutorial/comparison.", "audio": "/zhanghaomin/datas/musiccap/music_data/6QAZJ4H_5rA.wav"} +{"id": "6QHfXuVLhe0", "caption": "This pop song starts off with the backing singers singing vocables in harmony. This is backed by percussion playing a simple beat. The bass plays a flourish ending on the root note of the next chord. The string section plays high pitched notes. The piano plays a flourish of ascending notes before the main female voice starts to sing the main melody. This is accompanied by the percussion continuing with the simple beat. The string section fades away. The bass plays a descending walk down and ends on a high note. This song has a romantic feel. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/6QHfXuVLhe0.wav"} +{"id": "6QfM3BRp-78", "caption": "This is an instrumental track played over a short film. It begins with the sound effects of a drink being prepared. Then the electric piano and the acoustic drums start playing a simple, groovy tune. The beginning part with the sound effects could be used as a sample for a beat or an animation film. The instrumentals could also be used as a loop in the making of a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/6QfM3BRp-78.wav"} +{"id": "6SB2FIU9SBc", "caption": "This song contains a loud organ sound playing a chord melody in the mid-higher register along with a piano panned to the left side of the speakers. The organ is slightly pulsating. A loud e- guitar is playing a simple short and monotone melody with a delay on the right side of the speakers. All the instruments use reverb. This song may be playing on a beach bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/6SB2FIU9SBc.wav"} +{"id": "6Sdu56gquJE", "caption": "A male vocalist sings this intense Rap. The tempo is slow with boomy bass drumming and atmospheric synthesiser. The music is minimalist with emphatic vocals. The song is a passionate, youthful,insightful,persuasive and intense Synth Rap.", "audio": "/zhanghaomin/datas/musiccap/music_data/6Sdu56gquJE.wav"} +{"id": "6Si3eGkmmy8", "caption": "Rhythmic African afrobeat music that sounds celebratory and fun. Busy hand percussion and mallet percussion play in an odd meter, accompanying group female vocals with a lead female vocalist. Feels organic and earthy.", "audio": "/zhanghaomin/datas/musiccap/music_data/6Si3eGkmmy8.wav"} +{"id": "6TSluKI0X54", "caption": "This clip features a home recording of a musical piece using low quality gear. The clip is of a bass guitar and the sound is captured on the video capturing device and not through a mixer. The bass is playing hammer ons and harmonic notes. The notes are played on a particular scale. No percussion is played and no other instruments are featured in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/6TSluKI0X54.wav"} +{"id": "6Tf5IwOHBlw", "caption": "A harp playing solo.", "audio": "/zhanghaomin/datas/musiccap/music_data/6Tf5IwOHBlw.wav"} +{"id": "6UJhTZgnVro", "caption": "This song contains a male voice singing together with kids singing and giggling. A piano is playing a melody along with other keyboard sounds. This song may be playing in a kids tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/6UJhTZgnVro.wav"} +{"id": "6VJ_auuKzss", "caption": "A female vocalist sings this enthusiastic pop. The tempo is fast with an energetic and punchy drumming, synthesiser arrangements and flute melody. The song is youthful, enthusiastic, upbeat, vivacious, vibrant with a dance groove. This song is contemporary pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/6VJ_auuKzss.wav"} +{"id": "6XHdybfV5Cw", "caption": "This is a pop punk music piece. The male vocals are singing melodically. Initially, there is a clean sounding electric guitar playing the main melody. Then, a rising pattern starts to play and the distorted electric guitar takes the place of the clean electric guitar. The bass guitar is playing in the background. The rhythm is provided by an upbeat acoustic drum beat. The atmosphere is hard-hitting. This piece can be used in the soundtrack of a teenage drama as the opening theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/6XHdybfV5Cw.wav"} +{"id": "6XZGmRuaOfo", "caption": "This is a techno trance music piece being performed on the keyboard. It is an instrumental piece. Initially, a brief tune is being played with the piano sound. Then, a wobbly bass and an electronic drum beat starts playing. The atmosphere is energetic and the sound is urban. This piece could be used in the soundtrack of a mobile car racing game.", "audio": "/zhanghaomin/datas/musiccap/music_data/6XZGmRuaOfo.wav"} +{"id": "6YXjJ6ABnZU", "caption": "A male singer sings this rapping vocals with a backup singer. The song is medium tempo with a groovy drum rhythm, disc scratching sounds, strong bass line and string accompaniment. The song is groovy and has a dance rhythm. The song audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/6YXjJ6ABnZU.wav"} +{"id": "6Yh7Cdm2GgY", "caption": "The song is an instrumental. The song is medium tempo with drums playing in march style and a brass section plays this triumphant harmony. The song is spirited and gives an adrenaline rush. The song is a western movie soundtrack with an average sound quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/6Yh7Cdm2GgY.wav"} +{"id": "6_zzu2KON6c", "caption": "A male guitarist plays a cool guitar like on an electric guitar. The song is medium tempo with a guitar solo with heavy a[echoes played though a guitar amplifier and no other instrumentation. The song is bluesy and passionate. The song is a casual blue slick played on a guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/6_zzu2KON6c.wav"} +{"id": "6ayVxYbKBe0", "caption": "This music is an electric guitar instrumental Rock. The tempo is medium with an electric guitar lead. The music is loud and boomy with an intense riff. The audio quality is inferior so the sound is muffled and muddy. The music however is energetic, youthful, spirited and enthusiastic.", "audio": "/zhanghaomin/datas/musiccap/music_data/6ayVxYbKBe0.wav"} +{"id": "6c1vNidtVTc", "caption": "This is a military anthem sung by male voices in the French language. The choir sings in a grave but determined manner, implying a feeling of perseverance. There are no instruments. This piece could be used in parades or historical content related to the French army.", "audio": "/zhanghaomin/datas/musiccap/music_data/6c1vNidtVTc.wav"} +{"id": "6cQbxwbBqqI", "caption": "This audio contains someone playing a chord on a ukulele. A male voice is talking in the midrange. This is an amateur recording. This may be playing live while taking a ukulele workshop.", "audio": "/zhanghaomin/datas/musiccap/music_data/6cQbxwbBqqI.wav"} +{"id": "6cQjwXNY4sc", "caption": "The song is an instrumental. The song is medium tempo with a steady drumming rhythm, cymbal crashes, groovy bass line and various percussion hits. The song is youthful and energetic. The song has an average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/6cQjwXNY4sc.wav"} +{"id": "6dFCMXNlmzQ", "caption": "This song is a lively instrumental. The tempo is medium fast with an enthusiastic accordion harmony and acoustic guitar accompaniment. The music is spirited, melodious, warm, cheerful, happy, vivacious and colourful. This music is a Folk song instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/6dFCMXNlmzQ.wav"} +{"id": "6elnFyuUnaU", "caption": "This audio contains someone playing a melody on a horn with reverb on it. This song may be playing as a solo in an orchestra performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/6elnFyuUnaU.wav"} +{"id": "6evOjRxZlHI", "caption": "The Soul song features a passionate male vocal singing over a shimmering crash cymbal, sustained strings melody and mellow arpeggiated piano melody. At the very beginning there are some sizzling bells. It sounds romantic and heartfelt - like something you would want to sing to your partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/6evOjRxZlHI.wav"} +{"id": "6gTrMRQPZMU", "caption": "The low quality recording features groovy organ keys played over punchy kick and snare hits, shimmering cymbals and groovy bass guitar. It sounds energetic, passionate and uptempo. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/6gTrMRQPZMU.wav"} +{"id": "6iZ49s7eH5g", "caption": "The Rock song features a groovy piano melody followed by passionate electric guitar melody, church organ chord progression, strummed acoustic rhythm guitar chords, shimmering cymbals, punchy snare and mellow kick hits. It sounds emotional, soulful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/6iZ49s7eH5g.wav"} +{"id": "6ieXDFjLKNo", "caption": "This audio is an instrumental playing in the background. The music is sinister and anticipatory of something bad. There are ambient sounds of nature like roaring, grunting, scuffling, wild boar squealing,birds chirping loudly and painful cries, indicative that this is an animal being hunted.", "audio": "/zhanghaomin/datas/musiccap/music_data/6ieXDFjLKNo.wav"} +{"id": "6iyinlZEgS4", "caption": "This audio clip features a tom roll followed by a descending slide on the bass. This is followed by the sound of two different calling bells one after the other. Four different voices call out numbers one through four in ascending order one after the other. This is followed by a pattern played on a drum machine. This song can be played at a DJ party.", "audio": "/zhanghaomin/datas/musiccap/music_data/6iyinlZEgS4.wav"} +{"id": "6jZ8VNANHwM", "caption": "The music features a girlish female voice singing a sparse melody. The bass guitar and drums drive the pulse of the music but the drums play a more active role in that regard. Towards the middle of the music excerpt a crescendo leading into an orchestra hit can be heard. After this, a calming synth pad sound can be heard providing harmonic context.", "audio": "/zhanghaomin/datas/musiccap/music_data/6jZ8VNANHwM.wav"} +{"id": "6jdeSAmkzEU", "caption": "Someone is playing a distorted e-guitar solo melody with a lot of reverb over another e-guitar finger picking chords. This is an amateur recording. This song may be playing guitar at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/6jdeSAmkzEU.wav"} +{"id": "6jeq5lP5Up0", "caption": "A male singer sings this poignant melody. The tempo pop is slow with a steady drumming rhythm, cymbal crashes, guitar accompaniment, keyboard organ accompaniment and a strong bass line. The song is a poignant love song.", "audio": "/zhanghaomin/datas/musiccap/music_data/6jeq5lP5Up0.wav"} +{"id": "6k4lcF9IGUk", "caption": "This R&B song features a male voice singing the main melody. Another male voice sings a high pitched melody after the main voice pauses. This is accompanied by a piano playing chords in the background. In between, there are two banging sounds. At the end, hand claps are heard. There are no other instruments heard in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/6k4lcF9IGUk.wav"} +{"id": "6k6tF0s0lNs", "caption": "This audio contains someone playing a very distorted e-guitar melody in the midrange. This song may be playing guitar at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/6k6tF0s0lNs.wav"} +{"id": "6lPgzqrvHHw", "caption": "The low quality recording features a jazz orchestra live performance and it consists of synchronized brass melody played over energetic drums and groovy bass. The recording is vintage and therefore a bit noisy and in mono, but also passionate and upbeat. Sounds like something you would hear in old movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/6lPgzqrvHHw.wav"} +{"id": "6lPw0wKu7_M", "caption": "This audio contains someone playing a big acoustic drum set with a lot of fill-ins before breaking into the next part of the song. It sounds as if it is the big finale. With loud hits on the cymbals a e-bass is playing a long note and the organ is playing loud chords in the higher register. This song may be playing live at a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/6lPw0wKu7_M.wav"} +{"id": "6nWWTNVRDjw", "caption": "A male vocalist sings this upbeat Arabic pop. The tempo is fast and enthusiastic with intense bass lines, keyboard arrangement , vigorous drumming, violin symphony, oud accompaniment with vocal backup and sound of clapping and tambourine beats. The song is energetic, vivacious, enthusiastic, engaging and compelling with a high energy dance vibe. This song is contemporary Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/6nWWTNVRDjw.wav"} +{"id": "6o6DsSnbpxE", "caption": "This song contains a male voice singing sounding sad. Drum and percussion are playing a reggae rhythm along with two e-guitars playing. One a melody panned to the right side of the speakers and another short rhythmic strokes as a rhythmic element. The bass is playing its own melody. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/6o6DsSnbpxE.wav"} +{"id": "6og50XOZeIk", "caption": "This jazz song features percussion playing a fast tempo beat. This is accompanied by a double bass playing the bass part of the song. There are no voices in the song. This is an instrumental song. After the music pauses, a male voice narrates his part. This song can be played in a movie involving a bank robbery.", "audio": "/zhanghaomin/datas/musiccap/music_data/6og50XOZeIk.wav"} +{"id": "6oqbYipROOs", "caption": "The low quality recording features a traditional song that consists of a breathy flute melody in the right channel and acoustic guitar chords in the right channel of the stereo image, followed by wooden percussion, simple bass and arpeggiated string melody. It sounds soulful and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/6oqbYipROOs.wav"} +{"id": "6pHo6fPdPvM", "caption": "Someone is playing a bass melody through a distortion effect. This song may be playing bass at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/6pHo6fPdPvM.wav"} +{"id": "6ragcEJVErI", "caption": "A male vocalist sings this energetic song. The tempo is fast with a spirited piano accompaniment and ambient street noises like vehicles, people talking and breeze. There is a sound of clapping and cheering indicating that this is a live street performance. The audio quality is inferior causing static and muffled sounds.This song is a cheerful, animated, spirited, happy, chirpy and bouncy pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/6ragcEJVErI.wav"} +{"id": "6sWVG6GyJBU", "caption": "This song contains a piano playing a melody in the mid range and also in the higher register. A flute is adding another melody in the mid range. A digital drum is holding a simple groove before dropping out completely. A male voice is softly rapping/talking in the mid range then another male with an effect takes over singing in a higher pitch. In the background you can hear strings underlaying chords. This song may be playing with headphones daydreaming.", "audio": "/zhanghaomin/datas/musiccap/music_data/6sWVG6GyJBU.wav"} +{"id": "6u1ckcErgcQ", "caption": "The Funk song features a passionate female vocalist talking and singing over funky wide electric guitars and some guitar licks in the right channel, followed by smooth synth keys, punchy snare hits, soft kick hits, bouncy hi hats, soft crash cymbals and funky bass guitar. What makes this song low quality is the stereo imbalance - regardless, it sounds funky.", "audio": "/zhanghaomin/datas/musiccap/music_data/6u1ckcErgcQ.wav"} +{"id": "6uIOGE36tWo", "caption": "This audio contains someone playing a melody on a guitar in the midrange while someone else is strumming a melody on a cuatro in a higher key. Someone is playing a tambourine while a clarinet is playing a fast lead melody. This audio may be playing as a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/6uIOGE36tWo.wav"} +{"id": "6vM7Kv42Uv0", "caption": "The low quality recording features a pop song that consists of stuttering vocal effects, flat male vocal speaking alongside female vocal, bleating goat sound effect, some percussive elements, boomy bass, crispy snare and shimmering hi hats. There are some scratching effects in the left channel of the stereo field. It sounds funny and like it is a parody song.", "audio": "/zhanghaomin/datas/musiccap/music_data/6vM7Kv42Uv0.wav"} +{"id": "6vRBp8jo40Q", "caption": "The instrumental music features a string section playing an ascending long-note melody while at the same time providing harmonic support. A harp is playing arpeggios. Although it feels as if time passes slowly, the tempo is medium. Listening to this music I get a sense of profoundness that's moving me. This music could work well as the soundtrack for a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/6vRBp8jo40Q.wav"} +{"id": "6xxu6f0f0e4", "caption": "This hip-hop song features a male voice singing the main melody. As the voice sings the higher register, he starts to sing in falsetto. After his line, other voices sing a line in harmony. This is accompanied by programmed percussion playing a trap beat. Synth pads play an epic fill in the background. The bass plays the root notes of the chords. The mood of this song is motivational. This song can be played in a sports themed movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/6xxu6f0f0e4.wav"} +{"id": "6yB6plsrjO0", "caption": "Music that promotes focus. The music is instrumental and the instruments are all electronic. Synthesized string harmonies, harp plucks and bell sounds blend over a driving bass. The music is tranquil, yet focused. Good for an IT training video.", "audio": "/zhanghaomin/datas/musiccap/music_data/6yB6plsrjO0.wav"} +{"id": "6zgvEiJJrM8", "caption": "This pop song starts with children's voices singing a melody. This is accompanied by a tuba playing the low registers. A string section plays a repetitive staccato phrase. This is followed by a phrase played on a trumpet and a descend run played on bells. The children's voice repeats the first melody once again. In between the sound of church bells is played. This song has a holiday feel. This song can be played in the intro credits of a holiday movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/6zgvEiJJrM8.wav"} +{"id": "7-mNJ4IUY5Q", "caption": "The music features for the most part an instrumental that makes use of synth sounds and a drum beat using sampled drums and claps. Towards the end of the music excerpt a female voice starts singing a simple melody and another female voice can be heard singing brief interventions in the background. The music is highly accentuated.", "audio": "/zhanghaomin/datas/musiccap/music_data/7-mNJ4IUY5Q.wav"} +{"id": "70pyoqX0U9Y", "caption": "The song is an instrumental. The song is medium tempo with various explosive sounds played percussively, along with counter beeps. The song is exciting and very novel. The song is probably the theme song of a modern video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/70pyoqX0U9Y.wav"} +{"id": "71KE7B1vvdI", "caption": "The low quality recording features an afrobeats song that consists flat male vocal, alongside wide harmonizing male vocals, rapping over sustained synth lead melody, short synth melody, groovy bass, soft kick hits, punchy snare, shimmering shakers and syncopated toms. The mix is bad, thus it sounds kind of unprofessional, but still energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/71KE7B1vvdI.wav"} +{"id": "71hqRT9U0wg", "caption": "A female vocalist sings this lively Children\u2019s Song. The tempo is fast with a cheerful acoustic guitar and ukulele accompaniment along with clapping. The song is lively, upbeat, engaging, energetic, simple and enthusiastic. The song is a children\u2019s nursery rhyme with the catchy , simple tune and lyrics meant to make learning fun. It is engaging, interactive, instructional, educational teaching coordination.", "audio": "/zhanghaomin/datas/musiccap/music_data/71hqRT9U0wg.wav"} +{"id": "72_Hk1cdoxk", "caption": "This low quality audio features a salsa song. A male voice sings the main melody. The audio starts off with a solo being played on a trumpet. This is accompanied by percussion playing a salsa beat. A keyboard plays chords in salsa style. Other instruments are not heard clearly due to the low quality of the audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/72_Hk1cdoxk.wav"} +{"id": "73YTz8RC2Fo", "caption": "The low quality recording features a passionate male vocal singing over playback instrumental that consists of straight piano chord progression. It is noisy and reverberant, as the singer is singing in a larger room. It sounds emotional, passionate and powerful.", "audio": "/zhanghaomin/datas/musiccap/music_data/73YTz8RC2Fo.wav"} +{"id": "74p3DLeDCHE", "caption": "The excerpt features a single chord played on an unamplified electric guitar. After this, one can hear the sounds made by someone walking in the near vicinity.", "audio": "/zhanghaomin/datas/musiccap/music_data/74p3DLeDCHE.wav"} +{"id": "752bW5cjXzw", "caption": "This folk rock song features an electric guitar playing the main melody in the form of a solo. This is accompanied by fast paced percussion. Another guitar plays a galloping rhythm. A violin plays staccato notes at a fast tempo and the notes follow the root notes of the chords but at higher octaves. This is an instrumental song with no voices. This song has a hippie feel. This song can be played in a retro movie with a hippie theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/752bW5cjXzw.wav"} +{"id": "75UH33tO0Bo", "caption": "This country song features a female voice singing the main melody. The melody is a contemporary country song melody. This is accompanied by the kick drum playing on every count. A synth is playing a repetitive melody in the background using two note groups. A guitar plays chords in the background. The bass plays the root notes of the chords. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/75UH33tO0Bo.wav"} +{"id": "75_dMqpSM4o", "caption": "This song features a male voice singing the main melody. The quality of recording is low. The musical instruments are not clearly distinguishable. The voice is accompanied by simple percussion playing in common time. The bass plays a soul type groovy bassline. This song is romantic. This song can be used in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/75_dMqpSM4o.wav"} +{"id": "769EHEG4Mqc", "caption": "The song is an instrumental. The tempo is medium fast with a strong techno drumming groove, strong bass line, keyboard harmony and various percussion hits. The song is energetic and passionate. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/769EHEG4Mqc.wav"} +{"id": "76ON0Ixrr9s", "caption": "The low quality recording features an electric guitar melody playing. The melody fades out in the beginning and it starts playing again in the second part of the loop, where it has an echoing effect on. It gives off psychedelic vibes. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/76ON0Ixrr9s.wav"} +{"id": "770ZkZhGy6A", "caption": "This song has a lot of percussive elements. Also a catchy melody with arpeggios in the background rising and falling. A kick is playing every beat while motorbike sounds evade the soundscape. This song may be playing as an advertisement for a product.", "audio": "/zhanghaomin/datas/musiccap/music_data/770ZkZhGy6A.wav"} +{"id": "78BtX0oNXHQ", "caption": "This audio contains acoustic drums playing a kick on every beat along with a simple e-bass line. In the background you can hear the sound of wind and a wolf's howling. A tambourine like instrument reminds of christmas and a flute like instrument is playing an uplifting melody along with a piano sound hitting short chords in the mid to higher register. This song may be playing in a funny video around christmas time.", "audio": "/zhanghaomin/datas/musiccap/music_data/78BtX0oNXHQ.wav"} +{"id": "78S8DnvLQDY", "caption": "This is an amateur recording of a live beatboxing performance. The beatbox is being performed initially slowly and then at a fast tempo. The recording is a bit dated, so the quality is quite low. The sounds from the setting of the recording such as the crowd cheering for the performer can be heard. Parts of this recording can be lifted as samples to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/78S8DnvLQDY.wav"} +{"id": "79tuMIiWMZ4", "caption": "This is a nu-metal piece performed live on the stage. There is a male vocal shouting the words at the end of the song. The electric guitar is repeating the same tune while the bass guitar is playing in the background. The drummer plays fills on the acoustic drums to provide the rhythmic background. There is a high energy atmosphere to this piece. It could be used in an ad targeted for teenagers.", "audio": "/zhanghaomin/datas/musiccap/music_data/79tuMIiWMZ4.wav"} +{"id": "7AC9RqECN5k", "caption": "This choir song features male and female voices. The voices sing different parts. The female voices sing the soprano and alto parts. The male voices sing the tenor and bass parts. The voices sing in harmony. This is an acapella song. There are no instruments in this song. The song is a gospel hymn. This song can be played in a historic animation movie before a battle scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/7AC9RqECN5k.wav"} +{"id": "7B1OAtD_VIA", "caption": "This audio contains a big soft kick drum hit along with a soft bassline changing into an even deeper octave. On top of that, violins and an acoustic guitar-like instrument are playing a melody. This recording has some reverb on it. This song may be playing in an adventure movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/7B1OAtD_VIA.wav"} +{"id": "7DIPyJB4osY", "caption": "The low quality recording features a live performance of groovy wooden percussion. There is a wooden impact in the form of a wooden stick falling on the floor - which is a part of the groove. The recording is a bit noisy, due to a ventilation system, which also makes it very intimate.", "audio": "/zhanghaomin/datas/musiccap/music_data/7DIPyJB4osY.wav"} +{"id": "7EvLwfwRrqA", "caption": "This classical song features an orchestra playing a complex song. The string section plays the main melody. The horn section plays the bass harmony. The brass section plays the backing parts. The bass is played on a cello. At the beginning there is no percussion. Toward the end, the timpani is played as part of the percussion. The melody is complex. The mood of this song is epic and victorious. This song can be played in a successful bank robbery scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/7EvLwfwRrqA.wav"} +{"id": "7FHzw4HV75Y", "caption": "The Regional Mexican song features a soft piano melody, rhythm acoustic guitar, smooth bass, addictive brass melody and passionate male vocal singing on top of it. It sounds soft, mellow, passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/7FHzw4HV75Y.wav"} +{"id": "7FkuqqdWRhw", "caption": "This is a pop R & B song with an electronic influence. We hear layers of synths driving the melodic component of the instrumental. The first synth has a repeated rapid motif that has the same beeping tone as a video game. The second synth is fuzzy and sustained.", "audio": "/zhanghaomin/datas/musiccap/music_data/7FkuqqdWRhw.wav"} +{"id": "7Ht_Vu1D8nc", "caption": "This music is a Bagpiper Instrumental. The tempo is slow with a droning , chanting melody. The melody of the music has middle eastern influences. The droning sound is incessant and hypnotic. It is charming ,sharp, and captivating.", "audio": "/zhanghaomin/datas/musiccap/music_data/7Ht_Vu1D8nc.wav"} +{"id": "7ITwarmdyfI", "caption": "This music is an instrumental with a lot of vocalisation and animated sounds. There are sounds of swishing, water bubbling, guitar string plonking, acoustic guitar riff, camera clicking pictures, kids screaming in glee, cheering and clapping. This music seems to be an introduction to a Show.", "audio": "/zhanghaomin/datas/musiccap/music_data/7ITwarmdyfI.wav"} +{"id": "7IllUjk5fk0", "caption": "Low pitched female singer demonstrating vocal virtuosity in free time accompanied by bird sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/7IllUjk5fk0.wav"} +{"id": "7IndxxjZe1c", "caption": "70's jazz fusion featuring an eccentric male singer accompanied by drum kit, electric bass, electric piano and mallet percussion all playing odd meters and complex rhythms and staccato band hits. The music is quirky and complicated and features a drum fill.", "audio": "/zhanghaomin/datas/musiccap/music_data/7IndxxjZe1c.wav"} +{"id": "7J6U-HE3Lko", "caption": "This song contains a acoustic drum playing a lot on the toms before changing to a groove with strong crash hits. A e-guitar is playing single notes in a very high pitch while the other e-guitar is playing a melody along with the bass in a lower register. A male voice is singing, almost streaming a melody on top. A male backing voice is supporting in between the breaks of the main singer. In the background you can hear male voices shouting. That seems not to be a part of the music. This song may be playing while running with headphones.", "audio": "/zhanghaomin/datas/musiccap/music_data/7J6U-HE3Lko.wav"} +{"id": "7JE2eBK1f9M", "caption": "This is a contemporary classical music piece. It is an instrumental piece. There is a strings section playing the chords while the violin in the lead is playing a dramatic tune. The piano is playing accentuated notes. There is a percussion line in the rhythmic background. There is a dramatic atmosphere that is full of suspense. This piece could be used in the soundtrack of a sci-fi drama movie, especially during the scenes where a big revelation is about to take place.", "audio": "/zhanghaomin/datas/musiccap/music_data/7JE2eBK1f9M.wav"} +{"id": "7JMN4DdhwsM", "caption": "This music is instrumental. The tempo is slow with a ukelele melody. The musician plays two notes in monotone which sounds like the instrument is being tuned. This clip is a tutorial on how to tune a ukulele.", "audio": "/zhanghaomin/datas/musiccap/music_data/7JMN4DdhwsM.wav"} +{"id": "7KCikXm6hic", "caption": "The Folk song features a sustained string, low bass, subtle tinny bells melody and passionately played breathy and reverberant flute melody. There are some foley effects from the flute which could be quieter in the mix. It sounds very traditional, cinematic and cultural.", "audio": "/zhanghaomin/datas/musiccap/music_data/7KCikXm6hic.wav"} +{"id": "7KIn0zojwu8", "caption": "This audio contains someone playing a ballad on a piano then a male voice starts talking and the piano-playing ends. This song may be playing at home practicing piano.", "audio": "/zhanghaomin/datas/musiccap/music_data/7KIn0zojwu8.wav"} +{"id": "7L5HQ4AJyLc", "caption": "The song is a hardcore, fiery and intense rock song. There are layers of electric guitar that are overdriven and drums that are powerful. There's a breakdown section that sees snare rolls and a motif on the electric guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/7L5HQ4AJyLc.wav"} +{"id": "7LGLhQFiE0s", "caption": "A male vocalist sings this soft melody. The tempo is slow with soft , ambient piano /keyboard accompaniment. The song is mellow,melodic, romantic, soothing, emotional, idyllic, charming and dreamy. There is a female vocal at the onset of this clip indicating that this could be a duet.", "audio": "/zhanghaomin/datas/musiccap/music_data/7LGLhQFiE0s.wav"} +{"id": "7LlKoQAvXUc", "caption": "A female singer sings this beautiful melody with vocal harmony. The song is medium tempo with a piano accompaniment, steady drumming rhythm, strong bass drum kicks and a steady bass line. The song is melancholic and emotional. The song is a modern Christmas carol.", "audio": "/zhanghaomin/datas/musiccap/music_data/7LlKoQAvXUc.wav"} +{"id": "7LlnLjZOqVI", "caption": "This music is instrumental . The tempo is medium fast with a catchy drumming rhythm and turntable effect with a vocal riff. The music is youthful, engaging, groovy and buoyant. This is a tutorial on DJ scratching techniques.", "audio": "/zhanghaomin/datas/musiccap/music_data/7LlnLjZOqVI.wav"} +{"id": "7Msk_hkz6zk", "caption": "This song is a spirited duet in foreign language . The tempo is fast with male and female vocals, animated digital drums and synthesiser arrangement . The song is upbeat, catchy, engaging, punchy, buoyant and has a nice dance groove. This music is contemporary Regional Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/7Msk_hkz6zk.wav"} +{"id": "7MuFNZHhrOE", "caption": "This is the gameplay recording of a video game. A lot of sound effects such as jumping, swinging and shouting related to the video game can be heard. There is an orchestra playing the theme that is composed of strings, brass and percussion. The atmosphere is dramatic and adventurous. Samples from this recording could be used in soundboards or in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/7MuFNZHhrOE.wav"} +{"id": "7Mv4eKPe850", "caption": "The low quality recording features a live performance of a rock song that consists of an energetic female vocal singing over electric guitar chords, punchy snare and kick hits and distorted bass guitar. The recording is very noisy and buzzy, in mono, muffled and messy, as it was probably recorded with a phone. It still sounds energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/7Mv4eKPe850.wav"} +{"id": "7NF2kcEfMBI", "caption": "An instructional guitar lesson featuring a male instructor speaking over nylon string guitar playing a picked single note melody featuring slurring, or hammer-ons and pull-offs.", "audio": "/zhanghaomin/datas/musiccap/music_data/7NF2kcEfMBI.wav"} +{"id": "7NnvEryyYdo", "caption": "This is a cumbia piece. There is a female vocal singing seductively joined by male back vocals singing in the chorus. The trumpet is playing the main melody joined by the piano and the bass guitar in the background. Latin percussion playing a cumbia beat provides the rhythmic background. The atmosphere of the piece is very playful. The ideal setting for this piece can be a latin dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/7NnvEryyYdo.wav"} +{"id": "7NtM1MM76s0", "caption": "The low quality recording features a drum roll solo, followed by laughter. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/7NtM1MM76s0.wav"} +{"id": "7OgH3B49_E4", "caption": "This is an industrial metal piece. The male vocalist in the lead is singing using the fry scream technique. The distorted electric guitar is playing a heavy riff while there is a groovy bass line. There is a loud metal beat being played by the acoustic drums in the rhythmic background. Industrial sound effects can be heard which are distinctive to the industrial and nu metal scenes. The atmosphere is aggressive and energetic. This piece could be played at a rock/metal bar. It could also be included in the soundtrack of an action movie/video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/7OgH3B49_E4.wav"} +{"id": "7OjXHfVoI64", "caption": "This song is an instrumental interlude of the Gospel song \u2018Thorns in the Straw. The music is slow with a melancholic trombone and tuba harmony, acoustic guitar accompaniment , bass, steady drumming,and synthesiser arrangements. The music is soft, mellow, poignant,pensive, sentimental,emotional, reflective and serene. This song is a Gospel Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/7OjXHfVoI64.wav"} +{"id": "7PtHb9jQCtg", "caption": "This is an amateur recording of a rock music concert. There is an electric guitar playing the main tune while another electric guitar is starting to play a solo. A bass guitar can be heard in the background playing the root notes of the tune. There is a loud acoustic drum beat in the rhythmic background. The recording is a bit outdated so the quality is pretty low.", "audio": "/zhanghaomin/datas/musiccap/music_data/7PtHb9jQCtg.wav"} +{"id": "7RUkkhkqyUw", "caption": "This is an Afropop music piece. There is a male vocalist singing melodically. The melody is being played by the piano and the keyboard while the rhythmic background consists of an electronic drum beat. There is a sentimental atmosphere to the piece. This piece can be used in the soundtrack of a drama TV series taking place in Africa.", "audio": "/zhanghaomin/datas/musiccap/music_data/7RUkkhkqyUw.wav"} +{"id": "7RtQpW2dSU4", "caption": "The low quality recording features a rock song that consists of a passionate female vocal, alongside harmonizing background female vocals, singing over wide acoustic guitar chords, groovy bass, punchy kick and snare hits. It sounds addictive and easygoing, even though the recording is a bit messy.", "audio": "/zhanghaomin/datas/musiccap/music_data/7RtQpW2dSU4.wav"} +{"id": "7S3fU4RHabw", "caption": "The music has a calming effect. It's a traditional chinese type of song, with a zheng being the lead instrument used for the melody. The song would be suitable for meditation, relaxation, a massage, or any serene environment.", "audio": "/zhanghaomin/datas/musiccap/music_data/7S3fU4RHabw.wav"} +{"id": "7TmKzUgWiRU", "caption": "This is a multi track audio. There are several things happening. There\u2019s an energetic song in the background with enthusiastic vocals, drumming and trumpets. There\u2019s a loud whirring of an engine, like a chain saw, beeps and a phone dial tone. The audio is loud, confusing, chaotic, boisterous,unrelated , noisy, loud, dissonant and unpleasant.", "audio": "/zhanghaomin/datas/musiccap/music_data/7TmKzUgWiRU.wav"} +{"id": "7Us4WHDmfeA", "caption": "The low quality recording features a folk song that consists of a groovy accordion melody, strings melody, acoustic rhythm guitar, energetic drums and some crowd male chants and wide claps. It sounds energetic, fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/7Us4WHDmfeA.wav"} +{"id": "7V0G65FK2VQ", "caption": "The song is an instrumental guitar solo. The song tempo is medium with a racy electric guitar solo with a show of technique of note bending, tremolo and playing rhythmically. The song is home video and an average quality recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/7V0G65FK2VQ.wav"} +{"id": "7Vjp9y6wvkY", "caption": "This song is a soothing instrumental. The tempo is slow with a melancholic violin harmony, banjo and resonator accompaniment, sound of chimes and a sharp tinkle. The music is soft, soothing, melancholic, serene, meditative, pensive and nostalgic. The music uses country style instrumentation.", "audio": "/zhanghaomin/datas/musiccap/music_data/7Vjp9y6wvkY.wav"} +{"id": "7WR-hMV2RKs", "caption": "The low quality recording features a steel drum solo melody over playback instrumental of urban latin song that consists of groovy synth bass, wide brass melody, sizzling synths, syncopated snare and punchy \"4 on the floor\" kick pattern. It sounds addictive, passionate and upbeat. The steel drum is reverberant due to the fact that it was recorded in a medium size room.", "audio": "/zhanghaomin/datas/musiccap/music_data/7WR-hMV2RKs.wav"} +{"id": "7WZwlOrRELI", "caption": "This is a k-pop song with a bouncy and upbeat feel. The instrumental mainly revolves around an intricate bassline and its interplay with the four on the floor percussive pattern. The vocalist has a gentle and seductive voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/7WZwlOrRELI.wav"} +{"id": "7XMqcbZKNNw", "caption": "The music is purely instrumental and so it features no human voice. More gamelans are played but by using different techniques. Other metallic percussion instruments can be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/7XMqcbZKNNw.wav"} +{"id": "7XQN9XDnRm4", "caption": "The song is led by a theremin whistle which plays high pitched tones and a harp playing arpeggios in the background. The feel of the song is soothing, tranquil, ethereal - and makes you feel as if you are peacefully sitting in an otherworldly environment.", "audio": "/zhanghaomin/datas/musiccap/music_data/7XQN9XDnRm4.wav"} +{"id": "7YWMPBHKdyY", "caption": "This song features a shofar playing the main melody. This is accompanied by a synth playing chords in the background. There are no other instruments in this song. There are no voices in this song. This song can be played in a sad scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/7YWMPBHKdyY.wav"} +{"id": "7YtKrL6ScXA", "caption": "This song contains an e-piano playing a major and minor chord melody along with a minimalistic digital drum groove that has a delay on it. A female voice is singing with a little reverb on her voice. The song sounds minimalistic. There is a lot of room for the voice to sing and for the other instruments. A shaker sound is spun to the right side of the speaker. This song may be playing with headphones running through the park.", "audio": "/zhanghaomin/datas/musiccap/music_data/7YtKrL6ScXA.wav"} +{"id": "7ZW8xO37bA4", "caption": "The low quality recording features a reverberant, electric guitar solo melody. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/7ZW8xO37bA4.wav"} +{"id": "7ZXz3Xa7APs", "caption": "This is a tongue-in-cheek version of a reggae song edited to make it sound like a movie character was featured in it. It has a male vocal that starts singing with a Jamaican accent that turns into gibberish. Clean electric guitar and bass guitar provide the melodic background while the acoustic drums and percussion play a basic reggae beat for the rhythmic background.", "audio": "/zhanghaomin/datas/musiccap/music_data/7ZXz3Xa7APs.wav"} +{"id": "7_0g3tEcM0w", "caption": "This symphonic song starts off with a melody featuring a flute, marimba and violins. The mood of this song is happy. After three bars, a snare drum plays a marching beat. This is followed by a melody played on trumpets and trombone. There are no voices in this song. This song can be played at the intro of a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/7_0g3tEcM0w.wav"} +{"id": "7_80oVTLkGU", "caption": "This music is a percussion instrumental . The tempo is medium fast with a rhythmic tambourine beat. The music is minimal with the sound of the tambourine metal plates clanging and a dull drum head beat. The music is catchy, enthusiastic and has a rhythmic beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/7_80oVTLkGU.wav"} +{"id": "7_Sr2zv1sQc", "caption": "The low quality recording features a traditional song that consists of passionate female vocal singing over sustained string melody, wobble bass, wooden percussive elements and shimmering shakers. It is a bit noisy, in mono and it sounds vintage, passionate, emotional and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/7_Sr2zv1sQc.wav"} +{"id": "7_q36NyJtQY", "caption": "A female vocalist sings this romantic song in a foreign language that sounds like Spanish. The tempo is medium with a melodious guitar accompaniment, slick drumming, piano accompaniment, steady bass line and pandeireta rhythm. The song is soft, mellow, catchy, emotional and soothing. This song is a Folk Pop/Regional Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/7_q36NyJtQY.wav"} +{"id": "7_yBcHaoR0w", "caption": "This music is an electric guitar lead instrumental. The tempo is slow with no accompaniment and ambient sounds like a popping and swishing sound. The music is a rhythmic, controlled, pleasant, melancholic, sentimental and emotional Electric guitar solo.", "audio": "/zhanghaomin/datas/musiccap/music_data/7_yBcHaoR0w.wav"} +{"id": "7avMUhHOCR8", "caption": "A male vocalist sings this enthusiastic Electro Hop. The tempo is fast with synthesiser articulation, Dj mixer and digital drum beats. The song has emphatic, insistent vocals, punchy, youthful, buoyant, funky,strong,psychedelic, persuasive, groovy and untiring. This song is a contemporary Electronic HIp-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/7avMUhHOCR8.wav"} +{"id": "7chwYGGSkmE", "caption": "The low quality recording features an arpeggiated acoustic guitar melody over which a reverberant passionate female vocal is singing. At the very end of the loop there is a metallic bells melody. The recording is noisy and in mono, but it sounds traditional, calming, relaxing and spiritual.", "audio": "/zhanghaomin/datas/musiccap/music_data/7chwYGGSkmE.wav"} +{"id": "7cvqeU9Wh-I", "caption": "This is a soft rock/blues music piece. There is a male vocalist singing melodically in the lead. The electric guitar is playing bits and pieces of sound with the slide technique. There is a synth string sound in the background. The piece has a story-telling mood to it. The atmosphere is calm. This piece could be playing in the background at a coffee shop or a seaside restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/7cvqeU9Wh-I.wav"} +{"id": "7cw7rDLcujI", "caption": "This clip features quirky sounds. In the foreground, the sound of a male narrator is played. In the background, sliding whistles are played. Some other quirky sounds are played which are comedic. A random melody is played on a keyboard. The mood of this song is funny. These sounds can be played in a comedy clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/7cw7rDLcujI.wav"} +{"id": "7dmT4SgS_EM", "caption": "A female singer sings this sultry vocals. The song is medium tempo with traditional Arabic percussions playing steadily, tambourine percussion, keyboard accompaniment and a strong bass-line. The song is romantic and passionate. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/7dmT4SgS_EM.wav"} +{"id": "7e46Hfy5j8g", "caption": "The low quality recording features a trance song that consists of ambient wide synth pad chords, growly synth bass, another layer of synth bass stab and echoing female vocals over it. It sounds mystical, hypnotic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/7e46Hfy5j8g.wav"} +{"id": "7eZTmLV9gcY", "caption": "This is an instrumental piece from a soap opera soundtrack. The violin and the acoustic guitar are playing a mellow tune while there is an occasional piano tune in the background. The rhythm is kept by a very quiet acoustic drum beat. The atmosphere is gentle and romantic. This piece could be used in the soundtrack of romance movies where the characters are having a good time in the presence of each other.", "audio": "/zhanghaomin/datas/musiccap/music_data/7eZTmLV9gcY.wav"} +{"id": "7fVfG0DrLjI", "caption": "Encouraging gospel music featuring a women's choir, hand clapping, female background shouting, and a lead female vocalist. The choir is accompanied by a band vamping on one chord with an organist, heavy drumkit, and a syncopated bassline. Would fit in a southern spiritual service.", "audio": "/zhanghaomin/datas/musiccap/music_data/7fVfG0DrLjI.wav"} +{"id": "7h6nTyP7d9o", "caption": "This low quality audio features a percussion playing a simple beat in common time. The snare is struck on every alternate count. the bass plays one note. A synth plays one note for four counts followed by a lower note for the next four counts. This song does not have any voices. This song can be played in a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/7h6nTyP7d9o.wav"} +{"id": "7hKG33wkr0k", "caption": "The low quality recording features a classical orchestra music that consists of wide strings, pulsating woodwind melody, glissando harp melody and heartbeat low tom hits. It sounds spooky, vintage, haunting, suspenseful and intense, like something you would hear as background music in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/7hKG33wkr0k.wav"} +{"id": "7jWRIjFaoeU", "caption": "The low quality recording features a rock song that consists of wide electric guitar chords, punchy kick and snare, electric guitar slide, distorted bass guitar, aggressive drums cymbals and flat male vocals singing over it. It sounds energetic, but also harsh and messy thanks to those cymbals.", "audio": "/zhanghaomin/datas/musiccap/music_data/7jWRIjFaoeU.wav"} +{"id": "7k3M0pQvzhY", "caption": "This audio contains someone playing a low didgeridoo while people are talking in the background. The didgeridoo sounds amplified. This song may be playing live at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/7k3M0pQvzhY.wav"} +{"id": "7k3OZ_fPXuM", "caption": "A voice sample is ringing out with a lot of reverb. A synth pad is underlining an acoustic piano being played with a lot of reverb and delay creating an arpeggio. A guitar is playing another melody also with a lot of reverb and delay creating a ping pong effect on both sides of the speakers. There is another pulsating little synth sound being played in a higher key. This song may be playing at home relaxing and daydreaming.", "audio": "/zhanghaomin/datas/musiccap/music_data/7k3OZ_fPXuM.wav"} +{"id": "7kEeYQx2VLE", "caption": "This song features a trumpet playing the main melody. The melody is like a melody played before announcements are made in a kingdom. This is accompanied by a tambourine and a bass. The bass plays one note four times followed by a higher pitched note eight times and back to the first note once. After a three count rest, the bass phrase is repeated. This song can be played in a movie scene announcing the arrival of royalty.", "audio": "/zhanghaomin/datas/musiccap/music_data/7kEeYQx2VLE.wav"} +{"id": "7l4-QmvXxEs", "caption": "This is a space disco music piece. It is a funky version of the Star Wars movie theme. There is a lively combination of the strings and the brass sections playing the main melody while a groovy bass guitar is playing alongside them. The rhythmic background is composed of a disco type acoustic drum beat. Robotic sounds akin to the ones that can be heard in the movie are added in the music. The atmosphere is unique and danceable. This piece could be used in retro-themed parties. It could also be playing in the background at a Star Wars themed event.", "audio": "/zhanghaomin/datas/musiccap/music_data/7l4-QmvXxEs.wav"} +{"id": "7lG2zPKo9e4", "caption": "A female vocalist sings this sweet melody. The tempo is medium with a ukulele accompaniment. The song is dulcet, melodic,pleasant , euphonious, simple and sweet however the male vocal backup seems completely unrelated and dissonant. It changes the vibe of this song from sweet to creepy and eerie.", "audio": "/zhanghaomin/datas/musiccap/music_data/7lG2zPKo9e4.wav"} +{"id": "7lV4IvuW2lk", "caption": "The low quality recording features a live performance of distant trumpet melody, followed by energetic cymbals, snare roll and manically played metallic percussion. It sounds energetic and loud, while the recording is noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/7lV4IvuW2lk.wav"} +{"id": "7muzlOrbDu8", "caption": "This is a cartoon theme in the style of alternative metal. There is a male lead vocal singing loudly while there are male back vocals singing more melodically. The distorted electric guitars and heavy bass guitar are playing an aggressive tune. The rhythmic background is provided by an acoustic drum beat just as aggressive. The atmosphere is energetic and action-filled. This piece can be used in the soundtrack of an action-based cartoon or a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/7muzlOrbDu8.wav"} +{"id": "7nrOZXbpXBo", "caption": "Male and female voice over with harpsichord in the background playing. The woman chuckles.", "audio": "/zhanghaomin/datas/musiccap/music_data/7nrOZXbpXBo.wav"} +{"id": "7pYavsK9sPg", "caption": "The low quality recording features a reggae song that consists of a fruity male vocal singing over shimmering hi hats, groovy bass, organ keys, chords, claps and male vocal chants. It sounds addictive, groovy and muddy, due to the poor quality of the mix.", "audio": "/zhanghaomin/datas/musiccap/music_data/7pYavsK9sPg.wav"} +{"id": "7p_Mnxl4Vq8", "caption": "This is an instrumental occult rock piece. There is an electric guitar playing a simple melody with a minimal bass guitar backing. The atmosphere of this piece is sinister and unsettling, it gives the impression of a Satanic ritual about to commence. The tempo is slow. This music piece could be included in the soundtrack of a ritualistic horror movie/TV series or a video game of the similar genres.", "audio": "/zhanghaomin/datas/musiccap/music_data/7p_Mnxl4Vq8.wav"} +{"id": "7pdrGzdWMzI", "caption": "This is a drumstep piece which is a mixture of the genres drum & bass and dubstep. There is a fuzzy and aggressive synth bass sound playing the melody with the use of a vocoder. An electronic drum with a sound similar to a 909 kit is playing a simple beat in the rhythmic background. The song is mid tempo, but it still has a danceable aura. It could be used in sportswear advertisements or could be playing in the background of a nightclub.", "audio": "/zhanghaomin/datas/musiccap/music_data/7pdrGzdWMzI.wav"} +{"id": "7qaRlUc4fb0", "caption": "A female vocalist sings this beautiful melody in soprano . The tempo is slow with a harp accompaniment. The song is mellow, soothing, sentimental,calming, ethereal, and dulcet.", "audio": "/zhanghaomin/datas/musiccap/music_data/7qaRlUc4fb0.wav"} +{"id": "7uKkUTml-DA", "caption": "This is a Carnatic classical music piece. It is a live performance. There is a male vocalist singing in a versatile manner. The melody is being played by the Carnatic violin. There is a tabla percussion beat in the rhythmic background. There is a complex feel to the piece. The atmosphere is vibrant.", "audio": "/zhanghaomin/datas/musiccap/music_data/7uKkUTml-DA.wav"} +{"id": "7vC1iriZlX8", "caption": "This is a meditation music piece. It is an instrumental piece. Tibetan singing bowls in various sizes are rung to create a soothing atmosphere. It is the perfect background music for a meditation video. It could also be playing in the background at a spa or a wellness center.", "audio": "/zhanghaomin/datas/musiccap/music_data/7vC1iriZlX8.wav"} +{"id": "7wSTdp1hiTA", "caption": "This clip features animal noises in the forest. The noises are those of wolves or werewolves howling. It sounds like birds are scattering away as soon as the howling noises are heard. There are no musical instruments in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/7wSTdp1hiTA.wav"} +{"id": "7xD_Ib3VS_w", "caption": "The low quality recording features widely spread electric guitar melodies. One of the melodies is solo and it is panned to the right channel, while the other one is an arpeggiated electric guitar melody, and it is panned to the left channel of the stereo image. The recording is a bit noisy and weird, since it is a bit too wide, but it also sounds passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/7xD_Ib3VS_w.wav"} +{"id": "7y9RfZXJZsk", "caption": "The low quality recording features a regional Mexican song that consists of a reverberant male vocal singing over widely spread groovy piano chord progression, brass section, shimmering shakers, groovy percussive elements and smooth bass. It sounds tropical, exotic and fun, like something you would hear at latin weddings.", "audio": "/zhanghaomin/datas/musiccap/music_data/7y9RfZXJZsk.wav"} +{"id": "7yK4-hsVX1o", "caption": "This is a French electronic pop music piece. There is a male vocalist singing in the lead. A melodic pad is playing a repeated theme while a fuzzy synth bass is playing a loud bass line. There is an electronic drum beat in the rhythmic background. The atmosphere is sensual and erotic. This piece could be playing in the background at a nightclub or a dance club in France.", "audio": "/zhanghaomin/datas/musiccap/music_data/7yK4-hsVX1o.wav"} +{"id": "7ym-LzgwSPE", "caption": "The low quality recording features an electro song that consists of a gliding synth lead melody played over groovy synth keys chords, exciting synth riser, punchy snare layered with claps, shimmering shakers and punchy kick hits. It sounds energetic and exciting, due to the fact that it is a build up section of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/7ym-LzgwSPE.wav"} +{"id": "7zP5kNyDn88", "caption": "This is the live performance of a medieval music piece. The piece is instrumental. The main melody is being played by a vielle while the lute is playing a backing tune. The rhythm is provided by the drums and a chime bell percussion. The atmosphere is lively. This piece could be used in the soundtrack of a historical drama movie or a TV show that takes place during the medieval era.", "audio": "/zhanghaomin/datas/musiccap/music_data/7zP5kNyDn88.wav"} +{"id": "81SgTHg66QY", "caption": "The low quality recording features a traditional, medieval song sung by reverberant low male vocals and followed by acoustic rhythm guitar. It is a bit noisy and it sounds traditional.", "audio": "/zhanghaomin/datas/musiccap/music_data/81SgTHg66QY.wav"} +{"id": "86YDiQjYU1U", "caption": "A brass ensemble playing a fast piece with a quick tempo and virtuosity. Male voice over.", "audio": "/zhanghaomin/datas/musiccap/music_data/86YDiQjYU1U.wav"} +{"id": "886Qu4V0km4", "caption": "Someone is playing a melody on a semi acoustic guitar along to a bass ukulele with a very big sound. In the background you can hear something like a harmonica playing a drone chord. This song may be playing at a local concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/886Qu4V0km4.wav"} +{"id": "89eBh_Djflw", "caption": "The low quality recording features a cover of a boogie song sung by a passionate male vocalist, followed by funky electric guitar melodies. It sounds passionate, groovy, funky and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/89eBh_Djflw.wav"} +{"id": "8BJljuSm2Aw", "caption": "This song is a ballad which features a male voice singing the main melody. This is accompanied by a plucked guitar playing arpeggiated chords. There are no other instruments. There is no percussion. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/8BJljuSm2Aw.wav"} +{"id": "8Bu8CkR1xZY", "caption": "This is a tutorial on the electric guitar. The guitar is high-pitched and rapid arpeggio notes are played on it. The audio is of a poor quality. The individual makes a comment at the end of the video.", "audio": "/zhanghaomin/datas/musiccap/music_data/8Bu8CkR1xZY.wav"} +{"id": "8CY7G2NrlxY", "caption": "A male singer sings this humming vocal. The song is medium tempo with a strong drumming rhythm, groovy bass slime, keyboard accompaniment, piano accompaniment and tambourine accompaniment . The song is emotional and romantic. The song is a modern pop love song with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/8CY7G2NrlxY.wav"} +{"id": "8DHtPopFvII", "caption": "This is a vocal performance recording of a pop music piece. It is an amateur recording. The female vocalist is singing in a rising-and-falling manner in medium-to-high pitch. The backing track consists of a simple piano tune, a groovy bass line provided by a bass guitar and a 4/4 signature slow tempo drum beat with clicks on every fourth beat. The atmosphere is sentimental and heart-touching.", "audio": "/zhanghaomin/datas/musiccap/music_data/8DHtPopFvII.wav"} +{"id": "8DQbnR7hwpc", "caption": "The song is instrumental. The tempo is medium with a harpist playing a bass line accompanying a violist. The song is folk-like with a dance rhythm. The audio quality is poor with ambient crowd noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/8DQbnR7hwpc.wav"} +{"id": "8DTKCAv9ods", "caption": "This clip is an indian blow horn called the Tutari or Sringa being played, followed by a dialogue between two male voices. The tutari is a Royal instrument from western India, sounded during ceremonies, festivities or to make announcements.", "audio": "/zhanghaomin/datas/musiccap/music_data/8DTKCAv9ods.wav"} +{"id": "8FZb_R2UANY", "caption": "The low quality recording features a pop song that consists of an electric guitar melody, shimmering hi hats, groovy bass, sustained strings melody, pulsating synth melody, punchy kick and echoing synth bell melody. It sounds emotional, passionate and cinematic, as it also sounds like something that would go well as a background music for movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/8FZb_R2UANY.wav"} +{"id": "8FawGISo8wY", "caption": "A male singer sings this slick melody with male backup singers in vocal echo type harmony. The song is medium tempo with heavy bass drops, strong drumming rhythm, keyboard accompaniment and slick percussive hits. The song is a modern techno dance tune and groovy in nature. The song is average in audio quality and serves as a documentary soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/8FawGISo8wY.wav"} +{"id": "8GKbDSu9Xd0", "caption": "The jazz music features a clarinet playing a melody that's ending a song. A big band that incorporates a jazz acoustic guitar accompanies the clarinet. The tempo is slow and the style is ballad. The medium quality audio recording leads me to believe this is an older recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/8GKbDSu9Xd0.wav"} +{"id": "8HHrlxQuZKE", "caption": "This audio contains reggae-like drums playing along with a bass. An e-guitar is strumming short chords on the backbeat giving this song its typical reggae feel. An organ is playing a melody panned to the left side of the speakers playing short fast chords. A male voice is singing a melody in a higher pitch than a piano is walking down the scale creating a melody then a chime comes in getting the song ready for the next part. This song may be playing while sitting by a lake with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/8HHrlxQuZKE.wav"} +{"id": "8Ha5qGnT7lg", "caption": "The low quality recording features a soul instrumental that consists of a mellow arpeggiated acoustic guitar melody, shimmering tambourine and soft low tom hits in the background. There are some guitar strings crackle sound effects and at the end of the loop there is a sustained string swell. The recording is noisy and muddy, but it sounds emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/8Ha5qGnT7lg.wav"} +{"id": "8KIoQ2HZ0Hg", "caption": "This is the amateur recording of an instrument showcase jam. There is a didgeridoo playing at low-to-medium range making various resonant sounds in the process. The atmosphere is ominous and tribal. The quality of the audio is quite poor. This piece could be played at a primary school music class to give the kids an impression of how a didgeridoo sounds like.", "audio": "/zhanghaomin/datas/musiccap/music_data/8KIoQ2HZ0Hg.wav"} +{"id": "8KUV2TFTpGo", "caption": "This is a live acoustic performance of a folk rock music piece. There are male vocals singing melodically in the lead. The melody consists of a wide range of elements such as the acoustic guitar, the bass guitar, the piano and the saxophone. The acoustic drums are being played with brushes in the rhythmic background. The atmosphere is easygoing and joyful. This piece could be playing in the soundtrack of a feelgood movie during a road trip scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/8KUV2TFTpGo.wav"} +{"id": "8LP_wbFLaJE", "caption": "This song contains a digital drums playing a groove that invites to dance along with some percussive sounds. A bass hit sounds is adding rhythmic and harmonic elements along with a short synth lead sound in the higher register. A male voice is shouting/singing with delay on his voice. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/8LP_wbFLaJE.wav"} +{"id": "8LYWfpPUokc", "caption": "The low quality recording features a snare roll played over metronome beep. It sounds energetic and exciting, even though the recording is in mono and a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/8LYWfpPUokc.wav"} +{"id": "8MF6nFj02sM", "caption": "This audio contains a string section playing a sad/melancholic piece. A violin/viola is playing the lead melody while celli and upright basses being played with a bow are supporting the melody with chords. The lead melody is panned to the right side of the speakers. This song may be playing in a sad and dramatic movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/8MF6nFj02sM.wav"} +{"id": "8MKemM0h5mE", "caption": "The Afrobeats song features a flat male vocal, supported by male ad libs in the right channel of the stereo image, rapping over punchy kicks, muffled claps, syncopated snare hits and pulsating synth pad chords. At the very end of the loop there is a short snippet of groovy synth bass, as the section changes. It sounds lower in quality mainly because of the bad sound selection, as the instruments are too thin and too digital.", "audio": "/zhanghaomin/datas/musiccap/music_data/8MKemM0h5mE.wav"} +{"id": "8MbxazeMw2E", "caption": "A female vocalist sings this loud chant like folk song in a foreign language. The tempo is medium fast with vocal backup, rhythmic small hand cymbals and xylophone like instruments. The audio quality is inferior so the music is incoherent. This song is a live performance or concert with ambient sounds. The song is loud, lilting, chant-like, meditative, droning, hynoptic, melodious and classical. This song is a Classical Laos Folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/8MbxazeMw2E.wav"} +{"id": "8NIxqHJrL68", "caption": "This song contains a piano playing a melody along with a digital flute and a plucked string instrument. An e-bass is playing a simple line with long notes along with acoustic drums being in the background. This song may be playing in a landscape video.", "audio": "/zhanghaomin/datas/musiccap/music_data/8NIxqHJrL68.wav"} +{"id": "8Nrp4jUZeGE", "caption": "This is an electronic dance music piece. It opens with loud fuzzy synth bass and electronic drums and continues with a repeating melody from a bright keyboard. It has an upbeat, loud and energetic aura that would be ideal in a nightclub setting. It could also be used in a DJ setlist.", "audio": "/zhanghaomin/datas/musiccap/music_data/8Nrp4jUZeGE.wav"} +{"id": "8OsmFmhNjoA", "caption": "The low quality recording features a latin urban song that consists of a passionate male vocal, alongside wide harmonizing vocals, singing over punchy kick and snare hits, shimmering cymbals, funky electric guitar melody, synth pad chords, groovy bass and synth keys melody. It sounds energetic and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/8OsmFmhNjoA.wav"} +{"id": "8PcfPX11Hjg", "caption": "This song features a choir with male and female voices. Some of the male voices sing the bass part of the vocals. This is accompanied by a harmonica playing a high pitched melody. An acoustic guitar plays arpeggiated chords. After the instruments come to a rest, the voices continue to sing in harmony without the instruments. This song has a romantic mood. This song can be played in a.", "audio": "/zhanghaomin/datas/musiccap/music_data/8PcfPX11Hjg.wav"} +{"id": "8UhdwnsckJ8", "caption": "The low quality recording features a tutorial that contains a flat male vocal talking over acoustic guitar strummed chords. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/8UhdwnsckJ8.wav"} +{"id": "8WPG0dD20lg", "caption": "This instrumental song features a guitar played clean in the beginning and then switching to an overdrive sound. There are no other instruments in this song. There are no voices in this song. The mood of this song is bluesy.", "audio": "/zhanghaomin/datas/musiccap/music_data/8WPG0dD20lg.wav"} +{"id": "8WnXfe3ud4E", "caption": "This song is an instrumental. The tempo is medium with an enthusiastic keyboard harmony, steady drumming and boomy bass lines with rustling , whooshing sounds, muffled voices of people cheering or chanting and crackling sounds. The song is intense, passionate, youthful, inspiring, impactful and fervent. The audio quality is inferior so the music is muddy and incoherent.", "audio": "/zhanghaomin/datas/musiccap/music_data/8WnXfe3ud4E.wav"} +{"id": "8XBsesSEbbU", "caption": "The song is an instrumental. The song is medium with a strong bass line, steady techno drumming rhythm, various percussion hits and a synth horn melody. The song has mismatched tempos and is amateurish in production. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/8XBsesSEbbU.wav"} +{"id": "8XGXHDMIJw4", "caption": "The low quality recording features a processed vocoder male vocals singing over punchy \"4 on the floor\" kick pattern, shimmering hi hats, low percussions and tinny wooden percussions. It sounds weird, addictive and hypnotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/8XGXHDMIJw4.wav"} +{"id": "8Y0FRjkX9xI", "caption": "This song contains two acoustic guitars strumming and fingerpicking minor key melodies. A male voice is singing in the mid to high register sounding sad. This song may be playing gathered around a bonfire.", "audio": "/zhanghaomin/datas/musiccap/music_data/8Y0FRjkX9xI.wav"} +{"id": "8Yt55huZGZc", "caption": "The low quality recording features a folk song that consists of passionate accordion melody played over sustained strings melody, groovy piano melody and groovy double bass. It sounds uplifting, passionate, emotional and it feels like something you would hear in France, played by street musicians.", "audio": "/zhanghaomin/datas/musiccap/music_data/8Yt55huZGZc.wav"} +{"id": "8Z5xnSxUmGE", "caption": "The low quality recording features a regional Mexican song that consists of a passionate male vocal singing over groovy trombone and short brass melody. It sounds passionate and emotional, even though the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/8Z5xnSxUmGE.wav"} +{"id": "8ZK1ajW598M", "caption": "The low quality recording features a live performance of a traditional song that consists of harmonizing male vocals singing over plucked strings melody and wooden percussion. It sounds passionate and soulful, but the recording is very noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/8ZK1ajW598M.wav"} +{"id": "8akqVDDGsNQ", "caption": "The low quality recording features a live performance of an Alternative/Indie song and it consists flat male vocal singing over electric guitar chord progression, thin, but groovy bass guitar, punchy kick and snare hits, soft rimshots, soft crash cymbal, shimmering hi hats and a drum break. It sounds energetic, groovy and addictive, due to the cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/8akqVDDGsNQ.wav"} +{"id": "8dE1x--TuF8", "caption": "This is a Hindi film music piece. This is an instrumental piece. The harmonica is playing a cheerful melody in the lead. The glockenspiel is playing a secondary melody while the acoustic guitar and the bass guitar are supporting them in the background. The acoustic drums are playing a jazz swing beat with the brushes. The atmosphere is lively. This piece could be used in a feelgood movie during scenes where everything is going well for the main character.", "audio": "/zhanghaomin/datas/musiccap/music_data/8dE1x--TuF8.wav"} +{"id": "8fInAz_GICs", "caption": "This is a marching band piece. The only instruments playing are a snare drum and a bass drum. The snare drum is playing a drumroll while the bass drum is keeping the rhythm. This piece could be sampled for use in beat-making. It could also be playing in the background at a national holiday parade.", "audio": "/zhanghaomin/datas/musiccap/music_data/8fInAz_GICs.wav"} +{"id": "8fibq2VXibw", "caption": "This is a festive music piece used as a theme for a cartoon. It is a slow tempo piece. There is a female vocalist singing melodically. The keyboard is playing the melody while the bass guitar is following in the background. The rhythm consists of a calm acoustic drum beat. The atmosphere is serene. This piece could be playing in the background at a slow dance event.", "audio": "/zhanghaomin/datas/musiccap/music_data/8fibq2VXibw.wav"} +{"id": "8hO1S9VIfPY", "caption": "This is the recording of a preaching session at a Christian church. The preacher is shouting and screaming while the crowd is chanting in accordance. There is an electric guitar and acoustic drums in the backing track that can be barely heard from all the noise. The atmosphere is loud and chaotic. Parts of this piece could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/8hO1S9VIfPY.wav"} +{"id": "8hSmQpOPXJE", "caption": "The low quality recording features a cover of a kids song that consists of sweet girl vocal singing over breathy flute melody, groovy bass and acoustic rhythm guitar. It sounds mellow, happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/8hSmQpOPXJE.wav"} +{"id": "8hT2G2ew6-c", "caption": "This audio contains someone playing a melody on a dulcimer. The recording is full of reverb. This is an amateur recording and of poor audio-quality. This song may be playing in an oriental documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/8hT2G2ew6-c.wav"} +{"id": "8iPpgyEh8WM", "caption": "This is a modern classical instrumental piece. The melody is played by an orchestra with the strings section as the lead, the piano playing an arpeggio and the bass guitar carrying the background. There is a light percussive element resembling a tambourine keeping the rhythmic background. The piece has a melodic, story-telling mood to it which would make it the perfect choice to use in a movie soundtrack, especially a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/8iPpgyEh8WM.wav"} +{"id": "8jDanS4ZzRc", "caption": "This orchestral song features violins playing the main melody along with trumpets. This is accompanied by the bass being played on a cello. The percussion is played on a timpani. There are no voices in this song. This is an amateur recording. This song can be played in a fairytale animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/8jDanS4ZzRc.wav"} +{"id": "8kH-dzSBthI", "caption": "This music is a Western classical piece. The tempo is slow with a lilting harpsichord melody, flute harmony and violin accompaniment. The music is classical, serene, splendid, uplifting, lush, melancholic, pensive, dreamy symphonic music.", "audio": "/zhanghaomin/datas/musiccap/music_data/8kH-dzSBthI.wav"} +{"id": "8kx5ST65Fog", "caption": "The low quality recording features a live performance of a folk song and it consists of a metallic percussive melody, wooden percussions, acoustic guitar melody and flute melody. It sounds soulful, upbeat and passionate and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/8kx5ST65Fog.wav"} +{"id": "8m-a_6wLTkU", "caption": "The low quality recording is a noisy and windy recording that has some asphalt sound effects in it and a wide, happy sounding background song added in postproduction. Sounds really loud and harsh, due to the wind.", "audio": "/zhanghaomin/datas/musiccap/music_data/8m-a_6wLTkU.wav"} +{"id": "8nJ2MhvhnJ0", "caption": "The low quality recording features a metallic hit, followed by resonating bowl tone. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/8nJ2MhvhnJ0.wav"} +{"id": "8ntKBILZ06k", "caption": "This song is a child yodelling .The tempo is medium with an enthusiastic guitar accompaniment. The yodelling is melodic, calm, engaging, and pleasant. The song has minimal instrumentation with vocal emphasis.", "audio": "/zhanghaomin/datas/musiccap/music_data/8ntKBILZ06k.wav"} +{"id": "8o2UyEYbNmY", "caption": "The low quality recording features an ambient song that consists of mellow dark synth pad chords playing. It sounds calming, relaxing and hypnotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/8o2UyEYbNmY.wav"} +{"id": "8oTTgXIO0-I", "caption": "This song contains someone scratching over a Hip-Hop track. The track contains acoustic drums with a rim-shot as snare and congas playing along. The e-bass and an e-guitar are playing the same lines in the lower register. This song may be playing live at a scratching contest.", "audio": "/zhanghaomin/datas/musiccap/music_data/8oTTgXIO0-I.wav"} +{"id": "8oUI02eK3SM", "caption": "This song contains a male voice singing in the midrange while backing voices are supported with vocals in the higher register. Someone is playing a complex jazzlike groove on the drums. An e-guitar is playing a loud arpeggio melody panned to the right side of the speakers along with an e-bass. This song may be playing live at a jazz festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/8oUI02eK3SM.wav"} +{"id": "8olHAhUKkuk", "caption": "You can hear percussion instruments playing a rhythm along with a tambourine. String instruments are being plucked and also played with a bow providing the main melody. A female voice is crying. This song may be playing as part of a very sad movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/8olHAhUKkuk.wav"} +{"id": "8pYHLfKqHL4", "caption": "The Jazz song features a wide brass section playing over soft kick and rimshot hits, smooth bass guitar, mellow keys chords and soft electric guitar arpeggiated melody. It sounds relaxing, warm and calming - like something you would hear in waiting rooms.", "audio": "/zhanghaomin/datas/musiccap/music_data/8pYHLfKqHL4.wav"} +{"id": "8pc8fjPIV-Q", "caption": "A male singer sings this cool melody with backup female singers in vocal harmony. The song is medium tempo with a groovy rhythm, steady drumming rhythm, disc scratching tones, and piano accompaniment. The song is groovy and has a dance rhythm. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/8pc8fjPIV-Q.wav"} +{"id": "8pit9UV69S8", "caption": "Harsh amateur recording of hardcore aggressive speed metal. The recording is blown out and distorted. Male scream vocals can be heard as well as loud drums and distorted guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/8pit9UV69S8.wav"} +{"id": "8pl1D6oG38k", "caption": "The low quality recording features an electro song that consists of a punchy kick, buzzy synth bass, claps and shimmering hi-hats. It sounds exciting and a bit too digital - like something you would hear in old video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/8pl1D6oG38k.wav"} +{"id": "8q0An6WY7_c", "caption": "The low quality recording features a theremin solo melody. It sounds haunting, intense, suspenseful and cold. There are some water flowing sounds in the background. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/8q0An6WY7_c.wav"} +{"id": "8qeTEfOqB0A", "caption": "The low quality recording features an electro song that features loud choir vocals singing over loud low percussions and some tom rolls. Towards the end of the loop, the choir vocal is sustained and it blends with synth lead riser. It sounds powerful, epic, energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/8qeTEfOqB0A.wav"} +{"id": "8r1y_Bz4VfQ", "caption": "This is an acoustic ballad that is sung in a melancholic manner by two male vocalists and a female vocalist. There is an acoustic guitar in the background playing a simple tune. The tempo and the general atmosphere of the song is relatively calm. The music could be played at a coffee shop in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/8r1y_Bz4VfQ.wav"} +{"id": "8rCYRgePG-4", "caption": "A female vocalist sings this spirited Latin Rap. The tempo is medium fast with keyboard harmony , infectious drumming, groovy basslines and digital beats. The song is upbeat, youthful, catchy, energetic, emphatic, melodic and vivacious with a dance groove. This song is a Latin Urbano.", "audio": "/zhanghaomin/datas/musiccap/music_data/8rCYRgePG-4.wav"} +{"id": "8sSV_vqOlS4", "caption": "The low quality recording features a jazz song that consists of a saxophone solo melody played over groovy piano, groovy double bass, shimmering hi hats and punchy snare. It sounds passionate and soulful, even though the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/8sSV_vqOlS4.wav"} +{"id": "8tY6nioUQIw", "caption": "This song features a flute being played at a high pitch. The melody is of a folk song. There are no other instruments in this song. There are no voices in this song. This song can be played in an animation movie featuring a person skipping in a forest.", "audio": "/zhanghaomin/datas/musiccap/music_data/8tY6nioUQIw.wav"} +{"id": "8vFJX7NcSbI", "caption": "A digital drum is playing a four on the floor groove with a kick on every beat and a noisy sounding snare. A synth bass sound is playing a bassline along with a sub bass. On top of that a synth pluck sound is playing a fast arpeggiated melody. A noise sound is used as an atmospheric element. This song may be playing in an arcade video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/8vFJX7NcSbI.wav"} +{"id": "8wty3wJfmEY", "caption": "A male Latin singer sings this cool melody. The song is medium tempo with keyboard accompaniment and steady drumming rhythm and a percussive bass-line with missing harmonies. The song is experimental and has bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/8wty3wJfmEY.wav"} +{"id": "8y36aT4C_c0", "caption": "This music is a western classical. The tempo is slow with violins, trumpets, flute, cello. Viola, bassoon harmony. The music is soft, mellow, mellifluous, rich, elegant and exquisite. This is a live performance/concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/8y36aT4C_c0.wav"} +{"id": "8yiJOImd6k0", "caption": "This music is instrumental . The tempo is fast with a vibrant and vivacious Harpsichord solo of the famous composition of the French composer Jean-Philippe Rameau. The music is complex, lively, spirited, enchanting, playful , engaging and a masterpiece.", "audio": "/zhanghaomin/datas/musiccap/music_data/8yiJOImd6k0.wav"} +{"id": "8ynjAtF5VnA", "caption": "An acoustic drum is playing a fast and complex drum groove with a lot of crash hits and double bass drum. Distorted e-guitars strumming wild chords along with an e-bass holding the melody while a male voice is screaming/singing loud and aggressively. In-between the song high and awkward laughing can be heard. This is an amateur recording. This song may be playing at a hard rock tattoo studio.", "audio": "/zhanghaomin/datas/musiccap/music_data/8ynjAtF5VnA.wav"} +{"id": "8zCZzzAaC4I", "caption": "This is an opera song that's recorded at a very low quality. The vocal audio is distorted and creates some fuzzy sounds, and the string instruments are muffled. The song is an uplifting, emotional song.", "audio": "/zhanghaomin/datas/musiccap/music_data/8zCZzzAaC4I.wav"} +{"id": "8zDbEfC6Uf0", "caption": "This song is a loud, energetic electronic instrumental. The audio quality is substandard making it hard to hear the song. One can tell that the song is vibrant , vivacious, bright, youthful and buoyant from the beat of punchy drumming and rapid incoherent vocals. Thesong sounds like EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/8zDbEfC6Uf0.wav"} +{"id": "8zGJ9N7c6pE", "caption": "This classic rock song features a hammond organ playing the main melody. This is backed by the percussion playing a simple beat. The percussion plays the hi-hat at every count and ends with a roll at the end of every bar. The bass plays the same melody as the hammond. There are no voices in this song. This is an instrumental song. This song can be played in a bank robbery scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/8zGJ9N7c6pE.wav"} +{"id": "8zcogfmAD_o", "caption": "A woman talks before the beginning of the music track. The song is instrumental with a trumpet playing a swing melody accompanied by a brass band and jazz orchestra. The tempo is medium with a walking bass line, piano accompaniment, steady rhythm and clapping percussion. The song is a classic swing jazz tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/8zcogfmAD_o.wav"} +{"id": "9-R70gSqvrc", "caption": "A full sounding male voice is singing mid range with kind of a radio effect on his voice. Two banjos are strumming chords with one playing the lead melody on top. One is panned to the right side of the speakers. An acoustic drum is playing a four on the floor groove with a kick on every beat and an e-bass is playing his own melody along. In the background you can hear the sound of a photo taken. This song may be playing in an advertisement for a product.", "audio": "/zhanghaomin/datas/musiccap/music_data/9-R70gSqvrc.wav"} +{"id": "90NsBZvepy0", "caption": "The low quality recording features a fast camera shuttering sound effects, while the alternative rock instrumental is playing in the background. The Instrumental features a slap snare, tinny kick hits, shimmering hi hats, electric guitar melody and low bass guitar. It sounds almost like a video game background music.", "audio": "/zhanghaomin/datas/musiccap/music_data/90NsBZvepy0.wav"} +{"id": "91AmOKytRUM", "caption": "A female vocalist sings this soft song in a foreign language. The tempo is slow with a soft piano accompaniment and sound of chimes. The vocals are mellow, passionate,emotional, sentimental, nostalgic, melancholic and reflective. This song is a sad classic Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/91AmOKytRUM.wav"} +{"id": "91Qp8XUskXo", "caption": "Someone is playing a shofar in a high frequency blowing overtones in the higher register before dropping into the high-mid range. At the end you can hear a backing track playing. This song may be playing at home while enjoying your instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/91Qp8XUskXo.wav"} +{"id": "92QYLjfo68Q", "caption": "This Latin pop song features a male voice singing the main melody. The voice sings at a high pitch. This is accompanied by Latin style percussion. A variety of percussion is used including the claves and cowbell. The bass plays a groovy bassline. The piano plays chords with a Latin feel. The brass section plays fills in between lines. This song has a romantic mood. This song can be played in a party for a slow dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/92QYLjfo68Q.wav"} +{"id": "92k_81uqMSM", "caption": "The song is an acoustic pop song with acoustic guitar strumming chords, a drumset playing a simple steady groove accompanied by a bassline. At every end of a phrase some keys are playing a chord in the middle to higher register. In the foreground are some noises made by a machine. This song may be playing as background music.", "audio": "/zhanghaomin/datas/musiccap/music_data/92k_81uqMSM.wav"} +{"id": "92sRFZvCnWo", "caption": "This is a dance remix of a pop music piece. There are two vocals in the piece, one male and one female. Heavy effects are used on the vocals to make them repeat syllables. There is a repeating string sample as the melody. A complex electronic drum beat provides the rhythmic background. The piece has a groovy feel. It can be played at nightclubs. It could also be used in the soundtrack of a high school drama.", "audio": "/zhanghaomin/datas/musiccap/music_data/92sRFZvCnWo.wav"} +{"id": "940MNbCeobw", "caption": "This is the recording of a cowbell. The cowbell is being played with the side and the tip of the drumstick repeatedly. This recording could be sampled for use in beat-making especially for genres that have a heavy usage of cowbells such as latin dance music.", "audio": "/zhanghaomin/datas/musiccap/music_data/940MNbCeobw.wav"} +{"id": "95ThRxhl-ug", "caption": "This song contains an acoustic drum and an e-bass playing along to someone strumming chords on an acoustic guitar. Panned to the right side of the speaker you can hear a mandolin playing a melody in a higher register. An e-piano is playing chords that are panned to the left side of the speakers. A male voice is singing at a higher pitch. This song may be playing when feeling happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/95ThRxhl-ug.wav"} +{"id": "98YBS2tdpdU", "caption": "The low quality recording features a children's song that consists of passionate girls and boys singing over soft kick and snare hits, shimmering shakers located in the left channel of the stereo image, groovy bass, synth lead melody and groovy piano melody. It sounds soft, mellow, passionate, happy, fun and joyful - like something kids and babies would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/98YBS2tdpdU.wav"} +{"id": "99ZgIQwLC60", "caption": "This song is played with a harp. It sounds mystic and calming. This song may be playing in a melancholic video game-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/99ZgIQwLC60.wav"} +{"id": "9A4VNkMdwhk", "caption": "The low quality recording features a live performance of an instrumental folk song that contains sitar guitar melody and boomy bass. There are some background clapping sounds, probably from a crowd, by which we can conclude that it is in fact a live performance. It sounds like it was recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/9A4VNkMdwhk.wav"} +{"id": "9A_OmOetiuw", "caption": "The low quality recording features a, what it seems like, cover of a country song and it consists of flat male vocals singing over acoustic sitar guitar melody. It sounds very noisy, but also heartfelt and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/9A_OmOetiuw.wav"} +{"id": "9BHvpWP2V9Y", "caption": "A female singer sings this catchy tune with backup singers in vocal harmony. The song is medium tempo with a groovy bass line, keyboard accompaniment, steady drumming with a clapping percussion. The song is catchy and has a dance rhythm. The song is a pop dance song.", "audio": "/zhanghaomin/datas/musiccap/music_data/9BHvpWP2V9Y.wav"} +{"id": "9CJu43AvIds", "caption": "A male singer sings this animated melody with backup singers in vocal harmony. The song is medium tempo with a groovy drum rhythm, clapping percussion and strong bass hits. The song is a pop dance hit with a groovy dance rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/9CJu43AvIds.wav"} +{"id": "9Cfs00bZRCg", "caption": "This techno song features a falsetto voice in the beginning. This is accompanied by 2 counts of programmed percussion. A synth plays one chord using synth strings. The voice, percussion and synth pause and only a repetitive synth loop is played. After four bars, the kick drum starts playing on every count. The mood of this song is upbeat. This song can be played in a trance party or a DJ party.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Cfs00bZRCg.wav"} +{"id": "9DCJTAzUwNc", "caption": "The low quality recording features a reverberant, intimate female vocal singing over soft, arpeggiated piano melody. It sounds haunting, hypnotic, heartfelt and muddy, as the frequencies are clashing and creating a mess in the mix. It sounds like a lullaby.", "audio": "/zhanghaomin/datas/musiccap/music_data/9DCJTAzUwNc.wav"} +{"id": "9EUXyEQZqLo", "caption": "Two acoustic guitars are strumming flamenco chords being panned to the left and right side of the speakers. A soft bass is playing subnotes. Percussive instruments are building up tension at the end.", "audio": "/zhanghaomin/datas/musiccap/music_data/9EUXyEQZqLo.wav"} +{"id": "9FLDpfkbxZs", "caption": "This song is led by a e-guitar solo playing a lightly distorted guitar on the upper register. An acoustic guitar panned to the left and right side of the speakers is playing chords along with a bass that gets slapped and an acoustic drums in the background. This song may be played at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/9FLDpfkbxZs.wav"} +{"id": "9GRNQKSsbvU", "caption": "The low quality recording features a breathy flute melody layered with low flute melody, followed by mellow piano melody, punchy kick, snappy rimshots and shimmering shakers. It sounds soulful and emotional, but the recording is very noisy, harsh and distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/9GRNQKSsbvU.wav"} +{"id": "9HQNvz4eZPU", "caption": "The song is an instrumental. The tempo is slow with a female operatic singer singing, piano accompaniment, bells singing, trumpets playing harmony, various percussion hits and strong bass line. The song is full of tension and sounds ominous like an impending gun fight.", "audio": "/zhanghaomin/datas/musiccap/music_data/9HQNvz4eZPU.wav"} +{"id": "9IdAIIywBfY", "caption": "This song contains a simple acoustic drum groove with a cowbell and a bassline following. Two e-guitars are playing a melody then a male voice starts singing loud and in the mid-range. This song may be playing while working in the garage.", "audio": "/zhanghaomin/datas/musiccap/music_data/9IdAIIywBfY.wav"} +{"id": "9Ijpv6e57a4", "caption": "This pop ballad features a female voice singing the main melody. This is accompanied by percussion playing a simple beat in the background. The bass plays the root notes of the chords. A synth plays chords and fills. The sound of wheels on concrete can be heard. The mood of this song is romantic. A live recording sound is overdubbed on this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Ijpv6e57a4.wav"} +{"id": "9InBmD_Miek", "caption": "This is a gentle and soothing song that feels like a calm Christmas night by the fire. We hear a flute play a melody, and the piano playing chords that match the melody notes. There is some audio distortion in the recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/9InBmD_Miek.wav"} +{"id": "9JeN1ld-3fY", "caption": "This is a funky disco song. A song like this would be suitable for an eighties themed dance party. It has a groovy bassline, upbeat rhythmic percussion, and vibrant brass motifs. The singer sounds charming and energetic. The background singers are soulful and sharp on the beat with their vocals - they sing their notes almost in staccato, so that they can stay close to the beat and keep the song feeling groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/9JeN1ld-3fY.wav"} +{"id": "9JlifkCmUOk", "caption": "This is a recording of a live indie rock performance. The recording is distorted and of a low quality. There are two male singers singing in an indie style with a lot of reverb applied to their vocals. The bass is rumbling and low and constant.", "audio": "/zhanghaomin/datas/musiccap/music_data/9JlifkCmUOk.wav"} +{"id": "9K8EePrEDdo", "caption": "The low quality recording features a live performance of a classical song and it contains trombone melody playing over shimmering hi hats and sustained strings. It sounds muffled, but also passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/9K8EePrEDdo.wav"} +{"id": "9KK6rg03bC8", "caption": "This music is instrumental. The tempo is medium with synthesiser harmony and jazz style drumming. The music is a collaboration of jazz and electronica. It is an experimental,futuristic,funky, psychedelic and Ambient Funk Jazz.", "audio": "/zhanghaomin/datas/musiccap/music_data/9KK6rg03bC8.wav"} +{"id": "9Kut4r8hswE", "caption": "The low quality recording features an electro song that consists of punchy kicks, crispy claps, male vocal chants and groovy, filter modulated synth bass. There is a short noisy traffic noise at the beginning of the loop. Overall it sounds noisy, groovy and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Kut4r8hswE.wav"} +{"id": "9L6ePkWtZI4", "caption": "The low quality recording features a cover of a rock song that consists of acoustic sitar chord progression played so loudly that the male vocal is inaudible. The recording is noisy, but it sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/9L6ePkWtZI4.wav"} +{"id": "9Lst8RagMYs", "caption": "This ska song features the main melody played on the brass section. This includes saxophone, trumpet and trombones being played in harmony. The bass plays a groovy bassline. The percussion plays a jazz beat with focus on the ride cymbal. A guitar plays chords in the background using a tron or wah effect. This song can be played in a comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Lst8RagMYs.wav"} +{"id": "9M4IT3lOU10", "caption": "This clip features very low quality recorded music. There is a lot of ambient noise and the music is not audible. A Latin beat is played and a male voice sings the main melody. This song can be played in a club. No other instruments can be identified.", "audio": "/zhanghaomin/datas/musiccap/music_data/9M4IT3lOU10.wav"} +{"id": "9NJEKpPeWpE", "caption": "The low quality recording features a DJ scratching his vinyl record of an electro song that consists of flat male vocals talking over \"4 on the floor\" kick, synth keys melody, groovy bass, shimmering hi hats, energetic crash cymbals and punchy snare hits. It sounds muddy and messy, since the frequencies are clashing and since it is probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/9NJEKpPeWpE.wav"} +{"id": "9PMoI31ncIs", "caption": "This is a house music piece. There is a synth with a crisp sound playing the melody while a lot of turntable scratches can be heard in the background. An electronic drum beat with lots of snare beat repeat sounds provide the rhythm. The atmosphere is energetic and upbeat. This piece could be played at nightclubs or dance clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/9PMoI31ncIs.wav"} +{"id": "9PQZSLa_A8A", "caption": "The low quality recording features a harpsichord solo melody. It sounds passionate, emotional and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/9PQZSLa_A8A.wav"} +{"id": "9QEm6u4bowQ", "caption": "This music is instrumental. The tempo is medium fast with an energetic electric guitar lead. The music is minimalist with no accompaniment. It is youthful, powerful, enthusiastic, controlled, engaging and intense. This music is Hard Rock/Heavy Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/9QEm6u4bowQ.wav"} +{"id": "9QYo50tFm6w", "caption": "This is a video game theme that is in the style of a kids song. The main melody is being played by a vibraphone while a glockenspiel can be heard adding texture. There is a medium-to-high pitch synth string sound that joins them later on. In the background, there are sleigh bells and a wind effect to imply a winter aura. The atmosphere is playful. The piece could be included in the soundtrack of a kids cartoon or a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/9QYo50tFm6w.wav"} +{"id": "9Qd6AdTq3Ls", "caption": "This song contains percussive digital drums. In the background you can hear a string instrument playing a melody along with a digital flute sound. A keyboard is playing digital strings and brass sounds setting accents and a countermelody. The female voice is singing in the same melody as the strings. A bass is also playing the melody but at the low register. This song may be playing in a dance video-clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Qd6AdTq3Ls.wav"} +{"id": "9Qle4fgMbzk", "caption": "This music is instrumental. The tempo is slow with a lead harmony on an acoustic guitar. The music is mellow, soft , mesmerising and nostalgic . There is minimal instrumentation with the guitarist playing the tune for the movie Godfather. This music is a tutorial on how to play free style guitar .", "audio": "/zhanghaomin/datas/musiccap/music_data/9Qle4fgMbzk.wav"} +{"id": "9QwaP-cvdeU", "caption": "This song is a Jazz instrumental . The tempo is slow with a lively saxophone harmony, groovy bass line, syncopated piano and slick drumming along with the sound of breeze, some clicking and super mario theme. The song in the background is classic Jazz.", "audio": "/zhanghaomin/datas/musiccap/music_data/9QwaP-cvdeU.wav"} +{"id": "9Rx57dlJtIA", "caption": "The low quality recording features a blues song that consists of a passionate male vocal singing over acoustic guitar melody in the left channel, muted acoustic guitar melody in the right channel of the stereo image, groovy bass, mellow snare and shimmering cymbals. It sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Rx57dlJtIA.wav"} +{"id": "9STauy5DsC8", "caption": "A male rapper sings this exciting melody. The tempo is fast with a groovy bass line, grunge keyboard tones, strong drumming rhythm, various percussion hits and beeping tones. The song is pulsating and energetic. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/9STauy5DsC8.wav"} +{"id": "9TkW1M_ZRr0", "caption": "This is a breakbeat piece. There is a groovy electronic drum beat providing the rhythmic structure. A medium pitched pad is playing a repeated theme. There is a synth bass in the background. Occasional string stab hits can be heard. This piece could fit well in the soundtracks of crime movies taking place in the city and car racing video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/9TkW1M_ZRr0.wav"} +{"id": "9Tl2l3bsLpE", "caption": "People are playing the same groove on a lot of percussive instruments. In the background you can hear shakers. Someone is strumming chords with an effect on an e-guitar and someone is playing fill-ins on acoustic drums. This song may be playing at a local live concert from a music school.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Tl2l3bsLpE.wav"} +{"id": "9UCLvFqkFxk", "caption": "This is a jazz music piece. There is a saxophone playing a jazzy solo for the melody. There is an upright bass playing in the background. The rhythmic background consists of a slow tempo acoustic drum beat that is played with brushes. The atmosphere is mellow. This piece could be playing in the background of a classy restaurant or a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/9UCLvFqkFxk.wav"} +{"id": "9UD7qz7DuVY", "caption": "Someone is playing a minor chord composition on an acoustic piano while a female voice is singing with a lot of reverb on her voice. This song may be playing on a karaoke night.", "audio": "/zhanghaomin/datas/musiccap/music_data/9UD7qz7DuVY.wav"} +{"id": "9UOPRQhNzQ8", "caption": "The low quality features a rock song that consists of a muffled passionate male vocal singing over wide acoustic rhythm guitars chords, shimmering cymbals, punchy kick and groovy bass. It sounds addictive, passionate and groovy - like something you would hear in pubs and bars during the 50s.", "audio": "/zhanghaomin/datas/musiccap/music_data/9UOPRQhNzQ8.wav"} +{"id": "9VE1-3q27Qg", "caption": "The music excerpt features a sparse melody being played by an electronic sound that has a vibrating reverb effect on. A synth bass accompanies the melody by playing two notes per beat, one being low and the other an octave higher. In the background one can hear sound effects.", "audio": "/zhanghaomin/datas/musiccap/music_data/9VE1-3q27Qg.wav"} +{"id": "9WrIbJC_C7A", "caption": "This is an animation theme. There is a brass section playing the melody with the saxophone being the lead. The hi-hat cymbals are played with a feeling of swing on the acoustic drums. The atmosphere is sneaky and filled with intrigue. These characteristics make it a perfect soundtrack for a heist/detective cartoon or an animation movie. It could also work well in the soundtrack of a video game from a similar genre.", "audio": "/zhanghaomin/datas/musiccap/music_data/9WrIbJC_C7A.wav"} +{"id": "9WzzYYWpeyA", "caption": "Here we have a quartet of clarinet players playing a classical piece. One of them plays a rapidly ascending melodic motif. The others play sustained notes ranging from bass to alto which provide a support for the melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/9WzzYYWpeyA.wav"} +{"id": "9Y8NR6nDxjk", "caption": "This audio clip features the sound of pages being turned. The percussion is played at regular intervals. In the background, synth sounds are heard playing a soft melody. This sound is from a PC or mobile game.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Y8NR6nDxjk.wav"} +{"id": "9YnYlDFKn-U", "caption": "Live, amateur recording of record scratching over an instrumental old-school hip hop beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/9YnYlDFKn-U.wav"} +{"id": "9Z6Q0X60rmo", "caption": "The low quality recording features a reverberant trumpet melody playing over a wide brass melody and a mellow arpeggiated melody in the background. It sounds glorious, passionate, emotional and calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/9Z6Q0X60rmo.wav"} +{"id": "9ZAmdxKLnhs", "caption": "This is a neo-soul music piece. There is a male vocal singing melodically with another male back vocal singing in a more erotic fashion. The tune is played with a keyboard and a synth. There is a mellow bass line in the background. An acoustic-sounding electronic drum kit provides the rhythmic background. The piece has a seductive atmosphere to it. It could be played at a nightclub during earlier hours. It could also work well as the jingle of a fashion/fragrance advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ZAmdxKLnhs.wav"} +{"id": "9ZUzftiN2uw", "caption": "The clip features the tone of an alarm bell beeping. It beeps with a high and fuzzy tone. A button is then pressed. There is then the sound of a grungy electric guitar being played in a rock style.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ZUzftiN2uw.wav"} +{"id": "9ZWmZdgrE78", "caption": "The low quality video features a cover of a kids song and it consists of a sweet girl vocal singing over acoustic rhythm guitar. The recording is in mono, noisy and it sounds fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ZWmZdgrE78.wav"} +{"id": "9ZeoYezrI7Q", "caption": "This audio clip is just vocalisation. There is a loud drum roll with an evil laughter, sound of metal, followed by grunting and straining noises and then loud, noisy chewing and smacking of lips.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ZeoYezrI7Q.wav"} +{"id": "9ZilD_4pi7E", "caption": "This is an electronica piece played over a workout camp video. There is a male vocoder sound in the lead. The main theme is being played by the medium pitched keyboard. A groovy electronic drum beat with strong kicks provide the rhythmic background.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ZilD_4pi7E.wav"} +{"id": "9ZinCW4jTeE", "caption": "Various percussive instruments are being played. In the foreground stays the cowbell. A trumpet is playing the lead melody while other trumpets are supporting along with a piano playing chords together with an organ sound. A steeldrum is ending the phrase of a melody with his own melody. An e-bass is playing a complex salsa groove. This song may be playing dancing salsa.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ZinCW4jTeE.wav"} +{"id": "9ZryMX2UtAo", "caption": "This is a country music piece. There is a female vocalist singing melodically in the lead. The electric guitar is playing a simple tune with occasional fiddle tunes adding texture. The bass guitar is playing a simple bass line. There is a basic rock acoustic drum beat in the rhythmic background. It has a normal tempo. The atmosphere is easygoing. This piece could be used in the soundtrack of a teenage drama movie/TV series. It could also be used as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ZryMX2UtAo.wav"} +{"id": "9aE33JEIGOg", "caption": "A female vocalist sings this soft melody. The song is slow tempo with a mellow electric guitar harmony, soft keyboard accompaniment , a soft lilting flute melody and subtle bass line. There is no use of percussion. The song is soft, mellow, emotional, nostalgic and sentimental . This song is Soft pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/9aE33JEIGOg.wav"} +{"id": "9cojCCMSABc", "caption": "The low quality recording features a passionate boy vocal singing over punchy kick, groovy bass, shimmering hi hats and crash cymbal hit and groovy piano melody. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/9cojCCMSABc.wav"} +{"id": "9dBWFEpcJIo", "caption": "The low quality recording features a rock song that consists of wide electric guitar chord progressions, distorted bass guitar, shimmering hi hats, uptempo kick pattern and punchy snare. This instrumental sounds a bit muffled and imbalanced in volume, as the guitars are really loud, but it is very energetic regardless.", "audio": "/zhanghaomin/datas/musiccap/music_data/9dBWFEpcJIo.wav"} +{"id": "9dx9IhSqwC4", "caption": "This audio contains two trombone players playing a warm melody. One in a higher key the other in a lower register. This song may be playing live listening to a performance in a theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/9dx9IhSqwC4.wav"} +{"id": "9gCeNCnWZhE", "caption": "This is an instrumental flute piece. The flute is playing a solo while ambient samples of the wind and the birds singing can be heard in the background. There is also a very faint clattering bell-like percussion that can be heard. The piece is very relaxing. It could be used in a meditation video. It could also be used during the scenery shots in the soundtrack of a documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/9gCeNCnWZhE.wav"} +{"id": "9gSOOPDuD4Y", "caption": "The low quality recording features a new age song that consists of sustained synth pad chord, bagpipe melody and subtle piano melody. It sounds mystical, soulful, passionate, emotional and ambient - like something you would hear in Scotland.", "audio": "/zhanghaomin/datas/musiccap/music_data/9gSOOPDuD4Y.wav"} +{"id": "9gkppwB5CXA", "caption": "The song is an instrumental. The tempo is medium fast with a guitar lead, guitar rhythm, steady rock drumming , a percussive bass line along with ambient street noises and roller skate wheel noises. The song is a home video sound track with lots of energy. The song audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/9gkppwB5CXA.wav"} +{"id": "9hCnEfZFZ04", "caption": "The low quality recording features a reverberant acoustic guitar melody. It sounds passionate and emotional. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/9hCnEfZFZ04.wav"} +{"id": "9iYxf1hS4Yk", "caption": "This piece has no melody. Only percussion instruments can be heard in the background. The drumming is rapid and vigorous with a boomy bass drum and sounds of a helicopter, roaring, grunting,gunshots, blasts,fireworks, and clanging of metal and a siren at the end. The vibe is intense, sinister, hostile and dangerous.", "audio": "/zhanghaomin/datas/musiccap/music_data/9iYxf1hS4Yk.wav"} +{"id": "9jeEfi6nDak", "caption": "This music sounds oriental full of semitones and quarter-notes that are used in oriental music. A violin is playing a melody along with the keyboard player also playing a stringsound. Another string instrument is playing along while fast paced, pitched percussion is playing a rhythm with a lot of fill-ins. This song may be played at a live concert or an cultural event representing a country or area of this country.", "audio": "/zhanghaomin/datas/musiccap/music_data/9jeEfi6nDak.wav"} +{"id": "9kt7rsziUVQ", "caption": "instrumental rock music with a drum kit, lots of cymbal crashes, acoustic guitar strumming, harmonized lead guitars and an active bass guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/9kt7rsziUVQ.wav"} +{"id": "9m0tNvskmTc", "caption": "This song contains string instruments being played with a bow playing the main melody. Coming in after a flute starts playing the melody. An acoustic instrument is providing the rhythm. A guzheng is playing the same melody in a lower register. In the background you can hear crickets chirping. This song may be playing as a live performance from a music school.", "audio": "/zhanghaomin/datas/musiccap/music_data/9m0tNvskmTc.wav"} +{"id": "9mIDP_OT1uM", "caption": "Someone is strumming an acoustic guitar while playing a fingerstyle melody and percussive sounds. This is an amateur recording. This song may be playing at a bonfire.", "audio": "/zhanghaomin/datas/musiccap/music_data/9mIDP_OT1uM.wav"} +{"id": "9mqA4YdX444", "caption": "This is an Alpine folk music piece. The piece is instrumental. It is being performed by an orchestra composed of the clarinets, the accordion, the cello and the acoustic guitar. The atmosphere is cheerful. This piece could be used in the soundtrack of a movie that takes place in the Alps region.", "audio": "/zhanghaomin/datas/musiccap/music_data/9mqA4YdX444.wav"} +{"id": "9nVpyqfyBSE", "caption": "The low quality recording features an excited crowd cheering for a flat female vocalist speaking afterwards. The recording is a bit noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/9nVpyqfyBSE.wav"} +{"id": "9ogEGxsJcSY", "caption": "A male vocalist sings this passionate song. The tempo is slow with emphatic vocals and an acoustic guitar accompaniment. The song is melodic, emotional,sentimental, passionate,pensive, reflective and deep. This song is Alternative Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ogEGxsJcSY.wav"} +{"id": "9ohu45KlgYA", "caption": "The low quality recording features a reverberant flat male vocal singing over sustained strings melody, mellow piano melody, shimmering bells melody, shimmering hi hats and groovy bass. It sounds emotional, mellow and soft.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ohu45KlgYA.wav"} +{"id": "9oiSwXk8Nsk", "caption": "This reggaeton song features a male voice singing the main melody. This is accompanied by other male voices singing backing vocals. The percussion plays only in the second half of the song. The beat is a reggae beat. A shaker plays a rhythm in the beginning of the song when the main voice sings. Synth sounds are played in the beginning of the song. This synth plays a harpsichord voice. Synth strings are also played in between lines in the song. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/9oiSwXk8Nsk.wav"} +{"id": "9r01cpNx2vk", "caption": "The song is an acapella cover of a game theme song. The song is medium tempo with no instrumentation by different male vocals engaging in different vocal mimicry of actual instruments, like bass line, melody , percussion and harmony tones. The song is cheerful and amateurish in production. The song is a cover of a popular game theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/9r01cpNx2vk.wav"} +{"id": "9rgB0wKU1-g", "caption": "This is an excerpt from a music documentary on harp making. A very brief harp performance can be heard in the beginning. There is a female voice that is speaking in an instructive manner about the extent of difference the wood material makes on the sound of the harp.", "audio": "/zhanghaomin/datas/musiccap/music_data/9rgB0wKU1-g.wav"} +{"id": "9uToez74x_M", "caption": "A male country singer sings this passionate melody with backup singers in vocal harmony. The song is medium tempo with a strong drumming rhythm, guitar accompaniment, guitar lead, percussive bass line and percussion hits. The song is passionate and romantic. The song has bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/9uToez74x_M.wav"} +{"id": "9vbsI9xFuo8", "caption": "The Alternative/Indie song features a mixed background choir singing over punchy kick and snare hits, energetic cymbals that include crashes and ride hits, followed by groovy bass and strings section melody. The instrumental probably contains more instruments in the background, like a brass section or something orchestral, but due to the low quality mix of the song, it is not audible. Sounds epic and energetic, almost like a final boss theme song for video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/9vbsI9xFuo8.wav"} +{"id": "9x7jWb4lE7c", "caption": "This is an instrument showcase jam. There is an electric guitar with a mellow sound strumming simple chords. The atmosphere is easygoing. Parts of this piece can be used as an advertisement jingle. It could also be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/9x7jWb4lE7c.wav"} +{"id": "9xV0nmojVeg", "caption": "This instrumental pop song features an acoustic guitar being played fingerstyle. The notes are being plucked. Guitar harmonics are played in between the plucked notes. This song is played at a moderate tempo. There is no percussion in this song. There are no other instruments in this song. The mood of this song is relaxing. This song can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/9xV0nmojVeg.wav"} +{"id": "9z4YXc9rjTo", "caption": "The song has a tranquil and mellow vibe to it. It's a Christian worship song, with a singer that has a raspy tone to his voice and a calm approach to performing. The main instrumental factors are the acoustic guitar layers which are strummed, as well as piano chords and simple folk style drumming.", "audio": "/zhanghaomin/datas/musiccap/music_data/9z4YXc9rjTo.wav"} +{"id": "9zW-E0XdWdw", "caption": "The music features a few girl voices singing a melody in harmony. An acoustic guitar accompanies the singers with strummed chords. The overall atmosphere is calming and moving at the same time.", "audio": "/zhanghaomin/datas/musiccap/music_data/9zW-E0XdWdw.wav"} +{"id": "9ziKfjHWqZ0", "caption": "The low quality recording features a gospel song that consists of harmonizing mixed choir singing. The recording is noisy, in mono and it sounds passionate, joyful, soulful and reverberant.", "audio": "/zhanghaomin/datas/musiccap/music_data/9ziKfjHWqZ0.wav"} +{"id": "9zmQwBUFwd4", "caption": "This is a hip-hop music piece. There is a male vocal rapping in the lead. The beat has a soul music sample as the main structure. There is a choir singing melodically. The piano and the electric guitar are playing the tune with the backing of a bass guitar. The rhythmic background consists of a mild tempo acoustic drum beat. The atmosphere is groovy. This piece could be used in the soundtrack of a crime movie, especially during the scenes where a long-lost rival is making a comeback in the town.", "audio": "/zhanghaomin/datas/musiccap/music_data/9zmQwBUFwd4.wav"} +{"id": "A-7dmBdsFXc", "caption": "The low quality recording features a dark tinny bells melody played over synth pad chords, followed by echoing whispering male and haunting whispering female vocals. It sounds haunting, hypnotic, creepy, scary and like something that belongs to a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/A-7dmBdsFXc.wav"} +{"id": "A-oSBMP-Zy4", "caption": "This is a live performance from a female cabaret quartet. They have different vocal ranges and harmonise every line of the song. The audience cheers and claps as they sing. The song feels jazzy.", "audio": "/zhanghaomin/datas/musiccap/music_data/A-oSBMP-Zy4.wav"} +{"id": "A0XXmVts1y0", "caption": "This song contains digital drums playing a groove along with an aggressive synth saw wave pad repeating the same simple melody. A male kid's voice is chopped into a sample creating a rhythmic phrase. The same goes for a female voice. So it sounds like they are singing. This is an amateur recording. This song may be playing in a funny video.", "audio": "/zhanghaomin/datas/musiccap/music_data/A0XXmVts1y0.wav"} +{"id": "A2NtJ12KIuU", "caption": "This is a jingle piece in the background of an advertisement video. There is an acoustic guitar playing a generic tune while medium-pitched strings can be heard accompanying it. There is a slightly fast-paced acoustic drum beat as the rhythmic background. Sounds can be heard related to the ad such as a blood pulse sound effect, a pingpong ball bouncing and people shouting. The overall atmosphere is generic.", "audio": "/zhanghaomin/datas/musiccap/music_data/A2NtJ12KIuU.wav"} +{"id": "A2WdjyKQ57A", "caption": "This is the live performance of a classical music piece. The piece is being performed with a harpsichord. It is in the minor key. The piece is medieval sounding. It could fit perfectly in the soundtrack of a historical drama that takes place in the medieval era.", "audio": "/zhanghaomin/datas/musiccap/music_data/A2WdjyKQ57A.wav"} +{"id": "A2bI-MIIJfU", "caption": "This audio contains a synth drone playing in the lower mid-range. While another synth pad is playing a melody in a higher register along with atmospherical sounds. This song may be playing for a documentary about the universe.", "audio": "/zhanghaomin/datas/musiccap/music_data/A2bI-MIIJfU.wav"} +{"id": "A2pgKzeDRqg", "caption": "A male singer sings this Latin dance melody. The tempo is fast with a harpist playing fast passages with an acoustic guitar strumming rhythm. The song is emotional and energetic. The audio quality is bad with ambient Street noises and high gain.", "audio": "/zhanghaomin/datas/musiccap/music_data/A2pgKzeDRqg.wav"} +{"id": "A3vsvL-Yx0Q", "caption": "A male singer leads backup singers in a vocal harmony. The song is medium tempo with a heavy percussive drum rhythm, strong bass line, keyboard accompaniment and a trumpet playing in unison with the vocals. The song is groovy and passionate and sounds like the theme song of a football club. The song audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/A3vsvL-Yx0Q.wav"} +{"id": "A446kjocnCg", "caption": "This song features percussion being played at a fast tempo. The beat is of moderate difficulty. The kick is played on the first count of each bar. The snare is played on the second and fourth counts of each bar. The hi-hat is played at a unique rhythm with accents on the first 'and' and the third, third and and fourth counts. There are no voices in this song. This is an instrumental song at a fast tempo. There are no other instruments in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/A446kjocnCg.wav"} +{"id": "A4jSRfZ6yd0", "caption": "A male vocalist sings this lively melody in a foreign language. The tempo is fast with a loud and banjo harmony, tambourine beats and tapping beats. The song is a spirited, cheerful,celebratory, happy, enthusiastic and festive Regional/Folk Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/A4jSRfZ6yd0.wav"} +{"id": "A4vwbziwPm8", "caption": "The low quality recording features a mixed harmonized vocals singing over quiet instrumental playing in the background. It is noisy and in mono, as it sounds heartfelt and emotional. It seems like it is a recording of a karaoke session, considering the volume balance between the vocals and instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/A4vwbziwPm8.wav"} +{"id": "A5fPSkTvjmY", "caption": "The low quality recording features a hip hop song that consists of a flat male vocal rapping over punchy kick and snare hits, shimmering hi hats, DJ scratching sound effects and groovy bass. It sounds energetic, upbeat and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/A5fPSkTvjmY.wav"} +{"id": "A6HJBIU1rD0", "caption": "This is a jazz song with some latin infusions into the style. The brass section plays bright and ascending melodies. The percussionists play bongos and snares with brushes. The song is fun and suitable for some loose dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/A6HJBIU1rD0.wav"} +{"id": "A6ilKRqIDH4", "caption": "The low quality recording features a DJ scratching a vinyl of an electro dub song that consists of uptempo hi hats, punchy kick and snare hits, short bass stabs, soft crash cymbal and simple synth melody. It sounds energetic, cool and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/A6ilKRqIDH4.wav"} +{"id": "A7RgbrJYe_s", "caption": "This song is used as a theme for a prank video. There is a keyboard and bass guitar providing the melodic background while a dissonant synth plays an on-the-nose comedic tune. There is a funky but simple electronic drum beat for the rhythmic background. Scratching sound effects and a laughing track were also used to emphasize the comedic element.", "audio": "/zhanghaomin/datas/musiccap/music_data/A7RgbrJYe_s.wav"} +{"id": "A8CJ4YSsUgs", "caption": "This is a country pop music piece. There is a female vocalist singing melodically as the lead. The melody comprises various elements such as the electric guitar, the bass guitar, the harmonica and the banjo. There is a rock acoustic drum beat in the rhythmic background. The atmosphere is easygoing. This piece could be the opening theme of a teenage sit-com.", "audio": "/zhanghaomin/datas/musiccap/music_data/A8CJ4YSsUgs.wav"} +{"id": "A8P5zzHCjJw", "caption": "This audio contains a fully overdriven aggressive kick sound with a lot of digital noise sounds. This is an amateur recording. This song may be playing in a post apocalyptic video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/A8P5zzHCjJw.wav"} +{"id": "A8b-0yWXBCE", "caption": "This music is an electronic instrumental. The tempo is medium fast with synthesiser arrangements, DJ mixer, turn table and digital drums. The music is futuristic , emphatic, intense, loud , enthusiastic; heavily synthesised and groovy. It has a psychedelic, trace-like vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/A8b-0yWXBCE.wav"} +{"id": "A9ECxUIqw6s", "caption": "A female teen voice is singing along with backing voices and screams. While acoustic drums are playing along with a simple bassline. The e-guitar is playing the suiting chords on top along with a high pitched sound coming out from a digital piano or organ. This song may be playing in a movie for the whole family.", "audio": "/zhanghaomin/datas/musiccap/music_data/A9ECxUIqw6s.wav"} +{"id": "AAFsg91kje4", "caption": "The Electro song features a repetitive synth keys melody playing over snare roll, claps, shimmering open hats, all being affected with a filter modulation, that serves as a build up element. It sounds exciting and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/AAFsg91kje4.wav"} +{"id": "AAP5pAB-4jM", "caption": "This song contains several synth pad sounds from the low, to the mid and higher register. Then the sounds stop and a glass breaking sound comes in as it gets reversed right away. This song may be playing in an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/AAP5pAB-4jM.wav"} +{"id": "AAWe4zRLVVU", "caption": "This is the opening theme of a program that was meant for kids. It is in an instrumental piece. There is a keyboard playing the main melody in the lead. There is a bass guitar playing in the background. The rhythm is provided by a fast-tempo acoustic drum beat. There are various sound effects that add a lively texture to this piece. The atmosphere is playful. This piece could be used in kids shows or cartoons. It could also be played during kindergarten activities or child birthday parties.", "audio": "/zhanghaomin/datas/musiccap/music_data/AAWe4zRLVVU.wav"} +{"id": "AAoqx07aTRI", "caption": "The song is an instrumental abstract piece. The song is medium tempo but with no actual pulse, whizzing sounds, shaker tones and buzzing noise and keyboard tones.The song is chaotic and highly experimental. The song is a psychedelic instrumental like a music Rorschach test.", "audio": "/zhanghaomin/datas/musiccap/music_data/AAoqx07aTRI.wav"} +{"id": "ABSLnckbB8w", "caption": "This is an ambient house music piece. There is no singer in the music. There are various resonating synth sounds used with ambient sound effects. Electronic drum hits can be heard reverberating in the piece. The atmosphere is airy. The best use for this piece would be either as an advertisement jingle or as a background music for a tutorial/instructive video.", "audio": "/zhanghaomin/datas/musiccap/music_data/ABSLnckbB8w.wav"} +{"id": "ABVYSaLu_VM", "caption": "Here we have a slow piano piece played in a major key. The peace feels calm and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ABVYSaLu_VM.wav"} +{"id": "ABWE9tjTvuI", "caption": "This song has a characteristically disco-like groove, with its funky bassline. There is an electric guitar where single notes are being plucked. The vocalist has an alternative indie type voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/ABWE9tjTvuI.wav"} +{"id": "ABr4Q_ecoPw", "caption": "The song is a funky, soulful disco song. The whole vibe is vibrant and upbeat and features a bouncy groove from a bass guitar as well as bright and shimmery sounding brass instruments. There's a sustained silky synth sound. The singer sounds cheerful. The song is suitable for dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/ABr4Q_ecoPw.wav"} +{"id": "AD3aI9avJ8Q", "caption": "The low quality recording features a distorted, processed male vocal with delay effect on. The recording is very noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/AD3aI9avJ8Q.wav"} +{"id": "AD5Tc2TDCmM", "caption": "This song features a guitar playing a solo. This is played in the style of a banjo in a bluegrass song. The guitar is playing fast licks. The bass plays the root note and lower fifth of the chords. A percussion plays a simple beat and ends with a crash. There are no voices in this song. This song is an instrumental song. Due to the low quality of the audio, other instruments cannot be identified. This song can be played in a bluegrass concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/AD5Tc2TDCmM.wav"} +{"id": "ADPSmeFofpo", "caption": "This music is an electronic instrumental. The tempo is fast with atmospheric synthesisers playing an intense harmony with boomy keyboard feedback. There is no other instrument or accompaniment except for a whooshing sound. The music sounds amateur and has a sinister, eerie, mysterious, spooky, scary vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/ADPSmeFofpo.wav"} +{"id": "ADffHhHMtjU", "caption": "This is a progressive rock music piece. There is a male vocalist singing melodically. The piano is playing the main melody while there is an airy keyboard backing. The atmosphere is gentle and sentimental. This piece could be used in the ending credits of a teenage drama movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/ADffHhHMtjU.wav"} +{"id": "ADxuhHNZVCc", "caption": "The low quality recording features a live opera performance sung by passionate female vocalists and followed by sustained and plucked strings melody. The recording is very noisy and the stereo image is unbalanced, since the audio from the left channel is occasionally cut out. It sounds emotional, mellow and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/ADxuhHNZVCc.wav"} +{"id": "AElgGuUSSKE", "caption": "This piece is a compilation of an opera singer's high-pitched singing that shows how high of a pitch she can reach. For the most part, she is holding a single high note as the strings in the orchestra provide the harmonic background.", "audio": "/zhanghaomin/datas/musiccap/music_data/AElgGuUSSKE.wav"} +{"id": "AEwkS57P4eE", "caption": "The low quality recording features a blues song that consists of passionate male vocal singing over groovy piano chords, brass melody, whistling melody and smooth bass. It sounds vintage and thus nostalgic and sentimental. The recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/AEwkS57P4eE.wav"} +{"id": "AEyeITzfPa0", "caption": "This is a Bhajan music piece. There is a male vocalist singing in a calm but devotional manner. The bansuri and the tanpura provide the melodic background of the song while the tabla percussion can be heard in the rhythmic background. There is a spiritual atmosphere to the piece. This music could be played at Hindu religious events and related social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/AEyeITzfPa0.wav"} +{"id": "AF7sah5a_DE", "caption": "someone is picking and strumming a melody on the acoustic guitar while a slide guitar is playing the main melody on top of it. Then an acoustic drum comes with an e-bass providing the rhythmic support.", "audio": "/zhanghaomin/datas/musiccap/music_data/AF7sah5a_DE.wav"} +{"id": "AFWy1qyyMHE", "caption": "Chill, tropical roots reggae music from the 1970's featuring a male vocalist, vocal harmonies, off beat guitar strums, phaser effect, a reggae drum beat and a simple bass part.", "audio": "/zhanghaomin/datas/musiccap/music_data/AFWy1qyyMHE.wav"} +{"id": "AFwmMFq_xlc", "caption": "A male singer sings this emotional song. The song is medium tempo with guitar accompaniment, strong bass line, steady drumming rhythm, violins playing emotional and tambourine percussion. The song is overlapped with sounds of a vehicle engine and Tarmac sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/AFwmMFq_xlc.wav"} +{"id": "AFwtBviVhhM", "caption": "This song is an instrumental. The tempo is medium with an enthusiastic electric guitar solo. There are no other instruments used. The guitar riff is loud, enthusiastic and youthful.", "audio": "/zhanghaomin/datas/musiccap/music_data/AFwtBviVhhM.wav"} +{"id": "AGNqX_OL-dU", "caption": "A male singer sings this cool melody with female and male backup singers in vocal harmony. The song is medium tempo with a groovy bass line, percussive drum rhythm, keyboard harmony and guitar rhythm. The song is exciting and groovy. The song is a R&B cover of a famous pop song. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/AGNqX_OL-dU.wav"} +{"id": "AGsMCWB1tTk", "caption": "A male vocalist sings this popular Christmas carol . The tempo is medium with soft acoustic guitar and steady drumming. The emphasis is on vocals and the highlight of this song is the cheerful and perfectly synced and harmonised vocalisation. It adds layers and textures and gives this age old song a makeover. It is light, happy, peppy, joyful, playful and cheerful.", "audio": "/zhanghaomin/datas/musiccap/music_data/AGsMCWB1tTk.wav"} +{"id": "AH6Xnyj6Ykc", "caption": "This ska song features a trumpet playing the main melody. The trumpet plays one staccato note followed by a six note pattern and then plays the same sequence starting on a different root note. This is accompanied by percussion playing a simple beat. A keyboard plays chords in the background. The bass plays a groovy bassline. There are no voices in this song. This is an instrumental song. The mood of this song is happy. This song can be played in a comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/AH6Xnyj6Ykc.wav"} +{"id": "AHmcuClSTL4", "caption": "This song contains an acoustic drum playing a simple rock groove with an e-bass playing a bassline along with the e-guitar strumming chords on the same notes as the bass. A deep male voice is singing, almost streaming sounding wild and loud. Then a synth pad comes in playing a melody panned to the left side of the speaker. This song may be playing at a rock festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/AHmcuClSTL4.wav"} +{"id": "AHrUfa2H_5s", "caption": "A male voice is singing in the mid-range with a lot of vibrato on some notes along with a shrutibox playing one chord. Here and there you can hear some hits of a tabla. The recording is full of voices talking in the background. This seems to be an amateur recording. This song may be playing at a concert with people sitting in chairs.", "audio": "/zhanghaomin/datas/musiccap/music_data/AHrUfa2H_5s.wav"} +{"id": "AI9P6HoiJy8", "caption": "Male and female singers sing this heavenly harmony . The song is slow tempo with a vocal four part harmony created by a choral section. The harmony is ethereal and emotional. The music is highly relaxing and pleasing.", "audio": "/zhanghaomin/datas/musiccap/music_data/AI9P6HoiJy8.wav"} +{"id": "AJROvxlmo40", "caption": "The low quality recording features suspenseful strings chords layered with a reversed crash riser, after which there is a flat female vocal talking. It sounds suspenseful and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/AJROvxlmo40.wav"} +{"id": "AJTU5RhF3S4", "caption": "This folk song features an accordion playing the main melody. Another accordion plays a backing melody and chords. The bass plays a groovy lick based around the root note of the chord. A triangle plays the part of the percussion. This is a low quality audio and the percussion is not audible. This song can be played in a village fair.", "audio": "/zhanghaomin/datas/musiccap/music_data/AJTU5RhF3S4.wav"} +{"id": "AJeRSlZuZbk", "caption": "This is a Kumaoni music piece. There is a male vocalist singing while playing a bina instrument at the same time. Both the vocal and the bina melody have a lot of vibrations.", "audio": "/zhanghaomin/datas/musiccap/music_data/AJeRSlZuZbk.wav"} +{"id": "AJj6GGLaIfI", "caption": "The low quality recording features a hypnotic mellow synth lead melody, low percussive elements, sustained synth strings and some hollow snare hits. It sounds noisy, resonating, but also nostalgic and sentimental, as it gives off an old console game soundtracks.", "audio": "/zhanghaomin/datas/musiccap/music_data/AJj6GGLaIfI.wav"} +{"id": "AJw-x30L46E", "caption": "This blues instrumental rock song features an acoustic guitar being aggressively strummed. There are no other instruments in this song. There are no voices in this song. The tempo of this song is fast. The rhythm of this song comprises fast upstrokes and downstrokes. Some of the strums are muted and the main rhythm is played with a mix of open and palm muted techniques.", "audio": "/zhanghaomin/datas/musiccap/music_data/AJw-x30L46E.wav"} +{"id": "AKI0VrXEDww", "caption": "The Soft Rock song features harmonizing male vocals singing over sustained organ keys chords, shimmering cymbals, groovy piano chords in the left channel, acoustic rhythm guitar in the right channel of the stereo image and groovy bass guitar. It sounds passionate and hopeful, like something you would sing along at concerts.", "audio": "/zhanghaomin/datas/musiccap/music_data/AKI0VrXEDww.wav"} +{"id": "ALU-1AILj1c", "caption": "This music is a mellifluous Indian classical instrumental. The tempo is fast with a harmonic sarod and rhythmic Oud accompaniment. The music is mesmerising, spirited, engaging, captivating and skilfully rendered Ragas. This instrumental is an Indian/Pakistani classical music.", "audio": "/zhanghaomin/datas/musiccap/music_data/ALU-1AILj1c.wav"} +{"id": "ALVS3Q_jNaU", "caption": "This is the recording of a jazz reggae concert. There is a saxophone lead playing a solo. There is a keyboard and an electric guitar playing the main tune with the backing of a bass guitar. In the rhythmic background, there is an acoustic reggae drum beat. The atmosphere is groovy and chill. This piece could be playing in the background at a beach. It could also be included in the soundtrack of a summer/vacation/tropical themed movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/ALVS3Q_jNaU.wav"} +{"id": "ALcCb2HJmG8", "caption": "A typical drum&bass drummer is playing at fast speed with a very liquid digital bass while a male voice is rapping super fast along to the instrumental. This song may be playing in a competition.", "audio": "/zhanghaomin/datas/musiccap/music_data/ALcCb2HJmG8.wav"} +{"id": "ANaaOqwO0Uo", "caption": "This is a meditation music piece. There is an ambient synth sound playing very faint notes. There are natural sounds that can be heard in the piece such as the water flowing and the crickets chirping. The atmosphere of the piece is relaxing and soothing. The piece would suit perfectly as background music for a meditation video. It could also be playing in the background at spas and wellness centers.", "audio": "/zhanghaomin/datas/musiccap/music_data/ANaaOqwO0Uo.wav"} +{"id": "AOgbZUl0y0A", "caption": "This is a Khaliji music piece. There is a male vocal singing in a melancholic manner in the Arabic language. The oud is playing a solemn melody in the background. There is a sentimental atmosphere. This piece could be used in the soundtrack of a drama movie taking place in the Arab world.", "audio": "/zhanghaomin/datas/musiccap/music_data/AOgbZUl0y0A.wav"} +{"id": "APSbmhJam74", "caption": "This is a Christian gospel music piece. There is a male vocalist singing melodically in the lead. The tune is being played by the acoustic guitar and the piano while the bass guitar is following with the root notes. The rhythm is played with brushes on the acoustic drums. The atmosphere is mellow. This piece could be playing in the background at Christian religious events.", "audio": "/zhanghaomin/datas/musiccap/music_data/APSbmhJam74.wav"} +{"id": "APTh9uhf7WQ", "caption": "This is the live recording of a dubstep performance. The DJ is performing the beat on a MIDI control panel. There is an ever-changing synth sound that plays the melody and also provides the strong and fuzzy bass. The rhythmic background consists of an aggressive electronic drum sound. The atmosphere is loud and energetic. This piece could be played at rave parties and at nightclubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/APTh9uhf7WQ.wav"} +{"id": "APUDprnfOIs", "caption": "The low quality recording features a plucked melody and groovy bass playing in the background and shimmering shakers and kids talking sound in the front. The recording is very noisy, as it was probably recorded with an old phone. It gives off happy and fun vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/APUDprnfOIs.wav"} +{"id": "ARXTRdKCupM", "caption": "The low quality recording features a punk song that consists of a groovy bass guitar, punchy kick, shimmering hi hats, energetic cymbals and aggressive electric guitar riffs. At the very beginning of the loop, there is a drum stick countdown, after which the bass drops. It sounds energetic, groovy and aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/ARXTRdKCupM.wav"} +{"id": "ASgLbz48BaY", "caption": "This song features an overdriven guitar being played. One single note is played with a vibrato. A metronome is playing in the background. There are no other instruments. There are no voices in this song. This song can be played in a guitar instruction video.", "audio": "/zhanghaomin/datas/musiccap/music_data/ASgLbz48BaY.wav"} +{"id": "ATDi-irUEWc", "caption": "The low quality recording features a muffled male vocal speaking, right after the didgeridoo tone. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ATDi-irUEWc.wav"} +{"id": "AT_076RUWPs", "caption": "This is a pop music piece. There is a male vocalist singing at a medium-to-high pitch in the lead. There is a melodic pad and an electric guitar sound providing the melody. A strong bass sound can be heard playing. The rhythm consists of a simple electronic drum beat. The atmosphere is energetic and danceable. This piece can be played at nightclubs and dance clubs. It could also be used during club scenes in movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/AT_076RUWPs.wav"} +{"id": "AU1l1i0H0j0", "caption": "The song is an instrumental. The song is medium tempo with a groovy bass line, techno drumming rhythm, keyboard synth string accompaniment and other percussive hits. The song is energetic and passionate. The song is a techno dance tune and has poor audio quality,", "audio": "/zhanghaomin/datas/musiccap/music_data/AU1l1i0H0j0.wav"} +{"id": "AUNK8dJzjLo", "caption": "This is the live performance of a traditional Greek folk music piece. The main melody is being played by a bouzouki which is a Greek instrument that is akin to the mandolin. There is a rhythmic accompaniment composed of a tambourine and the crowd clapping to the beat. The atmosphere is lively and upbeat. This piece could be playing in the background at a Greek tavern.", "audio": "/zhanghaomin/datas/musiccap/music_data/AUNK8dJzjLo.wav"} +{"id": "AUPmWhim37Y", "caption": "The song is an instrumental with a smattering of female and male vocals. The song is medium tempo with a groovy drum rhythm, church bell accompaniment, slick percussion hits, sustained bass hits, flute playing and vocal chants. The song is relaxing. The song is a techno lounge tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/AUPmWhim37Y.wav"} +{"id": "AUs5OVYg078", "caption": "A male voice is singing a melody with a lot of semitones. Following an accordion sounding instrument playing the same melody. This is an amateur recording. This song may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/AUs5OVYg078.wav"} +{"id": "AVG-Wmdd2yU", "caption": "Lush synth pads with reverb are accompanied by ambient static sounds which give way to a filtered male vocal over a simple, filtered electronic drum beat, giving a mellow ethereal feel to the music.", "audio": "/zhanghaomin/datas/musiccap/music_data/AVG-Wmdd2yU.wav"} +{"id": "AVJ-NxMmF6E", "caption": "A male vocalist sings this enthusiastic song,the tempo is fast with synthesiser articulation, rhythmic digital drum, cymbals and vocal backup. The music is upbeat, youthful, enthusiastic, compelling, intense and passionate with a catchy beat and riff. This song is an EDM/Synth pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/AVJ-NxMmF6E.wav"} +{"id": "AVPm96vrUQw", "caption": "This is a video game theme. There is an arcade synth playing the main theme at a medium-to-high pitch. The character of the piece is analog sounding. There is a playful and adventurous atmosphere. This piece could be used in movies, TV shows and advertisements targeted at kids. It could also be used in video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/AVPm96vrUQw.wav"} +{"id": "AVVfOYSmexM", "caption": "The low quality recording features a muffled echoing male vocal singing over a muffled instrumental. It sounds noisy, but also passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/AVVfOYSmexM.wav"} +{"id": "AVmJF1uaRuE", "caption": "This classical Indian song features a male voice singing in vocables without any lyrics. This is accompanied by a harmonium playing the same melody as the voice and continuing to play after the voice has rested. Sitars are playing in the background. There is no percussion in this song. This song can be played in a retro movie in which a classical singer is performing in front of a live audience.", "audio": "/zhanghaomin/datas/musiccap/music_data/AVmJF1uaRuE.wav"} +{"id": "AVogdV8khxc", "caption": "This is a Christian gospel music piece. There is a male vocalist singing melodically and in an emotion-filled manner. The keyboard is playing the melody with a harp sound while the rhythmic background consists of a simple acoustic sounding drum beat that is only played on the hi-hats. The atmosphere is spiritual. This piece could be playing in the background at a Christian religious event.", "audio": "/zhanghaomin/datas/musiccap/music_data/AVogdV8khxc.wav"} +{"id": "AVsNJgR_K6w", "caption": "This is a congregational singing performance performed at a Christian church. Male and female voices from all age groups are singing together in this piece. The atmosphere is religious. This piece could be used in the soundtrack of a gospel movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/AVsNJgR_K6w.wav"} +{"id": "AVuh8-CucrE", "caption": "The low quality recording features funky electric guitar chords, electric guitar solo melody and groovy bass playing in the background. The recording is very noisy, distorted and harsh, but it is still easygoing and chill - like something you would listen to when you are trying to relax.", "audio": "/zhanghaomin/datas/musiccap/music_data/AVuh8-CucrE.wav"} +{"id": "AYOlvoM5bjY", "caption": "The low quality recording features a wide shimmering shakers, soft crash cymbals, wide whistling and crowd cheering sounds, followed by addictive accordion melody, walking double bass and \"4 on the floor\" cowbell pattern. It sounds fun, happy, sentimental, euphoric and nostalgic.", "audio": "/zhanghaomin/datas/musiccap/music_data/AYOlvoM5bjY.wav"} +{"id": "AY_yCk4eTTI", "caption": "This is a tutorial video recording on how to tune an acoustic guitar to drop D tuning. There is a female voice speaking in an instructive manner as she is plucking the chords and tuning the acoustic guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/AY_yCk4eTTI.wav"} +{"id": "AYln23c8g6w", "caption": "A synth lead is playing a high pitched melody along with a piano playing chords. The piano has some delay and in the background you can hear a thin synth pad rising in volume with all the other instruments. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/AYln23c8g6w.wav"} +{"id": "AZsupJ68Hp0", "caption": "The song is instrumental music. The tempo is medium tempo with a piano bass note playing rhythmically, along with piano accompaniment, a violin playing a high pitched drone along with pizzicato violins. The song is tense and includes ambient Street noises like birds chirping and cups rattling. The song is a movie soundtrack for a specific scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/AZsupJ68Hp0.wav"} +{"id": "A_NkQM85g6Q", "caption": "The low quality recording features a widely spread harpsichord melody. The recording is a bit noisy and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/A_NkQM85g6Q.wav"} +{"id": "A_Yd5huF2Pg", "caption": "The song is an instrumental. The tempo is medium with a church organ playing melody, steady drumming rhythm, cymbals crashing, tambourine percussion, steady bass, and guitar playing rhythm. The song is exciting and retro nostalgia. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/A_Yd5huF2Pg.wav"} +{"id": "A_oaLt-n4fQ", "caption": "The low quality recording features a hip hop song that contains boomy bass, punchy snare layered with claps, DJ scratching sound effects, addictive staccato violin melody and haunting female vocals melody in the background. The recording is in mono and it sounds energetic and addictive, regardless of the quality of the recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/A_oaLt-n4fQ.wav"} +{"id": "AaUZb-iRStE", "caption": "This is an amateur recording of heavy metal music being performed live. The audio quality is quite poor. There is a distorted electric guitar playing the main tune while the bass guitar is playing in the background. There is a simple metal acoustic drum beat in the rhythmic background. Sounds from the crowd cheering and screaming can be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/AaUZb-iRStE.wav"} +{"id": "AaVUuKl8294", "caption": "A boys' singing slow, stoic spiritual music accompanied by harp and a woodwind ensemble. No drums.", "audio": "/zhanghaomin/datas/musiccap/music_data/AaVUuKl8294.wav"} +{"id": "AaajkQEU3A0", "caption": "This song contains someone playing a melody on the oud. This song may be playing by a performer live on stage.", "audio": "/zhanghaomin/datas/musiccap/music_data/AaajkQEU3A0.wav"} +{"id": "AagemOzvoZE", "caption": "This song is a romantic duet. The tempo is medium with a plethora of instruments like the auto harp, fiddle, acoustic guitar, electric guitar, bass guitar, banjo,intense drumming, cello, violin harmony and vocal harmony. The song is a romantic, charming,emotional, passionate love song. The instrumentation style and music decibels indicate that this is the climax of a country love song.", "audio": "/zhanghaomin/datas/musiccap/music_data/AagemOzvoZE.wav"} +{"id": "Aak-VLHtFPM", "caption": "This music is a lively instrumental. The tempo is fast with an enthusiastic Brass and wind instrument harmony. The vigorous trumpets, trombone and tuba accompaniment, along with clanging cymbals and playful clarinet make for an upbeat, cheerful, happy, energetic and Perky Band Music.", "audio": "/zhanghaomin/datas/musiccap/music_data/Aak-VLHtFPM.wav"} +{"id": "AareFwTIg1s", "caption": "Someone is playing a piece of music on an accordion. The song sounds uplifting. This song may be playing live at a local theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/AareFwTIg1s.wav"} +{"id": "Ac4M-EkdkDs", "caption": "The Trap song features a very short snippet of hard 808 bass, shimmering hi hats, punchy snare and synth keys melody after which comes the second part of the loop where there is a wide filtered stuttering down sweep sound effect. It sounds like an interlude in the middle of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ac4M-EkdkDs.wav"} +{"id": "AcX1B_Pr-RQ", "caption": "The low quality recording features a reggae song sung by low flat male vocals, followed by repetitive synth lead melody, groovy bass, vocal chants, claps, punchy kick hits, shimmering hi hats and open hats. It sounds energetic, suspenseful and it is in mono. At one point the vocal cracks and it sounds out of tune for a split second.", "audio": "/zhanghaomin/datas/musiccap/music_data/AcX1B_Pr-RQ.wav"} +{"id": "AcX6rAwFTiY", "caption": "This song contains a female voice singing a melody along with a flute and strings playing the same melody. You can hear white noise that almost sounds like rain. This song may be playing in a movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/AcX6rAwFTiY.wav"} +{"id": "Ade0UZnb6dw", "caption": "This is a modern sounding Afrobeat music piece. There is a male vocal singing the same line repeatedly vocal with a male back vocal ad-libbing in the background. The electric guitar is playing a mellow tune. A low-to-medium range bass line that can be heard. The rhythm consists of an acoustic drum beat with supporting percussive elements. Brass stabs can be heard every now and then. The atmosphere is groovy. This piece could be played at African nightclubs or dance clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ade0UZnb6dw.wav"} +{"id": "AdxKsUW2mAo", "caption": "There is a meditative chant sung at a medium pitch by a female voice. In the background, an acoustic guitar plays a mellow tune while an ambient synth can be heard holding the bass notes of the chant. It has a peaceful atmosphere which makes it a perfect match for meditation sessions.", "audio": "/zhanghaomin/datas/musiccap/music_data/AdxKsUW2mAo.wav"} +{"id": "Ae8o_FMI0Xs", "caption": "This is a DJ freestyle performance with old-school and latin house influences. There is a female vocalist singing melodically with an 80s pop feel. A fuzzy synth bass is playing a groovy bass line. In the rhythmic background, there is an electronic drum beat with a 909-like sound. The atmosphere is eccentric and the sound is modern. This performance could be played at nightclubs or dance clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ae8o_FMI0Xs.wav"} +{"id": "AeDNy6Ff7VE", "caption": "This is a groovy R&B piece that is used as a soundtrack for a short film. A saxophone plays the main tune while the synth provides the backing theme. Playful electronic drums are in the rhythmic background giving it a 90 feeling. The music piece could be used as a soundtrack theme for a city-themed movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/AeDNy6Ff7VE.wav"} +{"id": "AeXDtbfpQlQ", "caption": "A male vocalist sings this simple melody. The song is medium tempo with steady keyboard harmony ,boomy bass drops and rhythmic finger snapping. The vocalist is spelling a word in a simple melody indicating that this song is a Children\u2019s Song . It is educational, simple, catchy, bouncy and a fun way of learning to spell small words.", "audio": "/zhanghaomin/datas/musiccap/music_data/AeXDtbfpQlQ.wav"} +{"id": "AgCSBCsHkMk", "caption": "The low quality recording features water and some metallic sound effects, followed by a dynamic orchestra that consists of a mellow string section, simple plucked harp and mystical woodwinds playing in the background. In the first part of the loop, the sound is completely muffled. It sounds like something you would hear in old movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/AgCSBCsHkMk.wav"} +{"id": "AgJH6Ul1EFg", "caption": "The low quality recording features a mellow piano melody playing over sustained strings melody. It sounds sad, emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/AgJH6Ul1EFg.wav"} +{"id": "AgVUGzrzJ20", "caption": "The low quality recording features a jazz song that consists of groovy double bass located in the right channel, groovy piano melody leaning towards the left channel of the stereo image and widely spread shimmering shakers and soft hi-hats. It sounds smooth, chill, easygoing and relaxing - like something you would hear in high-end restaurants.", "audio": "/zhanghaomin/datas/musiccap/music_data/AgVUGzrzJ20.wav"} +{"id": "AgtY6m-b3Gk", "caption": "This is an instrumental jazz improvisation piece with heavy bossa nova influences. There is an over-arching bossa nova syncopation not only being played by the acoustic drums in the backing track but also followed by the electric rhythm guitar and the bass guitar. The lead is a guitar solo being played by a gentle sounding electric guitar. Although there are complex chords and riffs, the general atmosphere is tranquil. This piece could be playing in the background of a restaurant. It could also be included in the soundtrack of a movie during serene scenery.", "audio": "/zhanghaomin/datas/musiccap/music_data/AgtY6m-b3Gk.wav"} +{"id": "Ah_aYOGnQ_I", "caption": "The low quality recording features an EDM song that consists of shimmering bells, buzzy synth bass, pulsating synth chords, snaps, claps, punchy kick, shimmering open hats and tambourine hits. The recording is a bit noisy, but it sounds energetic. The mix is a bit dirty, which makes the song sound a bit messy in terms of frequencies.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ah_aYOGnQ_I.wav"} +{"id": "AiGGDpbgp6I", "caption": "This audio contains someone playing a 8 string e-bass, fingerpicking and tapping a soothing soft melody in a higher register with some long bass notes underneath. This may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/AiGGDpbgp6I.wav"} +{"id": "Ail32Z1T4QM", "caption": "This song contains experimental synth sounds creating a dark and mystical atmosphere. This song may be playing at a festival building up tension.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ail32Z1T4QM.wav"} +{"id": "AjLX_1rBDPM", "caption": "The song is an instrumental Indian classical tune. The song is medium tempo with two Indian double reed instruments called nadaswaram playing in a duet. The song is emotional and highly lyrical . The song is amateur quality recording and a classic Carnatic music tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/AjLX_1rBDPM.wav"} +{"id": "AjLuenrAsbE", "caption": "An acoustic drum is playing a 3/3 groove along with a bass. Two e-guitars are playing melodie while one of the e-guitars is highly distorted and takes the lead with a loud and wild melody in the higher register. This song may be playing in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/AjLuenrAsbE.wav"} +{"id": "AjjQqd0eLzw", "caption": "Someone is playing an instrument sounding like a bowl/pad/whale singing in a metallic tone with a long sustain and shifting in pitch. This song may be playing in a horror-movie scene. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/AjjQqd0eLzw.wav"} +{"id": "AkHaDKuiE_s", "caption": "This is an instrumental percussion piece. There is an acoustic latin drum kit composed of the cowbells and the timbales. The drummer is playing an energetic solo on this kit. This piece could be playing in the background at a drum shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/AkHaDKuiE_s.wav"} +{"id": "AkbCw7oVkw0", "caption": "The Indie song features a reverberant male vocal passionately singing over electric guitar chords. It sounds emotional, sad and passionate - like something you would listen to while feeling down.", "audio": "/zhanghaomin/datas/musiccap/music_data/AkbCw7oVkw0.wav"} +{"id": "Akg1n9IWSrw", "caption": "This audio contains a big wind sound before an acoustic drum starts playing a pattern on the toms with an opening and closing hihat. Then a male voice starts speaking at a higher pitch. Other male voices seem to respond to him. This song may be playing in the background for a movie skit.", "audio": "/zhanghaomin/datas/musiccap/music_data/Akg1n9IWSrw.wav"} +{"id": "Aky0DF507fw", "caption": "This is a didgeridoo jam piece. The didgeridoo is playing tunes at a pitch varying from low to medium. There is a tribal sound to this recording. It could be used in the soundtrack of a movie/TV series with a jungle/primitive setting. It could also be sampled to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/Aky0DF507fw.wav"} +{"id": "AlVr7-ntuqw", "caption": "This jazz song is an instrumental song featuring a trombone playing the main melody. The trombone is accompanied by a piano playing chords using jazz rhythms. The tone changes at the end to an uplifting mood. There is no percussion in this song. This song can be used in a highway driving scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/AlVr7-ntuqw.wav"} +{"id": "Al_OdIuqoe0", "caption": "This is the live performance of an afrobeat music piece. There is a male voice singing occasionally. The melody is being played by a wide variety of instruments such as the electric guitar, the keyboard and the bass guitar. There is a saxophone playing a solo. In the rhythmic background, there is an acoustic drum beat in the style of afrobeat. It is joined by percussive elements. There is a vibrant atmosphere in this recording. This piece could be playing in the background of a West African cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/Al_OdIuqoe0.wav"} +{"id": "AmAThmRphk0", "caption": "The Jazz song features a passionate solo acoustic guitar melody and acoustic rhythm guitar chords, followed by simple double bass. It sounds smooth and elegant, something you would hear in fancy restaurants or good jazz clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/AmAThmRphk0.wav"} +{"id": "An-4jPvUT14", "caption": "A male singer sings this hip hop song with backup singers in vocal harmony. The song is medium tempo with slick drumming rhythm, groovy bass line, and keyboard harmony. The song is story telling and emotional in nature. The song has poor audio quality with ambient noises like squeaking wheel tones.", "audio": "/zhanghaomin/datas/musiccap/music_data/An-4jPvUT14.wav"} +{"id": "AnErEDywInE", "caption": "This song contains a brass section playing a melody and a string section taking over with a melody. A harp is playing a melody in the background along with plucked celli. An upright bass is playing single notes along. A male voice is singing loud and with an opera technique. This song may be playing while watching an opera.", "audio": "/zhanghaomin/datas/musiccap/music_data/AnErEDywInE.wav"} +{"id": "AnMR6SOBa9k", "caption": "This song is an instrumental. The tempo is slow with an intense spanish guitar melody, and keyboard accompaniment. The music is intense, deliberate, scary, sinister, spooky , eerie and meant to induce fear.", "audio": "/zhanghaomin/datas/musiccap/music_data/AnMR6SOBa9k.wav"} +{"id": "AobHGHJSd-s", "caption": "This is a live performance of what sounds like a Middle Eastern. The female singer has a calm and soothing voice which she uses to sing vocables - or open mouthed humming. There are percussive chimes, and an acoustic guitar arpeggio which adds to the calm and soothing feel of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/AobHGHJSd-s.wav"} +{"id": "ApDJYsi9UGg", "caption": "This audio clip is a harmonica melody with vocalisation.The music is dissonant with the sound of a dog howling/whining to the rhythm of the harmonica. It is sweet, entertaining and adorable.", "audio": "/zhanghaomin/datas/musiccap/music_data/ApDJYsi9UGg.wav"} +{"id": "AqSV_WKZxEc", "caption": "The song is an instrumental. The tempo is slow with a string section harmony with sweeping lines of music, piano playing poignantly and emotional chord changes. The song is a movie soundtrack that has an air of suspense and hope. The song audio quality is very poor with hissing tones.", "audio": "/zhanghaomin/datas/musiccap/music_data/AqSV_WKZxEc.wav"} +{"id": "Aro-HcWNsHI", "caption": "The low quality recording features an acoustic rhythm guitar playing over a pop song played on playback in the background. It sounds joyful and happy, while the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Aro-HcWNsHI.wav"} +{"id": "Arqvnp6yUCg", "caption": "This composition contains a lot of lower pitched percussive sounds. Timpanis are playing rolls that are getting louder at the peak a gong is played loudly. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/Arqvnp6yUCg.wav"} +{"id": "AsR5us-IS00", "caption": "This is the live recording of an alternative metal piece. There is a male vocal screaming every now and then. There is a heavy use of electronic elements which makes up for the majority of the melodic structure. There is a distorted electric guitar and a bass guitar playing. The rhythmic background consists of an aggressive acoustic metal drum playing in synchrony with the electronic elements. The atmosphere is energetic and violent. This piece could be playing in the background at a metal bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/AsR5us-IS00.wav"} +{"id": "At5v5ZZQHmw", "caption": "The low quality recording features a live performance of R&B/Soul song and it consists of passionate female vocal singing alongside widely spread harmonizing female background vocals. It sounds passionate, emotional and heartfelt.", "audio": "/zhanghaomin/datas/musiccap/music_data/At5v5ZZQHmw.wav"} +{"id": "AtJ2RXQ98kY", "caption": "A male singer sings this cool melody with backup singers in vocal harmony. The tempo is medium with a groovy drumming rhythm, guitar accompaniment, piano accompaniment, percussive bass line and ambient crowd noises. The song is a modern Asian pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/AtJ2RXQ98kY.wav"} +{"id": "AtWf5OAE8aM", "caption": "Quirky, cheeky, jazzy music featuring a lead trombone melody, a triangle playing a swing pattern, a cheesy organ and a medium tempo.", "audio": "/zhanghaomin/datas/musiccap/music_data/AtWf5OAE8aM.wav"} +{"id": "AuG9i5cwGW0", "caption": "The Alternative/indie song features harmonizing male vocals singing over groovy bass, punchy kick and snare hits, straight piano chords, synth lead melody and arpeggiated synth melody. It sounds groovy and addictive - like something you would hear in clubs during the 80s.", "audio": "/zhanghaomin/datas/musiccap/music_data/AuG9i5cwGW0.wav"} +{"id": "AuZNuyR2OJs", "caption": "This music is an Electronic instrumental. The tempo is medium with synthesiser articulation and drum machine arrangement. The music is muffled as the audio is of poor quality and the recording is done outdoors. There are ambient nature sounds in the background like the wind and some rustling.", "audio": "/zhanghaomin/datas/musiccap/music_data/AuZNuyR2OJs.wav"} +{"id": "AuvFmMpgj70", "caption": "This is an instrumental jam recording. The only instrument being played is a didgeridoo. A solo is being played on this instrument with a wide variety of frequencies. There is a resonant sound. The atmosphere is unique. Samples could be lifted from this recording to use in beats.", "audio": "/zhanghaomin/datas/musiccap/music_data/AuvFmMpgj70.wav"} +{"id": "AuwwPMrH5sE", "caption": "This is the electric guitar cover of a pop punk/pop rock music piece. There is an electric guitar playing a simple riff. In the backing track, a male vocalist is singing melodically at a high range.", "audio": "/zhanghaomin/datas/musiccap/music_data/AuwwPMrH5sE.wav"} +{"id": "Aw2ctwyhe28", "caption": "This song contains acoustic drums with a fat kick drum and a funky bassline. The acoustic guitar is strumming chords in the background being panned to the left side of the speaker while a e-guitar panned to the right side of the speaker is playing the lead melody strumming chords with a wah-wah pedal. A male backing voice is singing the same melody in a loop. The male lead voice is singing over the backing vocals. This song may be playing on a road trip.", "audio": "/zhanghaomin/datas/musiccap/music_data/Aw2ctwyhe28.wav"} +{"id": "AwcuLXAPFDs", "caption": "This song contains a complex digital drum groove with a loud snare sound and fast sharp hihats. A synth stab sound is running through a fast arpeggiator. A lower arpeggiated synth sound is provided by the bassline along with a sub bass panning to both sides of the speakers. This song is full of electronic effects and noises. This song may be playing in an arcade video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/AwcuLXAPFDs.wav"} +{"id": "AzGtPHlrlzU", "caption": "The low quality recording features an electro song played on a device that produces the mono sound only. The song features a flat male vocal rapping, after which there is a drop that consists of punchy kick and snare hits, shimmering cymbals and synth lead melody. It sounds exciting and energetic, while the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/AzGtPHlrlzU.wav"} +{"id": "AzWIKyRnhG8", "caption": "A male vocalist sings this gentle Puja song. The tempo is slow with atmospheric synthesiser, chimes, keyboard harmony and electronic arrangements to give an intense, ethereal, celestial vibe. The song is a Sanskrit chant, melodious prayer, and devotion song. It is soothing, calming, meditative, prayerful, reflective and pensive.", "audio": "/zhanghaomin/datas/musiccap/music_data/AzWIKyRnhG8.wav"} +{"id": "AzhfZ8rNhRk", "caption": "This is the noise of a fire alarm with rock music faintly playing in the background. The rock music piece has a shouting vocal, electric guitar and drums. The fire alarm makes a very disturbing sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/AzhfZ8rNhRk.wav"} +{"id": "AzsBSUmhl1M", "caption": "The low quality recording features a folk song that consists of an echoing male vocal singing over syncopated toms, punchy kick, shimmering hi hats and wide plucked strings melody. It is kind of noisy and the vocals are really loud, compared to other instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/AzsBSUmhl1M.wav"} +{"id": "B-1QW7g81gA", "caption": "The Curacao Waltz song features a flamenco guitar melody, electric bass guitar, acoustic guitar chords and shimmering shaker. Sounds very reverberant, as no instruments are clearly heard in the recording - except for the flamenco guitar. Overall, the recording is low quality, as the bad stereo microphone setup was used.", "audio": "/zhanghaomin/datas/musiccap/music_data/B-1QW7g81gA.wav"} +{"id": "B00nfVc4FPI", "caption": "A female vocalist sings this upbeat country song. The tempo is fast with enthusiastic fiddle, banjo, resonator, mandolin and dobro accompaniment, tambourine beats, keyboard harmony, bright drumming and groovy bass lines. There is sound of clapping, cheering, people talking, party horns and hooting superimposed on the song, indicating that this is a live performance. The song is a spirited, lively,happy, punchy and buoyant Country Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/B00nfVc4FPI.wav"} +{"id": "B1beLwV4yzw", "caption": "This is a rock music piece. It starts with a clock. There is a female vocalist singing melodically in the Thai language. The overdriven electric guitar is strumming the chords of the main tune while the bass guitar is supporting it in the background. The acoustic drum is playing a simple but powerful beat. The general atmosphere is energetic. The piece can be used as a soundtrack in a coming-of-age drama taking place in Thailand.", "audio": "/zhanghaomin/datas/musiccap/music_data/B1beLwV4yzw.wav"} +{"id": "B1ixRtiUJ-U", "caption": "The song is an instrumental. The tempo is medium with a cellist playing a JS Bach tune with exemplary skill in a rehearsal session. The song has bad audio quality. The song is a western classical music tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/B1ixRtiUJ-U.wav"} +{"id": "B1vY7kxQ9Xg", "caption": "The electro song features a filtered echoing male vocal speaking over layered riser and kick impact, after which there is a repetitive high pitched vocal, male chants, pulsating synth bass and addictive synth lead melody. It sounds exciting, happy and fun - like something you were listening to when you were younger.", "audio": "/zhanghaomin/datas/musiccap/music_data/B1vY7kxQ9Xg.wav"} +{"id": "B1va1NqaA4o", "caption": "This rap song features a male voice rapping in a foreign language. This is accompanied by programmed percussion playing a simple beat. The bass plays the root note of the chord in sets of 3 strokes. The same note is played through the song in sets of three. A repetitive plucked synth sound is played in loop. Quirky sounds are heard in the background. This song has a defiant mood. This song can be played in a gangster movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/B1va1NqaA4o.wav"} +{"id": "B2yLFcmZ51I", "caption": "A female singer sings this cool melody with backup singers in vocal harmony. The song is fast tempo with a percussive bass line, steady drumming with various percussion hits, keyboard harmony and other sonic effects. The song is groovy and exciting. The song is a modern techno dance hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/B2yLFcmZ51I.wav"} +{"id": "B32m9Jqqrpo", "caption": "The low quality recording features a DJ that scratches his vinyl hip hop song. The song consists of punchy snare and kick hits, bouncy hi hats and boomy bass. It is noisy, uptempo, energetic and it sounds a bit sloppy.", "audio": "/zhanghaomin/datas/musiccap/music_data/B32m9Jqqrpo.wav"} +{"id": "B3WaJ_3M0vw", "caption": "This clip features a combination of different parts. There are footsteps outdoors, the sound of peeling or squishiness, a muffled voice and rock music at the end. The rock music is hard rock music which features a grungy electric guitar and some simple punchy drumming.", "audio": "/zhanghaomin/datas/musiccap/music_data/B3WaJ_3M0vw.wav"} +{"id": "B3lq6U4PDZo", "caption": "This instrumental song features a melody played using bells. There are chiming sounds played in the background like clockwork. A theremin plays a vibrato note. There is no percussion in this song. This song has a spooky theme and can be used in a children's scary movie. There is a lot of white noise that can be heard in this low quality recording. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/B3lq6U4PDZo.wav"} +{"id": "B3q2wHpzhoM", "caption": "This composition contains a string section playing a rising and dissonant chord along with strings playing short notes. In the background you can hear atmospheric noises. This song may be playing in a scary movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/B3q2wHpzhoM.wav"} +{"id": "B41tuPoJ61c", "caption": "A digital drum beat repeats the same pattern with a strong and reverbed snare sound. An aggressive low to mid range sound is playing a melody underlined by a sub bass. On top of that a synth lead sound is playing a melody in the higher register that repeats itself the whole time. This song may be playing in an action video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/B41tuPoJ61c.wav"} +{"id": "B496Qv0CuOQ", "caption": "This song is a Retro electronic instrumental. The tempo is fast with electronically arranged music, slick drumming, bright amplified keyboard harmony, tambourine beats,synthesiser arrangements and male and female vocalisation. The song is youthful, groovy,vibrant, upbeat, passionate, catchy and punchy. This song is a Retro EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/B496Qv0CuOQ.wav"} +{"id": "B4KIQtk7fT4", "caption": "This is a gear showcase jam. The bass guitar is playing a random tune while it is connected to a synth pedal that constantly changes the characteristics of its sound. The piece starts out with a fat and wobbly sound and then later turns into a crisp synth sound. These sounds could be sampled for use in beat-making. It could also work well in the soundtrack of an outer space video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/B4KIQtk7fT4.wav"} +{"id": "B4lGhVjoMTk", "caption": "The soundtrack has a bell ringing producing several overtones and a man speaking the benefits of the therapy. The music produced is healing in nature and helps in the overall well-being. The sound quality is pretty average. The tempo is slow.", "audio": "/zhanghaomin/datas/musiccap/music_data/B4lGhVjoMTk.wav"} +{"id": "B5XTBvnpwqU", "caption": "We hear a vintage middle eastern traditional song. The instrument is an old flute, and we have an elderly man singing. There's a crackling sound throughout the recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/B5XTBvnpwqU.wav"} +{"id": "B7V_grbxflg", "caption": "This song sounds sensual, slightly erotic. The female voice is singing in the mid range and with delay and reverb on her voice. The bass is playing long notes with little changes. The drums are playing a rather complex groove. An e-guitar is playing single notes contributing to the rhythm while another guitar is playing an almost looped melody on top. This guitar has some effect on it and it sounds sensual and provocative. Synthesizer hits and keys are adding more little elements that are panned to the left and right side of the speakers. This is a very rhythmic song with its harmonic elements. This song may be playing at a nightclub for adults.", "audio": "/zhanghaomin/datas/musiccap/music_data/B7V_grbxflg.wav"} +{"id": "B7iRvj8y9aU", "caption": "This is a country music piece. A steel guitar is playing the main melody. There is a bass guitar in the background playing a mellow bass line. A slow tempo, mild-volume acoustic drum track is in the rhythmic background. The general atmosphere is relaxing. This piece could be used in the soundtrack of movies that take place in rural USA. It could also be played in western-themed bars.", "audio": "/zhanghaomin/datas/musiccap/music_data/B7iRvj8y9aU.wav"} +{"id": "B8pesuUc8Ek", "caption": "A male singer sings this retro pop melody. The song is medium tempo with a steady drumming rhythm, steady bass line, guitar accompaniment, and fiddler playing. The song is romantic and slow dance-like. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/B8pesuUc8Ek.wav"} +{"id": "B90BOtSOD2Q", "caption": "A female singer sings this bluesy melody. The song is medium tempo with minimal guitar accompaniment and no other instrumentation. The song's medium tempo is very emotional and passionate. The song is a modern pop hit but with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/B90BOtSOD2Q.wav"} +{"id": "B9IAl-ygE2k", "caption": "This techno song features a male voice narrating a line. The song starts off with programmed percussion playing the kick and sleigh bells on alternate counts of the bar. A sliding sound is heard in the background like a sleigh on snow. The volume of the sliding sound increases in volume toward the end. A vinyl scratch is played two times. Toward the end, the instruments pause and a male voice narrates a line. This song can be played in a promotional video about a Christmas DJ party.", "audio": "/zhanghaomin/datas/musiccap/music_data/B9IAl-ygE2k.wav"} +{"id": "B9K58KYq-Cs", "caption": "This is a meditation track. There is a mellow sounding ambient synth in the background. A female voice can be heard speaking gently in the Spanish language. The general atmosphere of the track is calm.", "audio": "/zhanghaomin/datas/musiccap/music_data/B9K58KYq-Cs.wav"} +{"id": "B9ME0Vcm_xA", "caption": "This is an instrumental alternative music piece. There are two electric guitars with heavy effects playing chill melodies. A distinct crackling effect can be heard. The rhythm consists of a medium tempo percussion beat. The atmosphere is trippy. This piece can be used in the soundtrack of a drama movie, especially during a flashback scene involving good memories.", "audio": "/zhanghaomin/datas/musiccap/music_data/B9ME0Vcm_xA.wav"} +{"id": "BAUQY0e25DM", "caption": "This is the live performance of an Islamic nasheed. There is no instrument in this piece. There is a male vocalist singing the piece in a devotional manner. This piece could be used in Islamic social media content/Islamic radio stations.", "audio": "/zhanghaomin/datas/musiccap/music_data/BAUQY0e25DM.wav"} +{"id": "BBSApRvkaqY", "caption": "This is the sound of a didgeridoo being played. This sound alternates between a droning sound and a deep bass sound. There are no other instruments in this song. There are no voices in this song. This song can be played in a movie featuring aboriginals.", "audio": "/zhanghaomin/datas/musiccap/music_data/BBSApRvkaqY.wav"} +{"id": "BBmXMoI9Qus", "caption": "The Ambient music features soft metallic percussive elements and wide synth pad chords. It sounds calming, relaxing, mellow and soft - like something you would listen to while meditating.", "audio": "/zhanghaomin/datas/musiccap/music_data/BBmXMoI9Qus.wav"} +{"id": "BC7dI3lQ2Cg", "caption": "This Mexican song features a male voice singing a repetitive melody. This is accompanied by percussion playing a simple beat. Shakers are played in the background. The bass plays a repetitive bassline. A piano plays one chord on the 'and' part of alternate counts in each bar. The song has a monotonous feel. This song is at a moderate tempo. This song can be played at a party.", "audio": "/zhanghaomin/datas/musiccap/music_data/BC7dI3lQ2Cg.wav"} +{"id": "BDH7Fx1APR8", "caption": "This song has a repeating bassline that is accompanied by a highly distorted e-guitar playing along the low notes with the bass. The other strongly reverbed e-guitar is playing a long note melody against the beat of the drums that is playing loud and with a lot of open hihat. The male voice sounds loud and aggressive. He is screaming/singing in a higher pitched tone. This song may be played at a live rock festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/BDH7Fx1APR8.wav"} +{"id": "BEEknOFrVdU", "caption": "This is a Japanese pop-punk music piece. There is a teen female vocalist singing merrily and melodically in the English language. There is a distorted electric guitar playing the main tune with a bass guitar. The rhythmic background consists of a fast-paced punk beat being played on the acoustic drums. The atmosphere is uplifting. This piece could be used in the soundtrack of a teenage/young adult feelgood movie/TV show. It could also take place in the soundtrack of an animation movie or an anime.", "audio": "/zhanghaomin/datas/musiccap/music_data/BEEknOFrVdU.wav"} +{"id": "BEZdszHKGTQ", "caption": "This is a tutorial of a song that could be described as blues-rock. The performer plays the harmonica while strumming chords on an acoustic guitar. The feel of the instrumental is reflective, mellow and bluesy.", "audio": "/zhanghaomin/datas/musiccap/music_data/BEZdszHKGTQ.wav"} +{"id": "BEhIGoq9tow", "caption": "The low quality recording features a mellow synth pad, mellow snare hits, soft kick hits, reverberant tinny bells, groovy bass and there is a flat male vocal singing over it. It sounds calming and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/BEhIGoq9tow.wav"} +{"id": "BEwNrjvNiYs", "caption": "The Metal song features wide harmonizing hums in the background and repetitive harmonized mixed vocals singing over them. It sounds quiet and low quality as the mix is not very clean.", "audio": "/zhanghaomin/datas/musiccap/music_data/BEwNrjvNiYs.wav"} +{"id": "BGD7J6MP2C8", "caption": "This is an excerpt from an advertisement that is all full of sound effects. There is a burning beam coming from the sky and blowing up the earth. Sounds of explosions can be heard as a car and multiple people jump to the sky and the people start grunting as they see their surroundings burning. The sounds from this track can be sampled to be used in beat-making and in soundboards.", "audio": "/zhanghaomin/datas/musiccap/music_data/BGD7J6MP2C8.wav"} +{"id": "BHDhHO7J-Oo", "caption": "The low quality recording features a hip hop beat and some skateboard sound effects in the background. The beat consists of female opera vocalists that sing over punchy snare and kick hits, simple hi hats, energetic crash cymbals, simple piano chords, smooth bass and sustained strings melody. It sounds epic and powerful, almost inspiring. The stereo image is unbalanced, since the snare hits are panned a bit to the right channel, and overall the left channel is a bit louder.", "audio": "/zhanghaomin/datas/musiccap/music_data/BHDhHO7J-Oo.wav"} +{"id": "BHu95Y_kVQA", "caption": "This song contains acoustic drums playing a steady groove with an uplifting bassline that repeats itself. An e-guitar is playing a single note melody while strings and an organ are elevating the energy with long higher register chords. Some backing vocals are singing along to the strings while the male voice is singing his melody. This song may be playing on a sunny day at the park having a picnic.", "audio": "/zhanghaomin/datas/musiccap/music_data/BHu95Y_kVQA.wav"} +{"id": "BI8YQ3ueD24", "caption": "Intentionally lo-fi bedroom recording of acoustic guitar strumming, knocking and fingerstyle playing. Finger snaps can also be heard. There is a slightly muffled room reverb over everything. Has an indie folk DIY aesthetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/BI8YQ3ueD24.wav"} +{"id": "BK2laUCyaH0", "caption": "This is an instrumental music piece composed of electronic/virtual elements. There is a repeated-theme of an eerie sound effect resembling a radar signal. Downtempo electronic drums and electronic percussion provide the rhythmic background. A synth keyboard plays the melody at a low-to-medium pitch. This piece could be used in movies/shows that take place in outer space.", "audio": "/zhanghaomin/datas/musiccap/music_data/BK2laUCyaH0.wav"} +{"id": "BKQYrrJVg6g", "caption": "The music is purely instrumental and it features an atmospheric vibe. In the beginning two or more flutes are playing melodies which are overlapping because of an added reverb effect. I believe a clarinet can be heard in one instance. Percussion drums are also present and a bell-like sound can be heard in the second half of the music excerpt. I believe the purpose of this music is to create floating vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/BKQYrrJVg6g.wav"} +{"id": "BL181hSAG60", "caption": "The low quality recording features a folk song that consists of loud passionate male vocal singing over acoustic guitar melody, shimmering shakers, percussive bongos, \"4 on the floor\" kick and mellow pad chords. It sounds loud, dull, messy and muffled, since the frequencies are clashing. It also sounds traditional and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/BL181hSAG60.wav"} +{"id": "BM9XDXA-CUE", "caption": "The low quality recording features a sound from a video game that consists of some footsteps sound effects and a wide mellow synth pad progression playing in the background. The synth pad volume ducks every time there is a synth bell melody, followed by synth bell sound effects. Sounds like a game with loud interactive gameplay sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/BM9XDXA-CUE.wav"} +{"id": "BMPmavj4keA", "caption": "This is a loud rock music piece played over two toy trains crashing. There is an even louder explosion sound effect whenever the toys crash. The distorted electric guitar plays a simple tune in the minor scale while the acoustic drums keep a basic rock beat as the rhythmic background.", "audio": "/zhanghaomin/datas/musiccap/music_data/BMPmavj4keA.wav"} +{"id": "BMgYWTTJv3s", "caption": "This is the live performance of a Turkish folk music piece with arabesque influences. The clarinet is playing the main melody in the lead at a medium-to-high pitch. A secondary melody is playing the qanun in the background. There are supportive elements in the melodic background such as the saz, the keyboard and the bass guitar. The acoustic drums are playing a mellow beat accompanied by rich percussion. There is a vibrant atmosphere in this piece. This could be playing in the background of a Turkish cuisine restaurant or a hookah place. It could also be used in the soundtrack of a Turkish soap opera.", "audio": "/zhanghaomin/datas/musiccap/music_data/BMgYWTTJv3s.wav"} +{"id": "BMxgDBoPv_0", "caption": "This music is a soft instrumental. The tempo is slow with a beautiful keyboard harmony. The music is soft, mellow, sentimental, nostalgic, melancholic and romantic. This song is classic pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/BMxgDBoPv_0.wav"} +{"id": "BN63M3_lPCQ", "caption": "The low quality recording features a folk song playing in the background while the flat male vocalist is speaking. The song contains shimmering shakers, acoustic rhythm guitar, wooden percussion and harmonica melody. The song sounds happy, joyful and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/BN63M3_lPCQ.wav"} +{"id": "BN6W6OQnVoE", "caption": "This music is an Electronic instrumental. The tempo is medium fast with a mellifluous flute harmony with slick drum arrangements , sustained droning,and synthesiser articulations. The music is futuristic, contemporary, experimental, psychedelic, meditative,minimalist and ambient. This music is Electronic Dance Music.", "audio": "/zhanghaomin/datas/musiccap/music_data/BN6W6OQnVoE.wav"} +{"id": "BQ_KrefFiTw", "caption": "This is an Iranian classical music piece. There is no singer in the piece. The melody is being played by the tar which is an Iranian lute. The rhythm is being played by the daf which is an Iranian percussion instrument. The atmosphere is profound. This piece could be playing in the background at an Iranian cuisine restaurant. It could also be used in the soundtrack of a mystery movie that takes place in the Middle East.", "audio": "/zhanghaomin/datas/musiccap/music_data/BQ_KrefFiTw.wav"} +{"id": "BR5MDhvcGM8", "caption": "This clip features a bass playing the main melody of the song. This is accompanied by percussion playing a minimalistic rock and roll beat. There are no other instruments in this song. There are animal grunting sounds played in this clip. The instruments are recorded in low quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/BR5MDhvcGM8.wav"} +{"id": "BRTHyoVgZT0", "caption": "The bass and drums build the foundation of this song with a simple grove with kick and snare. The strings support the snare with short bow strokes being percussive elements of the song. The male voice is singing in the lower to mid range, he sounds like telling a story. This song may be playing at home, cleaning the house and singing along.", "audio": "/zhanghaomin/datas/musiccap/music_data/BRTHyoVgZT0.wav"} +{"id": "BS2ZnUhmHj4", "caption": "This seasonal song features a flat male vocal, supported by wide harmonizing male vocals, singing over punchy kick, soft snare, groovy bass, shimmering shaker bells, muffled bells melody, staccato strings melody, brass section progression and simple piano chord progression. It sounds fun and happy, leaving the listener with the feelings of euphoria, nostalgia and excitement.", "audio": "/zhanghaomin/datas/musiccap/music_data/BS2ZnUhmHj4.wav"} +{"id": "BSLriWJ7hn8", "caption": "The low quality recording features bagpipes melodies playing over snare rolls. It sounds traditional and passionate, as the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/BSLriWJ7hn8.wav"} +{"id": "BSe5J0KlN3k", "caption": "A male singer sings this chanting vocals. The song is slow tempo with stringed instrument harmony that warbles and creates a psychedelic effect with no percussion. The song is trance and probably a prayer chant. The song is poor in audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/BSe5J0KlN3k.wav"} +{"id": "BT4env-Tw2o", "caption": "This song has a bassline that repeats itself playing along with a distorted guitar that supports the melody by playing the low notes along with slight variations and licks. The acoustic drums sound in the background but are played at full force. Fast paced with a lot of hits on different crashes and using a double bass kick. The male voice is screaming full force then a synthesizer lead sound is playing a simple melody that is panned to the right side of the speakers. This song may be playing at a live-concert jumping up and down enjoying the energetic energy of the surrounding and the music.", "audio": "/zhanghaomin/datas/musiccap/music_data/BT4env-Tw2o.wav"} +{"id": "BTMWpYzpu5g", "caption": "This is a traditional south asian song featuring the use of a pair of tablas for percussion, violins and a sitar. On the sitar, a rapid ascending melody is played in eighth notes. The song is played at a medium tempo and suitable for some energetic dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/BTMWpYzpu5g.wav"} +{"id": "BUDb8YieUgU", "caption": "The low quality recording features an electro song that consists of a punchy kick, shimmering hi hats, echoing stuttering vocal, punchy snare and synth down sweep. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/BUDb8YieUgU.wav"} +{"id": "BUzsQ6WohH4", "caption": "A male vocalist sings this melodic song. The tempo is medium with muffled vocals, violin harmony, rhythmic guitar , steady drumming and straight bass lines. The language and lyrics of the song are inaudible because of the amateur recording.This song is a Classic Rock and Roll.", "audio": "/zhanghaomin/datas/musiccap/music_data/BUzsQ6WohH4.wav"} +{"id": "BVonSUC3zIQ", "caption": "The Jewish religious instrument shofar is being played. It has a sound that resembles a bugle. In between each articulation, sounds of a dog barking can be heard coming from the street.", "audio": "/zhanghaomin/datas/musiccap/music_data/BVonSUC3zIQ.wav"} +{"id": "BVt8RgNrwbQ", "caption": "The low quality recording features an ambient song that consists of a wide echoing female vocal talking over resonating bowl tone and mellow percussion. It sounds passionate, percussive and hypnotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/BVt8RgNrwbQ.wav"} +{"id": "BWKQXn5xDwo", "caption": "An acoustic piano is playing a sad piece accompanied by a female singer. A simple digital drum with crash hits rounds up the composition. This song is an amateur recording but of decent quality. This song may be playing at a talent show.", "audio": "/zhanghaomin/datas/musiccap/music_data/BWKQXn5xDwo.wav"} +{"id": "BWSJjF32tQA", "caption": "The song is an instrumental. The song is medium tempo with a moog bass accompaniment, keyboard organ tone and a strong bass line. The song is emotional and poignant. The song is a new age pop soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/BWSJjF32tQA.wav"} +{"id": "BWVovghBe2c", "caption": "The low quality recording features a distorted electric guitar melody with an overdrive pedal on. It sounds cool and easygoing, even though the recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/BWVovghBe2c.wav"} +{"id": "BWvKAcOV_co", "caption": "This music is a lively Banjo instrumental. The tempo is fast with the musician dexterously playing a very spirited, vivacious and complex harmony. There is no other instrument accompaniment. This instrument is often heard in Country and Bluegrass.", "audio": "/zhanghaomin/datas/musiccap/music_data/BWvKAcOV_co.wav"} +{"id": "BXUS7pTYDzI", "caption": "A female vocalist sings this soft melody. The song is slow tempo with accordion harmony and acoustic guitar accompaniment and alto vocal harmony. The song is mellow, soft, pleasant, dulcet, emotional, romantic and nostalgic. This song is a Swiss/German folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/BXUS7pTYDzI.wav"} +{"id": "BXcEsM8ykhE", "caption": "This song contains someone playing a harp along with someone playing a melody on a transverse flute in the higher mid range. In the background you can hear people whispering.", "audio": "/zhanghaomin/datas/musiccap/music_data/BXcEsM8ykhE.wav"} +{"id": "BXo1Tr_oJds", "caption": "This music is a vigorous electric guitar instrumental. The tempo is fast with an electric guitar rapid melody lead and an electric guitar Accompaniment. The melody is contrasted and syncopated. The music is dark, intense, extreme, dire and compelling Heavy Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/BXo1Tr_oJds.wav"} +{"id": "BXv69uAoHk4", "caption": "The Soul song features a passionate male vocal, alongside wide, harmonizing background female vocals, singing over shimmering chime bells, shimmering hi hats, mellow piano chords, wide strings chords, electric guitar melody and simple bass guitar. It sounds passionate and emotional - like something you would sing to your partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/BXv69uAoHk4.wav"} +{"id": "BYi0fAZtBls", "caption": "This music is an Electronica instrumental. The tempo is fast with synthesiser articulations, hard hitting digital drum beats and electronic arrangements with a repetitive female vocal riff. The music is punchy, vibrant, thumping, pulsating, youthful, enthusiastic, energetic ,psychedelic, hypnotic, trance like and buoyant. This music is EDM/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/BYi0fAZtBls.wav"} +{"id": "BYnYTgeM6Go", "caption": "This is a live recording of a performance on the bagpipes. There are two bagpipes, one playing a low pitched buzzing hum and the other playing an intricate celtic-style melody. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/BYnYTgeM6Go.wav"} +{"id": "BYwS1dJRTi0", "caption": "The Rock song features wide harmonizing male vocals singing over wide electric guitar chord progression, punchy snare and kick hits, shimmering cymbals and groovy bass. At the very beginning of the loop there is a flat male vocal singing over echoing electric guitar melody and less energetic drums, after which the previously mentioned chorus starts. It sounds energetic and uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/BYwS1dJRTi0.wav"} +{"id": "BZyf8LPltYs", "caption": "This is a drum & bass music piece. There is a very fast-tempo, high energy electronic drum beat in the rhythmic background. There is a strong and fuzzy bass sound playing a loud bass line while a synth can be heard adding texture. The piece is upbeat and has an aggressive atmosphere. This music is perfect for nightclubs and DJ sets. It could also work well in the soundtrack of a car racing video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/BZyf8LPltYs.wav"} +{"id": "B_kAtTBUDIA", "caption": "The low quality recording features a regional Mexican song that contains wooden percussive elements, groovy bass and staccato brass melody over which flat male vocalists sing. It sounds vintage, as the recording is very noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/B_kAtTBUDIA.wav"} +{"id": "B_ohqOgK6T8", "caption": "This music is instrumental. The tempo is medium with synthesiser articulation. The music is minimalist with the sound of wind, beep, and vinyl record scratch sound followed by silence.", "audio": "/zhanghaomin/datas/musiccap/music_data/B_ohqOgK6T8.wav"} +{"id": "B_tbkQYT9N0", "caption": "The song is an instrumental. The song is medium fast tempo with a techno drumming rhythm, keyboard harmony and synth string pad tones. The song is inorganic and exciting. The audio quality is poor and vintage in quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/B_tbkQYT9N0.wav"} +{"id": "BaMBwXQwK3g", "caption": "This is a live performance of a pop music piece. There is a teenage female vocalist singing melodically in the Spanish language. An acoustic guitar plays the main tune while there is a slow tempo acoustic drum beat in the rhythmic background. The spectators are joining the song at a volume that is sometimes higher than the song itself and it creates an irritating aura.", "audio": "/zhanghaomin/datas/musiccap/music_data/BaMBwXQwK3g.wav"} +{"id": "Bap5P9buB0Y", "caption": "The low quality recording features an echoing flat male vocal, alongside harmonizing male vocal, singing over sustained strings melody, shimmering open hats, wooden percussions, punchy kick and groovy bass. It sounds traditional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/Bap5P9buB0Y.wav"} +{"id": "BcVapmCbULQ", "caption": "This is a drum beat in the rock and roll style, with a drum roll in between that's intricate. The snare, toms, hi-hats and crash cymbal are used.", "audio": "/zhanghaomin/datas/musiccap/music_data/BcVapmCbULQ.wav"} +{"id": "Bd0PbyrG6H4", "caption": "The epic music excerpt starts off full force with an orchestral ensemble playing loud blocks of sound. The taiko drums play with the same rhythm the orchestra does. After a few seconds the volume is dialed down and one can hear a melody being created from electronic sounds and possibly a bass guitar. In the background a metallic percussive instrument is being played with bare hands.", "audio": "/zhanghaomin/datas/musiccap/music_data/Bd0PbyrG6H4.wav"} +{"id": "Bd9TjPP31U0", "caption": "This is an R&B/soul music piece. There is a female vocalist singing melodically while another female vocalist is singing the backing melody. The keyboard is playing the main tune. There is a bass guitar playing in the background. The rhythm is provided by a ballad-type slow tempo acoustic drum beat. The atmosphere is sentimental. This piece could be used in the soundtrack of a drama movie, especially during the scenes of a reunion or a homecoming after a long period of separation.", "audio": "/zhanghaomin/datas/musiccap/music_data/Bd9TjPP31U0.wav"} +{"id": "BdKiPR3kdjo", "caption": "This Spanish pop song features a male voice singing the main melody. This is accompanied by percussion playing a Latin beat. A shaker or maracas plays a continuous rhythm. An accordion plays chords in the background. The bass plays the root note of the chords. This song can be played at a party. The mood of this song is romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/BdKiPR3kdjo.wav"} +{"id": "BdhaR2QUGqY", "caption": "This song contains a cymbal holding the rhythm while different piano and keyboards are playing melodies. A xylophone is playing a melody in a higher pitch on top of that. A female voice choir sample comes in every year and then being part of the rhythmic composition. This song may be playing in a adventure video-game with beautiful landscapes.", "audio": "/zhanghaomin/datas/musiccap/music_data/BdhaR2QUGqY.wav"} +{"id": "BeFjxrUwAC4", "caption": "The low quality recording features a trap song that consists flat male vocal, alongside widely spread male ad libs, rapping over arpeggiated, echoing synth melody, sustained and distorted synth melody, boomy 808 bass, punchy snare, soft kick hits, bouncy hi hats and shimmering open hats. There is a short snare roll at the end of the first part of the loop. It sounds quiet, but still energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/BeFjxrUwAC4.wav"} +{"id": "BeFzozm_H5M", "caption": "This song features synth pads playing one chord in the background. A chord melody is played on the piano. The melody played is sets of two chords being played in a pattern of one high chord followed by one lower pitch chord. This is an instrumental song. There are no voices in this song. There are no other instruments in this song. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/BeFzozm_H5M.wav"} +{"id": "BfMKdrK9D8M", "caption": "The low quality recording features a cover of a song and it consists of passionate male vocals that together with the actual song's vocal, sounds harmonizing. There are simple acoustic guitar chords too. The recording is very noisy as it was probably recorded with a phone, but regardless it sounds emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/BfMKdrK9D8M.wav"} +{"id": "BfUoopDpmmY", "caption": "The low quality recording features a children's song that features a flat male vocal, alongside wide harmonizing children vocals, singing over acoustic rhythm guitar, steel guitar melody, happy bells melody, soft kick hits, mellow snare hits, shimmering hi hats and groovy bass. It sounds joyful, happy and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/BfUoopDpmmY.wav"} +{"id": "BgTB_xt11bA", "caption": "This song contains digital drums playing along with a raw synth bass sound playing a melody while a male voice is rapping in a higher key. Then a female voice takes over singing a melody along to the bass. This song may be playing loud when at home alone.", "audio": "/zhanghaomin/datas/musiccap/music_data/BgTB_xt11bA.wav"} +{"id": "Bgsy5UpXx8I", "caption": "The low quality recording features a rock song that consists of flat male vocal singing over punchy snare, soft kick hits, repetitive organ keys chords, shimmering hi hats and groovy bass. It sounds messy, loud, muddy and chaotic, since the frequencies are clashing with each other due to a bad mix.", "audio": "/zhanghaomin/datas/musiccap/music_data/Bgsy5UpXx8I.wav"} +{"id": "BhJa0kTUdGY", "caption": "Two acoustic guitars being strummed can be heard while a male voice is singing in the mid range. Someone is strumming chords in a higher key alone. In the background you can hear acoustic drums and the crowd is cheering. This song may be playing live in a pub.", "audio": "/zhanghaomin/datas/musiccap/music_data/BhJa0kTUdGY.wav"} +{"id": "BhYaXU1MVcQ", "caption": "The low quality recording features a sustained horn tone. There is a subtle inhale sound and it sounds reverberant as if it was recorded in a room. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/BhYaXU1MVcQ.wav"} +{"id": "BiPwCMlghhQ", "caption": "This reggae song features a male voice singing the main melody. Other male voices sing backing voices repeating the same melody in between lines. This is accompanied by percussion playing a simple melody using reggae rhythm. The bass plays a groovy bassline using runs within the scale. A guitar plays chords by muting technique producing a reggae rhythm. A keyboard plays chords in the background. This song can be played in a documentary about alleviating poverty.", "audio": "/zhanghaomin/datas/musiccap/music_data/BiPwCMlghhQ.wav"} +{"id": "BiQik0xsWxk", "caption": "The Soul song features a passionate male vocal singing over shimmering hi hats and shakers, groovy bass, widely spread wooden percussions, punchy kick and snare hits, wide sustained strings melody and mellow piano melody. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/BiQik0xsWxk.wav"} +{"id": "BiqPn3d_dKM", "caption": "This audio contains someone playing a very low sounding bass flute like instrument. Playing a rhythmic melody with a percussive sound created with the mouth. This song may be playing during a live performance from a busker.", "audio": "/zhanghaomin/datas/musiccap/music_data/BiqPn3d_dKM.wav"} +{"id": "BjAL68IMlp0", "caption": "This pop rock song features a male voice. This is accompanied by percussion playing a simple beat in common time. A lead guitar with heavy reverb plays a fill in between lines. An acoustic guitar strums chords in the background. A bass plays the root notes of the chords. The mood of this song is romantic. This song is played at a slow tempo. This song can be played in a retro romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/BjAL68IMlp0.wav"} +{"id": "BjIksWR4oKw", "caption": "This is a jazz music piece used as an accompaniment for a tap dancing contest. It is an old recording. There is a brass section and a piano that are playing the melody while the upright bass is playing a simple bass line. The rhythmic background consists of acoustic drums and the tapping of the shoes to the ground. There is a lively atmosphere. This piece is used in the background of comedic social media content or advertisement jingles.", "audio": "/zhanghaomin/datas/musiccap/music_data/BjIksWR4oKw.wav"} +{"id": "BjqhHeJD28U", "caption": "The song is an instrumental. The song is medium tempo with an amplified guitar playing lead with different tone settings. The song is melancholic and more of a demo play. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/BjqhHeJD28U.wav"} +{"id": "BkOfrw3c3EE", "caption": "This is a jazz piece played in the background of a video game. A trumpet plays the main melody while a xylophone and a bass guitar is supporting the tune in the background. A playful jazz drum beat carries the rhythmic background. Occasional electric guitar fills in the form a strum can be heard. There are a lot of sound effects related to the game such as squeaking, chewing and explosions.", "audio": "/zhanghaomin/datas/musiccap/music_data/BkOfrw3c3EE.wav"} +{"id": "BkSCfcTBMRY", "caption": "This is a classical music piece performed by a trio of the violin, the cello and the piano. The melody being played is a gentle one and there is a feeling of resolution in this section of the piece. This piece could be used in the soundtrack of a drama TV series during the closing scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/BkSCfcTBMRY.wav"} +{"id": "BkjpjAohg-0", "caption": "The electronic music features a section that repeats roughly every two seconds. It consists of a beat that's made of a kick drum and claps. A buzzing synth sets the pulsation of the music by playing once every two beats. The whole music sounds like a loop being played over and over. Towards the end of the excerpt a crescendo-like buzzing sound can be heard, increasing the tension.", "audio": "/zhanghaomin/datas/musiccap/music_data/BkjpjAohg-0.wav"} +{"id": "BkoCi-IZccI", "caption": "A female vocalist sings this energetic song. The tempo is fast with enthusiastic drumming, funky bass line, keyboard harmony and synthesiser arrangements. The song is youthful, vibrant, vivacious, hyper, spirited, passionate, bright and has a dance groove. This song is an Electro Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/BkoCi-IZccI.wav"} +{"id": "Bl-lCgr5hGY", "caption": "A female voice is singing loud and in a high key. Her voice is full of reverb and a little delay. It is so loud that the speakers are speaking a lot. There are percussive instruments like chimes and tabla like sounds playing a rhythm while a flute is playing a melody in the background. This is an amateur recording with poor recording quality. This song may be playing at a local dance event.", "audio": "/zhanghaomin/datas/musiccap/music_data/Bl-lCgr5hGY.wav"} +{"id": "BlhUt8AJJO8", "caption": "This is a deep house piece. There is a repeating female vocal sample playing while the keyboard and bells are carrying the melody playing the same two chords repeatedly. There is also a nice sound effect. The electronic drum beat is in a crescendo movement creating a hyped-up atmosphere. A male vocal uttering a few words can be heard later on. The piece has a danceable but chill aura to it. It could be used at house parties, dance clubs and tourism advertisements.", "audio": "/zhanghaomin/datas/musiccap/music_data/BlhUt8AJJO8.wav"} +{"id": "BlsbeyimUDE", "caption": "The low quality recording features a jazz song playing in the background while people are shoe tapping to it. The jazz song at least consists of passionate male vocal, groovy bass and brass section, since those elements are audible. It is reverberant and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/BlsbeyimUDE.wav"} +{"id": "BnkDQXlrIX4", "caption": "This song seems to be experimental. An e-bass is playing a light funky groove along with a clapping sound while other percussion's are adding a rhythm rounding up the rhythm section. A oriental sounding string is playing one single note rhythmically while another oriental and plucked instrument is playing a melody in the higher register. The whole recording sounds a little old but is of good quality. This song may be playing in the kitchen while cooking.", "audio": "/zhanghaomin/datas/musiccap/music_data/BnkDQXlrIX4.wav"} +{"id": "BojCkFK3pNg", "caption": "This music is instrumental. The tempo is fast with a lively and happy harpsichord melody. The music is upbeat, engaging, happy, cheerful and peppy. This music is a Classical piano/harpsichord Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/BojCkFK3pNg.wav"} +{"id": "BpLUOKHl51E", "caption": "The low quality recording features a reverberant intimate female vocal singing over sustained strings and mellow piano. It sounds loud and emotional and the recording is extremely noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/BpLUOKHl51E.wav"} +{"id": "BqIZipifARo", "caption": "The song is an instrumental. The tempo is medium with an electric guitar playing a dreamy solo with a keyboard accompaniment , string section harmony and rhythmic percussion rhythm. The song is passionate and emotional. The song is a rock guitar instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/BqIZipifARo.wav"} +{"id": "BquHBzP5Ep0", "caption": "The song feels cinematic and momentous. It's an orchestral piece with string instruments, and then with an electric guitar lick. The emotion is gripping and a little sombre.", "audio": "/zhanghaomin/datas/musiccap/music_data/BquHBzP5Ep0.wav"} +{"id": "BrCW3BA8TIQ", "caption": "This is a Christian gospel music piece. There is a male vocalist singing melodically while the piano is gently playing a simple tune. The atmosphere is religious. This piece could be playing in the background at Christian religious events or Christian social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/BrCW3BA8TIQ.wav"} +{"id": "Brc_nOquNbY", "caption": "A male vocalist sings this spirited rap. The tempo is fast with an animated piano accompaniment, groovy bass lines, intense drumming, cymbal rides and vocal backup. The song is youthful, vibrant, vivacious, animated, compelling ,enthusiastic and passionate . This song is contemporary Hip-Hop/Rap.", "audio": "/zhanghaomin/datas/musiccap/music_data/Brc_nOquNbY.wav"} +{"id": "BsLFQV8HVZE", "caption": "The song is an instrumental. The song is medium tempo with a walking bass line, steady drumming rhythm with cymbal crashes, guitar strumming rhythm and an accordion playing melody. The song is background music for a toy hobbyist video. The song is cheerful and reminiscent of a childhood adventure.", "audio": "/zhanghaomin/datas/musiccap/music_data/BsLFQV8HVZE.wav"} +{"id": "BsVsoZ4ojp0", "caption": "This song is of low quality. This features a male voice singing the main melody in a foreign language. Female voices sing the vocal harmony in this song. This is accompanied by simple percussion. Trumpet play fills in between lines. The mood of this song is happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/BsVsoZ4ojp0.wav"} +{"id": "BscoQHJrNm8", "caption": "The low quality recording features a metal song that consists of a screaming female vocal singing over punchy kick and snare hits, energetic cymbals, groovy bass guitar, wide distorted electric guitars, strings melody and repetitive piano melody. At the very end of the loop, there is a short distorted static sound. It sounds energetic, aggressive and manic.", "audio": "/zhanghaomin/datas/musiccap/music_data/BscoQHJrNm8.wav"} +{"id": "BsnjK6DypAg", "caption": "Someone is playing a didgeridoo while using his voice to create overtones and using circular breathing for a continuous tone. This may be playing at home, getting into meditation. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/BsnjK6DypAg.wav"} +{"id": "BtdzVnXZ0i4", "caption": "This is a theme from a movie soundtrack. It is an instrumental piece. There is a synth playing a mellow tune at a low-to-medium range. The tune has a melancholic feel to it. It could be used in the soundtrack of a drama movie during introspective scenes where a character is reminiscing over troublesome memories.", "audio": "/zhanghaomin/datas/musiccap/music_data/BtdzVnXZ0i4.wav"} +{"id": "BurGML_ZqSA", "caption": "This sound is of a doorbell. It is playing a high pitched melody with a chiming sound. There are no other instruments in this song. There are no voices in this song. This sound is similar to what you would find in a music box.", "audio": "/zhanghaomin/datas/musiccap/music_data/BurGML_ZqSA.wav"} +{"id": "Bx1HZVX4UxM", "caption": "The low quality recording features a metal song that consists of screaming male vocals over smooth bass guitar, shimmering cymbals and electric guitar feedback that creates a perfect transition for the section that has a muffled electric guitar riff located in the left channel of the stereo image. It sounds aggressive and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/Bx1HZVX4UxM.wav"} +{"id": "Bx3nzrmGXhw", "caption": "A female soprano singer sings this high pitched melody. The song is medium tempo with just the singer singing this hauntingly beautiful choral melody with no accompaniment. The song is emotional and devotional. The audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/Bx3nzrmGXhw.wav"} +{"id": "Bx726MYz6Uo", "caption": "A male singer sings this spirited Latin vocal. The song is fast tempo with slick guitar strumming and percussive guitar accompaniment. The song is romantic and steeped in rich Latin classical music traditions. The song is about a Latin street musician playing folk music. The recording is of average quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Bx726MYz6Uo.wav"} +{"id": "BxQSEvHdyjQ", "caption": "A rock drum beat that uses a boomy kick, trashy percussion, a tambourine to make a 'found sound' vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/BxQSEvHdyjQ.wav"} +{"id": "BxbB2_N5Xtk", "caption": "This amateur recording features a female voice saying the alphabet in a non-musical tone. There are sounds of hard plastic objects striking each other. After the striking sounds, an organ melody is played. The organ plays a sequence of four notes.", "audio": "/zhanghaomin/datas/musiccap/music_data/BxbB2_N5Xtk.wav"} +{"id": "ByF0pp-dVEo", "caption": "This audio contains someone beatboxing. Then a male voice starts singing loud and at a higher pitch. The crowd is cheering in the background. This song may be playing live during a beatbox performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/ByF0pp-dVEo.wav"} +{"id": "ByOqw8M2U-Q", "caption": "A female vocalist sings this melodious harmony. The tempo is slow with a dulcet Harp accompaniment . The song is soft, mellow, meditative, angelic, celestial,mystical, dreamy and mellifluous. This song is a Catholic prayer or salutation.", "audio": "/zhanghaomin/datas/musiccap/music_data/ByOqw8M2U-Q.wav"} +{"id": "Byk9p21g51g", "caption": "The low quality recording features an urban latin remix that consists of passionate female vocal singing over groovy piano chords, wooden percussive elements, \"4 on the floor\" kick pattern, syncopated claps, shimmering shakers, smooth bass and exciting male vocals. It sounds energetic, fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Byk9p21g51g.wav"} +{"id": "BzM0qok5Cns", "caption": "The low quality recording features a commercial song that consists of an acoustic rhythm guitar, claps, shimmering shakers, shimmering bells melody, synth lead melody, simple bass and generic female voice tag. It sounds happy, fun and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/BzM0qok5Cns.wav"} +{"id": "C-1i2GlbiIY", "caption": "A male vocalist sings this emotional R&B song. The tempo is slow with a melancholic piano accompaniment with drum machine arrangement. The song is an emotional , soulful, pensive, sentimental,melancholic, romantic love song. This song is a Soul/R&B.", "audio": "/zhanghaomin/datas/musiccap/music_data/C-1i2GlbiIY.wav"} +{"id": "C-7ubPOCeJk", "caption": "The Pop song features a passionate female vocal singing over groovy bass, wide electric guitar melodies and shimmering shakers, as the overall audio is slowly fading out. It sounds addictive, passionate and intimate.", "audio": "/zhanghaomin/datas/musiccap/music_data/C-7ubPOCeJk.wav"} +{"id": "C-NYmja61zE", "caption": "Someone is playing an e-guitar with a chorus effect playing a melody. This song may be playing at home practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/C-NYmja61zE.wav"} +{"id": "C0AQyOVGvFM", "caption": "A male vocalist sings this mellow song.he tempo is medium with jazz style piano accompaniment, synthesiser articulation, slick drumming, funky bass line, cajun beat and an interactive vocal harmony. The music is mellow, soothing, ambient, soulful, passionate, emotional and persuasive. This song is a contemporary R&B/Soul.", "audio": "/zhanghaomin/datas/musiccap/music_data/C0AQyOVGvFM.wav"} +{"id": "C0eCERYt4bA", "caption": "This is a live performance by an African music group in a gospel style. The drum pattern is intricate and there are other percussive elements like an occasional bongo and a wooden percussion instrument. The melodic elements are the vintage sounding electric piano as well as the vibrant and fun brass melody played on the trumpets.", "audio": "/zhanghaomin/datas/musiccap/music_data/C0eCERYt4bA.wav"} +{"id": "C0sSgrr5xrQ", "caption": "A male singer sings this cool retro melody with duck quacking sounds. The song is medium tempo with a steady drumming rhythm with various funny percussion hits, accordion accompaniment and a groovy bass line. The song is inspiring and nostalgic. The song has an average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/C0sSgrr5xrQ.wav"} +{"id": "C1M5xqDQW58", "caption": "This is a rock music piece. There is a medium-to-high pitched electric guitar solo at the forefront. In the melodic background, a keyboard and a bass guitar repeating the same pattern can be heard. The acoustic drums are playing a loud and slightly fast-paced rock drum beat. There is a rebellious atmosphere to this piece. It can be used in the soundtrack of a teenage drama or a crime shootout video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/C1M5xqDQW58.wav"} +{"id": "C25xvcl4YAU", "caption": "This is the recording of a box opening with a dubstep piece playing in the background. A knife cutting through the box can be heard. The track in the background has a loud synth bass and an aggressive electronic drum beat. It is a fast-paced piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/C25xvcl4YAU.wav"} +{"id": "C33WdI64FiY", "caption": "This is an educational music piece. The male vocalist is singing in an instructive manner asking questions directed at kids. There is a quirky piano sound joined by an upright bass. The rhythmic background consists of an electronic drum beat joined by electronic percussive sounds. There is an eccentric atmosphere to this piece. It could be used in an educational atmosphere such as an introductory physics class.", "audio": "/zhanghaomin/datas/musiccap/music_data/C33WdI64FiY.wav"} +{"id": "C3Jhu77uffQ", "caption": "This is a video game music piece. It starts with gear sounds resembling a music box being set up before it starts playing. Afterwards, a high-pitch melody starts playing from a music box that is very loud. The atmosphere is haunting. This piece could be used in the soundtrack of a horror movie or a horror video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/C3Jhu77uffQ.wav"} +{"id": "C3o8pEsAu5U", "caption": "An acoustic drum is strumming chords while a percussion instrument is playing a bass sound along with an e-bass. A male choir is singing in the background while the female voice is singing the first melody. In the background you can hear voices. This song may be playing in a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/C3o8pEsAu5U.wav"} +{"id": "C3s-DmHtDUg", "caption": "A classical sounding music piece which sounds like a music box being played through a tiny, distorted speaker of an ice cream truck. Low fidelity.", "audio": "/zhanghaomin/datas/musiccap/music_data/C3s-DmHtDUg.wav"} +{"id": "C4-mZ1jGQ-E", "caption": "The Reggae song features a flat male vocal rapping over shimmering cymbals, heavy bass, bouncy snare, wide sustained synth lead and \"4 on the floor\" kick pattern. Even though the song is uptempo, it sounds easygoing and like something you would listen to in a car, or while chilling.", "audio": "/zhanghaomin/datas/musiccap/music_data/C4-mZ1jGQ-E.wav"} +{"id": "C4MeKaeaPcU", "caption": "This is a recording of a skilled organ player playing some intricate motifs on the organ. The music is soulful and also has a gospel feel to it. It's a live recording with low-quality audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/C4MeKaeaPcU.wav"} +{"id": "C5MhO2HM2Wg", "caption": "The drums are just playing the hihat and the kick on the second beat which is typical for reggae. The keys are playing one chord on the offbeat. A guitar is playing some repeating chords along while the bass is playing a simple rhythmic pattern to support the drums. The female voice is singing with some reverb on her voice. This song may be playing on a sunny day at home with open windows mixed with the noises of a lovely small town.", "audio": "/zhanghaomin/datas/musiccap/music_data/C5MhO2HM2Wg.wav"} +{"id": "C5Zs-Lb2rIM", "caption": "A male vocalist sings this passionate Hip-Hop. The tempo is medium fast with synthesiser articulation, digital drumming and turn table effects with vocal backup. The song is enthusiastic, passionate, persuasive, emphatic, emotional , youthful and groovy. This song is a freestyle Hip-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/C5Zs-Lb2rIM.wav"} +{"id": "C6-JxDWYJ-A", "caption": "The low quality recording features a flat male vocal singing over groovy bass, brass melody, punchy snare and shimmering hi hats. The recording is messy, noisy, distorted and in mono, vintage as it is probably old.", "audio": "/zhanghaomin/datas/musiccap/music_data/C6-JxDWYJ-A.wav"} +{"id": "C6m_OWe-JE4", "caption": "The drums hold a solid R&B groove with little fill-ins here and there that are panned to the left and right side of the speakers. Along with the drums a e-bass is playing a round and full-sounding bassline in the background. One e-guitar is strumming chords panned to the right side of the speakers. While the other guitar is playing a lead melody ending the phrases of the keys playing chords in the mid range. The male singer sounds soulful and his voice is deep. This song may be playing at home on a romantic dinner with your partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/C6m_OWe-JE4.wav"} +{"id": "C6roSYqchkk", "caption": "A male singer sings this pop melody with back up singers in choral harmony. The song is medium tempo with a superimposed Latin Cumbia rhythm, which creates a discombobulated rhythm structure. The song audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/C6roSYqchkk.wav"} +{"id": "C6ws4MxOH2Y", "caption": "The recording features a tutorial for a cover of a pop song and it consists of a saxophone melody alongside some buttons tapping noises. It sounds warm and mellow.", "audio": "/zhanghaomin/datas/musiccap/music_data/C6ws4MxOH2Y.wav"} +{"id": "C7OIuhWSbjU", "caption": "This is a heavy metal piece. There is a female singer upfront singing in medium pitch in the Japanese language. The distorted electric guitar is playing the melody while a relatively quieter bass guitar is accompanying it. The acoustic drums are playing an accentuated heavy metal beat full of rapid fills. A faint rhythmic pad can also be heard in the chorus. The general atmosphere of the song is energetic and rebellious. This piece could be used in an action-filled anime soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/C7OIuhWSbjU.wav"} +{"id": "C7WAx3n57Hk", "caption": "This song contains acoustic drums holding a steady groove with a complex fill in at the end of the phrase. An e-bass and e-guitar are playing the same notes, just the e-guitar is strumming a chord. The male voice is singing loud and in a higher register. This song may be playing in a garage workshop.", "audio": "/zhanghaomin/datas/musiccap/music_data/C7WAx3n57Hk.wav"} +{"id": "C8Euv69GR3U", "caption": "The Rock song features a wide, mellow, high pitched synth pad swelling into the drop that consists of punchy drums, smooth electric and bass guitars. Right before the \"drop\", there is a short toms roll. It sounds calming and relaxing, at least until the bass drops.", "audio": "/zhanghaomin/datas/musiccap/music_data/C8Euv69GR3U.wav"} +{"id": "C8VECv8kicU", "caption": "This is a flamenco music piece being performed live. There is a female vocalist singing passionately in the Spanish language. The acoustic guitar is playing the melodic background while the rhythmic background is played by the cajon percussion and a group of musicians clapping in a syncopated manner. The atmosphere is vibrant and agitated. This piece could be used in the soundtrack of a soap opera or a romance/drama movie. It could also be playing in the background at a Spanish/Latin American cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/C8VECv8kicU.wav"} +{"id": "C9e2k030QcY", "caption": "The song is an instrumental. The tempo is medium with a Harpsichord being played by an elder gentleman in classic baroque style. The music is engaging and exciting. The song audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/C9e2k030QcY.wav"} +{"id": "CAL5CgkKkR4", "caption": "This is a bluegrass gospel piece. The multitrack male vocalist is singing religious lyrics loudly. For the melodic background, a banjo and a violin is playing the tune while a bass guitar is providing the rhythmic background. The atmosphere is hopeful. This song could be used in Christian religious social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/CAL5CgkKkR4.wav"} +{"id": "CAbNGe1PWoY", "caption": "This is a heavy metal music piece. There is no singer in this piece. There is a complex electric guitar solo being played. The melodic background consists of the distorted electric guitar and the bass guitar. The rhythm is being played by the acoustic drums. The atmosphere of this piece is loud and hard-hitting. This piece could be used in the soundtrack of an action-filled cartoon/animation movie, especially during the combat scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/CAbNGe1PWoY.wav"} +{"id": "CBUAy9Zl6ZE", "caption": "This is a melancholic Moroccan music piece. The male vocalist is singing in an agitated, crying-like manner. The only accompaniment being the violin creates a dense atmosphere loaded with emotion. This piece could be used in the soundtrack of a movie or a TV show involving a tragedy which is taking place in North Africa.", "audio": "/zhanghaomin/datas/musiccap/music_data/CBUAy9Zl6ZE.wav"} +{"id": "CCFYOw8keiI", "caption": "This is the theme playing in the background of a mythological TV series episode. It is an instrumental piece. There is a brass section playing a loud and dramatic melody. The rhythmic accompaniment is composed of the drums and some sort of big cymbal that is most probably a gong. The atmosphere is dramatic and full of suspense. There is an implied moment of revelation in the scene. The piece could be used in the soundtrack of a mystery movie during a scene where the plot begins to unfold and the secrets are revealed.", "audio": "/zhanghaomin/datas/musiccap/music_data/CCFYOw8keiI.wav"} +{"id": "CD3OyaDW348", "caption": "A jazz organ trio playing a swing blues song with a male singer accompanied by electric guitar, Hammond organ, a steady ride pattern on the cymbals. The whole band hits on beat one with the drum breaks, as is common in this style of music.", "audio": "/zhanghaomin/datas/musiccap/music_data/CD3OyaDW348.wav"} +{"id": "CEJXvm2vH_4", "caption": "This is instrumental Chinese music. The main melody is played by dizi, a Chinese flute. Qin (a Chinese xylophone) is played with syncopation while at the same time carrying the bass notes. There is also a simple acoustic drum beat in the rhythmic background. The piece has a positive, optimistic atmosphere. It could be used in the movies/shows that take place in China. It could also be used in the background of a Chinese cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/CEJXvm2vH_4.wav"} +{"id": "CFT9P94NMDw", "caption": "Someone is playing an e-guitar melody with a big chorus effect and a lot of reverb and a little delay. This song may be playing for an effect pedal advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/CFT9P94NMDw.wav"} +{"id": "CGYflJRiLt0", "caption": "The low quality recording features an emotional electric guitar chord progression being played with a huge reverb effect on it. It sounds like it is played in a huge space.", "audio": "/zhanghaomin/datas/musiccap/music_data/CGYflJRiLt0.wav"} +{"id": "CH-zch2pUic", "caption": "This song contains samples of water sounds over and under water. String pads are playing a soft and calming melody in the higher register along with single pluck sounds playing a little melody on top. This song may be playing for an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/CH-zch2pUic.wav"} +{"id": "CHo8wKj9J1w", "caption": "The song is an instrumental. The song is medium tempo with a percussionist practising Latin bass drums with a drum stick to a music track with male vocals, trumpet harmony and other percussion. The audio quality is poor and boomy.", "audio": "/zhanghaomin/datas/musiccap/music_data/CHo8wKj9J1w.wav"} +{"id": "CHufyCHSF1U", "caption": "The low quality recording features an uptempo country song sung by passionate male vocalists, followed by acoustic rhythm guitar and electric guitar melody. It sounds really bad and imbalanced, as the left channel is louder than the right.", "audio": "/zhanghaomin/datas/musiccap/music_data/CHufyCHSF1U.wav"} +{"id": "CIoEXRnAr-Y", "caption": "The Rock song features a flat male vocal singing over a wide electric guitar melody, shimmering hi hats, energetic crash cymbals, punchy snare and kick hits, groovy bass guitar and piano chord progression. At the end of the loop, there is a short tom roll, representing a transition to the next section. It sounds energetic - like something you would hear on a radio.", "audio": "/zhanghaomin/datas/musiccap/music_data/CIoEXRnAr-Y.wav"} +{"id": "CJjyrDGmxIY", "caption": "This song contains acoustic drums playing a kick on every beat and playing the hi hat with 16th notes. An e-bass is playing a simple line along with an organ sound in the background. Percussions are adding rhythms that want to make you dance. An e-guitar is playing another melody while the male and female voices are singing together creating harmonies. This song may be playing at a beach bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/CJjyrDGmxIY.wav"} +{"id": "CKEPPcaCjbw", "caption": "solo electric guitar music with a clean tone. The guitar is slightly out of tune. The music mostly consists of single notes as opposed to chords. The guitar plays blues licks.", "audio": "/zhanghaomin/datas/musiccap/music_data/CKEPPcaCjbw.wav"} +{"id": "CKO35LsM0XI", "caption": "The low quality recording features an indie rock song that consists of passionate female vocal singing over energetic drums, electric guitar solo melody and groovy bass, over which there is a flat, nasal and muffled male vocal narrating. The song sounds energetic and uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/CKO35LsM0XI.wav"} +{"id": "CKkbZCb9Y18", "caption": "A rock backing track is being played containing a e-bass, acoustic drums and a clean e-guitar playing a melody on top. In the foreground you can hear sounds that do not belong to the song. Chainsaws slashing things, monster sounds and female voices screaming like being in a fight. This is an amateur recording. This song may be playing in a violent videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/CKkbZCb9Y18.wav"} +{"id": "CLx4iYWSB1c", "caption": "The low quality recording features an electro song that consists of a \"4 on the floor\" kick pattern, groovy, buzzy synth bass and a reverberant down sweep at the very beginning of the loop. It sounds energetic and very digital - like something you would hear in old video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/CLx4iYWSB1c.wav"} +{"id": "CM2rKZmcR0I", "caption": "This slow pop song features a male voice singing the main melody. Another male voice sings backing voices in harmony with the main melody. A synth plays the same melody as the main voice using staccato notes. This is accompanied by percussion playing a trap beat. The bass plays the root notes of the chords and flourishes during chord changes. The bass notes are played without pausing in between notes. Instead, the notes are slid into each other. The mood of this song is romantic. This song can be played in a heartbreak scene in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/CM2rKZmcR0I.wav"} +{"id": "CM7jMnBXw2Y", "caption": "This rock song features a guitar solo being played on a distortion guitar. This starts off with a string bend followed by a descending lick. A harmonic string scratch technique is played to produce a screeching sound. This is followed by a fast ascending scale run. This is accompanied by percussion playing a simple rock beat. The bass plays the root notes of the chords. There are no voices in this song. This is an instrumental. Due to the low audio quality, the instruments are not clearly heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/CM7jMnBXw2Y.wav"} +{"id": "CMfAu72qma0", "caption": "The low quality recording features a live performance of a rock song that's sung by flat male vocals and played by electric guitars, groovy bass guitar and energetic drums that consists of punchy kick and snare hits and some short snare rolls, energetic cymbals and shimmering hi-hats. At one point in the loop, it seems that the drummer fell out of rhythm, so it kind of sounds sloppy. It also sounds very noisy, messy, muddy, but still energetic too.", "audio": "/zhanghaomin/datas/musiccap/music_data/CMfAu72qma0.wav"} +{"id": "CN2QSmhP-HI", "caption": "This salsa song features a female voice singing the main melody. This is accompanied by the congas. The beat is a dance beat. Trumpets and a saxophone play fills in between lines. A piano plays a melody at the end of the song. The song starts with the voice singing a melody at a moderate tempo. After the piano plays, the tempo of the song increases. Other instruments cannot be heard as the quality of the recording is low. This song can be played in a Latin dance sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/CN2QSmhP-HI.wav"} +{"id": "COe_UKKVpVo", "caption": "Fast techno with a hardstyle edge. Four on the floor kick with the synth bass and hi-hat on the off beats combined with a rhythmic synth gives the music an intense vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/COe_UKKVpVo.wav"} +{"id": "CP3phqztym0", "caption": "A male vocalist sings this vivacious latin pop song. The tempo is fast with rhythmic Spanish guitar,keyboard harmony, bright drumming, mandolin harmony, groovy bass line and lively pandeira beats. The song is melodic, simple, happy, cheerful, bouncy, peppy , warm and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/CP3phqztym0.wav"} +{"id": "CPX6f-Awx-0", "caption": "A male vocalist sings this spirited French Pop song. The tempo is medium with electronic music, synth arrangements and slick digital drumming. The song is youthful, peppy, buoyant, perky, catchy, romantic, simple and charming. This song is a contemporary French Urbano.", "audio": "/zhanghaomin/datas/musiccap/music_data/CPX6f-Awx-0.wav"} +{"id": "CPr0YRTcaKg", "caption": "The clip contains mostly moments of silence, apart from intermittent moments of activity. There's a camera snapshot sound effect, a male saying some unintelligible words, and rapid synth notes for one second. The male voice is followed by a kick drum, and a riser - we immediately feel as if a song is to ensue.", "audio": "/zhanghaomin/datas/musiccap/music_data/CPr0YRTcaKg.wav"} +{"id": "CQlh4k5pXKA", "caption": "The song is a movie soundtrack. The song is medium tempo with groaning tones, crying sounds, ambient Street noises, and guitar strumming rhythm. The sound track is played for an emotionally sad scene. The audio quality is overall poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/CQlh4k5pXKA.wav"} +{"id": "CRDDdjDinYc", "caption": "A e-guitar takes the lead melody along with the hammond organ. The drums and the bass are providing a rock groove in the background. Another e-guitar is playing along with the bass on the lower notes, it's highly distorted and has some overdrive on it. The male singer streams and sings. His voice is full of reverb and delay. The whole recording is of poor quality. This song may be playing at an old bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/CRDDdjDinYc.wav"} +{"id": "CRHEuoCnI74", "caption": "This clip features a note played on a saxophone. The note goes slightly flat and slightly sharp over the course of playing. There is no melody in this song. There are no other instruments in this song. There are no voices in this song. This song can be used for an instruction video on holding a note on a saxophone.", "audio": "/zhanghaomin/datas/musiccap/music_data/CRHEuoCnI74.wav"} +{"id": "CRIFRYhiKUA", "caption": "Synthesizers are playing soft meditative pad sounds along with strong percussive drum hits, hi-hats and other sound effects that are highly reverbed . In the background you can hear birds singing; glass shattering; water tripping and other sounds that do not belong to the musical composition. This song may be playing for an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/CRIFRYhiKUA.wav"} +{"id": "CRUd8kY3L70", "caption": "This music is an energetic instrumental. The tempo is fast with a vivacious harmonica lead, lively guitar rhythm, enthusiastic cello and punchy drumming. The song starts with an enthusiastic vocal riff. The music is an upbeat, catchy, buoyant, peppy, youthful, energetic and lively Harmonica instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/CRUd8kY3L70.wav"} +{"id": "CRxIJ7YbcZA", "caption": "An acoustic drum is playing a simple groove with a strong kick. The e-bass is playing on every hit of the kick together with an e-guitar strumming a chord. A female voice is singing a slow paced melody. In the background you can hear some maschine sounds and piping sounds. This song may be playing in a James Bond movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/CRxIJ7YbcZA.wav"} +{"id": "CSzMTqkLHyg", "caption": "This is a home recording of a didgeridoo performance. The performance is in the low-to-medium range. There is a raw, tribal atmosphere to this recording. It could be used in the soundtrack of a horror video game that has a jungle/primal setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/CSzMTqkLHyg.wav"} +{"id": "CVLqZyUwqv8", "caption": "The low quality recording features a traditional song that consists of widely spread plucked strings melody, calming pad chord progression playing in the background and reverberant female vocal singing melodies on top of it. It sounds relaxing and calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/CVLqZyUwqv8.wav"} +{"id": "CVgLrsBPt4o", "caption": "This song features a didgeridoo being played. Only one note is played. A male voice narrates a line before playing the instrument. There are no other instruments in this song. There is no melody in the music.", "audio": "/zhanghaomin/datas/musiccap/music_data/CVgLrsBPt4o.wav"} +{"id": "CWKBzt-v8w4", "caption": "A group of female vocalists sing this enthusiastic swing song. The tempo is fast with bright trumpet harmony, cello , rhythmic acoustic guitar and slick drumming. The song is upbeat with vocal emphasis and a lively orchestra. This song is a Classic Swing.", "audio": "/zhanghaomin/datas/musiccap/music_data/CWKBzt-v8w4.wav"} +{"id": "CWQvCCRuU6k", "caption": "Someone is playing a melody on a clean e-guitar, then another e-guitar comes in with a different processed tone, adding some notes to the melody. An acoustic drum is playing a simple groove with a round and soft sounding bass. A male voice is singing/rapping on top with backing voices singing along. This song may be playing in a car on a road trip with friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/CWQvCCRuU6k.wav"} +{"id": "CXCbBSUuugs", "caption": "Pop EDM with a four on the floor kick pattern, a high male vocal with vocal harmonies, synthesizer melodies and dramatic risers for the transitions. This is a club track that sounds professionally recorded and mixed for high fidelity.", "audio": "/zhanghaomin/datas/musiccap/music_data/CXCbBSUuugs.wav"} +{"id": "CYZZIkEw_jY", "caption": "This music is an energetic drum solo. The tempo is fast with an enthusiastic, vigorous drumming riff. The drummer uses the snare and bass drum to create a thumping beat. It is youthful, rhythmic,vivacious, upbeat ,buoyant and infectious.", "audio": "/zhanghaomin/datas/musiccap/music_data/CYZZIkEw_jY.wav"} +{"id": "CYuYfvQv4eo", "caption": "This is the live performance of a jazz music piece. There is an organ playing the chords in the background. There is a complex and improvised saxophone solo in the lead. The acoustic drums are playing a mellow jazz beat. The atmosphere is rather tranquil. This piece could be playing in the background at a coffee shop or a classy restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/CYuYfvQv4eo.wav"} +{"id": "CZWLPPO0KL4", "caption": "A female opera singer sings this high pitched lyrical melody. The song tempo is slow with a philharmonic orchestra accompaniment, with a string section harmony and pizzicato violin play. The song is extremely emotional and spirited. The song is a vintage opera hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/CZWLPPO0KL4.wav"} +{"id": "CZZSQ6rd8h0", "caption": "This audio contains someone playing a violin with a sad melody and strong bow strokes. The piece sounds as if someone is frustrated and emotional. This song may be playing at a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/CZZSQ6rd8h0.wav"} +{"id": "CZoPTJNmiCw", "caption": "The low quality recording features a solo still guitar melody. The recording is a bit noisy and it sounds like it is a live performance. There are also some pluck and string sounds as the instruments are being played.", "audio": "/zhanghaomin/datas/musiccap/music_data/CZoPTJNmiCw.wav"} +{"id": "CZuH43NPynA", "caption": "This song contains several instruments playing the same melody. Violins; flutes, and tin whistles. An acoustic guitar is strumming chords along and a percussive instrument is playing along with the acoustic guitar. In the background you can hear people talking. This song may be playing in an Irish bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/CZuH43NPynA.wav"} +{"id": "Ca3b8qNUbsk", "caption": "A digital drum is full of little percussive and industrial sounding elements that are spread across the sides of the speakers. A synth bass with delay is playing a dark bassline along with a synth pluck melody in the higher register. This song may be playing in a dark movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ca3b8qNUbsk.wav"} +{"id": "CaCjiFUL6Fg", "caption": "This audio contains someone playing tablas along to a string instrument playing a melody with a bow. A female voice is singing the same melody. This song may be playing live singing along to train singing.", "audio": "/zhanghaomin/datas/musiccap/music_data/CaCjiFUL6Fg.wav"} +{"id": "Cchf2QH63bI", "caption": "The track features a scary and confused atmosphere. A female singer with a grating voice screams incomprehensive vocals. A piano accompanies the vocals. The track is simple but has a strong presence.", "audio": "/zhanghaomin/datas/musiccap/music_data/Cchf2QH63bI.wav"} +{"id": "Cd7JefC6-Zw", "caption": "This music is a youthful instrumental. The tempo is fast with a DJ using a turntable to manipulate sounds and music on a turntable using vinyl records. The music has a repetitive, catchy vocal riff , thumping beats and scratching sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/Cd7JefC6-Zw.wav"} +{"id": "CdFutCUKTXI", "caption": "This song is an instrumental. The tempo is fast with synthesiser arrangements , boomy bass and digital drumming. The song is youthful, enthusiastic, engaging, upbeat; vivacious, punchy and buoyant. This song is an EDM/Synth pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/CdFutCUKTXI.wav"} +{"id": "CdWA-SNcYpM", "caption": "This clip features low quality audio. The song is a heavy metal song where a guitar solo is played on the higher register of the scale. This is accompanied by percussion playing an uptempo beat. The bass plays a heavy riff using open notes and its octave. The distortion guitar plays power chords. There are no voices in this song. This is an instrumental song. This song can be played in a racecar sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/CdWA-SNcYpM.wav"} +{"id": "CdgQIiMdBa4", "caption": "This is a Christian gospel music piece. The male vocalist is singing melodically in the Spanish language. There is an acoustic guitar playing the main melody while a bass guitar plays in the background. In the rhythmic background, the acoustic drums are playing a calm beat. The atmosphere is religious. This music would suit well in Christian religious events in Spanish speaking countries.", "audio": "/zhanghaomin/datas/musiccap/music_data/CdgQIiMdBa4.wav"} +{"id": "Ce-Xok6SRPU", "caption": "This is a classical orchestral piece. The piece gives off the feeling of intensity and excitement. It would be used in any scene that is thrilling and suspenseful. We hear french horns, violins and tubas. The violins are used to create a hurried moment of tension before descending back to the main motif on the brass instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ce-Xok6SRPU.wav"} +{"id": "CeaWlENtRio", "caption": "The low quality recording features a traditional song that consists of a repetitive and addictive string melody, wooden percussion and shimmering cymbals. It sounds really energetic and addictive - almost like a pop song would. The recording is a bit noisy and the left channel of the stereo image is occasionally muffled.", "audio": "/zhanghaomin/datas/musiccap/music_data/CeaWlENtRio.wav"} +{"id": "Cf1zNtZEcc8", "caption": "This is a movie music piece. There is a cinematic synth holding a single high-pitched note which creates an aura of suspense and horror. War drums and occasional cymbals create a preparation for battle feeling. This piece could certainly be used in war and horror movies. It could also be used in video games that involve horror and battles.", "audio": "/zhanghaomin/datas/musiccap/music_data/Cf1zNtZEcc8.wav"} +{"id": "CfRzy-RtqnQ", "caption": "These are sounds coming from a film. There is an ambient atmosphere of birds singing. There is a velcro ripping sound. These sounds could be sampled to be used in soundboards or in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/CfRzy-RtqnQ.wav"} +{"id": "CgK0DU3KFBc", "caption": "This slow jazz song features a female voice. This is accompanied by an acoustic guitar playing chords. A keyboard plays a fills using a xylophone-like tone. The bass plays the root notes of the chords. Finger snaps are played in some spaces between lines. A shaker provides the percussion for this song. The song features a jazz chord progression providing some complexity to this song. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/CgK0DU3KFBc.wav"} +{"id": "ChCdYoDz7CY", "caption": "Kid voices are talking along with female voices. Then a background song starts playing a track containing acoustic drums, a piano and a female voice singing. The kids are singing along loudly, sounding cheerful. This song may be playing in a classroom full of kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/ChCdYoDz7CY.wav"} +{"id": "ChqJYrmQIN4", "caption": "The low quality recording features a live performance of a folk song that consists of an accordion melody playing over groovy bass, shimmering hi hats, punchy snare and electric guitar melody. There are crowd chattering noises in the background. It sounds passionate and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ChqJYrmQIN4.wav"} +{"id": "ChyayWIp_vU", "caption": "A male voice is singing along to a fast paced reggae instrumental. The drums are playing a reggae-groove along with a harmonica on the offbeat. Two e-guitars are playing a single note melody. Both are following the bassline adding harmonies. A saxophone is adding a little melody after every end of a phrase. The male voice is singing in the mid-range and sounds doubled. Some of the instruments are panned to the left and right side of the speakers. This song may be playing at a local bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/ChyayWIp_vU.wav"} +{"id": "Ck-1kRnHqro", "caption": "This audio contains complex and fast acoustic drums with a lot of cymbal hits along with a tambourine shaker. E-guitars and e-bass are playing along to the drums. This piece is in a 7/4 time signature. This song may be playing at a live rock concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ck-1kRnHqro.wav"} +{"id": "Ck_bvV8Aa-k", "caption": "This is the amateur recording of a jazz music piece performed live on the street. The volume of the recording is quite low. There is a female vocalist singing upfront. The tuba is playing the bass line as an accompaniment to the vocals. The tuba player is playing a minimal acoustic drum kit made up of just a drum kick and a ride cymbal in the meantime. There is a swing feel to it. The quietness of the recording makes it sound like the music is coming from vinyl. It would suit perfectly as a piece in a movie playing on a vinyl record player.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ck_bvV8Aa-k.wav"} +{"id": "CkgzMSbE68M", "caption": "The low quality recording features a sound from a video game that consists of sea sound effects, seagull sound effects, ping pong sound effects and weird, short, pitch bend riser sounds. In the beginning of the loop, there is a short snippet of some music playing in the background. The instrumental consists only of drums - wide kick hits, shimmering cymbals and some manic snare hits. There is a short echoing effect on drums that serves as a transition to the in-game sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/CkgzMSbE68M.wav"} +{"id": "ClK_qf_Twm8", "caption": "The song is instrumental. The song is medium tempo with a groovy bass line, keyboard harmony, various percussion hits and a steady drumming rhythm. The song has a dance rhythm and is exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/ClK_qf_Twm8.wav"} +{"id": "ClNTn1wtq7E", "caption": "Someone is playing an acoustic drum groove with a slightly open hi hat while an e-guitar is strumming chords along with an e-bass playing the root note walking up the fretboard. Another e-guitar is playing the lead melody. A male voice is singing a short phrase. This song may be playing at home sitting in your room and enjoying music and memories.", "audio": "/zhanghaomin/datas/musiccap/music_data/ClNTn1wtq7E.wav"} +{"id": "Cn3xoxvbkF0", "caption": "This is the live performance of a reggae piece. There is a female vocalist in the lead singing melodically. The keyboard can be heard playing the main melody. The bass guitar is playing a simple but groovy bass line. In the rhythmic background, there is a slow tempo acoustic drum beat. The atmosphere is emotional. This is an amateur recording and a bit dated, so the audio quality is quite poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/Cn3xoxvbkF0.wav"} +{"id": "CnTMm-bzssM", "caption": "The low quality recording features a mellow piano melody, followed by sustained strings melody. It sounds sad, emotional and melancholic.", "audio": "/zhanghaomin/datas/musiccap/music_data/CnTMm-bzssM.wav"} +{"id": "CodqNx1ukOc", "caption": "Someone is playing a melody on the e-guitar with a lot of reverb and a little bit of delay. This song may be playing guitar at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/CodqNx1ukOc.wav"} +{"id": "CpHRQ-f4UtA", "caption": "This song contains a timpani hit going along with single notes of an upright bass. A string section is playing a simple melody in a higher key while an oboe/flute is playing the lead melody. In the background you can hear a brass section playing along with the strings rising and falling in volume. This song may be playing in a sad and mystic movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/CpHRQ-f4UtA.wav"} +{"id": "CphwhKgYHaM", "caption": "A male vocalist sings this mellow jazz song. The tempo is medium with a spirited saxophone accompaniment, jazzy piano, groovy bass lines, slick drumming and trumpet . The song is melodic, catchy, ambient, romantic, groovy, light and breezy with a swing rhythm. This song is a lively Jazz song.", "audio": "/zhanghaomin/datas/musiccap/music_data/CphwhKgYHaM.wav"} +{"id": "CqtknE729Lw", "caption": "This is an instrumental classical music piece with clear Italian influences. There is a piano playing a gentle melody and a mandolin being strummed rapidly but with low velocity. The atmosphere is relaxing. This piece can be used during the scenery shots of a romance movie taking place in a Mediterranean country.", "audio": "/zhanghaomin/datas/musiccap/music_data/CqtknE729Lw.wav"} +{"id": "CrbZHPkHeV4", "caption": "A male vocalist sings this passionate Rap. The tempo is medium with steady drumming, keyboard harmony, amplified piano accompaniment, and groovy bass lines . The song is emotional, intense, persuasive, intense and has a catchy groove. This song is contemporary Rap/Hip-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/CrbZHPkHeV4.wav"} +{"id": "CretxKgW4Jk", "caption": "This is a K-pop music piece being performed live by a girl group. There are female vocals singing melodically. There is a keyboard playing a simple and repeated theme. The rhythmic background consists of a danceable electronic drum beat. The atmosphere is easygoing. This piece could be playing in the background at a clothing store.", "audio": "/zhanghaomin/datas/musiccap/music_data/CretxKgW4Jk.wav"} +{"id": "CrjSYvGWusQ", "caption": "This raaga music features a male singer. This is accompanied by twinkling sounds made by bells at different frequencies. There is a synth playing a wind-like sound in the background. There are no other instruments in this song. This song has a religious chanting feel. This song can be played for a meditation session. The mood of this song is peaceful.", "audio": "/zhanghaomin/datas/musiccap/music_data/CrjSYvGWusQ.wav"} +{"id": "CrkxrgTiVyk", "caption": "The low quality recording features a live performance of a jazz song and it consists of a groovy bass guitar, groovy rhodes keys, electric guitar melody, shimmering hi hats, punchy kick and punchy snare hits. It sounds groovy, funky and passionate. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/CrkxrgTiVyk.wav"} +{"id": "CtcmYF7mufk", "caption": "This is a minimal techno music piece. There is a repeated vocal sample shouting the same thing repeatedly. In the background, a very strong bass is accompanied by the electronic kick drum to provide the rhythmic background. A dirty snare drum with heavy effects joins them later on. The piece is very danceable. It could be used in a nightclub. It could also be included in a DJ set.", "audio": "/zhanghaomin/datas/musiccap/music_data/CtcmYF7mufk.wav"} +{"id": "CuUu6L5hhMs", "caption": "The instrumental music features a medium sized band playing Latin music. The melody is being played in unison by the saxophones, trumpets and trombones in an almost fast tempo. A bass guitar is playing repeating lines in the low register. The drums play a busy rhythm. An electric guitar is playing a chord on the second half of every beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/CuUu6L5hhMs.wav"} +{"id": "CudxWnS7ukw", "caption": "The song is an instrumental. The song is medium fast tempo with a groovy bass line, acoustic guitars strumming rhythm, and a ukulele playing lead. The song is spirited and exciting. The song is an instrumental with country music influences.", "audio": "/zhanghaomin/datas/musiccap/music_data/CudxWnS7ukw.wav"} +{"id": "CwHSb1NOi4c", "caption": "The marimba takes the lead melody along with an acoustic piano providing some underlining jazzy chords with a lot of changes. The upright bass sounds round and quiet. The acoustic elements are providing latin grooves. The instruments are all slightly panned to the left and right side of the speakers. This song may be playing in an elevator.", "audio": "/zhanghaomin/datas/musiccap/music_data/CwHSb1NOi4c.wav"} +{"id": "CwImmV7q1MY", "caption": "The low quality recording features a harmonica solo melody playing over a boomy playback song in the background. The song consists of shimmering hi hats, groovy bass and electric guitar melody. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/CwImmV7q1MY.wav"} +{"id": "Cwbtn_h6TP8", "caption": "A female singer sings this screaming metal melody. The song is medium tempo with a steady metal drumming rhythm, steady bass line and a distorted guitar playing rhythm. The song is rebellious and passionate. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/Cwbtn_h6TP8.wav"} +{"id": "CwmUMySSNQc", "caption": "A male and female singer sing this vocal duet. The song is medium fast tempo with a guitar accompaniment, steady drumming rhythm with exciting drum rolls, cymbals crashes and a percussive bass line. The song is romantic and exciting. The song is retro pop with a bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/CwmUMySSNQc.wav"} +{"id": "CxTFgimfNfA", "caption": "This audio contains a loop repeating a beatbox pattern and clapping sound. A horn is playing a lower melody while someone is playing a long note on top in a higher key. This is an amateur recording and may be playing while looping yourself.", "audio": "/zhanghaomin/datas/musiccap/music_data/CxTFgimfNfA.wav"} +{"id": "CxgVq6eovRU", "caption": "The low quality recording features a drums tutorial where a flat male vocalist is talking after shimmering his hats, snappy snare hits and pumping kicks. It sounds groovy and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/CxgVq6eovRU.wav"} +{"id": "Cy3HWnwMLyI", "caption": "This music is an intense instrumental. The tempo is medium with an incessant droning of the didgeridoo, stringed instrument riff, and synthesised sounds like metallic sounds,menacing grunts, roars, echoes, resonance and bells ringing in the distance. The music is intense, sinister, dangerous, anticipatory, burgeoning, spooky and hostile. This is an Electro Trap.", "audio": "/zhanghaomin/datas/musiccap/music_data/Cy3HWnwMLyI.wav"} +{"id": "CyFsI_EYFQQ", "caption": "The Electro song features an addictive synth lead melody playing over quiet snare roll, some claps and sweeping sound effects. In the second half of the loop, there is a \"4 on the floor\" kick patter. It is uptempo and it sounds energetic and sort of addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/CyFsI_EYFQQ.wav"} +{"id": "CyiPyjYX6AE", "caption": "The audio starts with someone playing singing bowls with a lot of sustain/release time. Then another sequence begins with someone playing a hand pan along with a shaker. This is an amateur recording. These songs may be playing during a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/CyiPyjYX6AE.wav"} +{"id": "CzHZNJEV-3o", "caption": "This clip features a nursery rhyme. The singer plays the guitar and sings in a calm and gentle tone. The singer misses some notes on the guitar - playing with some mistakes. The quality of the audio recording is low.", "audio": "/zhanghaomin/datas/musiccap/music_data/CzHZNJEV-3o.wav"} +{"id": "CzMNiypg1I8", "caption": "The music features a male voice singing and being backed by similar male voices. The rhythm section consists of a busy drum rhythm, a shaker, a bass guitar and the traditional Indian drums - tablas. In the background one can hear an electric guitar playing a repeating note in the first half of the music excerpt and in the second one an electronic sound playing a repeating melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/CzMNiypg1I8.wav"} +{"id": "Czbi1u-gwUU", "caption": "This song contains acoustic drums and percussion playing a complex rhythm along with a bassline. Some brass sounds come here and there to set accents. In the background you can hear a string sound playing a high note. A keyboard lead sound is playing the main melody along with a male voice singing with a melody on his own. This song may be playing at a celebration.", "audio": "/zhanghaomin/datas/musiccap/music_data/Czbi1u-gwUU.wav"} +{"id": "D-PxXM2I5gY", "caption": "The low quality recording features a chill electric guitar melody. It sounds easygoing and relaxing. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/D-PxXM2I5gY.wav"} +{"id": "D-p9s8y2z_U", "caption": "This music is instrumental . The tempo is fast with mandolins playing a lively, spirited rhythmic harmony with acoustic guitar accompaniment. The instrumentation is minimal with emphasis on the mandolin melody. The music is chirpy, perky, cheerful, happy, animated and spirited.", "audio": "/zhanghaomin/datas/musiccap/music_data/D-p9s8y2z_U.wav"} +{"id": "D0L-M4trkpw", "caption": "The drums and the upright bass are playing in a bluesy, country vibe with a half open hi hat. An acoustic guitar is strumming chords that are almost not noticeable. The e-guitar is playing a loud lead melody in the foreground while a violin is playing short bowed notes along. This is an amateur recording. This song may be playing in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/D0L-M4trkpw.wav"} +{"id": "D2w3qHmJrdU", "caption": "The song is an instrumental. The song is medium tempo with a guitar playing solo, steady drum rhythm, groovy bass line and steady bass line. The song is funky and groovy in nature. The song is an ad jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/D2w3qHmJrdU.wav"} +{"id": "D3FyfFIKLVc", "caption": "A male vocalist sings this sweet melody in a foreign language. The tempo is medium with keyboard accompaniment, steady drumming, synthesiser arrangement and acoustic guitar. The song has a simple, easy melody. It is earnest, emotional, calm and soothing. This song is a Regional Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/D3FyfFIKLVc.wav"} +{"id": "D3f5VIJYR7M", "caption": "The low quality recording features a saxophone scale run melody. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/D3f5VIJYR7M.wav"} +{"id": "D3ht_xXl5S0", "caption": "The low quality recording features a disco song that consists a fruity male vocal singing over groovy bass, punchy \"4 on the floor\" kick pattern, wide funky electric guitar chords, shimmering open hats, muffled punchy snare, shimmering bells melody, groovy bass, high pitched sustained strings melody and low toms. There is a short snippet of harmonizing vocals at the end of the loop. It sounds energetic and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/D3ht_xXl5S0.wav"} +{"id": "D3q_stCeCA8", "caption": "This is an African folk music piece. There are two female vocalists and a male vocalist singing in a tribal style. The rhythm is played by one of the singers with a shekere in her hand. The atmosphere is vibrant. This piece could be playing in the soundtrack of an adventure movie that takes place in Africa.", "audio": "/zhanghaomin/datas/musiccap/music_data/D3q_stCeCA8.wav"} +{"id": "D4GVgBX1eYc", "caption": "This composition contains a cello playing in the lower register providing a bass melody while other violas and violins are playing a melody and a countermelody in the mid to high range. This song sounds suited for a wedding proposal.", "audio": "/zhanghaomin/datas/musiccap/music_data/D4GVgBX1eYc.wav"} +{"id": "D4ccFYk3bhU", "caption": "This music clip is an electronic instrumental. The audio quality is inferior, so the music is incoherent, but there are some elements that stand out like intense drumming; punchy bass lines, synthesiser arrangements, female vocalisation, a syncopated xylophone-like instrument. The music is being played outdoors as there is the sound of vehicles, honking,people talking and some rustling. The music is peppy, energetic , enthusiastic and has a trippy, trance like vibe.This song is an EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/D4ccFYk3bhU.wav"} +{"id": "D644BWAUOXo", "caption": "This is a gentle, soothing and meditative song of South Asian origin. The electric piano is played along with a group of singers who sing calmly in unison. The song has an uplifting emotional effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/D644BWAUOXo.wav"} +{"id": "D6xrH93lnoc", "caption": "This is a rock-n-roll music piece. There is a male vocalist singing as if he is telling a story in the lead. The electric and the bass guitar are playing a simple tune. The acoustic drums are playing an upbeat rhythm with a heavy use of rimshots. The atmosphere of the piece is groovy. This piece could be used in the soundtrack of a romance/romantic comedy movie where the protagonist cannot stop thinking about a girl.", "audio": "/zhanghaomin/datas/musiccap/music_data/D6xrH93lnoc.wav"} +{"id": "D712KM8PE3I", "caption": "This song features female voices singing in harmony. There are no instruments in this song. The voices are relaxing. The song starts with vocables and then the singers sing some Hindi words in a very relaxing tone. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/D712KM8PE3I.wav"} +{"id": "D7Cvisf3jf8", "caption": "This is a documentary music piece. There is a strings section that is holding a single chord. The bass guitar is repeating an ominous bass line. There is a simple percussion beat in the rhythmic background. The atmosphere has a dramatic feel to it. It feels like a story is about to unfold. The piece suits perfectly as a documentary music piece. It could also fit well in the soundtrack of a mystery movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/D7Cvisf3jf8.wav"} +{"id": "D7pjR9cQChM", "caption": "The drums are playing a four on the floor techno rhythm with hihats and a strong kick. A synthetic bass follows the kick with almost just a single note playing. Panned to the left and right side of the speakers you can hear a monotone, repeating synth melody. This song may be playing in a technoclub.", "audio": "/zhanghaomin/datas/musiccap/music_data/D7pjR9cQChM.wav"} +{"id": "D7z2Q-hH25s", "caption": "This salsa song features a male voice singing the main melody. This is accompanied by percussion playing a salsa beat. The piano plays a typical salsa rhythm using the main chords for the song. The bass plays the root note and fifth of the chord. Due to the low quality of the audio, other instruments are not audible. This is a cover song of another famous song. This song can be played for a salsa dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/D7z2Q-hH25s.wav"} +{"id": "D8-x1T8M4gk", "caption": "This is a rock and roll piece used as an accompaniment for a dance. There is a male vocal singing at a low-to-medium pitch. The main melody is being played by an electric guitar while the bass guitar is repeating a bass line with a groovy pattern in the background. The acoustic drums are playing an upbeat 4/4 rock and roll beat. There is a raw feeling to it. The tune is catchy. This piece could be playing in the background of a sports bar or a rock bar. It could also work well at sports venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/D8-x1T8M4gk.wav"} +{"id": "D8zK7PHIkgA", "caption": "A male vocalist sings this enthusiastic hip-hop song. The tempo is medium fast with a lively keyboard harmony, slick drumming, subtle drumming, cymbals, synthesiser arrangements and enthusiastic vocal backup. The song is lively, spirited, youthful, passionate, emotional and persuasive. It talks about love, peace, freedom,harmony and kindness towards humankind. This song is a Reggae Fusion/ Hip-Hop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/D8zK7PHIkgA.wav"} +{"id": "D9893od03Sc", "caption": "The low quality recording features a live performance of a country song that consists of an acoustic rhythm guitar, groovy bass guitar, shimmering hi hats, simple kick, punchy snare and steel guitar repetitive melody. At the end of the loop, there is a short snippet of passionate male vocal singing, while at the beginning there is a crowd clapping sound. It sounds joyful and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/D9893od03Sc.wav"} +{"id": "D9TuP8PKD6M", "caption": "A marimba playing the main melody along with a little brass-section playing another melody along. The e-bass is playing along with the drums holding a country-like rhythm. This song may be playing at a park with little food trucks.", "audio": "/zhanghaomin/datas/musiccap/music_data/D9TuP8PKD6M.wav"} +{"id": "DA3fNvbZoBM", "caption": "This is a quintessentially folk-rock song, with at least a three-part country-folk harmony. There is an acoustic guitar arpeggio throughout the clip, and a powerful stab on the bass strings every second bar. The song feels sombre, in a way.", "audio": "/zhanghaomin/datas/musiccap/music_data/DA3fNvbZoBM.wav"} +{"id": "DA8lw6Mq0DY", "caption": "A female voice is singing a ballad with some reverb on her voice while an acoustic guitar is finger-picking chords on the left side of the speakers. A string section is playing harmonies along with the singer. A e,bass is played along with shakers and ride hits from a drummer. A piano is playing along with the melody. The elements are spread across the sides of the speakers.", "audio": "/zhanghaomin/datas/musiccap/music_data/DA8lw6Mq0DY.wav"} +{"id": "DAPGvg8qOAU", "caption": "This is an acoustic folk piece. The main melody is being played with a mandolin while there is an acoustic guitar backing. A male vocalist is singing in a story-telling mood. The overall atmosphere of the piece is mellow. This piece could definitely be used in the soundtracks of romantic movies. It could also be played in sequences that emphasize longing and loneliness.", "audio": "/zhanghaomin/datas/musiccap/music_data/DAPGvg8qOAU.wav"} +{"id": "DAX9uKYlDvw", "caption": "This is a traditional Latin American song which would be suitable for salsa dancing. There are layers of percussion including bongo drums and snare drums. The pianist plays intricate melodies and the brass section plays vibrant and punchy motifs. It's a live performance with a relatively poor audio quality. There is a male group of singers performing energetically.", "audio": "/zhanghaomin/datas/musiccap/music_data/DAX9uKYlDvw.wav"} +{"id": "DB38NRSHw9A", "caption": "The music contains an erotic male voice which is out of key and clearly in the foreground. In the background there's a sustained soft piano synth and a drum kit playing a mid pitch beat. The atmosphere is sexual and seductive.", "audio": "/zhanghaomin/datas/musiccap/music_data/DB38NRSHw9A.wav"} +{"id": "DC0C-KO9EJk", "caption": "This song contains a synth bass changing pitch really fast along with a digital drum groove. A distorted e-guitar is playing a riff that is panned to the right side of the speakers. This audio may be playing in a fast paced, arcade video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/DC0C-KO9EJk.wav"} +{"id": "DCFrCX4HPO8", "caption": "A female singer sings this passionate melody. The song is a medium tempo with a groovy bass line , steady drumming, keyboard accompaniment, Indian percussion and tambourine accompaniment. The song is playful and romantic. The song is a modern Bollywood pop song with average quality audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/DCFrCX4HPO8.wav"} +{"id": "DDZlMjb-0i4", "caption": "This song contains digital drums with a reverbed snare and a helicopter-sound. The whole recording is completely over-driving the speakers. It is of very poor sound quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/DDZlMjb-0i4.wav"} +{"id": "DE6bdmnmPtg", "caption": "A male vocalist sings this energetic funk pop. The audio quality is inferior and the song is not clear.The tempo is. Fast with animated trumpets, with a boomy trombone, infectious drumming, keyboard harmony, groovy bass lines, rhythmic electric and acoustic guitar and melodious choral backup. The song is melodic, enthusiastic, energetic, animated and captivating Retro Funk/Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/DE6bdmnmPtg.wav"} +{"id": "DEnayQZiPGc", "caption": "The song is an instrumental. The tempo is variable, with a timpani crash, various beeping tones and a crescendo grungy keyboard harmony tone. The song is a soundtrack for an advertisement. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/DEnayQZiPGc.wav"} +{"id": "DG5d4megH8g", "caption": "An acoustic guitar is strumming chords. A violin is playing a melody along with a flue and another hammered string instrument. Percussions are being played in a rhythm that is not a 4 bar count. All the instruments are spread across the sides of the speakers. This song may be playing in a desert movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/DG5d4megH8g.wav"} +{"id": "DGON0D8E17Q", "caption": "This music is instrumental. The tempo is fast with a burgeoning beat and digital swishing sounds. The music clip seems to be the introduction of the song as it starts with a slow tempo and decibel and rapidly builds up to a faster beat. The music is youthful, buoyant, energetic, pulsating and high spirited. This song is an Electronica/Techno Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/DGON0D8E17Q.wav"} +{"id": "DGbMEkQerYs", "caption": "A male voice is singing along to a blues/rock bassline and acoustic drums. A e-guitar and a banjo are playing the same melody as the bass. All the instruments are playing when the male voice is not singing. Then after fading out a new song starts with a percussive sound, an upright bass, piano and a female voice singing.This song may be playing in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/DGbMEkQerYs.wav"} +{"id": "DGlP6oTqe5Y", "caption": "A male vocalist sings this energetic song. The tempo is fast with synthesiser arrangements, digital drumming and tambourine beats along with an incessant catchy vocal riff and vocalisation. The music is buoyant, energetic,enthusiastic , pulsating, punchy and groovy. This song is Techno Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/DGlP6oTqe5Y.wav"} +{"id": "DHDn79ee98Q", "caption": "This song contains synthesizer pads and plucks playing all over the place along with ringing sounds, timpani and snare hits. This song may be playing for a bossfight in a video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/DHDn79ee98Q.wav"} +{"id": "DHo1z0_ZUNA", "caption": "The song is a slow country song - a country ballad played on a steel guitar. This is the type of song that would be suitable for an old country western movie where a hero character walks into a diner. This is a live recording and the song has a slow tempo.", "audio": "/zhanghaomin/datas/musiccap/music_data/DHo1z0_ZUNA.wav"} +{"id": "DJHEBMNPc-A", "caption": "a solo electronic drum beat featuring snaps with a long reverb, a clicky synth melody through a stereo delay, a crunchy kick playing a syncopated pattern and high fidelity production. Sophisticated and stylish.", "audio": "/zhanghaomin/datas/musiccap/music_data/DJHEBMNPc-A.wav"} +{"id": "DKBbLySEGic", "caption": "The low quality recording features a live performance that consists of harmonizing mixed vocals singing over distorted bass and arpeggiated synth keys melody. It sounds crushed, harsh and the stereo image is unbalanced since the sound is leaning towards the right channel of the stereo image. There are some crowd excitement sounds in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/DKBbLySEGic.wav"} +{"id": "DKflAAykh6A", "caption": "A male singer sings this Latin melody. The song is medium tempo with a groovy Latin percussive rhythm, keyboard accompaniment, brass band harmony and a groovy bass line. The song is romantic and emotional. The song is a salsa dance hit, but has poor audio quality issues..", "audio": "/zhanghaomin/datas/musiccap/music_data/DKflAAykh6A.wav"} +{"id": "DLDZrtwyY_Y", "caption": "The song is an instrumental. The song is medium tempo with a brass quartet playing French horns playing a well known movie soundtrack to the crowds cheering, clapping and whistling. The sound quality is bad with ambient crowd noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/DLDZrtwyY_Y.wav"} +{"id": "DLJGT99uEh4", "caption": "The low quality recording features a reverberant instrumental that consists of punchy kick hits, claps, shimmering hi hats, bouncy and tinny percussive elements. There are wide echoing effects at one point of the loop. Sounds energetic and groovy, like something you would hear in underground clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/DLJGT99uEh4.wav"} +{"id": "DMwvY--3XD0", "caption": "This children's song features the voices of children singing the main melody. This is accompanied by percussion playing a simple beat. A keyboard plays the sounds of a marimba to give this song a reggae feel. The bass plays the root notes followed by a run at every chord change. This song has a happy mood. This song can be played in a children's animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/DMwvY--3XD0.wav"} +{"id": "DNYDyXn6qso", "caption": "Two female singers sing this delightful vocal duet in harmony. They make funny animated vocal effects like yodelling and funny animal noises. The song is medium fast tempo with a guitar accompaniment and no percussion. The song is cheerful and story telling in nature. The song is a vintage pop song with bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/DNYDyXn6qso.wav"} +{"id": "DO8Db_i7IVc", "caption": "This is a techno trance music piece. Multiple synths are used to create the repetitive theme of a multi-layered melodic background. There is a strong fuzzy synth bass sound. A piano can be heard playing a leading tune. The atmosphere is loud and vibrant and danceable. It could be played at nightclubs and DJ playlists.", "audio": "/zhanghaomin/datas/musiccap/music_data/DO8Db_i7IVc.wav"} +{"id": "DOb8htND5_o", "caption": "This disco song features female voices and male voices singing vocables in harmony in the background. A synth melody is played in the foreground. Toward the end of the melody, a synth swell is played in a ringing tone. At the peak, the percussion starts to play a dance beat. The synth changes melody to a faster rhythm. The mood of this song is happy and upbeat. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/DOb8htND5_o.wav"} +{"id": "DP2vmsftZHY", "caption": "This song is a sweet duet. The tempo is medium with a melodious, intense piano accompaniment , electric guitar rhythm, steady drumming and synthesiser arrangements. This song is melodic, story telling, spirited, emotional, passionate and sweet. The lyrics are simple and so this song could be a Children\u2019s Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/DP2vmsftZHY.wav"} +{"id": "DP72GDe6AAs", "caption": "This song contains a drum set playing a groove with an outstanding snare hit and hihats panned to the right side of the speakers. Synthesizer pad sounds are rising up in pitch to the mid range. The recording also contains something like a short sniffing sound used as part of the rhythm and sound effects. This song may be playing in a thriller-movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/DP72GDe6AAs.wav"} +{"id": "DPW5M1FYxu4", "caption": "This composition contains acoustic guitars strumming chords panned to the right side of the speakers. Other plucked string instruments are playing a melody along. An acoustic drum is playing a simple dance groove with a pregnant hihat. In the background you can hear an upright bass and violins playing a melody on the next part of the song. A male voice is singing in the mid-to high range. This song may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/DPW5M1FYxu4.wav"} +{"id": "DQ_gcdLhAsY", "caption": "A female singer sings this Bollywood melody. The song is medium tempo with a steady drumming rhythm with various Indian percussion like bells and tabla, keyboard harmony and string harmony. The song is romantic and emotional. The song is a retro Bollywood love song with an average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/DQ_gcdLhAsY.wav"} +{"id": "DQrdOgRb-oA", "caption": "This is an ambient/electronica music piece. It is an instrumental piece. There is a granular synth playing a vague sounding melody while a warp effect enters and a piano starts playing gently. There is a nostalgic and melancholic feel to it. This piece could be playing in the soundtrack of a drama movie during a scene where the feeling of regret is emphasized.", "audio": "/zhanghaomin/datas/musiccap/music_data/DQrdOgRb-oA.wav"} +{"id": "DQzg3cZeYSw", "caption": "This is an amateur recording of a little girl performing on a turntable. The girl can be heard talking to the person behind the camera. There is a repeating male vocal sample and an electronic drum beat in the piece that is playing. There is an urban atmosphere to the track.", "audio": "/zhanghaomin/datas/musiccap/music_data/DQzg3cZeYSw.wav"} +{"id": "DRU-IFx-7yQ", "caption": "This song contains a synth riser sound than a male voice sample that was pitched very low and starts to say a phrase before the beat hits in with a fast digital drum and bass groove along with an aggressive synth bass sound. A synth lead sound is playing a melody creating a countermelody to the bass. This song may be playing while doing extreme sports.", "audio": "/zhanghaomin/datas/musiccap/music_data/DRU-IFx-7yQ.wav"} +{"id": "DTkKGYCRMlc", "caption": "Quick, forceful wind ensemble music featuring a horn solo with brass, tuba, bass drum and snare drum accompanying.", "audio": "/zhanghaomin/datas/musiccap/music_data/DTkKGYCRMlc.wav"} +{"id": "DTnCrtCro44", "caption": "This song features a didgeridoo playing the main melody. This is a droning sound. This is accompanied by percussion playing a simple beat. A bass playing fills in the same scale as the didgeridoo melody. A piano plays filler chords in between lines. In the background, the sound of crickets is played. The sound of birds chirping is played. This song can be played in a meditation session. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/DTnCrtCro44.wav"} +{"id": "DU3Vlaa8rU0", "caption": "The low quality recording features a tutorial on boomy organ keys narrated by flat male vocals. It is noisy and the recording is in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/DU3Vlaa8rU0.wav"} +{"id": "DU5pD63Pv30", "caption": "These are sounds coming from an advertisement. There are sound effects of bed creaking and laughter implying an intercourse is taking place. Then the act is interrupted by a goofy accordion tune. Sounds from this track can be used in soundboards or in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/DU5pD63Pv30.wav"} +{"id": "DUNOn71oGCw", "caption": "The song is an instrumental. The song is medium tempo with a guitar playing solo accompaniment style, with a subtle bass line. The song is entertaining and passionate. The song audio quality is poor with a lot of ambient echoes.", "audio": "/zhanghaomin/datas/musiccap/music_data/DUNOn71oGCw.wav"} +{"id": "DUmXpq-Cksg", "caption": "The low quality recording features a percussionist playing groovy cowbell over instrumental music playing in the background. It is kind of loud, noisy and the recording is in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/DUmXpq-Cksg.wav"} +{"id": "DV5mynb77JM", "caption": "Here we have a guitarist playing an intricate rock motif on the electric guitar. We hear some rapid plucking of a melody that sounds dark and mysterious. This is a live recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/DV5mynb77JM.wav"} +{"id": "DVuWm53IlVw", "caption": "The low quality recording features a live performance of an aggressively strummed Spanish guitar and passionate female vocal singing on top of it. It is very noisy, but it sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/DVuWm53IlVw.wav"} +{"id": "DW3z-ByrfWY", "caption": "The low quality recording features a flat male vocal talking over digital synth melody, followed by stuttering buzzy noise. The recording is in mono and very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/DW3z-ByrfWY.wav"} +{"id": "DW7Qe-50X_A", "caption": "This is a Jordanian folk music piece. There is a male vocalist singing in the Arabic language in a melancholic manner. The melody is being played at a medium range by the rabab. There is a string section backing holding a single note. The atmosphere is solemn. This piece could be playing during a mourning scene in a drama movie that takes place in the Arab world.", "audio": "/zhanghaomin/datas/musiccap/music_data/DW7Qe-50X_A.wav"} +{"id": "DX4_QlYLq30", "caption": "This is a lullaby music piece. It is an instrumental piece. There is a music box playing a gentle melody in the major key. The atmosphere is calming and relaxing. This piece could fit perfectly in a playlist meant to be played for babies before sleep. It could also be playing in the background at a daycare center.", "audio": "/zhanghaomin/datas/musiccap/music_data/DX4_QlYLq30.wav"} +{"id": "DXd83S6NHLg", "caption": "This clip features the sound of a Tibetan singing bowl. The sound is a high pitched sound that is sustained without breaks. It's a relaxing and serene sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/DXd83S6NHLg.wav"} +{"id": "DXeiJpZXVAI", "caption": "The low quality recording features a live performance that consists of shimmering hi hats, claps, groovy bass, groovy piano melody, brass melody and punchy snare. In the second half of the loop, there is a boomy microphone feedback, which makes a happy and fun atmosphere a bit suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/DXeiJpZXVAI.wav"} +{"id": "DY7ko7iQCug", "caption": "A female voice is singing along to a karaoke track containing an acoustic drumset playing a simple groove, an e-guitar playing a melody on top and female backing voices. This song may be playing at a karaoke night.", "audio": "/zhanghaomin/datas/musiccap/music_data/DY7ko7iQCug.wav"} +{"id": "DYp8940tHso", "caption": "This is the guitar cover of a speed metal/progressive metal piece. The distorted electric guitar is playing a solo. There is a rapid and complex procession of notes in the solo which is played by the shredding technique. There is a loud and violent atmosphere to the recording. The quality is quite poor since the recording is a bit dated.", "audio": "/zhanghaomin/datas/musiccap/music_data/DYp8940tHso.wav"} +{"id": "DYpjbiyPUho", "caption": "The low quality recording features an explosion and glass shattering sound effects, while sustained accordion melody, muted plucked strings melody, bouncy snare, snappy rimshots, shimmering hi hats and \"4 on the floor\" kick pattern are playing in the background. The Drums are mostly panned to the left channel of the stereo image, which is making it unbalanced, although it sounds fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/DYpjbiyPUho.wav"} +{"id": "DZ3EShJzOOc", "caption": "Synthesizes are playing dreamy pads with a lot of reverb. This song may be playing while watching a documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/DZ3EShJzOOc.wav"} +{"id": "D_QEW1Lnl2Q", "caption": "The low quality recording features mono sounds of beeping sound effects, scissors sound effects and some wooden foley effects. It is obviously a video game sound effect, but the sound quality is low since it does not have much depth to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/D_QEW1Lnl2Q.wav"} +{"id": "D_usHKfOXCw", "caption": "This audio features a drum practice pad being played. A shuffle beat is played on the practice pad. There are no other instruments in this song. A male voice narrates instructions. This song can be played in an instructional video on the shuffle beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/D_usHKfOXCw.wav"} +{"id": "DaeJYtWgcoI", "caption": "The song is instrumental.The tempo is fast with a strong metal drumming rhythm, groovy bass line, cymbals crashing, guitar lead and guitar rhythm. The song is chaotic and energetic. The song has very poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/DaeJYtWgcoI.wav"} +{"id": "DaiVfxATCEE", "caption": "This is a live performance of a Tarab music piece. It is being played by an orchestra that is composed of string and oud players that provide the melody and percussion players that provide the rhythmic background. There is a male vocalist as the lead. Clear influences of Arabian music can be heard in the piece. There is a joyful atmosphere. It can be played in the background of a Middle Eastern/North African cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/DaiVfxATCEE.wav"} +{"id": "Db0c4aAwUbY", "caption": "A lot of people are playing different parts of a funk song on steel-drums. An acoustic drum is playing a faster funk groove together with congas and shakers. This song may be playing outside at a live show.", "audio": "/zhanghaomin/datas/musiccap/music_data/Db0c4aAwUbY.wav"} +{"id": "DdxW_JziHTA", "caption": "The low quality recording features a funk song that consists of passionate male vocal singing over shimmering open hats and shakers, funky and groovy keys melody, groovy bass, wooden percussive elements and \"4 on the floor\" kick pattern. It is noisy, but also funky and the stereo image is unbalanced, as the song is leaning towards the right channel.", "audio": "/zhanghaomin/datas/musiccap/music_data/DdxW_JziHTA.wav"} +{"id": "DewyiIpkzi8", "caption": "The song has a traditional jazzy feel to it. The piano chord progression is bouncy and light. The electric guitar has a chorus applied to it, and we hear various licks being played.", "audio": "/zhanghaomin/datas/musiccap/music_data/DewyiIpkzi8.wav"} +{"id": "Dg8BLvkzdr0", "caption": "The low recording features a boomy trombone played in a large space and, at the very end of the loop, the short and subtle female vocal. It sounds very noisy and there are a couple of floor crackling sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/Dg8BLvkzdr0.wav"} +{"id": "DgVpK6r7JT4", "caption": "This is an excerpt from a dubbed anime. There is a male voice speaking in a funny manner. Then, a dramatic orchestra piece starts playing to imply something is about to happen. The brass section and the timpani are playing a rising pattern until a sneeze and hissing sounds can be heard. There is a peculiar feel to this track. Parts of it could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/DgVpK6r7JT4.wav"} +{"id": "DgqPgNqW2hE", "caption": "A female singer sings this beautiful vintage French melody. The song is medium tempo with a steady drum rhythm, steady bass line, piano accompaniment , string section harmony and some lush snare play. The song is romantic and cheerful with an avant-garde nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/DgqPgNqW2hE.wav"} +{"id": "DhnNZn8JjEQ", "caption": "This song is an instrumental. The tempo is medium with simple keyboard harmony, melodious guitar rhythm with the sound of a bell, waves and fingers snapping which could be a friction of fingers against the strings.The song is soft, melodic, pleasant, simple, calming and peaceful.", "audio": "/zhanghaomin/datas/musiccap/music_data/DhnNZn8JjEQ.wav"} +{"id": "Di7Rs4QmYKI", "caption": "This is a classical music piece that resembles the style of a march. It is an instrumental piece performed by a brass orchestra. The main theme is being played by the trombones while a bass line is played by the tuba. The tempo of the piece is slow and this creates an epic but solemn atmosphere. This piece would work perfectly as a movie music piece. It could be playing during the scenes of an important character dying.", "audio": "/zhanghaomin/datas/musiccap/music_data/Di7Rs4QmYKI.wav"} +{"id": "Dk7ziLlNfeM", "caption": "The song is an instrumental. The song is slow tempo with a keyboard harmony, grunge tone, guitar playing lead , screaming vocals and no percussion. The song is psychedelic and very sci-fi like in nature. The song audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/Dk7ziLlNfeM.wav"} +{"id": "DkZ1Or_D-g8", "caption": "This audio contains someone creating sounds with a theremin. This is not a musical composition. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/DkZ1Or_D-g8.wav"} +{"id": "DlU56FGTVEk", "caption": "The low quality record features a blues song played on some device and it features brass melody, electric guitar solo melody, energetic drums, smooth bass and passionate male vocal singing over it. It sounds crushed, distorted and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/DlU56FGTVEk.wav"} +{"id": "DlVgHV1UobM", "caption": "The low quality recording features a dubstep song that consists of manic laughing sound effects, man yelling sound effects, punchy snare and kick hits, shimmering hi hats, hard synth bass, aggressive synth lead melody and energetic crash cymbals. The mix of the song is not very good, thus the quality of the recording is lower - although it sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/DlVgHV1UobM.wav"} +{"id": "DpAfyjjQJyk", "caption": "This is a movie music piece. Elements with sharp characters in varying ranges such as strings, cinematic synth and synth bass have been used to create a feeling of dread and hopelessness. The electronic drums have been used for crash hits to put emphasis points. There are also other unnerving sound effects. The atmosphere of the piece is ominous. It could be used in the soundtrack of a horror movie or a horror video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/DpAfyjjQJyk.wav"} +{"id": "DpS_TigOHWo", "caption": "This is the recording of a gear showcase jam. The only instrument being played is an electric guitar. There is a solo being played while a reverb effect pedal is in use. The atmosphere is easygoing and the tunes are simple. Parts of this piece could be used as samples for beat-making. These samples could also work well for advertisement jingles.", "audio": "/zhanghaomin/datas/musiccap/music_data/DpS_TigOHWo.wav"} +{"id": "Dr4Ijx7Q9jk", "caption": "This is amateur low quality audio. A violin plays sets of two notes. A continuous percussion is played which drowns out the other instruments. The tempo is moderate.", "audio": "/zhanghaomin/datas/musiccap/music_data/Dr4Ijx7Q9jk.wav"} +{"id": "DroAzooK4yw", "caption": "Someone is playing acoustic guitar. While a higher pitched male voice is singing a sad song. This is an amateur recording. This song may be playing at home on a rainy day.", "audio": "/zhanghaomin/datas/musiccap/music_data/DroAzooK4yw.wav"} +{"id": "DsAp3b1poeA", "caption": "This clip features game sounds. The main melody is played using bells There is the sound of brass instruments playing a swell toward the end. There is the sound of jumping. The sound of a large percussion is played in the background. There are no voices in this clip. There are quirky sounds played in this clip which are not immediately identifiable. The quality of this recording is low.", "audio": "/zhanghaomin/datas/musiccap/music_data/DsAp3b1poeA.wav"} +{"id": "Du3Q6NdsSso", "caption": "The low quality recording features a cover that consists of a muffled tuba melody. The recording is very noisy, in mono - as it was probably recorded with a phone, but it sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/Du3Q6NdsSso.wav"} +{"id": "DueNcVFHI0k", "caption": "This amateur recording clip features a snare drum playing a continuous roll. It is like a marching beat. It sounds like a roll made before an important announcement in a kingdom. This is an instrumental clip. There are no voices in this clip. There are no other instruments in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/DueNcVFHI0k.wav"} +{"id": "Dv21JlCT4_k", "caption": "This is a Gregorian chant performed at a Christian Orthodox church setting. There is a female vocalist singing in the lead while a choir is singing in a hum-like manner at low-to-medium pitch. The atmosphere is religious and the character of the song is solemn. This piece can be used in the background at Orthodox religious events. It could also be playing in tragedy/aftermath of battle scenes in historical drama movies or TV shows with a Balkan/Eastern European setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Dv21JlCT4_k.wav"} +{"id": "DvN5813H7Bo", "caption": "This is a reggae music piece. There is a male vocalist singing in a laid-back manner. The keyboard is playing the main tune. The electric guitar is being strummed in a staccato off-beat pattern. There is a groovy bass line being played by the bass guitar. The rhythmic background consists of a reggae acoustic drum beat. The atmosphere is chill and trippy. This piece could be used in the soundtrack of a romance movie with a tropical setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/DvN5813H7Bo.wav"} +{"id": "DvOA0K-DIFM", "caption": "This is an amateur jam video of an electric guitar solo. The player uses the flanger pedal to achieve the effect of two tape recordings playing at the same time, one slower than the other. This piece could be used as a sample for a beat with a trippy feel.", "audio": "/zhanghaomin/datas/musiccap/music_data/DvOA0K-DIFM.wav"} +{"id": "Dx58W7opw5A", "caption": "This song features a song being played on a didgeridoo. This features a droning sound. A shaker is played through the song and is doubled in tempo at the end of the song. An acoustic guitar strums chords. This song can be played at a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/Dx58W7opw5A.wav"} +{"id": "DyPmDDN8m78", "caption": "The song is an instrumental. The song is medium tempo with keyboard harmony, string section harmony, piano playing melody and a poignant new age influence to the music. The song is emotional and ethereal in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/DyPmDDN8m78.wav"} +{"id": "DysXetu2I0E", "caption": "An acoustic drum is playing a hiphop/funk groove along with a bassline. One e-guitar is strumming a funk chord while the other guitar is playing a melody sequence and then the other guitar responds with a chord. The male voice sings in the mid to high range and at the end of the song a keyboard is playing a chord with a string sound. This song may be playing at home cleaning the house.", "audio": "/zhanghaomin/datas/musiccap/music_data/DysXetu2I0E.wav"} +{"id": "E16FgDFQI_w", "caption": "A female vocalist sings this groovy pop song. The tempo is fast with accordion harmony, funky bass lines, punchy drumming and keyboard accompaniment. The song is youthful, infectious, catchy, bouncy, nifty and groovy with a dance rhythm. This song is Modern pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/E16FgDFQI_w.wav"} +{"id": "E29kpquu8W4", "caption": "The Drum & Bass song features a mellow electric guitar melody, synth pad chord, long crash cymbal, buzzy synth lead melody and distant, fading out drums playing in the background. It is very reverberant, thus the song has a spacey vibe. It sounds relaxing and calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/E29kpquu8W4.wav"} +{"id": "E2gstPe3Im4", "caption": "This music is instrumental. The tempo is slow with a steady, droning keyboard harmony and synthesiser arrangements to create sounds like howling wind, door thudding and a rhythmic male vocal riff. The music is serious, suspenseful, grim, spooky, sinister, chilling ,anticipatory and terrifying. This music is Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/E2gstPe3Im4.wav"} +{"id": "E2v025Ilsqo", "caption": "This Indian folk song features a male voice singing the main melody. This is accompanied by tablas playing the percussion. A flute and another wind instrument voice are played on a synthesizer. The synth repeats the melody which is sung by the voice. A tambourine plays on every count of each bar. This folk song can be played in a village scene in an Indian movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/E2v025Ilsqo.wav"} +{"id": "E3F9bzeCgTQ", "caption": "The song is an instrumental. The song is fast tempo with soloists playing an enthusiastic guitar strumming and harmony. The song is energetic and entertaining. The audio is poor and the song is played in front of a live audience that is cheering and hooting in approval.", "audio": "/zhanghaomin/datas/musiccap/music_data/E3F9bzeCgTQ.wav"} +{"id": "E3iPiZlT6f8", "caption": "The song features a steelpan that creates the main melody. The sounds are bright and have a positive atmosphere. The track fits the afrobeat genre. In the background there are drums that play a mix between hip-hop and afrobeat patterns. A percussion synth creates a counter melody that contrasts the whole instrumental. This is a song you would play at a beach party in the caribbean at night.", "audio": "/zhanghaomin/datas/musiccap/music_data/E3iPiZlT6f8.wav"} +{"id": "E4To9BC2jx8", "caption": "This is a folk rock song with a strong Irish influence. We hear a typical Irish fiddle tune played on the violin - as the leading melodic motif for the instruments. The singer has a burly rock and roll voice and the song just has a general feel-good aura to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/E4To9BC2jx8.wav"} +{"id": "E4a3s8NRqUM", "caption": "This music is instrumental. The tempo is fast with a rapid electronic harmony and vigorous digital drum rhythm in the background with turntable arrangement. The harmony is syncopated, repetitive, insistent, psychedelic, trance, trippy and groovy. It is energetic, youthful, contemporary, groovy, vigorous and animated.", "audio": "/zhanghaomin/datas/musiccap/music_data/E4a3s8NRqUM.wav"} +{"id": "E6B81rrUlnE", "caption": "The low quality recording features a swinging and resonating sound. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/E6B81rrUlnE.wav"} +{"id": "E6JR3htwgyE", "caption": "The song is instrumental. The song is medium with a bell ringing with echoes in the room. There is no other instrumentation. The song is healing and relaxing in nature. The audio quality is bad with ambient room noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/E6JR3htwgyE.wav"} +{"id": "E7D42u8a5gc", "caption": "An acoustic drum is playing with crash hits along with a distorted e-guitar and an e-bass playing along before breaking into the next part. The male voice is screaming in a high pitch. This song may be playing live at a Rock&Roll festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/E7D42u8a5gc.wav"} +{"id": "E7q_QwLYI8U", "caption": "The low quality recording features a country song played on acoustic guitar. The chords are sliding and the recording is noisy and it sounds like a player is practicing. At the very end of the loop, there is a short snippet of percussive instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/E7q_QwLYI8U.wav"} +{"id": "EBpa2CADNJA", "caption": "This is a live recording of a blues piece being played by a guitarist. The audio recording is vintage and the quality could be improved. The guitarist plays an intricate finger picked piece with slides embedded between the plucked notes.", "audio": "/zhanghaomin/datas/musiccap/music_data/EBpa2CADNJA.wav"} +{"id": "EC4GbkL3XvI", "caption": "This is an intricately played piece on the electric guitar, there is a high level of reverb applied to the guitar. There's also one singular sustained note underneath the complex guitar lick being played.", "audio": "/zhanghaomin/datas/musiccap/music_data/EC4GbkL3XvI.wav"} +{"id": "ECP7EJka6N8", "caption": "This is a classical music piece played on the viola da gamba and the harpsichord. The performance is live, and the song has a refreshing, light and fun \"Spring\" feel to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/ECP7EJka6N8.wav"} +{"id": "EC_JNTVDrok", "caption": "This is a funk piece. It has an electronic drum beat with heavy use of claps in the rhythmic background. A synth with an organ sound is playing the melody, but it is filled with effects, so the sound is constantly changing. A fuzzy sounding bass is playing a funky groove in the background. There is an eccentric atmosphere. This piece could be used in the soundtracks of young-adult cartoons.", "audio": "/zhanghaomin/datas/musiccap/music_data/EC_JNTVDrok.wav"} +{"id": "EFlGHxV5WsY", "caption": "Heavily effected, instrumental psychedelic rock music featuring phaser effects, strummed acoustic guitars, and bass guitar played in a compound meter. The feeling is airy.", "audio": "/zhanghaomin/datas/musiccap/music_data/EFlGHxV5WsY.wav"} +{"id": "EGIeykrN4eg", "caption": "This song is vibrant, alive, exciting and fun. It features elements of inspiration from Latin and French music, as heard in the use of the flamenco guitar alongside the accordion.The song is suitable for dancing, and has a charming bounce to it. The initial part of the song builds up to the section that's most alive and layered.", "audio": "/zhanghaomin/datas/musiccap/music_data/EGIeykrN4eg.wav"} +{"id": "EHm7vLZewS0", "caption": "A female vocalist sings this melodic Soft Rock. The tempo is medium with intense electric guitar harmony, keyboard accompaniment, synthesiser arrangements, steady drumming and subtle bass. The vocals are soft and melodic . The song is passionate, emotional, euphonious, simple, fresh and pleasant. This song is contemporary soft rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/EHm7vLZewS0.wav"} +{"id": "EIzBD62ja8E", "caption": "This song features a guitar being played to a flamenco melody. Fingerstyle guitar is used. The song starts off at a higher register and ends at the lower register. The guitar is strummed at intervals. There are no other instruments in this song. There are no voices in this instrumental song. This song has a romantic mood. This song can be played at a quiet restaurant overlooking the sunset.", "audio": "/zhanghaomin/datas/musiccap/music_data/EIzBD62ja8E.wav"} +{"id": "EJMUwh1vY2s", "caption": "The low quality recording features a flat male vocal singing over muffled acoustic rhythm guitar. The recording is very noisy, it sounds uptempo and like it is recorded via phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/EJMUwh1vY2s.wav"} +{"id": "EKZvq0dUk50", "caption": "Drums and percussion are playing a groove that animates to dance along with a bassline. In the background you can hear a clean e-guitar strumming chords. A male voice is singing in a higher register and an accordion ends the phrase with a short and fast melody. This song may be playing at a kids party.", "audio": "/zhanghaomin/datas/musiccap/music_data/EKZvq0dUk50.wav"} +{"id": "EKt_KEbqQfQ", "caption": "The song is an instrumental. The tempo is slow with a steady drum rhythm, various percussion hits and shakers playing percussively. The song is groovy and muted in the harmony section. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/EKt_KEbqQfQ.wav"} +{"id": "EL2DtgPD4J4", "caption": "This song is full of electronic, percussive noises and effects. A kick is playing on every beat with some sharp hits. A bass is playing along with the kick. Male voice samples with delay can be heart to spice up the mix. This song may be playing at a rave in the woods.", "audio": "/zhanghaomin/datas/musiccap/music_data/EL2DtgPD4J4.wav"} +{"id": "ELhxZhWsGM8", "caption": "This music is instrumental. The tempo is fast with synthesiser articulation, electronic sound arrangements and vigorous digital drumming along with a catchy vocal riff. The music is youthful, futuristic, progressive, hypnotic, psychedelic and trance like. This music is contemporary Synth Pop/ Electro Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/ELhxZhWsGM8.wav"} +{"id": "EN_FOFkxAEw", "caption": "The low quality recording features an ambient song that consists of mellow wide bells and wide low synth pad playing in the background. It sounds calming, relaxing and hypnotic, like something you would hear in a hypnotic therapy session.", "audio": "/zhanghaomin/datas/musiccap/music_data/EN_FOFkxAEw.wav"} +{"id": "EO_tdzbN75Q", "caption": "This electronic beat contains digital drums playing a four on the floor groove with percussive elements panned to the left and right side of the speakers. A synthesizer pad is playing one, long and evolving note in the higher register. It sounds like a lot of reverb has been added. This song may be playing in a Minimal/Techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/EO_tdzbN75Q.wav"} +{"id": "EOaQnfDjVyo", "caption": "This is a live recording of a symphonic orchestra. The recording quality is good, and every section is clearly audible. The music creates excitement and a feeling of needing to hurriedly get somewhere.", "audio": "/zhanghaomin/datas/musiccap/music_data/EOaQnfDjVyo.wav"} +{"id": "EPjfqS5NvCY", "caption": "A male voice is speaking while someone is playing an e-guitar with a lot of reverb and a little delay running down the strings. This is an amateur recording. This may be playing while demonstrating someone your guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/EPjfqS5NvCY.wav"} +{"id": "EPvnkbo5wrI", "caption": "A male voice is screaming aggressively and loud while a acoustic drum set is playing a drum&bass groove along with a distorted e-guitar and bass playing the bassnotes along with the drums: Than the drums breaks into another part changing the beat along with the guitar and the bass while the male voice is screaming in a high frequency. The music sounds energetic and aggressive. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/EPvnkbo5wrI.wav"} +{"id": "EQHrQIaQNv8", "caption": "This file contains someone playing a slide guitar melody over a backing track. The backing-track contains an e-bass playing the footnote of an acoustic guitar strumming chords. You can hear a shaker serving as a rhythmic instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/EQHrQIaQNv8.wav"} +{"id": "EQSv7DIJJtw", "caption": "A female singer sings this cool pop melody. The song is medium with a steady drumming rhythm, percussive bass line, keyboard accompaniment and various percussion hits. The song is modern K-pop. The song is romantic and cheerful.", "audio": "/zhanghaomin/datas/musiccap/music_data/EQSv7DIJJtw.wav"} +{"id": "EQVZLtlDkHw", "caption": "The low quality recording features a lullaby sung by soft, passionate female vocals over a mellow, arpeggiated acoustic guitar melody. It sounds hypnotic, relaxing, calming and soft. It is in mono, so that is the only thing that could make this fall in the low quality category.", "audio": "/zhanghaomin/datas/musiccap/music_data/EQVZLtlDkHw.wav"} +{"id": "ER1fTL9-pQw", "caption": "A digital drum is playing a groove with triangle sounds and finger snapping. Two synth sounds are playing a catchy and simple lead melody in a higher key. A deep male voice is rapping/shouting along to a male backing voice. This song may be playing in a hiphop club.", "audio": "/zhanghaomin/datas/musiccap/music_data/ER1fTL9-pQw.wav"} +{"id": "ESFANzZTdYM", "caption": "This is a lullaby being sung by a comedian. The male vocalist is singing melodically. The main melody is being played by a piano while strings in the background are holding the root notes of the piece. An occasional xylophone riff can be heard adding texture in the high range. This piece has a gentle but comedic atmosphere.", "audio": "/zhanghaomin/datas/musiccap/music_data/ESFANzZTdYM.wav"} +{"id": "ESbtW0CUmp4", "caption": "This audio contains someone playing a gospel/jazz melody when a very loud drum comes in with a fill-in on the toms. This is an amateur recording and of poor audio-quality. This song may be playing in a gospel church.", "audio": "/zhanghaomin/datas/musiccap/music_data/ESbtW0CUmp4.wav"} +{"id": "ET6HVZ8muVE", "caption": "This country song features a male voice singing the main melody. This is accompanied by percussion playing a simple country beat in common time. A pedal steel guitar plays sliding notes as fills in between lines. The bass plays the root note and the lower fifth of the chords being played. The other instruments are not audible as the audio quality is low. This song can be played in a square dancing party.", "audio": "/zhanghaomin/datas/musiccap/music_data/ET6HVZ8muVE.wav"} +{"id": "ET7yQfaiF_8", "caption": "The low quality recording features a cover of a rock song and it consists of a passionate male vocal singing over an auto harp melody. It sounds passionate, emotional and mellow, despite the fact that the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ET7yQfaiF_8.wav"} +{"id": "ETl0hYRlVmg", "caption": "The low quality recording features a live performance of a jazz song and it features a passionate female vocal singing over shimmering hi hats, groovy piano chords and smooth double bass. The recording has some audio crackles and that would be the only reason for it to go under the \"low quality\" category. It sounds emotional, passionate and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ETl0hYRlVmg.wav"} +{"id": "EUNTykrvpok", "caption": "The low quality recording features a northern soul song that consists of flat male vocals, alongside melodic male background vocals, singing over funky guitar chords, groovy piano chords, groovy bass, \"4 on the floor\" kick pattern and shimmering open hats. It is noisy and in mono and therefore vintage, but it also sounds warm, nostalgic and sentimental.", "audio": "/zhanghaomin/datas/musiccap/music_data/EUNTykrvpok.wav"} +{"id": "EUmfsCvmkgo", "caption": "This is an advertisement jingle in the style of a kids song. It is in major key. There is a female vocalist singing in the lead while the sound of children talking can be heard every now and then. The bass guitar is playing a groovy tune. There are wind chimes that can be noticed. The rhythmic background consists of a simple acoustic drum beat. The atmosphere is cheerful but generic.", "audio": "/zhanghaomin/datas/musiccap/music_data/EUmfsCvmkgo.wav"} +{"id": "EXRKJRL0TDU", "caption": "The low quality recording features an alternative rock song that consists of crushed snare hits, punchy kick, shimmering hi hats, groovy bass guitar, widely spread electric rhythm guitar and wide mellow synth pad, followed by some squeaky sound effects. It sounds groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/EXRKJRL0TDU.wav"} +{"id": "EY8boPZ1hPs", "caption": "A male voice is talking in a typical advertisement manner. In the background you can hear a song containing a strummed acoustic guitar, a melody played with a xylophone and whistling in the same melody. An e-bass is underlining the song with a walking bassline. A kid's voice talks for a moment then the song stops as it comes to its end. This song may be playing in a happy advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/EY8boPZ1hPs.wav"} +{"id": "EZAwPnGOJPE", "caption": "The low quality recording features a Northern Soul song sung by passionate female vocalists and background harmonizing female vocals over punchy snare, groovy bass and sustained brass melody. It sounds upbeat, crushed, vintage, emotional and funky. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/EZAwPnGOJPE.wav"} +{"id": "EZJzzWEDtQo", "caption": "This audio contains someone playing a horn solo in a room full of reverb. This song may be playing in an orchestra.", "audio": "/zhanghaomin/datas/musiccap/music_data/EZJzzWEDtQo.wav"} +{"id": "EZb1wQsg6CU", "caption": "This bollywood song features a harmonica playing the main melody. The harmonica is played with a tremolo effect at the end of the lines. This is accompanied by a percussion playing a simple beat, A violin repeats the last part of the melody as played by the harmonica. The bass plays the root note of the chords. This is an amateur recording and the rest of the instruments are not clearly audible. This song can be played in a happy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/EZb1wQsg6CU.wav"} +{"id": "EZi80fUpBfE", "caption": "The low quality recording features a manically arpeggiated steel guitar. The recording is noisy and in mono, as it sounds like the player is practicing to execute the melody properly -probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/EZi80fUpBfE.wav"} +{"id": "E_34BmDVnOI", "caption": "The low quality recording features a wide filtered, reverberant laser synth, punchy kick layered with energetic crash cymbal and synth pad chord. It sounds suspenseful, intense and weird.", "audio": "/zhanghaomin/datas/musiccap/music_data/E_34BmDVnOI.wav"} +{"id": "E_IG2ubeTME", "caption": "This song contains a digital drum playing a dubstep groove with a morphing sub-bass sound that is being used as melody. This song may be playing loud with headphones while running.", "audio": "/zhanghaomin/datas/musiccap/music_data/E_IG2ubeTME.wav"} +{"id": "E_kgtQ93Q1s", "caption": "This is an instrumental version of a heavy metal piece. There is a distorted electric guitar and a bass guitar playing the main tune while another distorted electric guitar is playing a medium-to-high pitch solo. The acoustic drums are playing a medium tempo heavy metal beat. It is a hard-hitting piece. This piece can be used in the soundtrack of an action-filled video game. It could also be playing in the background of a rock/metal bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/E_kgtQ93Q1s.wav"} +{"id": "EaGhKzpkNso", "caption": "A male vocalist sings this simple, peppy melody. The tempo is fast with keyboard harmony, enthusiastic drumming, steady bass line, acoustic guitar rhythm and electronic arrangements. The song is fun, animated, upbeat, catchy, energetic, spirited and vibrant and appealing to children . This song is a Synth Pop/Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/EaGhKzpkNso.wav"} +{"id": "EayN_Jj0740", "caption": "The low quality recording features a classical song that consists of a sustained cello melody playing over sustained strings. It sounds emotional, passionate and the recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/EayN_Jj0740.wav"} +{"id": "EcEDVL6vn_w", "caption": "The low quality recording features an arpeggiated harp melody. The recording is noisy and it sounds mellow, soft and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/EcEDVL6vn_w.wav"} +{"id": "Ee6MP1bIRUA", "caption": "A sultry female singer croons over a mellow rock electronic drum beat, electric bass and two clean, picked electric guitars. Has an indie surf feel with a smooth synth pad underneath and lots of reverb.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ee6MP1bIRUA.wav"} +{"id": "EfUUgsioXyU", "caption": "A male vocalist sings this peppy pop.The tempo is fast with synthesiser articulation, groovy bass lines, bright digital drumming , keyboard harmony and electronic arrangements. The song is spirited, enthusiastic, energetic, lively, vibrant and youthful with a dance groove. The song is an Electro Pop/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/EfUUgsioXyU.wav"} +{"id": "EgwGYmAH0BA", "caption": "This song has an arpeggiated bassline that runs through a filter opening up. A drum groove that sounds acoustic is panned to the left side of the speaker with the snare being panned to the right. Atmospheric pad sounds, melodies are being played along with noise that reminds of wind. They are full of reverb and a ping pong panning effect. This song may be playing in a videogame completing a secret mission.", "audio": "/zhanghaomin/datas/musiccap/music_data/EgwGYmAH0BA.wav"} +{"id": "EhFWLbNBOxc", "caption": "This music is an instrumental. The tempo is slow with a rhythmic guitar riff. The music abruptly ends to disown sound of a keyboard. The music is soft, mellow and cheerful plucking. There seems to be no connection between the two instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/EhFWLbNBOxc.wav"} +{"id": "Ehks1uuwR3s", "caption": "Here we have a live recording of an artist playing on the bagpipes. He plays a piece that feels emotional and uplifting. This piece would be fitting on the battlefield to bring about conviction and courage. It is a Scottish instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ehks1uuwR3s.wav"} +{"id": "EieK70X8lnw", "caption": "Someone is playing a complex groove on the drums playing along to digital strings playing in a minor key. A very low sounding e-bass is playing a bassline. Panned to the right side of the speakers you can hear a synth lead sound playing a melody in the mid-range. This song may be playing live on a drum off show.", "audio": "/zhanghaomin/datas/musiccap/music_data/EieK70X8lnw.wav"} +{"id": "EijTwCm-pRM", "caption": "A group of male vocalists sing this popular Christmas song. The song is medium tempo with vocalisation by the vocalists to a keyboard accompaniment. The song is funny, animated, cheerful, playful, animated,jolly and high-spirited.", "audio": "/zhanghaomin/datas/musiccap/music_data/EijTwCm-pRM.wav"} +{"id": "EkMgPJfSL04", "caption": "This audio contains someone playing a piece of music on a harp. The piece sounds dreamy and peaceful. There is some reverb from the room in the recording. This song may be playing for a soft indie-video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/EkMgPJfSL04.wav"} +{"id": "EkmHGd0U8yE", "caption": "This music is instrumental. The tempo is slow with a melancholic cello harmony, and a piano and violin accompaniment. The music is soft, pensive, melancholic, sentimental, sad, reflective, meditative and delicate. This music is a Violin Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/EkmHGd0U8yE.wav"} +{"id": "Ekoh6TJpA88", "caption": "Female singers sing this Christmas carol in vocal harmony. The song is medium tempo with bells percussions, keyboard accompaniment, steady drumming rhythm and a percussive bass line. The song is a Christmas carol that doubles as a lullaby. The song is cheerful and festive.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ekoh6TJpA88.wav"} +{"id": "EmSZKb0LdVM", "caption": "The low quality recording features an electro house song that consists of punchy \"4 on the floor\" kick pattern, claps, funky electric guitar melody, groovy synth keys, groovy bass that glues everything together and shimmering shakers. It sounds a bit muddy, but also energetic, fun and exciting - like something you would hear in clubs during 70s and 80s a lot.", "audio": "/zhanghaomin/datas/musiccap/music_data/EmSZKb0LdVM.wav"} +{"id": "Emc18GpAeRY", "caption": "A male vocalist sings this traditional Carnatic vocals. The song is medium tempo with a violin accompaniment, tabla and mridangam playing percussion. The song is energetic and passionate and highlights the traditional Carnatic music art form. The audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/Emc18GpAeRY.wav"} +{"id": "EnJ8zV3vaJA", "caption": "This audio contains a saxophone player playing along to a high beeping tone that seems not to be part of the music. In the background you can hear people laughing. THis song may be playing live at a jazz performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/EnJ8zV3vaJA.wav"} +{"id": "EnewI6fNhVA", "caption": "This music is an instrumental.the tempo is fast with a harmonium melody and tabla accompaniment. The performance is live with ambient sounds of people talking, sound of glass bangles and a woman\u2019s voice. This music is Indian Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/EnewI6fNhVA.wav"} +{"id": "EoZH1gyRlr4", "caption": "This classical song features a harpsichord. An ascending pattern is played on the instrument. There are no other instruments in this song. There are no voices in this song. This song can be played when aristocracy is introduced to the public.", "audio": "/zhanghaomin/datas/musiccap/music_data/EoZH1gyRlr4.wav"} +{"id": "Eop_sG9FVgA", "caption": "A female vocalist sings this enigmatic electro pop. The tempo is medium with synthesiser arrangements and electronic music layers. The vocals are monotone, incessant and droning like the music and have a hypnotic, trance like vibe. The song is youthful, ambient, enigmatic and meditative.", "audio": "/zhanghaomin/datas/musiccap/music_data/Eop_sG9FVgA.wav"} +{"id": "EptdhC17avY", "caption": "This is a compilation of various flamenco recordings. The acoustic guitar is being played at first with the picado technique and then with the free stroke technique. There is a percussive backing track in each part. The music has an exotic feel to it. These separate parts could be used as an advertisement jingle or they could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/EptdhC17avY.wav"} +{"id": "EremEyLrdUY", "caption": "modern folk rock or indie with fingerstyle acoustic guitar and smooth male vocals. The vocal production is loud. Drums are present with the ride cymbal playing a steady pattern and the snare being played with brushes. The mood is mellow.", "audio": "/zhanghaomin/datas/musiccap/music_data/EremEyLrdUY.wav"} +{"id": "Es9FNjZ-SHI", "caption": "A male voice is singing/yodeling along to an accordion playing a melody and chords while an upright bass is playing a simple line along with a minimal drum playing along. In the background the crowd is clapping along to the beat. This song may be playing at a folk fest.", "audio": "/zhanghaomin/datas/musiccap/music_data/Es9FNjZ-SHI.wav"} +{"id": "EsHXnkZ_W2c", "caption": "The low quality recording features a Chicago house song that consists of a punchy \"4 on the floor\" kick pattern, some snare rolls, syncopated claps, shimmering hi hats, low echoing vocals, echoing toms and high pitched male vocals one shot. It sounds chaotic and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/EsHXnkZ_W2c.wav"} +{"id": "EsssGCL-Axw", "caption": "The low quality recording features a live performance of a rock song that contains harmonizing background vocals, alongside passionate female vocals, singing over wide electric guitar melody, punchy snare, groovy bass, punchy kick and shimmering hi hats and crash cymbals. It sounds emotional, passionate and addictive - thanks to that cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/EsssGCL-Axw.wav"} +{"id": "EtmKuWPpjG0", "caption": "This pop song features a female voice singing the main melody. This is accompanied by male and female backing voices. The voices sing a repetitive melody. This is accompanied by percussion playing a simple beat. Trumpets play a backing melody. The bass plays a groovy descending bassline. The mood of this song is happy. This song can be played at a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/EtmKuWPpjG0.wav"} +{"id": "Euu6zlJQSD0", "caption": "This is a dancehall music piece. There is a male vocalist singing with a Jamaican accent. An electric guitar and a bass guitar are playing the melody in the background while occasional keyboard notes can be heard. The rhythmic background is provided by the mild tempo basic 4/4 played on the acoustic drums. There is an echo delay effect on the snare drum every now and then. The atmosphere of the piece is chill and groovy. This piece could be playing through loudspeakers at a beach. It could also suit well at a summer barbecue party.", "audio": "/zhanghaomin/datas/musiccap/music_data/Euu6zlJQSD0.wav"} +{"id": "EwDiNj_5PEg", "caption": "This Indian instrumental song features the main melody being played on a bowed instrument called the dilruba. This starts off by going to a higher note and then playing a descending lick. This is accompanied by a santoor playing an ascending lick. There is no percussion in this song. There are no voices in this song. This song can be played in a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/EwDiNj_5PEg.wav"} +{"id": "EwoCbcSXlSM", "caption": "A male vocalist sings this soft Christian Worship song. The tempo is medium with a keyboard accompaniment, steady drumming, flute melody, subtle bass line; rhythmic acoustic guitar and soft vocals. The song is a melodious, soothing, prayerful, calm ,contemporary Christian Praise and Worship song.", "audio": "/zhanghaomin/datas/musiccap/music_data/EwoCbcSXlSM.wav"} +{"id": "Ex0ukzO5z9M", "caption": "The low quality recording features a reggae song that consists of passionate male vocal singing over groovy bass, simple hi hats and punchy snare. There are some loud stuttering low frequency audio crackly noises in the recording, which makes it a bit uncomfortable to listen. It sounds groovy and chill regardless.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ex0ukzO5z9M.wav"} +{"id": "Ex18Xwznj60", "caption": "The low quality recording features a live performance of a punk song that consists of screaming female vocal singing over a muffled instrumental. It sounds energetic, harsh, crushed, loud and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ex18Xwznj60.wav"} +{"id": "ExghbCGRBx0", "caption": "This is a bluegrass music piece performance. Iconic to the American folk songs, it involves a rapidly played banjo solo. The atmosphere of the piece is cozy and positive. This piece could be used in rural social media content or in a comedy show taking place in rural USA.", "audio": "/zhanghaomin/datas/musiccap/music_data/ExghbCGRBx0.wav"} +{"id": "EyO5vB4eqo0", "caption": "This music is instrumental. The tempo is slow with atmospheric keyboard, melodic piano, amplified organ and sound of rain falling and water flowing. The music is peaceful, soothing, meditative, ethereal, pensive,reflective, celestial and calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/EyO5vB4eqo0.wav"} +{"id": "EzP7PB2x670", "caption": "The low quality recording features a hip hop song being scratched by the DJ. The song features a filtered flat male vocal, punchy snare, bouncy kick, widely spread shimmering cymbals, groovy bass and arpeggiated electric guitar melody. It sounds bouncy and groovy, as the DJ is probably practicing his scratching skills.", "audio": "/zhanghaomin/datas/musiccap/music_data/EzP7PB2x670.wav"} +{"id": "Ezodz2aZnzQ", "caption": "The low quality recording features a mellow keys melody and breathy flute melody being played. It sounds sad, passionate and emotional. The recording is noisy and in mono as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ezodz2aZnzQ.wav"} +{"id": "F1X7egd8Us0", "caption": "This blues guitar song features a resonator guitar. Fingerstyle guitar is being played. The melody is a blues style guitar. There are no other instruments in this song. There are no voices in this song. This song can be played in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/F1X7egd8Us0.wav"} +{"id": "F1uXNtotVsg", "caption": "This is an instrumental jam piece. The only instrument is an acoustic guitar which is being played with a percussive slap technique. The track is groovy. This piece could fit perfectly as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/F1uXNtotVsg.wav"} +{"id": "F2ekiX14ID4", "caption": "The low quality recording features a cello solo melody played over mellow piano chords. It sounds passionate and emotional. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/F2ekiX14ID4.wav"} +{"id": "F3uf_RleI3E", "caption": "Male singer sings this cool Latin melody. The song is medium tempo with various Latin percussion instruments and a brass band playing percussively in harmony. The song is energetic and has a cool dance rhythm. The audio quality of the song is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/F3uf_RleI3E.wav"} +{"id": "F5e-SEICJP4", "caption": "The music features for the most part an instrumental but almost at the end of the excerpt a male voice starts to yodel. Up to that point the melody is being played by a marimba, then trumpets and horns, possibly trombones too. A tuba is holding the beat pulsation in the low register. At the end of the excerpt a harp can be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/F5e-SEICJP4.wav"} +{"id": "F5xnAYHuGlo", "caption": "This salsa song features a male voice. It starts off with the keyboard and bass playing a synchronized melody. The percussion is played only as a rimshot in a grouping of two strokes followed by a group of three strokes. This is followed by a male voice singing one word. The rest of the instruments start playing at a faster tempo. The main melody of the song is played on the trumpet and saxophone. This is accompanied by percussion playing a salsa beat. A keyboard plays chords with a salsa feel. This song can be played at a dance party.", "audio": "/zhanghaomin/datas/musiccap/music_data/F5xnAYHuGlo.wav"} +{"id": "F5zDEHggiMg", "caption": "We hear a viola and harpsichord being played, with the overall emotion of the piece being thrilling and suspenseful. A high tremolo is played on the violin, which creates the feeling of an energy build-up. This is a classical style piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/F5zDEHggiMg.wav"} +{"id": "F7JllgnefSI", "caption": "The low quality recording features a rock song that consists of throaty male vocal singing over widely spread arpeggiated electric guitar melody, smooth bass guitar, punchy snare, shimmering hi hats and soft kick hits. It sounds thin, distorted and messy, since the frequencies are clashing.", "audio": "/zhanghaomin/datas/musiccap/music_data/F7JllgnefSI.wav"} +{"id": "F7Y1T-rQ2JU", "caption": "This is an educational recording. There is a male voice speaking in an instructive manner regarding numerous singing bowls in different shapes and sizes. The player hits each singing bowl while describing their feelings. The sound of the bowls could be isolated from the voice for meditation music.", "audio": "/zhanghaomin/datas/musiccap/music_data/F7Y1T-rQ2JU.wav"} +{"id": "F8MCOgWhgvY", "caption": "The Drum & Bass song features a shimmering hi hats, punchy snare and kick hits, manic repetitive synth lead melody and synth pad swell. It sounds energetic, aggressive and upbeat - like something you would hear in clubs during the 00s.", "audio": "/zhanghaomin/datas/musiccap/music_data/F8MCOgWhgvY.wav"} +{"id": "F8wGRd9332s", "caption": "Someone is strumming chords on a guitar while someone else is playing a melody using a harmonica. This song sounds like sitting around a bonfire.", "audio": "/zhanghaomin/datas/musiccap/music_data/F8wGRd9332s.wav"} +{"id": "F9LJIyqQFe8", "caption": "This audio contains marching drums with a kick and snare rolls. A brass section starts to play a melody in the low to mid range up to the higher register. In the background you can hear a strong wind that seems not to be part of the song. This song may be playing in a pirate movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/F9LJIyqQFe8.wav"} +{"id": "FAhfuP_xh5Y", "caption": "This music is an energetic instrumental. The tempo is fast with a regional string instrument playing the lead with hand percussion like a small hand drum, tambourine and shaker beats. The music is lively, cheerful, happy, youthful, buoyant, enthusiastic, sunny and celebratory with a peppy dance groove. This music is Folk dance music.", "audio": "/zhanghaomin/datas/musiccap/music_data/FAhfuP_xh5Y.wav"} +{"id": "FBXBDe3OU5s", "caption": "This is a recording of the steel pan tuning process. The performer repeatedly hits different parts of the steel pan to check if the tuning is correct. The instrument gives off a tropical sound. There is an irritating crackle sound coming from the recording. If it were not for this noise, the piece could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/FBXBDe3OU5s.wav"} +{"id": "FCvs17jk10A", "caption": "This is a drum cover of a hard rock/alternative metal music piece. There is a male vocalist singing melodically in the lead. The main tune is being played by the distorted electric guitar. There is a bass guitar playing in the background. The rhythmic background consists of a simple but loud rock acoustic drum beat. The atmosphere is aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/FCvs17jk10A.wav"} +{"id": "FCzMqo8kh1o", "caption": "A male singer sings this passionate melody. The song is medium tempo with guitar strumming rhythm, steady drumming rhythm, keyboard accompaniment and a percussive bass line. The song is romantic with a cool dance groove. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/FCzMqo8kh1o.wav"} +{"id": "FDO5BekX478", "caption": "A male vocalist sings this high spirited Portugal song. The tempo is fast with keyboard harmony, punchy drumming, groovy bass lines, animated trumpets, backed with harmonica, party whistles, lively vocalisation and vocal backup, tambourine beats and congas. This song is a sonic treat with a plethora of instruments in perfect sync and harmony. It is happy, joyful and merry with a dance groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/FDO5BekX478.wav"} +{"id": "FDYIdBZUl2Y", "caption": "A synthbass is playing a soft line along with a piano playing a melody while a noise riser sound is slowly rising up creating tension. The female voice sings a melody on top of that. This song may be playing while running with headphones.", "audio": "/zhanghaomin/datas/musiccap/music_data/FDYIdBZUl2Y.wav"} +{"id": "FE2kALvHjEU", "caption": "The low quality recording features an old video game song that consists of sustained synth strings melody, mellow percussions, groovy, thin bass and synth pad chords. The recording is very noisy and the stereo image is unbalanced as it is leaning towards the left channel. It sounds a bit glitchy and slightly detuned too.", "audio": "/zhanghaomin/datas/musiccap/music_data/FE2kALvHjEU.wav"} +{"id": "FENJIDecy5s", "caption": "This song has a catchy synthesizer bassline that is repeating. The electronic drums are playing a four on the floor techno groove with some tambourines and some processed crash sounds. The elements are gently panned to the left and right side of the speakers. The male voice is rapping over the instrumental while a low pitched vocal sample melody is singing a melody and some pieces of that are also panned to the left and right side of the speakers along with some reverb and light delay. This song may be playing in a club or a beach party.", "audio": "/zhanghaomin/datas/musiccap/music_data/FENJIDecy5s.wav"} +{"id": "FEuXIeWoCQQ", "caption": "The low quality recording features a live performance of an urban latin song that consists of flat male vocal singing over groovy piano melody, groovy bass guitar, wooden percussive elements, wide toms, warm brass melody and widely spread claps. There is a short, exciting background male vocal in the middle of the loop. It sounds exotic, groovy and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/FEuXIeWoCQQ.wav"} +{"id": "FF0VaBxb27w", "caption": "A male vocalist sings this animated song. The tempo is medium with vocal emphasis, a bright ukelele harmony, groovy bass guitar, rhythmic acoustic guitar and piano accompaniment. The song is emphatic, passionate, jealous, emotional, sentimental and story telling. The song has an orchestral vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/FF0VaBxb27w.wav"} +{"id": "FFQVVwFjy7s", "caption": "This is a drum & bass electronic music piece. There is no singer. There is a strong and fuzzy feeling bass sound. The rhythmic background consists of a loud and high tempo electronic drum beat. The atmosphere is modern and energetic. This piece could be playing at a nightclub or a dance club.", "audio": "/zhanghaomin/datas/musiccap/music_data/FFQVVwFjy7s.wav"} +{"id": "FGZ0sLt4dXA", "caption": "A female singer sings this spirited song. The tempo is fast with a lively piano accompaniment, punchy drumming, funky bass line, rhythmic acoustic guitar, and a droning synthesiser harmony. The music is loud, busy, chaotic and bustling and the vocals are subdued. This clip sounds like the song climax as the instrumentation is strong and powerful. The song is spirited, melodic,energetic, enthusiastic, youthful and engaging. This song is an Indie Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/FGZ0sLt4dXA.wav"} +{"id": "FGoDfNZezh0", "caption": "A female vocalist sings this soft love song in a foreign language. The tempo is medium with a mellifluous violin harmony, keyboard accompaniment, subtle bass, steady drumming and rhythmic acoustic guitar. The song is sweet, youthful, simple, romantic, sentimental, melancholic and pensive. This song is Romantic Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/FGoDfNZezh0.wav"} +{"id": "FHC7gN3NnX8", "caption": "The low quality recording features a cover of a rock song sung by harmonizing female choir vocals. The recording is noisy, in mono and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/FHC7gN3NnX8.wav"} +{"id": "FI_Dl0Cmd38", "caption": "The low quality recording features a suspenseful synth pad playing in the background and echoing breathy flute melody playing over it. It sounds intense, mellow and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/FI_Dl0Cmd38.wav"} +{"id": "FKBryvLMTY4", "caption": "The low quality recording features a traditional song that consists of a flat male vocal, alongside monotone female vocal, singing over sustained strings melody, wooden percussion, shimmering shakers and some claps. It sounds passionate and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/FKBryvLMTY4.wav"} +{"id": "FKChZXXhufE", "caption": "The instrumental music features a harp playing a combination of melody and accompaniment. In the background one can hear a synth pad providing harmony throughout the music excerpt. The message of the song seems romantic and the atmosphere is calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/FKChZXXhufE.wav"} +{"id": "FLFmcZiRuzU", "caption": "This is a gear showcase jam recording. The only instrument being played is an electric guitar with heavy distortion. There is a hard-hitting guitar solo. The sound is crunchy. There is a raw atmosphere to this recording. This piece could be used in advertisements as a jingle. It could also be sampled to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/FLFmcZiRuzU.wav"} +{"id": "FLJPxFCPeDY", "caption": "The low quality recording features an accordion melody played over regional Mexican playback that consists of accordion chords, groovy bass and flat male vocal singing over it. The recording is in mono, noisy and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/FLJPxFCPeDY.wav"} +{"id": "FMjUGdTn7lU", "caption": "This audio contains someone playing a fast paced piece with a fast left hand and a slower melody in the right hand playing in the midrange. Someone starts playing an accordion alone. This song may be playing live jamming with your friend.", "audio": "/zhanghaomin/datas/musiccap/music_data/FMjUGdTn7lU.wav"} +{"id": "FMr1WHtXJbc", "caption": "The low quality recording features an arpeggiated steel acoustic guitar playing alongside acoustic rhythm guitar chord progression. The recording is noisy and in mono and it sounds like a cartoon song.", "audio": "/zhanghaomin/datas/musiccap/music_data/FMr1WHtXJbc.wav"} +{"id": "FNnKFUkFJ5M", "caption": "This blues song features a solo played on a harmonica. It starts off with the harmonica playing three descending notes. This is followed by the same three notes but the first note is played twice followed by the remaining two notes. This is accompanied by a guitar playing a rock and roll strumming pattern. The bass plays the root note of the chord. A piano plays in the background. There are no voices in this song. This song can be played in a bar scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/FNnKFUkFJ5M.wav"} +{"id": "FRZzUh9hcTo", "caption": "A male vocalist sings this quirky Rock melody. The tempo is medium fast with groovy electric guitar harmony, funky, intense bass lines, infectious drumming, keyboard accompaniment and vocal backup. The song is catchy, rhythmic, emotional, incessant, sentimental, melancholic, lonely, romantic , unconventional, quirky and upbeat. This song is classic rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/FRZzUh9hcTo.wav"} +{"id": "FSQ3E4XbpPU", "caption": "This audio clip features sounds of whales. A synth plays fills in the background. There are no voices and no percussion. This clip can be used in a dreamy movie sequence.", "audio": "/zhanghaomin/datas/musiccap/music_data/FSQ3E4XbpPU.wav"} +{"id": "FTdcanPJw6E", "caption": "This is a folk metal/Celtic metal music piece. There is a male vocalist singing in the lead using the brutal vocal technique. The electric guitar is playing the main tune with a keyboard and a bass guitar backing it. The rhythm is being played by the acoustic drums at a slightly fast tempo. The atmosphere is loud and aggressive. This piece could be used in the soundtrack of a Celtic historical drama movie during scenes of battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/FTdcanPJw6E.wav"} +{"id": "FXQxobF8FWw", "caption": "This is an instrumental progressive rock piece. There is an electric guitar playing an arpeggio in the melodic background while another is playing a solo as the lead. A simple 4/4 rock beat is with electronic drum sounds. The atmosphere has a trippy, psychedelic feeling to it. This piece could be used in the trip/nightmare sequences of retro themed horror movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/FXQxobF8FWw.wav"} +{"id": "FXVu-YwjhxM", "caption": "A male singer sings this cool melody. The song is medium tempo with a groovy guitar lead and steady drumming with tambourine percussion. The song is cool and sophisticated. The audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/FXVu-YwjhxM.wav"} +{"id": "FY8bZRm_QiE", "caption": "This song contains acoustic drums playing kind of a slow drum&bass rhythm along with a bass playing the rootnote of a e-guitar strumming along. Another e-guitar is strumming along, panned to the right side of the speakers. A male voice is singing in a higher key with delay in his voice. This song may be playing with headphones on a rainy colder day.", "audio": "/zhanghaomin/datas/musiccap/music_data/FY8bZRm_QiE.wav"} +{"id": "FYFapDVOFHg", "caption": "This music is an enthusiastic instrumental. The tempo is fast with an amplified harmonica solo. The music is lively, animated, happy, cheerful, energetic, enthusiastic and peppy.", "audio": "/zhanghaomin/datas/musiccap/music_data/FYFapDVOFHg.wav"} +{"id": "FYux89o7Hhk", "caption": "This is a live recording of the outro of a latin american salsa song. There are brass instruments like the saxophone and trumpet. There is a man who speaks in Spanish once the music stops. It was the end section or outro of a song.", "audio": "/zhanghaomin/datas/musiccap/music_data/FYux89o7Hhk.wav"} +{"id": "FYwDTJtEzhk", "caption": "This audio clip features a recording from a movie sequence. There are sounds of bombs blasting. There is the sound of a machine gun firing. The sound of a man grunting as if he is escaping from the firing gun. In the background, there is the sound of a bass playing one note in a repetitive sequence. A simple percussion plays in the background and a wind instrument plays a note.", "audio": "/zhanghaomin/datas/musiccap/music_data/FYwDTJtEzhk.wav"} +{"id": "Fa1KdG8niq0", "caption": "The song is an instrumental. The tempo is medium with a heavily doctored guitar playing lead with strong rock drumming. The song is highly distorted with hissing and crackling audio. The audio quality is very poor and the song is a tv show tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fa1KdG8niq0.wav"} +{"id": "Fa1c4qfBqzE", "caption": "This is the recording of a DJ performance. In the rhythmic background, the electronic drums are playing a simple yet groovy beat. The DJ is scratching the turntable rapidly over this track. The piece is danceable. It has a dirty mix. Parts of this piece can be used as turntable samples for a beat. It could also be used in the soundtrack of a show with a big city setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fa1c4qfBqzE.wav"} +{"id": "FaD9qs2ACpI", "caption": "The Hip Hop song features a passionate female vocal singing and flat male vocal rapping over piano chords, punchy kick and snare hits, repetitive synth hits and sustained strings melody. At the end of the first section there is an echoing effect on vocals. It sounds energetic and addictive, even though the audio cuts out in the middle of the chorus, straight to the verse.", "audio": "/zhanghaomin/datas/musiccap/music_data/FaD9qs2ACpI.wav"} +{"id": "FaRrq7cYu84", "caption": "The Ambient song features a mellow piano melody and soft synth pad chords. It sounds relaxing, calming and hypnotic - like something you would listen to while doing yoga.", "audio": "/zhanghaomin/datas/musiccap/music_data/FaRrq7cYu84.wav"} +{"id": "FbV2Lgt3H1Q", "caption": "The low quality recording features a live performance of a rock song that consists of flat male vocal singing over simple electric guitar chords. The recording is noisy and it has some seat crackling noises in it. It sounds sad and emotional though.", "audio": "/zhanghaomin/datas/musiccap/music_data/FbV2Lgt3H1Q.wav"} +{"id": "FcwWl5JBnoU", "caption": "The Classical song features a mixed harmonizing choir singing over organ melody, brass section melody and wooden percussion. It sounds powerful and epic.", "audio": "/zhanghaomin/datas/musiccap/music_data/FcwWl5JBnoU.wav"} +{"id": "FdPaa6WR2F8", "caption": "This is a techno music remix of a classical music piece. It is an instrumental piece. The melody is being played by a melodic pad. There is a constantly shifting synth sound. The rhythm is being played by an electronic drum beat. The atmosphere is trippy and eccentric. This piece could be used in the soundtrack of a psychedelic movie during a hallucination scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/FdPaa6WR2F8.wav"} +{"id": "FdvGsAq99r0", "caption": "This is an Arabic music piece being performed live by an orchestra. There is a new flute playing a solo in the lead. The melodic background consists of the violin, the oud, and the qanun while the cello and the bass guitar are playing in the lower range. The rhythmic background is provided by percussive elements that sound like the doumbek. The atmosphere is vibrant. This piece could be used as an opening theme for a drama movie or a TV series that takes place in the Middle East.", "audio": "/zhanghaomin/datas/musiccap/music_data/FdvGsAq99r0.wav"} +{"id": "Fg8yzA7zifw", "caption": "The low quality recording features a very interactive live performance of a gospel song that consists of crowd harmonized singing and clapping, alongside passionate male vocals and shimmering hi hats which gives it a subtle rhythm. It sounds passionate, energetic and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fg8yzA7zifw.wav"} +{"id": "FgUSmmTEE3M", "caption": "This is a piano-based ballad. The song is emotional, uplifting and generally pulls on your heartstrings. The singer sounds passionate and sings legato notes while the violins play sustained notes behind him to create an even more dramatic effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/FgUSmmTEE3M.wav"} +{"id": "Fh53p0Tnnxg", "caption": "The clip is of traditional eastern sounds that would be found in India. We hear notes being played on a sitar, as well as an acoustic guitar. There's also a sustained buzzing instrument in the background which creates a relaxed atmosphere.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fh53p0Tnnxg.wav"} +{"id": "FiKY19GK6-8", "caption": "This folk song features the melody played on a harp. The instrument plays the bass and treble notes of the song. There are no other instruments in this song. There is no voice in this song. This song can be played in a sad movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/FiKY19GK6-8.wav"} +{"id": "FkpJaXzgMBQ", "caption": "A female vocalist sings this song. There are two separate tracks where the vocalists sing very low notes in the former and high notes in the latter with ukelele accompaniment. The voice is controlled and melodious but the tracks are unrelated.", "audio": "/zhanghaomin/datas/musiccap/music_data/FkpJaXzgMBQ.wav"} +{"id": "Fm6ss1PBC1Q", "caption": "The low quality recording features a reverberant female vocal singing over acoustic guitar arpeggiated melody. It sounds soft, mellow and passionate. The recording is noisy and since the overall sound is leaning towards the right channel, the stereo image is unbalanced.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fm6ss1PBC1Q.wav"} +{"id": "FmytwY7SAfU", "caption": "The low quality recording features a DJ scratching a hip hop song that consists of punchy kick and snare hits, shimmering hi hats and syncopated open hats. There are some plastic tapping sounds. The recording is noisy, in mono and it sounds groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/FmytwY7SAfU.wav"} +{"id": "FoFMRXlNJ6Y", "caption": "A male vocalist sings this simple pop. The tempo is medium with an electric guitar melody, keyboard accompaniment, steady drumming, steady bass lines and acoustic guitar rhythm. The song is a simple, melodic, earnest, engaging Soft Rock;", "audio": "/zhanghaomin/datas/musiccap/music_data/FoFMRXlNJ6Y.wav"} +{"id": "FsCQmTluSDw", "caption": "The drums sound complex and fast paced going into the direction of drum&bass. Full of hihat and snare hits. Barely noticeable a synthetic bass is playing along with the drums giving this song a ragga feeling. A very simple synthesizer pad is playing a high pitched melody. The male voice sounds lower and energetic. This recording is of poor audio quality. This song may be playing at a dancing event or while working out.", "audio": "/zhanghaomin/datas/musiccap/music_data/FsCQmTluSDw.wav"} +{"id": "FscE_AHEmFk", "caption": "This symphonic song features a string section playing the main melody. There are multiple violins playing different parts in harmony. The music starts off with four ascending notes followed by one descending note which is stretched out. This is followed by a descending run. The song has an epic feel and can be played as a grand entrance theme of royalty.", "audio": "/zhanghaomin/datas/musiccap/music_data/FscE_AHEmFk.wav"} +{"id": "Fsm-xDmyFKg", "caption": "An acoustic drum is playing a fast groove with a kick-hit on every beat. The snare hit is full of reverb and panned to the right side of the speaker. A loud e-bass is playing a melody along with a clean e-guitar. A piano is playing a chord progression also adding a rhythmic element to the song. The male voice is singing in the mid range and gets support from backing voices that are barely noticeable. This song may be playing at a headshop.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fsm-xDmyFKg.wav"} +{"id": "FsnRM2irjvI", "caption": "The low quality recording features a live performance of an alternative/indie song and it consists of flat female vocal singing over synth keys and arpeggiated electric guitar melody. There are also some crowd noises in the background. It sounds thin, but also emotional and like something you would want to sing along.", "audio": "/zhanghaomin/datas/musiccap/music_data/FsnRM2irjvI.wav"} +{"id": "Fsv_syCvzsc", "caption": "solo marching snare music. The snare is tight and high pitched. The player is performing various rudiments. The feel is regimented, almost militaristic and demonstrates virtuosity.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fsv_syCvzsc.wav"} +{"id": "FteW_2gNtD4", "caption": "This is an Algerian folk music, also known as Rai. There is a male vocalist singing in a chant-like manner. There is a flute playing the main melody while the rhythm is being provided by several percussive elements. There is a lively feel to it. This piece could be used in the opening shots of a movie taking place in North Africa. It could also be in the soundtrack of a desert-themed video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/FteW_2gNtD4.wav"} +{"id": "FtskdD6Py7Y", "caption": "Amateur recording of solo beat boxing of a cover of a popular song.", "audio": "/zhanghaomin/datas/musiccap/music_data/FtskdD6Py7Y.wav"} +{"id": "Fv9swdLA-lo", "caption": "A male voice is singing/shouting phrases while an acoustic drum is playing a dance groove along with an e-bass. On top of that a acoustic guitar is playing a melody and another one is strumming chords while an accordion is playing a loud melody that seems to be the lead. The drum fill-ins are panned to the left and right side of the speakers. This song sounds like the people are having fun. This song may be playing at a dance event in the countryside.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fv9swdLA-lo.wav"} +{"id": "FvIKye4-iGc", "caption": "The excerpt features fighting sounds in the foreground, even fire sounds. In the background a tense music is being played by horns and accompanied by strings. It sounds as if the audio recording is of someone playing a game.", "audio": "/zhanghaomin/datas/musiccap/music_data/FvIKye4-iGc.wav"} +{"id": "FvQgVl5IBHw", "caption": "The music features a male voice singing a descending melody that repeats. The instrumental consists of a drum kit that's playing a light rhythm, a double bass that's playing a repeating descending melody and an electric guitar that's strumming chords once per beat. The quality of the audio recording is not so good which leads me to believe this is an amateur recording and not something professional.", "audio": "/zhanghaomin/datas/musiccap/music_data/FvQgVl5IBHw.wav"} +{"id": "FvdUm5j_oA0", "caption": "The low quality recording features a drum cover of a pop song that consists of energetic tom rolls, shimmering cymbals and punchy kick and snare hits. The audio slowly fades out, as it is probably an Outro section of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/FvdUm5j_oA0.wav"} +{"id": "FxeA9blzUD8", "caption": "This song contains a string section playing a soft rising melody with key changes then an upright bass comes in being played with a bow and long strokes. An acoustic piano panned to the right side of the speakers is playing a melody along to the female voice singing. This song may be playing in a dramatic scene of a Disney movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/FxeA9blzUD8.wav"} +{"id": "FxpV97ILuSo", "caption": "The Acid Folk song features a flat female vocal singing over repetitive bass guitar, wide arpeggiated acoustic guitar melody and banjo guitar melody. It sounds vintage, warm, easygoing and like it came out of a western movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/FxpV97ILuSo.wav"} +{"id": "Fy51z2RwH3E", "caption": "A digital drum is playing a four on the floor groove with a kick on every beat. Other percussive sound samples have been used to spice it up and give it a little bit more dance feeling along with a funky bassline. Cowbell sounds are panned to the left and right side of the speakers. A noise/riser sound is creating a little atmosphere before fading out. A piano is playing a chord progression adding a little bit more harmony. This song may be playing at a beachbar.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fy51z2RwH3E.wav"} +{"id": "Fz-ZNyVKWro", "caption": "This is an Ethiopian traditional music piece. There is a female vocalist singing in a crying-like manner through the use of autotune. There are traditional Ethiopian instruments such as washing and masenqo in the melodic background. The rhythm is being played by the percussion. There is an atmosphere of mourning in this piece. This piece could be used in the soundtrack of an Ethiopian drama movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Fz-ZNyVKWro.wav"} +{"id": "FzG8ZQAhKrE", "caption": "A string section is playing tritones and dissonant notes to create tension. Then a synth pad takes over together with a digital choir sound playing a drone sound while strong and loud timpani hits are creating a shocking atmosphere along with some fast paced percussion. This song may be playing in a dark, dramatic and chasing movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/FzG8ZQAhKrE.wav"} +{"id": "G-5UYGccne4", "caption": "The low quality recording features a mixed harmonizing vocals singing over shimmering bells and groovy piano melody. It sounds passionate and euphoric. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/G-5UYGccne4.wav"} +{"id": "G-7BfzMgZL8", "caption": "A male vocalist sings this perky song. The tempo is medium fast with an animated trumpet harmony, intense drumming, keyboard accompaniment and punchy bass lines. The vocals are energetic, vivacious, spirited, lively, rhythmic speech. The song is a Latin Urbano.", "audio": "/zhanghaomin/datas/musiccap/music_data/G-7BfzMgZL8.wav"} +{"id": "G13NEVAm6-o", "caption": "The low quality recording features a flat male vocal counting rhythm over shimmering ride cymbals and soft snare hits. The recording is a bit noisy and it sounds like a tutorial on how to play drums.", "audio": "/zhanghaomin/datas/musiccap/music_data/G13NEVAm6-o.wav"} +{"id": "G18Nt0ZeEJQ", "caption": "This song contains an overlayer of trumpets playing a melody in a higher register along to a tuba serving as bass. This song may be playing for a video layering sounds on top of each other.", "audio": "/zhanghaomin/datas/musiccap/music_data/G18Nt0ZeEJQ.wav"} +{"id": "G22YfD5xxMU", "caption": "This is a live performance of an electronic dance music piece. There is a vocal sample repeating the same line. A synth is playing the tune while the electronic drums are playing the rhythm. There is a rising pattern and an energetic atmosphere. If it were not for the poor quality of the recording, this piece would fit nicely at a nightclub.", "audio": "/zhanghaomin/datas/musiccap/music_data/G22YfD5xxMU.wav"} +{"id": "G2JDDwIuNrQ", "caption": "This song contains a digital beat with a soft and deep kick with other percussive sounds and a mallet instrument playing a melody. In the foreground you can hear water running down and other noises than a voice starts to appear along with a short melody of strings and horns playing as if there was an achievement. This song may be playing in a desktop video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/G2JDDwIuNrQ.wav"} +{"id": "G2uCAwYS6w0", "caption": "This pop song features a female voice singing the main melody. This is accompanied by percussion playing a simple beat. At the end of the first bar, the percussion pauses and a piano strikes one chord when the voice reaches her high pitch. The percussion resumes playing the simple beat. The bass follows the root notes of the chords. The piano plays chords in the background. A string section plays notes in the background filling the musicscape. This song has a romantic theme. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/G2uCAwYS6w0.wav"} +{"id": "G4fTKotMoWI", "caption": "Someone is playing an acoustic guitar ending his phrase. In the background you can hear high pitched noises. This song may be playing at home practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/G4fTKotMoWI.wav"} +{"id": "G6A9NKeK8ko", "caption": "The music is instrumental. There are ambient sounds like door banging sounds, eerie squeaks, church bells ringing and string section harmony. The song is a video game soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/G6A9NKeK8ko.wav"} +{"id": "G6ihF82lvEA", "caption": "This audio contains a male voice talking with a lot of reverb on his voice. Then someone starts playing a single tone on a cembalo. This is an amateur recording and sounds more like a tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/G6ihF82lvEA.wav"} +{"id": "G7pD1K3jYg4", "caption": "The low quality recording features a live performance of a classical song and it consists of tuba melody. It sounds mellow, soft and reverberant, as it was recorded in a huge concert hall. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/G7pD1K3jYg4.wav"} +{"id": "G8iTuTi8ywU", "caption": "The song is an instrumental. The tempo is medium fast with a strong guitar lead, rock drumming rhythm, percussive bass line and an electric guitar strumming rhythm. The song is high on adrenaline and exciting. The audio quality is very bad with ambient crowd screaming noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/G8iTuTi8ywU.wav"} +{"id": "G9gsCU85c8k", "caption": "This song features a male voice singing the main melody. Other male voices sing fills in between lines as backing voices. A repetitive melody is played on the marimba. The percussion is programmed and the focus is on the continuous hi-hat strokes. The bass plays the root notes of the chords. The mood of this song is happy. This song can be played at a dance party.", "audio": "/zhanghaomin/datas/musiccap/music_data/G9gsCU85c8k.wav"} +{"id": "GAoGADilmV8", "caption": "Ominous orchestral music with long held string notes, bowed string bass, electronic cymbal roll and concert bass drum. The mood is eerie.", "audio": "/zhanghaomin/datas/musiccap/music_data/GAoGADilmV8.wav"} +{"id": "GAohd8KvONo", "caption": "This is an ambience track that features a burning flame sound effect. The atmosphere is scary and horror-like. You could hear this track as a background on a halloween event.", "audio": "/zhanghaomin/datas/musiccap/music_data/GAohd8KvONo.wav"} +{"id": "GBLKj2d0iC4", "caption": "This music is instrumental. The tempo is slow with a theremin solo lead. There is no accompaniment. The music has sharp, high notes with the thereminist playing an electronic syncopated harmony.", "audio": "/zhanghaomin/datas/musiccap/music_data/GBLKj2d0iC4.wav"} +{"id": "GBMlv6j0WJ8", "caption": "This music is a didgeridoo instrumental. The tempo is slow with an incessant unusual, droning harmony of the didgeridoo. There are no other instruments used. The music is continuous droning, meditative, hypnotic and trance like.", "audio": "/zhanghaomin/datas/musiccap/music_data/GBMlv6j0WJ8.wav"} +{"id": "GBsate-JQAo", "caption": "The low quality recording features a live performance sung by harmonizing mixed vocals and followed by acoustic rhythm guitar and shimmering shaker. In the second part, a hollow male vocal continues to sing over shaker and acoustic guitar. It sounds thin, but fun, happy and emotional - it was probably recorded with a phone or camera microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/GBsate-JQAo.wav"} +{"id": "GF8QWSW0UbY", "caption": "This is an isolated vocal track of a rock opera piece. There are no instruments. A passionate male vocalist is singing melodically in the lead. There is a choir in the background providing medium-to-high pitched back vocals. There is an uplifting atmosphere. This piece could be used in remixes. Vocal samples can be lifted for DJ sets or beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/GF8QWSW0UbY.wav"} +{"id": "GFGwPa9d9XQ", "caption": "This is a country folk song with a generally positive, cheerful and joyful vibe to it. The singer is a man with an elderly voice that has a quality that sounds like a gurgle. His style of singing and the content of lyrics and melody are similar to hearing a story being told. There aren't really any rhyming lyrics - it's more like he is telling a story in song form. There are licks being played on an electric guitar, as well as certain motifs on the violin in between particular phrases by the singer.", "audio": "/zhanghaomin/datas/musiccap/music_data/GFGwPa9d9XQ.wav"} +{"id": "GFJNgqcX7u0", "caption": "This is an instrumental electric guitar jam meant to showcase an echo delay pedal. The guitar using the pedal is merely strumming the chords while there is another electric guitar in the background playing the melody. There is also a bass guitar playing a simple bass line. In the rhythmic background there is a chill rock beat played by the acoustic drums. There is a calm and chill atmosphere in this piece. It could be used as the loading screen music in a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/GFJNgqcX7u0.wav"} +{"id": "GFT6TeQx_0U", "caption": "The song is an instrumental. The song is slow tempo with eerie sounds created by an effects module playing chords. The song is eerie and haunting . The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/GFT6TeQx_0U.wav"} +{"id": "GFbSHWBjuuQ", "caption": "This music is an upbeat instrumental. The tempo is fast with an animated trombone melody with an enthusiastic piano accompaniment. The music is vibrant, engaging, buzzing, incessant, untiring and droning like a bee.This music a Western Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/GFbSHWBjuuQ.wav"} +{"id": "GG6XkHATIyw", "caption": "The music excerpt features a bass guitar that plays with the string slapping technique. This passage sounds as if it's meant to show some practicing exercises.", "audio": "/zhanghaomin/datas/musiccap/music_data/GG6XkHATIyw.wav"} +{"id": "GHQlBD-6rkA", "caption": "The low quality recording features a compilation of pop songs. The first song features an echoing female vocal sining, alongside wide harmonizing female vocals, over arpeggiated solo electric guitar melody, sustained strings progression, smooth bass, soft kick hits, punchy snare, simple hi hats and shimmering open hat. At the very end of the loop, there is a short snippet of the second song that consists of flat female vocals singing over claps, synth keys melody and punchy kick. It sounds emotional and passionate, even though the mix is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/GHQlBD-6rkA.wav"} +{"id": "GHyUAl9Yaos", "caption": "Two male vocalists sing this melodic Indian Classical music. The tempo is medium slow with Carnatic music accompaniments like violin, Ghatak and mridangam. The song is a good natured vocal duel between two carnatically trained vocalists. There is the sound of people cheering and clapping to the beat in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/GHyUAl9Yaos.wav"} +{"id": "GJYhDjThTHM", "caption": "This is a thrilling orchestral piece that feels epic, suspenseful and intense. There are string instruments like violins and cellos, and timpani for percussion. There is one over-bearing vibrational sound that overwhelms the whole arrangement - it is played once and rings for three seconds.", "audio": "/zhanghaomin/datas/musiccap/music_data/GJYhDjThTHM.wav"} +{"id": "GLIXnXZEOxY", "caption": "An acoustic piano is playing a sad melody while two women are singing as a duo taking turns. Their voices have some reverb and in the background you can hear the crowd cheering. This song may be playing live on stage.", "audio": "/zhanghaomin/datas/musiccap/music_data/GLIXnXZEOxY.wav"} +{"id": "GMFWnMRtfNI", "caption": "This is a classical music piece played with the virtual sounds of a wind orchestra. The orchestra is composed of the oboe, the clarinet, the basset horn, the bassoon and the contrabass. The piece is in major key which gives the piece a more positive aura in general, but the virtual sounds make it feel inauthentic.", "audio": "/zhanghaomin/datas/musiccap/music_data/GMFWnMRtfNI.wav"} +{"id": "GMtb7U-8IYM", "caption": "The low quality recording features a live performance that's barely audible and it consists of sustained strings and a choir. It sounds crushed, distorted and very noisy, as it was recorded with a broken microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/GMtb7U-8IYM.wav"} +{"id": "GNjsxLdSwHI", "caption": "The low quality recording features a classical music played by orchestra that consists of staccato string melody, woodwinds melody, staccato brass melody and solo, low tuba melody. The recording is a bit noisy and it sounds like background music for old movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/GNjsxLdSwHI.wav"} +{"id": "GNu_hiHGEp0", "caption": "This hip-hop song features programmed percussion playing a hip-hop beat. The bass follows the root notes of the chords. Synth strings play chords. The sound of an object being thrown can be heard. The sound of shattering glass is also heard. This song appears in a game.", "audio": "/zhanghaomin/datas/musiccap/music_data/GNu_hiHGEp0.wav"} +{"id": "GOTy3yhCylw", "caption": "This is a bass guitar jam in the style of funk. It is an instrumental performance. The bass guitar is playing a complex solo using the slap technique. There is a backing track composed of a programmed acoustic sounding drum beat. There is a groovy atmosphere to it. This piece could be used in the opening theme of a tutorial/unboxing YouTube channel.", "audio": "/zhanghaomin/datas/musiccap/music_data/GOTy3yhCylw.wav"} +{"id": "GOujNXEtDmg", "caption": "The low quality recording features a hip hop song that consists of flat male vocals, alongside background male ad libs, rapping over boomy bass, punchy kick, slap snare, shimmering hi hats, tinny percussive elements and weird, funny and repetitive percussion. It sounds groovy and boomy, but also muddy and poorly mixed.", "audio": "/zhanghaomin/datas/musiccap/music_data/GOujNXEtDmg.wav"} +{"id": "GPSqrciDLog", "caption": "This live recording features an instrumental song. This Regional Mexican song features an accordion playing the main melody. This is accompanied by an acoustic guitar strumming chords. A double bass plays the bass notes. A tambourine acts as the percussion. This song is in an upbeat mood. The song can be played at the entrance of a carnival.", "audio": "/zhanghaomin/datas/musiccap/music_data/GPSqrciDLog.wav"} +{"id": "GPwzpw_47Dg", "caption": "Low fidelity live recording of an instrumental eastern European string ensemble with bowed violin, bowed bass. Crowd noise is audible. No drums are present. There is a feeling of gaiety and levity.", "audio": "/zhanghaomin/datas/musiccap/music_data/GPwzpw_47Dg.wav"} +{"id": "GQPOpFX20Gw", "caption": "This instrumental contains a digital piano playing a beautiful melody that sounds a little bit like standing in the rain on a summer day. The electronic drums sound without dynamics but with a strong kick that gets supported by the bassline. A snare hit stands in the foreground. A hi-hat fills the space in between and gets surrounded by stringsounds playing a minimalist melody with a lot of reverb on it. A short snappy pluck sound is also playing a melody. barely noticeable. This song may be playing in a chapter of a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/GQPOpFX20Gw.wav"} +{"id": "GQbUpJFArKI", "caption": "This is a rock and roll music piece. There is a male vocal singer singing as the lead while other back vocals sing rhythmic back vocals at a higher pitch than the lead. An electric guitar is playing a simple and repeated tune while there is a bass guitar in the background. The acoustic drums are playing a basic 4/4 rock beat with claps simultaneous with the snare hits. There is an easygoing atmosphere in this piece. It could be playing in the background of a rock bar. This piece could also work well in sports venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/GQbUpJFArKI.wav"} +{"id": "GQbytKkt0tg", "caption": "The Alternative/Indie song features a passionate female vocalist singing over an arpeggiated electric guitar melody. It sounds passionate, emotional, heartfelt and sad.", "audio": "/zhanghaomin/datas/musiccap/music_data/GQbytKkt0tg.wav"} +{"id": "GQz_u0Vc8Os", "caption": "The Soft Rock song features a soulful male vocal melody over widely spread acoustic rhythm guitar, arpeggiated electric guitar melody and smooth bass. At the end of the loop there is a short snippet of the drop that consists of energetic drums and solo electric guitar melody. Right before the drop, the drums are slowly fading into the drop. Overall it sounds passionate, soulful, emotional and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/GQz_u0Vc8Os.wav"} +{"id": "GRdzFvQezUE", "caption": "This is a hip-hop music piece. There is a duo of one male and one female vocal singing in a way that resembles rapping. The beat has an electric guitar and a bass guitar playing a groovy tune. The rhythmic background consists of an electronic drum beat. The atmosphere is urban. This piece could be playing in the soundtrack of a crime movie where the characters are doubting their actions.", "audio": "/zhanghaomin/datas/musiccap/music_data/GRdzFvQezUE.wav"} +{"id": "GSAMEMX_oAg", "caption": "This is a pop music piece performed acoustically. The male and female vocals take turns singing melodically as a duet. The simple melody is being played by a ukulele. The aura of the song is very calm and easygoing. It could be used in the soundtrack of a teenage drama. The music could be playing in the background at a coffee house.", "audio": "/zhanghaomin/datas/musiccap/music_data/GSAMEMX_oAg.wav"} +{"id": "GT9g4uqK9G8", "caption": "The song is an instrumental blues song. The song is medium tempo with a blues harmonica playing a cool melody, walking bass line, guitar accompaniment , steady drumming rhythm and other percussion hits. The song is exciting and groovy. The song has a bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/GT9g4uqK9G8.wav"} +{"id": "GU782ddSBvk", "caption": "The song is instrumental. The tempo is medium with timpani\u2019s playing in a marching rhythm with room echoes. The song is energetic and has a sense of duty like a battle march. The song is an interactive game play soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/GU782ddSBvk.wav"} +{"id": "GUwBLItoJXk", "caption": "This is the live performance of a flamenco music piece. There is a male vocalist singing passionately in the Spanish language. An acoustic guitar strums a characteristic flamenco tune. Sounds of the crowd cheering can be heard in the background. The atmosphere is vibrant.", "audio": "/zhanghaomin/datas/musiccap/music_data/GUwBLItoJXk.wav"} +{"id": "GW6pti04qIo", "caption": "The low quality recording features a tutorial where a flat male vocal is talking, followed by acoustic rhythm guitar chords. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/GW6pti04qIo.wav"} +{"id": "GWcMqKYOJR4", "caption": "This clip features a drum solo being played. The first beat in the clip is played by striking the hi-hat and kick twice and then the snare once. This pattern is repeated three times followed by a roll. The snare is played four times followed by the toms. This pattern is played twice. This is followed by a pattern where the snare and toms are struck in a sequence of four strokes, five strokes and six strokes all fitting within the counts of the bar. This song is a demo of the percussion instrument being used.", "audio": "/zhanghaomin/datas/musiccap/music_data/GWcMqKYOJR4.wav"} +{"id": "GWcTd6XrQj4", "caption": "The low quality recording features a breathy flute melody played over mellow strings melody. It sounds soulful and passionate. The recording is noisy and slightly distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/GWcTd6XrQj4.wav"} +{"id": "GWxiiDBK5s8", "caption": "This is the poor quality recording of a bebop jazz music performance. The organ is playing an insanely complex improvised solo. In the background, there is a bass guitar and a jazz acoustic drum beat. The atmosphere is energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/GWxiiDBK5s8.wav"} +{"id": "GX-QhoihLeI", "caption": "The song is an instrumental with sounds of a woman screaming and running with huffing and puffing sounds. A chainsaw buzzes ominously , with a string section playing a scary and tense accompaniment along with a cello building the tension with a poignant harmony. The music is a horror movie soundtrack or an ad jingle. The song audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/GX-QhoihLeI.wav"} +{"id": "GXLeUXSVFYU", "caption": "someone is strumming a melody on a banjo along with some chords. In the background you can hear people talking. This is an amateur recording. This song may be playing outside at a bonfire surrounded by friends and family.", "audio": "/zhanghaomin/datas/musiccap/music_data/GXLeUXSVFYU.wav"} +{"id": "GYCfrx0ruz4", "caption": "The low quality recording features an instrumental cover that consists exotic steel pan melody, punchy kick hits layered with claps, groovy piano chord progression and groovy bass. It is in mono and it sounds a bit harsh, but energetic, tropical and exotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/GYCfrx0ruz4.wav"} +{"id": "GYx6HNQbP1w", "caption": "The song is an instrumental. The tempo is medium with a strong drumming rhythm, keyboard harmony, string synth harmony, guitar lead and a bass guitar shadowing the melody line in harmony. The song has rock music influences with a sense of mystery and adventure. The song is a soundtrack for an adventure sports documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/GYx6HNQbP1w.wav"} +{"id": "G_iJif-fC6E", "caption": "This music is an ominous instrumental. The tempo is slow with a spooky electronic keyboard harmony and menacing bass on the cello. The music is eerie, sinister, frightening, and baleful.", "audio": "/zhanghaomin/datas/musiccap/music_data/G_iJif-fC6E.wav"} +{"id": "GaNjXwElAUE", "caption": "An acoustic drum is playing a straight groove while an e-bass is playing a bassline that reminds of reggae. This feeling gets enhanced by a e-guitar strumming a short rhythmic chord on the offbeat giving the song its typical reggae vibe. On top of that, someone is playing a melody on a steeldrums. This song may be playing at beachbar.", "audio": "/zhanghaomin/datas/musiccap/music_data/GaNjXwElAUE.wav"} +{"id": "GbjtSTTEFK4", "caption": "Sounds like happy instrumental karaoke music featuring synthesized horns and a simple chord progression. There is a mallet percussion instrument playing rolls and following a pentatonic melody. Drums playing a simple beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/GbjtSTTEFK4.wav"} +{"id": "Gc8xf7CJiFY", "caption": "The low quality recording features a traditional song that consists of a shimmering tambourine, sizzling triangle, wide sustained strings melody, lead strings melody and wooden percussive elements. It sounds passionate, emotional, happy and fun, like something you would hear at weddings in the East.", "audio": "/zhanghaomin/datas/musiccap/music_data/Gc8xf7CJiFY.wav"} +{"id": "GcOOmVSM8Uw", "caption": "The low quality recording features, in the first half of the loop, a mono and noisy recording of a punk live performance with some crowd cheering noises. It sounds energetic and the recording suddenly fades out, transitioning into the second part of the loop which features a side synth pad that sounds suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/GcOOmVSM8Uw.wav"} +{"id": "GcYeBWujhjw", "caption": "This amateur recording features a rock song. A repetitive phrase is played on the guitar. The first bar consists of only the guitar sound. The bass and percussion start playing after one bar. The bass plays one note in groups of twos. The percussion plays a groovy rock beat. The hi-hat is played in a group of four strokes on the closed hi-hat followed by one stroke on the open hi-hat. There are no voices in this song. The mood of this song is melancholic.", "audio": "/zhanghaomin/datas/musiccap/music_data/GcYeBWujhjw.wav"} +{"id": "GcbCOmNiVm8", "caption": "This is a home recording. The guitar in this recording is being played off-pitch and no real chords are being played. The singer is a child who sings in falsetto.", "audio": "/zhanghaomin/datas/musiccap/music_data/GcbCOmNiVm8.wav"} +{"id": "GcnLApOeCh0", "caption": "The low quality recording features a reverberant background electro music that consists of claps, \"4 on the floor\" kick pattern and addictive violin melody. It is in mono and it sounds like it was recorded with a phone in a medium size room, as the music is playing through a speaker.", "audio": "/zhanghaomin/datas/musiccap/music_data/GcnLApOeCh0.wav"} +{"id": "GcqCHmHXEjo", "caption": "This music is instrumental . The tempo is fast with a burst of harmonious instrumentation. The music is orchestral with animated trumpets, melodious violin symphony, enthusiastic drumming, piano accompaniment and male vocalisation in the background. The music is bright, lively, powerful, commanding, fluent, gripping ,compelling and a delight to the ears.", "audio": "/zhanghaomin/datas/musiccap/music_data/GcqCHmHXEjo.wav"} +{"id": "Gde1fn1Y1uM", "caption": "This hard rock song features a male voice singing the main melody. The song starts with a distortion guitar playing a riff. The percussion plays a simple beat in common time. Once the voice starts singing, the guitars play power chords using down strokes. The bass follows the root notes of the chords. The mood of this song is happy. This song can be played in a car chase sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Gde1fn1Y1uM.wav"} +{"id": "GglIHiqClGM", "caption": "This music is a percussion instrumental. The tempo is medium fast with the drummer playing a groovy beat on the bass drum. The effect is low pitched loud, booming, resounding vibrato. There is no other instrument in this clip, so this could either be a tutorial or an introduction to a song.", "audio": "/zhanghaomin/datas/musiccap/music_data/GglIHiqClGM.wav"} +{"id": "Gh4KBdcCU64", "caption": "This song features a female voice crooning the main melody. She is using vocables and no lyrics. The same melody is played on the synth immediately after she sings the first first line. A percussion player plays a simple beat. A tambourine plays in the background. The rest of the instruments are not clear due to the low audio quality. This song can be played in a coffee shop. The mood of this song is romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/Gh4KBdcCU64.wav"} +{"id": "GiTmjE7az74", "caption": "This is a video game theme cover. The theme belongs to the Super Mario franchise. The main theme is being played on an analog sounding small keyboard. There is an added rhythmic background of beatboxing in this version. The atmosphere is playful. This piece could be used in the background of arcade gaming social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/GiTmjE7az74.wav"} +{"id": "GinP_ZRgAoY", "caption": "The audio contains someone playing an acoustic guitar while a female voice is singing. The performance sounds calming but there is a loud buzzing in the recording disturbing the atmosphere. This is an amateur recording. This song may be jamming at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/GinP_ZRgAoY.wav"} +{"id": "Gj6etuzTWlQ", "caption": "The low quality recording features a harmonized kids' vocals singing over a muffled flute melody. The recording is very noisy and it is in mono, but regardless it sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/Gj6etuzTWlQ.wav"} +{"id": "GjE_iD2BbFg", "caption": "This is a traditional south asian song. We have an accordion-like instrument for the melodic component and a tabla for percussion. The singer has a passionate voice. The audio quality is poor and the song distorts.", "audio": "/zhanghaomin/datas/musiccap/music_data/GjE_iD2BbFg.wav"} +{"id": "GkB_BkyVyPs", "caption": "The low quality recording features a live performance of a reggae song that consists of shimmering cymbals, addictive brass melody and muffled male vocal singing over it. It is noisy and in mono, and it sounds thin, harsh, muddy, messy and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/GkB_BkyVyPs.wav"} +{"id": "GmGWvBNO8JI", "caption": "This is an instrumental showcase jam. A clean sounding electric guitar solo is being played. The track has an easygoing aura to it. Parts of this jam can be picked and lifted to be used as clean guitar samples for a beat. It could also be used in advertisement jingles.", "audio": "/zhanghaomin/datas/musiccap/music_data/GmGWvBNO8JI.wav"} +{"id": "GopccU3Am1w", "caption": "The low quality recording features a live performance of a spooky glass melody. The recording is very noisy, as there are crowd chattering noises in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/GopccU3Am1w.wav"} +{"id": "Gow0TlxIx7U", "caption": "Someone is playing an acoustic guitar strumming chords on the backbeat while someone is holding the rhythm with a shaker and a percussion in the background. This song may be playing while having a jam session with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/Gow0TlxIx7U.wav"} +{"id": "GrbrWNohr6Y", "caption": "A female vocalist sings this mellow song. The tempo is slow with a subtle electric guitar accompaniment. The audio quality is inferior making it difficult to hear the song well. There is another track superimposed over the song which has sound so footsteps, metal being dragged, crickets, cricket chirping, breeze and some rustling. This is an audio of a song being played outdoors.", "audio": "/zhanghaomin/datas/musiccap/music_data/GrbrWNohr6Y.wav"} +{"id": "Grtmre_r9yI", "caption": "The low quality recording features a live performance of a folk song that consists of flat female vocals, harmonizing low male vocals, muffled drums, some wooden percussive elements, groovy bass and short strings licks. It sounds energetic and groovy, but the drums are really poorly recorded.", "audio": "/zhanghaomin/datas/musiccap/music_data/Grtmre_r9yI.wav"} +{"id": "GuHDy--gWiM", "caption": "The low quality recording features a live performance of a folk song and it contains a steel guitar solo melody played over, acoustic rhythm guitar, electric guitar melody, shimmering cymbals, punchy snare, groovy bass, followed by violin melody, crowd noises and claps. It sounds passionate, uptempo, soulful and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/GuHDy--gWiM.wav"} +{"id": "GuJdy864xWM", "caption": "Along with the vintage south asian vocal performance from an emotive female vocalist, this song features enchanting melodies from the bansuri. For percussion, we have tablas and tambourines. This is a live performance in a concert venue.", "audio": "/zhanghaomin/datas/musiccap/music_data/GuJdy864xWM.wav"} +{"id": "GuQFhmGqdog", "caption": "A female vocalist sings this rather vigorous country song. The tempo is fast with vocalisation. The vocalist is yodelling vigorously and rhythmically to the accompaniment of an animated banjo, fiddle, resonator and mandolin harmony, vibrant drumming and.", "audio": "/zhanghaomin/datas/musiccap/music_data/GuQFhmGqdog.wav"} +{"id": "GuYRF0no7hw", "caption": "The low quality recording features a rock song that consists of electric guitar chords, being played in a video game by plastic guitar, which makes plastic tapping noises. There are also some crowd cheering noises and the recording is very noisy overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/GuYRF0no7hw.wav"} +{"id": "Guu30szkA-0", "caption": "This is a drum & bass music piece. There is a female vocal sample that is being played repetitively. The main theme is being played by a keyboard while there is a strong bass in the background. The rhythmic background consists of a very fast tempo electronic drum beat. The atmosphere is modern. This piece could be played at nightclubs, at drum & bass events and in DJ sets. It could also work well in the soundtrack of a futuristic movie or a car racing video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/Guu30szkA-0.wav"} +{"id": "Gw0KmZ3kbjs", "caption": "The low quality recording features a repetitive synth bass melody played on a modulated synthesizer, followed by bouncy snare. The recording is very noisy, in mono, with some chair squeaking and phone grip noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/Gw0KmZ3kbjs.wav"} +{"id": "GwTXkfuc5v8", "caption": "A male vocalist sings this HIp-hop. The tempo is medium with subdued keyboard accompaniment, slick drumming, boomy bass drops, synthesised arrangements and vocal backup. The song is youthful; enthusiastic, passionate, insistent, repetitive, groovy,rhythmic chanting with a dance groove. This song is Contemporary Hip-Hop/Rap.", "audio": "/zhanghaomin/datas/musiccap/music_data/GwTXkfuc5v8.wav"} +{"id": "GwxSvUoYSZg", "caption": "This recording is full of atmospheric sounds that are modulated rising and falling in pitch with liquid klick noises, white noise and a lot of reverb. These sounds are probably created with a synthesizer. A pad sound is playing long notes in the mid range while a soft subbass is underlining the strings. This composition may be playing in an underwater scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/GwxSvUoYSZg.wav"} +{"id": "GxeDIuOzxmU", "caption": "The low quality recording features an arpeggiated harp melody. It sounds emotional and passionate and the recording is noisy, in mono and a bit muffled.", "audio": "/zhanghaomin/datas/musiccap/music_data/GxeDIuOzxmU.wav"} +{"id": "GyxH8ep_Vx8", "caption": "The low quality recording features a funky harmonica solo melody being played. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/GyxH8ep_Vx8.wav"} +{"id": "Gz8RlHf3Czs", "caption": "The low quality recording features a female vocal beatboxing a dubstep song. It sounds energetic and aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/Gz8RlHf3Czs.wav"} +{"id": "GzRvq0gJbj0", "caption": "In this clip we have a set of uilleann pipes being used to play a sweet and enchanting melody. It's a live performance. There's a sustained pad synth which also sounds ethereal, being used to support the uilleann pipes. This is traditional Irish or Celtic folk music. The song is emotional and captivating, with a slow tempo.", "audio": "/zhanghaomin/datas/musiccap/music_data/GzRvq0gJbj0.wav"} +{"id": "H-bTMbePj0A", "caption": "The song is an instrumental. The song is medium tempo with a percussionist playing a delightful melody on the steel drums with a steady drum rhythm and a percussive bass line. The song is cheerful and has a life message of being happy. The song audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/H-bTMbePj0A.wav"} +{"id": "H18aK9HhNSM", "caption": "The low quality recording features a live performance of a country song played by ukulele orchestra, smooth double bass and sung by fruity male vocals. It is uptempo and it sounds energetic, even without drums, and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/H18aK9HhNSM.wav"} +{"id": "H4rdJlSSt5Y", "caption": "The low quality recording features a covered song with arpeggiated banjo melody and flat female vocal that is occasionally out of tune. The recording is noisy and in mono, as if it was recorded with a phone, but it is also emotional, regardless of the voice crack.", "audio": "/zhanghaomin/datas/musiccap/music_data/H4rdJlSSt5Y.wav"} +{"id": "H4tyvJJzSDk", "caption": "Professionally recorded music featuring an intimate female vocal, delicate piano, and orchestral string accompaniment. The tempo is slow, the production is high fidelity and the mood is an introspective one. Would be perfect in an animated kids movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/H4tyvJJzSDk.wav"} +{"id": "H6Y_7Ax34-g", "caption": "This is a gear review jam. There is an electric guitar playing simple tunes. An amp plug is connected to the electric guitar. The atmosphere is easygoing. Sounds from this recording can be sampled to be used in advertisement jingles.", "audio": "/zhanghaomin/datas/musiccap/music_data/H6Y_7Ax34-g.wav"} +{"id": "H6qzijVEqZQ", "caption": "This is a pop funk piece used as a jingle for an ad. There is a male vocalist singing melodically while the electric guitar is playing a catchy tune with the bass guitar playing a groovy bass line. A normal tempo acoustic drum beat provides the rhythmic background. There are a couple of sound effects in the end. The piece has an easygoing atmosphere. It is the perfect match for a jingle. It could also be used in DJ sets or remixes.", "audio": "/zhanghaomin/datas/musiccap/music_data/H6qzijVEqZQ.wav"} +{"id": "H6rZwBc6aNM", "caption": "The low quality recording features an electro song that consists of a reverberant \"4 on the floor\" kick pattern, followed by suspenseful synth stabs. At the very end of the loop there is a short riser, after which comes the snippet of a filtered synth bass. It sounds thin, as it was poorly mixed.", "audio": "/zhanghaomin/datas/musiccap/music_data/H6rZwBc6aNM.wav"} +{"id": "HAEoz3VbaP8", "caption": "Someone is playing a ukulele. The piece sounds calming as someone is picking the strings: At the beginning of the song you can hear some white noise. This is an amateur recording but the quality is not bad. This song may be playing a documentary showing landscapes in slow motion.", "audio": "/zhanghaomin/datas/musiccap/music_data/HAEoz3VbaP8.wav"} +{"id": "HAHn_zB47ig", "caption": "The low quality recording features a groovy finger snapping. It is uptempo and the recording is in mono and very noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/HAHn_zB47ig.wav"} +{"id": "HCCGZh-TxK0", "caption": "A male vocalist sings this light melody. The tempo is medium with a funky bass line, keyboards accompaniment; slick drumming, groovy electric guitar and acoustic guitar riff with female vocal backup. The song is light, punchy, buoyant, groovy, funky,insightful, reflective and melodic. This song is a spirited Reggae song.", "audio": "/zhanghaomin/datas/musiccap/music_data/HCCGZh-TxK0.wav"} +{"id": "HDSV7Pzq8CA", "caption": "A drum is playing a four on the floor groove with a kick on every beat along to a bassline and a tambourine. Two e-guitars are strumming funky sounding chords. Male singers are singing a melody together in the mid-range. This song may be playing live at a local event.", "audio": "/zhanghaomin/datas/musiccap/music_data/HDSV7Pzq8CA.wav"} +{"id": "HEclHruM37s", "caption": "This is a rap rock song that fuses elements from each genre. The rapper has a charismatic and fiery approach, and after his rap verse we hear a blues-rock electric guitar solo. There's a sustained warm synth with a flanger that supports the whole melodic aspect of the track. The mood of this song feels motivating.", "audio": "/zhanghaomin/datas/musiccap/music_data/HEclHruM37s.wav"} +{"id": "HEhogaw0vUg", "caption": "The low quality recording features a live performance of a pop song and it consists of flat female and male vocal rapping over \"4 on the floor\" kick pattern and electric guitar melody. There are some crowd clapping and cheering noises in the background. It sounds exciting and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/HEhogaw0vUg.wav"} +{"id": "HEk4fx_XNNE", "caption": "The song is an instrumental. The song is medium tempo with ambient room noises, like a volume knob turned up, a guitar being plugged in and the rhythmic strumming of an amplified distortion guitar. The song is energetic and passionate. The song is an introduction to a rock song.", "audio": "/zhanghaomin/datas/musiccap/music_data/HEk4fx_XNNE.wav"} +{"id": "HFH9tcIK_PM", "caption": "A female vocalist sings this enthusiastic song. The tempo is fast with keyboard harmony, infectious drumming, turntable effects, digital drumming, electronic music arrangements, boomy bass lines, vocal backup, vocalisation and synthesiser articulation. The song is passionate, emotional, powerful, impactful, engaging and inspiring with a punchy and youthful dance groove. This song is a powerful Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/HFH9tcIK_PM.wav"} +{"id": "HFVM5pVTwkM", "caption": "The Blues/Pop song features groovy hi hats, punchy snare and kick hits, tinny snare rolls in-between snare hits, addictive brass melody and smooth bass at the very end of the loop. It sounds a bit repetitive, but still addictive and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/HFVM5pVTwkM.wav"} +{"id": "HH3ryAEP308", "caption": "The song is an instrumental. The tempo is medium fast with a groovy bass line, massive bass drops, various percussion hits, chirping tones, keyboard accompaniment and syncopated rhythms. The song is a modern electronic techno dance tune produced in a home studio.", "audio": "/zhanghaomin/datas/musiccap/music_data/HH3ryAEP308.wav"} +{"id": "HHTgjmgTV6c", "caption": "The low quality recording features a house song that contains echoing male vocal singing over shimmering hi hats, bouncy claps, \"4 on the floor\" kick pattern and repetitive synth lead melody. It sounds energetic and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/HHTgjmgTV6c.wav"} +{"id": "HHZGjS4g-w4", "caption": "This folk song features a female voice singing the main melody. This is accompanied by a tabla playing the percussion. A guitar strums chords. For most parts of the song, only one chord is played. At the last bar, a different chord is played. This song has minimal instruments. This song has a story-telling mood. This song can be played in a village scene in an Indian movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/HHZGjS4g-w4.wav"} +{"id": "HIDXdH6R6T8", "caption": "This funk song features a male voice singing the main melody. Female voices sing backing vocals. This is accompanied by percussion playing a simple beat. The bass plays a funky bassline using the root notes of the chords. A wah or tron effect is added on the bass. The sound of bells is heard in the background. This song has a flirty mood. This song can be played as a slow dance song in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/HIDXdH6R6T8.wav"} +{"id": "HJuR9WJ1iRY", "caption": "The low quality recording features a live performance of a classical song and it consists of harpsichord and sustained strings melodies. The recording is a bit noisy and quite reverberant, as it was recorded in a medium size concert hall. It sounds easygoing, passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/HJuR9WJ1iRY.wav"} +{"id": "HLXGkzzQHUU", "caption": "This is an Egyptian music piece. There is a heavy use of percussion in the rhythmic background with the accompaniment of occasional claps. Medium-pitched strings are leading the melody. The male vocals are chanting rhythmically while the female vocal is singing in a soothing manner that creates a contrast in between the two elements. There is an adventurous, suspense-filled feeling. This piece could be used in a mystery/thriller video game. It could also be used in a movie that takes place in the Middle East.", "audio": "/zhanghaomin/datas/musiccap/music_data/HLXGkzzQHUU.wav"} +{"id": "HLsRePLObfI", "caption": "The song is instrumental. The tempo is fast with a beautifully played hand pan arrangement by a soloist. The song is ethereal and innocent in its beauty. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/HLsRePLObfI.wav"} +{"id": "HLz3N5nG8fQ", "caption": "An acoustic drum is playing a jazzy groove on the ride along with a bassline while an e-guitar is playing jazz chords with a lot of changes together with an acoustic piano rendering phrases with an uplifting melody. The singer's voice sounds low and romantic. This song may be playing while dancing with a partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/HLz3N5nG8fQ.wav"} +{"id": "HMJe5jS0Yt4", "caption": "An electro swing, or swing house track featuring a four on the floor kick pattern, acoustic jazz piano sample playing a classic rhythm changes chord progression, a female blues singer, synthesizer risers, ambient bell sounds, a walking synth bassline and a snare on backbeat. Would be fitting music for a modern day speakeasy.", "audio": "/zhanghaomin/datas/musiccap/music_data/HMJe5jS0Yt4.wav"} +{"id": "HMQfp_qtF-M", "caption": "Someone is beatboxing a reggaeton beat. In the background you can hear the crowd clapping and cheering. This song may be playing live as part of a beatbox performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/HMQfp_qtF-M.wav"} +{"id": "HNf9eHqDT1A", "caption": "This music is instrumental. The tempo is medium fast with a melodious keyboard harmony, steady drumming, groovy bass, synthesiser arrangements , electronically articulated sounds and tambourine beats . The melody is harmonious, pleasant, uncomplicated and well layered. This music is Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/HNf9eHqDT1A.wav"} +{"id": "HOIIp5NyFx0", "caption": "The low quality recording features a flat male vocal singing over crowd cheering sound, punchy kick, shimmering cymbals, groovy accordion melody, acoustic rhythm guitar chords and smooth bass guitar. There is a short toms roll before the bass drops. It sounds fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/HOIIp5NyFx0.wav"} +{"id": "HOkuea1wExA", "caption": "The low quality recording features a synth key melody played over simple bass and snare rolls. It sounds happy and fun, while the recording is quiet, dull and muffled.", "audio": "/zhanghaomin/datas/musiccap/music_data/HOkuea1wExA.wav"} +{"id": "HQ9HlWProm0", "caption": "This is a clip of a tutorial where we have a male teacher playing a minor scale on a nylon string guitar. The energy of the video is calm.", "audio": "/zhanghaomin/datas/musiccap/music_data/HQ9HlWProm0.wav"} +{"id": "HQb2jhmw1BE", "caption": "The Classical song features a dynamic arrangement of energetic orchestra drums, woodwinds, arpeggiated strings melody and shimmering brass melody. It sounds cinematic and epic - like a background movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/HQb2jhmw1BE.wav"} +{"id": "HRVVqstIabc", "caption": "The low quality recording features an orchestra song that consists of a string section melody. The section contains violin melody playing in the left channel, cello in the right channel and later on, double bass in the middle. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/HRVVqstIabc.wav"} +{"id": "HRxTN4TH-80", "caption": "Someone is hitting a high pitched singing bowl that rings out for a long time. This song may be playing during a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/HRxTN4TH-80.wav"} +{"id": "HS_ikHx4LIQ", "caption": "The low quality recording features a hip hop song that consists bright, widely spread steel guitar melody, tinny muffled percussive elements, shimmering triangle, reverberant flute melody, claps, soft kick hits, mellow synth pad and groovy bass that glues everything together. It sounds kind of dull, but groovy, energetic and tropical - thanks to those flute and guitar melodies.", "audio": "/zhanghaomin/datas/musiccap/music_data/HS_ikHx4LIQ.wav"} +{"id": "HSrzR9hhEe8", "caption": "This clip starts with a low frequency music bowl being struck. The note is allowed to sustain. After a while, a higher frequency music bowl is struck and that note is allowed to sustain. There are no other instruments in this song. There are no voices in this song. The sound of music bowls can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/HSrzR9hhEe8.wav"} +{"id": "HTQySJM4Jhg", "caption": "This is a Christmas music piece. There is one male and one female vocalist singing in a festive manner in the Romanian language. There is a keyboard playing the melody and a bass guitar playing in the background. The rhythm is kept by the sleigh bells. The atmosphere is joyful. This piece could be playing in the background at a Christmas event in Romania.", "audio": "/zhanghaomin/datas/musiccap/music_data/HTQySJM4Jhg.wav"} +{"id": "HU7oqkJeItQ", "caption": "The low quality recording a boomy steel guitar being aggressively strummed. The recording is noisy, reverberant and it sounds muddy, but regardless, the melody is addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/HU7oqkJeItQ.wav"} +{"id": "HVA9-fjtv6U", "caption": "This music is a short instrumental. The tempo is medium with a church organ harmony with a male voice speaking something incoherent and subtle sounds like clinking and whirring. The audio is short and skillful. This is a tutorial on how to play the piano/organ.", "audio": "/zhanghaomin/datas/musiccap/music_data/HVA9-fjtv6U.wav"} +{"id": "HVsXJDR1_Lw", "caption": "The low quality recording features a musical played on a small device that reproduces mono sound. The song consists of energetic drums, brass section and passionate female vocal singing on top of it. It sounds noisy, muffled and thin, as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/HVsXJDR1_Lw.wav"} +{"id": "HWZdPxRzCWs", "caption": "This audio recording features a crickets sound effect, sea waves sound effect and mellow synth pad chords in the background, followed by shimmering tambourine and muffled snare. At the very end of the first section of the loop, there is a short filter modulation riser, after which there is silence. At the very end of the loop there is a soft white noise down sweep. It sounds very relaxing and calming, especially because of the pad and sound effects.", "audio": "/zhanghaomin/datas/musiccap/music_data/HWZdPxRzCWs.wav"} +{"id": "HWe3TSUcvHc", "caption": "This is an amateur recording of a hard rock piece. An electric guitar solo is being played over a backing track that has a rhythm guitar, a bass guitar, a keyboard and acoustic drums playing in it. The sound resembles an 80s feel. It is a raw recording, so the mix is a bit muddy.", "audio": "/zhanghaomin/datas/musiccap/music_data/HWe3TSUcvHc.wav"} +{"id": "HXG8DnTpyPc", "caption": "This instrumental song features a violin playing the main melody. This is accompanied by a guitar playing chords. The piano plays backing chords. At the end of the song, the piano plays a fill. The bass is played on a double bass. There is no percussion in this song. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/HXG8DnTpyPc.wav"} +{"id": "HXwX9f9ugZ4", "caption": "This jazz song features a trumpet playing the main melody. This is accompanied by a string section. There are long pauses in between lines where the backing instruments pause while the trumpet solo is played. Percussion is played along with the string section. There are no voices in this song. This is an instrumental song. This song can be played in a silent movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/HXwX9f9ugZ4.wav"} +{"id": "HY1KdNS19CM", "caption": "This audio contains a e-guitar playing a riff in the mid range. Another clean e-guitar is strumming chords while another e-guitar answers to the first melody. An e-bass is underlining the scenario. All the instruments are spread across the speakers. This song may be playing live using a looper pedal.", "audio": "/zhanghaomin/datas/musiccap/music_data/HY1KdNS19CM.wav"} +{"id": "HYjSrwSm0T4", "caption": "This song contains three guitars playing chords, and two melodies while one of the guitars stands out to be playing the main melody. The guitars are panned to the left and the right side of the speakers. An e-bass is playing a walking line that repeats itself. Different percussive instruments are panned to the left and right side of the speakers. There are some noises of doors opening and closing that I think do not belong to the musical composition and they sound in the foreground. This song may be playing in a house in the countryside.", "audio": "/zhanghaomin/datas/musiccap/music_data/HYjSrwSm0T4.wav"} +{"id": "H_2ZPxy80Eo", "caption": "The low quality recording features a lullaby that consists of mellow girl vocal singing over staccato string melody in the left channel and plucked strings melody in the right channel of the stereo image. There are muffled, barely audible, muffled snare rolls in the background. The recording is noisy and reverberant, and it sounds soft, emotional and mellow.", "audio": "/zhanghaomin/datas/musiccap/music_data/H_2ZPxy80Eo.wav"} +{"id": "H_5wh4aMQe0", "caption": "The low quality recording features a groovy orchestra percussions, sustained strings melody and shimmering hi hats. In the second half of the loop, there is a wind sound effect, followed by loud metallic impact. It sounds glorious, epic, uplifting and like a sync sound for a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/H_5wh4aMQe0.wav"} +{"id": "H_He9_zHk8I", "caption": "This audio contains someone playing a classical piece on a cembalo. This song may be playing live while listening to a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/H_He9_zHk8I.wav"} +{"id": "Ha-FS_CHmGw", "caption": "A female opera singer sings this soprano melody. The tempo is slow with an ethereal violin symphony accompaniment. The song is mellifluous , soft, enchanting, enigmatic, mystical, ethereal,celestial and dreamy. This is a Classic Opera.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ha-FS_CHmGw.wav"} +{"id": "HbX1ZIuD0ac", "caption": "This audio contains a very fast snare drum-roll. You can hear a high pitched sound falling in pitch and then a explosion of a bomb. This audio may be playing in a movie-warscene.", "audio": "/zhanghaomin/datas/musiccap/music_data/HbX1ZIuD0ac.wav"} +{"id": "Hc_UM8l_sTg", "caption": "This song features a pedal steel guitar playing the main melody. This starts off with a slide to a high register followed by plucking low register strings. This is accompanied by percussion playing a simple beat in common time. An acoustic guitar strums chords in the background. The bass guitar plays the root notes of the chords. This song is at a slow tempo. There are no voices in this song. This is an instrumental song with a Country feel. This song can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hc_UM8l_sTg.wav"} +{"id": "HdRPdh-cSTw", "caption": "A female vocalist sings this Hindi Devotion song. The tempo is slow with keyboard harmony,tambourine beats, violin melody and rhythmic tanpura accompaniment. This clip is the song introduction with slow chants like singing. The song is a Hindu Devotion song to the God Shiva. It is emotional, sentimental, devotional, prayerful praise and worship. There are ambient sounds of people talking and cheering, indicating that this is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/HdRPdh-cSTw.wav"} +{"id": "Hdko95EitpI", "caption": "This is an orchestral piece from a video game soundtrack. The brass and the strings sections are playing an ominous sounding tune. There is a timpani being played with a crescendo pattern. The atmosphere is grim. This piece could be added to the soundtrack of thrilling movies and video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hdko95EitpI.wav"} +{"id": "He63KV_9Pwg", "caption": "The low quality recording features harmonizing vocals singing over punchy kick and snare hits, shimmering hi hats, synth pads, simple bass and mellow piano chords. There are crowd cheering noises in the background as this is a live performance. It sounds passionate, emotional, exciting and the recording is noisy, in mono and slightly distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/He63KV_9Pwg.wav"} +{"id": "HfBh3lZZi8Q", "caption": "This music is instrumental. The tempo is fast with a male vocalist, beat boxing rhythmically to the melody of a backup track. The audio quality is inferior but the music is upbeat, punchy, buoyant and youthful with a dance groove. This music is a Synth Pop/Electro Pop with beat boxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/HfBh3lZZi8Q.wav"} +{"id": "HflVPAOVL7U", "caption": "This is the recording of an ice cream truck jingle. Engine sounds from the truck can be heard in the recording. It has an analog sounding high-pitch synth playing a cute melody in the major key. The atmosphere is happy and childlike. This piece could be used to lift samples from. It could also be added to the soundtrack of children's movies and TV shows. Another good use would be in the soundtrack of video games of the arcade genre.", "audio": "/zhanghaomin/datas/musiccap/music_data/HflVPAOVL7U.wav"} +{"id": "HfzEa06vDLg", "caption": "The female voice is singing lightly sad-sounding. Backing voices are supporting her in some phrases while strings are playing long notes that are panned to the left and right side of the speakers. A piano is playing ballad sounding chords and a melody underlined by the e-bass. This song may be playing in a soul musical.", "audio": "/zhanghaomin/datas/musiccap/music_data/HfzEa06vDLg.wav"} +{"id": "Hg4f2xt3oKA", "caption": "Someone is splaying a series of bell sounds and a big gong hit that rings out for a long time. Wild percussive hits are being played for a moment. Then a traditional string instrument takes over playing a single long note with a bow and a lot of vibrato. This is an amateur recording and of poor audio-quality. This song may be playing in a traditional festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hg4f2xt3oKA.wav"} +{"id": "HhQTvaZtURY", "caption": "This classical song is played on a harpsichord. This is music for royalty or aristocrats. There are some pedal notes played on the bass part and the main melody is played on the treble part. There are no other instruments in this song. There is no percussion in this song. There are no voices in this song. This song can be played in a movie scene where a king is entering his castle.", "audio": "/zhanghaomin/datas/musiccap/music_data/HhQTvaZtURY.wav"} +{"id": "Hij_QxDkIJI", "caption": "The Pop song features an echoing synth keys melody that consists of a passionate female vocal singing over punchy kick, synth bells melody, echoing synth keys melody and shimmering hi hats. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hij_QxDkIJI.wav"} +{"id": "HkCYA4ax4jI", "caption": "This low quality audio features a male voice singing the main melody. This is accompanied by percussion playing a simple beat. The bass plays the root notes of the chords. Strings play staccato notes in the background and at the end of the bar, the notes are allowed to ring. A synth plays chords using an organ voice. This voice plays chords in the background. At the end, the synth plays the sound of two bells playing a descending sequence. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/HkCYA4ax4jI.wav"} +{"id": "HkXSX7Kdhms", "caption": "Someone is playing a song through speakers. The song contains digital drums with strong loud rhythmic hits rising up in pitch and a kick on every beat. A guitar-like sound is playing an arpeggio melody with other string instruments. This is an amateur recording and of poor sound-quality. This song may be playing at a rave party.", "audio": "/zhanghaomin/datas/musiccap/music_data/HkXSX7Kdhms.wav"} +{"id": "Hl8OrRlMwi4", "caption": "This is an electronic dance music song, with a four on the floor beat. The melodic component of the song consists of a fuzzy beat that's treated with a flanger, and a drum roll upon arrival.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hl8OrRlMwi4.wav"} +{"id": "Hn46VuvS88Y", "caption": "This music is instrumental. The tempo is slow with an electric guitar playing two corresponding notes. The plucking pattern indicates that the guitar is being tuned. This is a Guitar tuning Tutorial/ Lesson.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hn46VuvS88Y.wav"} +{"id": "Hnk45Z0EAxg", "caption": "The song is instrumental. The song is medium tempo with traditional percussion instruments , bongos, piano accompaniment and groovy bass line. The song is improvisational and energetic. The song is jazz fusion and has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hnk45Z0EAxg.wav"} +{"id": "Hob0LAu8afQ", "caption": "The low quality recording features a dynamic bass guitar playing. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hob0LAu8afQ.wav"} +{"id": "Hp-lgcs4VXY", "caption": "This song contains digital drums playing a four on the floor groove with a kick on every beat along to an e-bass. In the background you can hear additional bongo rhythms. A synth string sound is playing long chord notes in the background. An e-guitar is finger picking a chord melody. A female voice is singing in a higher key and with backing vocals. This song may be playing while cleaning the kitchen.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hp-lgcs4VXY.wav"} +{"id": "HpkPTa1fQDE", "caption": "This is the recording of a flute lesson. There is a male voice speaking in an instructive manner on the technique of embouchure.", "audio": "/zhanghaomin/datas/musiccap/music_data/HpkPTa1fQDE.wav"} +{"id": "HplcVmJhuIc", "caption": "This is the background track of a challenge video. Many sound effects can be heard in procession such as the blood pulse, a metallic impact and clock ticking. Then the piece starts playing with loud synth bass and an electronic drum beat. The aura of the track is unnerving and violent which was the reaction expected in the challenge. Some parts of this track can be used to lift samples for a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/HplcVmJhuIc.wav"} +{"id": "HrPnGYGrvm0", "caption": "The song is an instrumental. The tempo is medium and sometimes glitch out if time, with a banjo being played by a beginner. The song is amateurish in quality and not pleasant. The song audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/HrPnGYGrvm0.wav"} +{"id": "Hrgl_1rGGU4", "caption": "This is an amateur recording of a gospel music performance. There are two organs playing simultaneously, taking turns in playing groovy melodies. There is a bass guitar playing in the background. The rhythmic background consists of an acoustic drum beat that gives peak sounds due to the poor quality of the recording. There is a sophisticated feel to this piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hrgl_1rGGU4.wav"} +{"id": "HrwpdRe7meM", "caption": "This music is an Altai instrumental. The tempo is medium fast with use of traditional and regional instruments. There is use of a droning stringed instrument, shakers and wind instruments. The music is incessant droning, pleasant, unique, close to nature and simple.", "audio": "/zhanghaomin/datas/musiccap/music_data/HrwpdRe7meM.wav"} +{"id": "HrxfNVYirCo", "caption": "This music is an instrumental, the tempo is medium slow with an insistent keyboard /amplified organ harmony, gentle electric guitar lead and ambient nature sounds in the background. The music is soft, mellow , soothing, pensive, meditative, reflective, nostalgic and poignant with the chirping of birds, sound of waves and gentle breeze.", "audio": "/zhanghaomin/datas/musiccap/music_data/HrxfNVYirCo.wav"} +{"id": "HtCkwxfAmzw", "caption": "This indie rock song features a piano playing the main melody. This is accompanied by percussion playing a simple beat. It seems like the hi-hat is substituted by the tambourine. A distortion guitar plays power chords. The bass follows the root notes of the chords. There are no voices in this song. The song is upbeat and the mood is happy. This song can be used in the end credits of a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/HtCkwxfAmzw.wav"} +{"id": "HtRjRuKnvjI", "caption": "The low quality recording features an echoing electric guitar melody played over synth pad chords and smooth bass. It sounds relaxing, calming and passionate - like something you would hear in a spa center.", "audio": "/zhanghaomin/datas/musiccap/music_data/HtRjRuKnvjI.wav"} +{"id": "HtSznF9_784", "caption": "A female singer sings this jazz scat improvisation. The song is medium fast tempo with jazz drumming, Latin percussion, steady bass line and a piano accompaniment. The song is energetic and highly improvisational. The song is a live jazz performance with ambient room noises and other disturbances.", "audio": "/zhanghaomin/datas/musiccap/music_data/HtSznF9_784.wav"} +{"id": "HtXtfCR-MUg", "caption": "This game music starts off with midi sounds playing a high pitched melody. This is followed by another instrument playing a louder melody in a descending pattern of five notes followed by an ascending pattern of three notes. Then an industrial machinery sound is heard followed by the sound of a person in boots running. This song is used in a game.", "audio": "/zhanghaomin/datas/musiccap/music_data/HtXtfCR-MUg.wav"} +{"id": "HuVgc2jf0Ec", "caption": "This clip features a melody played on the accordion. There are no other instruments in this song. This song starts off with an ascending triplet run played twelve times. The melody continues on the same scale. There are no voices in this song. This song is an instrumental. This song can be played in a silent movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/HuVgc2jf0Ec.wav"} +{"id": "HvOSaS8sXQM", "caption": "This song contains an acoustic drum playing along with a bass and an accordion melody creating a cheerful atmosphere. The crowd is so loud. Cheering, screaming and laughing. This song may be playing at a local event.", "audio": "/zhanghaomin/datas/musiccap/music_data/HvOSaS8sXQM.wav"} +{"id": "Hvs6Xwc6-gc", "caption": "This is the live recording of an Ethiopian traditional music piece. There is a male vocalist singing in a melancholic manner. The melodic background is composed of the Ethiopian bowed lute called masenqo. The atmosphere of the piece is solemn and emotional. This piece could be used in the soundtrack of a drama movie that takes place at an Ethiopian village.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hvs6Xwc6-gc.wav"} +{"id": "HvuHSr_yncE", "caption": "Someone is playing shakers before the acoustic drums come in with a loud fill and a groove with a lot of crash hits. Someone is playing chords on an e-guitar along with a synth plug melody with a lot of reverb. Another e-guitar is playing a melody on top. This song may be playing at a live festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/HvuHSr_yncE.wav"} +{"id": "HwGK5RvNOFI", "caption": "Swift intellectual music featuring interlocking piano and acoustic guitar arpeggios, a pizzicato string melody, a fast, driving hi-hat, and typing sounds. Good for a presentation on a new technology.", "audio": "/zhanghaomin/datas/musiccap/music_data/HwGK5RvNOFI.wav"} +{"id": "Hxf1seOpijE", "caption": "This is an instrumental piece. An electric guitar is playing the melody while another is playing secondary riffs. There is a granular synth holding notes at a high pitch. The overarching atmosphere of this piece is suspenseful. It feels like something big is about to happen that will break the intentionally superficial calmness. This piece would suit perfectly during suspense scenes in a movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/Hxf1seOpijE.wav"} +{"id": "HyJ2YaNrA3U", "caption": "This music is instrumental. The tempo is medium with a peppy keyboard harmony, groovy bass line, slick drumming and synthesiser arrangements with a hissing or whooshing sound in the background. The song is catchy, groovy, trippy, trance and youthful.", "audio": "/zhanghaomin/datas/musiccap/music_data/HyJ2YaNrA3U.wav"} +{"id": "HyXMWRU9Owc", "caption": "This audio contains a lot of percussion such as tablas playing a rhythm along with shakers and more. Male voices are singing something like a mantra repeating the same melody. Kids' voices are also singing the same melody in a higher octave. A bansuri flute adds little melody lines. This song may be playing during a ceremony.", "audio": "/zhanghaomin/datas/musiccap/music_data/HyXMWRU9Owc.wav"} +{"id": "HyyHwIK9SSI", "caption": "The music is an instrumental gameplay track. The track has sounds of growling monsters, church bells playing, a female crying in pain, chains being pulled, splashing noises, electrical spark buzzes and other disturbances. The music has very poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/HyyHwIK9SSI.wav"} +{"id": "HzXWXYxXyYA", "caption": "Someone is playing an e-bass along to a backing track that contains a male voice singing with backing vocals that are panned to the left and right side of the speakers. An acoustic drum set is holding a groove along. The bass is almost completely panned to the left side of the speakers.This song may be playing at a dance-competition. This is an amateur recording but of decent quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/HzXWXYxXyYA.wav"} +{"id": "I-C14nCneBs", "caption": "A male singer sings cheerful yodelling vocals. The song is fast tempo, with a steady drumming rhythm, groovy bass line, guitar accompaniment and piano playing enthusiastically. The song is cheerful and thoroughly entertaining. The song is a modern pop tune with yodelling to express happiness and free spirit.", "audio": "/zhanghaomin/datas/musiccap/music_data/I-C14nCneBs.wav"} +{"id": "I-XYm2Ck2r8", "caption": "Someone is playing an e-guitar melody and licks. This is an amateur recording. This song may be playing at home practicing e-guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/I-XYm2Ck2r8.wav"} +{"id": "I-Z3gB6pfIA", "caption": "A female vocalist sings this perky pop. The tempo is medium with rhythmic acoustic guitar , groovy bass lines, keyboard accompaniment and enthusiastic drumming. The song is simple, dulcet, fresh, peppy, youthful, vibrant and punchy with sounds of crowd hooting and cheering and talking. This song is a Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/I-Z3gB6pfIA.wav"} +{"id": "I-xPuRe9vF0", "caption": "This is a tropical, Caribbean style song which has a melody that is played on a steel drum. The song has a very relaxing feel, which makes you feel as if you are on an island somewhere in paradise. The bassline is intricate and the percussion is laid-back.", "audio": "/zhanghaomin/datas/musiccap/music_data/I-xPuRe9vF0.wav"} +{"id": "I06TOd9pXng", "caption": "The low quality recording features hip hop song that contains a low pitched male vocal singing over some camera shuttering sound effects, after which an echoing male vocal starts rapping over punchy kick and snare hits, low toms, electric guitar melody, reversed crash cymbal riser and shimmering hi hats. It sounds groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/I06TOd9pXng.wav"} +{"id": "I0q3IGmTkRo", "caption": "The low quality recording features a breathy, echoing flute melody over resonating arpeggiated piano melody. It is very noisy, in mono and it sounds very muddy as the frequencies in the lower register are clashing with each other.", "audio": "/zhanghaomin/datas/musiccap/music_data/I0q3IGmTkRo.wav"} +{"id": "I0skZ6yT36E", "caption": "This is a Peruvian folk music piece. It is an instrumental piece. There is a violin and a Peruvian harp playing a festive melody. The atmosphere is lively. This piece could be playing from a radio station in a movie that takes place in Peru.", "audio": "/zhanghaomin/datas/musiccap/music_data/I0skZ6yT36E.wav"} +{"id": "I11AcD1sGes", "caption": "Male and female singers sing together in vocal unison. The song is medium tempo with a violin playing countermelody, along with a traditional string bass rhythm and percussion instruments. The song is South American folk music with a lot of passion. The song audio quality is bad with high gains all over.", "audio": "/zhanghaomin/datas/musiccap/music_data/I11AcD1sGes.wav"} +{"id": "I1fcUe9MoMw", "caption": "This is an acoustic cover of a pop music piece. There is a boy singing melodically. The chords are being played on the ukulele. The atmosphere of the original piece is emotional, but the characteristics of the ukulele create a chill atmosphere. The piece is in medium tempo. This rendition of the piece could be used in the soundtrack of a high school drama movie/TV series. It could also be playing in the background of a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/I1fcUe9MoMw.wav"} +{"id": "I1wakVlpP6M", "caption": "The low quality recording features suspenseful strings and arpeggiated harp playing in the background while haunting boy vocal songs on top of it. At one point the vocal distorts a little bit, making the recording low quality. It sounds intense and suspenseful - like something you would hear in thriller movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/I1wakVlpP6M.wav"} +{"id": "I2yA-F-_A2E", "caption": "The low quality recording features a traditional song that consists of a distant woodwinds melody playing over wooden low percussion and strummed strings melody. It sounds soulful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/I2yA-F-_A2E.wav"} +{"id": "I368EWBLIs4", "caption": "This song is an electric guitar instrumental. The tempo is medium with two amplified guitars playing the lead and harmony respectively with steady drumming. The music is a simple, rhythmic, smooth and engaging Rock instrumental;", "audio": "/zhanghaomin/datas/musiccap/music_data/I368EWBLIs4.wav"} +{"id": "I3qbB4Kq3Y0", "caption": "The song is an instrumental. The song is slow tempo with a fiddler plays a rhythmic melody accompanied by a guitar accompaniment and other percussive instruments. The song is spirited and energetic. The song has country or Celtic influences. The song has average quality audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/I3qbB4Kq3Y0.wav"} +{"id": "I4Jp0kB2Ns0", "caption": "The Rock instrumental features a passionate electric guitar solo melody played over punchy kick and snare hits, shimmering hi hats, groovy bass guitar, wooden bouncy percussion and electric guitar, mellow feedback, located in the left channel of the stereo image. It sounds groovy, addictive and passionate, thanks to that solo melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/I4Jp0kB2Ns0.wav"} +{"id": "I4Rhe1XViYg", "caption": "This music clip is an Orchestral piece. There is a trumpet playing a lively solo to the accompaniment of an animated, vigorous Violin symphony and a church bell at the end. The music is lively, spirited, vivacious, happy and cheerful with the violins, cello and viola adding a happy, cheerful vibe to this Classical Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/I4Rhe1XViYg.wav"} +{"id": "I5CBPhpimtg", "caption": "Someone is playing a big djembe along to a fast paced melody in a higher register played on a bagpipe. This song may be playing during a traditional holiday in Ireland.", "audio": "/zhanghaomin/datas/musiccap/music_data/I5CBPhpimtg.wav"} +{"id": "I5KHYgtrVBw", "caption": "This is a DJ performance. The background track has a male singing upfront with a mellow guitar tune and groovy latin drums with Caribbean influences overall. The DJ plays a male vocal sample and sound effects over this track. The atmosphere is danceable. It is a low-resolution recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/I5KHYgtrVBw.wav"} +{"id": "I5mESbabhZY", "caption": "The low quality recording features a cover of a pop song sung by passionate female vocalists over acoustic guitar melody and acoustic rhythm guitar chords. It sounds emotional, passionate and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/I5mESbabhZY.wav"} +{"id": "I6eU2qRjJ7Y", "caption": "This music is instrumental. The tempo is medium with a dramatic, intense and suspenseful synthesiser arrangement, cymbal riff and conch shell sound. The music is a background score for a Bengali movie / TV series with a male voice giving instructions, a Hindu priest chanting Om with women joining in with the chant and vocalisations and the sound of the conch shell.", "audio": "/zhanghaomin/datas/musiccap/music_data/I6eU2qRjJ7Y.wav"} +{"id": "I6wri5XQQbU", "caption": "An acoustic drumset plays a rock groove along with a bassline building the foundation of the song. Someone is playing a solo melody on an e-guitar. This recording is of poor quality. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/I6wri5XQQbU.wav"} +{"id": "IAeYandwJqc", "caption": "The low quality recording features a harmonica solo melody played over funky acoustic rhythm guitar. It sounds passionate and easygoing, even though the recording is a bit noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/IAeYandwJqc.wav"} +{"id": "IC_Wpalzzm8", "caption": "Someone is playing a steady groove on the drums along with a simple bassline playing the footnote while a e-piano is playing minor chords panned to the right side of the speakers. Another distorted e-piano sound is playing a countermelody in a lower register panned more to the left side. A male voice is singing in the midrange. This song may be playing late night at a bar having a drink by yourself.", "audio": "/zhanghaomin/datas/musiccap/music_data/IC_Wpalzzm8.wav"} +{"id": "ICcASgMtIJ8", "caption": "This house music features a female voice singing the main melody. This is accompanied by programmed percussion playing a simple beat. The kick is played on every count. Hand claps are played at every alternate count. The bass plays the root notes of the chords. Synth chords are played in the background. This song can be played at a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/ICcASgMtIJ8.wav"} +{"id": "ICtri0ElFZc", "caption": "This is a traditional middle eastern type of song with traditional singing that involves vocal modulation. The percussion is simple and encourages dancing. The three men sing in unison and there's an intermittent chant. They repeat the same phrase like a refrain.", "audio": "/zhanghaomin/datas/musiccap/music_data/ICtri0ElFZc.wav"} +{"id": "ID4AoAfHMVk", "caption": "An acoustic drum is playing a reggae groove with a rim shot as a snare sound and shakers/tambourine in the background. An e-bass is playing a bassline accompanied by a clean e-guitar playing the same melody. A piano is playing short chords on the backbeat. Male voices are singing, sounding relaxed and joyful. This song may be playing at a reggae festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/ID4AoAfHMVk.wav"} +{"id": "IDHHAwqDpzU", "caption": "This is a gospel music piece. The piece is a church hymn that is being sung by a choir in the style of acapella. The male vocals are harmony singing. The atmosphere is festive. This piece can be played at Christian religious events. It could also be used in the soundtrack of a modern drama movie during religious scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/IDHHAwqDpzU.wav"} +{"id": "IEVVHo9nr7g", "caption": "A male vocalist sings this passionate rap. The tempo is medium with keyboard harmony, slick drumming, funky bass lines , sound of chimes and synthesiser arrangements. The song is emotional, passionate, emphatic, persuasive, youthful, impactful and rhythmic chanting. The song is a contemporary Hip-Hop/RAo.", "audio": "/zhanghaomin/datas/musiccap/music_data/IEVVHo9nr7g.wav"} +{"id": "IF-77lLlMzE", "caption": "This music is video game background music. The tempo is fast with aggressive synth articulation and electronic sounds like shooting and crashing . There is also a superimposed sound of a toy pig grunting incessantly with a man talking in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/IF-77lLlMzE.wav"} +{"id": "IFimpFwvbz8", "caption": "This is a drum & bass piece. Fast-paced electronic drums and electronic percussion are laying the rhythmic foundation of the piece. There is a constantly revolving synth bass sound while a gentle ambient synth can be heard adding texture. The piece is danceable. It could be played at nightclubs and also could prove useful for DJ setlists.", "audio": "/zhanghaomin/datas/musiccap/music_data/IFimpFwvbz8.wav"} +{"id": "IFumVgqOVaM", "caption": "This audio contains an e-bass playing a melody along with a simple drum groove and other stringlike instruments. An e-guitar is playing a lead melody on top and in the background you can hear the crowd screaming. This is an amateur recording and of poor audio-quality. This song may be playing during a live show.", "audio": "/zhanghaomin/datas/musiccap/music_data/IFumVgqOVaM.wav"} +{"id": "IGAzIIZRczw", "caption": "This song features the main melody played on a french horn and on a trumpet. The first part of the song is played on a french horn and the melody is continued on the trumpet. There are no other instruments in this song. The trumpet plays a battle call pattern. This is an instrumental song. There are no voices in this song. This song can be played just before a battle scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/IGAzIIZRczw.wav"} +{"id": "IGyDtKAU1u8", "caption": "This is a jazz music piece. It is an instrumental piece. The saxophone and the trumpet are playing the melody. The piano, the electric guitar and the bass guitar are accompanying them in the background. The tempo is slow. The atmosphere is chill. This piece could be playing in the background at a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/IGyDtKAU1u8.wav"} +{"id": "II1oyaWPiD0", "caption": "This is the recording of a trombone lesson. The male instructor is playing a note on the trombone and then speaking in an instructive manner in the Japanese language. The click of the metronome can be heard in the background. This recording can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/II1oyaWPiD0.wav"} +{"id": "IIK0EuHyb6w", "caption": "The low quality recording features a wide arpeggiated electric guitar melody. It sounds clean, passionate and the recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/IIK0EuHyb6w.wav"} +{"id": "IISJXKl1Ih4", "caption": "This is a classical harpsichord piece that elicits a feeling of suspense and tension in the listener. There are low sustained cellos which provide a contrast to the bright tones of the harpsichord. The piece feels haunting and has a sense of drama about it.", "audio": "/zhanghaomin/datas/musiccap/music_data/IISJXKl1Ih4.wav"} +{"id": "IJcLW4arT6s", "caption": "The low quality recording features a background sound ambience and atmosphere of a video game that consists of clothes movement, loud wind, exhale, background industrial impacts, metallic impact and wooden impact sound effects. It sounds like an action act, judging by the exhale and some metallic and wooden impacts.", "audio": "/zhanghaomin/datas/musiccap/music_data/IJcLW4arT6s.wav"} +{"id": "IJw2o_Yg00Q", "caption": "This is an electronic music piece. There is a high-pitched synth and stabbing strings in the melodic structure. An occasional vocal sample can be heard adding a haunting texture. There is a loud electronic drum beat in the rhythmic background. The atmosphere is unnerving and filled with terror. This piece could be used in a horror movie or a horror video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/IJw2o_Yg00Q.wav"} +{"id": "IKfmu7tAyUE", "caption": "The low quality recording features an arpeggiated acoustic flamenco guitar melody. The recording is noisy, in mono, and it sounds sad, easygoing and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/IKfmu7tAyUE.wav"} +{"id": "IKq2OF8jq1c", "caption": "The song sounds epic and is fully orchestrated with a string section; brass section; a male choir in the background, fast timpani hits and strings playing a melody. When the song stops, a door knocking sound can be heard along with a short video-game music sequence that does not belong to the previous song. The first song may be playing in a movie trailer.", "audio": "/zhanghaomin/datas/musiccap/music_data/IKq2OF8jq1c.wav"} +{"id": "IL1n6jzABVw", "caption": "This audio contains someone playing a fast melody on a tenor saxophone. This song may be playing in a jazz band.", "audio": "/zhanghaomin/datas/musiccap/music_data/IL1n6jzABVw.wav"} +{"id": "ILE12hEW5Ck", "caption": "A male singer sings this exciting melody with backup singers in vocal harmony. The song is medium fast tempo with a steady drumming rhythm, keyboard accompaniment, groovy bass line and various percussion hits. The song is energetic and passionate. The song is a retro pop hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/ILE12hEW5Ck.wav"} +{"id": "IMnh-TIyFuE", "caption": "The song is an instrumental. The tempo is medium with a strong bass line, steady drumming rhythm, triangle percussion, keyboard accompaniment and a male vocalist making guttural noises. The song is a modern techno pop dance tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/IMnh-TIyFuE.wav"} +{"id": "IN71kMOAk_k", "caption": "This song is sung by a female choir and then a single male voice along with the melody of an e-piano. In the background someone is playing lower tuned percussion and some chimes and wooden sounds. This song may be playing at a band rehearsal.", "audio": "/zhanghaomin/datas/musiccap/music_data/IN71kMOAk_k.wav"} +{"id": "INBx8CrIWcg", "caption": "The low quality recording features an electro song that consists of acid aggressive synth melody, repetitive synth lead melody, boomy 808 bass, claps and shimmering hi-hats. There is a sizzling riser in the first section of the loop. It sounds energetic and like something you would hear in an underground club.", "audio": "/zhanghaomin/datas/musiccap/music_data/INBx8CrIWcg.wav"} +{"id": "IO5QJRyoqO8", "caption": "This is a live recording of a keyboardist playing a twelve bar blues progression on an electric keyboard. The player adds embellishments between chord changes and the piece sounds groovy, bluesy and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/IO5QJRyoqO8.wav"} +{"id": "IOEwc-N2rX4", "caption": "The low quality recording features a mellow harp melody. The recording is noisy, in mono and it sounds soft and mellow.", "audio": "/zhanghaomin/datas/musiccap/music_data/IOEwc-N2rX4.wav"} +{"id": "IOzWDVGWRng", "caption": "This track features a cacophony of burping and farting sounds which are used in an instrumental manner to make up a Christmas jingle. There's a bell in the background and the sound of sleds and wings flapping.", "audio": "/zhanghaomin/datas/musiccap/music_data/IOzWDVGWRng.wav"} +{"id": "IPO79GrOYjg", "caption": "A male singer sings this passionately with backup singers in vocal harmony. The song is medium tempo with a steady drumming rhythm, various percussion, percussive bass line, guitar rhythm and keyboard harmony . The song is passionate and romantic with a cool dance groove. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/IPO79GrOYjg.wav"} +{"id": "IQbzpgmi4Ec", "caption": "EDM music with a four on the floor kick pattern holding down the dance beat. The vocalist is female and there are female fans screaming in the background. Overall, the music is low fidelity, as there is a fast sweeping resonant filter affecting the full mix and muffling it.", "audio": "/zhanghaomin/datas/musiccap/music_data/IQbzpgmi4Ec.wav"} +{"id": "IQxr3xwAbKk", "caption": "The low quality recording features a musician practicing bassoon scale. In the background, there is a muffled male vocal. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/IQxr3xwAbKk.wav"} +{"id": "IS5V2yjPp3k", "caption": "This clip is an amateur recording with very muffled audio. The song sounds like a lively chant, with women giggling, people talking and a booming , echoing voice that sounds like an announcement.", "audio": "/zhanghaomin/datas/musiccap/music_data/IS5V2yjPp3k.wav"} +{"id": "IT5hcf0KhYE", "caption": "The low quality recording features a live performance of a metal song and it consists of screaming male vocal singing over energetic, muffled instrumental. The recording is crushed, loud, distorted and mono - everything that the metal live performance should be.", "audio": "/zhanghaomin/datas/musiccap/music_data/IT5hcf0KhYE.wav"} +{"id": "ITYv4126yhk", "caption": "This clip features a percussion based song with no other instruments. The focus is on the kick drum and snare with minimal use of cymbals. Hand claps are played along with the snare. The percussion beat is random. Sounds of snipping are played. Crunchy sounds are played in this clip. There is the sound of sizzling in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/ITYv4126yhk.wav"} +{"id": "ITg9o6Gwsbo", "caption": "This music is an electronic instrumental. The tempo is fast with synthesiser arrangements, electronic beats , Dj mixer and a repetitive vocal riff. The music is incessant, psychedelic, hypnotic, trippy and trance like with a dance groove. This music is Techno Pop/EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/ITg9o6Gwsbo.wav"} +{"id": "ITq14s8h92I", "caption": "The low quality recording features electric rhythm guitar chords being strummed. It sounds monotone, but groovy and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ITq14s8h92I.wav"} +{"id": "IUD_ZYOh2MM", "caption": "This clip features the sound of an alarm clock. A female voice is also featured. The voice is irritated at the sound of the alarm. The device is being hit in an attempt to silence it. Only at the beginning of the clip, there is the sound of music fading away. There are no other instruments featured in this clip. The quality of audio is low.", "audio": "/zhanghaomin/datas/musiccap/music_data/IUD_ZYOh2MM.wav"} +{"id": "IUjzBX2Qm4k", "caption": "A e-guitar with a chorus effect is playing a simple, repeating chord progression while another guitar is playing a bassline over it that sounds more like a countermelody. On top of that, slightly panned to the right side of the speakers, a xylophone is playing single notes with a lot of reverb. This song sounds repetitive and relaxing and soft. This song may be playing with earphones waiting for the bus.", "audio": "/zhanghaomin/datas/musiccap/music_data/IUjzBX2Qm4k.wav"} +{"id": "IWbe-NSK6Ic", "caption": "An acoustic drum is played together with an e-bass. They both repeat the same pattern. The ride is panned to the right side of the speakers. Three e-guitars are playing. One is strumming the same chords as the bassline while another one is being strummed with a mute technique playing a reggae rhythm. The third guitar is playing a solo melody on top and is panned to the right side of the speakers. This song may be playing at a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/IWbe-NSK6Ic.wav"} +{"id": "IYiHhVWrh0w", "caption": "The low quality recording features a manically arpeggiated electric guitar melody and rock playback instrumental playing in the background. The recording is very noisy and it was recorded in mono - probably with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/IYiHhVWrh0w.wav"} +{"id": "IYtQfDsFVfA", "caption": "This is a house music piece. It has a fuzzy synth lead playing the main melody while there is a medium-to-high pitch pad playing an arpeggio. There is a fuzzy synth bass in the background. A loud electronic drum beat provides the rhythmic background. There is a constant crowd cheering effect giving the impression of the piece being performed live. The atmosphere is energetic. This piece can be played at nightclubs and EDM venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/IYtQfDsFVfA.wav"} +{"id": "IYumekd1VMg", "caption": "The Electro song features a punchy \"4 on the floor\" kick pattern, followed by shimmering hi hats and groovy synth bass. It sounds exciting and like something you would hear in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/IYumekd1VMg.wav"} +{"id": "I_a9OhfTcIc", "caption": "This audio contains several male voices singing an a acapella song as a choir. The voices go from the higher mids to the higher register. This song may be playing live in a church.", "audio": "/zhanghaomin/datas/musiccap/music_data/I_a9OhfTcIc.wav"} +{"id": "I_kUf7vgVNM", "caption": "This audio contains a digital drum playing a four on the flor groove with a kick on every beat and building up kicks to doubletime and triplets. Synth bass sounds and synth sounds in the midrange are playing arpeggiated melodies. This song may be playing with headphones while playing video-games.", "audio": "/zhanghaomin/datas/musiccap/music_data/I_kUf7vgVNM.wav"} +{"id": "I_wT76iYBdQ", "caption": "This music is a ukelele instrumental. The tempo is medium with the sound of a bee buzzing and an animated sound followed by a dialogue between two men in a foreign language. The music is mellow, soft and simple like it's meant for children.", "audio": "/zhanghaomin/datas/musiccap/music_data/I_wT76iYBdQ.wav"} +{"id": "IbD0zpcimgM", "caption": "This music is instrumental. The tempo is fast with a spirited small pipe harmony with rhythmic foot tapping. The music is upbeat, engaging, sharp, humming, haunting, droning and cheerful. This a live performance with ambient sounds of people talking and static as this is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/IbD0zpcimgM.wav"} +{"id": "IbJh1xeBFcI", "caption": "The song is an instrumental. The song is medium tempo, with disc scratching tones, whistling tones, keyboard accompaniment and techno drumming. The sound is poor audio quality, with ambient room noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/IbJh1xeBFcI.wav"} +{"id": "IbaQjxGDT-o", "caption": "Electronic dance music features a repeating melody played by an electronic sound. The beat of the music is being driven by a kick drum played on every beat, a hi-hat played four times every beat and some sampled claps played on beats two and four. In the background one can hear an altered female voice singing a short melody. Another electronic/synth sound can be heard in the background having sparse interventions. The music is meant to be danced to.", "audio": "/zhanghaomin/datas/musiccap/music_data/IbaQjxGDT-o.wav"} +{"id": "IcPbxJRbe5g", "caption": "This classical song features the main melody played on a harpsichord. The mood of this song is happy. This song does not have any percussion or any other instruments. There are no voices in this song. This song can be played for aristocracy.", "audio": "/zhanghaomin/datas/musiccap/music_data/IcPbxJRbe5g.wav"} +{"id": "Ie5FO_BetOE", "caption": "This song contains a bass-melody repeating itself like an arpeggio. On top of that you can hear a digital string sound in the mid range playing a simple melody along with short female choir sequences that also sound digital. In the background you can hear explosions that do not belong to the song itself. This is an amateur recording and of poor audio-quality. This song may be playing in an arcade/action game.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ie5FO_BetOE.wav"} +{"id": "IePfzUzlDng", "caption": "This is a hard rock music piece. There is a male vocalist singing melodically in the lead. The main tune is being played by the overdriven electric guitar with the bass guitar playing in the background. The rhythm is being played by the acoustic drums. The atmosphere is energetic. There is a vintage sound. This piece can be played in the background at a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/IePfzUzlDng.wav"} +{"id": "Ieef9l-gWN8", "caption": "This song features a marimba playing a melody on the higher register. The marimba plays a repetitive melody. This is accompanied by a clarinet and flute playing a dissonant chord together. This song is relaxing. It has a dreamy sound. This song can be played at the beginning of a dream sequence in a children's animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ieef9l-gWN8.wav"} +{"id": "Ife1WaGirdQ", "caption": "This is a medieval sounding music piece. There is a virtual harp playing the main melody while strings are holding the root notes of the tune. The use of these sounds induces a story-telling atmosphere similar to a bard's song. This piece would suit well with historical/adventure movies or video games. It could also be used in the background at a theater play.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ife1WaGirdQ.wav"} +{"id": "IhNPDueFVSo", "caption": "The clip has no melodic instruments. It is mainly built of a complex persuasive rhythm played on the drums, and a repeated phrase by a male speaker in a raspy vocal. In the background, we have a soulful male voice chanting the same phrase repeatedly, and a female screaming voice once roughly every two bars.", "audio": "/zhanghaomin/datas/musiccap/music_data/IhNPDueFVSo.wav"} +{"id": "IiBgER0W8iA", "caption": "This song contains e-guitars playing melodies and rhythmic strumming that are spread to both sides of the speakers. A male voice is singing a melancholic melody in a higher key sitting in the middle of the track. This song may be playing while walking through the park while listening to this song with headphones.", "audio": "/zhanghaomin/datas/musiccap/music_data/IiBgER0W8iA.wav"} +{"id": "IiJciyiQBDw", "caption": "The low quality recording features a drawers opening sound effects followed by a background orchestra music. The recording is extremely noisy, as it was probably recorded with a poor quality microphone or a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/IiJciyiQBDw.wav"} +{"id": "IizUHzmcPGA", "caption": "The recording features a brass quartet playing in a reverberant space. It consists of synchronized trombone melody and it sounds passionate, epic and powerful.", "audio": "/zhanghaomin/datas/musiccap/music_data/IizUHzmcPGA.wav"} +{"id": "Ij1-640aafg", "caption": "This music is instrumental. The tempo is medium with a short,electric guitar riff and a male voice doing an introduction to a demo. The video is a tutorial/review of an electric guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ij1-640aafg.wav"} +{"id": "IjP5kKfgBiI", "caption": "The low quality recording features a groovy piano melody, played over, groovy bass guitar, punchy kick and snare hits, shimmering hi hats, shimmering crash cymbal and short electric guitar lick. It sounds energetic, fun, happy, joyful and like an in-game video game sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/IjP5kKfgBiI.wav"} +{"id": "Ikdb_jA9ehU", "caption": "The low quality recording features a DJ scratching effect at the beginning of the loop, after which a synth wave song drops. The song consists of groovy synth bass, percussive tinny elements, shimmering hi-hats, punchy snare and kick hits, soft crash cymbals and wide simple bells melody. It sounds energetic and judging by the arrangement, it's a background song for some kind of video.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ikdb_jA9ehU.wav"} +{"id": "IlUcHzBzZvg", "caption": "A male vocalist sings a lively hip hop. The tempo is fast with energetic drumming, groovy bass lines and keyboard accompaniment with female backup vocals. The song is incoherent and muffled with a loud scratching like sound dominating the audio. The audio is chaotic, confusing, incoherent and unpleasant to the ears.", "audio": "/zhanghaomin/datas/musiccap/music_data/IlUcHzBzZvg.wav"} +{"id": "Ime3FHuQG4k", "caption": "The low quality recording features a live performance of a metal song and it consists of energetic male vocal singing over energetic drums, distorted bass guitar and electric guitar riff. It sounds crushed, energetic, distorted and noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ime3FHuQG4k.wav"} +{"id": "In44gO8Ej90", "caption": "This is a house music piece with Brazilian elements. There is a male vocal that starts by shouting and then starts repeating the same word over and over. In the rhythmic background, there is a repetitive electronic drum beat with a very strong low end. It is a very loud piece. This music could be used in nightclubs and sports venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/In44gO8Ej90.wav"} +{"id": "InKK8z21UYo", "caption": "Tablas and accordion lead a coed group chant with a male lead singer. Sounds spiritual.", "audio": "/zhanghaomin/datas/musiccap/music_data/InKK8z21UYo.wav"} +{"id": "InQs7K9MqaI", "caption": "This is a kids music piece. There are child vocals singing. There are idiophone instruments that sound much like a xylophone and a music box. There is a simple bass line in the background. The atmosphere is cheerful. This piece could be playing in the background at a theme park, especially for a carousel.", "audio": "/zhanghaomin/datas/musiccap/music_data/InQs7K9MqaI.wav"} +{"id": "InfQUMh935c", "caption": "The low quality recording features a live performance of a rock song and it consists of a passionate male vocal singing over groovy bass guitar, wide electric guitar melody, shimmering hi hats, punchy kick and snare hits. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/InfQUMh935c.wav"} +{"id": "Inuq5W98ktA", "caption": "A female vocalist sings this romantic love song. The tempo is slow with a melodic violin harmony, groovy bass line, rhythmic acoustic guitar and keyboard accompaniment. The song is soft, mellow, romantic, emotional, sentimental, melancholic and gentle. This. The song is a cover of a Classic Elvis Presley song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Inuq5W98ktA.wav"} +{"id": "Ip6FptuXHyk", "caption": "An almost clean e-guitar is playing a gentle melody in a minor chord that is repeating itself. This song may be played at a backing track to practice along.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ip6FptuXHyk.wav"} +{"id": "IpYw4nKPx5o", "caption": "This is an afrobeat music piece. The melody is being played by a vibrant orchestra of brass sections with a saxophone lead, a keyboard, an electric guitar and a bass guitar. In the rhythmic background, there is an afrobeat acoustic drum beat played with numerous percussion instruments. The atmosphere is playful. The piece could be used in the soundtrack of an action-filled movie or TV series. It could also be used in the soundtrack of an action video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/IpYw4nKPx5o.wav"} +{"id": "Ipow026xzVw", "caption": "A male singer sings this cool and animated melody with backup singers in vocal harmony. The song is medium tempo with steady drumming rhythm, groovy bass line, organ accompaniment and horns playing. The song is entertaining and cheerful. The audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ipow026xzVw.wav"} +{"id": "IqGB4nQIAcQ", "caption": "This clip is an instrumental. The tempo is medium with an electric guitar solo lead. There are no other instruments used. There is an interaction between two men in the interval . The music is powerful, loud and skilled and the speech indicates that this is probably a tutorial on how to play the guitar or an interview.", "audio": "/zhanghaomin/datas/musiccap/music_data/IqGB4nQIAcQ.wav"} +{"id": "IqV9wp0IeAo", "caption": "The low quality recording features a flat male vocal talking and playing a low pitched harmonica. It sounds like a tutorial and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/IqV9wp0IeAo.wav"} +{"id": "Ir82jewhXCo", "caption": "This song starts off with 2 heartbeats. The sound of a knife being honed is played. After this, we hear a short blasting sound. This is followed by a fast paced percussion starting off with a roll and then playing -two strokes on a hi-hat and one stroke on the snare drum. A male voice speaks in a narrative voice with a distortion guitar playing power chords in the background. The rest of the instruments continue playing in the background while the voice is narrating.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ir82jewhXCo.wav"} +{"id": "IrIKXhYuwuU", "caption": "The song is an instrumental. The song is medium tempo with a loud horn playing sonorously, ambient wind noise, thunder rolling, birds chirping and a harpsichord playing rhythmically . The song is scary and eerie. The song is an instrumental soundtrack for a spooky film.", "audio": "/zhanghaomin/datas/musiccap/music_data/IrIKXhYuwuU.wav"} +{"id": "ItLWKIhe58c", "caption": "This song is an instrumental. The tempo is fast with vigorous drumming, thumping bass lines and keyboard arrangement with sounds of an ambulance or police van, menacing voices, grunting, incoherent vocal riff and whooshing sound of wind. This song is aggressive, vigorous, energetic trippy, trance like with the syncopated music giving it a eerie, sinister, creepy vibe. This song is a Hard Rock/Goth Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/ItLWKIhe58c.wav"} +{"id": "ItSLkF6O3Mk", "caption": "This song features a drum pad being played. This is following a pattern of fast strokes in a rhythmic pattern. There are no other instruments in this song. There are no voices in this song. This song can be played in an instructional video.", "audio": "/zhanghaomin/datas/musiccap/music_data/ItSLkF6O3Mk.wav"} +{"id": "ItstzW7xuDU", "caption": "In this clip, a wooden percussion instrument is being played in a rhythmic manner. The instrument has a hollow sound, which also creates a partially melodic tone amidst the percussion.", "audio": "/zhanghaomin/datas/musiccap/music_data/ItstzW7xuDU.wav"} +{"id": "IwdjPDw6o5I", "caption": "The low quality recording features a jazz song that consists of groovy soft drums, smooth bass and saxophone solo, over which there is shoe tapping. It sounds like it is a live performance and like something you would watch in a theatre. It is a bit noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/IwdjPDw6o5I.wav"} +{"id": "IwobTmzjOiQ", "caption": "The low quality recording features a wide brass melody played over mellow piano melody. The recording is very noisy and it sounds like it was recorded in a large room.", "audio": "/zhanghaomin/datas/musiccap/music_data/IwobTmzjOiQ.wav"} +{"id": "IwqD859w2_E", "caption": "A fiery, passionate flamenco duet between a nylon string guitar player and a clapping dancer. The guitar playing is virtuosic, employing flamenco strumming and fast scales. The rhythms are complex and additive.", "audio": "/zhanghaomin/datas/musiccap/music_data/IwqD859w2_E.wav"} +{"id": "IyJ3a5uuCOs", "caption": "An accordion is playing short notes on the offbeat along with soft snare hits being played with brushes. A bass is playing straight, changing the note on every beat. Another accordion is answering the yodeling male voice with a short melody. The male voice is loud, clear and sings a melody in the higher register. A guitar-like instrument is strumming chords in the higher register. The instruments are panned to the left and right side of the speakers. This song may be playing at a concert in the countryside.", "audio": "/zhanghaomin/datas/musiccap/music_data/IyJ3a5uuCOs.wav"} +{"id": "Iz611KubW70", "caption": "This is a French opera/opera-ballet music piece. There is no singer in this piece. The only instrument that is being played is a harpsichord. The sound and the tunes are reminiscent of the medieval era. There is a theatrical feel to the piece. This piece could be used in the soundtrack of a historical drama that takes place in the medieval era. It could also be used as an accompaniment piece for a theater play or a ballet dance performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/Iz611KubW70.wav"} +{"id": "J0RzvGnQxD0", "caption": "This is an instrumental rock music jam. The only instrument is a clean-sounding electric guitar playing an arpeggio with an added echo effect. The atmosphere is calming. Although the recording quality is a bit low, this piece could be playing in the background of a rock bar after a decent mix is applied.", "audio": "/zhanghaomin/datas/musiccap/music_data/J0RzvGnQxD0.wav"} +{"id": "J0lA7ZDfPLE", "caption": "This instrumental song features a distortion guitar playing a guitar solo. The guitar starts playing an ascending pattern followed by a sweep picking lick. This is followed by an alternate picking pattern. The ending of this solo consists of a sweep picking lick using string skipping technique. There are no other instruments in this song. There is no voice in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/J0lA7ZDfPLE.wav"} +{"id": "J0t4VMnXDNM", "caption": "A DJ plays a cool groove with some female vocals. The song is medium tempo with a steady drumming rhythm, scratch disc percussions, and percussive bass line. The song is exciting and groovy. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/J0t4VMnXDNM.wav"} +{"id": "J1-Qvl7u2TI", "caption": "This audio contains environmental noises as ocean waves sounds; seabirds singing; a train passing by and a synth pad playing a short rising sound. This song may be playing in an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/J1-Qvl7u2TI.wav"} +{"id": "J1gZRam89EE", "caption": "This is a yodeling music piece. There is a female vocalist that is singing happily in the lead. The melody is provided by medium and high pitch woodwinds. In the background, the bass line is played by an upright bass while the rhythm is provided by an acoustic drum. The atmosphere is very lively. This piece could be used in the soundtrack of a comedy movie or a children's show.", "audio": "/zhanghaomin/datas/musiccap/music_data/J1gZRam89EE.wav"} +{"id": "J1nIXpnMe1U", "caption": "This is an instrumental rendition of a Christian gospel music piece. There is a melodeon and a piano accordion playing the tune. The atmosphere is festive and cheerful. This piece could be playing in the background at a charity event.", "audio": "/zhanghaomin/datas/musiccap/music_data/J1nIXpnMe1U.wav"} +{"id": "J2BDMndrvhA", "caption": "This song has a typical trap-beat with a very overdriven kick/bassline. A synthesizer key sound is playing a melody that repeats itself an octave higher. The male rapper sounds aggressive and is almost shouting along with ad-lips. This song may be playing while working out.", "audio": "/zhanghaomin/datas/musiccap/music_data/J2BDMndrvhA.wav"} +{"id": "J2R8Ab25reU", "caption": "This song contains a digital drum playing a techno groove with an overdrive kick and snare.A synth lead sound is playing a slightly offkey melody along with some reversed digital sounds converting into a high pitch note. This song may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/J2R8Ab25reU.wav"} +{"id": "J48F0e0guSQ", "caption": "A female vocalist sings this energetic song. The tempo is fast with furiously energetic drumming, intense electric guitar, groovy bass lines, keyboard harmony, vocal backup and synthesiser arrangements. The song is passionate, spirited,youthful, buoyant, punchy, energetic and animated. The audio is muddy and incoherent. This song is Pop Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/J48F0e0guSQ.wav"} +{"id": "J4DrdTy52kg", "caption": "This is a classical, uptempo salsa song full of percussive instruments playing the rhythm. An e-bass is playing underlining the percussion. While the brass instruments are playing a catchy melody along with the male backing singers. Then the male higher range singer takes over and responds to the backing vocals. This song may be playing in a salsa bar or latin festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/J4DrdTy52kg.wav"} +{"id": "J4tjy-0CNm4", "caption": "This is the live performance of a Huayno folk music piece which belongs to the Andean region. There is a female vocalist singing at a high-pitch, almost at a screeching range. The tune is being played by a violin and an Andean/Peruvian harp. The atmosphere is eccentric. This piece could be playing from a radio in a movie taking place in a mountainous Latin American village.", "audio": "/zhanghaomin/datas/musiccap/music_data/J4tjy-0CNm4.wav"} +{"id": "J7d3nuS9wqg", "caption": "The low quality recording features a kids song played through a toy and it consists of childish vocal singing over groovy piano chords and funky guitar melody. It is noisy, in mono and it sounds happy, fun, but also thin, messy, muffled and crushed.", "audio": "/zhanghaomin/datas/musiccap/music_data/J7d3nuS9wqg.wav"} +{"id": "J7fVdG7Zd3A", "caption": "This music is an electric guitar solo. The tempo is medium with a haunting and lilting electric guitar riff.The music is minimalist with no accompaniment. It is youthful, energetic, passionate , melodic and pensive.", "audio": "/zhanghaomin/datas/musiccap/music_data/J7fVdG7Zd3A.wav"} +{"id": "J7jVR6y6REA", "caption": "A male and female news reporter engage in a funny vocal banter. The background music is in medium tempo with harmonium accompaniment and subtle percussive rhythm with sudden percussion hits. The vocal dialogue is funny and engaging. The audio quality is overall very poor with painfully high gains.", "audio": "/zhanghaomin/datas/musiccap/music_data/J7jVR6y6REA.wav"} +{"id": "J8lCxfaiHeo", "caption": "The low quality recording features a passionate male vocal, alongside harmonizing female vocals, singing over simple bass guitar, punchy snare, soft kick hits, acoustic rhythm guitar, groovy piano melody and shimmering hi-hats. It sounds emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/J8lCxfaiHeo.wav"} +{"id": "J8pkQfYlJA4", "caption": "The song is an instrumental. The tempo is fast with three percussionists performing a rhythmic groove with sounds breathed by clapping body parts and tapping the floor. The song is energetic and highly engaging. The audio quality is average and performed live.", "audio": "/zhanghaomin/datas/musiccap/music_data/J8pkQfYlJA4.wav"} +{"id": "J9PJI1UwIQ4", "caption": "The song is an instrumental. The song is medium tempo with various percussion hits, groovy bass line, steady drumming rhythm and keyboard playing beep tones. The song is experimental and groovy. The song is modern electronic dance music with a poor audio quality recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/J9PJI1UwIQ4.wav"} +{"id": "J9ZlahUawkg", "caption": "A male vocalist sings this enthusiastic Rock. The tempo is fast and upbeat with a vigorous electric guitar lead and harmony, hard hitting drums and amplified keyboard. The music is an energetic, boisterous, youthful, enthusiastic, engaging, pulsating and electrifying Hard Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/J9ZlahUawkg.wav"} +{"id": "JC41M7RPSec", "caption": "This recording is full of environmental sounds. Birds singing, wind going, someone walking through water and water-dripping sounds. At the end a strongly reverbed kalimba starts playing a melody.\nThe whole thing sounds relaxing and would fit good into a documentary or a meditation session guided by sounds of nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/JC41M7RPSec.wav"} +{"id": "JCfZpSEH77Y", "caption": "The low quality recording features a blues song that consists of a passionate fruity male vocal singing over harmonica licks, acoustic rhythm guitar, groovy bass and steel guitar melody. It sounds passionate and soulful. The recording is noisy and since the bass sound is leaning towards the right channel of the stereo image - the stereo image is unbalanced.", "audio": "/zhanghaomin/datas/musiccap/music_data/JCfZpSEH77Y.wav"} +{"id": "JCsuOzlwJqA", "caption": "The track features a Christmas song with no vocals. The melody is very simple and it's played by a Schoenhut Piano that's accompanied by subtle strings. The atmosphere is positive and very Christmas-like.", "audio": "/zhanghaomin/datas/musiccap/music_data/JCsuOzlwJqA.wav"} +{"id": "JD9LYReBGXU", "caption": "The low quality recording features a harpsichord melody being played. There are some keyboard tapping sounds in the right channel of the stereo image. The whole sound is leaning towards the right channel, making the stereo image unbalanced. The recording is noisy and it sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/JD9LYReBGXU.wav"} +{"id": "JDBu-3VCyWc", "caption": "This is a live performance of a recital. A loud accordion is holding the melodic background as the clarinet performs a solo on top of it. There is also a now (Romanian pan flute) being played. A male voice starts speaking on the recording possibly retelling a story or a poem. There is a tragic atmosphere. This piece could be used in the soundtracks of drama movies or TV series with an Eastern European/Balkan setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/JDBu-3VCyWc.wav"} +{"id": "JDWPJ1AiDKc", "caption": "This recording contains a male voice talking and then playing a blues riff on a clean e-guitar. This song may be playing as part of a video tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/JDWPJ1AiDKc.wav"} +{"id": "JDrnf3vldLw", "caption": "This song contains an acoustic drum playing a kick and snare together on every beat along with a tambourine shaker. An e-bass is playing a distorted bassline. Two e-guitars are playing a modified melody on top of that. A female and male voice are singing together creating harmony. This song may be playing in a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/JDrnf3vldLw.wav"} +{"id": "JEJLTct-014", "caption": "Funk music featuring a bass guitar, synth melody, synth counter melody and group vocals, with a snare on the backbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/JEJLTct-014.wav"} +{"id": "JFGNmPzPXeA", "caption": "Someone is playing an acoustic drum groove with a snare that uses reverb. An e-bass is playing a sub bassline. An e-guitar is strumming short rhythmic chords on the backbeat giving this music its reggae vibe. A keyboard is playing a sound in the mid range and another keyboard responds with a countermelody playing a melody using a brass sound. In the background you can hear people talking. This song may be playing live at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/JFGNmPzPXeA.wav"} +{"id": "JFJuEOZx1K4", "caption": "This rock and roll song features a male voice singing the main melody. There is a female and male backing voice singing in harmony. This is accompanied by percussion playing a simple beat in common time. The bass plays a 12 bar blues lick. The organ fills in between lines. The mood of this song is happy. The quality of audio is low. This song can be played at a celebration party.", "audio": "/zhanghaomin/datas/musiccap/music_data/JFJuEOZx1K4.wav"} +{"id": "JHkcCXF5vII", "caption": "The song is an instrumental song. The song is medium tempo with a marching drum rhythm, string section harmony, brass instruments playing and a horn section playing various harmonies. The song is exciting and adventurous in nature. The song is a movie soundtrack, and the audio quality is quite poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/JHkcCXF5vII.wav"} +{"id": "JHvLuYk6TfI", "caption": "This folk song features a kora being played in waltz time. This starts off with the strings being plucked in waltz time followed by a descending run. The waltz plucking is played twice more followed by another descending run. There are no other instruments in this song. There are no voices in this song. This is an instrumental song. This song can be sampled and played in a hip-hop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/JHvLuYk6TfI.wav"} +{"id": "JI26wmUPcrM", "caption": "A male singer sings this rap vocals with backup singers in harmony. The song is medium tempo with typing and beeping tones, followed by steady drumming rhythm, groovy bass and keyboard harmony. The song is energetic and exciting. The song has a home video intro followed by a rap song.", "audio": "/zhanghaomin/datas/musiccap/music_data/JI26wmUPcrM.wav"} +{"id": "JIoA1KsfioQ", "caption": "The Electro song loop features a build up section that consists of intense siren sound effect, synth bass swell, arpeggiated synth melody, punchy kick layered with synth stabs, snare rolls and some claps. It sounds suspenseful, intense and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/JIoA1KsfioQ.wav"} +{"id": "JKbUVdMJAO8", "caption": "Someone is playing a fast paced melody running up and down a scale. This is an amateur recording. This song may be playing soundcheck with a band.", "audio": "/zhanghaomin/datas/musiccap/music_data/JKbUVdMJAO8.wav"} +{"id": "JKihzveDE5g", "caption": "The low quality recording features an ambient song that consists of sustained synth pad chord and mellow strings melody. It sounds mystical, soft, mellow, relaxing and calming - like something you would hear while having a massage.", "audio": "/zhanghaomin/datas/musiccap/music_data/JKihzveDE5g.wav"} +{"id": "JL4Z2_5Q7sU", "caption": "The low quality recording features a metal song that consists of an aggressive male vocal, alongside wide harmonizing background vocals, singing over punchy kick and snare hits, shimmering cymbals, distorted bass guitar and wide aggressive electric guitar melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/JL4Z2_5Q7sU.wav"} +{"id": "JL9Xxzf9e2A", "caption": "This music is an Electronic instrumental. The tempo is fast with synthesiser arrangements. It has an incessant, burgeoning rhythm. The music is youthful , captivating, psychedelic, trippy, groovy, trance EDM/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/JL9Xxzf9e2A.wav"} +{"id": "JLYb7DwCaQU", "caption": "The song is an instrumental. The tempo is medium with a slick drumming rhythm starting with a solid drum introduction, strong bass line and a blues guitar solo. The song is energetic and passionate. The audio quality is excellent.", "audio": "/zhanghaomin/datas/musiccap/music_data/JLYb7DwCaQU.wav"} +{"id": "JNW76fDWkA0", "caption": "The song is an instrumental. The song is medium tempo with an improvised percussion instrument playing steady rhythm and rattling sounds. The song has a very basic percussion rhythm. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/JNW76fDWkA0.wav"} +{"id": "JN_VJCJhC4Y", "caption": "The low quality recording features a live performance of dub song manically rapped by flat male vocals, followed by energetic drums, groovy bass and offbeat key chords. The recording is noisy and chaotic a bit, as it is probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/JN_VJCJhC4Y.wav"} +{"id": "JNw0A8pRnsQ", "caption": "Solo electronic bagpipe.", "audio": "/zhanghaomin/datas/musiccap/music_data/JNw0A8pRnsQ.wav"} +{"id": "JNwt0afB1fQ", "caption": "The Rock song features a flat male vocal singing over arpeggiated electric guitar melody located in the right channel of the stereo image, groovy bass guitar, punchy kick and snare hits and shimmering hi hats. The stereo image is unbalanced because of the electric guitar, which makes it lean towards the right channel. It sounds energetic, groovy, happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/JNwt0afB1fQ.wav"} +{"id": "JOhK7oq9KtU", "caption": "The low quality recording features a live performance of an indie song and it contains passionate female vocal singing over arpeggiated electric guitar melody and shimmering shakers. It is a bit noisy, there are some crowd noises and it sounds passionate, emotional and like an intro section of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/JOhK7oq9KtU.wav"} +{"id": "JOkuwbhMxbQ", "caption": "This music is an upbeat instrumental of the popular Christmas carol, \u2018Jingle Bells\u2019. The tempo is fast with electronic arrangements and digital drumming. The music is buoyant, happy, cheerful, festive, perky, enthusiastic,energetic and high spirited. This song is a Techno Remix.", "audio": "/zhanghaomin/datas/musiccap/music_data/JOkuwbhMxbQ.wav"} +{"id": "JP637fg_ZC0", "caption": "The music features no vocals and the main melody is made with a theremin. The sound is wobbly and quirky. In the background there are subtle strings that contrast the main melody by sustaining chords. This is a song you could hear in a movie about aliens.", "audio": "/zhanghaomin/datas/musiccap/music_data/JP637fg_ZC0.wav"} +{"id": "JPVRBbdykSw", "caption": "This is an instrumental electronic music piece. It has a high-pitched synth bass playing in a dissonant manner as the lead. The background consists of an ambient synth that is constantly switching between two chords and electronic percussion that keeps on reverberating. The dissonance and the character of the sounds create a very eerie atmosphere that is the perfect fit for a dystopian video-game soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/JPVRBbdykSw.wav"} +{"id": "JPZlyvPNZj4", "caption": "This music clip is a bass electric guitar instrumental. The tempo is medium fast with the guitarist playing an enthusiastic riff after giving instructions. No other instruments are used and the talking at the beginning of the audio clip indicates that this is a tutorial or instructional video.", "audio": "/zhanghaomin/datas/musiccap/music_data/JPZlyvPNZj4.wav"} +{"id": "JR-1k8GHYAw", "caption": "This is a punk rock piece that is being sung by children. The main vocal is a boy singing in a shouting manner while slightly straying off-key. There is an electric guitar and acoustic drums in the backing track of a song. The piece is clearly targeted for children. Therefore, it would fit perfectly in a play date or birthday party for little kids. The music is also suitable for an advertisement jingle that is targeted at kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/JR-1k8GHYAw.wav"} +{"id": "JRfU_hF1wdM", "caption": "The low quality recording features a jazzy song that consists of shimmering hi hats, repetitive cowbell, snappy rimshots and smooth bass in the right channel, short brass stabs and groovy piano chords in the left channel of the stereo image and electric guitar solo melody in the middle. The stereo image of the song is a bit unbalanced, due to the spreadness of low frequency sounds throughout the stereo image. It sounds easygoing and percussive.", "audio": "/zhanghaomin/datas/musiccap/music_data/JRfU_hF1wdM.wav"} +{"id": "JRmfjBDKCpE", "caption": "A male vocalist sings this high energy Rock song. The tempo is fast with enthusiastic and skilled bass guitar lines, intense, hard hitting drums, groovy electric guitar accompaniment and rhythmic keyboard. The song is youthful, animated, spirited, animated,vigorous, incredibly vital and vivacious. This song is Hard Rock/ Progressive metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/JRmfjBDKCpE.wav"} +{"id": "JSLqi_TsMzs", "caption": "The excerpt starts off with 3 bass drum beats after which an explosion and a crumbling sound can be heard. After this, downward sliding strings or a similar instrument in timbre can be heard creating a sort of scary effect. In the background wind sounds can be heard throughout.", "audio": "/zhanghaomin/datas/musiccap/music_data/JSLqi_TsMzs.wav"} +{"id": "JSdALuTneBM", "caption": "This music is instrumental. The tempo is fast with synthesiser and electronic arrangements and a boomy bass.There are sounds of shooting, beeps, bombing, blasts and sirens in the background identical to a Video game music. The audio quality is inferior so the music is loud, jarring and unpleasant to the ears. The music is aggressive, boisterous, destructive and chaotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/JSdALuTneBM.wav"} +{"id": "JSqyTVjYY6k", "caption": "This audio contains a catchy melody played by a brass instrument, maybe a saxophone and a keyboard. A horn is playing a bass in a lower register along with a drum. In the background you can hear people laughing. This is an amateur recording and of poor audio-quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/JSqyTVjYY6k.wav"} +{"id": "JU4CZ-GApu4", "caption": "This is a Jewish gospel music piece. There is a male vocalist singing melodically in the Hebrew language. A strings section is playing the melody with the acoustic guitar and the bass guitar in the backing. In the rhythmic background, the acoustic drums are playing a simple 4/4 beat. The atmosphere of this piece is religious/devotional. It could be used in Jewish religious events or related social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/JU4CZ-GApu4.wav"} +{"id": "JU6GUqRqbtI", "caption": "This is a big band jazz music piece. It is an instrumental piece. The main melody is played by a wide variety of the winds section composed of the saxophone, the trumpet, the flute and the clarinet. The piano and the upright bass provide backing structures. The rhythmic background consists of a jazz acoustic drum beat. The atmosphere is playful. This piece could fit perfectly in the soundtrack of a Disney-type animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/JU6GUqRqbtI.wav"} +{"id": "JUrYWttZJBM", "caption": "The low quality recording features a passionate reverberant female vocal singing over quiet resonating sound. The recording is noisy and it sounds passionate, soulful and cultural.", "audio": "/zhanghaomin/datas/musiccap/music_data/JUrYWttZJBM.wav"} +{"id": "JUwu4xOs8K4", "caption": "This is a Gujarati folk song. There is a female vocalist singing in a passionate manner. The melody is being played by a harmonium. The rhythm is being played by the tabla and little cymbals. The atmosphere is lively.", "audio": "/zhanghaomin/datas/musiccap/music_data/JUwu4xOs8K4.wav"} +{"id": "JV_IOR3DqiM", "caption": "The low quality recording features a kids song that consists of chiptune vocal singing over acoustic rhythm guitar. The recording is noisy, in mono and it sounds fun and happy, like something kids listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/JV_IOR3DqiM.wav"} +{"id": "JWNWCKdfpzM", "caption": "A male vocalist sings this pop song. The tempo is medium with keyboard accompaniment ,steady drumming, groovy bass, congas and bongos percussion and acoustic guitar accompaniment with vocal backup. The sound quality of the audio is inferior and there is the sound of chatter in the background .The song is fresh, simple, breezy, romantic, passionate, sentimental and youthful with a dance groove. This song is Regional Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/JWNWCKdfpzM.wav"} +{"id": "JXS5eW7g4HY", "caption": "The low quality recording features a pop song that consists of a passionate male vocal, alongside harmonizing background vocals, singing over people cheering sounds, shimmering hi hats, claps, snare rolls, groovy bass and wide electric guitar melody. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/JXS5eW7g4HY.wav"} +{"id": "JYYfw3id3ek", "caption": "This music is an enthusiastic Irish tenor Banjo instrumental. The tempo is fast with a lively, upbeat, soothing, emphatic, twangy, sweet, rich, and engaging with traditional and folksy groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/JYYfw3id3ek.wav"} +{"id": "JZWJlUdYpCU", "caption": "The Electro House song features sustained organ keys, chords, filtered drums, punchy kick hits layered with energetic crash and addictive synth lead melody. Right before the drop, there is a short snare roll. It sounds energetic, intense and exciting, as the song is preparing to drop.", "audio": "/zhanghaomin/datas/musiccap/music_data/JZWJlUdYpCU.wav"} +{"id": "JZnOGRCBW0I", "caption": "Two e-guitars are playing a melody with a little bit of reverb. The e-guitars sound clean. This is an amateur recording. This song may be jamming out with friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/JZnOGRCBW0I.wav"} +{"id": "JZyw6YUsGzo", "caption": "This song features three trombones playing different parts. One trombone plays the bass part. A second trombone outlines the chords being played. The third trombone plays the main melody. There are no other instruments in this song. There are no voices in this song. This is an instrumental song. The mood of this song is motivational. The song can be played in an adventure movie just before the adventure begins.", "audio": "/zhanghaomin/datas/musiccap/music_data/JZyw6YUsGzo.wav"} +{"id": "J_Raltj-6dk", "caption": "This is a Christmas music piece in the style of hip-hop. There is a child voice announcing the arrival of Santa. The male vocalist is rapping. There is a groovy bass line in the beat. The rhythmic background is provided by an electronic drum beat that has sleigh bells in it. The atmosphere is festive and amusing at the same time. This piece could be used in the soundtrack of a comedic Christmas movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/J_Raltj-6dk.wav"} +{"id": "JaGUY5ULTok", "caption": "This music is instrumental. The tempo is fast with a Didgeridoo harmony. There is minimal instrumentation with low, incessant droning bass notes. The music is intense, enthralling, powerful, velvety, blunt , meditative,hypnotic and trance like.", "audio": "/zhanghaomin/datas/musiccap/music_data/JaGUY5ULTok.wav"} +{"id": "JbWaSZPOh18", "caption": "This Regional Mexican song features a live recording of a male voice singing the main melody. The song starts with the cymbal played once and held so that it does not ring. Then the male voice sings one line with the crowd. The crowd shouts out in joy after a line is sung. The bass is played on a tuba. This is followed by trumpets playing a high pitched melody. This song is at a slow tempo. Apart from the initial cymbal sound, no other percussion is played. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/JbWaSZPOh18.wav"} +{"id": "Jcd63Ev7JXA", "caption": "Due to the sound quality and background cheering it can be assumed that this is a phone recorded audiofile. A male loud voice is singing a gospel song through a microphone that is overdriving through the speakers: He is accompanied by a tambourine, clapping and cheering from people while acoustic drums are backing him up. In the background you can hear an e-bass playing some licks as fill-ins. This song could be played in a gospel church or a disney movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Jcd63Ev7JXA.wav"} +{"id": "Jdy08IPLKdw", "caption": "This song is a mellow Christian hymn in a foreign language. The tempo is slow with soft piano, rhythmic acoustic guitar, steady drumming and keyboard harmony. The music is minimalist and the song is a prayerful, melodious, devotional, emotional and thankful Gospel Song/Hymn.", "audio": "/zhanghaomin/datas/musiccap/music_data/Jdy08IPLKdw.wav"} +{"id": "JiBAkAwK0GM", "caption": "This is a very poor quality recording of an electronic music piece played in the background of a dance video. There is an irritatingly high-pitched synth playing a repetitive melody while an electronic drum beat is in the rhythmic background. If an aggressive high-end cutoff was applied, samples could be lifted from this piece to be used in a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/JiBAkAwK0GM.wav"} +{"id": "Jj9orXFko0Y", "caption": "The low quality recording features a clock ticking and clock bells sounds, alongside some camera sounds. The recording is loud, noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/Jj9orXFko0Y.wav"} +{"id": "JjF1G5wgcvY", "caption": "This music is a lively Bagpiper instrumental. The tempo is fast with a piper playing a cheerful harmony on the bagpiper with an enthusiastic acoustic guitar accompaniment. The music is vibrant, vivacious, vigorous, engaging, cheerful and merry. The performance is live with a live audience and ambient sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/JjF1G5wgcvY.wav"} +{"id": "Jjr0_CbcYdg", "caption": "A female vocalist sings this Hindi Bhajan. The tempo is slow with a harmonium accompaniment and tabla rhythm. The song is mellow, soft, devotional, inspiring,insightful, emotional and persuasive. This song is a Hindi Devotional Bhajan.", "audio": "/zhanghaomin/datas/musiccap/music_data/Jjr0_CbcYdg.wav"} +{"id": "Jk2mvFrdZTU", "caption": "A male vocalist sings this energetic pop song. The tempo is fast with piano accompaniment, bright digital drumming, synthesiser arrangements and groovy bass lines. The song is youthful, fresh, catchy, vivacious, upbeat, sprightly and buoyant with a dance groove. This song is a Hip-Hop Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Jk2mvFrdZTU.wav"} +{"id": "JlzlNpttvVM", "caption": "The Disco song features a passionate male vocalist singing over funky electric guitar melody, groovy bass, punchy kick and snare hits, shimmering hi hats and groovy synth keys melody. It sounds groovy, funky and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/JlzlNpttvVM.wav"} +{"id": "JmbrGzgxrJ4", "caption": "This is an R&B/pop dance music piece. There is a versatile female vocalist singing melodically. There is a keyboard and an electric guitar playing the melody while there is a groovy bass guitar line in the background. The rhythmic background is provided by an electronic drum beat. The atmosphere is urban and danceable. This piece could be used in the soundtrack of a romantic comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/JmbrGzgxrJ4.wav"} +{"id": "JnfMv9ti9Sw", "caption": "This song is an instrumental. The tempo is slow. The musician is playing the Happy Birthday song very deliberately.", "audio": "/zhanghaomin/datas/musiccap/music_data/JnfMv9ti9Sw.wav"} +{"id": "JoBRbtAnbVM", "caption": "This ambient song features a female voice using a delay effect so that the words are repeated. This is accompanied by a cymbal played on every beat. No other percussion is played. The bass plays the root note of the chord. There are multiple synth layers in the background. One layer of synth plays a haunting sound which sounds like a string section in the background. Another layer of synth plays a high pitched ring modulated sound toward the end of the track. This song can be used in a gym or workout video.", "audio": "/zhanghaomin/datas/musiccap/music_data/JoBRbtAnbVM.wav"} +{"id": "JorNR3IXDyc", "caption": "The instrumental music features a marimba playing a simple melody in unison with another similar instrument and a xylophone accompanying them with fast repeating notes. A tambourine is playing once every beat. A drummer plays a repeating rhythm and drives the rhythm forward.", "audio": "/zhanghaomin/datas/musiccap/music_data/JorNR3IXDyc.wav"} +{"id": "JpMHnsdsCiY", "caption": "This is an instrumental punk rock/dub music piece. There is a distorted electric playing the main tune with a bass guitar in the background. The rhythmic background consists of a loud and rapid acoustic drum beat. The atmosphere is aggressive. This piece could be used in the soundtrack of a violent video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/JpMHnsdsCiY.wav"} +{"id": "Jq2w30NYstQ", "caption": "A male singer sings this poignant love song. The song is medium tempo with a steady drumming rhythm, strong bass line, keyboard accompaniment, guitar accompaniment and percussion hits. The song is emotional and romantic. The song audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/Jq2w30NYstQ.wav"} +{"id": "JqmOqYtQqB8", "caption": "This music is an Electronic instrumental. The tempo is fast with punchy, synthesised music and thumping drum beats on the drum machine. The music is youthful, energetic, enthusiastic,loud, buoyant, punchy, pulsating and electrifying. The sound quality is of inferior quality and there is a bit of static.", "audio": "/zhanghaomin/datas/musiccap/music_data/JqmOqYtQqB8.wav"} +{"id": "JrOV2Xz2djA", "caption": "A male vocalist sings this energetic rock song. The song is fast tempo with emphatic drumming, groovy bass lines, funky electric guitar feedback and keyboard accompaniment, with animated, high pitched backup. The song is youthful, energetic,spirited, intense, psychedelic and passionate. This song is Hard Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/JrOV2Xz2djA.wav"} +{"id": "JsHTGDW5dgw", "caption": "The low quality recording features an electro song that consists of percussive elements, echoing hi hats, shimmering shakers, cowbell, claps and repetitive percussive bass loop. At the end of the loop, there are snare rolls and risers layered together, building up tension for the drop. It sounds exciting and suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/JsHTGDW5dgw.wav"} +{"id": "Js_3Aa214xY", "caption": "This game music is an orchestral song with no lyrics. It starts off with low pitched instruments playing an eerie melody. A percussion instrument plays in the background. After the first four counts, a hissing sound is played. This song has no voices. This is a slow tempo song. It can be used in the game lobby of a game involving wizards.", "audio": "/zhanghaomin/datas/musiccap/music_data/Js_3Aa214xY.wav"} +{"id": "Jsk3ZUGvP-o", "caption": "The song is an instrumental. The song is medium tempo with two accordion players playing on harmony and no other instrumentation. The music is romantic and passionate. The song has gypsy music roots.", "audio": "/zhanghaomin/datas/musiccap/music_data/Jsk3ZUGvP-o.wav"} +{"id": "JtLNRHVGQuw", "caption": "This music is a soulful instrumental. The tempo is medium with a harmonica melody with a background track which is muffled. The melody is of a popular Spanish Classic song. This music is a Harmonica instrumental of Besame Mucho.", "audio": "/zhanghaomin/datas/musiccap/music_data/JtLNRHVGQuw.wav"} +{"id": "Jvj2WqgVy78", "caption": "Tuned bell-sounds are playing a melody walking down and up a scale along with some loud digital beeping noises also playing a melody. This song may be playing as an annoying doorbell.", "audio": "/zhanghaomin/datas/musiccap/music_data/Jvj2WqgVy78.wav"} +{"id": "JvqCsVj0I4k", "caption": "The low quality recording features a pop song that consists of groovy piano chords, harmonizing background vocals, punchy kick and snare hits, shimmering shakers, groovy bass and muffled female vocals singing over it. It sounds energetic, happy, fun and addictive - like something you would hear on a radio.", "audio": "/zhanghaomin/datas/musiccap/music_data/JvqCsVj0I4k.wav"} +{"id": "JvvnL7UnCGA", "caption": "This is a hardcore rave music piece. There is a female vocalist singing melodically. The high-pitched synth is playing the main theme while an ambient synth with medium-pitched characteristics is playing in the background. A very loud and fast-paced electronic drum beat carries the rhythmic background. The atmosphere is very energetic. This piece could be used in an anime or a video game. It could also be used in DJ sets at rave venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/JvvnL7UnCGA.wav"} +{"id": "JxwRvkjNJQ0", "caption": "This heavy metal song features a male voice singing at a distance in the background. Distortion guitars play a riff and end with a power chord. This is accompanied by percussion playing an aggressive metal beat. The bass follows the rhythm guitar for the beginning of the song and later plays licks while the notes of the distortion guitars are sustained. The mood of this song is aggressive. This song can be played on the entrance of a WWE star into the arena.", "audio": "/zhanghaomin/datas/musiccap/music_data/JxwRvkjNJQ0.wav"} +{"id": "JzJCn-puzS4", "caption": "This techno song features a female voice singing only in non-lexical vocables. This is accompanied by programmed percussion. The percussion pauses after one and a half bars. It plays again after half a bar in an eighth note pattern. A synth plays a melody that is the same as that of the voice. The melody is repetitive. This song has a happy mood. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/JzJCn-puzS4.wav"} +{"id": "JzRb1OVpat0", "caption": "Two viola/cello like instruments being played with a bow and a lot of tremolo. It sounds like they are complaining and crying, full of pain. They both are playing a melody as they are talking to each other. A low basslike drumhit/kick with a long release is hitting one single note. You can hear some white noise in this recording. This song may be playing in a sad and disturbing scene of a retro movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/JzRb1OVpat0.wav"} +{"id": "K-0qmhvJyzE", "caption": "This is an instrumental kids song. There is a xylophone and a music box playing a cute and cheerful melody. The atmosphere of the piece is cozy and relaxing. This piece could be used as a backing track for a nursery rhyme. It could be used in the soundtrack of a movie targeted at children.", "audio": "/zhanghaomin/datas/musiccap/music_data/K-0qmhvJyzE.wav"} +{"id": "K-zkbbliQcI", "caption": "The low quality recording features a hip hop song that consists of harmonizing male vocals, alongside background male vocals in the left channel and rough, repetitive male vocals in the right channel of the stereo image, singing over addictive synth lead melody, straight synth piano chords, boomy 808 bass and snaps. Right before the bass drops, there is a short snare roll. It sounds groovy and addictive, like something you would hear in clubs a lot.", "audio": "/zhanghaomin/datas/musiccap/music_data/K-zkbbliQcI.wav"} +{"id": "K0x_DxNxtbk", "caption": "This clip is an instrumental. The tempo is slow. The music is a single, loud , resounding electric guitar riff that ends abruptly and after a pause is followed by a muffled, fast melody. The music is tense, suspenseful, sinister, anticipatory and thrilling.", "audio": "/zhanghaomin/datas/musiccap/music_data/K0x_DxNxtbk.wav"} +{"id": "K1PzpuR6CqY", "caption": "This is a swing jazz music performance. The main melody is being played by trumpets while the brass section as a whole provides the melodic background. There is an upright bass playing an eighth-note walking bass line. The acoustic drums are playing a swing jazz beat in the rhythmic background. There is a smooth and vibrant atmosphere to the piece. It could be playing in the soundtrack of a video game. This piece could also be used in the soundtracks of historical drama pieces.", "audio": "/zhanghaomin/datas/musiccap/music_data/K1PzpuR6CqY.wav"} +{"id": "K2h6UiZSoZ4", "caption": "This is Electronic Dance music. The tempo is fast with synthesiser arrangements, punchy Digital drum rhythm, electronic sounds and a recurring, catchy vocal riff with the sound of talking in the background.The music is obscure as it is an amateur recording . It is buoyant, youthful, energetic, enthusiastic, and pulsating with a dance groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/K2h6UiZSoZ4.wav"} +{"id": "K55v5p5DEPE", "caption": "This is a latin dance music piece in the style of salsa. There are male vocals shouting in the lead. There is a crisp synth sound playing the melody with the backing of a piano and a bass guitar. The rhythm is played by the latin percussive elements. There is a sensual atmosphere to this piece. It could be playing in the background at a latin nightclub.", "audio": "/zhanghaomin/datas/musiccap/music_data/K55v5p5DEPE.wav"} +{"id": "K5ilD6nEJ-g", "caption": "This is an instrumental song. We have piano, brass, and string instruments. The piano melody is light and dainty, but also uplifting and positive. The pattern is like a dance among the clouds. The string instruments are violins, and the brass being the french horn. The brass gives the clip the sense of importance and grand atmosphere.", "audio": "/zhanghaomin/datas/musiccap/music_data/K5ilD6nEJ-g.wav"} +{"id": "K63Z_abB314", "caption": "This instrumental song features a lute being played. This is played using fingerstyle. The song sounds like a folk song. There are no other instruments in this song. There are no voices in this song. This song can be played in a documentary scene with green hills at the backdrop. The mood of this song is happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/K63Z_abB314.wav"} +{"id": "K6DSH7MSeOA", "caption": "This audio contains a didgeridoo with reverb panned to the right side of the speakers, some white noise risers that sound like wind. Various synth pads are playing drones in different ranges. This song may be playing while meditation or falling asleep.", "audio": "/zhanghaomin/datas/musiccap/music_data/K6DSH7MSeOA.wav"} +{"id": "K6KbEnGnymk", "caption": "The low quality recording features a live performance of mellow arpeggiated piano melody playing in the background and theremin sad lead melody playing on top of it. It sounds emotional, sad, muffled and dull, as the recording is lacking some high frequencies.", "audio": "/zhanghaomin/datas/musiccap/music_data/K6KbEnGnymk.wav"} +{"id": "K8On7nUJuP8", "caption": "The track is of a baby crying incessantly being consoled by a song being played on a phone. The song is medium tempo with a male singer singing to Bollywood music. The audio quality is extremely poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/K8On7nUJuP8.wav"} +{"id": "K9zE9x2ccJk", "caption": "Empowering youthful music with heavily processed female vocals and compressed drum samples. big claps on the backbeat and a funky electric bass part accompany. The production aims at high fidelity but comes across sounding over produced and ultimately amateur.", "audio": "/zhanghaomin/datas/musiccap/music_data/K9zE9x2ccJk.wav"} +{"id": "KB4e9v_5uTE", "caption": "The low quality recording features a live performance that consists of a tuba solo melody and some loud impact in the background. The recording is noisy, loud and distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/KB4e9v_5uTE.wav"} +{"id": "KB79k456DhI", "caption": "This is a pop-rap/dance-rap piece. There is a male vocal rapping joined by the occasional samples of other rappers. The electronic drums and the electronic percussion are providing the rhythmic background. There is a strong 808-style syncopated bass. The atmosphere has a groovy feeling to it. This song could be used in nightclubs and sports venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/KB79k456DhI.wav"} +{"id": "KChjW89XOF0", "caption": "This is a recording of two flamenco guitarists playing a captivating latin american rhythm. It's upbeat and suitable for dancing. The one guitarist strums chords in the percussive flamenco style, while the other guitarist plays flamenco lead with arpeggios and licks. The performance is live and outside. There is reverb applied to the lead guitar. Both are playing on nylon strings.", "audio": "/zhanghaomin/datas/musiccap/music_data/KChjW89XOF0.wav"} +{"id": "KCs_VPmsnKo", "caption": "This children's song features a male voice singing the main melody. Other voices sing vocables in harmony in the beginning and after the lyrics are sung. This is accompanied by percussion playing a fast beat. The bass plays the root notes of the chords. A synth plays an ascending lick with the vocables in the beginning. When the words are sung, the synth plays the same melody as the main voice. This is a moderate tempo song. The mood of this song is happy. This song can be sung in a children's action movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/KCs_VPmsnKo.wav"} +{"id": "KCytKo5LzCc", "caption": "The low quality recording features a cover of a children's song and it consists of an emotional girl vocal singing over acoustic rhythm guitar located in the right channel of the stereo image, which makes the stereo image unbalanced. The recording is a bit noisy and It sounds fun, happy, emotional and innocent.", "audio": "/zhanghaomin/datas/musiccap/music_data/KCytKo5LzCc.wav"} +{"id": "KDuusOmEMHg", "caption": "The Children song features wide harmonizing vocals singing over shimmering shakers, groovy bass, punchy snare, soft kick hits, groovy piano chords, shimmering bells melody and acoustic rhythm guitar chords. It sounds addictive, happy and fun - as every children's song should sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/KDuusOmEMHg.wav"} +{"id": "KDzy3ZL626U", "caption": "This is the opening jingle of a TV show that is in the style of a mashup. There is a male voice speaking and then burping. There is a melodic pad playing at random occasions. A female vocalist can be heard singing with a keyboard melody and an electronic drum beat very briefly. Then the male voice and the pad returns. There is a chaotic atmosphere. Separate samples from this piece could be used in both beat-making and DJ sets/remixes.", "audio": "/zhanghaomin/datas/musiccap/music_data/KDzy3ZL626U.wav"} +{"id": "KE-TVQhdCbs", "caption": "A mid-tempo two chord vamp on a roots rock song. The music is instrumental, featuring a strummed acoustic guitar, drum set, electric guitar, and pedal steel. The feeling is melancholic.", "audio": "/zhanghaomin/datas/musiccap/music_data/KE-TVQhdCbs.wav"} +{"id": "KEp2NhraIZI", "caption": "This is a classical music piece. There is a wide range of strings in the orchestra playing a lively melody while a horn is in the lead. The atmosphere is lighthearted. This piece could be used in the soundtrack of a documentary where there are natural movements happening in the scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/KEp2NhraIZI.wav"} +{"id": "KFB1raoIhoU", "caption": "A drum is playing a groove with a strong snare sound. An e-guitar is strumming short funky chords on the offbeat creating a reggae style rhythm. A male backing voice is shouting in the same offbeat. An e-bass is playing a soft funky bassline while a male voice sings in the mid range. A trumpet is adding a short melody on top spicing up the good vibes. This song may be playing in a car racing video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/KFB1raoIhoU.wav"} +{"id": "KHjEIheD-Cg", "caption": "The song is an instrumental. The song is in medium tempo with a classical guitar playing a lilting melody in accompaniment style. The song is emotional and romantic. The song is a romantic instrumental song.", "audio": "/zhanghaomin/datas/musiccap/music_data/KHjEIheD-Cg.wav"} +{"id": "KJHqQ5aKu8U", "caption": "This music is instrumental. The tempo is medium with a lilting middle eastern kind of melody on a string instrument that sounds like a santoor along with a classical tabla accompaniment. The music is traditional, classical, captivating, romantic and nostalgic. This music is an Eastern Classical instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/KJHqQ5aKu8U.wav"} +{"id": "KKgYvcfrxj4", "caption": "The Hard Rock song features a repetitive filtered male vocal over shimmering hi hats, down sweep, wide aggressive electric guitar chords, distorted bass guitar, echoing electric guitar licks, punchy kick and punchy snare hits. It sounds energetic, aggressive and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/KKgYvcfrxj4.wav"} +{"id": "KLFoZA8btu4", "caption": "The low quality recording features shimmering cymbals, brass melody, woodwinds melody, groovy piano, groovy bass and soft kick and snare hits played altogether. It sounds chaotic and manic.", "audio": "/zhanghaomin/datas/musiccap/music_data/KLFoZA8btu4.wav"} +{"id": "KMQmM12G9Z4", "caption": "A male vocalist sings this animated and upbeat pop song. The song starts with a slow tempo with male vocals and soft but emphatic piano accompaniment and cello drone, and a whirring sound like a camera rolling. Post this the song picks up to an upbeat tempo with hard hitting drumming, cymbal rides, upbeat synthesiser harmony and electronic instruments. The song is a ,vibrant, spirited, bouncy, punchy, vivacious, youthful Electronic Dance music/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/KMQmM12G9Z4.wav"} +{"id": "KN9vuaQvld0", "caption": "The low quality recording features a R&B/Soul song that consists of snappy rimshots layered with shimmering tambourine, mellow piano melody, punchy kick, smooth bass and synth keys melody. At the very end of the loop, there is a short snippet of passionate female vocal singing over the instrumental. It sounds emotional, passionate and hopeful.", "audio": "/zhanghaomin/datas/musiccap/music_data/KN9vuaQvld0.wav"} +{"id": "KOb-tRHYK68", "caption": "This techno song features a synth lead playing the main melody. This is accompanied by programmed percussion playing a simple kick focused beat. The hi-hat is accented in an open position on the 3-and count of every bar. The synth plays the bass part with a voicing that sounds like a cello. This techno song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/KOb-tRHYK68.wav"} +{"id": "KPG9s_s8siA", "caption": "A Vibraphone and a marimba are playing a composition with a lot of reverb. This is an amateur recording. This song may be playing at a school concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/KPG9s_s8siA.wav"} +{"id": "KPnIFb7T7VM", "caption": "The song feels funky and soulful. There's a rumbling funky bassline, and an electric guitar playing intermittent licks. The drumming sticks on the hi-hats for the feeling of a build-up;. The female vocalist has a powerful, soulful voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/KPnIFb7T7VM.wav"} +{"id": "KPymcVenomk", "caption": "This low quality audio features a guitar playing flamenco style. The guitar plays only two chords. The sound of foot-stomping can be heard. A female voice sings vocals in the background. This song has no other instruments. This song can be played for a flamenco dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/KPymcVenomk.wav"} +{"id": "KRKX_UtYV9c", "caption": "Someone is playing bongos or congas holding a simple groove while someone is playing a shaker here and there. Someone is playing a didgeridoo. The whole recording is full of a little reverb and the percussion is panned to the left and right side of the speakers. This song may be playing while meditating or doing slow movements as dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/KRKX_UtYV9c.wav"} +{"id": "KSFND-AdqZs", "caption": "This audio contains a e-guitar running through a tremolo effect that gets into faster modulation speed. This is an amateur recording and may be used for educational purposes.", "audio": "/zhanghaomin/datas/musiccap/music_data/KSFND-AdqZs.wav"} +{"id": "KSye2ifWZ_Y", "caption": "Percussions and tablas are playing a steady rhythm while a female voice sings a sad sounding melody in a high pitched voice. String instruments are playing along with the melody while others are adding a short melody at the end of a musical phrase. This song may be playing in a Hindi-movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/KSye2ifWZ_Y.wav"} +{"id": "KTqf_FXZygM", "caption": "This clip features low quality audio. This clip is of a male voice singing the main melody. The voice is emotional. This is accompanied by a piano playing chords. There are no other instruments in this song. The theme of this song is romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/KTqf_FXZygM.wav"} +{"id": "KU2bOYiBX28", "caption": "This music is an upbeat instrumental. The tempo is fast with keyboard harmony, enthusiastic drumming and electronic arrangements. The harmony sounds like a synthetic sound of a bagpiper . The music is chaotic, quirky, playful, and cheerful.", "audio": "/zhanghaomin/datas/musiccap/music_data/KU2bOYiBX28.wav"} +{"id": "KUE_I30--AY", "caption": "The song is an instrumental. The tempo is medium with a slick drumming rhythm and a DJ creating cool melodies by scratching and manipulating spinning music discs. The song is energetic and has a dance groove. The song is electronic dance music with poor audio quality and is at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/KUE_I30--AY.wav"} +{"id": "KV4noVyGHa4", "caption": "This is a calm and relaxing meditation track. We hear the ringing of a tibetan bowl and its resonance. This would be useful for any tranquil environment primed for meditation.", "audio": "/zhanghaomin/datas/musiccap/music_data/KV4noVyGHa4.wav"} +{"id": "KV99GJg0tvA", "caption": "This is a doo wop music piece. There are male vocals singing melodically. The main tune is being played by the electric guitar and the keyboard while the bass guitar is playing in the background. The rhythm is provided by the acoustic drums. The atmosphere is danceable and joyful. This piece could be playing at a dance club for an oldies night.", "audio": "/zhanghaomin/datas/musiccap/music_data/KV99GJg0tvA.wav"} +{"id": "KWpsFxRTGkI", "caption": "This song is an electronic instrumental. It is medium tempo with a recurring vocal riff, steady drumming, table turner arrangement and distorted sounds like metal scratching. The audio is muffled, making it difficult to hear the finer elements of the song.The repetitive beats and rhythm give it a trippy, psychedelic and trance vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/KWpsFxRTGkI.wav"} +{"id": "KXRngbBe0bg", "caption": "The song is an instrumental. The tempo is medium with a guitar playing lead and rhythm with differences ranging from echo tones to distorted high gains. The song is a guitar reverb pedal test or demonstration. The audio quality is poor with high gains.", "audio": "/zhanghaomin/datas/musiccap/music_data/KXRngbBe0bg.wav"} +{"id": "KXuB62SMFvA", "caption": "This is a classical music piece with its main tune played on the theremin instrument. At the same time, a piano plays the chords in the background. It is a unique instrumental piece with a bizarre atmosphere. It could take place in the soundtrack of an art movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/KXuB62SMFvA.wav"} +{"id": "KY5TY6ovKQg", "caption": "This is an amateur recording of a Ugandan traditional music piece. The piece is instrumental and percussive in nature. The amadinda (which is a Ugandan xylophone) is playing a joyful tune. The atmosphere is playful.", "audio": "/zhanghaomin/datas/musiccap/music_data/KY5TY6ovKQg.wav"} +{"id": "KZ8gBHLNmH0", "caption": "A male sings this resounding chant. The tempo is slow with no instrumentation. The chants are musical verses, meditative choral harmony.it is prayerful, calming, pensive, sacred, prayerful and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/KZ8gBHLNmH0.wav"} +{"id": "K_G_k1WTdoc", "caption": "The low quality recording features a classical song that consists of a harpsichord melody that sounds emotional and passionate. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/K_G_k1WTdoc.wav"} +{"id": "K_ZuxYxxT60", "caption": "The low quality recording features a passionate trumpet melody. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/K_ZuxYxxT60.wav"} +{"id": "KabP9iNokps", "caption": "This is a live recording. The percussion is beatboxing and the melodic element of the instrumental is a flute player who plays a low riff which ascends towards the end.", "audio": "/zhanghaomin/datas/musiccap/music_data/KabP9iNokps.wav"} +{"id": "KauCO8zH5bw", "caption": "The low quality recording features a flat male vocal talking, after which there is a synth key melody playing. The recording is noisy, in mono and it sounds happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/KauCO8zH5bw.wav"} +{"id": "KbDLu4VozGg", "caption": "This song contains acoustic drums playing a kick on every half-beat along with an e-bass playing a repeating bassline along with an e-guitar. Another e-guitar is playing long notes with a lot of reverb in a higher register. Another guitar is playing a counter melody in an even higher key. A male voice is singing in a higher key while being backed by another male voice singing a harmony in an even higher key. This song may be playing live at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/KbDLu4VozGg.wav"} +{"id": "Kd7aHdOwh0I", "caption": "This is an instrumental jam. The only instrument being played is a clean sounding electric guitar. The guitar solo has simple, groovy tunes played in an improvised manner. The atmosphere is easygoing. Parts of this recording could be sampled to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/Kd7aHdOwh0I.wav"} +{"id": "KdNhYvN4Xoo", "caption": "An acoustic drum is playing a faster groove along with a bassline and a harmonica playing a chord on the offbeat and in a lower key. A e-guitar is playing a melody in the mid range. There are some background noises that remind me of someone brushing his/her teeth. This song may be playing live at a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/KdNhYvN4Xoo.wav"} +{"id": "KduU8kmRsLg", "caption": "The song is an instrumental tolled by a guitarist introducing the lesson. The tempo is slow, a guitar playing gently with feedback buzz noise. The song is relaxing but has poor audio quality with a feedback noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/KduU8kmRsLg.wav"} +{"id": "KeSbjmMeyrY", "caption": "This song contains an acoustic piano playing a melody in the higher register playing mostly one note at a time. Celli is playing along the melody then changing into staccato strokes playing a melody in the low to high register. This song may be playing live during a dance scene in a musical.", "audio": "/zhanghaomin/datas/musiccap/music_data/KeSbjmMeyrY.wav"} +{"id": "KfAq7kxHjPk", "caption": "This song features a male voice singing the main melody. The first two lines are sung using the same melody and it culminates in the third line. This is accompanied by percussion playing a simple beat. The bass plays the root notes of the chords. The keyboard plays arpeggiated chords in the background. Another synth plays a windy pad voice throughout the song sounding like strings. This song has a holiday mood. This song can be played in a holiday movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/KfAq7kxHjPk.wav"} +{"id": "KfLxBjl-aBU", "caption": "The low quality recording features a didgeridoo melody and some water flowing sounds in the background, as it was recorded outdoors. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/KfLxBjl-aBU.wav"} +{"id": "KgMD2_Yhw7Y", "caption": "This music is instrumental. The tempo is fast with an intense, rigorous violin harmony, grim cello and keyboard harmony. The music is untiring, incessant, serious, grim, and staid. This music is a classical violin piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/KgMD2_Yhw7Y.wav"} +{"id": "KhXcEu7r6m8", "caption": "This song is an instrumental. The tempo is medium fast with dissonant rhythm on the drum machine with no vocals. This song is a pop instrumental with drums.", "audio": "/zhanghaomin/datas/musiccap/music_data/KhXcEu7r6m8.wav"} +{"id": "Ki7Bxz1CThI", "caption": "This song features a middle-eastern melody played on a flute. This song has no other instruments. There are no voices in this song. This is an amateur recording. This song can be played at a desert party.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ki7Bxz1CThI.wav"} +{"id": "KiFQFxJphjI", "caption": "This song is full of a digital key/pad sound taking a lot of space with a harmonic melody slightly panned to the right side of the speakers. The drums are a simple kick and clapping snare sound. Accompanied by a digital one note hit on the kick. A male doubled and panned voice is singing as backing vocals when a male mid ranged voice starts rapping. This song may be playing during a relaxing car ride with friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/KiFQFxJphjI.wav"} +{"id": "KikHXfUanJk", "caption": "We hear a twangy electric guitar on which some arpeggiated chords are played. The music style is a bluesy country rock style.", "audio": "/zhanghaomin/datas/musiccap/music_data/KikHXfUanJk.wav"} +{"id": "KjJj5-HvSvQ", "caption": "This is a box opening video. There is a male voice speaking and kids shouting. A rock music piece starts playing with a common sounding electric guitar tune and a simple acoustic drum beat. The atmosphere is generic.", "audio": "/zhanghaomin/datas/musiccap/music_data/KjJj5-HvSvQ.wav"} +{"id": "KjMRf4egAyA", "caption": "A female singer sings this soulful melody. The song is slow tempo with a guitar playing a subtle bass line and no other instrumentation. The song is romantic and emotional. The song is soul music with jazz and black gospel influences. The audio quality is poor as it is recorded casually at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/KjMRf4egAyA.wav"} +{"id": "KkW6ZkmAlEw", "caption": "The low quality recording features a weird arrangement of low growly sounds, alarm sound effects and wide synth pad progression. It sounds weird and spacey, almost like outer space communication.", "audio": "/zhanghaomin/datas/musiccap/music_data/KkW6ZkmAlEw.wav"} +{"id": "Kkqbi6c_40k", "caption": "This audio contains someone playing an upright bass with a bow creating a dissonant melody and tension. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/Kkqbi6c_40k.wav"} +{"id": "KlD1u-EDx_g", "caption": "This audio contains a fast complex drumpart playing along with a synth lead sound playing a complex melody in a high pitch. Then the song changes to a more calm part with a piano before changing back to action with a distorted e-guitar playing along the low notes with a e-bass. This song sounds very fast paced and may be playing in an arcade fighting game.", "audio": "/zhanghaomin/datas/musiccap/music_data/KlD1u-EDx_g.wav"} +{"id": "KlVO3gu-j70", "caption": "This song is an instrumental song. There are no voices. An accordion plays in a waltz beat. The main melody starts off later when a marimba plays high pitched notes. Other accordions join and play in harmony in the background. There is no percussion in this song. The mood of this song is happy and upbeat. This song can be used in a retro scene of a movie involving a happy couple.", "audio": "/zhanghaomin/datas/musiccap/music_data/KlVO3gu-j70.wav"} +{"id": "KmBaE7ozWow", "caption": "A male vocalist sings this melodic jazz/blues. The tempo is medium fast with a piano accompaniment, groovy bass lines, infectious drumming and guitar accompaniment. There is a sound of syncopated ukulele and another string instrument playing over the song. The song is melodic and ambient but the superimposed strings melody is making it chaotic, busy, confusing and confusing.", "audio": "/zhanghaomin/datas/musiccap/music_data/KmBaE7ozWow.wav"} +{"id": "KnZeEWVHaLc", "caption": "The low quality recording features a metallic scraping sound effect, soft scratching sound effect, water leaking sound effect, breathy flute melody and birds chirping sound effects. It sounds relaxing and calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/KnZeEWVHaLc.wav"} +{"id": "KoAGZ_dB8MM", "caption": "A female singer sings this eerie melody. The song is medium tempo with a rolling bells keyboard harmony, and other ambient echo tones and harp tones. The song is haunting and unsettling. The audio quality is very poor and not enjoyable.", "audio": "/zhanghaomin/datas/musiccap/music_data/KoAGZ_dB8MM.wav"} +{"id": "KoP8T0QqzeM", "caption": "This music is a lively instrumental using a maracas. The tempo is fast with a bongos accompaniment . The music is a duel between the two hand percussion. It is lively, vigorous and vibrant.", "audio": "/zhanghaomin/datas/musiccap/music_data/KoP8T0QqzeM.wav"} +{"id": "Kojo5khAAS0", "caption": "The song is an instrumental. The tempo is medium, with a dj creating vinyl scratch tones to a steady drumming rhythm, groovy bass line and a keyboard accompaniment. The song is youthful and groovy. The song is a techno dance rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/Kojo5khAAS0.wav"} +{"id": "KpRHRh9PaRU", "caption": "Melancholic Instrumental music with wide panned acoustic guitars strumming, glockenspiel or bells following the chord progression, and a syncopated electric bass guitar over a slow rock beat that fades into simple steady solo piano.", "audio": "/zhanghaomin/datas/musiccap/music_data/KpRHRh9PaRU.wav"} +{"id": "KpwdlYIdtfs", "caption": "The song is an instrumental. The song is medium tempo with a loud crash tone which undulates percussively and fades. The song is of poor audio quality and probably faded with a lot of humming noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/KpwdlYIdtfs.wav"} +{"id": "Kqo7am5oq0U", "caption": "The low quality recording features a fruity male vocal humming. In the first half of the loop, there is a lot of reverb on it, which progressively disappears. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Kqo7am5oq0U.wav"} +{"id": "KqtlecvEOGw", "caption": "The low quality recording features a drums solo at the very beginning of the loop, after which a pop song starts playing and it consists of a passionate female vocal singing over buzzy synth lead melody. The drums solo contains snare roll and shimmering cymbals. Overall it sounds exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/KqtlecvEOGw.wav"} +{"id": "KrK8Giu9ZUc", "caption": "The music excerpt starts off with a Latin band with instruments such as trombones, trumpets, upright bass, flute and latin percussion instruments. After a few seconds the band stops and a female voice starts to sing a voice that starts in the high register and moves to the low one. Right between these two moments one can hear claps coming from a crowd of people. Towards the ending of the excerpt the voice finishes singing the melody and the band starts again.", "audio": "/zhanghaomin/datas/musiccap/music_data/KrK8Giu9ZUc.wav"} +{"id": "KrmG43H1u70", "caption": "The low quality recording features a reverberant electric guitar melody. It sounds mellow, chill, relaxing and like a player is trying out his reverb pedals. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/KrmG43H1u70.wav"} +{"id": "KsFCPOKAH60", "caption": "The low quality recording features a breathy flute melody playing over acoustic rhythm guitar. The recording is noisy, in mono and it sounds passionate and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/KsFCPOKAH60.wav"} +{"id": "Kt2MwCHV3Ko", "caption": "This techno song features a female voice singing the main melody. This is accompanied by programmed percussion playing a techno beat. The kick is played at every count. The hi-hi-hat is played on every 'and' of the count. The bass plays a disco pattern using the root notes of the chords being played. Synth bursts are played in between lines. This song can be played in a club. The audio quality is low.", "audio": "/zhanghaomin/datas/musiccap/music_data/Kt2MwCHV3Ko.wav"} +{"id": "KubrAnJ0o0o", "caption": "This folk song features a choir singing the main melody. This is backed by percussion playing a simple beat in common time. A tambourine plays a continuous beat. The bass is played on a tuba. The tuba plays the root and fifth notes of the chords. At the beginning, a trumpet and accordion play a melody in harmony. The accordion continues to play chords in staccato while the choir sings the melody. The mood of this song is happy. This song can be played in a party where there is a large gathering.", "audio": "/zhanghaomin/datas/musiccap/music_data/KubrAnJ0o0o.wav"} +{"id": "KurvLmoKCog", "caption": "The song is an instrumental. The tempo is medium with various horns like trumpets, trombones and tubas playing blaring lots in harmony. The song is mysterious and ominous in nature. The song is a wildlife documentary soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/KurvLmoKCog.wav"} +{"id": "KxUcwQ5BEBk", "caption": "A percussionist plays various drum rhythms at a medium tempo. The tempo is me doom with no harmony instruments. The song is exciting and energetic. The audio quality is poor and sounds like a music tutorial for drummers.", "audio": "/zhanghaomin/datas/musiccap/music_data/KxUcwQ5BEBk.wav"} +{"id": "KxVbdGPAfjE", "caption": "This music is a calm Chinese instrumental melody. The tempo is slow with use of traditional chinese string instruments like the Guzheng and Pipa harmony accompanied with violin symphony and chimes. The music is soft, mellow, melancholic, meditative, dreamy, healing and ethereal.", "audio": "/zhanghaomin/datas/musiccap/music_data/KxVbdGPAfjE.wav"} +{"id": "KxZ0yDfyaJw", "caption": "This is a hardcore hip-hop/gangsta rap music piece. There are male vocals taking turns rapping and when they are not rapping they are shouting ad-libs. There is a fuzzy synth bass playing the repeated melodic theme of the beat while the rhythm consists of an electronic drum beat with gunshot effects every now and then. The atmosphere is urban and violent. This piece could be included in the soundtrack of a crime movie that takes place in the big city. It could also be used in the soundtrack of a crime video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/KxZ0yDfyaJw.wav"} +{"id": "KxjiEi2Eywk", "caption": "The song is an instrumental. The tempo is slow with a lion playing an emotional solo, string section harmony, strong drumming rhythm and a steady bass line. The song is emotional and inspiring. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/KxjiEi2Eywk.wav"} +{"id": "KyRJP_fDrbk", "caption": "Low-fidelity recording of a female singer displaying vocal virtuosity and melisma, accompaniment by strummed steel string acoustic guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/KyRJP_fDrbk.wav"} +{"id": "KyjeM7J-Pz4", "caption": "This music is an electronic dance instrumental. The tempo is fast with synthesiser arrangements, digital drumming, DJ mixer and electronic effects. The sound quality is inferior and muffled with static and booming sounds. The performance is live with ambient sounds of people whistling, cheering and talking. This is an Electro Pop instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/KyjeM7J-Pz4.wav"} +{"id": "KzvdKLdBw3s", "caption": "The low quality recording features a soul song sung by passionate female vocalists over mellow piano chords, smooth bass, shimmering cymbals and punchy kick and snare hits. There are some crowd chattering sounds. It sounds emotional, passionate and heartfelt.", "audio": "/zhanghaomin/datas/musiccap/music_data/KzvdKLdBw3s.wav"} +{"id": "KzydTOkZty8", "caption": "The low quality recording features a bossa nova cover of a rock song and it consists of soft female vocals, alongside wide harmonizing vocals, singing over shimmering cymbals, snappy rimshots, funky electric guitar chords, smooth bass and mellow synth keys melody. It sounds jazzy and easygoing, like something you would hear as a live performance in a high end restaurant or jazz club.", "audio": "/zhanghaomin/datas/musiccap/music_data/KzydTOkZty8.wav"} +{"id": "KzzKguqINa8", "caption": "This is an instrument showcase jam. Different tracks are being played to show the features of a keyboard. Initially, there is a synth pad playing. Then, an acoustic sounding drum beat and a groovy bass line starts playing in the background of a brass sounding melody. The sounds are mostly generic. Parts of this recording could be sampled to be used in advertisement jingles.", "audio": "/zhanghaomin/datas/musiccap/music_data/KzzKguqINa8.wav"} +{"id": "L0-l1LIa22g", "caption": "The low quality recording features a reggae song that consists of passionate male vocals singing over shimmering hi hats, snappy snare, punchy kick, groovy bass, brass melody and funky electric guitar chords. It sounds chill and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/L0-l1LIa22g.wav"} +{"id": "L0oun9F67tg", "caption": "This is a Valentine's ballad. The male vocalist is singing gently in the Thai language. There is an acoustic guitar, a piano and a flute playing the melody interchangeably. There is a simple acoustic drum beat in the rhythmic background. The atmosphere of this piece is romantic. It could be used in romantic social media content in Thailand. It could also be used in romantic movies and TV shows that take place in Thailand.", "audio": "/zhanghaomin/datas/musiccap/music_data/L0oun9F67tg.wav"} +{"id": "L1fxVVl_1bM", "caption": "Someone is strumming chords on a distorted e-guitar while someone is playing a fast solo up the fretboard with another e-guitar. This song may be playing practicing solos at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/L1fxVVl_1bM.wav"} +{"id": "L1s-oPHsOac", "caption": "A male singer sings this exciting melody. The song is medium fast tempo with a groovy bass line, latin percussion, steady drum rhythm, groovy bass line and keyboard accompaniment. The song is exciting and fun. The song is a modern Latin pop dance hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/L1s-oPHsOac.wav"} +{"id": "L1s7KZgWXGc", "caption": "The Swing song features an echoing male vocal singing over smooth double bass, offbeat soft piano chords and widely spread sustained strings melody. It sounds easygoing, relaxing, smooth, warm and euphoric as it reminds of Christmas.", "audio": "/zhanghaomin/datas/musiccap/music_data/L1s7KZgWXGc.wav"} +{"id": "L2-EGNKzUAQ", "caption": "The Pop song features a passionate male vocal, alongside wide harmonizing background vocals, singing over clapping, shimmering cymbals, groovy bass and soft kick hits. It sounds addictive, happy and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/L2-EGNKzUAQ.wav"} +{"id": "L3ZtE3rD2nc", "caption": "The low quality recording features a buzzy vibrating sound while a rock song on a radio, or some other device that can reproduce music, in the background is playing. The recording is very noisy and it sounds like it was recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/L3ZtE3rD2nc.wav"} +{"id": "L3d4ajg0bhk", "caption": "This is a shofar being played. Two notes are being played. The first note is short and the second note is played at a higher pitch and for a longer duration. There is no voice in this song. There are no other instruments in this song. This song can be played in a movie scene where soldiers are given instructions for a battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/L3d4ajg0bhk.wav"} +{"id": "L47F51OmZXo", "caption": "Here we have two saxophonists playing baritone saxophones. They play a jazzy bebop song that's groovy and light-hearted in its tone.", "audio": "/zhanghaomin/datas/musiccap/music_data/L47F51OmZXo.wav"} +{"id": "L5CgdTtGv8o", "caption": "The instrumental music features three instruments and no voice. The bass guitar and electric guitar play the same melody in unison. The drums play a repeating but not simple rhythm. I can hear influences ranging from funk to rock so I would say that the music comes closest to the fusion genre.", "audio": "/zhanghaomin/datas/musiccap/music_data/L5CgdTtGv8o.wav"} +{"id": "L5UDz2PJ9sk", "caption": "The song is an instrumental. The tempo is medium with a bamboo didgeridoo being played percussively with no other instrumentation. The tone is deep and meditative in nature. The song is a demo play with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/L5UDz2PJ9sk.wav"} +{"id": "L5Uu_0xEZg4", "caption": "The song is a traditional south asian dance song with clear reggae influences. It is upbeat, vibrant and features bouncy reggae percussion. There are brass instruments playing cheerful motifs, and the lead singer has reverb and ample autotune applied to his vocal. There's a background vocalist adding shouted ad-libs to the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/L5Uu_0xEZg4.wav"} +{"id": "L8zjEoQFws8", "caption": "This music is instrumental. The tempo is slow with a lush guitar harmony with the sound of switches being turned on and off. The sound is rich, deep, intense and dense. This is a review audio between a Tortuga Martini vs an Analog Martini.", "audio": "/zhanghaomin/datas/musiccap/music_data/L8zjEoQFws8.wav"} +{"id": "L9GXrmmlYhE", "caption": "This is a live classical music performance. The piece is being performed by a brass orchestra. There is a trombone playing the lead melody while other trombones and a tuba play the bass backing. The atmosphere is epic. This piece could be playing in the soundtrack of a historical drama movie during the scenes of an army marching towards the enemy territory.", "audio": "/zhanghaomin/datas/musiccap/music_data/L9GXrmmlYhE.wav"} +{"id": "L9j9fCHHPeg", "caption": "Full band playing a complex arrangement, possibly south asian or middle eastern. The music features odd meters and polyrhythmic full band melodies played by electric bass guitar, synthesizer, flute, and a female vocalist singing an eastern scale with female background harmonies. The drum ensemble is thunderous and fiery with percussion from finger cymbals and tambourine.", "audio": "/zhanghaomin/datas/musiccap/music_data/L9j9fCHHPeg.wav"} +{"id": "L9xj_v65UhU", "caption": "This is the recording of a lesson video. There is male voice talking in an instructive manner. The only musical element in the background is a repeated electronic kick drum pattern that is being modified.", "audio": "/zhanghaomin/datas/musiccap/music_data/L9xj_v65UhU.wav"} +{"id": "LAHWV6fZwUk", "caption": "This is an indie rock/pop rock music piece. There is a male vocalist singing melodically with a telephone vocal effect. The melodic background consists of an electric guitar and a bass guitar. The rhythm is played by a simple acoustic drum beat. The atmosphere is groovy. This piece could be used during a badass scene in a thriller movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/LAHWV6fZwUk.wav"} +{"id": "LAeWwMC2EaI", "caption": "This instrumental song features an electric guitar. This guitar plays chords using open strings. The chords are played in a descending pattern initially. This is followed by the strings being plucked at the end of the song. This song has the characteristics of a Scottish folk song. There is the added reverb effect on the guitar sound. There are no other instruments in this song. This song can be played in a highway drive scene of a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/LAeWwMC2EaI.wav"} +{"id": "LAxCq-s84F8", "caption": "The low quality recording features a flat female vocal shortly talking on a very noisy microphone, after which a song fades in. The song consists of soft, reverberant female vocal singing over echoing dark rimshots, punchy kick and groovy piano melody. Overall it has a dark and mellow vibe to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/LAxCq-s84F8.wav"} +{"id": "LB0u0PrlDHU", "caption": "This music is an Electronic dance instrumental. The tempo is medium fast with punchy drum beats and groovy electronic arrangements.The music is buoyant, energetic, electric, pulsating, youthful and vigorous. The thumpy, rhythmic bass and drumming gives it a groovy dance beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/LB0u0PrlDHU.wav"} +{"id": "LByEH80c6Eg", "caption": "The music excerpt features a big band playing. The trumpets play a repeating melody, and thus, stand out the most. Throughout this passage one can hear sounds made by the shoes of tap dancers. The quality of the audio recording is not so good and this leads me to believe it was recorded at a live tap dancing show.", "audio": "/zhanghaomin/datas/musiccap/music_data/LByEH80c6Eg.wav"} +{"id": "LCMQXFKMLIM", "caption": "The low quality recording features an arpeggiated harp melody playing. It sounds passionate, emotional and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/LCMQXFKMLIM.wav"} +{"id": "LClTjcyNJSI", "caption": "The song is an instrumental movie soundtrack. The song is medium tempo with a choral section changing, trumpet playing melody and drums playing in a march rhythm. The song is majestic like a funeral march. The song is a movie soundtrack with a poor audio quality issue.", "audio": "/zhanghaomin/datas/musiccap/music_data/LClTjcyNJSI.wav"} +{"id": "LCzldLY3E4g", "caption": "This is an opening theme for a TV series. It is an instrumental piece. The main theme is being played by a loud brass section. There is a groovy synth bass line playing. The rhythmic background consists of a strong electronic drum beat. The atmosphere is energetic. This piece could be used in lifting samples for beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/LCzldLY3E4g.wav"} +{"id": "LEG7xkYOsWA", "caption": "A female vocalist sings this emotional song. The tempo is slow with guitar accompaniment and vocal backup. The song is soft, mellow, emotional and sentimental in a foreign language that sounds like a lullaby.This is a Pop Folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/LEG7xkYOsWA.wav"} +{"id": "LF-5BAUGvWI", "caption": "This song is a classical flamenco mixed with a HipHop groove drums playing a digital set along with a cowbell sound. A piano is playing a salsa melody in the low to high range. A trumpet sample is playing a short melody every fourth beat. A male voice is singing in a higher pitch along with backing vocals spread across both sides of the speakers. Then another male voice takes over rapping over the instrumental. This song may be playing with a speaker sitting on the bike cruising.", "audio": "/zhanghaomin/datas/musiccap/music_data/LF-5BAUGvWI.wav"} +{"id": "LFW4yPH1z3M", "caption": "Someone is playing a melody on an e-guitar with a tremolo effect. This song may be playing at home practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/LFW4yPH1z3M.wav"} +{"id": "LFYRuK8YstI", "caption": "This amateur recording features a male voice singing the main melody. This is accompanied by a banjo being strummed in a country rhythm. This song is sung at a moderate tempo. This song has a patriotic feel. There are no other instruments in this song apart from the tenor banjo. This song can be played in a patriotic American movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/LFYRuK8YstI.wav"} +{"id": "LGW99kSaf6M", "caption": "This audio contains someone playing a melody on a violin. A female voice is singing along in a high pitch. The background is filled with percussive instruments and a tambourine. This song may be playing during the celebration.", "audio": "/zhanghaomin/datas/musiccap/music_data/LGW99kSaf6M.wav"} +{"id": "LGi38MqlPFA", "caption": "This R&B song features a male voice singing the main melody in falsetto. There are other male voices singing backing vocals in harmony with the main voice. This is accompanied by percussion playing a simple beat. The bass plays the root notes of the chords without any flourishes or embellishments. A piano plays an arpeggiated pattern that changes with the chords of the song. A guitar strums chords using upstrokes. The mood of this song is romantic. The melody has a motown feel. This song can be played at the end credits of a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/LGi38MqlPFA.wav"} +{"id": "LGrAwQnZ6Bs", "caption": "The low quality recording features a shimmering, widely spread, bell melody. It sounds soft, mellow and haunting. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/LGrAwQnZ6Bs.wav"} +{"id": "LH3mAtCou6g", "caption": "This is an amateur music video of a male musician playing a mellow harmony on the banjo with another amateur musician accompanying him on the acoustic guitar. This song has a simple melody but the recording is loud and sharp.", "audio": "/zhanghaomin/datas/musiccap/music_data/LH3mAtCou6g.wav"} +{"id": "LHTA8VZGoMs", "caption": "This audio contains someone playing a bass solo melody. In the background you can hear something that almost sounds like a dog barking. This song may be playing while listening to a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/LHTA8VZGoMs.wav"} +{"id": "LJsYl38zPOQ", "caption": "The low quality recording features a cover of a rock song and it contains an ukulele bass guitar. The recording is in mono and very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/LJsYl38zPOQ.wav"} +{"id": "LK6zk03lPlM", "caption": "This is a jingle piece in the background of a tech comparison video. There are various sound effects such as clock ticking and a camera shutter. The electric guitar is playing the same chord repeatedly with electronic drum hits to create an aura of tension. This piece can be used in advertisement jingles. It could also be used in the soundtrack of reality competition programs.", "audio": "/zhanghaomin/datas/musiccap/music_data/LK6zk03lPlM.wav"} +{"id": "LKUYtvUHn0Y", "caption": "The drums and the e-bass are creating a reggae groove together with the e-guitar that is playing on the offbeat and with a lot of ping pong delay that is jumping back and forth on both sides of the speakers. The male voice is singing and a shaker is playing panned to the right side of the speakers. This song may be playing at an alternative vegan restaurant with an outside terrace.", "audio": "/zhanghaomin/datas/musiccap/music_data/LKUYtvUHn0Y.wav"} +{"id": "LKVSEQCLCLo", "caption": "The song is an instrumental. The song is medium tempo with various Latin percussion playing groovily to the sounds of a Rhodes organ melody. The song is romantic and passionate. The soundtrack is a demonstration for a keyboard model.", "audio": "/zhanghaomin/datas/musiccap/music_data/LKVSEQCLCLo.wav"} +{"id": "LKurVRvkmKc", "caption": "Someone is playing a melody on a zitar along with a shrutibox in the background. At the end male and female voices are chanting in the mid to high range and a percussive sound can be heard. This song may be playing live at a concert while meditating.", "audio": "/zhanghaomin/datas/musiccap/music_data/LKurVRvkmKc.wav"} +{"id": "LLDHkHHKYkI", "caption": "A male singer sings these whispering vocals. The song is medium fast tempo with a fast metal drumming rhythm, percussive bass line, keyboard accompaniment and various percussion hits. The song is tense and full of suspense. The song is a game soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/LLDHkHHKYkI.wav"} +{"id": "LM2C1eIUX9M", "caption": "This is a Christian gospel piece. A male vocalist who is probably a preacher is chanting as the lead while a church choir sings melodically. The piece is being sung in an African language. The atmosphere is peaceful and hopeful. This piece could be used in religious social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/LM2C1eIUX9M.wav"} +{"id": "LMGpKPavV4Q", "caption": "The song is an instrumental. The tempo is medium with a strong marching drum rhythm, with cymbal crashes and bass drum kicks, percussive bass line and amplified guitar playing rhythm. The audio quality is pristine and the soundtrack is high on adrenaline.", "audio": "/zhanghaomin/datas/musiccap/music_data/LMGpKPavV4Q.wav"} +{"id": "LNFAeJ06KVs", "caption": "The low quality recording features a flat male vocal talking over a double bass slap. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/LNFAeJ06KVs.wav"} +{"id": "LP1yZRsRllQ", "caption": "This music is an electric guitar instrumental. The tempo is medium with an amplified guitar lead harmony and synthesiser articulation. The music is not very clear as the recording quality is inferior, but the harmony is catchy, spirited and youthful.", "audio": "/zhanghaomin/datas/musiccap/music_data/LP1yZRsRllQ.wav"} +{"id": "LPA8RDzl-Ss", "caption": "This swing music is an instrumental piece. It starts off with the trumpets playing high pitched notes in harmony. The percussion starts to play with an intro roll. A wind instrument swell is played after the intro percussion roll. A wind instrument plays a repetitive lick after this followed by a piano playing chords at higher octaves in the spaces between the wind instrument licks. The bass plays the same lick on a lower octave. There are no voices in this song. This song can be played in a retro movie dance scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/LPA8RDzl-Ss.wav"} +{"id": "LQYd-dsz62M", "caption": "This is an instrumental power metal piece. There is an electric guitar playing the melody with the accompaniment of a keyboard. There is an acoustic drum beat in the rhythmic background. There is an aggressive atmosphere. This piece could be used in the soundtrack of an action video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/LQYd-dsz62M.wav"} +{"id": "LR3U4b_fVBc", "caption": "The song is an instrumental. The song is medium tempo and tempo changes occur later, with piano accompaniment, guitar solo, chord changes, steady drumming rhythm, rhythm guitar, and strong bass line . The song is an iconic rock hit and has a bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/LR3U4b_fVBc.wav"} +{"id": "LRUdmYcXFuM", "caption": "Someone is playing an indian bansuri with reverb along with a shrutibox. A keyboard is playing a soft bell sounding melody on top along with some strings. This is an amateur recording. This music may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/LRUdmYcXFuM.wav"} +{"id": "LRfVQsnaVQE", "caption": "This instrumental folk music features the main melody being played on a saxophone and a bowed instrument like a rebab. Both instruments play the same melody. This is accompanied by hand claps at every count of the bar. A bass drum is played on every count of the bar. A tambourine is playing a rhythmic beat. A bass is playing the same melody as the saxophone at a lower octave. There are no voices in this song. This song can be played at a celebration party.", "audio": "/zhanghaomin/datas/musiccap/music_data/LRfVQsnaVQE.wav"} +{"id": "LRz6Y6oltQ4", "caption": "The low quality recording features a saxophone solo melody being played. It sounds passionate, soulful and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/LRz6Y6oltQ4.wav"} +{"id": "LSaLPObrnZw", "caption": "This is a classical orchestral piece. The melody played on the trumpets feels like a prelude to an important, impressive moment. This music would suit any momentous occasion - like the countdown to a rocket launch.", "audio": "/zhanghaomin/datas/musiccap/music_data/LSaLPObrnZw.wav"} +{"id": "LTDle_h2YD8", "caption": "The low quality recording features an arpeggiated acoustic guitar melody, shimmering bells melody, plucked strings melody and sustained strings melody, followed by chime bells. There are some crowd cheering noises in the background. It sounds emotional and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/LTDle_h2YD8.wav"} +{"id": "LTG-uVV_6q0", "caption": "The low quality recording features a cover of a rock song and it consists of a passionate girl vocal singing over acoustic rhythm guitar chords and simple bass guitar. It sounds passionate, emotional, heartfelt, mellow and soft.", "audio": "/zhanghaomin/datas/musiccap/music_data/LTG-uVV_6q0.wav"} +{"id": "LUtBqNS27AQ", "caption": "This is a folk music piece from the Balkans. It is an instrumental piece performed with virtual sounds. The leading tune is played by a realistic accordion sound. There is an upbeat bass guitar following the rhythm of a fast tempo acoustic sounding drum beat. The atmosphere is cheerful. This piece could be the perfect accompaniment piece for a Balkan folk dancing course. It could also fit well in the soundtrack of a comedy movie that takes place in the Balkan region.", "audio": "/zhanghaomin/datas/musiccap/music_data/LUtBqNS27AQ.wav"} +{"id": "LWHUat2fo9w", "caption": "The music features a female voice singing a melody. An acoustic guitar accompanies the singer with strummed chords in a fast tempo. In the background one can hear castanets playing fast. The lower quality of the recording leads me to believe this is an older recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/LWHUat2fo9w.wav"} +{"id": "LWIHz5kao3g", "caption": "This is a hip hop song which features a young and energetic rapper who raps his lines with passion. The instrumental is minimal, and features a high pitched percussive type of synth which has a transient element. Then we hear a deep 808 sub bass. There's a snare once a bar throughout the clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/LWIHz5kao3g.wav"} +{"id": "LWLLN9INTII", "caption": "This is a Latin salsa dance music piece. There are male vocals singing loudly in the Spanish language. There is a groovy bass line. The rhythmic background is provided by the cowbell strokes. The atmosphere is lively. This piece could be used as an accompaniment piece for a Latin dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/LWLLN9INTII.wav"} +{"id": "LYO7_GxyaZc", "caption": "The low quality recording features a regional Mexican song that consists of a flat male vocal singing over groovy trombone, shimmering shakers, short brass melody and wooden percussive elements. It sounds emotional, passionate and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/LYO7_GxyaZc.wav"} +{"id": "L_KkjB0Wt_Q", "caption": "A female singer sings this chanting vocals with backup singers in vocal harmony. The song is medium tempo with bell harmony, keyboard accompaniment, steady rhythm and a string pad harmony. The song is healing and a new age in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/L_KkjB0Wt_Q.wav"} +{"id": "L_fWnna7Np0", "caption": "The e-bass is playing an almost walking line along with a guitar playing a melody on top. The acoustic drums are playing a constant rhythm along with a piano playing one chord on the offbeat. The yodeling voice sings in a higher pitch and sounds amused. This song may be playing at a local folk festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/L_fWnna7Np0.wav"} +{"id": "L_ghM-NrH58", "caption": "The low quality recording features a loud gunshots sound effects, wooden impact and squeaking floor sound effects, while a suspicious background music is playing in the background and it consists groovy woodwind melody, woodwind solo melody, tinny bells melody located in the left channel of the stereo image and smooth bass. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/L_ghM-NrH58.wav"} +{"id": "L_nC2BvhRdQ", "caption": "The Latin Music features a \"4 on the floor\" punchy kick pattern, shimmering shakers, groovy bass that glues everything together, staccato brass melody and repetitive flat male vocal singing over it. The song is gradually speeding up, bringing the energy up along with it. It gives off happy and fun vibes as it sounds like something you would want to dance to.", "audio": "/zhanghaomin/datas/musiccap/music_data/L_nC2BvhRdQ.wav"} +{"id": "LaaC_q3QDUE", "caption": "The recording contains two parts. One being a song with digital drums with a sub bass on the kick and a finger snapping sound used as a snare. A steeldrum sample is playing a repeating melody while a male voice is rapping in a higher pitch along to backing vocals creating a cheerful atmosphere. Then the song stops and you can hear mobile phones ringing. Two male voices are talking to each other. Then the recording stops with a beeping sound. This recording may be playing in a movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/LaaC_q3QDUE.wav"} +{"id": "LadgIxZu8Oc", "caption": "The Rock song instrumental features a mellow synth pad with flanger effect on, and straight piano chords playing in the beginning. In the second part of the loop, there is an electric guitar solo melody layered with synth pad melody and electric guitar power chords layered with powerful bass guitar and energetic crash cymbal. It sounds energetic and powerful, even though it starts softly.", "audio": "/zhanghaomin/datas/musiccap/music_data/LadgIxZu8Oc.wav"} +{"id": "LaeRCg-NdeY", "caption": "The low quality recording features a cover of a classical song and it consists of a saxophone solo melody playing over a groovy piano melody. At the very end of the loop, there is an applause. It sounds easygoing, passionate and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/LaeRCg-NdeY.wav"} +{"id": "LaoUSBEVHVQ", "caption": "Someone is hitting tibetan bowls that keep ringing out with a big release time. This may be playing in a meditation workshop.", "audio": "/zhanghaomin/datas/musiccap/music_data/LaoUSBEVHVQ.wav"} +{"id": "LbPRGDwlfqs", "caption": "This is an electroclash piece. There is a male vocalist singing in the lead with hollering samples in the background. An electric guitar is playing the main theme repeatedly. The bass guitar is playing a groovy bass line. In the rhythmic background, there is an upbeat acoustic drum beat. The piece is groovy and danceable. It could be playing in the background at a sports bar or a rock bar. The music would also suit well with sports venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/LbPRGDwlfqs.wav"} +{"id": "LbQ4zHxhoSI", "caption": "The Acoustic song features an arpeggiated acoustic melody, wide synth pad chords, soft bass guitar, mellow synth keys melody, soft percussive drums loop and mellow female vocal singing on top. It sounds very relaxing and calming - almost like you can do yoga to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/LbQ4zHxhoSI.wav"} +{"id": "Lc6OfmzV7Pk", "caption": "This is a solo trumpet piece which is cheery and upbeat. The pitch is generally high, with a few low notes which contrast and stand out against the high notes.", "audio": "/zhanghaomin/datas/musiccap/music_data/Lc6OfmzV7Pk.wav"} +{"id": "Ld5G00HlbQs", "caption": "An orchestra is playing a piece full of mallets playing a part of the melody, along with strings, flutes and oboes playing the main melody. Timpani hits and cymbals are setting accents to give the composition its power. In the background you can hear a whistle blowing sound and other noise that seem not to belong to the music. This song may be playing in an adventure movie-scene with little insects.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ld5G00HlbQs.wav"} +{"id": "Le4aGNS8e0c", "caption": "This song contains loud acoustic drums with a groove on the ride. An e-bass and e-guitar are playing along in the lower register. A deeper male voice is singing/screaming with a delay on his voice. his voice is doubled. This song may be playing for an action packed youtube video.", "audio": "/zhanghaomin/datas/musiccap/music_data/Le4aGNS8e0c.wav"} +{"id": "LfbGHMumxIQ", "caption": "The low quality recording features a commercial music that consists punchy kick, claps, shimmering hi hats, short brass hit layered with short sustained synth lead note, groovy synth bass that sounds like a siren, reverberant percussive elements and crowd chant at the end of the loop. It sounds energetic and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/LfbGHMumxIQ.wav"} +{"id": "LfvdxSBCtFE", "caption": "This is an 80s electronic music piece. The rhythmic background consists of a disco electronic drum beat with frequent tom fills. There is a keyboard playing the main tune while a bass and an evolving synth are in the background. The atmosphere of this piece is groovy. This piece could be used at retro-themed nightclubs and parties. It could also be used in the soundtrack of an 80s movie or a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/LfvdxSBCtFE.wav"} +{"id": "Lg1HG6D_0Qk", "caption": "This is an amateur recording of a live rock music performance. There is a female vocalist singing in the lead. The electric guitar is playing the main melody with a bass guitar in the background. There is a fast-paced and loud acoustic drum beat in the rhythmic background. The atmosphere is loud and rebellious.", "audio": "/zhanghaomin/datas/musiccap/music_data/Lg1HG6D_0Qk.wav"} +{"id": "LgKOnHwaCmg", "caption": "The low quality recording features a live performance of arpeggiated acoustic guitar melody and passionate male vocal singing over it. There are some people chattering and traffic sound effects, probably because it was recorded outside. The recording is noisy, but it sounds emotional regardless.", "audio": "/zhanghaomin/datas/musiccap/music_data/LgKOnHwaCmg.wav"} +{"id": "Lhw0H3P4zUE", "caption": "This is the recording of a harmonica solo. The tune being played on the harmonica is a melancholic one. There is an emotional aura to it. It could be used in the soundtrack of an animation movie, especially during a scene where a character is going through feelings of heartbreak or disappointment.", "audio": "/zhanghaomin/datas/musiccap/music_data/Lhw0H3P4zUE.wav"} +{"id": "LjihfG0fit0", "caption": "This is a comedy music piece. There is a male vocalist at the forefront singing half-heartedly with tongue-in-cheek mannerisms. There is a keyboard playing the main theme joined by an electric guitar. There is a bass guitar in the background. An acoustic drum beat provides the rhythm. There is a sarcastic atmosphere in the piece. This piece could be used in the background of funny videos.", "audio": "/zhanghaomin/datas/musiccap/music_data/LjihfG0fit0.wav"} +{"id": "LjxhswBV1UA", "caption": "This song has a traditional Mexican mariachi sound. It is fun, vibrant and energetic and is led by rhythmic and melodic playing on the Mexican Vihuela. The maracas add an element of rhythmic percussion. There are sounds of laughter in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/LjxhswBV1UA.wav"} +{"id": "LktT1OQrPdo", "caption": "This audio contains a deeper male voice singing along with the rhythm played on a mridangam while someone is playing te melody on a viola. A second male voice starts singing in a higher register. In the background you can hear a shrutibox playing a drone chord. This song may be playing during a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/LktT1OQrPdo.wav"} +{"id": "LkzyG2F8mTM", "caption": "This is an Arabian folk music piece. It is meant to be an accompaniment to a folk dance. There is an oud playing the melody while a tambourine is playing as the rhythmic background. This is an amateur recording of a live performance. The atmosphere is playful. This could be playing in the background at a Middle Eastern cuisine restaurant or at a hookah place.", "audio": "/zhanghaomin/datas/musiccap/music_data/LkzyG2F8mTM.wav"} +{"id": "LnL3KFKGqHE", "caption": "This music is an aggressive instrumental . The tempo is fast with a violent yet melodic tune that dips suddenly to the sound of gunshots and the metallic sound of empty shells hitting the ground. This music is a violent, harsh, loud, and violent Hard Electronica.", "audio": "/zhanghaomin/datas/musiccap/music_data/LnL3KFKGqHE.wav"} +{"id": "LnczSOwV9Ds", "caption": "The song is an instrumental. The tempo is medium with subtle jazz drumming, keyboard accompaniment, groovy bass line and an electric guitar playing lead. The song is relaxing and groovy. The song is a live jazz instrumental performance with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/LnczSOwV9Ds.wav"} +{"id": "LoTRWc9WK9Q", "caption": "A male preacher talks and plays horn -like instruments to explain the ritual sequence. The song is medium tempo and the small horn is played rhythmically without any accompaniment. The audio quality is bad and the movie talks about Jewish custom sequences.", "audio": "/zhanghaomin/datas/musiccap/music_data/LoTRWc9WK9Q.wav"} +{"id": "LpcvkXs49Zo", "caption": "This audio contains someone playing a solo on a distorted e-guitar in the mid range up to the higher register. This song may be playing for a product advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/LpcvkXs49Zo.wav"} +{"id": "Lq0LMMZfHCU", "caption": "The song is an instrumental piece. The song is medium tempo with a casual piano accompaniment which is cheerful and jittery in style, along with violent sounds of a crash, crushing tones, metal clanging and rubber twisting sounds. The song is cheerful and at the same time has violent tones of injury and accident superimposed in it. The song is a background effect for an animated show which is violent in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/Lq0LMMZfHCU.wav"} +{"id": "LqP4F4a-HOc", "caption": "This is a live performance of a boogie woogie music piece. There is a trio of female vocal harmony singers. The main melody is being played by the piano and the electric guitar. Then, a trombone plays a brief solo. The bass guitar is playing in the background. The rhythmic background consists of an acoustic drum beat. The atmosphere is upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/LqP4F4a-HOc.wav"} +{"id": "Lrhy2auO6hY", "caption": "The song is an instrumental. The song is medium tempo with an electric guitar playing lead and distorted guitar rhythm, along with groovy bass line and rock drumming rhythm. The song is exciting and spirited. The song is a classic rock instrumental with poor quality audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/Lrhy2auO6hY.wav"} +{"id": "Ls6qMcgpdlM", "caption": "The low quality recording features a live performance of a rock song that consists of aggressive electric guitar chord progression, punchy snare, simple kick pattern, shimmering hi hats, energetic crash cymbal and a groovy bass guitar. At the very beginning the sound is gated, leaving only the distant, reverberant guitar chords and punchy snare hits audible. There is also a short snare roll, right before the drop. This instrumental is very energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ls6qMcgpdlM.wav"} +{"id": "LvpImXJMryI", "caption": "A male singer introduces the DJ lineup with an enthusiastic song. The tempo is medium with a groovy bass line, steady drumming rhythm, keyboard harmony and other percussion hits. The song is enthusiastic and energetic. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/LvpImXJMryI.wav"} +{"id": "LwmwCpAVPWU", "caption": "The low quality recording features a live performance including resonating bass, energetic drums and strings melody. The recording is in a terrible condition, as the bass is resonating much and the sound is overall muffled and muddy. There are some cheering and clapping sounds from a crowd. The listener can barely hear the instruments, as it sounds chaotic. It was definitely recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/LwmwCpAVPWU.wav"} +{"id": "Lwvf17xUxhE", "caption": "This is a live recording of a section on the french horn, played in classical style. The piece ascends rapidly and then descends rapidly. The piece has a regal and important feel to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/Lwvf17xUxhE.wav"} +{"id": "LyTwxJiSt7A", "caption": "A xylophone or another bell sounding metal instrument is playing a melody that sounds like a lullaby. Someone is burping loud and with full force. Then you can hear a high pitched voice laughing. These sounds don't seem to belong to the music. This song may be playing in a cartoon sequence.", "audio": "/zhanghaomin/datas/musiccap/music_data/LyTwxJiSt7A.wav"} +{"id": "LybSS4amIS0", "caption": "The low quality recording features a reverberant male vocal yodeling over acoustic rhythm guitar and smooth double bass, both located in the right channel of the stereo image. It sounds passionate, fun and happy - like something you would try to sing to when you are in a good mood.", "audio": "/zhanghaomin/datas/musiccap/music_data/LybSS4amIS0.wav"} +{"id": "LzSWdj4izHM", "caption": "An acoustic drum is playing a faster groove along with a walking bassline. An accordion is playing a melody on top of another instrument supported with short rhythmic chords on the offbeat. Male voice samples are used to create a simple melody. This song may be playing in a funny video. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/LzSWdj4izHM.wav"} +{"id": "M-RX7LqL50A", "caption": "A male vocalist sings this energetic Rap. The tempo is fast with the vocalist singing a Hip-Hop song with Acapella . No instrumentation is used apart from the vocal percussive beats. The song is a youthful, enthusiastic,engaging, insistent, passionate , groovy, rhythmic patter with slangy lyrics and a dance groove. This song is contemporary Hip-Hop/Rap.", "audio": "/zhanghaomin/datas/musiccap/music_data/M-RX7LqL50A.wav"} +{"id": "M0ygCD6WyXw", "caption": "This clip consists of a blowing horn being played. The horn's sound creates the feeling of an impending battle, and is reminiscent of the middle ages.", "audio": "/zhanghaomin/datas/musiccap/music_data/M0ygCD6WyXw.wav"} +{"id": "M1ds6tRFxhs", "caption": "The song is an instrumental. The song is medium tempo with chord changes played on different keyboards to check subtle differences in tonality. The song track is a comparison video playing funk jazz accompaniment.", "audio": "/zhanghaomin/datas/musiccap/music_data/M1ds6tRFxhs.wav"} +{"id": "M27mIdPCZEY", "caption": "The low quality recording features an acoustic guitar tuning tutorial. The recording is in mono and very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/M27mIdPCZEY.wav"} +{"id": "M2iOUwFHv9Q", "caption": "A male vocalist sings this aggressive song. The tempo is medium fast with electronic music; vigorous drumming, cymbal ride; synthesiser arrangements, distorted menacing vocals and electronic music. The song is angry, aggressive, sinister, menacing, spine-chilling and chaotic. This song is a Goth Rock/Hard Metal song.", "audio": "/zhanghaomin/datas/musiccap/music_data/M2iOUwFHv9Q.wav"} +{"id": "M4SIUPA05yc", "caption": "This DJ music features a didgeridoo playing the low end registers. There are different frequencies of didgeridoo instruments played in this clip which have been remixed. There are droning sounds which are all the sounds of didgeridoos. A synth plays staccato chords after two bars. The voicing used in the synth is close to a trumpet. A delay effect is used on the synth sound. This song has a tribal feel. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/M4SIUPA05yc.wav"} +{"id": "M4rXhyyvERM", "caption": "This is the recording of a jazz improvisation performance. It is in an instrumental piece performed with a keyboard that utilizes a classical piano sound. The chords are being played gently which creates a calming atmosphere. Due to various chords and lines being played in this performance, parts of it could be lifted to be used as piano samples for a beat. It could also be playing in the background of a restaurant or a jazz bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/M4rXhyyvERM.wav"} +{"id": "M4yst1q1nlU", "caption": "This is an instrumental rock piece which is a jingle for an ad. There is a clean electric guitar and a high-pitched keyboard playing the main melody. There is a mild bass guitar in the background supporting the melody. In the rhythmic background, there is a rock beat being played by the acoustic drums. A zipper sound effect can be heard synchronized with the ad. The atmosphere is very generic and calm. It is most suitable as an ad jingle or music behind a tutorial video.", "audio": "/zhanghaomin/datas/musiccap/music_data/M4yst1q1nlU.wav"} +{"id": "M5sptjrboqA", "caption": "This is an amateur DJ set performance with a turntable scratched over an electronic music piece with eurobeat characteristics. The track has a repeating fuzzy bass with a repeating loud electronic drum as the rhythmic background. There is an android voice singing the same words over and over.", "audio": "/zhanghaomin/datas/musiccap/music_data/M5sptjrboqA.wav"} +{"id": "M61BBJpvvx8", "caption": "This song is an instrumental. The tempo is medium with melodious synthesiser arrangement , steady drumming and funky bass in contrast to a dissonant gun firing like sound;. The mismatched rhythm is unpleasant to the ears and disturbs the harmonic vibe of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/M61BBJpvvx8.wav"} +{"id": "M7GSBDc6s_w", "caption": "Strings are playing a soft chord melody along to a a sitar supporting the male and female voice singing together. A digital soft and round kick drum sound is holding the rhythm together with another guitar-like sounding instrument. The instruments are spread across the two sides of the speakers. This song may be playing in a meditation group singing along.", "audio": "/zhanghaomin/datas/musiccap/music_data/M7GSBDc6s_w.wav"} +{"id": "M7fsgHyiicM", "caption": "The low quality recording features a digital flute melody, synth brass melody and monster growling sound effect. It sounds emotional and like an in game sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/M7fsgHyiicM.wav"} +{"id": "M9MgZXkYRBs", "caption": "The low quality recording features a classical song that consists of harmonizing trombone melodies. It sounds emotional and passionate, while the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/M9MgZXkYRBs.wav"} +{"id": "M9mc3HYL_GM", "caption": "The low quality recording features a breathy flute playing over dark mellow keys melody. It sounds passionate, soulful, emotional and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/M9mc3HYL_GM.wav"} +{"id": "MC0Aeu7RLSI", "caption": "This dancehall song features a male voice singing the main melody. Another male voice sings backing vocals in harmony with the main melody. The voice sings at a fast pace fitting many syllables in the rhythm phrases. This is accompanied by programmed percussion playing a simple beat. Synth sounds are played in between lines. This song is flirty. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/MC0Aeu7RLSI.wav"} +{"id": "MEew7OQ17HY", "caption": "This audio clip features a female voice singing the main melody. The quality of the audio recording is low. The voice is accompanied by Latin style percussion. Male voices sing backing vocals. This is a dance song at a moderate tempo. The sound of a camera shutter is played at the beginning and end of the clip. Other musical instruments are barely audible due to the low quality of audio recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/MEew7OQ17HY.wav"} +{"id": "MFxMPOAbUPA", "caption": "This is an R&B/soul music piece. There is a whole mix of male and female vocals singing melodically. The tune is being performed by the keyboard while the electric guitar and the bass guitar are playing in the background. There is a slow tempo electronic drum beat in the rhythmic background. The atmosphere is emotional. This piece could be used in the soundtrack of a romance movie, especially during the scenes of resolution.", "audio": "/zhanghaomin/datas/musiccap/music_data/MFxMPOAbUPA.wav"} +{"id": "MHHshnnqyco", "caption": "This is a live performance of a Khaliji music piece. There is an orchestra performing the piece. The melody is being played by the oud and the violin. The rhythmic background is composed of various percussive elements such as the riq, the darbuka and performers clapping their hands. The atmosphere is vibrant. This piece could be playing in the background at an Arab cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/MHHshnnqyco.wav"} +{"id": "MHgPpImV7b4", "caption": "The low quality recording features a Christmas song, played on a device that can produce mono sounds only, and it consists of a passionate male vocal singing over some muffled instrumental. It sounds euphoric, happy, joyful and fun. The recording is messy, in mono, noisy and slightly distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/MHgPpImV7b4.wav"} +{"id": "MHkfPjW0aRg", "caption": "The low quality recording features a dance hall rhythm Christmas song that consists of flat male vocals, alongside high pitched male vocals at the very beginning, singing over syncopated snare, plucked sitar melody, \"4 on the floor\" kick pattern and simple bass. It sounds fun and happy, like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/MHkfPjW0aRg.wav"} +{"id": "MIexFfOsuJs", "caption": "A male singer sings this emotional melody with a female backup singer singing chanting tones. The song is slow tempo with a guitar strumming gently and no other instrumentation. The song is emotional and romantic. The song is beautiful and lilting.", "audio": "/zhanghaomin/datas/musiccap/music_data/MIexFfOsuJs.wav"} +{"id": "MJtDDmS6xSY", "caption": "The low quality, noisy recording features a male throaty vocals singing and some footsteps sound effects. In the background, some dog is barking. The whole sound is panned to the left channel of the stereo image, thus the unbalanced stereo image and it sounds like a sound from TV was recorded.", "audio": "/zhanghaomin/datas/musiccap/music_data/MJtDDmS6xSY.wav"} +{"id": "MKXeCiPtZwo", "caption": "This is an amateur recording of a young girl singing over a pop music piece in the background. The piece has a female vocal singing melodically while the electric guitar and the bass guitar play in the background. The rhythmic background consists of a very basic 4/4 rock drum beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/MKXeCiPtZwo.wav"} +{"id": "MKikHxKeodA", "caption": "Very sounds like an old out of tune mechanical music making machine with harpsichord and recorder sounds. Very dissonant and atonal.", "audio": "/zhanghaomin/datas/musiccap/music_data/MKikHxKeodA.wav"} +{"id": "MM0seezR2F4", "caption": "This rocksteady song features a male voice singing the main melody. This is accompanied by percussion playing a simple beat. The bass is played on a double bass in a rock and roll style progression. A trumpet plays a fill at the end when the voice pauses. There are other instruments being played, but the quality of recording is low and the instruments are not heard clearly. The mood of the song is happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/MM0seezR2F4.wav"} +{"id": "MMGAKKhqxKg", "caption": "This amateur recording starts off with the sound of the crowd at a live show. This is followed by a male voice mouthing four blasting sounds over the mic. This is followed by a guitar playing a funk riff and another guitar playing a lower register melody. The percussion plays a fast beat. The bass plays only one note in a continuous pattern following the percussion. The mood of this song is upbeat. This song can be played in a retro club.", "audio": "/zhanghaomin/datas/musiccap/music_data/MMGAKKhqxKg.wav"} +{"id": "MNd8CRa48Uk", "caption": "Eastern European music featuring clean electric guitar, tambourine, two male vocalists. Could be traditional dance music.", "audio": "/zhanghaomin/datas/musiccap/music_data/MNd8CRa48Uk.wav"} +{"id": "MNlzpCwdh4g", "caption": "The low quality recording features a french horn melody played over playback that consists of snappy rimshots, shimmering hi hats and arpeggiated guitar melody. It sounds emotional and passionate, even though the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/MNlzpCwdh4g.wav"} +{"id": "MP7KPlqoQW0", "caption": "The song is an instrumental. The song is medium tempo with a slick drumming rhythm, grunge keyboard tones, overdriven synth tones and string pad section. The song is groovy and exciting. The audio quality is poor in general.", "audio": "/zhanghaomin/datas/musiccap/music_data/MP7KPlqoQW0.wav"} +{"id": "MPe6ztPtF0Y", "caption": "happy music featuring a solo acoustic strummed guitar playing open chords, quiet male singing, and a bird chirping in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/MPe6ztPtF0Y.wav"} +{"id": "MPxwPOOIskc", "caption": "Quiet instrumental cover of a popular pop/rock song by an orchestra that features winds and strings trading off parts of the melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/MPxwPOOIskc.wav"} +{"id": "MQ1Q7xydJPU", "caption": "This is the live performance of a hard rock piece. There is a male vocal who is shouting at the crowd while revving up a chainsaw. The electric guitar is playing the melody while the bass guitar is playing in the background. The acoustic drums are playing a simple blues rock beat. The atmosphere is aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/MQ1Q7xydJPU.wav"} +{"id": "MQrOnSzVlJg", "caption": "A female singer sings this beautiful melody. The song is medium tempo with no instrumentation but just the vocal echoes from the singer's vocals. The song is devotional and prayer-like in nature. The song is a Christmas hymn being sung by a Celtic singer. The audio quality is very muted and poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/MQrOnSzVlJg.wav"} +{"id": "MROotmz8a-U", "caption": "A female vocalist sings this enchanting song.the tempo is slow with this clip opening with the vocalist almost ending the sentence. The singer is accompanied by mesmerising Violin symphony and piano accompaniment . This song is a live performance as it is sung with an orchestra and there is the sound of people talking. The song is enchanting, ethereal, captivating, soothing and celestial.", "audio": "/zhanghaomin/datas/musiccap/music_data/MROotmz8a-U.wav"} +{"id": "MS8VU468rKk", "caption": "This is a cover of an alternative rock music piece. There is an electric guitar with a clean sound and a lot of reverb playing a gentle arpeggio. The atmosphere is dreamy and hazy. This piece could be used in the background of a tutorial video.", "audio": "/zhanghaomin/datas/musiccap/music_data/MS8VU468rKk.wav"} +{"id": "MSHbLrVlrQc", "caption": "The low quality recording features a kids song that had stretched audio, caused by digital compression, and it consists of chiptune vocal singing over groovy piano chords. Other elements of the instrumental are barely audible. The sound is almost crushed, but it still sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/MSHbLrVlrQc.wav"} +{"id": "MSqQKf3O3vY", "caption": "A male singer sings this pop melody with animated vocals making annoying sounds. The song is medium tempo with backup vocals singing harmony, keyboard accompaniment, percussive a bass line and strong drumming rhythm. The song is a background track for an animated tv show. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/MSqQKf3O3vY.wav"} +{"id": "MV4tgzc9X6s", "caption": "This song features a cowbell being struck with a stick. The cowbell is struck at different parts producing different sounds. The first sound is a muted sound. At the beginning, the cowbell is struck three times at different parts. The first sound is muted. The second sound is slightly open and at a higher pitch than the first sound. The third sound is higher in pitch again and sounds more open than the first two sounds. A pattern is then played using a drumstick and striking the cowbell at different parts. There are no other instruments in this song. There are no voices in this song. This song can be played in a cowbell instructional video.", "audio": "/zhanghaomin/datas/musiccap/music_data/MV4tgzc9X6s.wav"} +{"id": "MVAXHT67Na4", "caption": "This is a parody montage of a K-pop music piece. There is a girl band singing in the original track. On the parts where the girls are hollering, the sounds of goats bleating were added. The original track has a keyboard playing the melody while there is a strong bass in the background. The rhythm is played by the electronic drums. There is an amusing atmosphere.", "audio": "/zhanghaomin/datas/musiccap/music_data/MVAXHT67Na4.wav"} +{"id": "MVBQrBAXgw4", "caption": "This audio contains a very present kick on every beat. A synth bass is playing an arpeggio melody along with a synth lead sound playing in a higher pitch rising up in pitch. Then a riser sound also rises in pitch. Then the music stops and you can hear glass breaking. This song may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/MVBQrBAXgw4.wav"} +{"id": "MVYSWTF11Nc", "caption": "A digital drum is playing a groove with different little elements panned to the left and right side of the speakers. Little sprinkles of plucked digital synth sounds are playing melodies along with a keyboard playing soft chords. The female voice is singing being backed by a voice full of effects. Then padsounds come in serving as strings playing a slow chord progression. This song may be playing at the mall.", "audio": "/zhanghaomin/datas/musiccap/music_data/MVYSWTF11Nc.wav"} +{"id": "MVq9PYtypy0", "caption": "The hip-hop music features a male voice singing repetitive short bits of melody. The music excerpt contains a strong beat rhythm which drives the pulsation of the music. A synth sound is playing a repeating melody throughout the passage. The music sounds as if it was recorded by a phone from a playing speaker.", "audio": "/zhanghaomin/datas/musiccap/music_data/MVq9PYtypy0.wav"} +{"id": "MWS-Uxf1MRw", "caption": "This is a classical music piece. There is a piano playing an arpeggio in the background while a violin gently plays the main tune. The atmosphere of the piece is sentimental. This piece could be used in the background of tutorial videos. It could also be playing in the background at a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/MWS-Uxf1MRw.wav"} +{"id": "MX0wS7MX3Zo", "caption": "This is a contemporary classic music piece being performed on a theremin. The player gives the theremin and electronic sounding character. The atmosphere is weird and eccentric. This piece could go well in the soundtrack of an absurdist/surrealist art movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/MX0wS7MX3Zo.wav"} +{"id": "MXdVnDVjSL8", "caption": "This dubstep song features a turntable being played. It starts off with a high frequency pitch that is being brought down to a lower pitch till it fades away. A male voice raps a line and the instruments pause momentarily. This is followed by scratching of a vinyl in a pattern. This is accompanied by programmed percussion playing a dubstep beat. The sounds played are all synthesized by the DJ console. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/MXdVnDVjSL8.wav"} +{"id": "MY0PsDE3xHs", "caption": "A female singer sings soft pop songs. The tempo is medium fast with electronically arranged music, electric guitar harmony, digital drum beats, and melodious vocal backup. The song is simple, soft, emotional, upbeat, catchy, with a dance groove. This song is an Electro Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/MY0PsDE3xHs.wav"} +{"id": "MYtq46rNsCA", "caption": "This is a theme in the background of a cartoon. The strings are playing an agitated melody interchanged with a calm playing clarinet. There is a laser beam sound effect when the characters appear on screen. The usual atmosphere is made up of very generic and commonplace sounds. The piece can be used in the background of an animated video.", "audio": "/zhanghaomin/datas/musiccap/music_data/MYtq46rNsCA.wav"} +{"id": "MZhaDGgULtc", "caption": "A male vocalist sings this soft melody. The song is medium tempo, with violin harmony, steady drumming, straight bass lines, acoustic guitar and keyboard accompaniment with vocal backup. The song is in a foreign language. It is slow, and has a mellow, soft, emotional , sentimental and romantic vibe. This is a regional Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/MZhaDGgULtc.wav"} +{"id": "M_s-49rNCdw", "caption": "A male vocalist sings this spirited song. The song is medium tempo with energetic electric guitar lead, enthusiastic electric bass guitar , hard hitting drums and keyboard harmony. The vocals are passionate, youthful,energetic, vociferous, powerful and loud . This song is Hard Rock/Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/M_s-49rNCdw.wav"} +{"id": "MdYXznF3Eac", "caption": "To male voices are singing a melody. Someone is playing acoustic drums together with a djembe. A ukulele is being strummed on the offbeat along with a piano playing the same chords. This is an amateur recording. This song may be playing live at a small festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/MdYXznF3Eac.wav"} +{"id": "MdsRmMxkF4k", "caption": "These are the sounds coming from a martial arts movie. There are male voices shouting at each other. Sounds of footsteps and the movements of fighting can be heard. The music in the background has a dramatic tune being played on the strings. The rhythmic background is composed of Chinese paigu drums and the gong. There is a feeling of tension in this track. Some parts of this recording can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/MdsRmMxkF4k.wav"} +{"id": "MeA8CSKAuvw", "caption": "This pop song features a male voice singing the main melody. This is accompanied by percussion playing a simple beat. The hi-hat is played in eighth notes. The bass is played on a tuba. The root notes of the chords are played. Trumpets play a staccato note at every alternate beat. A brass instrument plays a fill after the first two bars. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/MeA8CSKAuvw.wav"} +{"id": "Mf6Ql55o7Es", "caption": "This is a pop music piece being played through a reverberation amp. There is a male and a female vocalist singing melodically. A clean sounding electric guitar is playing a simple tune while a keyboard is holding the chords and a bass guitar is playing in the background. The rhythmic background is provided by a medium tempo electronic drum beat that has characteristics resembling an acoustic drum kit. The atmosphere is sentimental and vibrant. This piece could be used in advertisement jingles. It could be playing in the background in a romantic setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Mf6Ql55o7Es.wav"} +{"id": "MfKSVJIcDK0", "caption": "An acoustic guitar is finger-picking a tremolo melody along with a flute playing a melody on top. This song may be playing in an adventure video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/MfKSVJIcDK0.wav"} +{"id": "MfX7Q0ucts8", "caption": "The low quality recording features an emotional electric guitar melody played with two different reverb pedal effects, one after the other. It sounds like the player is comparing the two reverbs. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/MfX7Q0ucts8.wav"} +{"id": "Mhvgz5AjV3U", "caption": "This audio contains various acoustic guitars playing a lead melody, a countermelody and strumming chords. An acoustic drum is holding a simple bossa nova groove along with shaker and percussion. This song may be played live outside by a busker.", "audio": "/zhanghaomin/datas/musiccap/music_data/Mhvgz5AjV3U.wav"} +{"id": "MiWskwqOMrg", "caption": "This is the recording of a gear review video. There is a male voice describing the feel of a certain reverb amp. There is a static sound that can be heard while he is talking, because the guitar is still plugged in. A mellow tune can be heard playing from a clean sounding electric guitar in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/MiWskwqOMrg.wav"} +{"id": "MipnqUXgpOA", "caption": "This is a remix of an R&B music piece. An auto-tuned male vocal is singing melodically in a minor scale at a high pitch. A fading electric guitar sample can be heard in the distance. Repeated hits of low-frequency percussion add a deepening effect to the piece. The atmosphere is very dreamy and very trippy. This piece could be used in a dream sequence at a movie or a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/MipnqUXgpOA.wav"} +{"id": "Mir959i7F2M", "caption": "Someone is playing a e-guitar solo over another e-guitar providing jazz chords along with acoustic drums playing a jazzy groove with little licks and a steady straight groove in the ride that is panned to the right side of the speakers. An upright bass in playing a walking bassline. This song may be playing at a jazz bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/Mir959i7F2M.wav"} +{"id": "MkPhe7TLLZ0", "caption": "Music and random sounds from an old 8 bit video game. A children's melody interspersed with harsh, digitally distorted sounds. Experimental and dissonant to the point of being chaotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/MkPhe7TLLZ0.wav"} +{"id": "MkTQQ0m8Ys8", "caption": "The low quality recording features a live performance of a classical song by an orchestra that consists of muffled sustained strings melody, subtle drums rhythm and woodwinds melody. It is noisy and in mono, like it was recorded with a phone or a camera microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/MkTQQ0m8Ys8.wav"} +{"id": "MlnK2sa7mm4", "caption": "The low quality recording features a Harmonica solo melody. The recording is noisy and in mono, as it was probably recorded with a phone and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/MlnK2sa7mm4.wav"} +{"id": "MmqRlHntd0Q", "caption": "This song contains a marching band playing a melody with a big brass section. Horns are playing the bass melody and kicks and snare rolls are providing the rhythm along with some cymbal hits. This song may be playing at a national sports-event.", "audio": "/zhanghaomin/datas/musiccap/music_data/MmqRlHntd0Q.wav"} +{"id": "Mnk6590abfY", "caption": "This is a latin dance music piece. There is a heavy use of percussive elements such as marimba and steel percussion. They act both as the melodic and the rhythmic background. The atmosphere of the performance is lively and cheerful. This piece could be used as an accompaniment piece for latin dance courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/Mnk6590abfY.wav"} +{"id": "MocXmVbat3s", "caption": "This is a low quality recording of a motown style song. The song seems to have been recorded using a cellphone. The lead female vocalist has a soulful and powerful voice. The song is upbeat and jovial.", "audio": "/zhanghaomin/datas/musiccap/music_data/MocXmVbat3s.wav"} +{"id": "Mp1MHSeHa0o", "caption": "The low quality recording features a wide synth pad, soft sustained strings, mellow harp melody, soft toms, reverberant rimshots and strummed strings. It sounds mystical, suspenseful and haunting, like something you would hear as the background music of a thriller movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Mp1MHSeHa0o.wav"} +{"id": "MpS2SSIhe2g", "caption": "An acoustic piano is playing a slow melody along with strings and brass in the background playing long minor chords. A bansuri flute is playing the lead melody. The whole composition sounds sad and may be playing in a sad movie scene like Titanic.", "audio": "/zhanghaomin/datas/musiccap/music_data/MpS2SSIhe2g.wav"} +{"id": "MpWGx5odhh8", "caption": "This amateur recording features a rock song. The main melody is played on violins. This is accompanied by percussion playing with breaks matching the breaks in the violin parts. At the end, the violins play a sustained note and a banjo starts to play a melody. A tambourine is played on the first count of the second bar after the banjo starts to play. This is an uptempo song and has a happy feel. This instrumental song can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/MpWGx5odhh8.wav"} +{"id": "MpjN21Z93JY", "caption": "A male singer sings this popular song. The tempo is medium with an ukulele playing rhythm accompanying the male vocals with no other instrumentation. The song is emotional and inspiring. The audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/MpjN21Z93JY.wav"} +{"id": "MrMXYO2fzJ4", "caption": "The low quality recording features a latin jazz song played in the background over which a drums solo is played. The solo consists of shimmering hi hats, punchy snare and kick hits and low tom rolls, while the latin jazz song consists of groovy piano chords and wooden percussion. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/MrMXYO2fzJ4.wav"} +{"id": "MsEoUVWS59M", "caption": "Sounds like a poorly recorded live sound check of an analog mono synthesizer. Low fidelity with ambient noise in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/MsEoUVWS59M.wav"} +{"id": "MsjeOXuUYG4", "caption": "The low quality recording features a distorted, filtered synth bass, echoing female vocal, arpeggiated synth lead melody playing, while there are outdoor sound effects like wind blowing, traffic, skateboard driving in the background. It sounds like a compilation of cool skateboard tricks.", "audio": "/zhanghaomin/datas/musiccap/music_data/MsjeOXuUYG4.wav"} +{"id": "MtVLmOvQopM", "caption": "This is a live performance of a Russian folk music piece. There is no singer in this piece. The single instrument being played is a garmon. The performer is playing a melancholic solo on the garmon. This piece could be used in the soundtrack of a movie or a documentary that takes place in Russia. It could also be playing in the background at a Russian cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/MtVLmOvQopM.wav"} +{"id": "Mv90uA0tmgc", "caption": "This is a video game theme in the style of jazz music. There is a male vocalist singing gibberish while imitating a brass instrument. The vibraphone is playing the main melody. There is a piano playing chords in a syncopated manner. The bass guitar is playing a groovy bass line. The rhythmic background consists of an acoustic jazz drum beat. The atmosphere is dreamy and cheerful. This piece could be playing in the soundtrack of an animation movie during a dream sequence.", "audio": "/zhanghaomin/datas/musiccap/music_data/Mv90uA0tmgc.wav"} +{"id": "MvnC1TfNiPY", "caption": "This song is an energetic dance pop. The tempo is medium fast with keyboard accompaniment, synthesiser articulation,infectious digital drumming and vocal backup supporting the male and female duet. The song is a youthful, upbeat, energetic, spirited, bouncy and pulsating Disco Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/MvnC1TfNiPY.wav"} +{"id": "MwE7REVj8JQ", "caption": "The song is an instrumental. The tempo is varying with maracas being played percussively. The playing is energetic and exciting. The song is a home music video and probably a demonstration of Latin percussion styles.", "audio": "/zhanghaomin/datas/musiccap/music_data/MwE7REVj8JQ.wav"} +{"id": "MwK9HYjeeN0", "caption": "An acoustic drum is playing a groove with brushes while an e-bass is playing a walking bassline. Someone is strumming chords on an acoustic guitar while an e-guitar is playing rhythmic chords on the offbeat along with a slide guitar playing a melody. A mid-ranged male voice is singing a melody supported by male and female backing singers. This song may be playing in a coffee shop in the morning.", "audio": "/zhanghaomin/datas/musiccap/music_data/MwK9HYjeeN0.wav"} +{"id": "Mwy5Y0S5jfM", "caption": "This is an instrumental pop-rock piece. There is a harp playing the main melody while a ukulele is strumming chords. An electric guitar and a bass guitar join the melodic background later on. A simple acoustic drum beat is in the rhythmic background. It has a joyful aura, but the sounds used are very generic. The best use for this piece could be the background of a tutorial/instructive type of video.", "audio": "/zhanghaomin/datas/musiccap/music_data/Mwy5Y0S5jfM.wav"} +{"id": "MyH8zQw9csc", "caption": "Someone is strumming chords on a guitar while playing a sad sounding melody on a harmonica. This song may be playing sitting on a bonfire surrounded by friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/MyH8zQw9csc.wav"} +{"id": "MyjxrBI9k4o", "caption": "The music features a single melodic element which is an electric guitar with reverb and delay. The guitar alternates between arpeggios and strums. The music could fit the indie rock genre. The overall vibe of the song is bright.", "audio": "/zhanghaomin/datas/musiccap/music_data/MyjxrBI9k4o.wav"} +{"id": "MzUgHy7SyS8", "caption": "A male vocalist sings this perky pop song. His tempo is medium fast with punchy drumming; animated amplified piano accompaniment, tambourine beats and funky bass lines. The song is simple, peppy, engaging, energetic, story telling, and catchy. This song is Classic Pop/ Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/MzUgHy7SyS8.wav"} +{"id": "N-dzfI3L5ic", "caption": "The song is an instrumental. The song is medium tempo with a flute paging embody, various stringed instruments playing in harmony and no percussion. The song is passionate and emotional. The audio quality is average .", "audio": "/zhanghaomin/datas/musiccap/music_data/N-dzfI3L5ic.wav"} +{"id": "N0i99VyZCg8", "caption": "This is an orchestral movie music piece. There is a brass section and a cinematic sounding strings section playing a dramatic tune. A percussive syncopation provides the rhythmic background. There is a faint high-pitched choir sound that is most likely coming from a synth. The atmosphere is full of suspense. This piece could be used in the soundtrack of a video game or a movie at a scene that implies an imminent threat or danger.", "audio": "/zhanghaomin/datas/musiccap/music_data/N0i99VyZCg8.wav"} +{"id": "N0q5vPAsHLI", "caption": "The low quality recording features a lullaby that contains wide sustained strings melody, leaning more towards the left channel and arpeggiated, mellow piano melody in the right channel of the stereo image. There is a short audio pop sound in the middle of the loop. It still sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/N0q5vPAsHLI.wav"} +{"id": "N1Mxns_JJTk", "caption": "The song is an advertisement jingle. A male singer sings rapping vocals, with a strong drumming rhythm, piano accompaniment, groovy bass line and a distorted guitar playing an aggressive lead. The song is high on adrenaline and energetic. The song is a soundtrack for an ad and is of poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/N1Mxns_JJTk.wav"} +{"id": "N4eMppEnPE0", "caption": "This clip features a variety of sounds that would be suitable for meditation or at a massage parlour. The music is serene, peaceful, and calm. It features a gong, a wind-chime and a diapason.", "audio": "/zhanghaomin/datas/musiccap/music_data/N4eMppEnPE0.wav"} +{"id": "N4tTZn8WlDM", "caption": "This clip is an instrumental. The tempo is slow with a stringed instrument playing a single monotone note. There is the sound of static in the background. This sound is of a stringed instrument getting tuned but it has a spooky, eerie, sinister and scary vibe when combined with the static in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/N4tTZn8WlDM.wav"} +{"id": "N5BAnG2zoUY", "caption": "This is a comedic music piece used in the background of an animation. There is a medium-to-high pitch synth playing the main theme with an electric guitar and bass guitar pattern in the background. The rhythm consists of a simple electronic drum beat. A lot of sound effects are used such as falling, biting and running.", "audio": "/zhanghaomin/datas/musiccap/music_data/N5BAnG2zoUY.wav"} +{"id": "N6YT8_jlt0E", "caption": "This clip features a synth pad and synth swells in the background. Game mode selection sounds are played. A boom and splash sound is played just before the game mode selection sound is played. The synth sounds continue to play in the background. There are no voices in this clip. There are no other instruments in this clip. This sound can be used in an online game.", "audio": "/zhanghaomin/datas/musiccap/music_data/N6YT8_jlt0E.wav"} +{"id": "N8Fg3L1Cc5E", "caption": "A female singer sings this beautiful melody. The tempo is medium with a piano or keyboard accompaniment and no other instrumentation. The song is emotional and passionate like a love song. The audio quality is very poor with a lot of hissing noise and distortion.", "audio": "/zhanghaomin/datas/musiccap/music_data/N8Fg3L1Cc5E.wav"} +{"id": "NBnz0xV9nb4", "caption": "The low quality recording features mellow piano chords playing. There is a short audio cut and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/NBnz0xV9nb4.wav"} +{"id": "NC5tIv4-8fg", "caption": "The R&B song features a passionate female vocal, alongside wide background female vocals, singing over shimmering cymbals, punchy kick and snare hits, groovy bass guitar and wide electric guitar melody. It sounds passionate, emotional and addictive - like something you would hear in clubs a lot.", "audio": "/zhanghaomin/datas/musiccap/music_data/NC5tIv4-8fg.wav"} +{"id": "NDJEKij2qOg", "caption": "This is a German Romantic era music piece. It is being performed live, however the quality of the recording is poor with frequently occurring peak noise. The french horn is playing the main melody while the background consists of a steady grand piano tune. The piece has a heart-touching feel to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/NDJEKij2qOg.wav"} +{"id": "NHA1l_Czm38", "caption": "This middle-eastern song features a male voice singing the main melody. An oud plays the same melody as the voice. This is accompanied by middle-eastern percussion instruments played with the hands. A tambourine is played to accent the percussion beats. After the voice, the main melody is played on a flute. This is accompanied by a qanun. This song can be played for a belly dance programme.", "audio": "/zhanghaomin/datas/musiccap/music_data/NHA1l_Czm38.wav"} +{"id": "NIcsJ8sEd0M", "caption": "This song is an oriental folk song featuring a male voice singing at a high pitch. The voice is tremulous. This is accompanied by the Chinese fiddle playing a melody similar to the main voice. A flute also plays the same melody as the voice. The percussion plays random beats leaving a lot of room in between. This song can be played in an Asian movie where a man is trying to woo a girl in a village.", "audio": "/zhanghaomin/datas/musiccap/music_data/NIcsJ8sEd0M.wav"} +{"id": "NJGo2fmUAII", "caption": "This music is instrumental. The tempo is fast with vigorous electric guitar feedback, hard hitting drums, amplified keyboard harmony and bass guitar. The music is loud, aggressive, boisterous, vital, persistent and high-powered. This music is a Heavy Metal Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/NJGo2fmUAII.wav"} +{"id": "NJ_Ha89QjiI", "caption": "The low quality recording features shoe tapping sounds alongside loud bagpipe melody and drum rolls. It sounds like it was recorded outside and therefore it is reverberant, epic and powerful. The recording is in mono and a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/NJ_Ha89QjiI.wav"} +{"id": "NKDBwJIwWoU", "caption": "This song features a distortion guitar playing a guitar solo. The solo is played at a high pitch. It is a slow tempo solo. The guitarist plays a lot of vibrato when the notes are allowed to ring for a while. The pattern follows three ascending notes followed by three strikes on a lower note. This is followed by one higher note, the lower note and a hammer on to a higher note. A synth plays backing chords. There are no other instruments in this song. The mood of this song is romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/NKDBwJIwWoU.wav"} +{"id": "NLQts9t7d8k", "caption": "The low quality recording features a wide harmonizing background vocals singing alongside passionate female lead vocal, over punchy snare hits, shimmering bells melody, simple hi hats, soft kick hits, simple bass and acoustic guitar melody. It sounds passionate, mellow and soft.", "audio": "/zhanghaomin/datas/musiccap/music_data/NLQts9t7d8k.wav"} +{"id": "NNeEzTVATHg", "caption": "This amateur recording features folk music being played on violins. There are multiple violins playing in harmony. The tempo is moderate. There is no percussion in this song. Crowd voices and whistles can be heard during the performance. This song is played for a folk dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/NNeEzTVATHg.wav"} +{"id": "NP5iO_HB-f0", "caption": "This audio features a drum machine playing different beats. It starts off with a phrase using seven strokes on the kick and one hand clap. This is followed by another sequence of seven strokes on another percussive instrument and one stroke on a different part of the instrument. This is followed by a hip-hop beat using booming kick sounds. This is a demonstration of a drum machine.", "audio": "/zhanghaomin/datas/musiccap/music_data/NP5iO_HB-f0.wav"} +{"id": "NPXZIqxKvXA", "caption": "The low quality recording features a repetitive didgeridoo melody. The recording is noisy and in mono, since it was probably recorded with a phone, and it sounds really low in frequency.", "audio": "/zhanghaomin/datas/musiccap/music_data/NPXZIqxKvXA.wav"} +{"id": "NQXQsVawPhU", "caption": "This is an excerpt from a music show. There is a female voice narrating an event that took place. In the background, there is hip-hop music playing. A male vocal can be heard rapping. The melody is being played by a synth sound. There is a strong bass in the piece. The rhythm is played by the electronic drums. This piece could be used as an advertisement jingle for a sportswear or automobile company.", "audio": "/zhanghaomin/datas/musiccap/music_data/NQXQsVawPhU.wav"} +{"id": "NRWlHRvaDcQ", "caption": "This music is instrumental. The tempo is slow with a dominant Trombone lead. The music is loud, powerful, emphatic , clear and rich. This music is a Western Classical Trombone instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/NRWlHRvaDcQ.wav"} +{"id": "NSS9_2FFVeo", "caption": "The low quality recording features an electro song scratched by a DJ. The song consists of buzzy synth bass, bouncy cowbells, stretched low pitched male vocals, punchy kick, punchy snare layered with claps and shimmering hi-hats. It sounds energetic and groovy, like something you would hear in an underground club during the 90s.", "audio": "/zhanghaomin/datas/musiccap/music_data/NSS9_2FFVeo.wav"} +{"id": "NSyqj1DXZKg", "caption": "This clip is a meditative and calming track. The leading instrument is a flute, which is played intricately and dynamically. In support, is a piano, on which arpeggios are played. The track would be suitable as music for relaxation at a spa.", "audio": "/zhanghaomin/datas/musiccap/music_data/NSyqj1DXZKg.wav"} +{"id": "NUTaOnEhvzE", "caption": "The song is an instrumental. The song is slow tempo with three accordions playing in harmony and in a relaxed manner. The song is beautiful and romantic. The audio quality is average and an amateur home recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/NUTaOnEhvzE.wav"} +{"id": "NVo-stvk_QE", "caption": "Here we have an electric guitarist intricately playing a guitar solo with a reverb effect applied to his guitar. The music is a jazzy type of backing track with a sophisticated walking bassline. The guitarist is highly skilled.", "audio": "/zhanghaomin/datas/musiccap/music_data/NVo-stvk_QE.wav"} +{"id": "NWL-P08eM-U", "caption": "A male vocalist sings this peppy rap. The tempo is medium fast with an enthusiastic and catchy guitar rhythm, drum stick clicks, congas, steady drumming and keyboard accompaniment. The song is simple, punchy; buoyant, youthful, animated, vibrant and has a catchy dance groove. This song is contemporary Hip-Hop/Rap.", "audio": "/zhanghaomin/datas/musiccap/music_data/NWL-P08eM-U.wav"} +{"id": "NX3KJ-tVdMI", "caption": "This audio contains a digital drum with a kick with a lot of overdrive, a snare on the backbeat and a long noisy snare sound. This song sounds very monoton. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/NX3KJ-tVdMI.wav"} +{"id": "NXuB3ZEpM5U", "caption": "This is a melodious instrumental. The tempo is slow with a cello harmony, ukulele accompaniment, boomy bass and steady drumming. The music is soft, mellow, ethereal, classic, soothing, captivating and mellifluous.", "audio": "/zhanghaomin/datas/musiccap/music_data/NXuB3ZEpM5U.wav"} +{"id": "NZ2kFIaW05k", "caption": "The low quality recording features an electric guitar melody played over a playback that consists of groovy bass, punchy snare and shimmering cymbals. At the end of the loop, there is a flat male vocal talking. It sounds groovy, fun and the recording is noisy and slightly distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/NZ2kFIaW05k.wav"} +{"id": "NZYDLDIyZr8", "caption": "The low quality recording features a traditional song that consists of a flat male vocal singing over pad chords. The recording is very noisy and it sounds passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/NZYDLDIyZr8.wav"} +{"id": "NZn4-gP2GiI", "caption": "A male singer sings this groovy melody. The tempo is medium with a strong bass line, steady drumming, keyboard playing a countermelody and various percussion hits. The song is funk pop in nature. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/NZn4-gP2GiI.wav"} +{"id": "N_41Y2vH6eA", "caption": "The low quality recording features squeaky toys sound effects, followed by noisy tinny bells melody. It sounds like a lullaby - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/N_41Y2vH6eA.wav"} +{"id": "N_LKZjw9DLk", "caption": "This song contains a female voice singing in a high pitch along to strings playing their own supportive melody and percussion's holding a groove with different elements. This is an amateur recording. This song may be playing at a gym during dancing classes.", "audio": "/zhanghaomin/datas/musiccap/music_data/N_LKZjw9DLk.wav"} +{"id": "N_Wx35sNqdM", "caption": "The male voice is singing while male backing voices are underlining some phrases. They are adding harmonies to his singing. An acoustic drum and e-bass are holding the groove while a piano and e-guitar are playing the same chords. Another e-guitar is playing a melody, almost repeating the singer's melody as a response. The e-guitar is running through an effect. The guitars are panned to the left and right side of the speakers. This song may be playing at a scene of a rom-com movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/N_Wx35sNqdM.wav"} +{"id": "NcsYdCbKgcc", "caption": "The song is an instrumental. The song is medium fast tempo with percussionists playing a groovy rhythm on three clap boxes. The sound quality is poor with a lot of ambient crowd noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/NcsYdCbKgcc.wav"} +{"id": "NdiSW-p2I0c", "caption": "The low quality recording features a passionate electric guitar solo melody over wide playback rock instrumental. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/NdiSW-p2I0c.wav"} +{"id": "NeSIT6sqLRA", "caption": "This is an instrumental jam recording. There is a mini theremin being played at a high pitch. It is making vibrating and squeaking sounds. There is an instructive male voice speaking. There is an eerie feel to the sound. This recording could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/NeSIT6sqLRA.wav"} +{"id": "Nep_3Y81E_w", "caption": "The drums are playing a steady rock groove with a half open hi hat constantly ringing through the song. The e-guitar is panned to the left and right side of the speakers or two e-guitars are shredding the same distorted chords along with the bass silently playing in the background. The female voice is singing in a higher pitch and is accompanied by a female backing voice singing a deeper harmony. This sounds like a typical high school rock song. This song may be played chilling in your room sitting on the bed daydreaming.", "audio": "/zhanghaomin/datas/musiccap/music_data/Nep_3Y81E_w.wav"} +{"id": "NgniX3tg_Mo", "caption": "The low quality recording features a live performance of a traditional song and it consists of a flat male vocal singing over sustained strings melody and mellow, subtle percussive element. There are some people talking in the background, followed by a cough. It sounds passionate and emotional, even though the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/NgniX3tg_Mo.wav"} +{"id": "NhVkzcCL0SA", "caption": "The orchestral music is purely instrumental and makes an exception only towards the ending of the music excerpt, where a male voice can be heard. Throughout this passage one can notice that segments of three different pieces are played one after the other, the 3rd one being the shortest - about 1 second in length. The first piece sounds like it depicts a dance, the second one an epic moment and the 3rd one is too short to draw any conclusions.", "audio": "/zhanghaomin/datas/musiccap/music_data/NhVkzcCL0SA.wav"} +{"id": "NjoKxRwQxCE", "caption": "This clip features a male voice in a narrative voice. This is accompanied by a synth sound using a ring modulator effect. The voice is calming. This song can be played in a documentary movie. There is no vocal melody in this song. There are no other instruments in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/NjoKxRwQxCE.wav"} +{"id": "NlCfScKw_Mk", "caption": "Someone is playing a track from speakers. This song contains a strong e-bass playing a funky bassline along with a funky drum groove. Then a piano comes in playing a jazzy melody in one scale accompanied by a synth brass sound swelling into existence and playing a short rise before leaving again. This is an amateur recording but of decent audio-quality. This song may be playing in a jazzbar.", "audio": "/zhanghaomin/datas/musiccap/music_data/NlCfScKw_Mk.wav"} +{"id": "NlUf1ppoSG4", "caption": "This music is instrumental , the tempo is slow with an electric guitar lead and a strong bass guitar accompaniment. The music is assertive and emphatic but sounds sad, melancholic,nostalgic, romantic , wistful and sentimental. This music is Blues Harmony.", "audio": "/zhanghaomin/datas/musiccap/music_data/NlUf1ppoSG4.wav"} +{"id": "Nlg8AbWRV_c", "caption": "The low quality recording features synth pad chords, followed by mellow arpeggiated piano melody. It sounds soft and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/Nlg8AbWRV_c.wav"} +{"id": "NmMJgUo19Gk", "caption": "This instrumental intro features a blues rock inspired electric guitar solo with string bending, an aggressively strummed acoustic guitar, a tambourine, an electric bass guitar and an uptempo rock drum beat. Feels like a protest song from the sixties.", "audio": "/zhanghaomin/datas/musiccap/music_data/NmMJgUo19Gk.wav"} +{"id": "Nms2A0wi0vU", "caption": "This song contains a fast paced melody played by several instruments like an e-bass and some pitched percussive instruments along with a keyboard and whistles. loud in the background you can hear underwater-sounds and high pitched digital game voices panned to the right side of the speakers. This is an amateur recording. This song may be playing in an adventure video-game for kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/Nms2A0wi0vU.wav"} +{"id": "NmwmOY6iBFg", "caption": "The music excerpt is split into two different songs. The first half features the type of turntable scratches that DJs usually do. A song is running in a loop in the background. In the second half the music fades in and becomes louder but at the same time it sounds as if it's interrupted.", "audio": "/zhanghaomin/datas/musiccap/music_data/NmwmOY6iBFg.wav"} +{"id": "NnYfF7E12dk", "caption": "The low quality recording features a tutorial on how to make the electric guitar sound like a banjo. It consists of a flat male vocalist talking over the background instrumental music, after which he starts playing the electric guitar. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/NnYfF7E12dk.wav"} +{"id": "NnmJ1UHWlas", "caption": "The low quality recording features a commercial song that consists of wooden percussion, soft kick hits, echoing bells, toms and buzzy synth lead. There is a very weird pause in the song, which was supposed to be a break. It sounds weird and minimal.", "audio": "/zhanghaomin/datas/musiccap/music_data/NnmJ1UHWlas.wav"} +{"id": "No4Bi6mG1J8", "caption": "The low quality recording features a rock song and it consists of harmonizing male vocals singing over groovy bass, punchy drums and electric guitar melody. It sounds completely crushed, muffled and messy, since the frequencies of the instruments are clashing with each other. Regardless, it still sounds energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/No4Bi6mG1J8.wav"} +{"id": "NoB_4XaZYVs", "caption": "This is an ambient jam performed on an electric guitar. The electric guitar is being played with an effect applied to it. There is a male voice describing the sound. The parts where he is not speaking could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/NoB_4XaZYVs.wav"} +{"id": "Npbs_4DZgEQ", "caption": "There is a very large bell ringing, and we hear the resonance thereafter. The bell rings repeatedly throughout the whole clip. The audio quality of the clip is poor, and we hear distortion in the clip as a result.", "audio": "/zhanghaomin/datas/musiccap/music_data/Npbs_4DZgEQ.wav"} +{"id": "NqDxpJ2uR_8", "caption": "Digital sound effects are rising in a high pitch along with the sound of ocean-waves. Then a song starts containing a digital/acoustic drum playing a simple and clear groove with a shaker sample as hi hat sound and a e-guitar finger picking a melody. This song may be playing as an intro for an informational video.", "audio": "/zhanghaomin/datas/musiccap/music_data/NqDxpJ2uR_8.wav"} +{"id": "Nqb7nw58q08", "caption": "The song is an instrumental. The song is medium tempo with a groovy drumming rhythm, percussive bass line and cool electric guitar riff played repeatedly. The song is exciting and energetic. The song has smooth jazz or funk jazz roots.", "audio": "/zhanghaomin/datas/musiccap/music_data/Nqb7nw58q08.wav"} +{"id": "Ns-iXXKmzzU", "caption": "This clip features a male voice singing the main melody. Toward the end, the voice transitions to a female voice to make this sound like a duet. This is accompanied by a harp sound plucking strings. Chimes are played when the voice transitions from male to female. There is no percussion in this song. The voices are calming and relaxing. The theme of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ns-iXXKmzzU.wav"} +{"id": "NsR60ehkHGA", "caption": "This is a Swiss rap music piece. There is a male vocal rapping in the German language. The melody consists of a repeating theme played by a synth sound. A low-to-medium range string sample can be heard every now and then. The rhythmic background consists of an electronic drum beat which contains very faint clicking sounds added for texture. It is an urban sounding piece. This piece would fit perfectly in the soundtrack of a crime movie that takes place in the ghettos of a German-speaking city.", "audio": "/zhanghaomin/datas/musiccap/music_data/NsR60ehkHGA.wav"} +{"id": "NsYVaRI6rXg", "caption": "The song is an upbeat pop song with a slight hip hop influence. It's a live performance and features a breathy, seductive female vocalist. The backup singers almost chant or laugh in a staccato way that creates a vocal riff. There are string instruments in the background. This is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/NsYVaRI6rXg.wav"} +{"id": "Nt0U-CXK6O0", "caption": "The low quality recording features a Chanson song that consists of passionate female vocal singing over mellow piano melody and soft sustained strings melody. The recording is noisy, crushed and it sounds vintage, and therefore sentimental and nostalgic.", "audio": "/zhanghaomin/datas/musiccap/music_data/Nt0U-CXK6O0.wav"} +{"id": "NtM3gudMBCQ", "caption": "This song is an instrumental. The tempo is medium fast with melodious steel pan, rhythmic percussion like bongos and congas, guitar sound, steady bass line and keyboard harmony. The sound of the breeze in the background indicates that music is being played outdoors. The music is invigorating, playful, light, pleasant, mellifluous and warm.", "audio": "/zhanghaomin/datas/musiccap/music_data/NtM3gudMBCQ.wav"} +{"id": "NuN-ug3dIkw", "caption": "This is the recording of an electronic dance music/rave party. The rhythmic background consists of a loud electronic drum beat. There is a synth playing a simple and repeated theme. The atmosphere is energetic. This piece could be played at nightclubs, dance clubs and rave events. It could also be playing at beach parties.", "audio": "/zhanghaomin/datas/musiccap/music_data/NuN-ug3dIkw.wav"} +{"id": "Nuks8XFdGMk", "caption": "The Ambient song features a widely spread dark mellow synth pad. There is a mellow noise sound effect at the beginning of the loop. It sounds dark, calming and relaxing - like something you would listen to while doing yoga.", "audio": "/zhanghaomin/datas/musiccap/music_data/Nuks8XFdGMk.wav"} +{"id": "NwA9JSlK_lM", "caption": "This is an Irish folk music piece. There is no singer. The main melody is being played by the uilleann pipes and the fiddle at a high pitch. The acoustic guitar is playing a rapid procession of chords in the background. The atmosphere is lively. This piece could be playing in the background at an Irish pub. It could also be used in the soundtracks of movies and TV shows that have a theme with an Irish influence.", "audio": "/zhanghaomin/datas/musiccap/music_data/NwA9JSlK_lM.wav"} +{"id": "NwUJe24OxC8", "caption": "The low quality recording features a live performance of a ballad song that consists of passionate male vocal singing over a mellow piano melody. It sounds soft, emotional, sad and heartfelt.", "audio": "/zhanghaomin/datas/musiccap/music_data/NwUJe24OxC8.wav"} +{"id": "NwfEO8cjSK0", "caption": "This is an analog sounding electronic jam. The automated melody is played by a sequencer that has a synthesizer base. The electronic drums in the rhythmic background have a 909-like sound. The atmosphere of the piece is very robotic and computer-like. This piece could be used in the soundtracks of movies and video games that have a cyberpunk/futuristic sci-fi theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/NwfEO8cjSK0.wav"} +{"id": "NxdQtpceXaI", "caption": "A male vocalist sings this energetic Rock song. The tempo is medium fast with an animated electric guitar harmony and lead, groovy bass lines,infectious drumming and keyboard harmony. The song is electric,pulsating, youthful, energetic, enthusiastic, passionate and powerful with emphatic vocals. This song is Heavy Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/NxdQtpceXaI.wav"} +{"id": "NxpnW_IdkSY", "caption": "The low quality recording features a live performance of a country melody on an acoustic rhythm guitar. There are some camera shuttering and beeping sounds in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/NxpnW_IdkSY.wav"} +{"id": "Ny4wnDN4K1U", "caption": "An acoustic drum is playing a constant groove along with an e-bass playing the footnote of an e-piano playing a major chord progression. A e-guitar is ending the phrases of the melody in a lower key. In the background you can hear bells playing. A female sounding voice is singing responding to a small choir taking turns singing a melody. This song may be playing during a cheerful event such as Christmas.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ny4wnDN4K1U.wav"} +{"id": "Nymjfq2kXnI", "caption": "A female vocalist sings this trippy vocal riff. The tempo is medium with atmospheric synthesiser and digital drums. The song is heavily synthesised and is psychedelic, intense, enigmatic, mysterious and youthful with a dance groove. This song is an EDM/Electro Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Nymjfq2kXnI.wav"} +{"id": "Nz4iLzJBTBo", "caption": "A female singer sings this animated melody. The song is medium tempo with church bells playing percussively, shakers percussion, walking bass line, steady drumming rhythm and keyboard harmony, the song is romantic and eclectic in nature. The song is an animated movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/Nz4iLzJBTBo.wav"} +{"id": "NzVg-cFQJbE", "caption": "This is a punk rock song with an energetic, youthful feel that is still grungy and gritty. The guitar is dark and powerful in the low tones, contrasted by another electric guitar that's bright and warm on the off beats. The drummer plays a high octane drum beat with drum fills between each line of the lyrics.", "audio": "/zhanghaomin/datas/musiccap/music_data/NzVg-cFQJbE.wav"} +{"id": "NzvkMWY4EjA", "caption": "Solo performance of an electric guitar player strumming chords. The tone is overdriven and warm. The genre is rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/NzvkMWY4EjA.wav"} +{"id": "O0sDg-yLvlE", "caption": "A male singer sings this gentle country music melody. The song is slow tempo with banjo, mandolin and guitar accompaniment and a double bass playing the lower register harmony. The song is emotional and nostalgic. The song is a country music hit with an average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/O0sDg-yLvlE.wav"} +{"id": "O0y-m0pCi5E", "caption": "This music is instrumental. The tempo is fast with a continuous droning harmony of the Didgeridoo and rhythmic beats of a small hand percussion.The music is unique, deep, droning, buzzing, hypnotic, psychedelic and incessant. This music is a Didgeridoo instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/O0y-m0pCi5E.wav"} +{"id": "O1EmHJyz5ds", "caption": "The song is an instrumental. The song is slow tempo with a piano playing beautifully with no other accompanying instruments. The song is emotional and relaxing. The song serves as soundtrack for an aquatic life documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/O1EmHJyz5ds.wav"} +{"id": "O1RmrE_HfpE", "caption": "This is a live acoustic performance piece. The didgeridoo is being used in varying ranges and effects to play many different tunes and to get a techno-like sound variety. There is a whole bunch of percussive instruments being used from membranous percussion to bell percussion. It all adds up into one big sensational performance. There is an eccentric atmosphere. This piece could be used in the soundtrack of a movie with a primitive/jungle setting. It could also be used in action or pursuit scenes in movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/O1RmrE_HfpE.wav"} +{"id": "O25IKwo2HkE", "caption": "This music is instrumental. The tempo is fast with an enthusiastic flute harmony and bassoon accompaniment. The music is upbeat, catchy, engaging, vivacious, melodic, cheerful, happy and pleasant. This music is an upbeat classical instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/O25IKwo2HkE.wav"} +{"id": "O28kY0aN8VI", "caption": "The Dance Electronic track features a filtered clapping, suspenseful synth arpeggio melody, shimmering open hat, subtle hi hat, tinny syncopated percussive element, groovy bongos located in the right channel and pulsating filter modulated riser that bring the energy up. In the second part of the loop there is a \"4 on the floor\" kick pattern with a slight variation, alongside wide, echoing female exhales and shimmering shakers. It sounds low quality, especially since there is a tiny audio cutout, but also energetic, like something you would hear in the clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/O28kY0aN8VI.wav"} +{"id": "O2HttJtcec4", "caption": "A male vocalist sings this soft melody. The tempo is slow with acoustic guitar accompaniment. The song is soft, mellow, dulse, emotional and gentle with minimal music. The song is a Christian Gospel Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/O2HttJtcec4.wav"} +{"id": "O3Cvn4yXrao", "caption": "Serious music in the gangster rap genre that features a strong male rapper with doubled vocals over a 90's hip hop beat. Deep bass drives the beat along with hand percussion, clap, electric piano, synth flute, and tambourine.", "audio": "/zhanghaomin/datas/musiccap/music_data/O3Cvn4yXrao.wav"} +{"id": "O40E8bpmONQ", "caption": "This ska song features a flute playing the main melody. Other flutes play staccato notes in the background. This is backed by trumpets playing chords in the background. The percussion plays a simple beat in common time. The double bass plays a 12-bar blues style bassline. There are no voices in this song. This is an instrumental. This song can be played at a Broadway event.", "audio": "/zhanghaomin/datas/musiccap/music_data/O40E8bpmONQ.wav"} +{"id": "O5IulN0n6d0", "caption": "A male rapper sings this cool melody with a backup singer in vocal harmony. The song is medium tempo with a groovy bass, keyboard playing harmony, stringed Asian instrument and a steady drumming rhythm. The song is story telling and passionate. The song is in poor audio quality and is a rap music video.", "audio": "/zhanghaomin/datas/musiccap/music_data/O5IulN0n6d0.wav"} +{"id": "O66lIRbF4Gw", "caption": "This is an electronic music piece with 80s disco characteristics. There is a slightly fast tempo electronic drums in the rhythmic background. The keyboard is holding the notes of the melody while a synth bass follows it with a repeated rhythmic pattern. Although it is a bit old-fashioned, it is a danceable piece. This music could work well with retro-themed parties at nightclubs. It could also fit nicely with action-filled social media content or the soundtrack of a car racing game.", "audio": "/zhanghaomin/datas/musiccap/music_data/O66lIRbF4Gw.wav"} +{"id": "O6QyYC7Tt2A", "caption": "A female choir is singing a melody. The instruments are playing the same melody. The percussion- section contains a bassline being played along with a tambourine. This song may be playing at a public folkfest.", "audio": "/zhanghaomin/datas/musiccap/music_data/O6QyYC7Tt2A.wav"} +{"id": "O6xMQnKJROc", "caption": "The low quality recording features a live performance of an orchestra that consists of staccato strings melody and sustained woodwinds melody at least. The recording is very noisy, to the point that it is distorting, and in mono - as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/O6xMQnKJROc.wav"} +{"id": "O73wigUotGo", "caption": "This is an amateur recording of a sound check jam. The audio quality is quite poor with an emphasis on the drum sound. There is a male vocal that can be barely heard over the sound of the bass guitar and the acoustic drums. The piece is easygoing. This recording can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/O73wigUotGo.wav"} +{"id": "O84YjlJ_Qw4", "caption": "The song is instrumental. The tempo is medium with a prolific fiddler playing melody and a banjo and guitar accompaniment. The song is adventurous and exciting. The song is a classic country instrumental. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/O84YjlJ_Qw4.wav"} +{"id": "O8EMm4QJjeo", "caption": "This is an experimental rock/indie rock music piece. The rhythmic background consists of a peculiar 6/8 acoustic drum beat that has shifted kick drum hits. There are sleigh bells accompanying the drums. The synth bass is playing a simple and repeated theme. The atmosphere is eerie. This piece could be used in the soundtrack of a noir movie where a character is devising a plan to deal with conflict.", "audio": "/zhanghaomin/datas/musiccap/music_data/O8EMm4QJjeo.wav"} +{"id": "O8rHjrG3HM4", "caption": "This track is purely percussion and features fast paced playing of rim shots, tom drums and a kick drum. There's also a clapping hands effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/O8rHjrG3HM4.wav"} +{"id": "O9Ag-dE-yfQ", "caption": "The Recording features a cover of a pop rock song and it consists of soft acoustic rhythm guitar located in the left channel and angelically harmonized mixed vocals singing on top of it. It sounds hopeful and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/O9Ag-dE-yfQ.wav"} +{"id": "O9_avJFKIQk", "caption": "The low quality recording features haunting and spooky noises of wind, sea and some church bell sound effects. Sounds like a thriller movie atmosphere.", "audio": "/zhanghaomin/datas/musiccap/music_data/O9_avJFKIQk.wav"} +{"id": "OA63sRxGk6o", "caption": "The low quality recording features a live performance of a female choir that consists of harmonizing female vocals. It sounds addictive, mellow and soft.", "audio": "/zhanghaomin/datas/musiccap/music_data/OA63sRxGk6o.wav"} +{"id": "OAl2EjbdQG8", "caption": "an uprising low modulated sound comes in with a lot of airy noise before a digital drum rhythm is playing. This is an amateur recording. This sequence may be playing at home programming a sampler.", "audio": "/zhanghaomin/datas/musiccap/music_data/OAl2EjbdQG8.wav"} +{"id": "OB7GyVqufwQ", "caption": "A digital drum is playing a reggaeton groove along with some acoustic percussion while someone is playing a turkish baglama. A male voice is singing/shouting. This is an amateur recording. This song may be playing outside busking with a band.", "audio": "/zhanghaomin/datas/musiccap/music_data/OB7GyVqufwQ.wav"} +{"id": "OBJM1TqPvu4", "caption": "Sinister sounding orchestral music with a foreboding low string melody using a tritone interval while the high strings and female choir hold a dissonant chord.", "audio": "/zhanghaomin/datas/musiccap/music_data/OBJM1TqPvu4.wav"} +{"id": "ODOrls3MuZI", "caption": "This pop song features a male and female voice singing the main melody. There are backing voices singing fills in between lines. Children sing in the background. This is accompanied by percussion playing a simple beat. The bass plays the root notes of the chords. A synth plays a pedal chord in staccato. This song can be played at the end credits of a holiday movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/ODOrls3MuZI.wav"} +{"id": "ODRAYQE9GXs", "caption": "Someone is strumming chords on an e-guitar while playing a melody with the harmonica in a higher register. This song may be playing gathered around a bonfire.", "audio": "/zhanghaomin/datas/musiccap/music_data/ODRAYQE9GXs.wav"} +{"id": "OECgm1obaFs", "caption": "This audio contains people playing a melody with bagpipes in a higher pitch. This song may be playing live during a traditional and formal event.", "audio": "/zhanghaomin/datas/musiccap/music_data/OECgm1obaFs.wav"} +{"id": "OEIj1UX5ZRg", "caption": "The low quality recording features a song that consists of pitch bend horn siren melody played over groovy piano chords, groovy bass, \"4 on the floor\" kick pattern, punchy snare and simple hi hats. At the end of the loop there is a short snare roll. The siren is very loud, and over time it sounds a bit uncomfortable, but it sounds fun and happy regardless - like something that kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/OEIj1UX5ZRg.wav"} +{"id": "OEjgIDubFbg", "caption": "A female singer sang this pop melody with female backup singers in vocal harmony. The song is fast tempo with various percussion instruments, but with a steady drumming rhythm, percussive bass line, guitar rhythm and keyboard accompaniment . The song is youthful and a party dance song. The song's audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/OEjgIDubFbg.wav"} +{"id": "OEpMpYMjO9Y", "caption": "Someone is scratching over a hip hop backing-track containing digital drums, a subby bassline and some pad sounds samples playing a melody. A male voice sample is shouting something. This song may be playing at home practicing scratching.", "audio": "/zhanghaomin/datas/musiccap/music_data/OEpMpYMjO9Y.wav"} +{"id": "OEuBITrf-kE", "caption": "The Metal song features a manic solo electric guitar melody over shimmering hi hats, shimmering crash cymbals, double pedal kick hits, punchy snare, groovy distorted bass guitar and aggressive electric guitar riffs. It sounds aggressive, manic and energetic - like something you would jump to at the concerts.", "audio": "/zhanghaomin/datas/musiccap/music_data/OEuBITrf-kE.wav"} +{"id": "OFJG5Wo_knI", "caption": "A female singer sings this vocal harmony with backup singers. The song is medium tempo with a steady drumming rhythm, tambourine percussion, groovy bass line and keyboard accompaniment. The song is trance-like and groovy. The song is a modern techno dance with an average audio quality. The song serves as a sound track for a car repairing video.", "audio": "/zhanghaomin/datas/musiccap/music_data/OFJG5Wo_knI.wav"} +{"id": "OFP5MYVDa4g", "caption": "The punk-rock music features a male voice singing a static melody. An electric guitar with a distortion effect accompanies the singer with repetitive chords. The drums play a simple and repetitive rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/OFP5MYVDa4g.wav"} +{"id": "OH2SQhJqZDg", "caption": "This music is an energetic Rock and Roll instrumental. The tempo is fast with animated, infectious drumming, lively trumpets and tambourine beats. The music is upbeat, pulsating, thumping, vivacious, bright, with a perky dance groove. This music is Rock and Roll.", "audio": "/zhanghaomin/datas/musiccap/music_data/OH2SQhJqZDg.wav"} +{"id": "OH8urnIthoQ", "caption": "This song is an instrumental solo. The tempo is medium fast with the guitarist playing an enthusiastic lead on an amplified guitar. The music is distorted with inferior audio quality. This song is a PopRock/Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/OH8urnIthoQ.wav"} +{"id": "OHZZuO2vY50", "caption": "The low quality recording features a shimmering cymbals in the left channel, alongside suspenseful didgeridoo melody, followed by tinny wooden percussion and violin melody in the right channel of the stereo image. The recording is noisy and due to the unconventional panning, the stereo image is unbalanced.Overall it sounds suspenseful and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/OHZZuO2vY50.wav"} +{"id": "OHrrS6AKW_c", "caption": "The tune is instrumental. The tempo is variable with a drum machine playing different styles and tempos. The song is a demonstration of a synth drum module with a guitar lead playing in the background. The audio quality is poor with hissing tones.", "audio": "/zhanghaomin/datas/musiccap/music_data/OHrrS6AKW_c.wav"} +{"id": "OI7S7vaBT4I", "caption": "A male vocalist sings this melodious country song. The tempo is medium with rhythmic acoustic guitar, fiddle, resonator, banjo, dobro and mandolin accompaniment, keyboard harmony, steady drumming and straight bass lines. The song is mellow, emotional, prayerful, pleading, sentimental, passionate and melodious. This song is Country Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/OI7S7vaBT4I.wav"} +{"id": "OII3VJoE0WA", "caption": "An acoustic drum is playing a funky groove with a crash hit while an e-bass with an effect on it is playing a melody along with an e-piano playing the same. Both are playing in the mid -range. This song may be playing practice for a concert with your band.", "audio": "/zhanghaomin/datas/musiccap/music_data/OII3VJoE0WA.wav"} +{"id": "OJuVsBojdvo", "caption": "This is an acapella version of a Christmas gospel music piece. There are children singing using the harmony singing technique. The piece has a heart-touching feel to it. This piece could be used in the soundtrack of a Christmas movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/OJuVsBojdvo.wav"} +{"id": "OKZF0oG1E14", "caption": "This is a musical piece. There is a story-telling mood in this piece. The female vocalist is singing about her troubles in a complaining manner. There are many instruments in the melodic background such as piano, strings, flute and upright bass. The atmosphere of the piece is easygoing and comedic.", "audio": "/zhanghaomin/datas/musiccap/music_data/OKZF0oG1E14.wav"} +{"id": "OKquGBKOgME", "caption": "The Funk song features a flat male vocal singing over widely spread, funky electric guitar chords, groovy bass guitar and energetic drums. It gives off happy and fun vibes, as it is probably very good for dancing with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/OKquGBKOgME.wav"} +{"id": "OLy3C8YpMsY", "caption": "The music features a female voice quietly singing a melody. A harp is accompanying the singer. Violins can be heard fading out from the beginning of the music excerpt. In the background one can hear the wind blowing softly. Towards the ending of the music excerpt a low pitch percussive sound can be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/OLy3C8YpMsY.wav"} +{"id": "OM04OFjNPGw", "caption": "A male singer sings this death metal melody with screaming vocals. The tempo is fast, with fast metal drumming, percussive bass line, rhythmic distorted guitar play and various percussion hits. The song is exciting and high on adrenaline. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/OM04OFjNPGw.wav"} +{"id": "OMApGp219Zc", "caption": "You can hear a bell ringing with a lot of release time. In the background a bird is chirping. This song may be used for starting a documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/OMApGp219Zc.wav"} +{"id": "OMcoFfaCaGM", "caption": "The low quality recording features a digital drum machine playing tinny syncopated percussion, shimmering hi hats, soft crash cymbals, punchy kick and snare hits. It sounds energetic, groovy and the rhythm of the hi hats is being modulated in the second half of the loop.", "audio": "/zhanghaomin/datas/musiccap/music_data/OMcoFfaCaGM.wav"} +{"id": "ONfd_rHtL74", "caption": "This funk rock song features a male voice singing the main melody. This is accompanied by percussion playing a simple beat. A tambourine, snare and kick are played simultaneously on every count. The tambourine plays on the eighth note. This song is common time. A repetitive piano melody is played in the background. The bass plays the root notes with fills. A whistling sound is played in the gap between lines. At the beginning and toward the middle of the song, the sound of strings is heard playing a short lick. This song can be played in a spy romance movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/ONfd_rHtL74.wav"} +{"id": "OO1Q-3kXCtM", "caption": "The low quality recording features a widely spread harmonizing french horn melody. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/OO1Q-3kXCtM.wav"} +{"id": "OOik9i9wrU8", "caption": "The low quality recording features a groovy bass guitar, punchy \"4 on the floor\" kick pattern and tinny percussion. In the second half of the loop the music cuts out and there is a short silence, after which comes the wide, muffled sound effects. At the very end, there is a slow riser, bringing the energy up.", "audio": "/zhanghaomin/datas/musiccap/music_data/OOik9i9wrU8.wav"} +{"id": "OPX9ukYun3o", "caption": "This is an amateur recording of a dance performance. There is a zumba dance music version of a movie theme playing in the background. The melody is being played by the strings and the keyboard while there is a loud electronic drum beat for the rhythm. There is a mysterious yet energetic feel to this piece. The recording quality is not that great. However, this piece could still be used to gather samples for beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/OPX9ukYun3o.wav"} +{"id": "OPimGlHcSRQ", "caption": "Fun, energetic music played back live in a large room. Boomy low fidelity sound. The music itself is rock n' roll from the 1950's featuring boogie woogie piano, loud drums and a charismatic male singer.", "audio": "/zhanghaomin/datas/musiccap/music_data/OPimGlHcSRQ.wav"} +{"id": "OQz8reoVQEI", "caption": "The low quality recording features a live performance of salsa music and it consists of flat male vocal talking over microphone, followed by groovy piano melody, some percussive elements, groovy bass and energetic crash cymbals. There are some loud crowd cheering noises and claps. It sounds exciting and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/OQz8reoVQEI.wav"} +{"id": "OR_YbeqV5tA", "caption": "The song features a calm, gentle male vocalist. It feels like a soft pop ballad, with a slight rock influence. There's an electric guitar arpeggio, bongo drums, and a prominent bassline. The song feels like it would be suitable as a loving dedication to someone.", "audio": "/zhanghaomin/datas/musiccap/music_data/OR_YbeqV5tA.wav"} +{"id": "ORikRIu7s1o", "caption": "A female singer sings this emotional melody. The song is medium tempo with guitar strumming rhythm, strong bass line, steady drumming rhythm, keyboard accompaniment and sound effects. The song is emotional and romantic. The song is a euro pop love song and has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/ORikRIu7s1o.wav"} +{"id": "ORt8LSgn-uA", "caption": "This is a quintessential indie garage rock band. The singer is calm and sings with a sort of haunting demeanor typical of this style. It's a live recording and the audio is of low quality. The singer goes off-pitch at one point.", "audio": "/zhanghaomin/datas/musiccap/music_data/ORt8LSgn-uA.wav"} +{"id": "OS4YFp3DiEE", "caption": "This music is an Arabic instrumental. The tempo is medium fast with a harmonious oud and Arabic hand percussion. The music is lilting, spirited, engaging, pleasant, traditional , middle eastern folk music.", "audio": "/zhanghaomin/datas/musiccap/music_data/OS4YFp3DiEE.wav"} +{"id": "OSlotCnSFow", "caption": "The rock song features a fruity male vocal with occasional echoing effects, singing over punchy kick and snare hits, energetic cymbals, wide electric guitar melody and distorted bass guitar. Towards the end of the loop, there is a stuttering effect, which makes a perfect variation for such an energetic and aggressive song. It also sounds addictive, due to that cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/OSlotCnSFow.wav"} +{"id": "OTu_vWZV4QA", "caption": "This sound is produced on a didgeridoo. The song has a droning sound interspersed with sounds of bass notes. There is a rhythm to this droning and bass sound but there is no melody. This song has a tribal feel. This song can be played in a movie scene where a person is lost in a forest.", "audio": "/zhanghaomin/datas/musiccap/music_data/OTu_vWZV4QA.wav"} +{"id": "OVNVaXZ9D0E", "caption": "The song is an instrumental. The song is medium tempo, with a keyboard accompaniment and string pad section. The song is emotional and passionate. The song is a movie soundtrack with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/OVNVaXZ9D0E.wav"} +{"id": "OWbfAmrFdp8", "caption": "This is an acoustic drum jam. The drummer is playing rapidly using the double bass technique which is an iconic technique used in metal drumming. The atmosphere is loud and aggressive. This piece can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/OWbfAmrFdp8.wav"} +{"id": "OZjpYGdvMX0", "caption": "Someone is playing a slightly distorted e-guitar. A funky riff is being played and repeated. The audio-quality is not the best. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/OZjpYGdvMX0.wav"} +{"id": "OZv8mtQEgA0", "caption": "This audio clip features programmed percussion playing a trap beat. Hi-hats are played at a very fast tempo. The kick drum plays continuously in eighth notes. The sound of racing cars is the main point of focus in this clip. There are no voices. There are no other instruments and no melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/OZv8mtQEgA0.wav"} +{"id": "Ob9iaGon5ak", "caption": "The excerpt features a song sounding from a speaker and being recorded with an amateur device like a phone. After a finger snap, the same song can be heard recorded in similar conditions but lower in volume.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ob9iaGon5ak.wav"} +{"id": "Obtx-A9Lt5c", "caption": "This song contains digital drums playing a four on the floor rhythm with a strong kick on every beat. A male voice is singing at a higher pitch. This song may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/Obtx-A9Lt5c.wav"} +{"id": "Occ4uW0lw0k", "caption": "This slow rock song features a female voice singing the main melody. This is accompanied by a piano and no other instruments. The piano plays chords backing the voice. It fills in between lines. The mood of the song is relaxing. This song can be played at a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/Occ4uW0lw0k.wav"} +{"id": "OcdrbkDm2LQ", "caption": "The Soul Instrumental features an addictive marimba melody, shimmering shakers, punchy kick hits, syncopated snare and tinny metallic percussive elements. It sounds narrow because it is recorded with one mono room microphone and therefore it is a low quality recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/OcdrbkDm2LQ.wav"} +{"id": "OdLCoLVRCmk", "caption": "This jazz song features a saxophone solo. This is accompanied by percussion playing at a fast tempo. The overall tempo of this song is moderate. The double bass plays on the off beats. A piano plays jazz chords in the background. There are no voices in this song. This song can be played in a luxury bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/OdLCoLVRCmk.wav"} +{"id": "OeNTAUKZgKs", "caption": "This is a dub/jazz music piece. There is an electric guitar playing the main melody while a fat bass guitar is supporting it in the background. The rhythm is being played by a laid-back acoustic drum beat. The atmosphere is chill and trippy. This piece could be playing in the background at a dance club for a slow dance night. It could also be used in the soundtrack of a romance movie that takes place in the city, especially during intimate scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/OeNTAUKZgKs.wav"} +{"id": "Oe_xSG_ic-c", "caption": "The low quality recording features a live performance of a jazz song and it consists of a saxophone solo melody played over mellow keys chords, groovy bass, punchy snare and kick hits and shimmering hi hats. It sounds passionate and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/Oe_xSG_ic-c.wav"} +{"id": "Ofry7lyQZDA", "caption": "We have an Urdu speaking male narrator, speaking over some ambient background music. The music is tranquil, relaxing and features the use of traditional South Asian melodies and instruments. We hear a Bansuri being played, and a stringed instrument on which arpeggios are being played.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ofry7lyQZDA.wav"} +{"id": "OgqDO1wxQ8E", "caption": "This audio contains an acoustic piano playing a minor key melody that sounds like being in a dream along with strings rising up from the background playing a melody in the low to the higher register. This song may be playing for a lovely movie scene where birds are flying in slow motion and kids are playing outside.", "audio": "/zhanghaomin/datas/musiccap/music_data/OgqDO1wxQ8E.wav"} +{"id": "OhZmxS5DUKU", "caption": "A male singer sings this youthful k-pop song. The tempo is fast with a heartbeat rhythm, electro static sounds, electric buzz, followed by a fast paced drum rhythm, guitar accompaniment and a groovy bass line. The song is groovy and very youthful.", "audio": "/zhanghaomin/datas/musiccap/music_data/OhZmxS5DUKU.wav"} +{"id": "OheHnFixwVk", "caption": "This song contains a piano-composition with a lot of reverb playing a relaxing melody while running a waterdrippling sample. This song may be playing at home for meditation or sleeping.", "audio": "/zhanghaomin/datas/musiccap/music_data/OheHnFixwVk.wav"} +{"id": "OiAJB9uydS8", "caption": "This music is instrumental. The tempo is medium with a piano harmony with the voice of a child speaking and a bee buzzing superimposed on the music. This clip is a tutorial on how to speak English. The music is subdued with the emphatic and loud voice of the child.", "audio": "/zhanghaomin/datas/musiccap/music_data/OiAJB9uydS8.wav"} +{"id": "OiNlYrlJE4g", "caption": "This music is instrumental. The tempo is slow with a euphonious harp melody with no accompaniment. The music is soft, mellow, ethereal, melancholic, nostalgic, pensive, soft and ambient. This music is a Western Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/OiNlYrlJE4g.wav"} +{"id": "OjEG808MfF4", "caption": "This music is an electric guitar solo. The tempo is medium fast with rhythmic bongo , atmospheric synthesiser, soft drumming with Cymbal rides, oud riff and keyboard harmony. The music is densely layered. It is soothing, engaging, compelling, mesmerising and building up gradually. This music is Contemporary Indian Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/OjEG808MfF4.wav"} +{"id": "OjoDuBkPDM8", "caption": "Someone is playing an acoustic guitar flamenco style finger-picking while a female voice sings loud and emotionally. This song may be playing live in a restaurant. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/OjoDuBkPDM8.wav"} +{"id": "OjvWDzPGeic", "caption": "This clip features a live recording of an ice-cream truck playing music. This music is high pitched. There is ambient noise that can be heard in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/OjvWDzPGeic.wav"} +{"id": "Ok-ia7ziJy0", "caption": "This song contains people strumming chords on acoustic guitars while a banjo and a mandolin are taking turns playing a lead melody. In the background you can hear an upright bass playing a fitting bassline. This song may be playing live while having a BBQ with friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ok-ia7ziJy0.wav"} +{"id": "OkcBJawiIHA", "caption": "This music is instrumental. The tempo is slow with a melancholic piano melody with violin harmony and keyboard accompaniment. The music is sad, mellow, grim, sombre, wistful, poignant, pensive, melancholic and reflective. This music is a soundtrack for a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/OkcBJawiIHA.wav"} +{"id": "OmjfHQB_lcs", "caption": "A male singer sings this passionate melody with auto tuned vocals. The song is medium tempo with Indian percussion, dholak percussion, keyboard accompaniment and various percussion hits. The song is a Punjabi pop song with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/OmjfHQB_lcs.wav"} +{"id": "On9epzZ_ceI", "caption": "The Video Game Sound recording features a lot of in-game sound effects of the main character and his surroundings, followed by background, jazzy music in the background. The music contains funky piano chord progression, groovy bass and uptempo drums. There are some man grunts sound effects, funny spring sound effects, some beeping sound effects and at the very end of the loop a gun reload sound effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/On9epzZ_ceI.wav"} +{"id": "OnL-e9X0oEc", "caption": "This song features a female voice singing the main melody. This song has a Middle-Eastern feel. The voice is accompanied by percussion playing a dance beat. A synth plays a high pitched melody in between lines. A synth pad plays chords in the background. The bass plays the root notes of the chords. Toward the end, all instruments except the synth pads pause. The voice continues to sing at this time. An autotune effect is used on the voice. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/OnL-e9X0oEc.wav"} +{"id": "OoJGMj5H7Wk", "caption": "This is a recording of one note being played on the guitar, followed by some string bending. There is then a dialogue between male Japanese speakers.", "audio": "/zhanghaomin/datas/musiccap/music_data/OoJGMj5H7Wk.wav"} +{"id": "OoRUo92emGo", "caption": "The low quality recording features a synth pad played at the very beginning of the loop, after which basic sine wave tone is played. It sounds weird and like a tutorial for making music.", "audio": "/zhanghaomin/datas/musiccap/music_data/OoRUo92emGo.wav"} +{"id": "OoyxPPoPmt0", "caption": "This amateur recording features a folk song played in India. The main melody is sung by a male voice. This is accompanied by a tabla and dhol playing the percussion parts in an Indian beat. A sarangi plays the same melody as the main voice. The sitar plays the rhythm parts. Cymbals are played at every count of each bar. This song can be played for a cultural dance programme.", "audio": "/zhanghaomin/datas/musiccap/music_data/OoyxPPoPmt0.wav"} +{"id": "OpWCljke4oQ", "caption": "This is a pop music ballad piece. There is a male vocal singing melodically in the lead with a female back vocal singing at a higher pitch in the background. The melodic background consists of the strings, the keyboard and the bass guitar. There is a 6/8 slow tempo acoustic drum beat in the rhythmic background. The piece has an emotional atmosphere. This piece could be used in a romantic setting such as a slow dance night event or a wedding. It could also be used in the soundtrack of a romance movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/OpWCljke4oQ.wav"} +{"id": "Or4CALipjig", "caption": "Someone is playing a melody on a theremin along with acoustic drums holding a groove with 8th notes on the ride while an e-bass and an acoustic guitar are playing along. The acoustic guitar is being strummed. This song may be playing on a relaxed car ride.", "audio": "/zhanghaomin/datas/musiccap/music_data/Or4CALipjig.wav"} +{"id": "Orge4_UlvNI", "caption": "The low quality recording features a live performance of a traditional song that consists of flat male vocal singing over wooden percussive elements, sustained strings melody and woodwinds melody. The recording is very noisy and buzzy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Orge4_UlvNI.wav"} +{"id": "OrsfEkAhie4", "caption": "This is an Indian classical instrumental. The tempo is fast with a vigorous tabla and Sitar introduction with temple bells, acoustic guitar,Manjira taal or small Indian hand cymbals and a traditional harmonium accompaniment. The simple instruments are layered perfectly and are in absolute sync to create this complex music. The music is fast and vigorous at the onset and settles down to a more mellow and easy rhythm. This music is a Hindustani Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/OrsfEkAhie4.wav"} +{"id": "OseeYF_ud7g", "caption": "Someone is playing a fast paced melody on a sitar accompanied by someone playing a rhythm on tablas. This song may be playing live during a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/OseeYF_ud7g.wav"} +{"id": "Ou2rEaq28PM", "caption": "This is a reggae/dub music piece. There is a fat sounding bass guitar playing a groovy bass line. An electric guitar with heavy delay and reverb effects is playing a vague tune. There is a reggae acoustic drum beat in the rhythmic background. The atmosphere is trippy. This piece could be used in the soundtrack of a movie during scenes where a character would be under the influence of substances.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ou2rEaq28PM.wav"} +{"id": "Ou7vteWmqfw", "caption": "This blues song features a male voice singing the main melody. This is accompanied by the percussion playing a simple beat. The percussion plays the tambourine as well. The bass plays the same licks played on the guitar. The guitar plays notes that are octaves apart. Toward the end of the song, an overdrive guitar plays a hammer on note. The mood of this song is comforting. This song can be played in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ou7vteWmqfw.wav"} +{"id": "OvX68hqDjeA", "caption": "The low quality recording features a hip hop song, that consists of flat male vocal rapping over widely spread shimmering bells, punchy kicks and claps, playing in the background. Right before the beat drops there is a short flat female vocal. There are some people talking to each other, while one of them is yelling. It sounds noisy and haunting and energetic thanks to the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/OvX68hqDjeA.wav"} +{"id": "OvjmfGU4y_M", "caption": "This is the compilation of live performances from a pop music boy band. There are teen male vocalists singing melodically. The melody is being played by an acoustic guitar and a bass guitar while an acoustic drum beat is playing in the rhythmic background. There are sounds of a crowd singing and cheering. The recording quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/OvjmfGU4y_M.wav"} +{"id": "Ovk5EfFj7Ws", "caption": "Male vocalist sings this upbeat Hip-Hop song. The tempo is fast with minimal instrumentation of a lively infectious, punchy drumming and enthusiastic vocal backup and incessant, vigorous vocalisation. The song is buoyant, catchy, punchy, funky, youthful,groovy, engaging, vibrant and vivacious. This song is contemporary Hip-Hop/Rap.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ovk5EfFj7Ws.wav"} +{"id": "OwUzGq0ceT8", "caption": "The song is an instrumental. The tempo is medium with theremin playing passionately, steady drumming rhythm ,groovy bass line and keyboard accompaniment . The tunes are Christmas carols with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/OwUzGq0ceT8.wav"} +{"id": "OwukabRF7I4", "caption": "The electro song features a speeding up, widely spread, synth lead, white noise riser and punchy snare going from left to the right channel in the stereo image. At the very beginning there is a short snippet of a bit more energetic part which contains \"4 on the floor\" kick pattern, synth pad chords and addictive synth lead. Overall it sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/OwukabRF7I4.wav"} +{"id": "OxxRnDpN9cc", "caption": "This classical sonata features a harpsichord playing a melody. This is accompanied by a cello playing the bass notes. There are no other instruments in this song. There is no voice in this song. This song can be played as a lullaby.", "audio": "/zhanghaomin/datas/musiccap/music_data/OxxRnDpN9cc.wav"} +{"id": "OyRtTtTSXuM", "caption": "This song starts with a descending phrase played on a synth. This is followed by an ascending phrase on another synth. This is accompanied by simple programmed percussion playing the hi-hat on the first two counts and the fourth count of each bar. The snare is played on the third count of each bar. After four bars, the percussion plays a roll and the bass plays one note two times. The synth sounds in the background get louder when the roll is played. There are no voices in this song. This song can be played in a night club.", "audio": "/zhanghaomin/datas/musiccap/music_data/OyRtTtTSXuM.wav"} +{"id": "OyouRYAq-tE", "caption": "This audio contains someone playing an upright bass with a bow. The melody sounds a little bit dangerous and tension building. This song may be playing in a movie scene where someone is being followed.", "audio": "/zhanghaomin/datas/musiccap/music_data/OyouRYAq-tE.wav"} +{"id": "OzaVvthCvtk", "caption": "This is an Indian folk music piece. There is a haunting female vocal in the lead. There is a group of strings which sound similar to Esraj being heard playing the main tune. In the rhythmic background, there are bell percussion that sound like manjira and membranous percussion that sound like tabla. The atmosphere is trippy. This piece could be used in the soundtrack of an exotic movie or could be sampled to be used in beat-making. It could also be playing in the background of an Indian cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/OzaVvthCvtk.wav"} +{"id": "P-eIhvCaK-s", "caption": "This is an instrumental heavy metal piece. There is a bass guitar gently playing the melody with a clean sound. It is a melodic piece with a touch of melancholy. This piece can be used in the soundtrack of a drama movie or a TV series, especially during flashback scenes. It could also be used in video games during story exposition cutscenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/P-eIhvCaK-s.wav"} +{"id": "P007re8_iyY", "caption": "This orchestral song starts with a melody played on a reed instrument backed by strings and the triangle. This is followed by the horn section playing a descending run. The violin plays a solo after the horn section. The violins are backed by the bass played on viola or cello. The mood of this song is comedic. This song can be played in a movie scene where a criminal is planning a cunning tactic.", "audio": "/zhanghaomin/datas/musiccap/music_data/P007re8_iyY.wav"} +{"id": "P0vjXnnIiR4", "caption": "This song features a melody played on an acoustic guitar. Delay and reverb effects are added to the sound. This song starts off with notes being fingerpicked. The second bar involves a chord being held and allowed to ring for four counts. This is followed by a double stop and then descending notes played with a higher open string. The melody is romantic. There are no voices in this song. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/P0vjXnnIiR4.wav"} +{"id": "P14zjckYFK0", "caption": "The low quality recording features an electro song that consists of a filter modulated bass, repetitive, echoing electric guitar melody, punchy kick and snare hits, shimmering hi hats and a saxophone solo melody played at the end. It sounds passionate and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/P14zjckYFK0.wav"} +{"id": "P1Vxm_ICSG0", "caption": "The Electro song features a filter modulated synth melody, groovy synth bass, shimmering hi hats, punchy kick and snare hits, followed by short snare roll, haunting synth lead, low pitched male vocal introducing the section and high pitched riser that builds the energy up. It sounds energetic, upbeat and exciting - like something you would hear in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/P1Vxm_ICSG0.wav"} +{"id": "P240GHf9Eq4", "caption": "This song is an instrumental. The tempo is medium with a melodious keyboard harmony, rhythmic guitar accompaniment, punchy drumming, subtle bass line, synth arrangement and tambourine beats. The music is soft, mellow, ambient, pleasant, uplifting, and mellifluous.", "audio": "/zhanghaomin/datas/musiccap/music_data/P240GHf9Eq4.wav"} +{"id": "P25JeM4lPGw", "caption": "The low quality recording features a live performance of a folk/country song that consists of flat female vocal singing over smooth double bass, groovy acoustic rhythm guitar, violins melody and groovy snare rhythm. It sounds a bit noisy and roomy, as it was probably recorded with a stereo microphone technique, but also energetic, uptempo and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/P25JeM4lPGw.wav"} +{"id": "P2F4iNqJmNU", "caption": "This song features the sound of a saxophone playing in the background. This is accompanied by the sound of a dog howling. There is no melody to the howling. This song has no other instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/P2F4iNqJmNU.wav"} +{"id": "P2UqnWU8d8o", "caption": "The low quality recording features an uptempo didgeridoo melody. It sounds reverberant, as it was probably played in a medium size room, and the recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/P2UqnWU8d8o.wav"} +{"id": "P39x5dOsJ40", "caption": "The low quality recording features a drummer playing his solo over a weird repetitive electric guitar solo melody. The drums consist of punchy kick and snare hits and shimmering cymbals. Overall it sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/P39x5dOsJ40.wav"} +{"id": "P3ZPbGjHFXE", "caption": "The low quality recording features a live performance of a rock song that consists of passionate male vocal singing over electric guitar solo melody, energetic cymbals, muffled snare and kick hits and groovy bass guitar. There are also some crowd noises, singing along. It sounds energetic, emotional and addictive, thanks to that cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/P3ZPbGjHFXE.wav"} +{"id": "P3aeojk4lCs", "caption": "The Folk song features muffled mixed vocals singing over, what it sounds like, orchestra in the background. The recording is so noisy and low quality that the listener can barely hear the actual song. It is mono and it sounds vintage and sentimental.", "audio": "/zhanghaomin/datas/musiccap/music_data/P3aeojk4lCs.wav"} +{"id": "P4aTFrJws40", "caption": "This is an instrumental music piece that was made for a soap opera soundtrack. The piano and the strings are playing gently in a melancholic manner. The atmosphere of the piece is emotional. This piece could be used in the soundtrack of a drama movie during scenes of hopelessness or heartbreak.", "audio": "/zhanghaomin/datas/musiccap/music_data/P4aTFrJws40.wav"} +{"id": "P4zWSoib5BU", "caption": "A deep male voice is talking then starts strumming chords on an acoustic guitar while blowing a melody on top with a harmonica. This song may be playing live explaining music.", "audio": "/zhanghaomin/datas/musiccap/music_data/P4zWSoib5BU.wav"} +{"id": "P54hbuQLkc4", "caption": "The low quality recording features foley effects that include metallic, wooden and screeching sound effects. At the very end of the loop, there is an intense background orchestra music, representing some combat scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/P54hbuQLkc4.wav"} +{"id": "P5AgEqouchI", "caption": "The low quality recording features a theremin solo melody played over playback that has a sustained strings melody playing. It sounds emotional, sad, heartfelt and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/P5AgEqouchI.wav"} +{"id": "P5IxlG4-CY8", "caption": "Someone is playing maracas very skillfully while an acoustic guitar is supported with strumming chords that are constantly changing. This sounds like an amateur recording. This song may be playing at a local music store where people jam.", "audio": "/zhanghaomin/datas/musiccap/music_data/P5IxlG4-CY8.wav"} +{"id": "P5tsRM1iokA", "caption": "Someone is playing a melody on a slide guitar over a backing track containing an uptight bass, acoustic guitar and mild acoustic drum groove. This song may be playing outside on a sunny day practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/P5tsRM1iokA.wav"} +{"id": "P5uIpVLEpm4", "caption": "This music is instrumental. The tempo is fast with an electric guitar riff playing a cover of a popular melody. The music is intense, loud, passionate, violent, aggressive and thunderous. This music is heavy metal/ death metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/P5uIpVLEpm4.wav"} +{"id": "P65yE_EXLd8", "caption": "This song is an animated duo in a male and female volume. The tempo is slow with a Pisano harmony, synthesiser arrangement and a small hand percussion. The song is a lively, simple, expressive,animated, rhythmic and informational children\u2019s song/ nursery rhyme .", "audio": "/zhanghaomin/datas/musiccap/music_data/P65yE_EXLd8.wav"} +{"id": "P8nK4i8XscM", "caption": "This is the comedic mashup used as a video game theme. There is a synth and an electronic drum beat playing the theme of \"I'm a Barbie Girl\". There is a male vocal and a female vocal singing in an automated fashion in the English language but with a German accent. They are singing the same tune as \"I'm a Barbie Girl\" but with different lyrics. There is an 8-bit sound effect related to the game. There is a sarcastic atmosphere in the piece, but it is also a bit bizarre in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/P8nK4i8XscM.wav"} +{"id": "P90rFZQFqWk", "caption": "This song is a low quality live recording of a performance. This features a male voice singing the main melody. At the end of the song, other voices sing with the main voice in harmony. This is accompanied by an electric guitar plucking chords. The double bass plays the root notes of the chords. The percussion plays the cymbal, increasing volume slowly, giving it a swell feel. The mood of the song seems romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/P90rFZQFqWk.wav"} +{"id": "P97w3AdePgQ", "caption": "This music is a latin dance piece. There is a trumpet playing a vibrant melody as a lead with latin percussive elements playing a syncopated beat in the background. Then a piano fill is played to connect the previous section to the next one followed with a voice announcement. This piece could be used for latin dance courses and dance themed events at bars.", "audio": "/zhanghaomin/datas/musiccap/music_data/P97w3AdePgQ.wav"} +{"id": "P996TZp25PM", "caption": "This song is an instrumental. The tempo is slow with a keyboard harmony, steady bass lines, congas and bongo rhythm and sound of an instrument like a harp and string instrument like a ukelele or Hawaiian guitar.The music is soft, mellow, pleasant and simple with the sound of people talking in the background. This is a Regional/Folk Pop instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/P996TZp25PM.wav"} +{"id": "P9fh7rOIKcM", "caption": "The excerpt features a melody played in the background on what sounds to be an accordion. In the foreground one can notice various sounds from punching to glass being broken. The crowd is cheering. All this leads me to believe this isn't a song but instead someone playing a fighting game.", "audio": "/zhanghaomin/datas/musiccap/music_data/P9fh7rOIKcM.wav"} +{"id": "PAX2PMha2dU", "caption": "The song is an instrumental piece with various tracks. The song is medium tempo with a piano accompaniment, groovy bass line , steady drumming track, a male sighing in pleasure and water filling a bottle tone. The song is a mix bag of music tracks for various scenes. The song is an instrumental track for a funny YouTube video.", "audio": "/zhanghaomin/datas/musiccap/music_data/PAX2PMha2dU.wav"} +{"id": "PB3i02Cjf1k", "caption": "Someone is strumming chords on an e-guitar. The e-guitar is slightly out of tune. This song may be playing at home trying out sounds on the e-guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/PB3i02Cjf1k.wav"} +{"id": "PBMfPDei93s", "caption": "A female singer sings this passionate melody backed up by singers in vocal harmony. The tempo is slow with a strong bass line, steady percussive rhythm and keyboard accompaniment. The song is emotional and spirited. The song is a modern hip hop hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/PBMfPDei93s.wav"} +{"id": "PBqNpMpD76k", "caption": "The low quality recording features a tropical song playing over speaker and it consists of jazzy drums, muddy bass and exotic marimba melody. It is mono and noisy, while there are also some crowd mumbling and water splashing noises in the background. It sounds thin and loud, but tropical and exotic - like something you would listen to on a vacation.", "audio": "/zhanghaomin/datas/musiccap/music_data/PBqNpMpD76k.wav"} +{"id": "PE1ges9nn6A", "caption": "The music features a female voice singing a long note melody for the first half of the excerpt. The drums play a steady rhythm and together with the bass guitar and tambourine drive the pulse of the music. A synth sound is playing a wobbly melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/PE1ges9nn6A.wav"} +{"id": "PF5LgwJjYuA", "caption": "This is an Armenian pop music ballad piece. The male vocalist is singing in a sentimental manner. The melody is being played by the piano and the strings section while the bass guitar plays a simple bass line composed of root notes. The rhythmic background is provided by a 6/8 slow tempo acoustic drum beat. The atmosphere is romantic. This piece would fit perfectly in an Armenian wedding. It could also be included in the soundtrack of a romance movie that takes place in Armenia.", "audio": "/zhanghaomin/datas/musiccap/music_data/PF5LgwJjYuA.wav"} +{"id": "PF6Mn51Nkvs", "caption": "This song is an instrumental. The tempo is slow with melodic violin, punchy bass lines, slick drumming, cymbal ride,vibrant trumpet, table turner and sounds in the background like thudding, clashing, glass shattering and crashing . It is soft, mellow, soothing and ambient.This music is contemporary Soul.", "audio": "/zhanghaomin/datas/musiccap/music_data/PF6Mn51Nkvs.wav"} +{"id": "PFX2OO75sRQ", "caption": "The Hip Hop/Rap song features a flat male vocal with filtered, background male vocals, rapping over repetitive plucked synth melody and addictive synth lead melody, followed by distorted 808 bass, snaps and some offbeat hi hats. The whole sound is distorted and everything is in mono, which makes the song low quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/PFX2OO75sRQ.wav"} +{"id": "PFa1XVCgPgM", "caption": "The low quality recording features a live performance of a classical song that consists of a fruity male opera singer over a piano melody. In the background there are coughing and telephone ring sounds. The recording is noisy, muffled and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/PFa1XVCgPgM.wav"} +{"id": "PFtcnQqLdEc", "caption": "This audio contains drum-rolls in the background playing along with a brass section and flutes. In the foreground someone is playing the same melody on a theremin. This song may be practicing playing along with an instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/PFtcnQqLdEc.wav"} +{"id": "PIIAyM4H1UE", "caption": "This clipping is an instrumental with rapid synthesised chimes like sound and a boomy bass drop against white noise. The contrast of the psychedelic fast music against the boom drop gives it an eerie vibe. It is sinister, spine-tingling, scary, spooky and spine-chilling.", "audio": "/zhanghaomin/datas/musiccap/music_data/PIIAyM4H1UE.wav"} +{"id": "PJRG2bwphUc", "caption": "The low quality recording features a female vocal singing with left-panned echoing effect, which creates this unbalanced stereo image. In the background, there is a harmonizing male vocal, followed by a rumbly sound effect located in the right channel of the stereo image. Sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/PJRG2bwphUc.wav"} +{"id": "PJUffXn-LIk", "caption": "This is the ending of a female choir performing on stage. It appears to be in a graduation ceremony setting. The crowd starts cheering and applauding the choir after the show is over.", "audio": "/zhanghaomin/datas/musiccap/music_data/PJUffXn-LIk.wav"} +{"id": "PKJMsnUJ994", "caption": "This audio contains gambelan bamboo mallets playing a melody in the higher mid-range along with a flute playing a melody in the higher register. In the background spread across the sides of the speakers you can hear different birds chirping. This song may be playing during a traditional dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/PKJMsnUJ994.wav"} +{"id": "PKsdjH0RmsU", "caption": "This music is a beautiful ,soothing instrumental. The tempo is slow with a wind instrument like a recorder/flute solo and an acoustic guitar accompaniment. The music is dulcet, serene,calming, soothing, mellifluous,soulful, therapeutic and idyllic. This is a folk song instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/PKsdjH0RmsU.wav"} +{"id": "PN3Lx8RutmI", "caption": "A male vocalist sings this energetic song. The tempo is fast emphatic vocals, bright acoustic guitar accompaniment and clap beat. The song is youthful, energetic, popular, cheerful, engaging and happy. The music is minimal with ambient sounds of people clapping, cheering, singing along and keeping beat with claps. The audio is distorted and muffled as it is an amateur home recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/PN3Lx8RutmI.wav"} +{"id": "PNT3hW4qFpQ", "caption": "The low quality recording features a live performance of the percussive & arpeggiated acoustic guitar melody. There are some crowd chattering noises in the background, by which we can definitely conclude that it is, in fact, a live performance. Sounds a bit boomy and the high frequencies of the guitar are lacking volume.", "audio": "/zhanghaomin/datas/musiccap/music_data/PNT3hW4qFpQ.wav"} +{"id": "POOu05eUvqE", "caption": "This music is a beautiful Harp instrumental. The tempo is slow with a mellow, gentle and rich Harp melody. The music is dreamy, cascading, ethereal, soothing, calming and harmonic. This music is a Western Classical Harp Solo.", "audio": "/zhanghaomin/datas/musiccap/music_data/POOu05eUvqE.wav"} +{"id": "PP3kNqPM434", "caption": "This punk rock song features a male voice singing the main melody at a comfortable pitch. This is accompanied by percussion playing a simple rock beat. A distortion guitar plays power chords using downstrokes. The bass plays the root notes of the chords. This song is played at a moderate tempo. This song can be played at the end credits of an action movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/PP3kNqPM434.wav"} +{"id": "PQ7cX2Cnusg", "caption": "This rock song features a guitar solo played on a guitar with heavy distortion. The solo starts off with high pitch notes being played. This is followed by a dive bomb using the whammy bar. The guitar then plays a descending lick followed by scratch harmonics and another descending run. This is accompanied by percussion playing a powerful rock beat in common time. The bass plays the root notes of the chords. Another distortion guitar plays power chords to back the lead guitar. There are no voices in this song. This song can be used in a car chase sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/PQ7cX2Cnusg.wav"} +{"id": "PQXYWc3JHhU", "caption": "The low quality recording features an arpeggiated synth melody, followed by synth pad chords. It sounds mellow, soft and relaxing, while the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/PQXYWc3JHhU.wav"} +{"id": "PQrYV7hJWDg", "caption": "This is an educational pop music piece. There is a female vocalist singing out-of-tune. The strings and the acoustic guitar are playing a simple tune while the rhythmic background is provided by a basic acoustic drum beat. The aura of the piece is generic and monotonous. The quality of the recording is subpar. It might be useful in the class setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/PQrYV7hJWDg.wav"} +{"id": "PRRcVdXsBQg", "caption": "Here we have a gentle and soothing instrumental piece on the piano and clarinet. The pianist plays an accompaniment to the lead melody of the clarinet - which feels like a relaxing afternoon at the beach. This is a live recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/PRRcVdXsBQg.wav"} +{"id": "PRzBkZSSyY0", "caption": "This recording contains a male voice speaking than you can hear a wooden clicking sound that comes from an instrument called three tone wood blocks. This may be playing in a tutorial video showing off your instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/PRzBkZSSyY0.wav"} +{"id": "PSYURntIjuc", "caption": "Animated vocalists singing a choral harmony. The song is medium tempo with no instrumentation, but just voices singing in various harmonic ranges. The song is cheerful and cartoonish. The song is a parody of a modern pop song with western classical music influences.", "audio": "/zhanghaomin/datas/musiccap/music_data/PSYURntIjuc.wav"} +{"id": "PTCsH-ffeq4", "caption": "This audio contains wind sounds, disturbing noises, a heart that is beating and dissonant synth strings in the background creating a scary atmosphere and tension. On top of that a synthesizer is playing a scary melody. This song may be playing in a horror film-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/PTCsH-ffeq4.wav"} +{"id": "PTLOLz9YzmM", "caption": "The song is an instrumental. The tempo is medium with a techno drumming rhythm, various string instruments playing melodies, flute playing, Indian dhol percussion and a tambourine playing percussively. The song is romantic and has Indian classical music influences. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/PTLOLz9YzmM.wav"} +{"id": "PTl5ixI1Ogc", "caption": "The ambient song features crickets, frogs and other night insects and animals sound effects, widely spread throughout the stereo image, while there is a reversed dark, mellow piano melody playing. It sounds calming and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/PTl5ixI1Ogc.wav"} +{"id": "PUy3cnNk4ys", "caption": "This is a gear showcase jam. There is an electric guitar playing simple tunes first without and then with a vibrato tailpiece to show the difference between two setups. The atmosphere is easygoing. Although the recording is a bit dated, the electric guitar could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/PUy3cnNk4ys.wav"} +{"id": "PWVr9weg00U", "caption": "A trombone is ending a melody together with a tuba and other brass instruments before going into the next part that sounds fast paced and uplifting. This song may be playing at a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/PWVr9weg00U.wav"} +{"id": "PXd0NCqZLzU", "caption": "This song contains a lot of atmospheric noise, sounds rising and falling in velocity and panning to the left and right side of the speakers with a lot of reverb. A high pitched pluck sound is playing a faster melody that is slightly panned to the right side while digital drums are only playing hihat and light snare sounds panned to both sides of the speakers and using a lot of delay and reverb. This song may be playing in a scary videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/PXd0NCqZLzU.wav"} +{"id": "PZZxVIIOQPo", "caption": "This folk song features the main melody played on the clarinet. This is accompanied by percussion played by hand. The tambourine is playing on every count. The bass plays with a groovy feel. The bass plays notes continuously at every count. The mood of this song is upbeat and happy. There are no voices in this song. This song can be played at a celebration party.", "audio": "/zhanghaomin/datas/musiccap/music_data/PZZxVIIOQPo.wav"} +{"id": "PaQGXIh94uc", "caption": "The song is an instrumental. The song is medium tempo with a ukulele played with a fast strumming technique. The song is groovy and melancholic. The song audio quality is poor but is very relaxing to listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/PaQGXIh94uc.wav"} +{"id": "PbUyPbafFh0", "caption": "This song is played on a French horn. There are no other instruments. The first part of this song consists of short bursts of two note pairs played twice followed by one stretched note in an ascending sequence. This is followed by three descending notes. Then two ascending notes are played. This is again followed by three descending notes. It ends with two more ascending notes. There are no voices in this song. This song is an instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/PbUyPbafFh0.wav"} +{"id": "PcdpjUIa8l0", "caption": "someone is masterfully scratching over an instrumental containing percussive elements with strings/sounds and a bass note on the kick. This audio is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/PcdpjUIa8l0.wav"} +{"id": "Pd4WnsXwdqw", "caption": "The Children song features a mellow kid vocal singing over groovy bass, punchy kick and snare hits, shimmering hi hats, shimmering bells melody, plucked strings melody and wide keys melody. It sounds happy, joyful and fun - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pd4WnsXwdqw.wav"} +{"id": "PdgswSjYhMw", "caption": "This is a live performance of an alternative rock music piece. There is a male vocalist singing in a drowsy manner in the lead. The main tune is being played by a keyboard with an organ sound meanwhile the electric guitar and the bass guitar are supporting it in the background. The rhythm is being provided by a slow tempo acoustic drum beat. The atmosphere is melancholic. This piece can be used in the soundtrack of a drama TV series, especially during the scenes where a character feels like they are depressed.", "audio": "/zhanghaomin/datas/musiccap/music_data/PdgswSjYhMw.wav"} +{"id": "PduP4CpaDtY", "caption": "The low quality recording features a children's song played on some small device that reproduces mono sound. The song consists of a funny male vocal, alongside harmonizing vocals, singing over a shimmering bell melody and some claps. It sounds happy, fun, joyful, muffled and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/PduP4CpaDtY.wav"} +{"id": "PeQ8L_svYcU", "caption": "This song has some experimental sounds. The string instrument sounds processed and slightly oriental. The synth plucks sound as running through different effects that are changing the bit rate and some filters. These elements are panned to the right and left and right side of the speakers playing different melodies. An acoustic drum is holding the whole construct together while an e-bass is playing his own run along with the drums. An e-guitar is playing long single chords. This song may be playing in an adventurous indie-videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/PeQ8L_svYcU.wav"} +{"id": "PeWXdkEUPbo", "caption": "This is a pop music piece meant for a wedding. There is a male vocalist singing melodically. An acoustic guitar is gently playing arpeggios. The atmosphere of the piece is mellow. This piece could be played at weddings or in the background of wedding-related content.", "audio": "/zhanghaomin/datas/musiccap/music_data/PeWXdkEUPbo.wav"} +{"id": "PemDZNVE370", "caption": "The low quality recording features a live performance of softly arpeggiated harp melody and mellow sustained strings. It sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/PemDZNVE370.wav"} +{"id": "Pf9AaTV4-yw", "caption": "A male opera singer sings this majestic operatic song with a philharmonic orchestra accompaniment, trumpets blaring, string section accompaniment and a strong rhythm section with loud timpani playing. The song is energetic and dramatic. The song is a movie soundtrack and western classic song with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pf9AaTV4-yw.wav"} +{"id": "PfO7ZVdzfZ4", "caption": "The Rock song features a passionate male vocal singing over punchy kick and snare hits, shimmering hi hats, groovy bass guitar and electric guitar melodies. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/PfO7ZVdzfZ4.wav"} +{"id": "PfpP3WjY118", "caption": "This song features a harmonica playing two notes. There is no melody in this song. There are no other instruments in this song. An audience member can be heard laughing in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/PfpP3WjY118.wav"} +{"id": "Pgpd1yxLcLI", "caption": "The song is an instrumental. The tempo is medium with a groovy bass line, keyboard accompaniment, percussive bass line , steady drumming drumming and other percussion hits. The song is a pop song cover with a bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pgpd1yxLcLI.wav"} +{"id": "Phy-_ko0zWU", "caption": "This is a live performance of a Scottish folk music piece. It is an instrumental piece. There is a single player on stage playing the Scottish bagpipes. There is a lively, ceremonial atmosphere to this piece. This piece could fit well in the soundtrack of a historical drama taking place in Scotland.", "audio": "/zhanghaomin/datas/musiccap/music_data/Phy-_ko0zWU.wav"} +{"id": "Pk5NZe-ah4U", "caption": "This music is instrumental. The tempo is medium fast with a melodic keyboard harmony, punchy drumming, funky bass lines, and rhythmic acoustic guitar, whistle harmony and clapping and fingers snapping.The melody is simple, sunny, warm, energetic and youthful with a retro vibe. This music is classic Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pk5NZe-ah4U.wav"} +{"id": "PkkhCW04O9k", "caption": "This audio contains someone slowly finger picking a chord up and down ending on the root note. This is an amateur recording and may be used for educational purposes.", "audio": "/zhanghaomin/datas/musiccap/music_data/PkkhCW04O9k.wav"} +{"id": "PlQibWaPAcM", "caption": "This music is instrumental. The tempo is fast with the musician playing a high , vigorous, high pitched melody on a Glass harp or angelic organ. The music is sharp, unique, enchanting, and celestial with no accompaniment.", "audio": "/zhanghaomin/datas/musiccap/music_data/PlQibWaPAcM.wav"} +{"id": "Pln4GLIMqKY", "caption": "This song has a typical reggaeton drumbeat that just sounds a little softer and not so much in the foreground. A synthetic bass is supporting the drums with a simple bassline. A processed guitar-like sound is panned to the left side of the speakers. Some gameboy coinlike sound is popping up here and there. A male voice is rapping while getting backing voices from another male voice. This song may be playing at a latin barber shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pln4GLIMqKY.wav"} +{"id": "Pm6vRblouxc", "caption": "The low quality recording features a R&B song that consists flat male vocal singing over layered repetitive plucked arpeggiated melody and synth arpeggiated melody, followed by smooth synth bass, bouncy snare, punchy kick, bright hi hats triplets and low toms. It sounds energetic and groovy, although it seems that the song is finishing, judging by the arrangement.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pm6vRblouxc.wav"} +{"id": "PmiH7RnCkhI", "caption": "The low quality recording features an echoing electric guitar melody played over shimmering cymbals, groovy bass guitar and synth bells melody. It sounds weird, suspenseful and intense. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/PmiH7RnCkhI.wav"} +{"id": "Pn8HqUbNQAc", "caption": "A male guitar player plays a guitar riff followed by an introduction of a guitar effects flanger pedal. The video has an instrumental solo of a guitar playing rhythm and no other instrumentation. The soundtrack has a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pn8HqUbNQAc.wav"} +{"id": "PnJx0uLJ_oE", "caption": "The low quality recording features a traditional song that consists of a flat male vocal singing over shimmering hi hats, strings melody and wooden percussion, while a male vocal is mocking them. It sounds groovy, funny and it gives off happy vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/PnJx0uLJ_oE.wav"} +{"id": "PpJKo-JPVU0", "caption": "Low fidelity recording of a solo banjo playing a banjo roll and plucking double stops in a bluegrass style.", "audio": "/zhanghaomin/datas/musiccap/music_data/PpJKo-JPVU0.wav"} +{"id": "PpamaOkNqoI", "caption": "This is an acoustic drums lesson recording concerning how to play double stroke rolls on the toms. Initially, there is a rapid drum fill that can be heard. Then, a male voice starts speaking in an instructive manner.", "audio": "/zhanghaomin/datas/musiccap/music_data/PpamaOkNqoI.wav"} +{"id": "Pq1jBX0RW2k", "caption": "This recording contains synth pads playing in the mid range, with added notes in the higher register playing a slow melody and also a padsound in the lower register serving as bass. The sound of waves and noises rising and falling like wind. Whales are singing at a higher pitch with a lot of reverb. This recording may be playing for a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pq1jBX0RW2k.wav"} +{"id": "PqN7aT4dVN4", "caption": "This song contains an acoustic drum playing a reggae rhythm along with an e-guitar with effects strumming a chord on the backbeat. A bass is playing a simple repeating line while an organ is playing a rhythmic melody panned to the right side of the speakers. A female voice is singing at a higher pitch. This song may be playing chilling at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/PqN7aT4dVN4.wav"} +{"id": "PqTPbZf44E0", "caption": "This music is instrumental. The tempo is slow with the musician plucking a single string of a ukelele. This audio is of a Ukelele being tuned.", "audio": "/zhanghaomin/datas/musiccap/music_data/PqTPbZf44E0.wav"} +{"id": "PqTTIfja0y8", "caption": "This clip features a South Asian, Indian song . There's a singer with a passionate vocal singing atop a tabla being played. There are manjeeras. The recording is of a live performance and it's low quality audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/PqTTIfja0y8.wav"} +{"id": "PrMKUjFxrvQ", "caption": "The noisy low quality recording features a loud bagpipes melody played while people are marching. It sounds reverberant as it was recorded outdoors. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/PrMKUjFxrvQ.wav"} +{"id": "PuJxL6tLxm4", "caption": "The low quality recording features a crowd talking and clapping to a soul song that is played on a playback. The song consists of a passionate female vocal, alongside mixed harmonizing vocals, singing over sustained strings melody, simple bass and harp melody. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/PuJxL6tLxm4.wav"} +{"id": "PufDOSkxwzQ", "caption": "The low quality recording features a dissonant harmonica melody, followed by lag tapping, birds chirping and dog barking sounds, as it was recorded outdoors. The recording is noisy and it sounds like a tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/PufDOSkxwzQ.wav"} +{"id": "Puu8SEqYN0k", "caption": "This is an excerpt from a horror movie trailer. There are ominous sound effects related to the movie such as heartbeat, a man beating a woman and a terrified female voice sounding like she is dying. There is cinematic sounding synth and a piano hitting the same high pitch note repeatedly in the theme. The atmosphere is bleak. Sounds from this track could be used as samples in beat-making. They could also be used in violent video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/Puu8SEqYN0k.wav"} +{"id": "Pv8ZWvM8bhw", "caption": "The low quality recording features a cowbell percussion, after which there is a tinny metallic impact. It sounds loud, resonating and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pv8ZWvM8bhw.wav"} +{"id": "PvHKu1XRSJ0", "caption": "This is the recording of a tuning video in the key of D sharp. There is an electric guitar playing the note on each string repeatedly. This piece could be used to lift samples to be used in a beat or in the making of a virtual guitar plug-in.", "audio": "/zhanghaomin/datas/musiccap/music_data/PvHKu1XRSJ0.wav"} +{"id": "PwmXO0J-PAA", "caption": "This is an alternative country music piece. There is a male vocal singing melodically with a thick reverb effect applied to it. The main tune is being played by the electric guitar with the bass guitar backing it. The rhythm is being provided by an acoustic drum beat. The atmosphere is easygoing. This piece can be used in the soundtrack of a drama movie, especially during the scenes where a character is trying to break free from an addiction.", "audio": "/zhanghaomin/datas/musiccap/music_data/PwmXO0J-PAA.wav"} +{"id": "PxXR74Uohfg", "caption": "This audio contains someone playing a very fast groove on tablas then another instrument takes over playing the same rhythm on a metallic rattle instrument. You can hear people talking and the crowd is cheering. The atmosphere sounds relaxed and joyful. This song may be playing live at an instrument battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/PxXR74Uohfg.wav"} +{"id": "PxxyplPsqBY", "caption": "This song is an electronic instrumental. The tempo is fast with heavily synthesised sounds, digital drum arrangements and electronic beats. The music is youthful, groovy, pulsating, electrifying, buoyant, thumping, psychedelic, trance like and trippy. This music is Techno Pop/EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/PxxyplPsqBY.wav"} +{"id": "Py8Vd0-qxYU", "caption": "A female vocalist sings this Spanish melody. The tempo is medium with keyboard harmony, tambourine beats, rhythmic congas and acoustic guitar. The song is upbeat, buoyant, groovy, lively, spirited,youthful and engaging. This is an outdoor live performance as there are ambient sounds like gentle wind, people talking, clapping and cheering. This song is a lively Spanish Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Py8Vd0-qxYU.wav"} +{"id": "PyVuHAskeUg", "caption": "The low quality recording features a cover of a rock song that consists of passionate electric guitar melody playing over playback. The playback features a groovy bass guitar, punchy snare and kick hits, shimmering cymbals and mellow synth key chords. It sounds groovy - thanks to the bass-drums relationship and passion - thanks to the electric guitar melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/PyVuHAskeUg.wav"} +{"id": "Pzp_oTEn0Yk", "caption": "This is a toy package opening video with a jazz music piece in the background. In the piece, there is a clarinet playing the leading melody while other brass elements, the piano and the upright bass are accompanying it with backing tunes. The rhythm is being played by the upbeat jazz acoustic drums. The atmosphere of the piece is lively. If the package opening sounds could be removed, the piece would suit well in the soundtrack of a feelgood animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Pzp_oTEn0Yk.wav"} +{"id": "Q-ATDBgDbLE", "caption": "This is a chamber music piece. It is performed by a quintet of the harp, the flute, the violin, the viola and the cello. There is a constant rising and falling pattern, resembling the feeling of a wave. The piece has a mysterious atmosphere to it. This music would fit perfectly in the soundtrack of an adventure movie during scenes of a journey where the characters are crossing the sea.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q-ATDBgDbLE.wav"} +{"id": "Q0KwG3ynscI", "caption": "In the foreground you can hear a saw wave pad playing along with a sub bass. This sound got some reverb and delay on it. The drums sound electronic and repeat a rhythm that leaves a lot of space for the bass sounds. This song may be played at a dance battle or an underground club.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q0KwG3ynscI.wav"} +{"id": "Q0VVfneN8MI", "caption": "This audio contains someone picking and strumming a fast paced melody on the mandolin. This song may be playing live in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q0VVfneN8MI.wav"} +{"id": "Q1LJotkUbUY", "caption": "Strings are playing a mid range drone sound along with a guitar playing a melody with reverb on it. A transverse flute is playing the main melody. This song may be playing in a lush adventure nature movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q1LJotkUbUY.wav"} +{"id": "Q1pjymZOm6Q", "caption": "A male singer sings this cool hip hop melody with backup singers in vocal harmony and screaming vocals. The song is medium tempo with a piano accompaniment, percussive bass line, steady drumming rhythm, clapping percussions, and keyboard accompaniment. The song is passionate like a courtship song. The song has bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q1pjymZOm6Q.wav"} +{"id": "Q2Omtt4A8ls", "caption": "This song contains someone playing a rhythm on a djembe along with a frame drum. Someone is strumming chords on guitar while the bagpipes are taking the main melody. Then a male voice starts speaking and the crowd is cheering and clapping their hands. This song may be playing live at a traditional concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q2Omtt4A8ls.wav"} +{"id": "Q6G1XGwd-rM", "caption": "The low quality recording features a flat male vocal talking, after which there is an acoustic guitar percussive tapping. The recording is in mono and so noisy that it is almost crushed.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q6G1XGwd-rM.wav"} +{"id": "Q6SgmlYMYLA", "caption": "This song contains e-guitars playing short repeating melodies. An acoustic drum is playing a slow drum and bass like groove with 8th notes on the ride. An e-piano is playing single high pitched notes on top. In the strings a string/pad section is playing long notes/chords in the mid range. This song may be playing at home on a loud speaker.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q6SgmlYMYLA.wav"} +{"id": "Q6dVti1YVwM", "caption": "Vintage south Asian Bollywood music featuring sitar and an orchestral string melody which uses a pentatonic scale. The song follows a waltz rhythm, using three beats to the measure.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q6dVti1YVwM.wav"} +{"id": "Q75y0TIp7Ds", "caption": "The Classical music features a happy sounding piano chord progression and happy woodwind instrument, followed by rhythmic shoe tapping foley effect. you could tell that the music is played on speakers, while the foley artist is trying to sync the shoe tapping to the scene. Judging by the audio cutouts and mono sound, you could tell that it is an old, low quality, recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q75y0TIp7Ds.wav"} +{"id": "Q789S_9JCio", "caption": "a pop hip hop track in a boy band style with harmonized male vocals, skittering hi-hat pattern, and an 808 style bass. Would appeal to international teens.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q789S_9JCio.wav"} +{"id": "Q7oWXOByo28", "caption": "This electropop song features a female voice singing a repetitive melody. The voice seems like it is coming from a distance. This is accompanied by programmed percussion playing a disco beat. The kick is played at every count. The bass plays a funky bass line using octaves and filler notes in between. There are synth layers that are played in this song. One synth layer plays a piano-sounding loop only with chords. Another synth layer plays an ascending and descending loop according to the chords being played. This song has a happy mood and can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q7oWXOByo28.wav"} +{"id": "Q8QXzYpl6Tw", "caption": "This piece contains someone playing a trumpet, a clarinet and a horn all playing the same note in different octaves. The horn is playing a bassnote. This song may be playing live as a school concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q8QXzYpl6Tw.wav"} +{"id": "Q8X6geEBR2o", "caption": "This is a pop rock music piece. There is a female vocalist singing melodically in the lead. The acoustic guitar and the electric guitar are playing a chill melody while the bass guitar is playing a simple bass line. The acoustic drums are playing in the rhythmic background. The atmosphere is easygoing and generic. This piece could be used as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q8X6geEBR2o.wav"} +{"id": "Q8f6y2IcVg0", "caption": "The low quality recording features a live performance of a rock song that consists of echoing, energetic male vocals that are singing over wide electric guitar chord progression, energetic crash cymbals, punchy snare, boomy kick and groovy bass guitar. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q8f6y2IcVg0.wav"} +{"id": "Q9gWfok9Q5c", "caption": "This recording contains a short musical melody but can not be labeled a song. The recording is full of creepy low voices and sound effects. This may be playing on a mobile phone videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q9gWfok9Q5c.wav"} +{"id": "QBMM1ocXkhY", "caption": "A male vocalist sings this spirited hip-hop. The tempo is fast with synthesiser articulation, digital drum arrangements and vocal backup. The music is a youthful , enthusiastic, bouncy, punchy rhythmic patter with a dance groove. This song is contemporary Hip-Hop/ Rap.", "audio": "/zhanghaomin/datas/musiccap/music_data/QBMM1ocXkhY.wav"} +{"id": "QBhhtVMiQBQ", "caption": "This file contains a more complex composition full of percussive elements spread across the sides of the speakers. A violin is playing a melody along to some bell sounds and a keyboard/string sound playing a chord rhythmically. A male voice is singing long notes in a higher key. This song may be playing as a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/QBhhtVMiQBQ.wav"} +{"id": "QCbUlDMu7Hk", "caption": "This is Samoan folk music. There is a choir singing melodically with male and female voices mixed. The electric guitar is playing a simple tune in the melodic background.", "audio": "/zhanghaomin/datas/musiccap/music_data/QCbUlDMu7Hk.wav"} +{"id": "QDTCAxyXt80", "caption": "This audio contains someone playing an acoustic piano along with an acoustic guitar strumming chords. Someone is playing a cajon with a fast paced groove and a tambourine. A horn takes the main melody in the midrange along with a male voice singing in a higher key. This song may be playing on the streets performed by buskers.", "audio": "/zhanghaomin/datas/musiccap/music_data/QDTCAxyXt80.wav"} +{"id": "QFhmzRkUx0I", "caption": "A male vocalist sings this energetic song. The tempo is medium fast with enthusiastic vocal backup, bright electric guitar lead and harmony, infectious drumming, keyboard accompaniment and groovy bass lines. The backup is a spirited recurring vocal riff. The song sounds like an anthem or cheer chant to show support for a team.it is passionate, enthusiastic, energetic, spirited, youthful and fervent.", "audio": "/zhanghaomin/datas/musiccap/music_data/QFhmzRkUx0I.wav"} +{"id": "QHCHK-NPO_U", "caption": "A group of male vocalists sing this charming melody in a foreign language. The tempo is fast with accordion lead music and acoustic guitar accompaniment. The song is lively, happy, light , warm, cheerful and charming . The audio quality is inferior as it seems to be an amateur home recording with ambient sounds. This Song is a Folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/QHCHK-NPO_U.wav"} +{"id": "QHNREJJRTS4", "caption": "This reggae song features a male voice singing the main melody. This is accompanied by percussion playing a simple reggae beat. The bass plays notes in reggae style. A guitar plays fills in the beginning and in between lines. Hand claps are played in groups of two and one in an alternating pattern. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/QHNREJJRTS4.wav"} +{"id": "QHmGUrpOgAU", "caption": "The music features an ukulele playing a combination of melody and arpeggiated accompaniment. There are no other instruments, this is a solo interpretation.", "audio": "/zhanghaomin/datas/musiccap/music_data/QHmGUrpOgAU.wav"} +{"id": "QIjShFhrp6w", "caption": "This is an instrumental blues music piece. A clean electric guitar is playing a groovy solo while the bass guitar plays in the background. The acoustic drums are playing a slow tempo blues beat. The piece has a relaxing atmosphere. It could be playing in the background at a rock bar. This piece could also be playing in the soundtrack of a romantic movie especially during flirting scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/QIjShFhrp6w.wav"} +{"id": "QIzSxE0WlKE", "caption": "The low quality recording features a mellow french horn melody, followed by mellow piano chords. It sounds passionate, emotional and beautiful, despite the fact that the recording is noisy, buzzy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/QIzSxE0WlKE.wav"} +{"id": "QJzveo6IBsU", "caption": "The low quality recording features an orchestra music that contains haunting sizzling bells melody, low wooden percussions, sustained strings melody and sustained brass melody. It sounds suspenseful and intense, as background music for movies would sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/QJzveo6IBsU.wav"} +{"id": "QK-mjNg8cPo", "caption": "This is an American folk music piece. There is a male vocalist singing in the folk style. The banjo is playing a cheerful melody at a steady tempo. The atmosphere of the piece is cozy and easygoing. This piece could be playing in the background at a roadside diner. It could also be included in the soundtrack of a movie or a TV show taking place in rural USA.", "audio": "/zhanghaomin/datas/musiccap/music_data/QK-mjNg8cPo.wav"} +{"id": "QKkhwAAGLIE", "caption": "A musician plays this classical instrumental. The tempo is medium with the musician playing a beautiful harmony using ragas with skill and dexterity with a tanpura accompaniment .The music is calming, complex, pleasant, classic and melodic.", "audio": "/zhanghaomin/datas/musiccap/music_data/QKkhwAAGLIE.wav"} +{"id": "QMoRiBjRLKc", "caption": "This sound is a synth played through a delay and reverb effects unit. A seven note ascending pattern is played which echoes due to the delay. The reverb effect gives it depth. This song can be played in a video game at different levels. There are no other instruments in this music. There are no voices in this music.", "audio": "/zhanghaomin/datas/musiccap/music_data/QMoRiBjRLKc.wav"} +{"id": "QNQ3sAMxZPY", "caption": "This low quality audio features an accordion playing the main melody. This is accompanied by percussion playing a simple beat. A tambourine is played with the percussion. This is a Latin style song. The guitar plays groups of three ascending and one descending note per bar. The bass plays a Latin rhythm. There are no voices in this song. This song is an instrumental. This song can be played at a house party.", "audio": "/zhanghaomin/datas/musiccap/music_data/QNQ3sAMxZPY.wav"} +{"id": "QQTWFTNy-WA", "caption": "This is an afrobeat remix of a hip-hop music piece. There is a male vocalist singing in a rap-like manner. A repeated hollering sample can be heard. The rhythmic background is provided by a variety of afro percussion elements. There is a danceable feel to it. This piece could be played at nightclubs or dance clubs. It could also be used as an accompaniment piece at a modern dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/QQTWFTNy-WA.wav"} +{"id": "QRKc90kuAaE", "caption": "This composition contains acoustic drums playing a complex groove on just the snare using brushes. The crowd in the background is cheering, whistling and clapping their hands. A bass, piano and horn section is playing a melody as a counter-beat along with trumpets playing along a modified melody in a higher register. Then saxophones are coming in playing their own countermelody. This song is highly complex and may be playing at a jazz festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/QRKc90kuAaE.wav"} +{"id": "QS3DabGF41Y", "caption": "This is an instrumental rock music piece. The piece is being performed on a clean sounding electric guitar. There is an easygoing guitar solo being played. The atmosphere is groovy. This piece could be used as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/QS3DabGF41Y.wav"} +{"id": "QSaX7QfeWog", "caption": "This is the live performance of a country music piece. There is a female vocal and two male vocals taking turns and sometimes singing the words at the same time. The melody consists of an electric guitar, an acoustic guitar and a bass guitar while in the rhythmic background there is an acoustic sounding upbeat drum beat. The atmosphere is cozy. There is an easygoing aura to it. This piece could be used in the soundtrack of a movie or a TV show that takes place in rural USA.", "audio": "/zhanghaomin/datas/musiccap/music_data/QSaX7QfeWog.wav"} +{"id": "QT1SjY9mQxc", "caption": "The low quality recording features a classical song that consists of a suspenseful brass melody, sustained strings and dynamic low percussion roll, after which there is an alarm sound. It sounds suspenseful, dramatic and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/QT1SjY9mQxc.wav"} +{"id": "QUB_vpjogmo", "caption": "The low quality recording features a dark moody piano melody and at the very end of the loop, a short snippet of muffled snare hit and flat male vocals. It sounds very noisy, as there are vinyl cracklings, but also warm, suspenseful, dark and dramatic - almost like a horror movie melody theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/QUB_vpjogmo.wav"} +{"id": "QUtyeIooCy4", "caption": "The low quality recording features wide shimmering bells, some inhale sounds, muffled acoustic rhythm guitar chords and natural sound effects. It sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/QUtyeIooCy4.wav"} +{"id": "QVpsAY9oR_4", "caption": "This song is a spirited Latin instrumental. The song is fast tempo with distorted keyboard harmony, electric guitar and percussion with some vocalisation. The song quality is inferior but the vibe of the song is upbeat, peppy, happy, celebratory, energetic with the sound of chatter in the background. This song is Latin pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/QVpsAY9oR_4.wav"} +{"id": "QXe9BpTENCc", "caption": "This carnatic song features a female voice singing the main melody. This is accompanied by percussion played on the ghatam. A violin plays a melody matching the vocal melody. A morsing is played in the background. Other instruments are not clearly audible due to the low quality of recording. This song can be played in a religious gathering.", "audio": "/zhanghaomin/datas/musiccap/music_data/QXe9BpTENCc.wav"} +{"id": "QYxFWV85-pg", "caption": "The song is music created by a toothbrush. The tempo is medium and sounds like a female singer singing in high pitch, motor whirring sounds and button clicks. The audio is poor quality in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/QYxFWV85-pg.wav"} +{"id": "QZNrK337wow", "caption": "This is a clip featuring an electric guitar being played through an amp. First a chord is played. This is followed by a descending pentatonic lick being played. This lick has a blues feel. This is an instrumental song. There are no voices in this song. There are no other instruments in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/QZNrK337wow.wav"} +{"id": "QZoclbefgak", "caption": "The low quality recording features a live performance of a rock & roll song performed by passionate female vocal and male vocal ad libs, followed by groovy piano melody, funky electric guitar melody, groovy bass guitar, shimmering hi hats, punchy snare and soft kick hits. It is a bit noisy and there are some subtle microphone feedback sounds in the middle of the performance. It sounds energetic, vintage and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/QZoclbefgak.wav"} +{"id": "Q_3GACs__Xs", "caption": "This is a low quality recording. This folk dance song is a fusion of traditional folk song with contemporary dance music. Traditional percussion instruments are played at the beginning of the clip. A female voice sings the main melody. The percussion continues to play in the background. This song has a hip-hop feel. A quirky voice sings high pitched sounds in the background. Other instruments cannot be identified due to the low quality of recording. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/Q_3GACs__Xs.wav"} +{"id": "Qa-Qs9CtOOw", "caption": "The track features a scary and cinematic atmosphere. Doom-like sounds play a progression that evokes a horror feeling. The instrumental is simple and almost abstract.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qa-Qs9CtOOw.wav"} +{"id": "QdoTdG_VNV4", "caption": "The song is an instrumental. The tempo is medium with the glass harp being played percussively by two glass harpists with no other instrumentation . The song is mysterious and ethereal in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/QdoTdG_VNV4.wav"} +{"id": "Qe71m678qEU", "caption": "This amateur recording features an overdriven guitar playing the main melody. This is a low quality recording and the volumes of the instruments are not professionally mixed. The overdriven guitar is loud. A piano plays a couple of notes in the beginning. The guitar is accompanied by percussion playing a simple beat in the background. The bass plays a blues style bassline. The tempo of this song is slow. The song is based on blues style.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qe71m678qEU.wav"} +{"id": "Qe_KwKVDgoE", "caption": "This clip features a saxophone being played. Only one note is played on the instrument and the note fades away. As it fades away, the sound of air being blown through it can be heard. There are no other instruments in this song. There are no voices in this song. This song can be played in an instructional video.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qe_KwKVDgoE.wav"} +{"id": "Qf87MJcWZQI", "caption": "This song contains digital drums almost playing a drum&bass groove along with a triangle sound. A synth bass is playing a melody with digital strings in a higher key. A synth pluck is playing a short melody on top. A female voice is singing the main melody. This song may be playing in a 90/2000s club.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qf87MJcWZQI.wav"} +{"id": "QfM5-WqvquQ", "caption": "A male singer sings this pensive melody. The tempo is slow with a Sarangi accompaniment . The instrumentation is minimal with vocal emphasis. The song uses classical Ragas and alaps to form a melody. The song is sad, pensive, regretful, pensive, melancholic, emotional, contemplative, wistful and meditative. This song is an Indian Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/QfM5-WqvquQ.wav"} +{"id": "QhF0CFyzzAc", "caption": "The music features a male voice singing. The music is secondary and is being played in the background by a speaker and recorded with a camera/phone. Louder than the music is the crowd continuously screaming.", "audio": "/zhanghaomin/datas/musiccap/music_data/QhF0CFyzzAc.wav"} +{"id": "QiD3AkQz17E", "caption": "Pop music that is dense and distorted with a male singer. Good for club music.", "audio": "/zhanghaomin/datas/musiccap/music_data/QiD3AkQz17E.wav"} +{"id": "Qj4r_MCC0mc", "caption": "This is a regional Mexican song, in a contemporary style. The song feels romantic and relaxed. The singer has a charming voice and his voice sits atop guitar arpeggios and a simple bassline.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qj4r_MCC0mc.wav"} +{"id": "QlaW568SeDc", "caption": "This music is a celestial instrumental. The tempo is slow with a symphonic harmony of the Vibraphones. The music is soft, gentle, and mellifluous with an ethereal, delicate, exquisite, elegant and beautiful sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/QlaW568SeDc.wav"} +{"id": "QmIhKF1BqCg", "caption": "This slow pop song features the end of a song. A male voice sings one syllable. The piano plays three notes followed by two high pitch notes. A guitar chord is heard ringing in the background. There is no percussion in this song. There are no other instruments in this song. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/QmIhKF1BqCg.wav"} +{"id": "QpX9dSCFxRI", "caption": "The low quality recording features a reverse processed low pitched female vocal, followed by punchy kick and snare hits, shimmering hi hats, synth keys chords and groovy bass. There are some crackling in the recording and it sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/QpX9dSCFxRI.wav"} +{"id": "QqRrZzOY2xw", "caption": "This is a rock opera piece. There is a male vocalist singing passionately with a choir of backing vocals. The piano plays the main theme with the electric guitar while a bass guitar plays in the background. The rhythmic background is provided by the acoustic drums playing a simple rock beat. There is an energetic atmosphere to the piece. This piece could be used at sports venues. It could also be playing in the background of a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/QqRrZzOY2xw.wav"} +{"id": "QrJVAHIkpCo", "caption": "The low quality recording features a live performance of a traditional song and it consists of an echoing female vocal singing over breathy woodwind melody and arpeggiated plucked string melody. It sounds passionate, soulful and mystical, even though the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/QrJVAHIkpCo.wav"} +{"id": "QrKJs6lBfmM", "caption": "The low quality recording features a drum solo that consists of a snare roll played together with a syncopated sloppy cowbell. The overall sound is leaning a bit towards the left channel, which makes the stereo image unbalanced.", "audio": "/zhanghaomin/datas/musiccap/music_data/QrKJs6lBfmM.wav"} +{"id": "Qt8Ze-k2h2o", "caption": "This music is a Western Classical. The tempo is fast with a lively violin harmony, electric cello, piano and string accompaniments. The music is classical, colourful, burgeoning, well layered, dense, rich, full , pleasant, cheerful, merry and elegant.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qt8Ze-k2h2o.wav"} +{"id": "QtfIj5cJzYw", "caption": "The music excerpt features a synth sound playing a melody. In the background, accompanying this melody is another synth sound that plays long chords and thus provides harmonic structure. A bass guitar can be heard alternating between regular playing and string slapping. A light rhythm is being played by a pair of congas. A metallic percussive sound can be heard from time to time.", "audio": "/zhanghaomin/datas/musiccap/music_data/QtfIj5cJzYw.wav"} +{"id": "QtjMlA_7dds", "caption": "The low quality recording features a live performance of an indie song and it features a passionate male vocal singing over acoustic rhythm guitar and soft double bass, There are laughing and crowd chattering noises in the background. It sounds emotional and sad, even though the recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/QtjMlA_7dds.wav"} +{"id": "Qu76GhRO9Yk", "caption": "This song contains a piano playing short rhythmic chords along with an acoustic guitar and an upright bass playing the same melody. A brass melody is opening the scene. sound A male voice is singing in a higher register. This song may be playing while celebrating with the whole family on a national holiday.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qu76GhRO9Yk.wav"} +{"id": "QutCXtWmzIs", "caption": "A male singer sings this melodic pop song. The tempo is fast with an acoustic guitar accompaniment, keyboard harmony, enthusiastic electric guitar melody and intense drumming. The vocals are emphatic and the song is pleasant, catchy, melodious, youthful, buoyant and fresh. This song is Soft Rock/ Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/QutCXtWmzIs.wav"} +{"id": "QvwD7NEg3Mw", "caption": "A male vocalist sings this energetic Rock song. The tempo is fast with intense drumming, vigorous electric guitar, funky bass and keyboard harmony. The song is a vibrant, enthusiastic, youthful, animated, spirited, buoyant and electrifying Heavy Metal/Rock. There are sounds of people cheering, clapping and singing along, indicating that this is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/QvwD7NEg3Mw.wav"} +{"id": "Qw468qlDaAE", "caption": "This clip features noises created by mixing output from different effect pedals. This is a synth noise. There are no instruments or voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qw468qlDaAE.wav"} +{"id": "Qy77eJc72UQ", "caption": "This recording contains a marching band playing kick sounds, fast snare rolls and cymbal hits. In the background you can hear people talking and cheering. A male voice is speaking as if making an announcement. This may be playing during a cultural event.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qy77eJc72UQ.wav"} +{"id": "QyMcSnNsAPw", "caption": "This song features an electric organ playing different tones. There is no melody in this song. This is a demo of the different tones that can be played on the electric organ. There are no voices in this song. This can be played in a demo video of this electric organ.", "audio": "/zhanghaomin/datas/musiccap/music_data/QyMcSnNsAPw.wav"} +{"id": "Qz2PIXM60iE", "caption": "A male singer sings this melody with a backup singer in vocal harmony. The song is medium tempo with a strong rock drumming rhythm, steady bass line and a guitar playing a groovy rhythm. The song is youthful and spirited. The audio quality is poor with hissing noises. The song is a sixties psychedelic rock song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qz2PIXM60iE.wav"} +{"id": "Qz8hNRg-7G0", "caption": "Someone is playing a song out of a speaker. The song contains a guitar melody and a digital drum hitting the bass drum on every beat along with a bass-melody. This is an amateur recording. The song is in very poor audio-quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Qz8hNRg-7G0.wav"} +{"id": "QzMsoz4XIkM", "caption": "This music is a Didgeridoo solo instrumental. The tempo is slow with a steady, vibrating drone like harmony with no accompaniment. The music is an intense, monotone , low pitched,incessant buzz like vibrations. It is unique with a captivating, alluring and hypnotic vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/QzMsoz4XIkM.wav"} +{"id": "QzO6ylLrTGg", "caption": "This song features a shofar being played. This shofar plays one long note. This is followed by 8 short bursts of three-note groupings. This is followed by one short note and one higher pitched note played for a longer duration. This pattern is played three times. There are no other instruments in this song. There are no voices in this song. This instrument has religious significance. This song can be played prior to a battle call.", "audio": "/zhanghaomin/datas/musiccap/music_data/QzO6ylLrTGg.wav"} +{"id": "R-aMYx9f0Ho", "caption": "This song is an instrumental. The tempo is medium with an interesting electric guitar riff and subtle keyboard followed by energetic drumming, Funky bass lines and keyboard arrangement. The song gradually builds up and is catchy, youthful, upbeat, melodious, captivating and groovy. This song is Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/R-aMYx9f0Ho.wav"} +{"id": "R0b3pU4AKNc", "caption": "This song features the sound of running water in the background. The sound of bells is played in the foreground. There is a ringing instrument playing through the song and this produces feedback at the end of the clip. There are no voices in this song. This song is relaxing and can be played for the purpose of religious meditation.", "audio": "/zhanghaomin/datas/musiccap/music_data/R0b3pU4AKNc.wav"} +{"id": "R0ws0tATJLg", "caption": "The low quality recording features church bells played over snare rolls, after which, at the end of the loop, there is a brass melody. It sounds suspenseful and intense in the beginning, but as soon as the brass melody appears, it sounds joyful. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/R0ws0tATJLg.wav"} +{"id": "R1RGIgC-xKw", "caption": "This music clip is a Lively Banjo instrumental. The tempo is fast with a spirited Banjo lead harmony. The music is simple, cheerful, happy, festive, upbeat and vivacious. The audio is not very clear as it is a home recording. The music has a country or folk song vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/R1RGIgC-xKw.wav"} +{"id": "R3urUtvSgkU", "caption": "The low quality recording features a cover of a rock song and it consists of distorted bass guitar playing over muffled audio. The recording is distorted and very noisy, almost crushed, but it still sounds groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/R3urUtvSgkU.wav"} +{"id": "R4b_-IT43P4", "caption": "The song is an instrumental. The song is medium tempo with an amplified guitar solo lead, complete with knob flicking tones. The song is loud and energetic. The audio quality is poor and recorded live at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/R4b_-IT43P4.wav"} +{"id": "R4jlQEweREY", "caption": "The song is an instrumental. The song is medium tempo with a didgeridoo playing percussively with double tonguing motion and no other instrumentation. The song is emotional and meditative. The song is an aboriginal instrument played in a home studio.", "audio": "/zhanghaomin/datas/musiccap/music_data/R4jlQEweREY.wav"} +{"id": "R4ulZgTCw-k", "caption": "The low quality recording features a classical song that consists of a wide string melody, shimmering triangle, shimmering cymbals and wide brass melody. It sounds epic, joyful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/R4ulZgTCw-k.wav"} +{"id": "R5JRh08zgMo", "caption": "The Reggae song features a flat male vocal singing, alongside wide background harmonizing female vocals, over metallic snare, simple kick hits, offbeat acoustic rhythm guitar chords, groovy bass, electric guitar licks and tinny percussive elements widely spread in the stereo image. Sounds happy and uplifting, like something you can listen to while chilling at the beach.", "audio": "/zhanghaomin/datas/musiccap/music_data/R5JRh08zgMo.wav"} +{"id": "R5KBk76b9HE", "caption": "This is a piano cover of a glam metal music piece. The piece is being played gently on a keyboard with a grand piano sound. There is a calming, relaxing atmosphere in this piece. It could be playing in the background at a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/R5KBk76b9HE.wav"} +{"id": "R60qQ3ag8y8", "caption": "An instrumental jazz piano and vibraphone duo. Peppy and upbeat with a latin tinge.", "audio": "/zhanghaomin/datas/musiccap/music_data/R60qQ3ag8y8.wav"} +{"id": "R6V85er9VXc", "caption": "This song contains drone sounds played by a string instrument and a synth. On top of that a panflute sound is playing a simple slow melody. A male voice is chanting a mantra in a deeper voice. This song may be playing in a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/R6V85er9VXc.wav"} +{"id": "R6k2BkwZt1Y", "caption": "This is the live performance of a jazz music piece. There is a trumpet solo at the forefront. The background consists of the piano, the upright bass and a jazz acoustic drum beat. The atmosphere is restless. This piece could be playing in the background at a jazz bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/R6k2BkwZt1Y.wav"} +{"id": "R6lRMU-zBLA", "caption": "This is a trap piece. There is a male vocal rapping at the forefront accompanied by a repeating hollering vocal sample. A high-pitch synth is playing an ominous melody. There is a strong bass and an electronic drum beat with cicada hiatus at the rhythmic background. The atmosphere of the song is aggressive. The piece can be used in the soundtracks of crime movies/TV series that take place in the big city.", "audio": "/zhanghaomin/datas/musiccap/music_data/R6lRMU-zBLA.wav"} +{"id": "R6mhBqTU0Tc", "caption": "Someone is skillfully scratching turntables along to a backing track with drums, bassline and synthesizer sounds. This recording is of poor audio-quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/R6mhBqTU0Tc.wav"} +{"id": "R77XPtKgvy4", "caption": "The low quality recording features a groovy bass guitar being played with chorus effect on. The sound of the bass is kind of leaning towards left, which makes the stereo image unbalanced.", "audio": "/zhanghaomin/datas/musiccap/music_data/R77XPtKgvy4.wav"} +{"id": "R7gHB-YuUZM", "caption": "The traditional song features a wide harmonizing children's vocals singing over percussive drums that consist of shimmering tambourine, wooden percussions, punchy snare and soft kick hits, followed by steel guitar melody and simple organ keys. Sounds uplifting, like something kids would sing along to.", "audio": "/zhanghaomin/datas/musiccap/music_data/R7gHB-YuUZM.wav"} +{"id": "RBniJk6GKK0", "caption": "This song contains a female voice sample that is repeating itself. A digital drum is playing snare hits that are building up in speed along with synthesizer pads with a ping pong delay panning to both sides of the speaker along with other synth sounds rising up in pitch creating tension. This song may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/RBniJk6GKK0.wav"} +{"id": "RD-oizm_35M", "caption": "This is the live performance of a sarcastic lullaby. Although the piece is written as if it is a lullaby, the words are about illegal alcohol production. The male vocalist in the lead is singing melodically in the style of a cabaret. There is a grand piano playing an accompanying tune in the background. The atmosphere is comedic. This piece could be playing at a radio station in a movie/TV show for a hidden comedic effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/RD-oizm_35M.wav"} +{"id": "RD8kf4453cY", "caption": "The song is instrumental. The song is medium tempo with a guitar accompaniment, piano playing pensively along with a keyboard harmony. The song is emotional and sad. The song is probably a social awareness message with ambient Street sounds included with the music track.", "audio": "/zhanghaomin/datas/musiccap/music_data/RD8kf4453cY.wav"} +{"id": "RDCXvJPzT5k", "caption": "This is a home recording of a conch shell being blown. There is a horn-like sound coming from the conch shell. The recording can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/RDCXvJPzT5k.wav"} +{"id": "RDNatVYvpeA", "caption": "Here we have a live recording of a meg whistle. The style of playing feels cheery and uplifting. This melody is reminiscent of medieval Irish folk songs or English folk songs.", "audio": "/zhanghaomin/datas/musiccap/music_data/RDNatVYvpeA.wav"} +{"id": "RDW_kz4SXo0", "caption": "This song features a bass guitar being played. At first, a single note is ringing. After a brief pause, an ascending lick is played in common time. The first note is played eight times. The second note is played four times, the third and fourth, two times each. The fifth note is played eight times. The sixth and seventh notes are played four times each. The last note is played once as a double stop with the open string above it and a fretted note on the higher register. This song is an instrumental and can be played in an instructional audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/RDW_kz4SXo0.wav"} +{"id": "REpuZwvyThM", "caption": "This bluegrass song features a solo played on a mandolin. This is accompanied by an acoustic guitar strumming chords. A double bass plays the root note and fifth of the chords. A banjo player fills in between phrases. This song is at a moderate tempo and has a country feel. The mood of this song is happy. This song can be played in an inspirational movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/REpuZwvyThM.wav"} +{"id": "RF3rog2YjYw", "caption": "The low quality recording features a kid and a male laughing back and forth. There are some plastic impacts throughout it. The recording ends with a wide synth pad layered with sustained strings over which there is a low male vocal singing. It sounds joyful, happy and heartful.", "audio": "/zhanghaomin/datas/musiccap/music_data/RF3rog2YjYw.wav"} +{"id": "RFKTlhbnfXA", "caption": "A low fidelity recording of a drone instrument playing a chord while a female singer and double reed instrument double a technically challenging melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/RFKTlhbnfXA.wav"} +{"id": "RFNRR78dh-8", "caption": "This is a fun, cheerful and positive song played on the marimba. Percussively, we heard a shaker and some hand tapping on a hard surface. The song creates a light mood and has an African vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/RFNRR78dh-8.wav"} +{"id": "RFbWkL818XQ", "caption": "Two banjo players trade solos in this instrumental song. The song is medium tempo with banjos playing in a call and response manner and no other instrumentation. The song is energetic and has a middle eastern classical music vibe. The audio quality is average and recorded at Jo e.", "audio": "/zhanghaomin/datas/musiccap/music_data/RFbWkL818XQ.wav"} +{"id": "RGTWqZoswAo", "caption": "solo performance of a virtuosic didgeridoo player playing a fast beat with complex rhythms. Sounds like beat boxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/RGTWqZoswAo.wav"} +{"id": "RI126_DmGLQ", "caption": "This is a Hindu bhajan music piece. There is a male vocalist singing in a devotional manner. The clarinet is playing the main tune while the piano plays a backing tune. The atmosphere is religious. This piece could be playing in the background at a Hindu religious event.", "audio": "/zhanghaomin/datas/musiccap/music_data/RI126_DmGLQ.wav"} +{"id": "RI71ebbU0PQ", "caption": "This audio clip features a drum kit being played. A stick count is played in the beginning followed by the beat in eighth note pattern. The closed hi-hat, snare and kick are played in eight notes. There are no other instruments in this song. There are no voices in this song. This song can be played in a drum instruction video.", "audio": "/zhanghaomin/datas/musiccap/music_data/RI71ebbU0PQ.wav"} +{"id": "RIe1omxr7nc", "caption": "This music is instrumental. There is no instrumentation. The clip starts with white noise and static and ends with the sound of a bell ringing. There are some ambient sounds in the background like bird chirping and flicking.", "audio": "/zhanghaomin/datas/musiccap/music_data/RIe1omxr7nc.wav"} +{"id": "RIiN9Ed1fqU", "caption": "This music is electronic pop. The tempo is fast with synthesiser arrangements, enthusiastic drumming, a sharp , shrill piano accompaniment and vocal riffs. There is the sound of laughter in the background and distorted sounds caused due to electrical reactance, making the song, noisy, chaotic, confusing, busy and painful to listen to. The song in the background is a Synth pop but it is incoherent because of the inferior audio quality .", "audio": "/zhanghaomin/datas/musiccap/music_data/RIiN9Ed1fqU.wav"} +{"id": "RIpfb9LSFe8", "caption": "The rock music features a female voice singing a melody. The band that accompanies her consists of drums, bass guitar and electric guitar. The drums play a repetitive rhythm, the bass guitar also incorporates slides into its playing and the electric guitar plays a simple melody that's composed of repetitive notes.", "audio": "/zhanghaomin/datas/musiccap/music_data/RIpfb9LSFe8.wav"} +{"id": "RJViDdqUYyo", "caption": "This music is instrumental. The tempo is medium with an intense electric upright double bass harmony. The music is dense, deep, powerful, full bodied and vibrant.", "audio": "/zhanghaomin/datas/musiccap/music_data/RJViDdqUYyo.wav"} +{"id": "RM0RELBtdfc", "caption": "This music is instrumental. The tempo is fast with a synthesiser arrangement. The music is youthful, buoyant, punchy, groovy and futuristic. This music is Synthpop/ Technopop.", "audio": "/zhanghaomin/datas/musiccap/music_data/RM0RELBtdfc.wav"} +{"id": "RNwiEsjrhiQ", "caption": "The low quality recording features a live performance of a regional Mexican song and it consists of passionate male vocal singing over groovy bass guitar, mellow synth keys melody and electric guitar melody, followed by shimmering tambourine, hi hats and punchy kick. It sounds passionate, emotional and soulful - like something you would hear at family gathering events.", "audio": "/zhanghaomin/datas/musiccap/music_data/RNwiEsjrhiQ.wav"} +{"id": "ROA6DMBPlNM", "caption": "Female singers sing this vocal in Tamil harmony. The song is medium tempo with a strong techno drumming rhythm, guitar accompaniment, stringed instrument accompaniment, flute countermelody, and a strong bass line. The song is devotional and highly passionate. The song is a Carnatic Hindu devotional song sung in Tamil.", "audio": "/zhanghaomin/datas/musiccap/music_data/ROA6DMBPlNM.wav"} +{"id": "ROM--1yVra8", "caption": "This is a pop music piece. There is a medium-to-high pitch male vocal singing melodically in the lead. The melody is being played by the strings and the piano. There is a loud but simple electronic drum beat in the rhythmic background. The piece is in major key, so there is an optimistic aura. The piece could be used in the soundtracks of teenage dramas. It could also work well in an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/ROM--1yVra8.wav"} +{"id": "RPqz3vJYMLQ", "caption": "This is a poor quality Christian pop music compilation. There are many pieces sung by male and female voices melodically. The usual theme of the instrumental backing consists of a tune played in major key by an electric guitar and a bass guitar alongside a simple acoustic drum beat. The overall atmosphere is uplifting. This mix could be used in a movie to imply the sounds coming from a gospel radio station in passing.", "audio": "/zhanghaomin/datas/musiccap/music_data/RPqz3vJYMLQ.wav"} +{"id": "RPuCtUVfntk", "caption": "A backing song is being played containing percussion, an accordion -like sound playing the main melody and a bass. In the foreground you can hear game related noises and sounds that do not belong to the music. This song may be playing in a video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/RPuCtUVfntk.wav"} +{"id": "RQ0-sjpAPKU", "caption": "This country song features a female voice singing the main melody. This is accompanied by percussion playing a simple beat in common time. A pedal steel guitar plays sliding licks in the background. The bass plays the root and fifth of the chords. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/RQ0-sjpAPKU.wav"} +{"id": "RQMUz0NFx6o", "caption": "This is an instrumental marimba piece. Two marimbas are being played simultaneously. The performance is a complex one. The atmosphere is playful. Parts of this piece can be used to make a ringtone or to lift samples to use in a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/RQMUz0NFx6o.wav"} +{"id": "RQbNC1J4Jfk", "caption": "This song is full of reverb and delay in the beginning. A riser effect is rising up to break into the next part of the song. Then a digital drum with kick and snare comes in along with a monotone bassline. A synthesizer is playing a rhythmic, very simple and monotone melody on top. The sound-elements are all panning from left to right with a ping pong delay.", "audio": "/zhanghaomin/datas/musiccap/music_data/RQbNC1J4Jfk.wav"} +{"id": "RS43EP1EXz4", "caption": "This is an acoustic piece. There is a male vocalist singing melodically. There is a simple tune being played on a ukulele. The atmosphere of the piece is easygoing. This piece could be used in the background of wholesome social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/RS43EP1EXz4.wav"} +{"id": "RSryuuvUfDM", "caption": "One acoustic guitar is strumming chords while the other one is playing a solo melody on top with bending notes in a pentatonic scale. This song may be playing at home practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/RSryuuvUfDM.wav"} +{"id": "RTQJe028VdU", "caption": "The drums are playing a complex groove full of tom hits and fill-ins. On every big hit a synth is playing a sound while e-guitars and another instrument are playing a countermelody. The song sounds like someone being chased by something fast and dangerous. This song may be playing in a game of a tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/RTQJe028VdU.wav"} +{"id": "RUUZzoeVrK4", "caption": "This song is an instrumental. The tempo is slow with an amplified organ playing an intense, sinister chord, followed by a cymbal ride and howling wind produced by wind machine and a chime.. The vibe of the music is spooky, dangerous, ghostly, suspenseful, sinister, grim and scary.", "audio": "/zhanghaomin/datas/musiccap/music_data/RUUZzoeVrK4.wav"} +{"id": "RV05BW-2WIc", "caption": "This music is a captivating Piano solo melody. The tempo is medium fast with no accompaniment. The suit is mellow, captivating , pleasant, soothing , engaging, charming and ambient. This music is a Classic Piano piece that sounds like the melody of a Hymn.", "audio": "/zhanghaomin/datas/musiccap/music_data/RV05BW-2WIc.wav"} +{"id": "RVevnXD4Fig", "caption": "This is a mantra/meditation music piece. There is a male vocalist in the lead that is singing in a chant-like manner. The flute is playing a calming tune. There is an electronic sound effect that gives a texture of vibration in the background. A bass guitar can be heard playing notes every now and then. There is an immersive atmosphere to this piece. It could be playing in the background of a meditation video. It could also be played as an accompaniment piece for meditation courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/RVevnXD4Fig.wav"} +{"id": "RVlXLa80vcE", "caption": "The low quality recording features an Acapella cover of a pop song and it consists of harmonizing mixed vocals singing and some beatboxing that mimics \"4 on the floor\" kick pattern. The recording is noisy and it sounds a bit roomy, since it was probably recorded with a phone. It sounds passionate and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/RVlXLa80vcE.wav"} +{"id": "RXGDlFry3Vo", "caption": "The low quality recording features a hip hop track that consists of flat male vocal rapping over smooth bass, high pitched female vocal, mellow piano melody, shimmering tambourine layered with punchy snare, followed by soft kick and crash cymbal hits. It sounds groovy and emotional, even though the recording is muffled and kind of dull, due to the bad mixing.", "audio": "/zhanghaomin/datas/musiccap/music_data/RXGDlFry3Vo.wav"} +{"id": "RXk0lQJ7ttc", "caption": "The electronic dance music features a female voice singing a short melody after which the song goes through a transition passage. After this a male voice can be heard singing a shorter melody. Throughout the music excerpt strings can be heard in the background as well as an electric guitar. The drums play a busy rhythm in the first half of the music passage. In the second half the synth bass kicks in.", "audio": "/zhanghaomin/datas/musiccap/music_data/RXk0lQJ7ttc.wav"} +{"id": "RZmH4hGiYBg", "caption": "A male uses a vocal phrase to the rhythm of background music. The tempo is fast with vigorous drumming, keyboard arrangements and muffled sounds of blasts, people screaming and shooting. This song is aggressive, sinister, creepy, mysterious and spine-tingling. This song is an Electro Pop/Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/RZmH4hGiYBg.wav"} +{"id": "R_HAtyDbw1M", "caption": "Someone is skillfully playing maracas playing different rhythms in the same tempo so they blend together. The audio-quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/R_HAtyDbw1M.wav"} +{"id": "RceCfg1FQq4", "caption": "A male vocalist sings this emotional Christian Worship Song. The tempo is medium with energetic drumming,harmonious electric guitar , acoustic Guiana keyboard accompaniment and subtle bass. The song is a soft, mellow, emotional, pensive, devotional, Christian music.", "audio": "/zhanghaomin/datas/musiccap/music_data/RceCfg1FQq4.wav"} +{"id": "RcfaWoTywcA", "caption": "The drums is playing a beat that reminds of a slower version of reggaeton along with some shakers and other percussive elements that are slightly panned to the right side of the speakers. An e-bass is helping to create a mood for dancing. A plucked string instrument is playing an oriental melody accompanied by a string-section playing along and adding little melody-licks. You can hear some backing vocals shouting to the rhythm. This song may be playing at a cafe.", "audio": "/zhanghaomin/datas/musiccap/music_data/RcfaWoTywcA.wav"} +{"id": "RczzNAr1T_Q", "caption": "The song is an instrumental. The tempo is medium with a guitar strumming to different settings of an effects delay pedal with echoes and effects being heard. The song is an effects pedal demonstration. The audio quality is poor with hissing sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/RczzNAr1T_Q.wav"} +{"id": "RdKQGIzKZ_c", "caption": "This song features a guitar being played. One guitar chord is struck per bar. This song lasts for 4 bars and four chords are played. There are no voices in this song. There are no other instruments in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/RdKQGIzKZ_c.wav"} +{"id": "Rdwtr2IX8ek", "caption": "Soft singer songwriter folk rock with a gentle male vocal and acoustic guitar strumming. The vocal production is quite loud. Music for an international artsy cafe.", "audio": "/zhanghaomin/datas/musiccap/music_data/Rdwtr2IX8ek.wav"} +{"id": "Rf7vygfb7w4", "caption": "The low quality recording features a melodic church bells impact. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Rf7vygfb7w4.wav"} +{"id": "Rhn6K9HCbC8", "caption": "A male vocalist sings this passionate metal song. The tempo is medium fast with keyboard accompaniment, steady drumming and bass lines, electric guitar , sound of siren and vocal backup. The lead vocals are loud, passionate , volatile, hysterical ,disturbed,emphatic,sad, emotional, painful, disappointed and hurt. This song is Heavy/Goth Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/Rhn6K9HCbC8.wav"} +{"id": "RiqtelZs_2I", "caption": "The low quality recording features Muffled drum roll followed by a widely spread explosion sound effect. The recording is noisy and it sounds scary.", "audio": "/zhanghaomin/datas/musiccap/music_data/RiqtelZs_2I.wav"} +{"id": "RlcIJsgtU58", "caption": "The Country Pop song features an echoing male vocal singing over offbeat acoustic rhythm guitar, punchy \"4 on the floor\" kick pattern and smooth bass. It sounds emotional, easygoing and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/RlcIJsgtU58.wav"} +{"id": "RlrNPBfOowg", "caption": "A male singer sings this Latin melody with backup singers in vocal harmony. The song is medium tempo with a brass band accompaniment, latin percussion and guitar accompaniment. The song is exciting and spirited. The song is perfect for Latin dancing. The song has a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/RlrNPBfOowg.wav"} +{"id": "RmDfwz0OG8E", "caption": "The low quality recording features a hip hop song that consists of a wide reverberant flat male vocal rapping over synth lead melody, sire sound effects, punchy kick, boomy 808 bass, claps and shimmering hi hats. It sounds exciting, energetic and addictive - like something you would hear in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/RmDfwz0OG8E.wav"} +{"id": "RmyyW-TMkVc", "caption": "This is a hindi ballad piece. There is a male vocalist singing with a lot of shifting notes. The main theme in the background appears to be played by a dilruba and a harmonium. It is a heart-touching piece. This piece can be used in the soundtracks of Bollywood dramas.", "audio": "/zhanghaomin/datas/musiccap/music_data/RmyyW-TMkVc.wav"} +{"id": "RneRJ5ZnHlE", "caption": "This is a salsa song with an upbeat and vibrant energy. It contains typical salsa instruments like the conga, the trumpet, and the piano. The percussion is upbeat and involves bongos and congas, and the singer is lively.", "audio": "/zhanghaomin/datas/musiccap/music_data/RneRJ5ZnHlE.wav"} +{"id": "RoDS0k7qrIo", "caption": "The Metal song features a low throaty male vocal singing over widely spread, aggressive and distorted electric guitars, groovy bass guitar, punchy snare, energetic cymbals and double pedal kick. In the second part of the loop, the instrumental calms down, as there is an arpeggiated piano melody over which a soft female vocal is singing. Overall it sounds energetic, aggressive and manic. The male vocal in the first part of the loop is leaning towards the left channel of the stereo image, making it sound unbalanced and therefore low quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/RoDS0k7qrIo.wav"} +{"id": "Rqv5fu1PCXA", "caption": "A female vocalist sings this dulcet melody. The tempo is medium with soft piano accompaniment, keyboard harmony, chimes, harp, and xylophone sounds , ambient sounds of nature like the sound of sea gulls, waves, water gently hitting the rocks, breeze along with the mellifluous vocalisation. The song is soothing, calming, meditative, peaceful, mellifluous, celestial, mystical, dreamy and dreamy. This song is a Lullaby.", "audio": "/zhanghaomin/datas/musiccap/music_data/Rqv5fu1PCXA.wav"} +{"id": "RtXe5T7NFrE", "caption": "This is an instrumental funk music piece consisting of a Chapman stick solo. Due to the nature of the instrument, only the tapping technique is used which gives a funky vibe to the piece. This piece could be used in the background at a jazz club.", "audio": "/zhanghaomin/datas/musiccap/music_data/RtXe5T7NFrE.wav"} +{"id": "RtgHU1UMo5o", "caption": "A male singer sings this groovy bop tune. The song is medium tempo with a groovy double bass playing, piano accompaniment, trumpet playing percussively and brush drumming rhythm. The song is entertaining and exciting. The song is a jazz dance tune with an electronica twist.", "audio": "/zhanghaomin/datas/musiccap/music_data/RtgHU1UMo5o.wav"} +{"id": "Rwt8j_USbWI", "caption": "This music is instrumental. The tempo is fast with lively synthesiser arrangements and electronic beats. There are whooshing sounds in the background, with a male voice screaming in excitement and someone sipping liquid out of an almost empty glass. This music is superimposed over a home video.", "audio": "/zhanghaomin/datas/musiccap/music_data/Rwt8j_USbWI.wav"} +{"id": "RxBFh-zdid4", "caption": "This is a product review video. There is a male voice describing the product. In the background music, there is a very generic jingle that contains an acoustic guitar, a bass guitar, an acoustic drum beat and bells. If the track can be isolated from the piece, it could be used as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/RxBFh-zdid4.wav"} +{"id": "RxmGtt0YzYY", "caption": "The low quality recording features a live performance of a traditional song and it consists of pitch bend wooden percussion. It sounds boomy and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/RxmGtt0YzYY.wav"} +{"id": "S0W_zIUYwrE", "caption": "The low quality recording features a live performance of a jazz big bend that consists of passionate trumpet melody, over groovy double bass, shimmering cymbals and mellow piano chords. It sounds reverberant, happy, passionate and fun. The recording is a bit noisy and the sound is leaning towards the right channel, which makes the stereo image unbalanced.", "audio": "/zhanghaomin/datas/musiccap/music_data/S0W_zIUYwrE.wav"} +{"id": "S29WiN-bTWo", "caption": "This song contains acoustic drums with some elements panned to the right side of the speakers. Accompanied by a bassline and a e-guitar strumming short chords on the backbeat. A male voice is singing in a higher register along with a trumpet and trombone playing a melody along. This song may be playing while listening to music in the kitchen while cooking.", "audio": "/zhanghaomin/datas/musiccap/music_data/S29WiN-bTWo.wav"} +{"id": "S2u5IE0n1ws", "caption": "An instrumental western swing group featuring a violin or fiddle solo. The upright bass lays down a steady walking bassline while two jazz guitars accompanied by strumming chords. Accordion is also present, but drums are not.", "audio": "/zhanghaomin/datas/musiccap/music_data/S2u5IE0n1ws.wav"} +{"id": "S2yXmXUJ5xU", "caption": "This is a flamenco music piece. The only instrument being played is an acoustic guitar. The acoustic guitar is playing exotic tunes. There is a sensual atmosphere. This piece could be used in the soundtrack of a romance movie, especially during the more intimate scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/S2yXmXUJ5xU.wav"} +{"id": "S38KjqRR418", "caption": "The song is an instrumental. The song is medium tempo with a harpsichord belting played with no other instrumentation. The music is emotional, passionate and melancholic. The song audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/S38KjqRR418.wav"} +{"id": "S48GsFznk50", "caption": "This song features a slider didgeridoo being played. It starts off with the didgeridoo playing a note and then siding to a higher pitch. The sound of a water splash is played just before the slide. Then a hissing sound is heard followed by the didgeridoo being played once again without the vibration of the lips. This produces a hollow sound. This sound is produced in a foley studio.", "audio": "/zhanghaomin/datas/musiccap/music_data/S48GsFznk50.wav"} +{"id": "S7R3NMq3MKk", "caption": "A male vocalist sings this groovy R&B. The tempo is medium with a funky bass guitar, steady guitar, bright electric guitar and keyboard harmony. The song is mellow, emotional, soft, smooth and engaging. This song is an R&B.", "audio": "/zhanghaomin/datas/musiccap/music_data/S7R3NMq3MKk.wav"} +{"id": "S7TYAcOEPt4", "caption": "A female voice is singing emotionally along to an acoustic piano. In the background you can hear people laughing. This song may be playing in a tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/S7TYAcOEPt4.wav"} +{"id": "S7igso5_MBE", "caption": "The low quality recording features a bright brass melody played in a reverberant space. The recording is in mono and it is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/S7igso5_MBE.wav"} +{"id": "S7rP6coeLTY", "caption": "A male vocalist sings this energetic song. The tempo is fast with synthesiser arrangements, punchy digital drumming, tambourine beats and keyboard harmony. The music is upbeat, punchy, groovy, youthful, buoyant and exciting. This song is Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/S7rP6coeLTY.wav"} +{"id": "S8WTaKLpmmg", "caption": "This is a symphonic black metal music piece. There is a male vocal singing using the guttural technique in the lead. The main tune is being played by a distorted electric guitar while orchestral elements such as the flute and brass elements. The bass guitar can be heard in the background. The rhythmic background is provided by a loud and rapid acoustic drum beat. The atmosphere is violent and ominous. This piece can be used in the soundtrack of a horror video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/S8WTaKLpmmg.wav"} +{"id": "S8fE5jNVchg", "caption": "This is a glitch music piece. There is an edited sound effect coming from a computer start-up and shut-down mixed with a water sound effect. It has a bizarre atmosphere to it. It could be used in the soundtrack of a dystopian futuristic movie or a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/S8fE5jNVchg.wav"} +{"id": "S9-i_pqoUCw", "caption": "The low quality recording features an aggressive male vocal talking over synth pad chords, sustained, mellow female vocals and reverberant percussion. It sounds suspenseful and intense. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/S9-i_pqoUCw.wav"} +{"id": "SBeC9TISHz8", "caption": "The country music features a male vocalist with a scratchy voice. Two acoustic guitars play a melodic intro riff that goes from melody to strumming. The strings are very sharp-sounding and bright. The atmosphere of the song is sad.", "audio": "/zhanghaomin/datas/musiccap/music_data/SBeC9TISHz8.wav"} +{"id": "SCcryBmDGPw", "caption": "A synthesizer holds a note with increasingly wide vibrato then joins the string bass ensemble in playing a lurching, creeping melody. Sounds like music from a spooky video game. Fearful male muttering can also be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/SCcryBmDGPw.wav"} +{"id": "SDTsifbpGMM", "caption": "The low quality recording features a DJ manically scratching a hip hop song. It is a bit reverberant, noisy and in mono, as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/SDTsifbpGMM.wav"} +{"id": "SEDfsU63w8I", "caption": "This is a live recording of a guitar being played through a high gain amp. The signal is clean at the beginning and switches to an overdrive or distortion tone. A humming noise is heard when the channel is switched to the distortion channel. There are no other instruments played in this clip apart from one guitar. The guitarist seems to be testing the clean and dirty channels of the guitar amplifier.", "audio": "/zhanghaomin/datas/musiccap/music_data/SEDfsU63w8I.wav"} +{"id": "SEHE3WGui30", "caption": "A piano is playing a ballad composition with a lot of reverb. This song may be playing as background music.", "audio": "/zhanghaomin/datas/musiccap/music_data/SEHE3WGui30.wav"} +{"id": "SFHoTmcgw8E", "caption": "This audio contains a string instrument playing a melody with a bow in the higher mid range. Someone is picking a harp while strings are playing long notes in the background. A deep and low bass is also almost serving as a soft kick hit. A flute is playing a short melody with a lot of reverb at the end. This song may be playing while doing qigong.", "audio": "/zhanghaomin/datas/musiccap/music_data/SFHoTmcgw8E.wav"} +{"id": "SG24NL2Xi3A", "caption": "The low quality recording features a hip hop song sung with an addictive flow by flat double male vocals over arpeggiated piano melody, boomy, layered bass and kick hits, soft crash cymbal and claps. It sounds muddy and messy as the mix of the song is bad making the frequencies clash with each other - especially in the low end.", "audio": "/zhanghaomin/datas/musiccap/music_data/SG24NL2Xi3A.wav"} +{"id": "SGF4N3JHF7Y", "caption": "This song contains a wide analog synthpad playing along with a piano and rhythmic strings in the background. Then an acoustic drum comes along playing with an e-bass and an e-guitar is picking single notes as a melody. The whole recording is full of reverb. This song may be playing at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/SGF4N3JHF7Y.wav"} +{"id": "SGFYFPs3Fic", "caption": "This music is an electronic instrumental. The tempo is fast with atmospheric synthesiser, intense drumming and ambient sounds of a helicopter, ambulance siren and wind. The music sounds sinister, grim, dangerous, urgent, panicky, catastrophic , exigent , acute, compelling and emergent. This is electronic music.", "audio": "/zhanghaomin/datas/musiccap/music_data/SGFYFPs3Fic.wav"} +{"id": "SGcjdZ19R1k", "caption": "This rock and roll song features a male voice singing the main melody. This is accompanied by percussion playing a fast tempo beat. Guitars play chords. The bass plays the root notes of the chords. The vocal melody follows a gospel style call and response theme. The main voice sings one line and the crowd responds by singing another line. The tempo of this song is fast. This is a low quality audio and other instruments cannot be identified.", "audio": "/zhanghaomin/datas/musiccap/music_data/SGcjdZ19R1k.wav"} +{"id": "SHYGoXwgKtk", "caption": "This is an acapella version of a rock music piece. There are male vocals performing the piece using the harmony singing technique. They are singing in the major key. The atmosphere is dreamy and vibrant. This piece could be used in the soundtrack of a drama movie that takes place in the United Kingdom.", "audio": "/zhanghaomin/datas/musiccap/music_data/SHYGoXwgKtk.wav"} +{"id": "SJ9TY-iqD9Q", "caption": "This is an amateur recording of a boy singing along to a kids song playing on a TV. It is an educational song with a female voice in the lead. The melody is being played by an acoustic guitar while the rhythm is played by the electronic drums. The quality of the recording is quite poor. Samples lifted from this recording could still be useful in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/SJ9TY-iqD9Q.wav"} +{"id": "SKQbQXPjmvE", "caption": "This song contains acoustic drums playing a simple rock groove after coming in with some fill-ins on the toms. An e-bass is playing along. An e-guitar is playing a simple repeating melody then another e-guitar comes in strumming chords in the background. You can hear clapping and the crowd screaming and cheering. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/SKQbQXPjmvE.wav"} +{"id": "SKt_3Nv2DHo", "caption": "This is a children's song that includes a clarinet melody that follows the vocal melody. There are children laughing and a child singing the main vocal melody. There's a child exclaiming joy. There's a subtle bassline.", "audio": "/zhanghaomin/datas/musiccap/music_data/SKt_3Nv2DHo.wav"} +{"id": "SLcIv8CNk20", "caption": "An orchestra plays a waltz with low strings playing arpeggios and high strings taking the melody. The music has a quaint, lilting feel. There are mechanical sounds in the foreground.", "audio": "/zhanghaomin/datas/musiccap/music_data/SLcIv8CNk20.wav"} +{"id": "SLdVSirZMSI", "caption": "This is an amateur acoustic rock performance of a Christmas song. There are three male voices singing the song. Two acoustic guitars and an electric guitar provide the melodic background. The players are stepping their foot on the ground for an added percussive effect to keep the rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/SLdVSirZMSI.wav"} +{"id": "SLq-Co_szYo", "caption": "This song is an upbeat pop song. The tempo is medium fast with energetic drumming, groovy bass lines, keyboard harmony, synthesiser arrangements and female vocal riff. The song is fresh, youthful, perky, catchy, cheerful and energetic. There are sounds of wind, breeze and some metal clanking. This song sounds like a Jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/SLq-Co_szYo.wav"} +{"id": "SMjYheNdAzg", "caption": "This is a kids music piece in the style of hip-hop. There is a female vocalist singing in a rap-like manner in the lead. The keyboard is playing the melody while there is a simple bass line in the background. A hip-hop electronic drum beat provides the rhythm. The atmosphere is playful. This piece can be used in the soundtrack of a kids TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/SMjYheNdAzg.wav"} +{"id": "SNhfvhWPXNc", "caption": "The low quality recording features a passionate acoustic guitar melody in the right channel, chill electric guitar licks in the left channel of the stereo image and buzzy bass guitar in the middle. There is a wooden percussive playback playing in the background. The recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/SNhfvhWPXNc.wav"} +{"id": "SOzuJU25uGc", "caption": "A hard digital kick is playing along with a monotone bass sound. A malled instrument is playing a repetitive melody in the mid to high register. Evolving liquid synth sounds are rising into focus and up in pitch then a male voice sample comes in before the drum breaks into a new part with a snare sound. This may be playing at a rave in the woods.", "audio": "/zhanghaomin/datas/musiccap/music_data/SOzuJU25uGc.wav"} +{"id": "SPeGy815lFQ", "caption": "This song contains a male voice repeating itself before continuing with its melody. It sounds like running through a sampler along with an electric drum that seems to be programmed, repeating itself with a kick, snare and a very sharp sounding industrial hihat/ride sound. This recording is of poor sound-quality and may be playing at home building a song.", "audio": "/zhanghaomin/datas/musiccap/music_data/SPeGy815lFQ.wav"} +{"id": "SSO7F_Ex0s4", "caption": "A male singer sings this cool melody with backup singers in vocal harmony. The song is medium tempo with a percussive bass line, ethnic drumming rhythm, trumpets playing percussively and a keyboard harmony. The song is groovy and cheerful. The song is retro final pop song;", "audio": "/zhanghaomin/datas/musiccap/music_data/SSO7F_Ex0s4.wav"} +{"id": "SSVlD_ZDb70", "caption": "This is a deep tech house song with a simple beat, and simple bassline that consists of one note. There aren't any melodic components to the song besides the one bass note that is played with the same repeated rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/SSVlD_ZDb70.wav"} +{"id": "SU9ZP2pbqyU", "caption": "This is an instrumental latin music piece. There is a rapidly-played acoustic guitar intro acting as a dance accompaniment. It has a lively atmosphere. This piece could be helpful in a latin dance course setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/SU9ZP2pbqyU.wav"} +{"id": "SUclDZHax0w", "caption": "This composition sounds calming as it is playing a melody with bell sounds then a wind sounds comes and the song changes to orchestral instruments playing strings and flutes. This song may be playing in an indie video game moving a cute figure through a dangerous but beautiful landscape.", "audio": "/zhanghaomin/datas/musiccap/music_data/SUclDZHax0w.wav"} +{"id": "SW4cW2oU07U", "caption": "The song is an instrumental. The tempo is medium with a keyboard accompaniment with bell tones, bass clarinet harmony and other percussion hits. The song has ambient room noise and sounds of sand falling on the floor. The song is a Christmas movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/SW4cW2oU07U.wav"} +{"id": "SWcEG8RLKsw", "caption": "A male vocalist sings this animated song. The tempo is slow, almost speech like with a vigorous Spanish guitar accompaniment and rhythmic tapping. The song is enthusiastic, vibrant, passionate, and energetic, with a dance groove for tap dancing or flamenco.", "audio": "/zhanghaomin/datas/musiccap/music_data/SWcEG8RLKsw.wav"} +{"id": "SWyF5TSxWso", "caption": "This is the recording of a toilet factory. The flushing systems of the toilets are being tested with a stream of water. Samples could be derived to be used in sound effects for a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/SWyF5TSxWso.wav"} +{"id": "SY6uwVbC944", "caption": "Bluegrass music featuring banjo, mandolin, acoustic guitar, upright bass, a simple chord progression and a fast tempo.", "audio": "/zhanghaomin/datas/musiccap/music_data/SY6uwVbC944.wav"} +{"id": "SYVcaQ1Bzu8", "caption": "This is a hardcore hip-hop music piece. There is a male vocal with a raspy voice rapping at the forefront. The melody is made up of a repeated keyboard sample. There is a bass guitar playing a groovy bass line. The rhythmic background is composed of a hip-hop electronic drum beat. The atmosphere is hard-hitting. This piece could be the opening theme of a crime movie that takes place in the big city.", "audio": "/zhanghaomin/datas/musiccap/music_data/SYVcaQ1Bzu8.wav"} +{"id": "S_Z7o4OmU30", "caption": "The Reggae/Dub song features a subtle funky electric guitar melody with echoing guitar pedal effects on, punchy snare, soft kick hits, groovy bass and shimmering cymbals, while the wide harmonizing male vocals are singing over it. It sounds easygoing and chill, like something you would listen to on a beautiful Sunday afternoon.", "audio": "/zhanghaomin/datas/musiccap/music_data/S_Z7o4OmU30.wav"} +{"id": "Sa3Ky5sJshU", "caption": "This is an instrumental cover of a J-pop music piece. There is no singer in this piece. The melodic background consists of the keyboard and the bass playing a repeated theme. There is a synth solo with an electric guitar sound being played as the lead. In the rhythmic background, there is a fast tempo electronic drum beat. The atmosphere is danceable and energetic. This piece can be used in the soundtrack of a car racing video game. It could also be used in the soundtrack of an anime during competitive scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/Sa3Ky5sJshU.wav"} +{"id": "SbUwQctvbHg", "caption": "This song is played on a glockenspiel. This is low quality audio. The glockenspiel sounds like large bells. There is a lot of reverb in this audio. There are no other instruments in this song. There are no voices in this song. This song sounds like the song that would be played in a music box.", "audio": "/zhanghaomin/datas/musiccap/music_data/SbUwQctvbHg.wav"} +{"id": "ScAlKYCgHV0", "caption": "This is the recording of an accordion lesson. There is a male voice describing the way a certain song is meant to be played on the accordion in the Spanish language. The quality of the recording is quite poor and there is a very frequent peak sound that crackles while the instructor is speaking.", "audio": "/zhanghaomin/datas/musiccap/music_data/ScAlKYCgHV0.wav"} +{"id": "Sdnv8043mdk", "caption": "This audio contains someone playing a very high pitched tone using tingsha bells. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/Sdnv8043mdk.wav"} +{"id": "SijRZIQUa08", "caption": "This song is an amateur recording of a person beatboxing. The sound is produced using the mouth. This features sounds of the kick, snare and hi-hat. There are no other instruments in this song. There is no vocal melody apart from the beatbox itself.", "audio": "/zhanghaomin/datas/musiccap/music_data/SijRZIQUa08.wav"} +{"id": "Simd4JoehW8", "caption": "The low quality recording features a synth lead melody and groovy synth piano playing over rock songs played on playback. The song consists of a punchy kick and snare hits, shimmering hi hats, funky electric guitar melody, groovy bass and passionate male vocals singing over it in the beginning. It sounds funky and groovy, while the recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Simd4JoehW8.wav"} +{"id": "Sj5MQtqDw8Y", "caption": "A male singer sings this Latin dance tune. The song is medium tempo with trumpets, latin percussions; medium drumming rhythm, keyboard harmony and guitar accompaniment. The song is exciting and groovy. The audio quality is poor and is played for work out exercise.", "audio": "/zhanghaomin/datas/musiccap/music_data/Sj5MQtqDw8Y.wav"} +{"id": "SkFG5SoXsVk", "caption": "The song is an instrumental. The tempo is medium with a distinctive reggae style backbeat drumming rhythm and a guitar playing rhythm along with a bass guitar solo. The song is extremely passionate and groovy in nature. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/SkFG5SoXsVk.wav"} +{"id": "SkIDF7iNJQE", "caption": "This is a simple dubstep piece. Electronic drums and percussion are played at the rhythmic background at 120 BPM. There is a high-pitched synth and a fuzzy synth bass playing a simple melody. The all-around quality of the sounds are a bit old-fashioned, reminiscing of the early 2000s. The piece has a danceable, trippy feel to it. It could be used in a retro-themed venue.", "audio": "/zhanghaomin/datas/musiccap/music_data/SkIDF7iNJQE.wav"} +{"id": "SkZ7mGbs3SI", "caption": "The salsa music features a melody being played by an electric guitar in unison with another instrument like flute or clarinet. The percussion is latin specific and drives the pulse of the music forward. A bass guitar alternates between playing the melody in unison with the electric guitar and playing something different. At the end of the music excerpt a brass section can be heard playing a short accentuated melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/SkZ7mGbs3SI.wav"} +{"id": "Sl9ZkYViEIs", "caption": "A male vocalist sings this melancholic country song. The tempo is slow with acoustic guitar lead and harmony with another string instrument accompanying. The song is soft, mellow, sad, pensive, melancholic and poignant with a sweet , pleasant melody. This song is a Classic Country song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Sl9ZkYViEIs.wav"} +{"id": "SlnjJv305Vg", "caption": "A cellist plays this lilting melody with a piano accompaniment and no other instruments. The music is emotional and tragic. The tempo is slow and has a lot of beauty to it. The song is a cover of a famous love song.", "audio": "/zhanghaomin/datas/musiccap/music_data/SlnjJv305Vg.wav"} +{"id": "Sp1YBy4h9OY", "caption": "This song contains bells playing a melody sounding like a lullaby. In the background you can hear people talking. This song may be playing near a church during holidays.", "audio": "/zhanghaomin/datas/musiccap/music_data/Sp1YBy4h9OY.wav"} +{"id": "Sp3T_x3SGzQ", "caption": "The low quality recording features a lullaby song that consists of an intimate, soft male vocal singing over arpeggiated acoustic guitar melody and wide sustained strings melody. It is a bit noisy and there is a tinny metallic impact towards the end of the loop. It sounds soft, mellow and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/Sp3T_x3SGzQ.wav"} +{"id": "Sr2Grfi3lFg", "caption": "This song would be classified as bubblegum pop. The music is more suitable for children, as it has a young and light-hearted style of production. There's a bright and tinny synth which is used to play a repeated motif, and at one point we hear a pair of birds mimicking the melody in their squeaky bird-like tones.", "audio": "/zhanghaomin/datas/musiccap/music_data/Sr2Grfi3lFg.wav"} +{"id": "SrLhnoBMyWM", "caption": "A classical, slightly jazzy piano is playing a lovely composition with a lot of reverb. During the song you can hear footsteps. Someone is running through water. Then at the end someone is burping really loud. This whole composition with the burping could be part of a funny embarrassing scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/SrLhnoBMyWM.wav"} +{"id": "Ss1bubMNPQE", "caption": "This is a world music piece in the style of Celtic folk music. There is a female vocalist singing gently and melodically. There is an airy strings section creating a relaxing atmosphere while the piano plays a mellow arpeggio. The atmosphere is soothing. This piece could be used during the vivid scenery shots of a movie that takes place in the middle of nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ss1bubMNPQE.wav"} +{"id": "SsVc1TAVsSc", "caption": "This music is instrumental. His tempo is fast with a lively ukelele rhythm, melodious harp harmony and shaker beats with male vocalisation. This clip is the beginning of a song with latin music influences. The music is a lively, spirited, happy, cheerful, warm, energetic latin folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/SsVc1TAVsSc.wav"} +{"id": "SvsCM0fLM5g", "caption": "This is a country music piece that is played in an instrument lesson recording. The steel guitar is playing a mellow tune while at the forefront while there is a backing composed of the acoustic guitar and the acoustic drums. There is a relaxing and psychedelic feel to the piece. This music could suit well in the soundtrack of a feelgood/comedy movie. It could also be playing in the background at a shopping mall.", "audio": "/zhanghaomin/datas/musiccap/music_data/SvsCM0fLM5g.wav"} +{"id": "SwRjY1-ojAU", "caption": "Something like a jukebox or kid's toy is playing a sweet melody for babies while in the foreground a real baby is making noises with its voice. This seems to be an amateur recording. This song may be played to entertain a baby.", "audio": "/zhanghaomin/datas/musiccap/music_data/SwRjY1-ojAU.wav"} +{"id": "SwaqANBpZGY", "caption": "A male vocalist sings this lively pop rock. The tempo is medium with an intense electric guitar harmony, punchy drumming, groovy bass lines and keyboard harmony. The song is muffled as the audio quality is inferior but it sounds enthusiastic, youthful, passionate and vibrant. This could be a live performance as there are background sounds of people talking, coughing, rustling. This song is Pop Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/SwaqANBpZGY.wav"} +{"id": "SwdhfGXkMCo", "caption": "This piece involves multiple french horns. The piece sounds regal and like something you would hear if the king of a country was moving in his chariot through his kingdom along with a grand parade. The staccato bassline helps add to the sense of marching forward.", "audio": "/zhanghaomin/datas/musiccap/music_data/SwdhfGXkMCo.wav"} +{"id": "Swien0oGl7o", "caption": "This song features a banjo being strummed. The banjo player plays four chords using downstrokes. There are no other instruments in this song. This is a low quality recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/Swien0oGl7o.wav"} +{"id": "SxYnb9_qDtk", "caption": "A male vocalist sings this spirited rap. The tempo is medium with keyboard accompaniment, digital drums,electric guitar riff and synthesiser arrangements with vocal backup. The song is passionate, compelling, strong telling, chanting, persuasive and youthful. This song is Contemporary Rap-Hip-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/SxYnb9_qDtk.wav"} +{"id": "SyJT8XsFsmE", "caption": "An orchestra is playing a melody with a string section and a brass section giving it a feeling of something great is about to come. Apart from the music you can hear sounds of things breaking and a beeping sound. This is an amateur recording and not of the best audio-quality. This song may be playing in a heroic movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/SyJT8XsFsmE.wav"} +{"id": "T0OFKHj6878", "caption": "This is a hip-hop music piece. There is a male vocal rapping at the forefront while there are repetitions and ad-libs that can be heard in the background. An eerie sounding melodic pad is playing the melody. There is a strong bass. The rhythmic background is composed of a hip-hop electronic drum beat. The atmosphere is unnerving. This piece could be playing in a scene where criminal activities are occurring in a crime/noir movie taking place in a big city.", "audio": "/zhanghaomin/datas/musiccap/music_data/T0OFKHj6878.wav"} +{"id": "T0oF8MyYhBM", "caption": "The Kurdish Folk music features an ambience choir synth accompanied by a piano melody. The vocals are passionate and almost romantic. The music might be playing in an eastern romantic TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/T0oF8MyYhBM.wav"} +{"id": "T0tyLNN7SKA", "caption": "The low quality recording features a folk song that consists of a digital synth melody played, after which there is an exciting male vocal. It sounds energetic and exciting. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/T0tyLNN7SKA.wav"} +{"id": "T0uoYE12cnI", "caption": "The low quality recording features an indie song that consists of harmonizing vocals melody, alongside passionate vocals over acoustic rhythm guitar melody in the left channel and funky strummed electric guitar chord progression in the right channel of the stereo image. It sounds passionate, soulful, funky and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/T0uoYE12cnI.wav"} +{"id": "T2pIUdaDMuA", "caption": "Amateur recording of electronic drum sounds played in free time. The sound is quiet, low fidelity and instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/T2pIUdaDMuA.wav"} +{"id": "T2zoWLYzEpo", "caption": "This song contains female voices singing in a soul fashion along to a piano and trumpets playing a finale. An acoustic drum is playing a closing cymbal hit at the end. Then the crowd starts clapping and cheering. This song may be playing as part of a movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/T2zoWLYzEpo.wav"} +{"id": "T5YZwhC7Br8", "caption": "This musical piece belongs to a cinematic scene. Strings are playing a creepy melody and fill in along with screeching sounds while there is the sound of someone knocking the door and then someone is screaming.", "audio": "/zhanghaomin/datas/musiccap/music_data/T5YZwhC7Br8.wav"} +{"id": "T6iv9GFIVyU", "caption": "This is an Afghan romantic pop piece. There is a male vocalist singing melodically in the lead. A harmonium is playing the main tune, at times simultaneously with the vocal. The rhythmic background is composed of the tabla percussion. There is an emotional feel to this piece. This piece could be used in the soundtrack of a soap opera taking place in Afghanistan. It could also be used in romantic social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/T6iv9GFIVyU.wav"} +{"id": "T78nMdsJMmk", "caption": "This is an R&B music piece from a sit-com soundtrack. Initially, there is a male voice narrating what is going on in the episode. Then the piece starts playing with a high pitched male vocal at the forefront. The melody is being played by the electric guitar and the bass guitar while the rhythmic background consists of an acoustic drum beat. The atmosphere is urban.", "audio": "/zhanghaomin/datas/musiccap/music_data/T78nMdsJMmk.wav"} +{"id": "T7A0RejsZIo", "caption": "This folk song features a male voice yodelling. There are no lyrics in this song. This is accompanied by percussion playing a waltz beat. The guitar plays double stops in a descending pattern before the singing starts. The notes are harmonized as per the major scale. A bass plays the root notes of the chord on each count of the bars. The mood of this song is happy. This recording is an amateur recording. This song can be played in a movie scene on a hill with green grass.", "audio": "/zhanghaomin/datas/musiccap/music_data/T7A0RejsZIo.wav"} +{"id": "T7ZSZhcsfjA", "caption": "A male vocalist sings this animated melody. The tempo is medium with loud vocals, incoherent lyrics and synthesised choral harmony followed by white noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/T7ZSZhcsfjA.wav"} +{"id": "T7bG4kIEw-M", "caption": "This is an amateur recording of an afrobeat piece playing in the background of a dance performance. The piece can be barely heard from the cheering sounds coming from the crowd. The piece has a clear afrobeat rhythm and it is used as an accompaniment for an African dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/T7bG4kIEw-M.wav"} +{"id": "T7khbuOBHbo", "caption": "This slow pop song features the brass section playing the main melody in harmony. This is accompanied by hand claps on every alternate count. A tambourine plays a rhythmic beat in the background. Two piano notes are played in the background in the first bar of the song. There are no voices in this song. This instrumental song has a romantic theme. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/T7khbuOBHbo.wav"} +{"id": "T8U3ihbHh9A", "caption": "The song is an instrumental. The tempo is medium with a bass guitar using innovative improvisation skills along with a drum track with heavy cymbal crashes. The song is energetic and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/T8U3ihbHh9A.wav"} +{"id": "T9dKp1EN4p8", "caption": "The low quality recording features a low didgeridoo solo melody. The recording is noisy, mono and reverberant as it was probably recorded in a room with a bad quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/T9dKp1EN4p8.wav"} +{"id": "T9fk99yqwN4", "caption": "This amateur recording features a shofar being played. It sounds like a bugle. The melody starts on a low note followed by a higher note and alternates the same with a long ring of the high note. It is played in a place with a lot of reverb. There are no other instruments in this song. There are no voices in this song. This can be played in a movie scene just before a war.", "audio": "/zhanghaomin/datas/musiccap/music_data/T9fk99yqwN4.wav"} +{"id": "TA-O_bVnvLY", "caption": "The song is an instrumental. The tempo is medium with an interesting fusion of old and new age Indian instruments like sitar playing, guitar lead, deep techno bass, slick drumming rhythm, piano accompaniment and groovy bassline. The song is emotional and new age in style.", "audio": "/zhanghaomin/datas/musiccap/music_data/TA-O_bVnvLY.wav"} +{"id": "TArWNq2retM", "caption": "This clip features an organ being played in an operatic style. The sound is haunting and emotional. It's played live in a room, and the quality of the audio in the recording is poor. We hear the acoustics of the room which heavily echo.", "audio": "/zhanghaomin/datas/musiccap/music_data/TArWNq2retM.wav"} +{"id": "TC4mH6nACm8", "caption": "The low quality recording features a wooden percussion, metallic percussion, percussive guitar and repetitive bells melody. It sounds groovy, bouncy, suspenseful, reverberant and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/TC4mH6nACm8.wav"} +{"id": "TCRxCAYyduo", "caption": "The clip starts off with a series of sound effects that indicate that a person is stepping into a car and starting the engine. The car is a powerful sports car. The person then turns on the music and we hear a metallic, overdriven electric guitar riff that's suitable for a song that's a sub-genre of rock and roll.", "audio": "/zhanghaomin/datas/musiccap/music_data/TCRxCAYyduo.wav"} +{"id": "TEWYFkjH2jc", "caption": "A male vocalist sings this upbeat song in a foreign language. The tempo is fast with a lively keyboard harmony, spirited drumming, funky bass line, rhythmic acoustic guitar, shakers enthusiastic vocal backup and clapping. The song is upbeat, high-spirited, energetic, buoyant, cheerful, peppy, happy and groovy. This song is a lively Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/TEWYFkjH2jc.wav"} +{"id": "TEoDtxjlctA", "caption": "The folk music excerpt features a group of male and female voices singing the same melody in unison which consists of yodeling. The instrumental consists of a few accordions, an acoustic guitar and an upright bass. The atmosphere is one of joy.", "audio": "/zhanghaomin/datas/musiccap/music_data/TEoDtxjlctA.wav"} +{"id": "TFLt7mn57ZI", "caption": "This instrumental slow rock song features a guitar playing arpeggiated chords. This is accompanied by a piano playing passing chords. The percussion consists of only the ride cymbal being struck in a set of two strokes followed by a set of four strokes. This pattern continues throughout the song. The bass plays the root notes and filler notes at the start of each bar. There are no voices in this song. This song can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/TFLt7mn57ZI.wav"} +{"id": "THfTLXBLpJE", "caption": "This is a low quality audio featuring a male voice singing the main melody. Another voice sings in harmony with the main voice. /the melody is simple and repetitive. This is accompanied by percussion playing a simple beat. The bass plays the root notes of the chords. Trumpet play fills in between lines. This is a happy song. This song has a ska feel. This song can be played at a retro style dance party.", "audio": "/zhanghaomin/datas/musiccap/music_data/THfTLXBLpJE.wav"} +{"id": "THhptTKMr9U", "caption": "This song contains someone playing ukulele along with a xylophone sound playing the melody along. A female voice is singing in a higher key sounding soulful. You can hear a rimshot sound. That sound is maybe coming from the ukulele. This song may be playing live entertaining your friends and family.", "audio": "/zhanghaomin/datas/musiccap/music_data/THhptTKMr9U.wav"} +{"id": "TIASpLtI8ks", "caption": "This song features the sound of two church bells playing together. One bell plays at twice the tempo of the other bell producing a set rhythm. There are no other instruments in this song. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/TIASpLtI8ks.wav"} +{"id": "TIAj-fi_R7c", "caption": "The low quality recording features a jazz song that consists of a passionate trumpet melody in the left channel of the stereo image and mellow piano chords in the right channel, followed by smooth double bass and shimmering hi hats. It sounds soft, mellow, passionate and relaxing. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/TIAj-fi_R7c.wav"} +{"id": "TIL8jEw8pSc", "caption": "The song is an instrumental. The song is medium tempo with a cool groove being played on a keyboard. The ambient sounds are that of a gardening hardware tool being conked into starting with wind noise and gravel crunching tones. The song is being played as background music for the home video. The audio quality is harsh and not pleasant to hear.", "audio": "/zhanghaomin/datas/musiccap/music_data/TIL8jEw8pSc.wav"} +{"id": "TJyzBaMwXFY", "caption": "Heavy, dark music featuring a gruff male vocalist rapping in a growl with group vocals. There are distorted guitars and bass while drums play a beat on the low toms, backbeat on the snare and four on the floor kick pattern. The genre is rap metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/TJyzBaMwXFY.wav"} +{"id": "TKSFbf-wQ8I", "caption": "This song is an instrumental. The tempo is fast but as the audio quality is bad it is hard to hear the song well. The song is electronic music with a boomy, thumping drum beats, rhythmic vocalisation and electrical wave disturbance causing a screechy ,static sound. This song is an Electro Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/TKSFbf-wQ8I.wav"} +{"id": "TLMEsc_42Gw", "caption": "The low quality recording features a live performance of an alternative/indie song, sung by passionate male vocalists over an acoustic guitar melody. It sounds passionate, emotional and heartfelt. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/TLMEsc_42Gw.wav"} +{"id": "TN53jpjqAGI", "caption": "This is a pop music piece with 80s characteristics. There is a female vocalist in the lead singing melodically. The main theme is played by a keyboard and an electric guitar at the same time in the major scale. There is a bass guitar and a medium-to-high range pad in the background. The rhythmic background is provided by a loud but simple acoustic drum beat. There is a maximalist, vibrant and energetic atmosphere. This piece could be used in the soundtrack of a romance movie. It could also fit very nicely as the soundtrack of an anime.", "audio": "/zhanghaomin/datas/musiccap/music_data/TN53jpjqAGI.wav"} +{"id": "TObYoD2pGb0", "caption": "This audio contains someone strumming one only chord on a e-guitar then a male voice starts speaking in the midrange. In the background you can hear people talking.", "audio": "/zhanghaomin/datas/musiccap/music_data/TObYoD2pGb0.wav"} +{"id": "TPYNIc_M1ng", "caption": "The clip is an upbeat, groovy funk song with jazzy elements. The retro vintage electric piano chords add an old school jazzy feel to the song. The bassline is intricate and bouncy and enables easy dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/TPYNIc_M1ng.wav"} +{"id": "TPdqEmS1Dr0", "caption": "This recording is of very poor audio-quality. The sub bass is strongly over-driving the recorder's speaker. You can also hear a digital drum and a male voice singing in the mid to high range. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/TPdqEmS1Dr0.wav"} +{"id": "TSl5LrM6LcQ", "caption": "This music is instrumental. The tempo is slow with a resonating electric guitar riff. The music is spooky, eerie, sinister, mysterious and suspenseful with a little white noise/static.", "audio": "/zhanghaomin/datas/musiccap/music_data/TSl5LrM6LcQ.wav"} +{"id": "TTytcT_1dmY", "caption": "This is the live recording of a pop music piece. The track is being performed with playback. There is a female vocal with child-like characteristics. There is a strong electronic drum beat in the rhythmic background. A fuzzy synth bass is playing the melodic part. There are lots of beat repeat effects. The atmosphere is loud and energetic. There are sounds that can be heard coming from the crowd cheering.", "audio": "/zhanghaomin/datas/musiccap/music_data/TTytcT_1dmY.wav"} +{"id": "TWV3YLscSaw", "caption": "The low quality recording features a passionate, reverberant male vocal singing over a wide arpeggiated acoustic guitar melody and acoustic guitar solo melody, followed by a simple bass. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/TWV3YLscSaw.wav"} +{"id": "TWm0OilO0uw", "caption": "The low quality recording features a door opening, room tone ambience, clothes movement and chain rattle sound effects, followed by repetitive high pitched male chant, weird male chant, sudden, loud white noise layered with male scream. In the second part of the clip, there is a synth pad in the background. It sounds aggressive, loud, harsh and weird, almost like a parody clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/TWm0OilO0uw.wav"} +{"id": "TWm_2QncYXg", "caption": "The song is an instrumental. The song is medium tempo with a percussive tabla rhythm, groovy bass line and a guitar strumming rhythm and playing lead. The song is Indian classical fusion with a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/TWm_2QncYXg.wav"} +{"id": "TWnrcjA6VTk", "caption": "The low quality recording features an accordion melody, electric guitar melody and trombone melody, after which there is a crowd clapping, laughing and chattering sounds. There are also tinny glass impacts in the background. It gives off fun and happy vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/TWnrcjA6VTk.wav"} +{"id": "TX9PGFdqRak", "caption": "This song contains a bit-rate lofi melody in a poor audio-quality. This song may be playing in an old 2d video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/TX9PGFdqRak.wav"} +{"id": "TZGDukKAVS8", "caption": "Here we have an early 2000s hip hop song which features a grungy guitar and a high pitched synth riff. The recording is done live, and thus the poor audio quality. There is a lower bass-synth which has the characteristics of a trumpet and a repeated riff is played on it.", "audio": "/zhanghaomin/datas/musiccap/music_data/TZGDukKAVS8.wav"} +{"id": "TZlFTbvfKPE", "caption": "This is the live performance of a blues rock piece. There is an electric guitar playing the melody with a bass guitar playing in the background. The acoustic drums are playing a rock beat. There is a groovy atmosphere to this piece. It could be playing in the background of a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/TZlFTbvfKPE.wav"} +{"id": "T_d82v2g93w", "caption": "This clip features a synth playing a chord in the background. Another synth plays swells in short bursts. There are no voices in this song. There is no percussion in the song. The mood of this song is eerie. This song can be played in a suspenseful movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/T_d82v2g93w.wav"} +{"id": "Ta0GmXPnGWk", "caption": "The song is an instrumental. The song is medium tempo with an electric guitar playing guitar riffs with a nice low end; The audio quality is average. The song is passionate and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ta0GmXPnGWk.wav"} +{"id": "TabaOeYq2ek", "caption": "A female singer sings this cool melody. The song is medium tempo with a percussive bass line, slick drumming rhythm, guitar accompaniment , keyboard accompaniment and various percussion hits. The song has a strong dance groove and retro pop in style.", "audio": "/zhanghaomin/datas/musiccap/music_data/TabaOeYq2ek.wav"} +{"id": "TakkuFZJsis", "caption": "A male rapper sings this groovy melody. The song is medium tempo with a steady drumming rhythm, groovy bass line, a melancholic flute countermelody, keyboard harmony and guitar accompaniment. The song is exciting and passionate. The song is a modern Russian rap song with a story telling nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/TakkuFZJsis.wav"} +{"id": "TbA_TZn35LA", "caption": "This is an energetic and positive old school rock song. The recording is of a live performance. The singing is muffled and the instruments sound mashed together in a way that diminishes their quality. You can just barely make out an intricate electric bass bassline, an organ that's high pitched, and some enthusiastic backing vocals.", "audio": "/zhanghaomin/datas/musiccap/music_data/TbA_TZn35LA.wav"} +{"id": "TbYahEEj_B4", "caption": "This song mainly contains rhythmic instruments with a monotone bassline giving the percussion's some low end. The male voice is speaking over the instrumental. The whole song sounds motivation and animates to dance. This song may be playing at a latin festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/TbYahEEj_B4.wav"} +{"id": "TcJ7rdYMHiQ", "caption": "This music is an instrumental. The tempo is fast with a keyboard harmony, boomy bass lines, chimes and electronic arrangements. The music is catchy, perky, vivacious, groovy, intense and ardent. This music is a Synth pop instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/TcJ7rdYMHiQ.wav"} +{"id": "TcoRmHHHNgI", "caption": "This song contains an acoustic drum playing a simple groove along with an upright bass. A piano is playing short chords along with the snare of the drums. Trumpets are playing a melody along with the male voices singing together in unison and other harmonies. In the background you can hear a synth string chord and plucks playing a little melody. This song may be playing in a theater while watching a musical.", "audio": "/zhanghaomin/datas/musiccap/music_data/TcoRmHHHNgI.wav"} +{"id": "TdHdD1wxu_0", "caption": "The music features a calm male voice singing a short melody. An acoustic guitar is accompanying the singer and playing chords throughout the music excerpt. In the background car horn-like sounds can be heard playing long notes. The overall atmosphere is calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/TdHdD1wxu_0.wav"} +{"id": "TdvwUwpYYos", "caption": "This song sounds like it would be fitting in some kind of fantasy sci-fi game. There is a melodic flute played at the beginning, along with a pad synth. There is the sound of water running from a tap and dripping into a bucket of water. The singer has a smooth, ethereal voice that's flawless.", "audio": "/zhanghaomin/datas/musiccap/music_data/TdvwUwpYYos.wav"} +{"id": "Tfc6184uCIk", "caption": "Here we have an instrumentalist blowing a horn. The horn makes a high pitched sound. This is a live recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/Tfc6184uCIk.wav"} +{"id": "TgCv5a22YUU", "caption": "The low quality recording features a muffled soul song that consists of harmonizing vocals and passionate female vocals. It is too noisy, almost crushed - it is barely recognizable as a soul song. It seems it was recorded with an old phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/TgCv5a22YUU.wav"} +{"id": "TgOr_C6xP6U", "caption": "This percussion song features only a percussion instrument being played and a crash cymbal. This is a promotional audio clip to feature the sound of the instrument. There are no other instruments in this clip. There are no voices in the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/TgOr_C6xP6U.wav"} +{"id": "Th6Tf6kA8RU", "caption": "The cinematic music features a violin solo with a light accompaniment by a string section. The solo repeats the same, simple theme several times. There's duck sounds playing in the background. The music sounds like a very old tv show soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/Th6Tf6kA8RU.wav"} +{"id": "TiDdR-6bIcY", "caption": "The low quality recording features a live performance of a pop song that consists of a passionate female vocal, alongside harmonizing background female vocals singing over synth pad chords, punchy kick and snare hits, shimmering cymbals, claps, mellow bells melody and smooth bass. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/TiDdR-6bIcY.wav"} +{"id": "TiOBlG-R1Y4", "caption": "This hard rock song feels like the kind of song that would play as you are preparing to go to war. The instruments are gritty, grungy, and intense. The electric guitarist plays an intricate motif and the bass player matches the main part of the riff. The drummer plays potent and punchy rhythms which feature the crash cymbal - which adds a bright shimmery contrast to the dark and grungry guitars.", "audio": "/zhanghaomin/datas/musiccap/music_data/TiOBlG-R1Y4.wav"} +{"id": "TkHZdMJPwKc", "caption": "The low quality recording features an ambient song that consists of synth pad chord, shimmering chime bells and simple bass. It sounds mellow, soft, calming and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/TkHZdMJPwKc.wav"} +{"id": "TkclVqlyKx4", "caption": "This is a live performance featuring bagpipes and a marching percussion section. The bagpipes are characteristic of Scottish music and the motif they play in unison is uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/TkclVqlyKx4.wav"} +{"id": "TnCXmm-v3Ys", "caption": "The excerpt features bells in different pitches being played/hit by what sounds to be a metallic object. The melody sounded by these bells is simple. There are no other instruments. This sounds like an amateur recording of an uncommon music instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/TnCXmm-v3Ys.wav"} +{"id": "TnJE6W6Z6mM", "caption": "A female singer sings this operatic melody. The song is medium tempo with a string section playing harmony and a piano accompaniment. The song is emotional and passionate. The song is a classic western music hit and a movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/TnJE6W6Z6mM.wav"} +{"id": "TokHdpvX7Es", "caption": "The low quality recording features a choir singing over punchy kick and snare hits, shimmering hi hats, groovy piano and groovy bass. In the first half, there are harmonizing female vocals singing, after which the male harmonizing vocals start singing. It sounds soulful, passionate and emotional. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/TokHdpvX7Es.wav"} +{"id": "Tp8PG2xae8c", "caption": "Acoustic guitars are playing chords, tremolos and melodies while a male choir is singing the same melody along. This song may be playing at a folkfest.", "audio": "/zhanghaomin/datas/musiccap/music_data/Tp8PG2xae8c.wav"} +{"id": "TqIptTnXb20", "caption": "Here we have a vintage recording of a traditional, religious Indian song. Mainly, the man with the burly and raspy voice sings and is backed by a group of female singers who sing softly.", "audio": "/zhanghaomin/datas/musiccap/music_data/TqIptTnXb20.wav"} +{"id": "TqWmuwAYmnI", "caption": "A virtuosic Male yodeler accompanied by an oompah band playing a fast beat and simple chord progression with electric bass, piano, fiddle, and drums. The feeling is manic.", "audio": "/zhanghaomin/datas/musiccap/music_data/TqWmuwAYmnI.wav"} +{"id": "TrvI6t4pAP0", "caption": "A male rapper sings this rap medley with a backup singer in vocal harmony. The song is medium tempo with a boomy bass line, synth string section and piano accompaniment. The song is storytelling and haunting in its style. The song is a retro rap song with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/TrvI6t4pAP0.wav"} +{"id": "Ts04bBeY1d4", "caption": "This is an Irish folk music piece. The melody is being played by an acoustic guitar and a mandolin. The atmosphere of the piece is cozy and easygoing. It has a steady tempo. This piece could be used in the soundtrack of a documentary. It could also be playing in the background at an Irish pub or an Irish cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ts04bBeY1d4.wav"} +{"id": "Ts3ZcUaELzA", "caption": "Someone is playing a distorted e-guitar melody in the lower mid-range. This song may be playing at home practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ts3ZcUaELzA.wav"} +{"id": "TsTdffJ9LHg", "caption": "This music is instrumental. The tempo is fast with a vigorous and rapid western classical saxophone harmony. It is spirited, vibrant,untiring, engaging, skillful and high-spirited.", "audio": "/zhanghaomin/datas/musiccap/music_data/TsTdffJ9LHg.wav"} +{"id": "Tsmx6Pb7CnU", "caption": "The Electro Pop song features a buzzy sustained synth lead, \"4 on the floor\" kick, short reversed snare hits, claps, shimmering hi hats, groovy piano chords, sustained synth pad chord and arpeggiated synth melody. It sounds energetic and like something you would hear in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/Tsmx6Pb7CnU.wav"} +{"id": "Tt3BnoJw8ds", "caption": "This symphonic rock song features a male voice singing the main melody in common time. This is accompanied by percussion playing a simple beat with single and double strokes on the snare in alternate counts. The bass plays only the root notes of the chords with no embellishments. The strings play a repetitive phrase of three notes throughout the song. The mood of the voice is storytelling. This song can be played in a rags to riches movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Tt3BnoJw8ds.wav"} +{"id": "Tvwi_YuLehk", "caption": "This is the live performance of a bluegrass music piece. There are male vocals singing together in a lively manner. There are two banjos playing the melody, one acting as the lead and the other as the rhythm. There is also an acoustic guitar following the banjos. An upright bass is playing the bass line which acts as a rhythmic background. The general atmosphere of the piece is very uplifting. The piece can be used in the soundtrack of rural comedies. It could also be used in the background for funny social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/Tvwi_YuLehk.wav"} +{"id": "TworrkXAPuI", "caption": "Female singers sing this vocal harmony with backup singers. The song is medium tempo with a groovy bass line, violin countermelody, and keyboard harmony. The song is entertaining and groovy. The song has a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/TworrkXAPuI.wav"} +{"id": "TyMZJqYmrwE", "caption": "A female singer sings this song. This section is probably a song fade as only the last bit of the word a can be heard with a mellow ukelele riff. This is followed with some sounds of something hitting a hard surface and then silence.", "audio": "/zhanghaomin/datas/musiccap/music_data/TyMZJqYmrwE.wav"} +{"id": "TzPuAqjoL80", "caption": "This song contains digital drums playing a four on the floor groove with a kick on every beat. A low synth arpeggio is serving as bassline rather than pitching up one octave while synth pluck instruments are playing a fast and repeating melody. A male voice is singing a melody in a higher key. The voice is panned to the right side of the speakers and is not the loudest element in the mix. You can hear a high pitch string drone. This song may be playing at a private houseparty.", "audio": "/zhanghaomin/datas/musiccap/music_data/TzPuAqjoL80.wav"} +{"id": "U-L9YCIdLbg", "caption": "This music is instrumental. The tempo is medium with rhythmic drumming accompaniment. The melody is simple and gets interesting as a layer of drums gets added. It is spirited, catchy and engaging.", "audio": "/zhanghaomin/datas/musiccap/music_data/U-L9YCIdLbg.wav"} +{"id": "U-UF93NA3ko", "caption": "The low quality recording features a rock song that consists passionate male vocal, alongside, harmonizing background vocals, singing over shimmering wide cymbals, bouncy snare hits, soft kick hits, electric rhythm guitar melody in the left channel, groovy bass guitar, acoustic rhythm guitar in the right channel of the stereo image and some wide toms roll. It sounds addictive and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/U-UF93NA3ko.wav"} +{"id": "U0sjbOT6hY4", "caption": "The low quality recording features a didgeridoo melody played over wooden percussion and shimmering shaker. There are some crowd chattering noises in the background. It is reverberant, due to the fact that it was performed in a medium size room, uptempo and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/U0sjbOT6hY4.wav"} +{"id": "U0xhbrULfNY", "caption": "This is a lullaby in the style of Chinese traditional music. It is an instrumental piece. The qin is playing the main tune while the erhu is holding notes in the background. The occasional higher end strum of the guzheng can be heard. The atmosphere is calming and relaxing. This piece would fit perfectly in the background of a meditation video. It could also be included in the playlists that are meant to induce sleep in babies.", "audio": "/zhanghaomin/datas/musiccap/music_data/U0xhbrULfNY.wav"} +{"id": "U3TpCc2zHrI", "caption": "This is an industrial metal/alternative metal music piece. There is a male vocal singing in a harsh manner using the guttural technique. The melody is being played by the keyboard and the distorted electric guitar while the bass guitar is playing in the background. The acoustic drums are playing a loud and fast-paced metal beat with heavy use of twin pedals on the kick drum. The atmosphere is violent. This piece could be used in the soundtrack of a gruesome horror video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/U3TpCc2zHrI.wav"} +{"id": "U4MdEIQcZxs", "caption": "The clip is a combination of various sound effects. There's a general atmospheric buzz of crowd chatter, and there are various beeping and buzzing sounds in the clip. The clip ends with a loud, slamming thud.", "audio": "/zhanghaomin/datas/musiccap/music_data/U4MdEIQcZxs.wav"} +{"id": "U4UtZeTl2DE", "caption": "A accordion-like wind instrument is playing a melody along with someone playing a rhythm on the tablas. This song may be playing at a music school jamming with the teacher.", "audio": "/zhanghaomin/datas/musiccap/music_data/U4UtZeTl2DE.wav"} +{"id": "U6SYfguaJtk", "caption": "This song contains male voices singing/shouting while an acoustic drum is playing an elevating pattern on the toms. You can hear hands clapping to the beat. A brass section/saxophones are playing a repeating melody creating tension. Then the song breaks into the next part with a piano playing along with the melody. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/U6SYfguaJtk.wav"} +{"id": "U6aLiMIlqCc", "caption": "This piece is a live performance of dancers playing the tambourine over a rock music piece in the background. The background piece has a female vocal and an electric guitar both in the major scale. A loud drum backing can also be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/U6aLiMIlqCc.wav"} +{"id": "U8XdDv5ERu4", "caption": "The low quality recording features an orchestral pop song that consists of a synth acid arpeggiated melody, claps, punchy kick, synth orchestral drums, some snare rolls, strings licks and a low male vocal choir. There are occasional ticking sound effects. It sounds epic, powerful and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/U8XdDv5ERu4.wav"} +{"id": "U8yqYlErUz8", "caption": "This music is a ukelele instrumental. The tempo is medium with a simple melody and a male voice at the end of this clip. This is a ukelele lesson/ tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/U8yqYlErUz8.wav"} +{"id": "UBfHLeCBBsA", "caption": "The Electro song features a low pitched male vocal talking over \"4 on the floor\" kick pattern, passionate female vocal melody, acid bass, claps, soft crash cymbal, shimmering hi hats and repetitive synth lead melody. Right before the drop in the second section of the loop, there is a short riser. It sounds energetic, like something you would listen to in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/UBfHLeCBBsA.wav"} +{"id": "UCBocxMCdck", "caption": "Here we have an electronic dance song that is building up to a crescendo moment. We hear a synth sound that is almost like a combination between a wood percussion instrument and the sound of water droplets. The sound has reverb applied to it, and speeds up towards the end as the song builds up. We hear a riser sound effect as well.", "audio": "/zhanghaomin/datas/musiccap/music_data/UCBocxMCdck.wav"} +{"id": "UC_XpUcIQ_8", "caption": "This clip features a rock and roll song. The main melody is sung by a male voice. Female voices sing backing vocals in harmony with the main voice. This is accompanied by percussion playing a simple beat in common time. A saxophone is playing fills in between lines. Due to the low audio quality, other instruments are not clearly audible. This song can be played in a dance party with a retro theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/UC_XpUcIQ_8.wav"} +{"id": "UD0pisqyLKA", "caption": "The low quality recording features a high pitched sound effect, followed by a siren sound effect and finally a muffled hip hop song. It sounds like it was recorded with the phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/UD0pisqyLKA.wav"} +{"id": "UDN11Q90Fa4", "caption": "A male vocalist sings this soft pop. The tempo is slow with a simple piano accompaniment, mellow acoustic guitar and rhythmic Cajun beats. The song is a simple, unaffected, romantic, melodic, sentimental, emotional and pensive Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/UDN11Q90Fa4.wav"} +{"id": "UDS6PrY9ZIM", "caption": "This pop song features a female voice singing the main melody. At the highest pitch, her voice goes into falsetto. This is accompanied by percussion playing a simple beat in common time. An electric guitar plays a repetitive two note phrase in the background. Another guitar player fills in the background. The bass plays the root notes of the chords. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/UDS6PrY9ZIM.wav"} +{"id": "UDTsCTLkZzc", "caption": "The low quality recording features an electro song being scratched by a DJ. The song consists of synth lead melody, punchy kick, claps, boomy bass and reverberant metallic impacts. It sounds groovy and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/UDTsCTLkZzc.wav"} +{"id": "UDg9vuBDtVU", "caption": "The song is an instrumental. The song is medium tempo with a groovy bass line, guitar playing accompaniment along with piano and a steady drumming rhythm with cymbal hits. The song is meditative and nostalgic. The song is a new age rock inspired tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/UDg9vuBDtVU.wav"} +{"id": "UEOUXjX5R2I", "caption": "The low quality recording features an electro song that consists of repetitive, high pitched female vocals, alongside exciting male vocals, over groovy bass, punchy kick, energetic snare hits and repetitive synth lead melody. It sounds groovy, energetic, aggressive and hypnotic - due to the repetitiveness.", "audio": "/zhanghaomin/datas/musiccap/music_data/UEOUXjX5R2I.wav"} +{"id": "UEel3wTf0Sk", "caption": "This is a gritty and upbeat indie pop song. The lead singer has a raspy voice. The drummer plays a build-up drum roll into a high energy chorus refrain.", "audio": "/zhanghaomin/datas/musiccap/music_data/UEel3wTf0Sk.wav"} +{"id": "UFyOGqmITjM", "caption": "This music is a lively fiddle instrumental. The tempo is fast with a percussion accompaniment. The music is spirited, vibrant, enthusiastic,cheerful, happy , merry and sunny. This music is Country Folk.", "audio": "/zhanghaomin/datas/musiccap/music_data/UFyOGqmITjM.wav"} +{"id": "UGEqY_NTMpI", "caption": "This is a live performance of salsa music. The quality of the sound is very poor and muffled. The song features a male singer with a nasal voice. In the background latin percussion instruments play a salsa music rhythm. Trumpets are in the background and have a muffled sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/UGEqY_NTMpI.wav"} +{"id": "UHvYrO1IGCc", "caption": "This is a gear showcase jam. Firstly, the performer describes the sound effect that is achieved when the octave pedal is connected to the electric guitar. Then, he starts to play a simple tune with a crunchy sound. Parts of the recording where the performer is not speaking can be used as electric guitar samples in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/UHvYrO1IGCc.wav"} +{"id": "UIOnnpaqBy8", "caption": "The Country song features a soft female vocal singing over repetitive arpeggiated acoustic guitar melody. It sounds heartfelt, emotional, passionate and hopeful, like something you would listen to when having a tough time.", "audio": "/zhanghaomin/datas/musiccap/music_data/UIOnnpaqBy8.wav"} +{"id": "UJA5AWbt6HM", "caption": "The Regional Mexican song features a passionate male vocal singing over guiro percussion, followed by wooden percussion, shimmering cymbals, acoustic rhythm guitar in the left channel of the stereo image and bright brass melody in the right channel. It sounds joyful, happy and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/UJA5AWbt6HM.wav"} +{"id": "UJAk1nNdo1I", "caption": "The low quality recording features a filtered, throaty male vocal singing over mellow piano melody which can barely be heard due to clashing of frequencies. There are some crackling sounds occasionally. The recording is noisy and in mono, and it sounds vintage, nostalgic, euphoric, but also kind of creepy.", "audio": "/zhanghaomin/datas/musiccap/music_data/UJAk1nNdo1I.wav"} +{"id": "ULHPhjaJ6p0", "caption": "This audio contains someone playing a complex and fast classical piece of music on a clavicembalo. This song may be playing live at a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/ULHPhjaJ6p0.wav"} +{"id": "ULXbXpLcoVA", "caption": "This is a disco/house music piece. There is a male vocal sample and a chopped hollering sample constantly repeating in the beat. The bass sound is fuzzy. The rhythm is provided by a slightly fast tempo electronic drum beat. The atmosphere is energetic. This piece could be played at nightclubs or dance clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/ULXbXpLcoVA.wav"} +{"id": "UNJswfXKJ3s", "caption": "This song is an instrumental. The tempo is fast with a lively keyboard harmony and rhythmic steel pan . It is minimal and rhythmic. The harmony is simple , straight and the steel pan adds an interesting layer to it. The music is engaging, interesting, energetic, spirited and melodic.", "audio": "/zhanghaomin/datas/musiccap/music_data/UNJswfXKJ3s.wav"} +{"id": "UO9HtZMrbBE", "caption": "The low quality recording features a repetitive synth lead melody playing over shimmering shakers and open hats and punchy \"4 on the floor\" kick pattern. It sounds energetic, uptempo and like it is an intro section of the song, since the audio is slowly fading in,", "audio": "/zhanghaomin/datas/musiccap/music_data/UO9HtZMrbBE.wav"} +{"id": "UOAv5b6MGxw", "caption": "The song is fun, playful and cheerful. It involves child vocalists who sing in unison, and various sound effects of children laughing, and a child exclaiming. The song features an intricate clarinet melody which follows the vocal in note selection.", "audio": "/zhanghaomin/datas/musiccap/music_data/UOAv5b6MGxw.wav"} +{"id": "UOC4VWQpnDM", "caption": "This audio contains a techno drum with a kick on every beat. A low male voice sample serves as bassline. A female voice sample is singing a repeated melody in the higher register. In the background you can hear an acoustic guitar being strummed like a flamenco guitar. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/UOC4VWQpnDM.wav"} +{"id": "UOKWQ2EHJQI", "caption": "A male vocalist sings this animated melody. The song is minimal instrumentation with a bright accordion harmony and organ accompaniment. It is perky, animated, bright, energetic, enthusiastic, and vibrant. This song is a classic German folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/UOKWQ2EHJQI.wav"} +{"id": "UPPHkyd7lwE", "caption": "This is an excerpt from a movie soundtrack. There is a string orchestra playing an ominous tune that is full of suspense. This piece could be used in the soundtrack of a horror movie, especially during the scenes where a character is walking through a dangerous zone.", "audio": "/zhanghaomin/datas/musiccap/music_data/UPPHkyd7lwE.wav"} +{"id": "UQKLBsZJsww", "caption": "This song is a happy Punjabi song. The tempo is fast with a male vocalist singing an enthusiastic melody to the beat of a dhol , tanpura and beat of a shaker. The song is lively, simple, energetic and festive. This song is sung at weddings. It is a jugalbandi between the bride and groom\u2019s side where two vocalists compete playful in vocal battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/UQKLBsZJsww.wav"} +{"id": "UR3k09hOxI4", "caption": "The song is an instrumental. The song is in medium tempo with various Latin percussions playing syncopated rhythms and an organ playing accompaniment. The song is a Latin Jazz tune with a definite dance rhythm. The audio quality is mediocre.", "audio": "/zhanghaomin/datas/musiccap/music_data/UR3k09hOxI4.wav"} +{"id": "URM1QgX5Ar4", "caption": "Someone is playing a rock/funk riff on an e-guitar with a lot of low end. Then a male voice starts speaking. This song may be playing during a guitar lesson.", "audio": "/zhanghaomin/datas/musiccap/music_data/URM1QgX5Ar4.wav"} +{"id": "US3ZL2zhXgI", "caption": "The low quality recording features a flat male vocal talking over ukulele melody. It sounds like a tutorial and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/US3ZL2zhXgI.wav"} +{"id": "UUJ1DNycpiQ", "caption": "This song is an energetic electronic instrumental. The song is medium fast tempo with an insistent synthesiser rhythm, dissonant tambourine funky bass and basic , amateur drumming, recurring vocal riff and vocal backup . The song is youthful, spirited, punchy and catchy with a dance groove. This song is an Electro Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/UUJ1DNycpiQ.wav"} +{"id": "UVMBRVJTvzg", "caption": "This amateur audio clip features a marching band. The quality of recording is very low. Percussion can be hard but the notes are not distinct. Steel pans are being played. The style of music is Calypso with Caribbean influence. This is not a typical marching band song as it has a danceable melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/UVMBRVJTvzg.wav"} +{"id": "UVY68vFiApA", "caption": "The low quality recording features a children's song that consists of a groovy piano, mellow bells melody, punchy kick and shimmering hi hats, after which a mellow female vocal starts singing. It sounds happy, fun, soft, mellow and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/UVY68vFiApA.wav"} +{"id": "UWl99yJsb8M", "caption": "The low quality recording features a live performance of a passionately and dynamically played classical piano melody. It is quite reverberant, as it was probably recorded in some concert hall. It also sounds emotional and passionate, even though the sound is not perfect.", "audio": "/zhanghaomin/datas/musiccap/music_data/UWl99yJsb8M.wav"} +{"id": "UXDzDV_f1jw", "caption": "This is a live performance of a theremin piece. The theremin is playing eerie high-pitched sounds in the lead while the bass guitar and the percussion is playing in the background. The atmosphere is creepy and unsettling. This piece could be used in the soundtrack of a horror movie or a horror video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/UXDzDV_f1jw.wav"} +{"id": "UY2_Q830lqo", "caption": "This song is played by an ensemble. The lead melody is played on a clarinet. A flute plays backing notes. A French horn plays the lower registers. Another clarinet plays a melody in harmony. This is an instrumental song. There are no voices in this song. There is no percussion in this song. This song is relaxing. This song can be played in a black tie dinner event.", "audio": "/zhanghaomin/datas/musiccap/music_data/UY2_Q830lqo.wav"} +{"id": "Ubj0jlheyvk", "caption": "This audio contains a synth bass playing a bassline in a steady 8th notes rhythm along with other digital pluck sounds playing a fast pattern melody in the mid to higher register. Digital flute-like sounds are playing a melody along and one on top in a higher pitch. This song may be playing in an adventure video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ubj0jlheyvk.wav"} +{"id": "UcNVLU-cRNg", "caption": "The Metal song features a manic drum roll followed by wide arpeggiated electric guitar melody in the beginning of the loop. When the beat drops, there is a flat male vocal singing over aggressive wide electric guitar chords, energetic bass guitar, energetic cymbals and punchy kick and snare hits. It sounds very energetic, like something you would go in a mosh pit for.", "audio": "/zhanghaomin/datas/musiccap/music_data/UcNVLU-cRNg.wav"} +{"id": "UcS5U1mpbAE", "caption": "This song is an electronic instrumental. His tempo is medium with atmospheric synthesiser, slick drumming and boomy, rhythmic bass drops , slide whistle along with a tapping sound. The music is distorted and muddled as the audio quality is mediocre.", "audio": "/zhanghaomin/datas/musiccap/music_data/UcS5U1mpbAE.wav"} +{"id": "Uc_1PzGr5xw", "caption": "The low quality recording features a tutorial where in the beginning there is a banjo guitar melody over which a passionate male vocalist is singing. In the second half of the loop, a flat male vocal is talking. The recording is noisy, in mono and it sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/Uc_1PzGr5xw.wav"} +{"id": "UcabTrKowlI", "caption": "This is an r&b/hip-hop music piece. There is a male vocal rapping and a female vocal singing in a rap-like manner. The beat consists of a piano playing the chords of the tune with an electronic drum backing. The atmosphere of the piece is playful and energetic. This piece could be used in the soundtrack of a high school drama movie/TV show. It could also be played at birthday parties or beach parties.", "audio": "/zhanghaomin/datas/musiccap/music_data/UcabTrKowlI.wav"} +{"id": "UdA6I_tXVHE", "caption": "The low quality recording features an onomatopoeia, performed by male vocalists. The recording is noisy and it is crackling.", "audio": "/zhanghaomin/datas/musiccap/music_data/UdA6I_tXVHE.wav"} +{"id": "UeYmnV-B8so", "caption": "This piece contains a lot of reverb and the instruments are using delay to create long arpeggio landscapes and rhythms. An acoustic guitar is being picked creating an arpeggio melody. A piano is playing a countermelody with a lot of reverb. A synth bassline playing one note in a 8th note rhythm is holding the ground of this composition. This song may be playing while dancing alone in your room.", "audio": "/zhanghaomin/datas/musiccap/music_data/UeYmnV-B8so.wav"} +{"id": "UfEGX0rNOvA", "caption": "A female singer sings this cool melody with male backup singer in harmony. The song is medium tempo with a groovy bass line, steady drumming rhythm, keyboard harmony and other percussion hits. The song is groovy with a story telling nature. The song is a retro hip hop dance hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/UfEGX0rNOvA.wav"} +{"id": "UfZP677y3Dc", "caption": "A male vocalist sings this animated song. The tempo is fast with a flute \nOr recorder and keyboard harmony with the sound of clapping and tapping in the background. The song is animated, spirited, enthusiastic, catchy and upbeat with rhythmic speech and childish lyrics. This is a Children\u2019s Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/UfZP677y3Dc.wav"} +{"id": "UhcoWyEQwBI", "caption": "This piece is an instrumental. The tempo is fast with the clip starting with white noise, followed by electronic beeps playing a melody, paper rustling, scribbling sounds and chatter of people in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/UhcoWyEQwBI.wav"} +{"id": "UhwJrftWAFg", "caption": "This music is an electronic instrumental. The tempo is fast with synthesiser articulation, digital drumming and circuitry based technology. The music is loud, futuristic, contemporary, psychedelic, trippy ,hypnotic and youthful with a dance groove. This music is EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/UhwJrftWAFg.wav"} +{"id": "UiiYMspxfhU", "caption": "The Pop song features an echoing female vocal singing over mellow piano chord progression and filtered sustained synth bass. It sounds emotional, mellow and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/UiiYMspxfhU.wav"} +{"id": "UinQGYfmZhE", "caption": "The low quality recording features a live performance of a gospel song and it consists of harmonizing mixed choir vocals singing in a very large space. It sounds passionate, emotional, soulful and powerful.", "audio": "/zhanghaomin/datas/musiccap/music_data/UinQGYfmZhE.wav"} +{"id": "UjDh1OlOwuE", "caption": "This audio contains someone playing percussion. In the background you can hear people's voices. This song may be playing in a cultural presentation.", "audio": "/zhanghaomin/datas/musiccap/music_data/UjDh1OlOwuE.wav"} +{"id": "UkTWmyy7ia8", "caption": "This audio contains an orchestral classical composition played by string instruments. violins/violas are playing the main melody in a higher key. The piece sounds fast paced and elevating. This song may be playing live sitting in an orchestra performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/UkTWmyy7ia8.wav"} +{"id": "UkZ76EFfLSg", "caption": "The techno music excerpt features only a beat, no other melodic or harmonic instruments. By the sound of it, the beat was made using sampled drums. Other percussive instruments can be heard in the background. This music would be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/UkZ76EFfLSg.wav"} +{"id": "UkqayNnk00w", "caption": "The Electro song features a reverberant reversed piano melody and synth bass with a modulated filter effect on it, over which there is a white noise riser that leads into the short snippet of drop that consists of layered punchy kick and shimmering hi hat. Right before the drop, there is a filtered, echoing male vocal too. It sounds emotional and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/UkqayNnk00w.wav"} +{"id": "UnFEqUWTefM", "caption": "A female vocalist sings this melodic song. The tempo is medium with female vocalisation, female choral backup, groovy bass lines,slick drumming, church organ harmony, and a lively piano accompaniment that comes in at the end of this clip. The song is pleasant, melodic, insistent, repetitive and recurring like a chant or trance. This song is a soul music/ Trip Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/UnFEqUWTefM.wav"} +{"id": "Uo-Okq1D8Xo", "caption": "The low quality recording features a classical song played on harpsichord. It sounds emotional, soulful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/Uo-Okq1D8Xo.wav"} +{"id": "UoGXR3V5Mro", "caption": "This is a low quality recording of a sped up song. The song features voices that have reached a high pitch of singing due to the sped up tempo. This is accompanied by percussion playing at a fast tempo. Distortion guitars are playing power chords but are now at a higher pitch due to speeding up the song. The bass plays the root notes of the chords. The song has a quirky mood. It can be used in a comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/UoGXR3V5Mro.wav"} +{"id": "UoSID1KzWuI", "caption": "This song contains a composition played on an acoustic 12 string guitar strumming fast chords while another guitar is playing a fast paced melody in a higher key. The whole pattern repeats itself. This song may be playing in an Irish bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/UoSID1KzWuI.wav"} +{"id": "UoxHwOl2gN0", "caption": "This song contains an acoustic drum-set holding the groove and changing his beat after a fill-in to a four on the floor with a kick on every beat. Mixed voices are singing a soulful sounding melody then an e-piano takes over playing a melody before a trumpet and a saxophone come in playing a loud melody. In the background you can hear percussion such as a cowbell being panned to the right side of the speakers. The crowd is cheering and clapping along. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/UoxHwOl2gN0.wav"} +{"id": "Ur8O3h8S0K4", "caption": "A female singer sings this lovely melody with a choral harmony support. The song is medium tempo with a Steady drumming rhythm, various percussion, percussive bass line, keyboard accompaniment and guitar rhythm. The song slows down at the end. The song is emotional and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ur8O3h8S0K4.wav"} +{"id": "UrgzGbGVV8I", "caption": "The song is an instrumental music piece. The song is slow tempo with an electric guitar playing lead with heavy echoes, steady drumming and a keyboard harmony. The song is casual and slightly out of rhythm. The song is an instrumental with a casual listening vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/UrgzGbGVV8I.wav"} +{"id": "UsHtZ7Bzi0s", "caption": "The low quality recording features a rock song that consists of mellow piano melody, energetic cymbals, punchy kick, punchy snare, female choir, wide electric guitar chords, sustained strings melody, smooth bass guitar and passionate female vocal singing over it. It sounds epic, powerful and energetic, like something you would hear in video games trailers.", "audio": "/zhanghaomin/datas/musiccap/music_data/UsHtZ7Bzi0s.wav"} +{"id": "UsdoUjuczY4", "caption": "This music clip is an percussionary instrument. The tempo is medium fast with steady bass drum, energetic snare drum beat and cymbal rides. This music is a youthful, punchy, energetic, simple drumming style.", "audio": "/zhanghaomin/datas/musiccap/music_data/UsdoUjuczY4.wav"} +{"id": "UtCRBs5p4EQ", "caption": "A female voice is singing with a slight opera feeling to it. A string section is playing along with her melody. An upright-bass is played with a bow providing the bassline. This song may be playing at a musical.", "audio": "/zhanghaomin/datas/musiccap/music_data/UtCRBs5p4EQ.wav"} +{"id": "UtZofZjccBs", "caption": "The drums are playing the kick along with an e-bass. Then 16th notes come in played on a hihat. A male singer with a higher register voice is singing loudly. The song seems to be building up before breaking into the next part. This song may be playing cruising down a hill with a skateboard.", "audio": "/zhanghaomin/datas/musiccap/music_data/UtZofZjccBs.wav"} +{"id": "Utl5it7YMUs", "caption": "This is a hard rock music piece. There is a male vocalist singing in the lead. The electric guitar is playing the main melody while a bass guitar plays in the background. The acoustic drums are playing a groovy rock beat. There is a raw, psychedelic feel to this piece. It could be playing in the background of a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/Utl5it7YMUs.wav"} +{"id": "Uu8m1oOWkiE", "caption": "The low quality recording features a loud bell impact. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/Uu8m1oOWkiE.wav"} +{"id": "UvCY9FHpKC8", "caption": "This pop song features female voices singing the main melody. This is accompanied by fast paced drumming. The percussion plays a simple fast paced beat in common time. Distortion guitars play power chords. The bass plays the root notes of the chords. There are quirky sounds played in the background. A cartoon whistle is played in the background. A triangle is also heard in the background. There is the sound of a cartoon laser blast in the background. The mood of the song is happy. This song can be played during the end credits of a college comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/UvCY9FHpKC8.wav"} +{"id": "Uvn7waPvseo", "caption": "This is an instrument showcase jam. It is an electronic music piece played on a drum machine. There is a booming electronic drum beat in the rhythmic background. There is a medium-to-high pitch melodic pad repeating the same tune. The sound of the piece is crisp and loud. This piece could be used in the soundtrack of a fast-paced video game in the arcade genre. It could also be playing in the background during breaks at a sports venue.", "audio": "/zhanghaomin/datas/musiccap/music_data/Uvn7waPvseo.wav"} +{"id": "UwxatzcYf9Q", "caption": "An acoustic piano is playing a composition that sounds sad and dramatic. At the end a loud higher pitched string is coming in. This song may be playing as an intro for a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/UwxatzcYf9Q.wav"} +{"id": "Ux1vBolJf5Q", "caption": "A male voice is singing in a higher register along with male background voices. An acoustic drum is playing a complex groove with a lot of fill-ins. A e-bass is holding the groove along with a e-guitar strumming single chords. This song may be playing live at a festival in the 70s.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ux1vBolJf5Q.wav"} +{"id": "Ux3YosKD-9I", "caption": "This is the live recording of a classical music recital. There is a harp being played in an innovative manner that combines both the melodic and the rhythmic aspects of the instrument. The atmosphere of the piece is dreamy. It could be used in the soundtrack of a calm video game or a nature documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ux3YosKD-9I.wav"} +{"id": "UxT3KG4AHAI", "caption": "The low quality recording features a passionate male vocal chant, followed by harmonizing male vocals chants, after which a shimmering shaker and wooden percussion start playing. It sounds soulful, passionate and dynamic. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/UxT3KG4AHAI.wav"} +{"id": "UxlrI-9RtWg", "caption": "The low quality recording features a resonating bowl tone. It sounds calming and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/UxlrI-9RtWg.wav"} +{"id": "UxrAsZ7Z09Y", "caption": "The low quality recording features an electro song playing, while the crowd is screaming. It sounds loud, harsh, distorted and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/UxrAsZ7Z09Y.wav"} +{"id": "Uxyu3XwXEV8", "caption": "This is a Japanese pop music piece. The music has a 70s feel to it. There is a female vocalist singing melodically at the forefront. There is a keyboard playing a melody while being backed by an electric guitar and a bass guitar. There is a simple acoustic drum beat in the rhythmic background. The piece has a melancholic, haunting atmosphere to it. This piece could be used in drama movies and TV series that take place in Japan.", "audio": "/zhanghaomin/datas/musiccap/music_data/Uxyu3XwXEV8.wav"} +{"id": "UzAXqTsdtjY", "caption": "The low quality recording features didgeridoo drone melody over wide, mellow synth pad and some light, echoing percussive element. It sound relaxing and calming - like something you'd put on while doing yoga.", "audio": "/zhanghaomin/datas/musiccap/music_data/UzAXqTsdtjY.wav"} +{"id": "UzDVZzIIcy8", "caption": "The low quality recording features a wide sustained strings melody and natural sound effects in the background that consist of reverberant birds chirping and water flowing sound effects. It sounds calming, relaxing and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/UzDVZzIIcy8.wav"} +{"id": "UzT20Rf8RPA", "caption": "A male vocalist sings this vigorous heavy metal song. The tempo is fast with intense electric guitar lead ,hard hitting drumming, steady bass lines, keyboard harmony and vocal backup. There is a sound of racing cars at the onset of the song followed by a vigorous male vocal harmony. The song is energetic, enthusiastic, gripping, intense, vital and youthful. This song is Heavy Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/UzT20Rf8RPA.wav"} +{"id": "V0zQHNmz0gU", "caption": "This is an instrumental jazz music piece. The main theme is being played on a theremin while there is a keyboard and an upright bass in the melodic background. For the rhythm, there is an acoustic swing jazz drum beat. There is an avant-garde feel to this piece. It could be used in the soundtrack of a sci-fi movie or a TV show. It could also be played in the soundtracks of video games with an outer space setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/V0zQHNmz0gU.wav"} +{"id": "V1A4wBgvPgI", "caption": "This jazz song features the main melody played on a flugelhorn and a saxophone. Both instruments play in harmony with variations in melody. These instruments compliment each other. This is accompanied by percussion playing a jazz beat with constant strokes on the ride cymbal. The bass guitar plays a groovy bassline starting with a descending lick. This is then followed with an ascending lick to reach the higher notes before descending back. The guitar plays chords with string muting in a jazz rhythm. The mood of this song is upbeat. This song can be played in an advertisement for a luxury car.", "audio": "/zhanghaomin/datas/musiccap/music_data/V1A4wBgvPgI.wav"} +{"id": "V1M3HiUz0ZQ", "caption": "The song is a pop band instrumental groove for an amateur home video recording. The song is medium tempo with a steady drumming rhythm, guitar lead, cowbell percussion, a percussive bass line and grunge keyboard harmony tones. The song is exciting and unimpressive like a background music track for an amateur skater video. The song is a mix of a retro pop instrumental and ambient Street noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/V1M3HiUz0ZQ.wav"} +{"id": "V3Jb0Q_e_pQ", "caption": "The music features a small group of children singing a repeating melody. A kick drum along with a hi-hat drives the pulse of the music. Throughout the music excerpt one can hear zipper sounds, vinyl scratches and other percussive sounds like cowbells.", "audio": "/zhanghaomin/datas/musiccap/music_data/V3Jb0Q_e_pQ.wav"} +{"id": "V3Vvp5HS90k", "caption": "The music features a group of male and female voices singing a melody in vocal harmony. Two of them are playing the melody on different pitches and at least another two are accompanying them with a rhythmic pattern that's sung with a voice effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/V3Vvp5HS90k.wav"} +{"id": "V4YUpQKeKD4", "caption": "This recording contains a marimba melody that sounds like it is being slowed down a lot. At the end there is digital sound like something heavy hitting the ground in slow motion. This is an amateur recording. This song may be playing in a videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/V4YUpQKeKD4.wav"} +{"id": "V5HMIxuAtv8", "caption": "The low quality recording features a live performance of a harmonizing mixed choir, introduced by a fruity male vocal. There is a footstep and crowd clapping sound right after introduction. The recording is a bit noisy, in mono and it sounds passionate, emotional and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/V5HMIxuAtv8.wav"} +{"id": "V5xL8hLFY58", "caption": "The Country Blues song features a flat male vocal singing over acoustic guitar melody, accordion and a sustained brass section melody. It sounds very noisy, vintage and therefore nostalgic and sentimental - like something you would hear in an old movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/V5xL8hLFY58.wav"} +{"id": "V7RPmwxyhBA", "caption": "This is an experimental electronica piece. There are various synth sounds, some at medium range and most at high range. There is a disorganized, chaotic feel to this piece. It carries an atmosphere of randomness that can be most optimistically classified as avant-garde. This piece could be used in horror movies and video games to signify a separation from reality.", "audio": "/zhanghaomin/datas/musiccap/music_data/V7RPmwxyhBA.wav"} +{"id": "V9EFYFKlYbE", "caption": "This is a hip-hop dance music piece. There is a male vocalist who is singing in a flamboyant manner. There is an electric guitar playing the melody joined by a strong bass sound. There is a groovy, urban atmosphere. This piece can be used as an accompaniment piece in modern dancing courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/V9EFYFKlYbE.wav"} +{"id": "V9jIsOTC1lY", "caption": "This song contains an acoustic drum set playing a jazzy swing groove using kick,snare and ride. You can hear various steeldrums playing different parts of the song. One is playing as bass, others as chords in the midrange and others are playing a melody in the upper register. This song may be playing live at a local event.", "audio": "/zhanghaomin/datas/musiccap/music_data/V9jIsOTC1lY.wav"} +{"id": "VAqPLAgn9NI", "caption": "This is a Hungarian hip-hop music piece. There is a male vocal rapping in the Hungarian language. There is a piano sample in the melodic background. There is also a strong bass sound. The rhythmic background has an electronic drum beat. The atmosphere is gloomy and urban. This piece could be used in the soundtrack of a crime movie or a TV series that takes place in Hungary.", "audio": "/zhanghaomin/datas/musiccap/music_data/VAqPLAgn9NI.wav"} +{"id": "VAqgpoyD2jc", "caption": "Someone is strumming a banjo along with playing a lead melody. This may be playing sitting in the countryside in front of your house in the garden.", "audio": "/zhanghaomin/datas/musiccap/music_data/VAqgpoyD2jc.wav"} +{"id": "VB82vMSTYK0", "caption": "This composition contains a small orchestra playing melodies on violas and violins in the higher mid range to the higher register. The celli and the upright bass being stroked with a bow are playing a rhythmic melody part that gives the foundation of the song. This song may be playing live as a classical concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/VB82vMSTYK0.wav"} +{"id": "VCIN1OJkNbg", "caption": "Someone is playing a melody along with chords in the mid range on an organ. This song may be playing in a gospel church.", "audio": "/zhanghaomin/datas/musiccap/music_data/VCIN1OJkNbg.wav"} +{"id": "VCozi4GDpxQ", "caption": "This music is instrumental. The tempos medium with vocalisation that sounds like blowing raspberries or a motor, followed by a man giving instructions on how to use this technique on a didgeridoo followed by a didgeridoo sound. There are ambient sounds in the background like people talking and gentle breeze. The didgeridoo sound is deep, rich, droning and unique. This clip is a tutorial/lesson on how to play a didgeridoo .", "audio": "/zhanghaomin/datas/musiccap/music_data/VCozi4GDpxQ.wav"} +{"id": "VCrnnx9jTqs", "caption": "In this clip, we hear some random drum sequences on the tom drums and snare drum of a drumkit. Towards the end, there is a slightly high pitched sound in the background that can be subtly heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/VCrnnx9jTqs.wav"} +{"id": "VCusyLPrFCo", "caption": "An acoustic drum is played along with a bassline, an acoustic guitar and piano all playing the same rhythm. Strings are playing a melody in the mid range along with the female singer that gets accompanied by backing vocals singing harmonies along. This song sounds romantic and cheerful. This song may be playing at the beginning scene of a rom-com movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/VCusyLPrFCo.wav"} +{"id": "VDYqYuPzW8E", "caption": "The low quality recording features an electro song that consists of a punchy \"4 on the floor\" kick pattern, shimmering hi hats, mellow claps, repetitive synth bass, short snare roll, subtle synth bells melody and loud synth lead melody. Even though it is thin, it is still something you would hear as an energetic track in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/VDYqYuPzW8E.wav"} +{"id": "VG6-MlmCgzI", "caption": "The music fits the carnatic genre from Indian folk. A sitar plays a background melody with a certain brightness to it. A female vocalist sings a repetitive mellow melody. The aura of the song is very traditional and spiritual.", "audio": "/zhanghaomin/datas/musiccap/music_data/VG6-MlmCgzI.wav"} +{"id": "VHYxygh1STA", "caption": "A male vocalist sings this jazz style melody. The tempo is fast with syncopated piano accompaniment, slick drumming, groovy bass line and rhythmic acoustic guitar. The music is energetic, ambient, mellow, pleasant with a dance groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/VHYxygh1STA.wav"} +{"id": "VHyXvbg6y9M", "caption": "This audio contains someone playing a fast melody on a harp. This song may be playing as part of a video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/VHyXvbg6y9M.wav"} +{"id": "VJ-dpTx_3Cg", "caption": "The country music features a male voice singing while being backed by female vocals. The drums play a simple and repeating rhythm and together with the bass guitar drive the pulse of the music. An electric guitar plays short repeating musical phrases that incorporate the slide technique. In the background a group of strings fills the harmony and also provides a melody in the higher register.", "audio": "/zhanghaomin/datas/musiccap/music_data/VJ-dpTx_3Cg.wav"} +{"id": "VJ1RqPqF9O4", "caption": "This pop ballad features a female voice singing the main melody. This is accompanied by an acoustic guitar playing chords. An electric guitar plays a descending lick after one line. There are no other instruments in this song. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/VJ1RqPqF9O4.wav"} +{"id": "VL6uF-XeE_A", "caption": "The song is an instrumental. The song is medium fast tempo with a keyboard playing chords percussively and a lower register bass line that is in harmony. The song is energetic and exciting. The song is of poor audio quality and sounds like the intro section.", "audio": "/zhanghaomin/datas/musiccap/music_data/VL6uF-XeE_A.wav"} +{"id": "VLjcIlZvkY0", "caption": "The low quality video features a filtered male breathing sound effects, muffled male screaming sound effects, monster roar sound effects and wide strings rising melody. It sounds intense and suspenseful, almost like some old horror movie with low quality sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/VLjcIlZvkY0.wav"} +{"id": "VM-U7MyZAck", "caption": "This music is instrumental. The tempo is fast with an electric guitar playing a bright lead with infectious drumming and syncopated bass lines. The music is upbeat, energetic, youthful, animated, spirited, enthusiastic, groovy and funky.", "audio": "/zhanghaomin/datas/musiccap/music_data/VM-U7MyZAck.wav"} +{"id": "VMWW9OX1EJM", "caption": "A man narrates a documentary in this video. The audio quality is poor with keyboard harmony and medium tempo percussions playing along with waves crashing sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/VMWW9OX1EJM.wav"} +{"id": "VMzn9GytUTk", "caption": "This pop song features a male voice singing the main melody. This is accompanied by female voices singing backing voices in harmony. The percussion plays a groovy bassline. Synth sounds are heard in the background in the form of volume swells and ring modulators. This song has a happy feel. This song is a dance song. It can be played at a house party.", "audio": "/zhanghaomin/datas/musiccap/music_data/VMzn9GytUTk.wav"} +{"id": "VNjYW4OXqTs", "caption": "This song is an instrumental. The tempo is fast with an animated keyboard harmony, funky bass lines; groovy electric guitar melody, slick drumming and synthesiser arrangements. The instrumental is upbeat, catchy, vibrant, animated, youthful and vivacious. This song is an Electro Rock/ Synth Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/VNjYW4OXqTs.wav"} +{"id": "VNzEAjztgxg", "caption": "The song is a drum and bass, techno kind of song. It features percussion in the form of clapping hands and rim shots, and a high tube bass type of synth. The song is fairly up-tempo while being mellow.", "audio": "/zhanghaomin/datas/musiccap/music_data/VNzEAjztgxg.wav"} +{"id": "VOWGbyg4KZY", "caption": "The Low quality recording features a groovy acoustic rhythm guitar melody that occasionally has some audio cuts out in the stereo image - making it sound unbalanced.", "audio": "/zhanghaomin/datas/musiccap/music_data/VOWGbyg4KZY.wav"} +{"id": "VP1cB_AVu6c", "caption": "This song contains a digital drum with a shaker sound and a triangle. A soft sub bass is playing along. In the background you can hear one continuous high tone from a digital string sound. Other strings and a piano are playing a simple repeating melody. The female voice is singing along with backing vocals in the background. This song may be playing loud while driving a car.", "audio": "/zhanghaomin/datas/musiccap/music_data/VP1cB_AVu6c.wav"} +{"id": "VRfi64fecj4", "caption": "This is an upbeat pop dance song in Spanish. The drum beat is energetic and punchy and features hi-hat hits in eighth notes throughout the clip. There's a male vocalist chanting the same phrase energetically, while the female singer calmly and coolly sings a gentle melody. The female singer's melody almost stands in contrast to the very lively beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/VRfi64fecj4.wav"} +{"id": "VRxFYwbik6A", "caption": "This is a piece from a movie theme. There is a cinematic synth being played to create a dramatic effect. There are a lot of sound effects such as explosions, thunderstorms, falling objects and engine sounds. The atmosphere is violent and filled with suspense. This piece could be used to lift samples from. These samples could be used to amplify movie scenes and video game sequences.", "audio": "/zhanghaomin/datas/musiccap/music_data/VRxFYwbik6A.wav"} +{"id": "VSAbMy1Rlio", "caption": "This is a comedy music piece. There are male vocalists singing in a rap-like manner in the Hindi language. The tune of the piece is being played by the synth bass while the rhythm is played by an electronic drum beat. There is an amusing aura to it. Due to the lyrics, this piece could be used in the soundtrack of a comedy movie involving married men.", "audio": "/zhanghaomin/datas/musiccap/music_data/VSAbMy1Rlio.wav"} +{"id": "VSf3_XpiPkQ", "caption": "This is an indie folk music piece. There is a melancholic melody being played by the banjo and the trombone, then they both stop and the organ can be heard holding a note. The atmosphere is sentimental. This piece could be used in the soundtrack of a drama, especially during the scenes where people are mourning the loss of a character.", "audio": "/zhanghaomin/datas/musiccap/music_data/VSf3_XpiPkQ.wav"} +{"id": "VTOf24hbq0A", "caption": "This is a pop music piece. There is a female voice that sings passionately at a high volume. The rhythmic background is provided by the acoustic drums. The melody is being played by a synthesizer with a strong bass in the background. There is a vibrant and romantic feel to it. This piece could be played at weddings or in the soundtracks of romance series.", "audio": "/zhanghaomin/datas/musiccap/music_data/VTOf24hbq0A.wav"} +{"id": "VTagIq90b7s", "caption": "The low quality recording features wide synth chords, sustained synth bass and mellow bells melody, followed by low tom hits located in the left channel of the stereo image. It sounds emotional, passionate, powerful and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/VTagIq90b7s.wav"} +{"id": "VV-DgnPPhSo", "caption": "The low quality recording features a cover of traditional folk song and it consists of reverberant, passionate female vocal singing over repetitive percussive instrument and plucked strings melody. It sounds passionate, cultural and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/VV-DgnPPhSo.wav"} +{"id": "VV85n-ebuUU", "caption": "The music features a male male voice singing a melody that repeats one time. Backing the singer are other male voices that sing in harmony. The instrumental part consists of a drum kit and a bass guitar that blend together to drive the pulse of the music forward.", "audio": "/zhanghaomin/datas/musiccap/music_data/VV85n-ebuUU.wav"} +{"id": "VZJfkEet6EQ", "caption": "The song is an instrumental. The tempo is medium and changes as the player changes the lick. The guitar is played solo styling with jarring string action. Playing amateur music is like a music lesson. The song is a bass guitar tutorial and sounds amateurish. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/VZJfkEet6EQ.wav"} +{"id": "VZfrDZhI7BU", "caption": "This is electronic dance music. The tempo is fast with a turntable output, synthesiser arrangement ,digital drum beats and loud sounds of clanging, crashing and tapping superimposed on the music. The music is youthful, punchy, buoyant and enthusiastic with a dance groove. This music is EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/VZfrDZhI7BU.wav"} +{"id": "VZjE27e9X7o", "caption": "The low quality recording features a didgeridoo groovy melody that slowly increases in volume. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/VZjE27e9X7o.wav"} +{"id": "Vbcy6KBJsAA", "caption": "The low quality recording features hip hop beatboxing. The recording is noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vbcy6KBJsAA.wav"} +{"id": "Vbx6TFxSPYY", "caption": "The low quality recording features a sound of a digital bell, followed by crowd noises in the background. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vbx6TFxSPYY.wav"} +{"id": "Vci2eZYzA-c", "caption": "The low quality recording features metallic and robotic sound effects which makes it sound industrial. The recording is very noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vci2eZYzA-c.wav"} +{"id": "VdYakZ4Yciw", "caption": "A classical composition containing strings playing a short repeating melody. You can hear a lot of background noises that seem to come from cars racing. This is an amateur recording. This song may be playing sitting in a limousine.", "audio": "/zhanghaomin/datas/musiccap/music_data/VdYakZ4Yciw.wav"} +{"id": "Ve6Zy1BXBbY", "caption": "This low quality audio features a child singing the main melody. This is accompanied by other children's voices singing vocables in the background in harmony. An acoustic guitar strums chords. There are no other instruments in this song. This song has a holiday mood. This song can be played in a Christmas movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ve6Zy1BXBbY.wav"} +{"id": "VeAomElRCJc", "caption": "The song is an instrumental. The song is a slow tempo with a stringed instrument playing a poignant melody, a strong bass line and a subtle percussive rhythm. The song is rich in tradition and poignant. The song has poor audio quality with hissing disturbances.", "audio": "/zhanghaomin/datas/musiccap/music_data/VeAomElRCJc.wav"} +{"id": "VeXcCHo5iMI", "caption": "The low quality recording features a male beatboxing through a didgeridoo. There is a sound of inhaling too. The recording is noisy, in mono and buzzy, as it was recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/VeXcCHo5iMI.wav"} +{"id": "VfARCp38XtA", "caption": "The low quality recording features a live performance of a rock song and it consists of passionate male vocal singing over energetic drums, funky bass guitar, electric guitar melody and solo brass melody. At the end of the loop, there is a short snippet of choir singing in harmony. Overall it sounds funky, energetic, soulful and passionate - as a live performance should sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/VfARCp38XtA.wav"} +{"id": "VfEJHqtsuIo", "caption": "The low quality recording features an electro song that consists of passionate female vocals singing over punchy kick, synth melody, male chants, snappy claps, shimmering hi hats, followed by echoing flat male vocals. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/VfEJHqtsuIo.wav"} +{"id": "Vfcfj4OIJXE", "caption": "This is an instrumental hip-hop music piece. It is meant to be used as a rap beat. There is a fuzzy synth bass playing a groovy bass line with a mellow sounding keyboard playing alongside it. There is a loud electronic drum beat in the rhythmic background. This piece has a crisp and urban atmosphere. It could either be used as a rap beat or it could take place in the soundtrack of a crime movie/TV show with a modern city setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vfcfj4OIJXE.wav"} +{"id": "VgwsGjRk61M", "caption": "The low quality recording features a groovy didgeridoo playing over playback that consists of a \"4 on the floor\" kick pattern and shimmering hi hats, followed by snappy rimshots. There is a flat male vocal talking at one point. The recording is loud, distorted and it sounds groovy overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/VgwsGjRk61M.wav"} +{"id": "Vi2posMLsrg", "caption": "The electronic instrumental music features a melody played by a synth sound and being accompanied by other electronic sounds. In the low-register a bass electronic sound can be heard playing at times twice every beat, driving the pulse of the music. In the second half of the music excerpt another electronic sound can be heard in the upper register playing chords.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vi2posMLsrg.wav"} +{"id": "ViF7A7XODiw", "caption": "The low quality recording contains a widely spread electric guitar melody played with chorus effect, which in the second part of the loop is turned off - judging by the sounds of the melody and a tinny switch sound effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/ViF7A7XODiw.wav"} +{"id": "VjXt63pqUgw", "caption": "This music section is instrumental. The tempo is slow with an amplified instrument playing a monotone Note with hollow sounds. The music is eerie, creepy, sinister, scary, spooky, mysterious, ominous, ambient and supernatural. This music is Goth Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/VjXt63pqUgw.wav"} +{"id": "VjbRot21Hq0", "caption": "The low quality recording features an electric guitar changing pitch as it is being tuned, string by string. The recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/VjbRot21Hq0.wav"} +{"id": "VkVKGyWi2r4", "caption": "This heavy metal song features a male voice singing the main melody. This is accompanied by aggressive percussion playing in common time. The distortion guitar plays power chords with a galloping rhythm. The gallop is ended with an ascending lick. The bass follows the same pattern as the distortion guitar but plays only the root notes of the chords. This song is upbeat. The quality of the audio is low. This song can be used when a wrestler enters the WWE arena.", "audio": "/zhanghaomin/datas/musiccap/music_data/VkVKGyWi2r4.wav"} +{"id": "VkXLtUx-RmI", "caption": "This audio contains crickets chirping. Then someone starts playing a digital accordion. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/VkXLtUx-RmI.wav"} +{"id": "VlXi2TxMXbc", "caption": "This is a live recording of a musician playing a Chinese flute, otherwise known as a dizi. It is a calming and melodic piece - and you could imagine yourself walking peacefully through marshlands or grasslands. Though the melody is enchanting, the audio quality is average - with a slight fuzzy buzz present in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/VlXi2TxMXbc.wav"} +{"id": "VlgOLOoctm0", "caption": "This is a lullaby version of a pop music piece. The main tune is played by a lyre which creates a medieval aura in the song. There is also a xylophone playing in the background with a supporting tune. A cello can be heard playing staccato notes for the bassline. An occasional bell percussion that sounds similar to a sleigh bell can be heard in the background. This could both be played in wholesome social media content and also due to its soothing nature in playlists meant to be played at bedtime for babies.", "audio": "/zhanghaomin/datas/musiccap/music_data/VlgOLOoctm0.wav"} +{"id": "VlwbDjggUKk", "caption": "This is an instrumental trumpet music piece. The trumpet is playing a calming main melody while the keyboard and the bass guitar are playing in the background. There is a slow tempo acoustic sounding drum beat playing the rhythm. The atmosphere is soothing.This piece could be used in the soundtrack of an art movie. It could also be playing in the background at a sauna.", "audio": "/zhanghaomin/datas/musiccap/music_data/VlwbDjggUKk.wav"} +{"id": "VnJeG9RGUVM", "caption": "The low quality recording features a big band song that consists of wide reverberant brass section melody, shimmering shakers and cymbals, bells melody, piano chord progression, smooth bass and soft kick hits. There are some tom rolls that represent a transition into the next section. It sounds happy and fun, but it also gives off euphoric and nostalgic vibes, as it sounds vintage.", "audio": "/zhanghaomin/datas/musiccap/music_data/VnJeG9RGUVM.wav"} +{"id": "Vo6eT8eMMfQ", "caption": "The low quality recording features a live performance of a hard rock song that consists of punchy kick and snare hits, energetic cymbals, distorted bass guitar and aggressive electric guitar riffs. There are some crowd cheering sounds in the background. It sounds energetic, aggressive and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vo6eT8eMMfQ.wav"} +{"id": "VpIhbDN58mA", "caption": "The low quality recording features a huge percussive toms and huge low tom hits playing in a very large, reverberant space. It has a lot of low frequencies and it sounds energetic and epic, like a combat background music for a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/VpIhbDN58mA.wav"} +{"id": "VpikuLP_9qQ", "caption": "The low quality recording features a rock song sung by passionate male vocalists, after which there are camera shuttering and crowd yelling sound effects. The recording is in mono and overall it sounds distorted, crushed, noisy and vintage.", "audio": "/zhanghaomin/datas/musiccap/music_data/VpikuLP_9qQ.wav"} +{"id": "Vr7wbGcvFts", "caption": "The music features a male voice singing and being accompanied by backing vocals. The drums play a laid-back rhythm and together with the bass guitar drive the pulse of the music. An acoustic guitar is accompanying the singer lightly. In the background one can hear birds chirping and children having fun. The overall atmosphere is uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vr7wbGcvFts.wav"} +{"id": "VrqBeY3kfKI", "caption": "This is a cinematic orchestral piece which feels victorious and announces an important moment. There is narration over the music. The instruments are violins and brass instruments. There is a rapid and light flute melody at the end.", "audio": "/zhanghaomin/datas/musiccap/music_data/VrqBeY3kfKI.wav"} +{"id": "VsMy72BoIbU", "caption": "This is a heavy metal piece from a video game soundtrack. There is a female vocalist singing melodically in the French language. The melodic background consists of the electric guitar, the keyboard and the bass guitar. In the rhythmic background there is an upbeat electronic drum sound. There is a gothic feel to the piece. This piece could work well in the soundtrack of a historical horror movie that takes place in France.", "audio": "/zhanghaomin/datas/musiccap/music_data/VsMy72BoIbU.wav"} +{"id": "VswY2mI7Wbo", "caption": "The low quality recording features a live performance of a folk, traditional song where a high pitch female vocal is singing over addictive flute melody, layered with accordion melody, followed by wooden percussive elements and simmering triangle. It sounds uplifting and cultural.", "audio": "/zhanghaomin/datas/musiccap/music_data/VswY2mI7Wbo.wav"} +{"id": "Vt3HzkNtOP4", "caption": "An acoustic drum is playing a light Rock&Roll groove with crash hits and emphasis on kick and snare along with a e-bass enhancing the fast paces mood and giving reasons to move the body along to the beat. Strings like a violin are adding some atmosphere with hits in the background and playing a crescendo to break into the next part of the song while male voices are singing together. This song may be playing when having or wanting a good mood.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vt3HzkNtOP4.wav"} +{"id": "VtHkxrta5xQ", "caption": "The song is an instrumental. The song is slow tempo with a sweeping string section harmony along with a low pitched harmony played in harmony, and howling tones played by a horn like instrument. The song is emotional with a surreal effect. The song audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/VtHkxrta5xQ.wav"} +{"id": "Vu7ZUUl4VPc", "caption": "This is a gear showcase jam recording. The only instrument being played is a clean sounding electric guitar. There is a chorus effect being applied on the guitar while it is playing mellow tunes. The atmosphere is relaxing and trippy. This track could be used in nostalgic/yearning sequences in movies and TV shows. Parts of it could also work well as an advertisement jingle. Samples from this recording could be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vu7ZUUl4VPc.wav"} +{"id": "VuWr1HXHoZg", "caption": "This is a mantra/meditation music piece. There is a male and a female vocal chanting in a devotional manner. There is a tambura melody going on in the background while certain percussive elements at higher and lower ranges can be heard in the rhythmic structure. The atmosphere is hypnotic. This piece could be used in Hindu religious events.", "audio": "/zhanghaomin/datas/musiccap/music_data/VuWr1HXHoZg.wav"} +{"id": "Vwekk3EOa-U", "caption": "The low quality recording features a smooth bass, electric guitar melody, synth pad chords and mellow piano chords playing. It sounds soft, mellow and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vwekk3EOa-U.wav"} +{"id": "VwkRHbqpHqk", "caption": "This music is an instrumental with medium tempo. Four different tracks that are completely unrelated are being played one after another. It begins with an intense violin symphony, followed by a beep and a dead phone tone, and some synthesised articulation with bass synth. The music is dissonant, chaotic, confusing and random.", "audio": "/zhanghaomin/datas/musiccap/music_data/VwkRHbqpHqk.wav"} +{"id": "Vx4aO4-nr0c", "caption": "A male vocalist sings this cheerful classic Happy Birthday song. The tempo is fast and high spirited with animated trumpets, enthusiastic, syncopated piano accompaniment, energetic congas and bongos beats, spirited drumming, tambourine beats and vocal backup. The music is loud, bustling, hyper, high-energy and a little bit syncopated. It is fun, cheerful, celebratory and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vx4aO4-nr0c.wav"} +{"id": "Vx_vqfpRdUU", "caption": "This music is a mellow instrumental. The tempo is medium with a passionate violin harmony and a simple, sharp piano melody with intense bass lines. The overall mood of the music is deep, sad, lonely, melancholic, nostalgic and poignant and yet beautiful and pleasant.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vx_vqfpRdUU.wav"} +{"id": "Vy00ycBpqpc", "caption": "First, we have a bass intro that is played on the upright bass - it lasts for around five seconds. And then we heard some women speaking in Spanish while there was the sound of a liquid splashing in the background. There is then an American man who speaks. Part of this clip was recorded live and then the narration dubbed over it.", "audio": "/zhanghaomin/datas/musiccap/music_data/Vy00ycBpqpc.wav"} +{"id": "VzFpg271sm8", "caption": "This composition is full of atmospheric sounds, machine beeping; bell/mallet sounds playing a melody with a lot of reverb. Pad/drone sounds playing a constant sound in the background. This composition may be playing in an obscure movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/VzFpg271sm8.wav"} +{"id": "VzGHr0aV220", "caption": "Instrumental music featuring dense synthesizers and bell sounds. Ethereal music with 80's style synthesis.", "audio": "/zhanghaomin/datas/musiccap/music_data/VzGHr0aV220.wav"} +{"id": "VzHL56yq8bI", "caption": "This song contains two different e-pianos playing melodies panned to the left and right side of the speakers. Two synthesizers are playing a tone that sounds like pulsating electricity and the other one a pad sound in a higher key. A e-bassline is playing together with the acoustic drum that is holding a steady groove without many changes. On top of that a male voice is singing in a higher key. This song may be playing while dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/VzHL56yq8bI.wav"} +{"id": "VzYc-c-uHjI", "caption": "A male singer sings this romantic melody. The song is slow tempo with a steady drumming rhythm, steady bass line, keyboard and guitar accompaniment. The song is romantic and emotional. The song is a Konkani wedding song and has a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/VzYc-c-uHjI.wav"} +{"id": "W-nkxlYTdV4", "caption": "This is an Indian classical duet. The tempo is slow with the ensemble of vocalists singing this melody in harmony to the rhythm of tanpura and keeping count by tapping. The song is a composition of Ragas, tala and Sruti . It is melodic, engaging, skilled, controlled and pleasing. This song is an Indian Carnatic Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/W-nkxlYTdV4.wav"} +{"id": "W00eTCOgUNs", "caption": "This country song features a female voice singing the main melody. Another female voice sings backing vocals in harmony with the main voice. This is accompanied by percussion playing a simple beat in common time. A guitar strums chords. The bass plays the root notes of the chords. After the voices pause, a guitar solo is played in a repetitive pattern. The mood of this song is romantic. Other instruments cannot be heard due to low quality of audio. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/W00eTCOgUNs.wav"} +{"id": "W0aT3SdtnfY", "caption": "An acoustic piano is playing a minor chord progression while two men are singing in the mid and higher register. They seem to be imitating cat sounds so the crowd is laughing. This is an amateur recording. This song may be playing in a comedic live performance on stage.", "audio": "/zhanghaomin/datas/musiccap/music_data/W0aT3SdtnfY.wav"} +{"id": "W2EJai-3k2w", "caption": "A female vocalist sings this passionate Rock song. The tempo is medium with infectious electric guitars on lead and harmony, tambourine beats , steady drumming and keyboard accompaniment. The song is intense, passionate, empathic, powerful, persuasive and compelling. This song is Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/W2EJai-3k2w.wav"} +{"id": "W2KaBnoGxek", "caption": "The Ambient song features wide synth pad chords, mellow piano melody and some sea waves sounds. It sounds relaxing and calming, like something you would hear in yoga sessions.", "audio": "/zhanghaomin/datas/musiccap/music_data/W2KaBnoGxek.wav"} +{"id": "W2nlA65AwtU", "caption": "The music features a synth sound playing a repeating melody. An electric piano accompanies the melody with chords. In the second half of the music except the drums and bass guitar kick in. Listening to this music I get lounge vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/W2nlA65AwtU.wav"} +{"id": "W3DwueAy65k", "caption": "This music is instrumental. The tempo is fast with incoherent music playing loudly with the sound of a vinyl record being scratched on a turntable. There are ambient sounds of people talking, hooting and cheering. This music is a DJ live in action.", "audio": "/zhanghaomin/datas/musiccap/music_data/W3DwueAy65k.wav"} +{"id": "W3lKc2hj4XU", "caption": "This song features male voices singing in harmony. It starts off on a high note, followed by a lower note and back up to a high note. At the end, a vocoder is used to give a start-stop effect to the voice. The ending of the voice is like if a person were to drive over road ramblers. There is a lot of reverb added to the voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/W3lKc2hj4XU.wav"} +{"id": "W4eLgBYEEqA", "caption": "The low quality recording features a short snippet of flat male vocal talking, while in the background an orchestral music is playing. The music contains sustained brass melody, wide huge percussion and sustained strings melody. It sounds powerful and epic.", "audio": "/zhanghaomin/datas/musiccap/music_data/W4eLgBYEEqA.wav"} +{"id": "W4nQpOHIPEw", "caption": "This song features a solo played on a pedal steel guitar. This is a country blues melody. This involves slides on the guitar. This is accompanied by percussion playing a simple beat in common time. The bass plays 12 bar blues style bassline. An organ outlines chords in the background. This is an instrumental song. There are no voices. This song can be played in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/W4nQpOHIPEw.wav"} +{"id": "W58kioYp1Ms", "caption": "The song is an instrumental. The song is medium tempo with an electric guitar playing a pleasant solo with a pedal affecting its tone. The song is a guitar effects demo. The song audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/W58kioYp1Ms.wav"} +{"id": "W5BB6pubJZI", "caption": "The song is an instrumental. The tempo is variable with two different soundtracks with snare play, sitar accompaniment, techno drumming and keyboard accompaniment. The song is a techno dance rhythm. The audio has average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/W5BB6pubJZI.wav"} +{"id": "W5eOW25vvbw", "caption": "The low quality recording features a clean arpeggiated electric guitar melody being played. The recording is noisy, in mono and it sounds muddy and boomy, as the player is probably practicing the melody or trying out the guitar amp settings.", "audio": "/zhanghaomin/datas/musiccap/music_data/W5eOW25vvbw.wav"} +{"id": "W5t-T1vP2DU", "caption": "This is a low quality audio recording. It starts with a DJ console scratching a record. This is accompanied by programmed percussion playing a repetitive melody. A berimbau plays after the scratching sound and the percussion continues to play the same beat. The berimbau plays the string as well as adds to the beat in the song. This is an instrumental song and there are no voices. This song can be played in a fashion show.", "audio": "/zhanghaomin/datas/musiccap/music_data/W5t-T1vP2DU.wav"} +{"id": "W7KbboEOmeM", "caption": "Someone is playing an e-guitar on top of another e-guitar. The guitar is full of reverb/echo. A soft drum/percussive pattern is playing along with a e-bassline. This song sounds dreamy due to the reverb and the slow melodic playing. This song may be playing in a live event.", "audio": "/zhanghaomin/datas/musiccap/music_data/W7KbboEOmeM.wav"} +{"id": "W7U-glgu4GM", "caption": "The track is an emotional love ballad that features heartfelt female vocals. Piano chords play in the background as a string section that sounds inspiring sustains chords. A drum kit plays a slow beat that adds to the romantic mood of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/W7U-glgu4GM.wav"} +{"id": "W7i4LkdSfjw", "caption": "The low quality recording features a live performance of a metal song that consists of manic drums played over aggressive electric guitar melodies and distorted bass guitar. The drums consist of a punchy double pedal kick, punchy snare hits and energetic cymbals. There are some crowd cheering sounds in the background. It sounds aggressive, and energetic overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/W7i4LkdSfjw.wav"} +{"id": "W85w938G5ZM", "caption": "A male singer sings this emotional melody. The song is medium tempo with shakers and other percussion, keyboard accompaniment and a subtle bass line. The audio quality is poor. The song is romantic and emotional.the song is probably a music video or a movie sound track.", "audio": "/zhanghaomin/datas/musiccap/music_data/W85w938G5ZM.wav"} +{"id": "W8Xv3Q2kGRA", "caption": "The low quality recording features a live performance of a traditional song and it contains wooden percussion, violin melody and flute melody. It sounds soulful, passionate and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/W8Xv3Q2kGRA.wav"} +{"id": "WAxDN-FyPn8", "caption": "This is a movie music piece. The theme is being played by an orchestra. There is a wide array of cinematic strings playing a gentle yet profound tune. The atmosphere is heart-touching. It could be used in the soundtrack of a drama movie at a scene where the characters are reminiscing the good memories they experienced with a character that has passed away.", "audio": "/zhanghaomin/datas/musiccap/music_data/WAxDN-FyPn8.wav"} +{"id": "WBBKiXYVEdM", "caption": "This song features a variety of choral voices singing different notes in harmony. This could also possibly be synth sounds programmed to have choral voices. This song can be played in a spa or meditation centre. This song is played at a slow tempo using only oohs and aahs.", "audio": "/zhanghaomin/datas/musiccap/music_data/WBBKiXYVEdM.wav"} +{"id": "WCiS9IDILQg", "caption": "This is a classical music piece. It is an instrumental piece. There is a violin playing a melancholic tune. The atmosphere is suspenseful. The quality of the recording is slightly poor. This piece could suit well during a mysterious sequence in a thriller movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/WCiS9IDILQg.wav"} +{"id": "WCifI6rwOoM", "caption": "This jazz song features the main melody played on the piano. The double bass plays jazz basslines using half note intervals and jazz fills. The percussion plays a complicated jazz rhythm mostly focusing on the snare hits. Another percussion is played using sticks sounding like a congo. A male voice speaks some meaningless phrase. This song can be played in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/WCifI6rwOoM.wav"} +{"id": "WCl93HBuj60", "caption": "This music is instrumental. The tempo is fast with lively percussion rhythms of the drums, cymbal riffs, congas, bongos, steel pan and piano accompaniment. The music is lively, spirited, engaging, funky, groovy and buoyant. This music is a percussive instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/WCl93HBuj60.wav"} +{"id": "WE0JqjuhaQI", "caption": "The low quality recording features a passionate female vocalist singing over dissonant brass stabs, groovy bass, wooden snare hits, synth pad chords, punchy kicks and shimmering hi-hats. It sounds groovy and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/WE0JqjuhaQI.wav"} +{"id": "WEVBqGarEIY", "caption": "Middle eastern or south Asian jazz influenced music of a male singer singing a free melody, accompanied by syncopated upright bass, shaker, steady drums. There is also a synthesizer pad and a rhythmic keyboard playing.", "audio": "/zhanghaomin/datas/musiccap/music_data/WEVBqGarEIY.wav"} +{"id": "WEXJSNm_T0o", "caption": "This audio contains a female choir singing a melody in harmony and acapella. Rising and falling in dynamics. This song may be playing live as a performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/WEXJSNm_T0o.wav"} +{"id": "WFPGA_BYkKU", "caption": "This song is an instrumental. The tempo is slow with the music starting with the sound of blasts,sinister melody of chimes , muddled sounds,sound of water or bubbles, and synthesised arrangements with beeps at the end of this clip.It is animated, sinister, chaotic with discordant music.", "audio": "/zhanghaomin/datas/musiccap/music_data/WFPGA_BYkKU.wav"} +{"id": "WI2d5vDJeLo", "caption": "Solo electric bass playing a scale passage in free time with a male singer singing along in unison two octaves up.", "audio": "/zhanghaomin/datas/musiccap/music_data/WI2d5vDJeLo.wav"} +{"id": "WIVu5PapmX4", "caption": "This is the sound of a certain frequency. It has a resonant, vibrational character. It is a medium range frequency.", "audio": "/zhanghaomin/datas/musiccap/music_data/WIVu5PapmX4.wav"} +{"id": "WIuLaxWIAAI", "caption": "This is the recording of a drum solo performance. The drummer is performing various complex beats and chops with a rapid procession on an acoustic drum kit. There is a tambourine placed on the snare drum that rattles with every stroke. The atmosphere of the solo is energetic. Parts of this solo could be sampled to be used as intro jingles for music channels. These samples could also be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/WIuLaxWIAAI.wav"} +{"id": "WJIrkvEq4EI", "caption": "The low quality recording features wide scratching effects of an uptempo hip hop song that contains repetitive male vocal, wooden percussive elements, siren sound effect and energetic drums. It sounds energetic, muffled and a bit harsh due to loud scratchings.", "audio": "/zhanghaomin/datas/musiccap/music_data/WJIrkvEq4EI.wav"} +{"id": "WJORWlj6BW8", "caption": "This clip features a low quality recording of a song played using a steel pan. There are no voices in this song. Other percussion instruments are played to emulate shakers and kick drums. The mood of this song is uplifting and happy. The song has a Caribbean influence. This is a song that can be played at a party.", "audio": "/zhanghaomin/datas/musiccap/music_data/WJORWlj6BW8.wav"} +{"id": "WK-gdfCurCg", "caption": "This music is a Jazz instrumental. The tempo is medium with a groovy bass one, smooth harmony on acoustic guitar and rim shots.The music is smooth, lively, informal, chill, ambient and atmospheric with the sound of musicians talking to each other.", "audio": "/zhanghaomin/datas/musiccap/music_data/WK-gdfCurCg.wav"} +{"id": "WKL40jfQD3g", "caption": "This composition contains a horn playing a melody with reverb on it. Then a string section comes in playing a soothing melody rising and falling in pitch. You can hear some digital clicking sounds that seem not to belong to the musical composition. This song may be playing in a fantasy adventure video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/WKL40jfQD3g.wav"} +{"id": "WKYUiLace9Y", "caption": "This dance song features a female voice singing the main melody. A delay effect is added to the voice which allows the last word to echo a few times. This is accompanied by programmed percussion playing a kick driven beat. A warbling sound is played in the background. A synth plays a leading riff in the foreground. This song is upbeat and can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/WKYUiLace9Y.wav"} +{"id": "WMtztIW1f6k", "caption": "A group of Arabic folk musicians play this poignant folk music . The song is medium tempo with percussion instruments playing a steady rhythm, a stringed instrument like violin plays a solo accompanied by other string instruments playing rhythm. The song is poignant and melancholic. The song is a traditional Arabic folk dance song.", "audio": "/zhanghaomin/datas/musiccap/music_data/WMtztIW1f6k.wav"} +{"id": "WNmAlKrAPjQ", "caption": "This music is instrumental. The tempo is slow with an emphatic violin harmony, keyboard accompaniment and rhythmic acoustic guitar with female vocalisation. The song is romantic, sentimental, emotional, nostalgic, poignant, charming, dreamy and soft.", "audio": "/zhanghaomin/datas/musiccap/music_data/WNmAlKrAPjQ.wav"} +{"id": "WNv-YNn1cZ8", "caption": "The low quality recording features a pop song that consists of an echoing electric guitar melody, followed by really bad samples of knocking and door opening sound effects. At the end of the loop the synth keys and smooth synth bass appear. It sounds like an intro section of a song.", "audio": "/zhanghaomin/datas/musiccap/music_data/WNv-YNn1cZ8.wav"} +{"id": "WO_Y7djT2k4", "caption": "A drum is playing a groove and sounds like running through a low pass filter opening up. Synthesizer pads are playing a simple melody that gets repeated in the lower register with overtones. Panned to both sides of the speaker a simple melody is playing pulsating synth sounds. A male voice is singing/streaming/rapping. The voice seems to be pitched down and processed with other effects. This song may be playing in a scary videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/WO_Y7djT2k4.wav"} +{"id": "WPguqXCBQCI", "caption": "The ska music features a male voice singing and being accompanied by another male backing vocal. The tempo is medium-fast, specific to the ska genre. The drums play a somewhat busy rhythm and the bass guitar plays a simple repeating bass line. In the background a piano accompanies the singer. Towards the end of the music excerpt a saxophone can be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/WPguqXCBQCI.wav"} +{"id": "WQsuFvw43RA", "caption": "The low quality recording features an ambient song that consists of a mellow piano melody, short plucked melody and wide synth pad. It sounds calming and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/WQsuFvw43RA.wav"} +{"id": "WRZGYDh7qRo", "caption": "This gothic rock song features a male voice singing the main melody. The melody is repetitive for each line. This is accompanied by percussion playing a simple rock beat in common time. A distortion guitar plays power chords. A synth plays a high pitched repetitive melody. This song has a suspenseful feel. This song can be played in a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/WRZGYDh7qRo.wav"} +{"id": "WSMdqFEjGXE", "caption": "This is a live performance of a classical music piece from the impressionist school. It is being performed by a string quartet of two violins, one viola and one cello. The quartet is playing a dramatic tune. The atmosphere is gloomy. This piece could be used in the soundtrack of a drama movie during tragic scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/WSMdqFEjGXE.wav"} +{"id": "WSaCGNkM6_k", "caption": "A female vocalist sings this sweet melody. It is medium tempo with rhythmic accompaniment of acoustic guitar, mandolin, resonator, dobro, banjo, cello, fiddle and auto harp. The song is soft, soothing, pleasant, dulcet, sentimental, emotional and simple. This song is Country Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/WSaCGNkM6_k.wav"} +{"id": "WT2iyJmKkc8", "caption": "The song is an instrumental followed by the DJ talking about his lessons. The tempo is medium with disc scratching, steady drumming rhythm, various clapping percussion, modulated vocal samples, and a percussive bass line. The song is an electronic dance tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/WT2iyJmKkc8.wav"} +{"id": "WTVC7ZI9WtY", "caption": "The low quality recording features a live performance of a pop rock song and it consists of flat male vocals counting down over addictive synth melody, energetic drums and groovy bass guitar. There are loud crowd screams in the background. It sounds distorted, loud and crushed, as it was probably recorded with a phone, but it is still energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/WTVC7ZI9WtY.wav"} +{"id": "WT_wvvEvkw4", "caption": "This is an outro for a kids song. The song features quirky male vocals. Right after the end of the phrase, thunderstorm sounds start to play in the background as well as ocean SFX.", "audio": "/zhanghaomin/datas/musiccap/music_data/WT_wvvEvkw4.wav"} +{"id": "WW4_c2J79QA", "caption": "Someone is strumming a melody on a banjo. This is an amateur recording. This song may be playing while singing to your partner at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/WW4_c2J79QA.wav"} +{"id": "WWIT13tTW7c", "caption": "This is a live performance of classical music with clear tango influences. The piece is being performed by four different ranges of saxophone: alto, baritone, tenor and soprano. The variety of range using similar characteristics of sound gives the piece a vibrant atmosphere. This piece could be used in the soundtrack of a movie that is about a culture clash situation between North American and Latin American characters.", "audio": "/zhanghaomin/datas/musiccap/music_data/WWIT13tTW7c.wav"} +{"id": "WY73T0xaY0A", "caption": "The low quality recording features a distant, mellow piano chord progression and sustained woodwind melody, Even though the recording is noisy and it has some chair squeaking sounds, it still gives off dark, haunting and hypnotic vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/WY73T0xaY0A.wav"} +{"id": "WYbD9YUrf_4", "caption": "The low quality recording features a bagpipes melody played while soldiers are marching. The recording is noisy, in mono and it sounds prideful, soulful and powerful.", "audio": "/zhanghaomin/datas/musiccap/music_data/WYbD9YUrf_4.wav"} +{"id": "WYxXUBP_XaM", "caption": "The low quality recording features an aggressive harmonica solo playing over a shimmering shaker. There is a low microphone pop sound right before the shimmering shaker comes in. It sounds passionate and energetic. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/WYxXUBP_XaM.wav"} +{"id": "WZd2nT2Afds", "caption": "The low quality recording features a flat female vocal talking over loud bells, reverberant male vocal talking, water leaking sounds and choir singing. It sounds like a compilation of sounds. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/WZd2nT2Afds.wav"} +{"id": "W_979HkE4EI", "caption": "This is a drum lesson recording. A double stroke roll pattern is being performed on the snare drum of an acoustic drum kit. A metronome click can be heard in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/W_979HkE4EI.wav"} +{"id": "W_MZo88gzrA", "caption": "The low quality recording features a live performance of a pop song that consists of passionate female vocals, alongside background harmonizing vocals, singing over energetic drums, groovy, thin bass, mellow synth pad and addictive synth lead melody. Even though the recording is noisy and in mono, it sounds energetic, happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/W_MZo88gzrA.wav"} +{"id": "W_zgEkvp4xU", "caption": "This is an Afropop music piece. There is a female vocalist singing melodically. The main tune is being played by the keyboard while the bass guitar is playing in the background. The rhythmic background consists of a slightly slow tempo acoustic drum beat and afro percussive elements. The atmosphere is vibrant and sentimental. This piece can be used as the soundtrack of a drama movie that takes place in Africa.", "audio": "/zhanghaomin/datas/musiccap/music_data/W_zgEkvp4xU.wav"} +{"id": "WaddbqEQ1NE", "caption": "The music features male and female voices singing the same melody in unison. An electric guitar accompanies the singers with strummed chords. The bass guitar and drums drive the pulse of the music forward. At one point a glockenspiel can be heard playing three notes. The overall atmosphere is happy and uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/WaddbqEQ1NE.wav"} +{"id": "WcC9sKxJ1gI", "caption": "This is a clip featuring a motif from an instrument that sounds a little like a theremin whistle. There is a fuzzy quality to the instrument as well. This song feels like an eighties pop style song.", "audio": "/zhanghaomin/datas/musiccap/music_data/WcC9sKxJ1gI.wav"} +{"id": "Wd4T3iTsgrI", "caption": "The low quality recording features a harmonizing french horn melody. It sounds passionate and easygoing, while the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wd4T3iTsgrI.wav"} +{"id": "Wd5l_FHGWfE", "caption": "Someone is playing an acoustic piano repeating a phrase of a chord with single notes in the mid-range while a voice-like synthesizer sound is being played in a higher register. The instrument does sound like a female opera singer with a lot of vibrato. This song may be playing in a theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wd5l_FHGWfE.wav"} +{"id": "WditOomsdRU", "caption": "This is a soothing folk pop piece. We hear a violin and a harp as the leading melodic instruments, and the cello and piano as backing. The song is airy and the vocalist has a light and ethereal voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/WditOomsdRU.wav"} +{"id": "Wdl7A3de0L4", "caption": "This song contains someone playing a ukulele fingerstly. This song may be playing live sitting around a bonfire with friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wdl7A3de0L4.wav"} +{"id": "Wdtku1dqJo0", "caption": "The low quality recording features a live performance of a ballad song that consists of sustained strings, soft crash cymbals and soft piano melody. At the very end of the loop, there are passionate muddy female vocals. It sounds passionate, emotional and heartfelt, while it is a bit noisy too.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wdtku1dqJo0.wav"} +{"id": "WdxNikVdK-U", "caption": "This is an Indian traditional music piece performed live by an orchestra. The orchestra is composed of the bansuri, the sitars and the tabla percussion. There is a vibrant atmosphere in the recording. This piece could be used in the soundtrack of a Bollywood movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/WdxNikVdK-U.wav"} +{"id": "We-bFXFjWaM", "caption": "The low quality recording features a percussive shoe tapping over hip hop beat playing in the background. The beat consists of shimmering shakers, hard 808 bass and punchy snare. At one point the shoe tapper gets a little bit sloppy. It sounds a bit muffled, boomy and reverberant.", "audio": "/zhanghaomin/datas/musiccap/music_data/We-bFXFjWaM.wav"} +{"id": "We0WIPYrtRE", "caption": "This composition contains a deep male voice singing a drone sound in a low key and with other male voices singing a mantra on top in the midrange. A gong/bow-hit is played once. The whole recording is full of reverb. This song may be playing while meditating in a temple.", "audio": "/zhanghaomin/datas/musiccap/music_data/We0WIPYrtRE.wav"} +{"id": "We9P_UcHNk8", "caption": "The low quality recording features a cover of an alternative/indie song that consists of acoustic guitar melody. It sounds groovy and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/We9P_UcHNk8.wav"} +{"id": "WeDA1mDFSCo", "caption": "This country rock song features a male voice singing at a high pitch. This is accompanied by percussion playing a simple beat. A guitar strums chords. The bass guitar plays the root notes of the chords. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/WeDA1mDFSCo.wav"} +{"id": "Weu8nsJRMqE", "caption": "This song is an instrumental. The tempo is medium with an acoustic guitar playing a monotone. There is no melody or instrumentation . It sounds like a guitar being tuned. It is repetitive, and insistent like a chant.", "audio": "/zhanghaomin/datas/musiccap/music_data/Weu8nsJRMqE.wav"} +{"id": "WgZ8KAnnTb8", "caption": "The low quality recording features a compilation that, in the first half, contains muffled hip hop song and in the second half sad, soft rock song. The rock song contains an arpeggiated acoustic guitar melody located in the right channel of the stereo image - which makes it unbalanced, and reverberant soft male vocal singing over it. It sounds emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/WgZ8KAnnTb8.wav"} +{"id": "Wgf7UYPVoAo", "caption": "Someone is playing an acoustic guitar with flamenco techniques and melodies. In the background you can hear someone playing shakers. This recording contains a little bit of reverb on the instruments. This song may be playing as a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wgf7UYPVoAo.wav"} +{"id": "Wh5JSj89tW8", "caption": "Amateur recording of solo acoustic guitar strumming. Tape hiss, room reverb and unintentional mic clipping is audible throughout.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wh5JSj89tW8.wav"} +{"id": "WhEd8h7J0Lk", "caption": "This song has a heavily synthesised voice singing a rhythmic melody. The tempo is medium fast with synthesiser arrangements, punchy drumming, groovy bass lines and electronic instrumentation, with enthusiastic vocal backup. The song is vibrant, youthful, trance-like because of the insistent, monotone, chanting nature of the melody. This song is EDM/Synth pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/WhEd8h7J0Lk.wav"} +{"id": "WhNun_U3cRU", "caption": "The sounds are background sound elements of a sci-fi tv show. There is no tempo, there are a collection of sounds like machine whirring, computer signal beeps, boomy explosion sounds, white noise, bad signal tones and glitchy noises. The music is chaotic like an alien invasion. This is background sound effects for a science fiction tv show.", "audio": "/zhanghaomin/datas/musiccap/music_data/WhNun_U3cRU.wav"} +{"id": "WhX3jQxHZWc", "caption": "This song is recorded in poor quality. Two acoustic guitars are playing. One of them is strumming chords while the other is playing a country solo up and down the fretboard. A cajon player is supported with mostly kick sounds. This song may be played at an Irish bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/WhX3jQxHZWc.wav"} +{"id": "Wh_g-Eiw9Kc", "caption": "A very young sounding kid's voice is singing along to a backing track containing acoustic drums, e-bass and a quirky sounding flute sound playing a melody to which the kid is singing along. This is an amateur recording and of poor sound-quality. This song may be playing for a talent show.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wh_g-Eiw9Kc.wav"} +{"id": "WiAFUo2nxIk", "caption": "This is a DJ performance recording of two kids scratching a turntable. The turntable is being scratched over a hip-hop breakbeat that consists of a loud electronic drum beat. The atmosphere is danceable and there is an urban sound. This piece could be played at sports venues. It could also be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/WiAFUo2nxIk.wav"} +{"id": "Wil8e6kBxe8", "caption": "This song contains a mandolin being strummed along to a clicking sound. This song may be playing in a video-tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wil8e6kBxe8.wav"} +{"id": "WjPHxUtF9go", "caption": "The low quality recording features an emotional electric guitar melody. The recording is noisy and in mono as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/WjPHxUtF9go.wav"} +{"id": "WkkhcwXpYy4", "caption": "This is a video game theme played in a music game. There is a keyboard playing the main tune. The bass guitar is playing a repetitive and simple bass line. Samples could be lifted from the piece to use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/WkkhcwXpYy4.wav"} +{"id": "WmTDKYYH5OU", "caption": "The low quality recording features a flat male vocal rapping over sustained strings melody, punchy kick, mellow snare, groovy bass and some commentary that can be heard in the background. It sounds emotional, energetic and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/WmTDKYYH5OU.wav"} +{"id": "WmyHFkyiiF8", "caption": "The Classical song features a wide mellow strings melody and soft plucked strings melody. It sounds mellow, soft, emotional and epic, like a background movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/WmyHFkyiiF8.wav"} +{"id": "WmyhSRhWh3k", "caption": "This is a big band jazz music piece. It is an accompaniment piece to the Charleston dance. The band consists of a wide range of brass sections, an upright bass, a jazz acoustic drum beat and a vibraphone. Sounds from the cheering crowd can be heard. The atmosphere is lively. The piece is upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/WmyhSRhWh3k.wav"} +{"id": "Wnl0qbVynL4", "caption": "This slow pop song features a female voice singing the main melody. The voice is tremulous and sings in a foreign language. This is accompanied by a string section playing chords and fills in harmony. The bass plays the root notes of the chords. There is no percussion in this song. The mood of this song is romantic and dreamy. This song can be played when there is a romantic flashback scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wnl0qbVynL4.wav"} +{"id": "WoWF7gGzGVY", "caption": "This is an indie/alternative music piece. There is a male vocalist singing melodically. In the background, an eastern sounding tune is playing with a bass and electronic drum beat alongside it. The atmosphere is generic and easygoing. This piece could fit well as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/WoWF7gGzGVY.wav"} +{"id": "WoXgPQQjcJU", "caption": "The low quality recording features a loud didgeridoo modulating low tone. It is in mono and it sounds buzzy and kind of weird.", "audio": "/zhanghaomin/datas/musiccap/music_data/WoXgPQQjcJU.wav"} +{"id": "Wp5AiCmbQjA", "caption": "The low quality recording features an acapella cover of a R&B song that consists of flat female vocal singing over hand tapping sounds and snaps. The recording is mono and noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wp5AiCmbQjA.wav"} +{"id": "WqC-fx3uNVE", "caption": "The song is a techno dance song sung by a male singer and backup singer harmony. The song is medium tempo with a strong bass line, keyboard harmony and steady drumming rhythm with strong bass kicks. The song is passionate and has a strong dance groove. The song is a poor recording of a modern tech pop song played for a live audience.", "audio": "/zhanghaomin/datas/musiccap/music_data/WqC-fx3uNVE.wav"} +{"id": "Wr5sFgqxLzQ", "caption": "This alternative rock song features a male voice singing the main melody. This is accompanied by percussion playing a simple beat. A shaker is played on every count. At the beginning, a scratch slide is played on the distortion guitar. The bass plays notes in groups of three on the first and second counts of each bar. A keyboard plays repetitive fills in between lines. The voice is emotive and the feel of this song is psychedelic. The audio quality is low. This song can be played in a night driving scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wr5sFgqxLzQ.wav"} +{"id": "WrpWb-Zumnc", "caption": "This is a classical music piece from a movie soundtrack. There is a brass section holding a single chord while a saxophone and then a trumpet plays a solo in the lead. The rhythmic background is provided with a crescendo movement played by a timpani. The atmosphere is dramatic. This piece can be used in the soundtrack of a drama movie during scenes of elevated tension.", "audio": "/zhanghaomin/datas/musiccap/music_data/WrpWb-Zumnc.wav"} +{"id": "WsDb16qzA5Q", "caption": "This is a mellow, groovy hip hop beat. Its distinguishing factor is a vinyl scratching technique used by DJs. It also consists of what sounds like a brass instrument and forms a chord progression along with the bass that plays at the same cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/WsDb16qzA5Q.wav"} +{"id": "WsaOJT2SsPg", "caption": "A male singer sings this spirited melody. The song is medium tempo with guitar accompaniment, telephone beep tones, steady bass line, keyboard harmony and steady drumming rhythm. The song is spirited and emotional. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/WsaOJT2SsPg.wav"} +{"id": "WtN6uiDikRM", "caption": "A semi-acoustic guitar is playing slow chords and the bassline at the same time while a female voice is singing/yodeling. A reverb effect is on her voice. In the background you can hear voices talking and clapping. This is an amateur recording but of decent sound quality. This song may be playing at a folkfest.", "audio": "/zhanghaomin/datas/musiccap/music_data/WtN6uiDikRM.wav"} +{"id": "Wu-Oh9OJIlI", "caption": "The heavy metal music features a guttural male voice. The sound is aggressive and energetic. The background has a dark tonality that contrasts the heavily distorted guitars that strum chords. An aggressive drum kit plays a common heavy metal beat in the background. This is a song you could hear at a monster truck show.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wu-Oh9OJIlI.wav"} +{"id": "Wu3LKQG1fwU", "caption": "The low quality recording features a rock song that consists of wide electric guitar melodies, groovy bass guitar, shimmering shakers, punchy snare and kick hits, followed by aggressive tom rolls. It sounds energetic and the drums are reverberant, as they were probably recorded in a medium size drum room.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wu3LKQG1fwU.wav"} +{"id": "WvEtOYCShfM", "caption": "This is an informational piece. There is a male voice narrating the details from the history of a Somali musician. In the end, we can hear briefly what the music of this musician sounded like.", "audio": "/zhanghaomin/datas/musiccap/music_data/WvEtOYCShfM.wav"} +{"id": "WvaIypMvAHY", "caption": "This is the recording of a guitar lesson video. There is a male speaking in an instructive manner, giving the name of the chord he is about to play next. The chords are being played gently on a clean sounding electric guitar. There is a mellow feel to the sound. Parts of this recording can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/WvaIypMvAHY.wav"} +{"id": "Wvg5rlMbjJc", "caption": "This is a pop punk music piece. There is a fast-paced distorted electric guitar playing the main tune. A bass guitar is supporting it in the background. The rhythm is being played by a loud acoustic drum beat. The atmosphere is rebellious and aggressive. This piece could be used in the soundtrack of a high school drama TV series, especially during scenes where acts of delinquency are committed.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wvg5rlMbjJc.wav"} +{"id": "Wvh59Y4OzUM", "caption": "This is an electronic percussion piece used in the background of a nerf shootout video. There are ominous, unnerving sound effects in the background while gunshot sounds can be heard at the forefront. The atmosphere is violent. Sounds from this track can be lifted to be used in soundboards or in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/Wvh59Y4OzUM.wav"} +{"id": "WxgolzWTmO4", "caption": "A lot of gun firing can be heard in this recording. In the background strings are playing a melody along with a piano. A male voice is making a sound like being annoyed. This is an amateur recording and the song may be more suitable for a relaxing and sad movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/WxgolzWTmO4.wav"} +{"id": "WyGJdstaxK4", "caption": "This song contains acoustic drums holding the rhythm together with a bass and almost clean e-guitar strumming chords. A piano is adding single notes on top while a male voice is singing a melody getting backed up by a female voice singing along. In the background motor race sounds can be heard. This song may be playing in a car with windows open on a road trip.", "audio": "/zhanghaomin/datas/musiccap/music_data/WyGJdstaxK4.wav"} +{"id": "WySgNm8qH-I", "caption": "The excerpt features three different songs stitched together like a collage. The first one lasts for a few seconds and features a male voice being accompanied by an acoustic guitar, drums, electric guitar and bass. The second one lasts for one second and features a male voice accompanied by drums, bass guitar and electric guitar. After a silence that lasts for a few seconds the third piece of the collage features a male voice accompanied by an acoustic guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/WySgNm8qH-I.wav"} +{"id": "X-uVubaJ3II", "caption": "A cello is picking a melody in the lower key serving as bass. Other instruments such as brass and oboes are playing melodies along with a xylophone playing the main melody. Strings in the background elevate some parts of the song. This composition sounds playful and may be playing in a magical fantasy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/X-uVubaJ3II.wav"} +{"id": "X0MN34Us6eE", "caption": "The low quality recording features a flat male vocal singing over tinny wooden percussions, punchy \"4 on the floor\" kick pattern, groovy bass, long crash cymbal, shimmering shakers, syncopated snare hits and electric guitar melody. In the first half of the loop, there is a short snippet of crowd cheering and clapping over brass melody. It sounds fun, happy and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/X0MN34Us6eE.wav"} +{"id": "X1KJfb5xhr4", "caption": "This amateur recording features trumpets playing the main melody. This is accompanied by the bass drum playing one beat on alternate counts and two beats on the remaining alternate counts. Hand claps are played on alternate counts. Other instruments are not audible due to the low audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/X1KJfb5xhr4.wav"} +{"id": "X1_RmTiDC4I", "caption": "This song sounds very meditative and calming. Containing drones, a digital choir and soothing synthesizer pads playing long notes with small changes and a lot of reverb. On top of that a harp is playing a melody. This song may be playing while meditating.", "audio": "/zhanghaomin/datas/musiccap/music_data/X1_RmTiDC4I.wav"} +{"id": "X28GWrn9LlI", "caption": "The low quality recording features a live performance that consists of a flat female vocal singing over electric rhythm guitar melody. It sounds passionate, reverberant and emotional. The recording is noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/X28GWrn9LlI.wav"} +{"id": "X2gHQb5ubco", "caption": "A female opera singer sings this climatic high pitched finish. The song is medium tempo with a string section accompaniment and a rhythm Section. The song is dramatic and high on adrenaline. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/X2gHQb5ubco.wav"} +{"id": "X6Q53uXgaHc", "caption": "This is an instrumental track featuring the double bass and acoustic guitar. Initially, chords are strummed on the acoustic guitar, and then arpeggio notes are played. The double bass is played with a bow and plays the leading melodic motif in the song. The song feels like it would be suitable in an adventure movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/X6Q53uXgaHc.wav"} +{"id": "X7LrhZX4rdU", "caption": "The Techno track features a punchy \"4 on the floor\" kick pattern, punchy snare, groovy bass, alongside echoing synth keys, short haunting synth lead and weird percussive sound effects. It is groovy and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/X7LrhZX4rdU.wav"} +{"id": "X7qFgrAl3OU", "caption": "A male vocalist sings this spirited song. The tempo is fast with electronic instrumentation, synthesiser articulation and turn table. The song is spirited,youthful , enthusiastic, energetic, vigorous and vital. This song is an EDM/ Synth Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/X7qFgrAl3OU.wav"} +{"id": "X96v9LlsjJM", "caption": "The low quality recording features a wide crowd sound effects that include loud clapping, whistling and cheering, while the orchestra is playing in the background. It sounds reverberant and like it was recorded with a better quality phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/X96v9LlsjJM.wav"} +{"id": "X9H8FzpVL8s", "caption": "This audio contains someone playing an e-guitar using a vibrato and chorus effect. This is an amateur recording. This song may be playing guitar at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/X9H8FzpVL8s.wav"} +{"id": "XCQMJXkI5bA", "caption": "A male vocalist sings this upbeat song in a foreign language. The tempo is medium fast with a very perky and bouncy beat. The song is happy, cheerful, groovy, simple light and catchy with middle eastern music influences. This song is a contemporary Folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/XCQMJXkI5bA.wav"} +{"id": "XDBxMQrRaFY", "caption": "This song is an instrumental. It is slow tempo with only an Electric guitar harmony. The music is emphatic, loud , clear and pleasant. This is instrumental soft rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/XDBxMQrRaFY.wav"} +{"id": "XE4NRSDLYG8", "caption": "The song is an instrumental. The tempo is slow with a piano accompaniment and a strong bass line, with people clapping , whistling, and cheering. The song is being played at a live arena with people getting excited to the song introduction.", "audio": "/zhanghaomin/datas/musiccap/music_data/XE4NRSDLYG8.wav"} +{"id": "XEIP1OUXU8E", "caption": "This music is a sinister Electronic instrumental. The tempo is medium with a claviharp melody and keyboard accompaniment with digital sounds and a menacing roar and grunt. The music is intense, sinister, scary, anticipating danger, menacing, mysterious and suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/XEIP1OUXU8E.wav"} +{"id": "XFuw-m2gYOQ", "caption": "Someone is playing a metal riff on a fully distorted and overdriven e-guitar. This is an amateur recording. This song may be playing while practicing with the band.", "audio": "/zhanghaomin/datas/musiccap/music_data/XFuw-m2gYOQ.wav"} +{"id": "XHczpbtBhk4", "caption": "This is a recording of a live show performance by a rock band. We hear some cheering fans and then the song starts with an electric guitar lick and a bass guitar, and a kick on the drums. The audio quality is muffled and poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/XHczpbtBhk4.wav"} +{"id": "XI-tRuDZ6HA", "caption": "The low quality recording features an alternative/indie song that consists of a passionate male vocal singing over groovy bass guitar, wide electric guitar melodies, shimmering cymbals and \"4 on the floor\" kick pattern. It sounds mellow, easygoing, emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/XI-tRuDZ6HA.wav"} +{"id": "XI9CNsX6JSE", "caption": "The low quality recording features an electro song being played in a club and it consists of high pitched, repetitive, female vocals singing over groovy bass, punchy snare hits and shimmering hi hats. It sounds upbeat and energetic, even though the sound is muffled, noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/XI9CNsX6JSE.wav"} +{"id": "XILyHZyyCik", "caption": "The low quality recording features a live performance of a pop song that consists of flat male vocal talking, passionate female vocal, alongside harmonizing wide female vocals, singing over punchy kick and snare hits, shimmering hi hats and groovy bass. There are crowd singing and cheering sounds in the background. It sounds groovy, emotional, energetic and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/XILyHZyyCik.wav"} +{"id": "XJ3VlCAIWQ0", "caption": "The instrumental music features a repetitive melody played by a not so sophisticated electronic sound. The accompaniment consists of electronic sounds of the same quality. The music is most likely background music for an early video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/XJ3VlCAIWQ0.wav"} +{"id": "XJXn88r9ys8", "caption": "The low quality recording features a cover of a rock song that consists of flat male vocal singing over distorted electric guitar melody, energetic drums and groovy bass guitar. The song sounds passionate and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/XJXn88r9ys8.wav"} +{"id": "XKp670Yh0E0", "caption": "This is the opening of a reggae song played live during a performance. There is a saxophone playing a solo as the lead. An electric guitar and a bass guitar play the tune in the background. The acoustic drums follow a basic, repetitive reggae beat. The song could be played at a bar or a coffee house.", "audio": "/zhanghaomin/datas/musiccap/music_data/XKp670Yh0E0.wav"} +{"id": "XM4hxyK-Ddo", "caption": "This is a symphonic orchestra playing a piece that's riveting, thrilling and exciting. The peace would be suitable in a movie when something grand and impressive happens. There are clarinets, tubas, trumpets and french horns being played. The brass instruments help create that sense of a momentous occasion. The percussion is done on timpanis and a cymbal.", "audio": "/zhanghaomin/datas/musiccap/music_data/XM4hxyK-Ddo.wav"} +{"id": "XNlFs7Yjauk", "caption": "This slow pop song features a male voice singing the main melody. This song starts with a melody played on synth strings. This is accompanied by percussion playing a simple beat. The bass plays the root notes of the chords with a run to reach the next note. There are different synth layers playing different melodies within the scale to produce a complex melody. The voice starts to sing a romantic melody. This is accompanied by the percussion playing a minimalistic beat. The synth pads play a sustained chord in the background. The bass note is sustained through the line being sung. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/XNlFs7Yjauk.wav"} +{"id": "XOLVI1bgxqk", "caption": "Someone is strumming a melody on a clean e-guitar. This may be playing for an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/XOLVI1bgxqk.wav"} +{"id": "XOsHEjo-RSg", "caption": "This is a Mexican folk music piece being performed live. There is male voice shouting at the end of the piece. The accordion is playing the main melody. The acoustic guitar and the bass guitar are playing in the background. The rhythmic background consists of a latin acoustic drum beat. The atmosphere is lively. This piece could be playing in the background at a Mexican restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/XOsHEjo-RSg.wav"} +{"id": "XPGtOugQ69U", "caption": "This techno song starts off with a synth playing a melody followed by another synth playing a burst of two chords. The two chord bursts are accompanied by percussion playing an outro roll. The instruments pause and a male voice starts to narrate a few lines. After two lines, the pitch of the voice is lowered in pitch to reach a bass pitch. This voice fades away to silence. This song can be played in a movie featuring a robot.", "audio": "/zhanghaomin/datas/musiccap/music_data/XPGtOugQ69U.wav"} +{"id": "XQB27QPic3k", "caption": "This is a gear showcase jam recording. There is an electric guitar playing a calm solo with the echo effect. The tune being played is a simple one and it is rather relaxed. This recording can be used to lift guitar samples with echo effect. It can also be used in advertisement jingles.", "audio": "/zhanghaomin/datas/musiccap/music_data/XQB27QPic3k.wav"} +{"id": "XRQyoAk-Qz0", "caption": "This epic song features a pulsating synth playing in eighth notes in the background. The clip starts with a crash cymbal being struck. A flute plays a melody and an angelic voice sings the same melody using vocables. A bass drum alternates between one stroke and two strokes played at alternate counts of each bar. This song has an epic feel. The mood is motivational. This song can be played in a slow motion clip of an athlete winning a race.", "audio": "/zhanghaomin/datas/musiccap/music_data/XRQyoAk-Qz0.wav"} +{"id": "XS-3djsJWTA", "caption": "This music is an acoustic guitar instrumental. The tempo is medium with the guitarist playing a dulcet harmony on an acoustic guitar. The music is calming,soothing, melodic, eloquent, moving and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/XS-3djsJWTA.wav"} +{"id": "XUD-9HkQuTE", "caption": "A female singer sings this soulful song. The song is slow tempo with piano accompaniment, strong bass line and groovy jazz drumming. The song is soulful and emotional. The song is a blues jazz song.", "audio": "/zhanghaomin/datas/musiccap/music_data/XUD-9HkQuTE.wav"} +{"id": "XUzaEsoOlWQ", "caption": "Dramatic female opera singer accompanied by orchestra and brass and cymbal crash.", "audio": "/zhanghaomin/datas/musiccap/music_data/XUzaEsoOlWQ.wav"} +{"id": "XW6tS4zAZ5E", "caption": "This audio contains trumpets playing the main melody in the higher mid range while oboes and flutes are playing a melody that sounds like a bunny hopping over obstacles. Then the music stops with a crashing sound and an alarm clock starts ringing. This song may be playing live as part of an orchestra composition.", "audio": "/zhanghaomin/datas/musiccap/music_data/XW6tS4zAZ5E.wav"} +{"id": "XWVGQbfpA0k", "caption": "This is a guitar cover video. There are no vocals in this piece. The acoustic guitar is playing a mellow tune with the heavy use of arpeggios. The atmosphere is gentle and relaxing. This piece could be used as the opening theme of a teenage drama TV series. It could also be playing in the background at a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/XWVGQbfpA0k.wav"} +{"id": "XWhmLbnrtd0", "caption": "The low quality recording features a cover of a pop song and it consists of harmonizing male vocals and loud shoe tapping that serves as a rhythm. The recording is in mono and very noisy, as it was probably recorded with a phone. It sounds passionate and energetic - even without the instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/XWhmLbnrtd0.wav"} +{"id": "XWj7nP7kfdQ", "caption": "This opera song features a female voice singing at a high pitch. This is accompanied by a shimmering background sound for one bar. This is followed by the sound of wind. This song has a victorious mood. This song can be played at the end of a war scene for the victor of the war.", "audio": "/zhanghaomin/datas/musiccap/music_data/XWj7nP7kfdQ.wav"} +{"id": "XXBVsNt2Qr8", "caption": "A female singer sings this passionate melody. The song is medium tempo with steady drumming rhythm, groovy bass line, Caribbean percussion, guitar accompaniment and a brass band playing percussively. The song is emotional and spirited. The song is a classic renege hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/XXBVsNt2Qr8.wav"} +{"id": "XXdPZMsrBd4", "caption": "The Techno song features a repetitive synth bass, repetitive, distorted synth cowbell percussion and punchy \"4 on the floor\" kick patter. It sounds energetic and addictive, almost hypnotic - like something you would hear in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/XXdPZMsrBd4.wav"} +{"id": "XYOnq7ju7o0", "caption": "This is a live DJ performance. There is a groovy bass line and a mellow electronic drum beat in the rhythmic background accompanied by the tune of a melodic guitar sample. The turntable is used to make a scratching sound over this track. There is an urban feeling to this piece. It could be used in the soundtrack of a crime movie/TV show taking place in the big city. It could be used in the background of an interesting sports video.", "audio": "/zhanghaomin/datas/musiccap/music_data/XYOnq7ju7o0.wav"} +{"id": "XYQnMxWnetY", "caption": "The pianist plays a classical piano piece which brings out a feeling of suspense and tension. The piece is complex and rapid. It has the sense of building up due to the low rumbling of the bass notes. The recording is a low-quality recording, and it is live.", "audio": "/zhanghaomin/datas/musiccap/music_data/XYQnMxWnetY.wav"} +{"id": "XZurp_Ex9No", "caption": "This music is an electronic instrumental. The tempo is medium fast with synthesiser arrangements, digital drumming and an insistent, persistent ,and incessant electronic drone sound that over powers the background music. It is loud, sharp and unpleasant after a bit.", "audio": "/zhanghaomin/datas/musiccap/music_data/XZurp_Ex9No.wav"} +{"id": "X_nfMNpw9SA", "caption": "An acoustic guitar being played walking down the fretboard using a tremolo finger picking technique. This song may be playing at home practicing guitar. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/X_nfMNpw9SA.wav"} +{"id": "XaUXJG0BZuk", "caption": "This music is a country song instrumental. The tempo is slow with a mellifluous Auto Harp harmony, steady drumming, rhythmic acoustic guitar, and subtle bass lines. The music is melodic, soothing, peaceful, nostalgic,mellow and dulcet Country Song Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/XaUXJG0BZuk.wav"} +{"id": "XalMIYYgHt0", "caption": "This song contains an acoustic piano playing a jazzy melody and chords along to a very light acoustic drum playing with brushes. An upright bass is playing its own line. On top of that a female voice is singing in a higher key and with a little reverb on her voice. This song may be playing at a jazz festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/XalMIYYgHt0.wav"} +{"id": "Xaq-segSEsQ", "caption": "A male vocalist sings this energetic Nigerian song. The tempo is fast and upbeat with keyboard harmony and Afro beats of conga, clave, drums and akuba. The music is upbeat, catchy, spirited, energetic, youthful and pulsating with a dance groove. This song is a Reggae song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xaq-segSEsQ.wav"} +{"id": "XaqVAF-ADWU", "caption": "This song is a vocal duet of male singers in a foreign language . The tempo is medium fast with an animated electric guitar melody, boomy bass drops, digital drums and synthesiser arrangements. The music is buoyant, youthful,punchy, groovy and emphatic with mellow vocals. This song is contemporary Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/XaqVAF-ADWU.wav"} +{"id": "XcvY-NdM8WA", "caption": "This song is an instrumental. The tempo is fast with boomy bass lines, slick drumming, digital drum rhythm; keyboard harmony, synthesiser arrangements and sound of a woman laughing. The song is electric, vibrant ,youthful ,psychedelic, trippy, hysterical and buoyant with a dance groove. This song is an EDM/Synth pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/XcvY-NdM8WA.wav"} +{"id": "XdBf_omYIO4", "caption": "This folk song features a harmonica playing the main melody. The harmonica plays three descending notes. This is followed by a double stop being played a total of nine times in groupings of two, three, three and one time. Then it plays a higher note going down a descending scale of two more notes. This is accompanied by an acoustic guitar strumming chords. The mood of this song is sad. This song can be played at a house party.", "audio": "/zhanghaomin/datas/musiccap/music_data/XdBf_omYIO4.wav"} +{"id": "XdxTZ4-sJvY", "caption": "This heavy metal song features a distortion guitar playing palm muted power chords using mostly down strokes. The bass plays the root note of the chord using the same rhythm pattern. The percussion plays the hi-hat in a continuous pattern and the kick on the first count of the bar. On the third bar, the distortion guitar plays one chord without palm muting. This song can be played at the introduction of a video game. This song has no voices. This is an instrumental song. The mood of this song is aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/XdxTZ4-sJvY.wav"} +{"id": "Xe59DpKa-O4", "caption": "This is a hardcore techno music piece. There is an extremely strong, ear-piercing bass sound. The rhythmic background is a fast-paced and loud electronic drum beat. The atmosphere is violent. This piece could be played at rave sets.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xe59DpKa-O4.wav"} +{"id": "Xf0aZ3a3Toc", "caption": "ambient space sounds that are a cold and desolate feeling. Metallic screeching, whooshing distant bells ringing, lots of reverb and a long synthesizer filter sweep. Good for a science fiction film.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xf0aZ3a3Toc.wav"} +{"id": "XfLI8gHCuFE", "caption": "This is a techno house music piece. There is a piercing sounding synth lead playing an alarm-like tune. The atmosphere is loud and aggressive. This piece could be playing during nighttime scenes in the soundtrack of a noir movie or a noir video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/XfLI8gHCuFE.wav"} +{"id": "XfLIbeSJSHE", "caption": "This is the sound of a wooden drawer being opened and a bunch of nails dropped on a surface. A very faint pop music can be heard with a melodically singing female vocal, strings and a simple electronic drum beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/XfLIbeSJSHE.wav"} +{"id": "XfdySM4X9Xo", "caption": "The song is an instrumental. The tempo is medium with a strong rock drumming rhythm, groovy bass slime, electric guitars playing lead and guitar harmony. The song is exciting, youthful and emotional. The song is a classic rock instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/XfdySM4X9Xo.wav"} +{"id": "XgLUXNAC7b8", "caption": "This is an electronic music piece. There is a repeated piano theme in the melody. There are various eerie sound effects. Then, a violin starts playing. The atmosphere is unsettling. This piece would fit well in the soundtrack of a mystery video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/XgLUXNAC7b8.wav"} +{"id": "XgOA5oRkL2A", "caption": "This clip is a percussion instrumental with vocalisation. The tempo is medium with the sound of steady,rhythmic drumming And tambourine beats and a male singer vocalising.The music is minimal with no other instruments used. It is rhythmic, chanting, monotone,insistent and recurring. This is a home recording with bustling sounds in the background, horns hooting, vehicles passing by, people talking.", "audio": "/zhanghaomin/datas/musiccap/music_data/XgOA5oRkL2A.wav"} +{"id": "XgXOW3lX25Y", "caption": "This hard rock song features a distortion guitar playing aggressive riffs. This is accompanied by a rock percussion playing a simple rock beat with a roll at the end. The bass guitar plays the root notes of the chord with a flourish to move to the subsequent note. There are no voices in this song. This is an instrumental song.", "audio": "/zhanghaomin/datas/musiccap/music_data/XgXOW3lX25Y.wav"} +{"id": "XhV4zf-Xlmk", "caption": "A male voice is singing in the midrange then another male voice joins singing in a lower harmony. In the background you can hear a jazz drum playing along with an upright bass and a flute. An acoustic piano is playing jazzy licks. Then the drum breaks the beat with strong fill-ins before a brass section elevates the piece. This song may be playing live during a jazz performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/XhV4zf-Xlmk.wav"} +{"id": "Ximk6BHj9nE", "caption": "This recording features a baptist church choir singing a worship song vibrantly. The song is energetic and uplifting. It's a live recording with unclear audio which makes it difficult to hear the song lyrics. There's an organ, drums, tambourine and bass.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ximk6BHj9nE.wav"} +{"id": "XjGm3Bn4j5k", "caption": "The low quality recording features a live performance of a metal song. The recording is noisy, in mono and so crushed, distorted, harsh and loud that you can barely hear anything but the loud noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/XjGm3Bn4j5k.wav"} +{"id": "XjUmXwVlDDo", "caption": "The low quality recording features a fruity male vocal, alongside processed background male vocal, with autotune and echoing effect on, rapping over repetitive synth melody, groovy synth bass, punchy kick and punchy snare hits. The song is uptempo and it sounds energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/XjUmXwVlDDo.wav"} +{"id": "XjoRxeEyjz4", "caption": "This song is an instrumental. The tempo is fast with electronic instrumentation and sounds. There is a vigorous keyboard harmony along with sounds of gunshots, clicking, whirring, beeping, phone ring and scratching. The music is busy, animated and boisterous. The audio quality is inferior and muddled, making it difficult to hear the finer elements.", "audio": "/zhanghaomin/datas/musiccap/music_data/XjoRxeEyjz4.wav"} +{"id": "XjrVSk0_4vc", "caption": "This song contains a digital/acoustic drum holding a simple groove with an e-bass while two distorted e-guitars are playing a melody with one being the lead. A male voice is singing in a higher register while you can hear hand clapping to the rhythm. This is an amateur recording and in poor audio-quality. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/XjrVSk0_4vc.wav"} +{"id": "XkBXsaSXDJ0", "caption": "The Pop song features a passionate male vocal, alongside widely spread harmonizing mixed vocals, singing over groovy piano chord progression, funky electric guitar melody, groovy bass guitar, shimmering hi hats, punchy kick and punchy snare. It sounds emotional, addictive and euphoric - like a Christmas song.", "audio": "/zhanghaomin/datas/musiccap/music_data/XkBXsaSXDJ0.wav"} +{"id": "Xl4RSHQsnl8", "caption": "The low quality recording features a live performance of a pop song that contains a reverberant soft male vocal singing over mellow piano chords. There are crowd singing noises in the background. It sounds soulful, passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xl4RSHQsnl8.wav"} +{"id": "Xm2ciX0_UP8", "caption": "The low quality recording features an alternative/indie song that consists of arpeggiated synth keys, growl synth bass, mellow synth bells melody and synth pad chords. It sounds chill and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xm2ciX0_UP8.wav"} +{"id": "XmMN-6g1L8w", "caption": "This is a live performance of a classical music piece. There is an orchestra performing the piece with a violin lead playing the main melody. The atmosphere is sentimental and heart-touching. This piece could be playing in the background at a classy restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/XmMN-6g1L8w.wav"} +{"id": "Xn0wIqnt_44", "caption": "This music is an electronic instrumental. The tempo is fast with heavily synthesised arrangements and intense drumming with a male voice speaking over the music. The music is intense, vigorous,animated, futuristic and vital. It sounds like video game music and the male voice seems to be reviewing Video Games.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xn0wIqnt_44.wav"} +{"id": "XnHAH2aPHk0", "caption": "Someone is playing a clean e-guitar with a lot of reverb and delay. Fingerpicking and creating dreamy rhythm and melodic patterns. In the background you can hear a drumloop and an e-bass. This song may be playing during a little live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/XnHAH2aPHk0.wav"} +{"id": "XnMokzAE5kk", "caption": "This is a rave music piece. There is a loud electronic drum beat in the rhythmic background. A strong synth bass and a sharp sounding pad are the main elements of the melody. It is an energetic piece to the point of being hyperactive. This piece could be played at nightclubs and rave venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/XnMokzAE5kk.wav"} +{"id": "XoTJkok3FlY", "caption": "Low quality recording features an arpeggiated electric guitar melody. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/XoTJkok3FlY.wav"} +{"id": "Xoke1wUwEXY", "caption": "The low quality recording features a live performance of a rock song that features muffled male vocals, loud electric guitar melody, buzzy bass guitar, punchy kick and snare and harsh cymbals. Sounds energetic, vintage and a bit harsh, due to the quality of the recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xoke1wUwEXY.wav"} +{"id": "XpueyrkcMyQ", "caption": "This is a jazz music piece. There is a trumpet and a saxophone playing the lead melody. The piano is playing the chords of the piece while the upright bass is playing a groovy bass line. The acoustic drums are playing a swing type beat for the rhythmic background. The atmosphere is groovy. This piece could be playing in the background at a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/XpueyrkcMyQ.wav"} +{"id": "XrjkzI6TVwc", "caption": "The excerpt features an electric guitar with a distortion effect on playing what sounds to be an improvised passage. The style comes closest to the rock genre. The lower quality of the audio recording coupled with string noises makes me think this is an amateur recording, most probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/XrjkzI6TVwc.wav"} +{"id": "XscK8V4Veac", "caption": "This clip features a female voice singing the main melody. The backing instruments cannot be clearly heard due to the low quality of recording. The voice sings with a gospel feel. The bass plays ascending notes. The vocal melody is repetitive. Hand claps are played at random points.", "audio": "/zhanghaomin/datas/musiccap/music_data/XscK8V4Veac.wav"} +{"id": "XscNEv9tX5U", "caption": "The low quality recording features plastic percussion hits. The recording is noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/XscNEv9tX5U.wav"} +{"id": "Xsvi5Mgl3qo", "caption": "The low quality recording features a mellow harp melody that sounds mystical, soft, hypnotic and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xsvi5Mgl3qo.wav"} +{"id": "XtpfZx12hDM", "caption": "The low quality recording features an electro song that consists of a typical punchy \"4 on the floor\" kick pattern, wide and mellow synth pad chords and synth lead melody with wide echoing effects on. It sounds energetic and like a song from the early 00s.", "audio": "/zhanghaomin/datas/musiccap/music_data/XtpfZx12hDM.wav"} +{"id": "Xus0LI3QV2A", "caption": "This clip is an instrumental. The tempo is slow and deliberate with an electric guitar playing an energetic riff. It is minimal instrumentation with no other instrument used. The electric guitar is loud, boomy, jarring, resonant,recurring, with an insistent riff.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xus0LI3QV2A.wav"} +{"id": "XvN-qr-WYmw", "caption": "The low quality, noisy recording features a live performance of a traditional song and it consists of loud synchronized percussion and bagpipe melody playing over it. It sounds soulful and passionate - like something you would hear in Scotland, as the bagpipe is their traditional instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/XvN-qr-WYmw.wav"} +{"id": "XvtL_TTLXHY", "caption": "This is a live Christian gospel music performance. There is male lead vocal singing melodically and passionately with the backing of a male choir. The melody is being played by a church organ and a bass guitar. The acoustic drums and the tambourine played in a very eccentric manner are the elements of the rhythmic background. The atmosphere is religious. This piece could be played at Christian religious events or in the background of Christian social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/XvtL_TTLXHY.wav"} +{"id": "XvyaEbEpAMc", "caption": "The low quality recording features a cover of a rock song and it consists of acoustic rhythm guitar and nasal, echoing male vocals. The recording is noisy and in mono and it sounds emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/XvyaEbEpAMc.wav"} +{"id": "XwhAoMLNYWQ", "caption": "The music features a male voice singing a melody in the med-high register. The drummer plays a steady and repeating rhythm. The bass guitar, for the most part, plays two repeating notes every beat. A synth sound is playing a melody in the mid-high register. Listening to this song I get Christmas vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/XwhAoMLNYWQ.wav"} +{"id": "XxKlsW4H0qo", "caption": "This is a clip of a singing bowl. The tone is high pitched and sustained and ringing. The song would be suitable for a meditation room or for any kind of environment wherein tranquility is the end goal.", "audio": "/zhanghaomin/datas/musiccap/music_data/XxKlsW4H0qo.wav"} +{"id": "Xxe6vTEwFvs", "caption": "The rock and roll music features a male voice singing a melody and at times singing in unison with a male backing voice. The band that accompanies the singer consists of a drum kit playing a light and simple rhythm, a bass guitar that plays in the style of walking bass, and a section of saxophones. On top of this recording one can hear a rattle that sounds close to a baby shaker toy. The recording quality is not that good, which leads me to believe it's an amateur phone recording of a speaker playing the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xxe6vTEwFvs.wav"} +{"id": "Xy7KtmHMQzU", "caption": "This is a traditional middle eastern song that would fit into the maghreb pop genre. The song features what sounds like strumming from a guitar instrument, as well as a melodic motif from the ney. The vibe is sultry and mysterious.", "audio": "/zhanghaomin/datas/musiccap/music_data/Xy7KtmHMQzU.wav"} +{"id": "XykUpCigu4w", "caption": "The song is an instrumental. The tempo is slow with percussive instruments playing, bells percussions and a music box melody. The song is educational and designed for toddlers. The audio quality is pretty average.", "audio": "/zhanghaomin/datas/musiccap/music_data/XykUpCigu4w.wav"} +{"id": "XzRxO8n3WRE", "caption": "This is a low quality recording of a veena being played. This is a classical Hindustani song. The veena plays a note bending the string to a higher note and then descending back to the original note. The audio gets cut off intermittently. Briefly, during the places where the audio is heard, a tabla is heard. There are no voices in this song. This song can be played in a conservative Indian movie featuring a wedding scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/XzRxO8n3WRE.wav"} +{"id": "XzTBNfQ7_GA", "caption": "This music is instrumental. The tempo is slow with an Oud lead with atmospheric synthesiser . The music uses minimal instrumentation to emphasise on the lead instrument. The hollow sound in the background is either a synthesiser or a wind instrument. The music is intense, grim, mysterious, suspenseful, sinister and enigmatic.", "audio": "/zhanghaomin/datas/musiccap/music_data/XzTBNfQ7_GA.wav"} +{"id": "XzlDa1dzUh4", "caption": "This amateur recording features an electric guitar playing hammer ons on the pentatonic scale. There is a backing track that fades away and stops playing. The electric guitar plays a chord and pauses. The guitar then strums one more chord four times. There are no voices in this song. This is an instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/XzlDa1dzUh4.wav"} +{"id": "XzwhTltRQcM", "caption": "This is an electronic music jam using a drum machine. The touchpads on the drum machine are used to perform chopped-up melodic pad sounds by tapping on them. Since this is an amateur recording, the finger tapping sounds can be heard as well. This piece could be used to lift low-resolution samples from to use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/XzwhTltRQcM.wav"} +{"id": "Y-qOOR0izlE", "caption": "A helicopter engine is starting with a song playing in the background. The song contains acoustic guitars, a keyboard melody and a drumset. This song may be playing in an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y-qOOR0izlE.wav"} +{"id": "Y02VBGoTi9w", "caption": "This is a performance of classical music on a vibraphone. It is a live recording and it is tranquil and soothing. The audio quality is not high, but the notes are still easily distinguishable.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y02VBGoTi9w.wav"} +{"id": "Y0_Ixl1d7oQ", "caption": "The low quality recording features a compilation of basketball game highlights and it consists of crowd cheering and floor squeaking sound effects, followed by commentary of energetic male vocals, while a R&B song is playing in the background. The song consists of a boomy kick, claps, shimmering hi hats, high pitched piano chord progression and passionate male vocals, alongside wide male doubling vocals, singing over it. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y0_Ixl1d7oQ.wav"} +{"id": "Y1ItBiA8nKU", "caption": "This audio contains someone talking while playing a rhythm with drumsticks on a drum pad. This is an amateur recording. This may be playing live while watching a lesson during drum class.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y1ItBiA8nKU.wav"} +{"id": "Y1gheqplpIg", "caption": "This is an instrumental theremin piece. The theremin is making vague sound effects. There is an eerie atmosphere to this performance. This recording could be sampled for use as sound effects in movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y1gheqplpIg.wav"} +{"id": "Y3WXrp3JFxU", "caption": "A low fidelity live recording of house music with camera noise from jostling a small microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y3WXrp3JFxU.wav"} +{"id": "Y5RVYmf3uWc", "caption": "A female vocalist sings this melodic song in Icelandic. The tempo is slow with vocal emphasis and a soft and romantic piano accompaniment. The song is a mellow, soothing, peaceful, soothing, ethereal, mesmerising and captivating Icelandic lullaby.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y5RVYmf3uWc.wav"} +{"id": "Y6OOFbrzdP8", "caption": "This is an amateur cover of a guitar solo in a heavy metal piece. The solo is being played on an electric guitar. There is a rapid procession of high-pitch notes in the solo. The feel is complex and aggressive. The quality of the recording is a bit poor. If the quality issue can be resolved, this piece could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y6OOFbrzdP8.wav"} +{"id": "Y7SoAXBFUew", "caption": "This song contains a piano adding single notes to digital strings being played in the high-mid and as a bassline. The recording is full of reverb and the instruments are slightly panned across the speakers. The atmosphere sounds sad,melancholic. This song may be playing in a sad movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y7SoAXBFUew.wav"} +{"id": "Y7mTjfgcybQ", "caption": "A female and male duo yodeling over a fast bluegrass band. The bass and drums are steady and simple as is the chord progression. The guitarist and other instrumentalists are virtuosic.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y7mTjfgcybQ.wav"} +{"id": "Y8ULUSXWTcY", "caption": "This is an electronic music piece. The female vocalist is singing in a rap-like repetitive manner and is occasionally joined by a male vocalist. There is a repeating one-note hollering female vocal sample in the background. A keyboard plays a simple tune. There is a loud electronic drum beat in the rhythmic background. The atmosphere is energetic and danceable. This piece can be played in nightclubs and bars in Thailand. It could also be used in dancing courses as an accompaniment piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y8ULUSXWTcY.wav"} +{"id": "Y8plCTF8xsY", "caption": "The low quality recording features a live performance of an orchestra playing sustained brass melody, shimmering cymbals and sustained strings melody. It sounds muddy and muffled, as it was probably recorded with a poor quality microphone, but also passionate. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y8plCTF8xsY.wav"} +{"id": "Y8wHDcVCGa0", "caption": "Male voices are yodeling with a lot of reverb on their voices. They are loud and the speakers of the recording are speaking. An accordion is playing a fast melody that is panned to the right side of the speakers. A guitar is strumming a rhythmic chord on the backbeat. An upright bass is playing a walking bassline. This song may be playing at a folksfest. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y8wHDcVCGa0.wav"} +{"id": "YAVVMxqtxGE", "caption": "The low quality recording features a tutorial that consists of a flat male vocal talking, after which there are a few different pitch cowbell one shots. The recording is in mono and it is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/YAVVMxqtxGE.wav"} +{"id": "YAYp2E5vMNw", "caption": "The low quality recording features a live performance of a classical song that consists of sustained strings, woodwinds melody, aggressive strings lick, wooden percussion and repetitive violin melody. It sounds suspenseful and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/YAYp2E5vMNw.wav"} +{"id": "YB28WMv7wUE", "caption": "This amateur recording features a synth string swell at the beginning of the audio. Alien sounds are played in the background. This is followed by a crash cymbal struck once. Other instruments are not audible due to the low quality of audio. There are no voices in this song. This is an instrumental song.", "audio": "/zhanghaomin/datas/musiccap/music_data/YB28WMv7wUE.wav"} +{"id": "YB_PzRgHOeo", "caption": "This is a pop music piece with an early 2000s feel. There is one male and one female vocalist singing melodically. The melody is being played by the electric guitar and the keyboard guitar with the bass guitar in the background. The rhythm is provided by the acoustic drums with occasional clap sounds. The atmosphere is easygoing and danceable. This piece could be used in the soundtrack of a sit-com movie or a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/YB_PzRgHOeo.wav"} +{"id": "YBbvQ0RPrG8", "caption": "This music is instrumental. The tempo is medium with an electric guitar harmony. The music is a catchy riff with a male voice speaking in a foreign language. This clip is an electric guitar lesson/ tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/YBbvQ0RPrG8.wav"} +{"id": "YDBxdZchOuM", "caption": "The song is an instrumental. The tempo is medium with a guitar playing a romantic lead, steady drumming, rock drumming, percussive bass line, cymbals crashing and guitar strumming rhythm. The song is exciting and youthful. The song has a bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/YDBxdZchOuM.wav"} +{"id": "YDh36ZdneAU", "caption": "This is the recording of a guitar lesson video. There is a male instructor first performing the tune and then describing what he is playing. The tune is being played on a clean sounding electric guitar and there is a blues feel to it. The atmosphere is easygoing. The parts the male voice is not heard can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/YDh36ZdneAU.wav"} +{"id": "YE2rN3xknlk", "caption": "Synthesizer pads are playing long chords with a lot of reverb creating a dreamy and relaxing atmosphere. A piano is sprinkling notes on top while a highly processed voice sample is singing a melody that uses a ping pong effect to move to both sides of the speakers. This song may be playing in between two songs in a DJ set to reset the atmosphere.", "audio": "/zhanghaomin/datas/musiccap/music_data/YE2rN3xknlk.wav"} +{"id": "YErpnsceZw8", "caption": "This is a live performance by a female vocal quartet. They harmonise their voices and sing in a vibrant and cheerful way. They sing in French. Later, we hear two violins playing in sync as well as an accordion. The recording quality of the audio is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/YErpnsceZw8.wav"} +{"id": "YEwikeeqF38", "caption": "This audio contains a scary song that may belong in a horror movie. There is a tuned wind sound, synth pads and drones creating an uncomfortable atmosphere. On top of that a synth pluck sound is playing a dissonant melody and a piano is playing one single note in the mid range.", "audio": "/zhanghaomin/datas/musiccap/music_data/YEwikeeqF38.wav"} +{"id": "YFXSbPFaxcA", "caption": "The song is an instrumental. The song is medium tempo with a keyboard accompaniment, groovy bass line and a funky drumming rhythm. There is a lot of office ambient noises, like a printer motor noises, wind noise and other office environmental sounds. The music track acts as a background to the ambient office sound environment. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/YFXSbPFaxcA.wav"} +{"id": "YFhbrSUb0JQ", "caption": "The low quality recording features a clarinet melody. It sounds harsh, loud and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/YFhbrSUb0JQ.wav"} +{"id": "YGWweVRzFrw", "caption": "This clip features a heavenly sounding harp. The piece is arpeggio driven and elicits a feeling of tranquility and peace. The harp is full bodied and the instrumentalist balances the high tones with a deep bass sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/YGWweVRzFrw.wav"} +{"id": "YIhfk4Zaevk", "caption": "Instrumental Chicago blues music featuring a saxophone melody interspersed with licks from harmonica, Hammond style organ, acoustic piano and electric guitar. The drums play a shuffled backbeat on the snare and low toms under a repetitive electric bass riff. Would be at home in a roadhouse or barbecue festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/YIhfk4Zaevk.wav"} +{"id": "YJKZVSvz1Bk", "caption": "This music is instrumental. The tempo is medium fast with boomy bass, turntable scratching and digitally arranged music. The music is muffled as the audio quality is inferior but the beats are punchy, buoyant, bouncy, youthful, groovy and energetic. This music is a turntable scratching technique.", "audio": "/zhanghaomin/datas/musiccap/music_data/YJKZVSvz1Bk.wav"} +{"id": "YK1AEw1kf28", "caption": "The low quality recording features a classical song that consists of passionate male opera vocal singing over wide strings melody, wide brass melody and woodwinds melody, over which there is a fruity male vocal talking. It sounds passionate, epic and powerful - like something for commercial.", "audio": "/zhanghaomin/datas/musiccap/music_data/YK1AEw1kf28.wav"} +{"id": "YKQMolFL2Rs", "caption": "The song has a bluesy funk feel to it. The singer has a raspy and burly vocal and sits on top of a grungy gritty electric guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/YKQMolFL2Rs.wav"} +{"id": "YLlbLSNxdQ4", "caption": "The low quality recording features a children's song that consists of a clock ticking, church bells melody, plucked strings melody and flat female vocal singing over it. It sounds happy, joyful and fun. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/YLlbLSNxdQ4.wav"} +{"id": "YMq4wE6KxmQ", "caption": "A synth pad is playing an evolving drone chord along with some glittering sounds. In the background of the recording you can hear wind, running and birds chirping. The whole scenario sounds calming and meditative. This song may be playing for a documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/YMq4wE6KxmQ.wav"} +{"id": "YNdexakUGOo", "caption": "The low quality recording features an arpeggiated electric guitar melody with an aggressive echoing effect on. The recording is noisy as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/YNdexakUGOo.wav"} +{"id": "YNoR-SR5t1s", "caption": "This audio contains a male voice talking while a theremin is playing a melody in the mid- to higher register with a lot of vibrato. Celli and upright basses are plucking a strange melody in the lower register creating tension. This song may be playing in an art/alien movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/YNoR-SR5t1s.wav"} +{"id": "YNv7mzbUUHc", "caption": "This is a gear comparison jam recorded with an electric guitar played with different chorus effect pedals. The electric guitar is playing simple tunes that sound dreamy with the added chorus effect. There is a psychedelic atmosphere. Certain parts of this recording can be sampled for use in beat-making or in advertisement jingles. These parts could also be played as an opening theme for rock music radio stations.", "audio": "/zhanghaomin/datas/musiccap/music_data/YNv7mzbUUHc.wav"} +{"id": "YOA1JOyd7cw", "caption": "The low quality recording features a cover of an R & B/soul song and it consists of a steel guitar solo melody. There are some pedal tapping noises. Overall the recording is noisy and it sounds passionate and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/YOA1JOyd7cw.wav"} +{"id": "YODoF8e7Jlk", "caption": "This is a street performance of an instrumental music piece. The performer is playing a melody on the didgeridoo while he is using various percussive elements to create the rhythmic background. The atmosphere is eccentric and there is a tribal sound to the piece. This piece could be used in the soundtrack of an adventure movie with a jungle or a desert setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/YODoF8e7Jlk.wav"} +{"id": "YOG_PPvTvW0", "caption": "The song is an instrumental. The tempo is medium with a harpsichord being played expertly with no other instrumentation. The song is melancholic and exciting. The song is western classical baroque piece that evokes a sense of grandeur.", "audio": "/zhanghaomin/datas/musiccap/music_data/YOG_PPvTvW0.wav"} +{"id": "YSXrSxC68VM", "caption": "Here we have an energetic, up-tempo japanese rock song. The drumming is potent, punchy and predominant. The drummer plays the ride cymbal frequently, creating a shimmery effect in the song. The female singer has a calming voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/YSXrSxC68VM.wav"} +{"id": "YSrTtw6ku2E", "caption": "The file contains acoustic drums playing with a lot of crash hits, an e-guitar playing a melody along with male voice singing the same melody. The crowd is cheering and screaming in the background. This is an amateur recording with poor sound-quality. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/YSrTtw6ku2E.wav"} +{"id": "YTYj8Bk0qM8", "caption": "This music is instrumental. The tempo is slow with a French Horn playing the Titanic soundtrack. The music is romantic, emotional, nostalgic, loud, lucid ,sad and poignant, mellow and sentimental. This music is a French Horn instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/YTYj8Bk0qM8.wav"} +{"id": "YTZK9FNgK74", "caption": "An orchestra plays a waltz supporting a Theremin which takes the lead melody while the piano plays a counter melody. The feel is cinematic, spooky and a bit quirky.", "audio": "/zhanghaomin/datas/musiccap/music_data/YTZK9FNgK74.wav"} +{"id": "YVEqyQjyy1Q", "caption": "A female vocalist sings this spirited pop. The tempo is fast with infectious piano melody, slick drumming, funky bass, baritone saxophone, Hammond organ accompaniment with enthusiastic vocals. The song is fresh, youthful, buoyant; energetic, high-spirited, cheeky, suggestive, playful and groovy. This is a hit Pop Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/YVEqyQjyy1Q.wav"} +{"id": "YW4AKwkpYxs", "caption": "This music is instrumental. The tempo is fast with an energetic electric guitar lead harmony. The music is emphatic, seasoned, enthusiastic,engaging and high-spirited. This music is a Hard Rock instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/YW4AKwkpYxs.wav"} +{"id": "YWf3I4jKusI", "caption": "A female vocalist sings this high energy pop song. The tempo is fast with vigorous drumming, synthesiser arrangements and boomy bass drops. The song is vibrant, lively, spirited, buoyant, punchy and youthful with a catchy vocal riff. The sound quality of this song is inferior and distorted. This song is an EDM/Synth Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/YWf3I4jKusI.wav"} +{"id": "YXDHyD4HU0E", "caption": "The low quality recording features a passionate male vocal singing over groovy bass piano melody, muted brass melody, sustained strings melody and shimmering hi hats. It sounds passionate and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/YXDHyD4HU0E.wav"} +{"id": "YZH-PZBir3E", "caption": "This is a house remix of a pop music piece. The female vocal from the original track is being repeated as a sample. There is a strong bass and a loud electronic drum beat in the background. The piece is upbeat and energetic. It could be played at nightclubs, dance clubs and DJ performances.", "audio": "/zhanghaomin/datas/musiccap/music_data/YZH-PZBir3E.wav"} +{"id": "YZvv4hOlNqw", "caption": "The low quality recording features a hip hop song where a fruity male vocal is rapping over punchy kick and snare hits, shimmering hi hats, groovy bass and brass melody. It sounds bouncy, groovy and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/YZvv4hOlNqw.wav"} +{"id": "YZx0_GRtvJk", "caption": "This song has a male vocalist singing a rhythmic vocal riff to the beat of digital drumming followed by the sound of a beep. The percussion is amateur and the vocals are muffled as the audio quality is inferior. The song is slow tempo and the beat is punchy, groovy, buoyant and youthful.", "audio": "/zhanghaomin/datas/musiccap/music_data/YZx0_GRtvJk.wav"} +{"id": "Y_eh6C0EBP8", "caption": "The song is an instrumental followed by a long pause. The song is medium tempo and features an electric guitar playing a solemn solo. The song is passionate and mysterious. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/Y_eh6C0EBP8.wav"} +{"id": "YbLR6dgY-K4", "caption": "This music clip is of a musician playing a lilting melody on the Banjo. The tempo is medium with a rhythmic lead harmony. There is no other instrument used. The music is soft, mellow, nostalgic, and calming. Soothing and simple.", "audio": "/zhanghaomin/datas/musiccap/music_data/YbLR6dgY-K4.wav"} +{"id": "YcWJUHWt-64", "caption": "The low quality recording features a Twoubadou song that consists of flat male vocal singing over acoustic guitar melody, arpeggiated guitar melody, syncopated rimshots, shimmering shakers, smooth bass and wooden percussive elements. Even though it is noisy, it sounds fun and happy - like something you would want to dance to.", "audio": "/zhanghaomin/datas/musiccap/music_data/YcWJUHWt-64.wav"} +{"id": "YcfGSJB1YvQ", "caption": "This gospel song features a male voice singing the main melody in an emotional voice. This is accompanied by the percussion playing continuously in sixteenth notes on the ride cymbal. The bass plays a groovy lick and fill based on the root note of the chord. The piano plays a chord followed by a fill and an ascending run. This song can be played in a Christian movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/YcfGSJB1YvQ.wav"} +{"id": "Ycid0vBwqUg", "caption": "This is a mellow and soulful 2000s R&B song. The female vocalist gives a sensual and passionate vocal performance. The song is seductive, intimate and relaxed. There are string-like sounds and a warm and bright pad-synth along with the mellow groovy drum beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ycid0vBwqUg.wav"} +{"id": "Yd8JBTdUvrw", "caption": "This song features the shofar being played. The shofar is blown and the pitch quickly changes from low to high while being blown. This is a religious instrument. There are no other instruments in this song. There are no voices in this song. This song can be played in a movie scene as a battle call.", "audio": "/zhanghaomin/datas/musiccap/music_data/Yd8JBTdUvrw.wav"} +{"id": "YddV91xnUz4", "caption": "The low quality recording features a rock song where dissonant female vocals are singing over electric guitar melody, groovy bass guitar, hollow snare, shimmering hi hats and soft kick hits. It sounds sloppy and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/YddV91xnUz4.wav"} +{"id": "YeIXmKPyTVY", "caption": "Synthesizer melodies and bassline being arpeggiated. On top of that another synth sound is playing a melody at the end of the phrases. Then a four on the floor kick comes in. This song may be playing at home while cleaning the house.", "audio": "/zhanghaomin/datas/musiccap/music_data/YeIXmKPyTVY.wav"} +{"id": "YgX85tZf1ts", "caption": "The tune is played by two vibraphones at the same time. The bright character of the instrument gives the piece a playful aura. It could be used as a ringtone or an alarm tone due to its generic, repeated nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/YgX85tZf1ts.wav"} +{"id": "Yiau7DypQi0", "caption": "This music is an electronic instrumental. The tempo is medium with intense synthesiser arrangements and electronic sounds, along with the sound of rhythmic whistling. The music sounds scary, sinister, anticipatory, futuristic, spotty and unnerving. This music is Electronic/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/Yiau7DypQi0.wav"} +{"id": "Yj7YyxKyXPU", "caption": "This music is instrumental. The tempo is fast with a lively trumpet harmony with steady drumming, keyboard harmony and tambourine beats. The music has middle eastern music influences . It is busy, loud, boisterous, and chaotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/Yj7YyxKyXPU.wav"} +{"id": "YjTz5y8DnWo", "caption": "This is an amateur recording of an Irish folk music piece. It is an instrumental piece. There is an Irish flute playing a playful melody in a home setting. The atmosphere is cozy. This piece could be used in the soundtrack of an arcade adventure video game during the parts where the protagonist is traversing through forested areas.", "audio": "/zhanghaomin/datas/musiccap/music_data/YjTz5y8DnWo.wav"} +{"id": "Yk2ZrS0ZS6g", "caption": "This music clip is an instrumental. The tempo is medium with a simple and interesting melody with a recorder harmony, steady drumming, groovy bass lines,keyboard accompaniment ,xylophone rhythm, a constant electronic sound like that of a child\u2019s toy gun or car , tambourine beats and chimes and bells. The music is mellow, unique, fun, simple and catchy. This music is Soft Rock/Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/Yk2ZrS0ZS6g.wav"} +{"id": "YlV45uBUVBc", "caption": "The song feels relaxing, soothing and gentle. It feels like the kind of music that you would play if you wanted to fall asleep. It features a gentle and dainty electric piano with a flanger, as well as a sustained synth pad.", "audio": "/zhanghaomin/datas/musiccap/music_data/YlV45uBUVBc.wav"} +{"id": "YlgCFc3OvmI", "caption": "This song features an acoustic guitar playing chords using only down strokes. There are only two chords being played. The rhythm is played on a 6/8 time signature. A male voice sings vocables in falsetto. Toward the end, the voice produces a belching sound. There are no lyrics in this song. There are no other instruments in this song. This song can be played at a quirky party.", "audio": "/zhanghaomin/datas/musiccap/music_data/YlgCFc3OvmI.wav"} +{"id": "YnE5ONaXtLY", "caption": "This is an instrumental Rajasthani folk music piece. There is a high-pitched flute playing a melody while a group of tambourines are keeping the rhythm. The atmosphere is vibrant. This piece could be used as an accompaniment piece for a folk dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/YnE5ONaXtLY.wav"} +{"id": "YpOHemscGCk", "caption": "The low quality recording features a sipping sound effect and some repetitive, weird burping sounds, while the jazz song is playing in the background. It sounds like it is an audio from some cartoon on a TV, as it sounds mono and a bit noisy too - like it was recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/YpOHemscGCk.wav"} +{"id": "Ypuv3htJlpg", "caption": "This is an amateur recording of a harmonica solo being performed over a blues/rock-n-roll music piece. The piece is instrumental. The harmonica plays a melodic solo in the style of blues. The backing track consists of the electric guitar and the bass guitar playing a simple tune while the medium tempo acoustic drums are playing a basic blues rock beat. The atmosphere is easygoing. This piece could be playing from the radio during a road trip in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ypuv3htJlpg.wav"} +{"id": "YqAsph_ouRM", "caption": "This low quality audio features an electric guitar playing a solo. The sounds of the instruments are not clear due to the low audio quality. The percussion plays a fast beat in the background. There are no voices in this song. This song can be played in a car chase sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/YqAsph_ouRM.wav"} +{"id": "YqZNMFyPJOQ", "caption": "This audio contains someone playing a melody on a banjo. A male voice is speaking with a deeper voice. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/YqZNMFyPJOQ.wav"} +{"id": "YrGQKTbiG1g", "caption": "This is an indie rock piece. There is a male vocalist in the lead with heavy effects. There is an ambient synth in the background playing the melody with the accompaniment of an acoustic guitar. A mellow bass guitar plays a groovy bass line. The rhythmic background consists of an electronic drum beat full of percussion samples. The piece has a trippy aura. It could be played at nightclubs. It could also be used in the soundtracks of drama films with a modern, urban setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/YrGQKTbiG1g.wav"} +{"id": "Ysrlv2UlG8A", "caption": "The song is instrumental. The tempo is medium with electrical current manipulation to produce different frequencies to play percussively and harmonically with each other. The song is for scientific research and not pleasing to the ear. The song is of poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ysrlv2UlG8A.wav"} +{"id": "Yt1czlnCUCg", "caption": "This children's song features a male voice singing the main melody. This is accompanied by male and female voices singing backing vocals in harmony. This has a call and response technique where the main voice sings a line followed by the response by the choir. This is accompanied by percussion playing a simple beat. After two bars, the instruments pause. The bass plays the root notes of the chords and sliding to a pause at the end of the bar. During the pause, the voices continue to sing. The main voice sings two lines and the choir sings the third line with the main voice in harmony. The mood of this song is happy. After the pause, the singers return to singing the same melody. This song can be played in an educational movie for children.", "audio": "/zhanghaomin/datas/musiccap/music_data/Yt1czlnCUCg.wav"} +{"id": "YtYjdkTK5oY", "caption": "The low quality recording features a synth melody and a lot of synth sound effects, over which there is a funny boy vocal talking. The synth melody continues to play in the second part of the loop where shimmering bells, snaps layered with snappy rimshots and harmonizing kids' vocals singing over them, appear. It sounds happy, joyful and fun - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/YtYjdkTK5oY.wav"} +{"id": "YuiQRYaF9SA", "caption": "Someone is playing a melody on acoustic guitar and then continues strumming chords along with a soft e-bass playing a melody along. These two instruments are panned on to the left and the other to the right side of the speakers. A male voice is sitting in-between singing in a higher pitch. This song may be playing in a movie scene of someone being in the countryside.", "audio": "/zhanghaomin/datas/musiccap/music_data/YuiQRYaF9SA.wav"} +{"id": "YvFY7xU2kGk", "caption": "This music is an electric guitar instrumental. The tempo is medium with an enthusiastic lead on the electric guitar.no accompanying instruments are used. The music is loud, emphatic, catchy, intense and powerful like in Rock/ Metal music.", "audio": "/zhanghaomin/datas/musiccap/music_data/YvFY7xU2kGk.wav"} +{"id": "YvT7qFbUOO0", "caption": "In this recording we hear two main instruments - the sitar and the tabla. The sitar player plays some simple and slow licks, in an emotive way. The tabla player plays a simple rhythm to support the sitar. The recording is an old recording - and this is a vintage south asian music piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/YvT7qFbUOO0.wav"} +{"id": "Yw28B_xflHk", "caption": "This folk song features the lead melody played on a rebab instrument which sounds like violins. This song has a Middle-Eastern melody. This is accompanied by traditional Middle-Eastern percussion. A tambourine is played in the background. The other instruments are not clear due to the low quality of the audio. There are no voices in this song. This is an instrumental song. This song can be played at a village scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/Yw28B_xflHk.wav"} +{"id": "YwUa3OS92ZQ", "caption": "You can hear birds chirping along with pig-sounds. Then a full orchestra with strings, bell sounds and a choir comes rising in tension. This song may be playing in a dramatic, epic movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/YwUa3OS92ZQ.wav"} +{"id": "YxQzJweGS2c", "caption": "This is a lullaby music piece. There is a female vocalist singing gently. The acoustic guitar is playing a mellow tune while the bass guitar accompanies with a simple bass line. There is a synth with a string sound in the background. The atmosphere is calming and sleep-inducing. This piece could be played at nurseries and it could be included in the soundtracks meant to put babies to sleep.", "audio": "/zhanghaomin/datas/musiccap/music_data/YxQzJweGS2c.wav"} +{"id": "YxkYVsE0UdQ", "caption": "This audio contains various e-guitars playing different parts and melodies of a song. One is playing as bass, another one is fingerpicking chords while another one is playing a distorted arpeggio melody on top. This song may be played live by a busker with a loop padel.", "audio": "/zhanghaomin/datas/musiccap/music_data/YxkYVsE0UdQ.wav"} +{"id": "YyHmz1vcob8", "caption": "This music clip is an instrumental. The tempo is slow with a steady keyboard harmony, ethereal male vocal harmony, cymbals, electronic sounds, sound of metal swiping,an engine whirring,and breeze. It is mysterious, suspenseful, enigmatic, grim and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/YyHmz1vcob8.wav"} +{"id": "YyYEzAY2e2I", "caption": "The song is an instrumental. The tempo is slow with a didgeridoo playing percussive grunting low tones in a sonorous manner. The song is trance-like with a dance performing live on stage. The song is meditative and deeply spiritual.", "audio": "/zhanghaomin/datas/musiccap/music_data/YyYEzAY2e2I.wav"} +{"id": "YyZ5bXcMDv4", "caption": "This pop ballad features a song played on an electric piano. The main melody is played on an electric piano. This is accompanied by synth layers playing fills in the background. Synth pads play a warm sound which is sustaining chords in the background to fill the musicscape. There are no voices in this song. This is an instrumental song. The mood of this song is romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/YyZ5bXcMDv4.wav"} +{"id": "Yz1DrC54UGk", "caption": "This song contains a acoustic drums running through a filter playing along with a tambourine. A e-guitar is playing a short repeating melody. A e-bass is first playing with a effect and then clean when a brass section comes in. This song may be playing with headphones while running on a sunny day.", "audio": "/zhanghaomin/datas/musiccap/music_data/Yz1DrC54UGk.wav"} +{"id": "YzpzKyzyL0Y", "caption": "Latin music featuring a quick tempo, hand percussion, tambourine, lively hand claps, guiro, a low tuned bass drum, an acoustic guitar solo with a wah effect, flamenco inspired fast acoustic guitar strumming, complex chords and a modern electric bass sound supporting a passionate female singer.", "audio": "/zhanghaomin/datas/musiccap/music_data/YzpzKyzyL0Y.wav"} +{"id": "Z-G7nL9tiws", "caption": "This music clip is an instrumental. The tempo is fast with different electronic sounds from a video game. The sounds and music are dissonant and unrelated. There are sounds of shooting, beeping, and game ending. This music is video game music.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z-G7nL9tiws.wav"} +{"id": "Z-Vb1Ay-zNA", "caption": "The song is an instrumental. The tempo is medium with a clarinet playing lead supported by a wind section, horn section, brass section and other percussion. The song is exciting and energetic. The song is a western classic tune with bad audio quality issues.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z-Vb1Ay-zNA.wav"} +{"id": "Z0O2r0Dl2T4", "caption": "This is an instrumental wind band music piece. There are three trumpets playing the main melody while a wind instrument sound is playing a supporting tune. There is a bass guitar playing in the background. The rhythm consists of a simple electronic drum beat. The atmosphere is playful and cheerful. This piece could be used in the soundtrack of a kids TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z0O2r0Dl2T4.wav"} +{"id": "Z0OTDXtjK9M", "caption": "The low quality recording features an electric guitar melody being played. There is a tiny audio pop in the left channel of the stereo image. The recording is noisy and muffled, but regardless it sounds hopeful.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z0OTDXtjK9M.wav"} +{"id": "Z0htOHTOtHY", "caption": "A female opera singer accompanied by an orchestra featuring string bass, harp and string ensemble. It sounds like it was performed in a concert hall. Dramatic.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z0htOHTOtHY.wav"} +{"id": "Z19W44ZI15Q", "caption": "This is a home recording of two electric guitar players jamming some random rock/metal tunes. It is a dated amateur recording so the quality is quite poor. The electric guitars have a distortion effect that gives them a crunchy sound. The sound is hard-hitting, but the atmosphere feels spontaneous and random. Parts of this recording could be lifted as distorted electric guitar samples to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z19W44ZI15Q.wav"} +{"id": "Z2c1npe5AYY", "caption": "The low quality recording features a deep tone singing bowl resonance and a bowl hit impact. It sounds relaxing, calming and hypnotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z2c1npe5AYY.wav"} +{"id": "Z31gI08SMzI", "caption": "Male voices are singing a hymn while supported by strings playing chords, a triangle sound can be heard as a rhythmic addition. Upright basses being plucked along with a soft timpani hit. This song may be playing at an official national event.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z31gI08SMzI.wav"} +{"id": "Z5x5BLzQKZI", "caption": "The song contains synth pad sounds in the low to mid range playing drone sounds with little atmospheric sounds. In the background you can hear sounds of something falling to the ground. This song may be playing for meditation.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z5x5BLzQKZI.wav"} +{"id": "Z6q5doznOcI", "caption": "This sounds like the ending of a big orchestral piece, with the brass section sustaining a harmony at the end. The piece feels warm, relaxing and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z6q5doznOcI.wav"} +{"id": "Z7V7Curou7s", "caption": "The low quality recording features a parody that contains metallic detuned percussion, funny synth lead, wide sustained string melody in the background, male and crow cough, wooden percussion hits layered with coughs and flat male vocals, alongside harmonized mixed vocals, singing over it. It sounds funny and weird - almost like a TV commercial.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z7V7Curou7s.wav"} +{"id": "Z8L3jychP14", "caption": "A female singer sings this casual melody. The tempo is medium with clapping and desk tapping percussion and no other instrumentation. The song is very casual and made up for fun. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z8L3jychP14.wav"} +{"id": "Z9hnLYpypCU", "caption": "The low quality recording features a munching and humming sound effect - like someone is enjoyably eating. At the very beginning, there is also a haunting synth lead melody and a smooth bass located in the left channel of the stereo image - making it unbalanced.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z9hnLYpypCU.wav"} +{"id": "ZAT2_-x59pY", "caption": "This audio contains someone playing a rhythm using acoustic drum samples along with synth pad sounds with a lot of reverb creating harmonies and a melody. This song may be playing and producing music at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZAT2_-x59pY.wav"} +{"id": "ZCKzgf3QD4M", "caption": "People chant and sing in unison. The song is medium fast tempo with Indian percussion playing fast, violins and other stringed instruments playing harmony along with people clapping. The song is meditational and spirited. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZCKzgf3QD4M.wav"} +{"id": "ZCR7qJ2IgGI", "caption": "The song is an instrumental. The tempo is medium with ambient sounds like a sawing tool sounds, guitar rhythm, bass guitar solo and a steady drumming with various percussion hits. The song is an advertisement jingle for a tool works company. The sound quality is average with ambient room sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZCR7qJ2IgGI.wav"} +{"id": "ZE0f_S44O7M", "caption": "This is a middle eastern dance pop song. We hear a fun, and vibrant beat that's for dancing, and a vocalist who sounds charming and has a silky voice. There are string instruments for the melodic component of the instrumental. We hear high pitched falsetto backing vocals behind the lead vocalists' performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZE0f_S44O7M.wav"} +{"id": "ZEN8_GtW_UQ", "caption": "The low quality recording features an ambient song that consists of a low bells melody. It sounds calming and relaxing - like something you would listen to while meditating. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZEN8_GtW_UQ.wav"} +{"id": "ZEuY5HnECuo", "caption": "This disco song features a male voice singing the main melody. Another voice sings in harmony with the main voice. This is accompanied by programmed percussion playing a simple melody. There is a distinctive hi-hat ring at alternate strokes giving this a unique sound. The bass plays a groovy bassline using the root notes of the chords. A synth plays chords in the background. This song is at a moderate tempo. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZEuY5HnECuo.wav"} +{"id": "ZF8uHVu4Res", "caption": "This is an instrumental military march music piece. The uilleann pipes are playing the piece at a medium-to-high range. The atmosphere is epic. This piece could be used in the soundtrack of a historical drama during the scenes of a victory parade.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZF8uHVu4Res.wav"} +{"id": "ZFG9jHrLtBE", "caption": "This is a lesson recording on how to deploy certain turntable scratching techniques. There is a female voice speaking in an instructive manner. She is showing how to achieve the stab sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZFG9jHrLtBE.wav"} +{"id": "ZFg6KpT5ehU", "caption": "This song features beat boxing. There are no instruments in this song. This beat boxing melody is played using the mouth. There is no vocal melody in this song. This is an amateur recording. This song can be played in a live dance party.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZFg6KpT5ehU.wav"} +{"id": "ZFimyfPWltk", "caption": "a male vocalist sings this enthusiastic swing pop. The tempo is fast with an enthusiastic electric guitar harmony, energetic drumming, funky bass lines, keyboard harmony, emphatic vocals superimposed by an infectious Bass kazoo melody. The song is energetic, enthusiastic, youthful, fun , groovy, vivacious and chirpy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZFimyfPWltk.wav"} +{"id": "ZGfGiVauGL4", "caption": "The low quality recording features a sustained strings melody, mellow brass melody and wooden percussion one shot at the end of the loop. It sounds passionate, emotional and the sound is slowly fading in - which could mean that it is an intro section of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZGfGiVauGL4.wav"} +{"id": "ZH8VGGvZBok", "caption": "This song features synth pads being played in the background. An organ sound is layered with this sound. A synth sound plays chords in this song. There is a squeaky sound like the sound of a squeaky cycle wheel playing in the background. There are no voices in this song. There are no other instruments in this song. This song is dreamy and relaxing. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZH8VGGvZBok.wav"} +{"id": "ZHsAU90h8oc", "caption": "This audio contains a jazz composition with a saxophone taking the lead-melody supported by a string section, a e-bass and a piano playing some notes along in a higher pitch. This song may be playing in a romantic restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZHsAU90h8oc.wav"} +{"id": "ZHzhdhKEjMc", "caption": "This song contains an acoustic drum set playing a fast groove along with a bassline. A e-guitar is playing a distorted solo melody while a male voice gets backed by harmony singers before singing on alone to duck-like sounds. In the background you can hear a lot of duck-like sounds and a hammering that does not belong to the musical composition. This song may be playing as an intro for a kids TV-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZHzhdhKEjMc.wav"} +{"id": "ZJHlHb-VyDc", "caption": "The track is a mediterranean folk song and features a main melodic element which is a clean electric guitar playing a romantic melody. Eastern sounding drums play a slow tempo pattern that adds to the romantic aura of the song. The atmosphere is nostalgic and evokes romance. In the background there's a choir that sings an ambience melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZJHlHb-VyDc.wav"} +{"id": "ZJZxWLYzNh8", "caption": "This seems to be a life recording because you can hear people in the background cheering. An electric bass is playing a bluesy bassline along with the drums holding a simple steady groove. One guitar is panned to the right side of the speakers playing chords while another e-guitar is playing a melody on the left side of the speakers. Both are fairly in the background. A male mid ranged voice is singing with a little reverb on his voice. This song may be playing life at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZJZxWLYzNh8.wav"} +{"id": "ZK3bYlekfm0", "caption": "This is the recording of a harmonica lesson. There is a male instructor who is playing the harmonica and then describing his technique.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZK3bYlekfm0.wav"} +{"id": "ZK5M3DZejzk", "caption": "The commercial music features a groovy piano melody played over snare rolls in the first half of the loop. Right after, there is a drop that consists of a punchy \"4 on the floor\" kick pattern, shimmering hi hats, claps, groovy piano and wide synth lead melody. It sounds happy, fun, euphoric and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZK5M3DZejzk.wav"} +{"id": "ZKkfCOqLrT0", "caption": "This is a Russian lullaby piece with classical music elements. The male vocalist is singing at a medium-to-high pitch in an opera-like manner. The strings and the piano are playing a gentle but crestfallen melody. The atmosphere is haunting. This piece could fit perfectly in the soundtrack of a post-apocalyptic war movie or a video game of similar theme. It could also work well in the soundtrack of a drama movie or an art movie that takes place in Russia or Eastern Europe. It might also be playing in the background at a high-tier Russian cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZKkfCOqLrT0.wav"} +{"id": "ZLDQ8-8AyI4", "caption": "The low quality recording features a live performance of a blues song that consists of nasal male vocal singing over acoustic rhythm guitar chord progression and smooth double bass. There are also some crowd talking noises. It sounds groovy and kind of dull, since it is probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZLDQ8-8AyI4.wav"} +{"id": "ZLXW4ewrVpQ", "caption": "This tribal fusion song features a male voice singing the main melody. This is accompanied by percussion playing a dance beat using traditional tribal percussion instruments. The bass plays the root notes of the chords. At the end of the clip, a female voice sings a line. The theme of the song is an African dance. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZLXW4ewrVpQ.wav"} +{"id": "ZLxhZcS3Ppw", "caption": "This is a Indo-European fusion music piece. There is a mix of Carnatic music with Western sounding elements. There is a female vocalist singing at a medium-to-high pitch. The melody consists of a variety of intertwined sounds such as a piano, an electric guitar, a bass guitar and a virtual sounding brass section. The rhythmic background is provided by electronic percussive elements. There is an eccentric atmosphere to this piece. It sounds unique.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZLxhZcS3Ppw.wav"} +{"id": "ZM0imDMXuw8", "caption": "An acoustic drum is playing a groove that is not strongly connected to reggae rhythm. A e-bass and piano-keys are bringing the typical reggae backbeat while another synth sound is playing short plucks as a melody. The male voice is singing in a reggae-fashion and in a higher key. In the background you can hear a big organ sound coming in and playing along with the melody. The elements are spread along the speakers. This song may be playing with speakers riding on your bike.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZM0imDMXuw8.wav"} +{"id": "ZMd8mAKe-k8", "caption": "The track fits the carnatic music genre from India. A male vocalist sings with a sharp and nasal voice. The ambience melody is made with a sitar that has a rough and sharp sound. The atmosphere is mystical and traditional.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZMd8mAKe-k8.wav"} +{"id": "ZNGJN30LCwM", "caption": "A male vocalist sings this Christmas song. The tempo is medium with minimal instruments like keyboard harmony and steady drumming. The audio quality is inferior so the music is incoherent. This is a live performance with ambient sounds of people clapping and cheering. This is a contemporary Christmas Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZNGJN30LCwM.wav"} +{"id": "ZNGvyFsCx4g", "caption": "This is a reggae piece. There is a male vocalist singing with a Jamaican accent. An electric guitar is playing the main melody with a groovy bass guitar in the background. The rhythmic background is a simple 2/4 reggae beat being played by acoustic drums. The atmosphere is very chill. This piece could be played at beaches and summertime barbecue parties.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZNGvyFsCx4g.wav"} +{"id": "ZOGMpGQQ3FI", "caption": "This is the live performance of an electric guitarist. The chords are arpeggiated and the guitar has effects applied to it to produce a warm and rich tone. The song is calm and peaceful, and would be suitable for a tranquil afternoon walk at the park.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZOGMpGQQ3FI.wav"} +{"id": "ZOKQFjrfbpw", "caption": "This is an intricate melody played on the harpsichord. It's recorded live and has a suspenseful feeling to it. The melody is played at a medium tempo.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZOKQFjrfbpw.wav"} +{"id": "ZOzavOPeuJQ", "caption": "The low quality recording features a metal song that contains a flat male vocal, alongside harmonizing high pitched female vocal, singing over punchy kick and snare hits, shimmering hi hats, distorted bass guitar, mellow synth bells melody and groovy wide electric guitar riff. It sounds energetic, groovy, aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZOzavOPeuJQ.wav"} +{"id": "ZPK1hSPI540", "caption": "A female vocalist sings this pleasant pop song. The tempo is medium with a keyboard harmony, melodious acoustic guitar harmony, bright drumming , steel pan and the sound of birds chirping. The song is mellow, soft, pleasant, soothing, hopeful, sentimental, sweet and cheerful.this song is a Reggae Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZPK1hSPI540.wav"} +{"id": "ZQwpXl8qnnk", "caption": "This is an intimate and warm R&B instrumental. We hear fuzzy synth melodies driving the crux of the sound, and in this particular instrumental we are able to appreciate the crossovers between hip hop and R&B - as the drum beat is complex and hip hop inspired, with punchy snare action.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZQwpXl8qnnk.wav"} +{"id": "ZSGRzalgx4s", "caption": "This song features trombones playing the main melody. The trombones slide down from higher pitch notes and play tunes like elephants trumpeting. This is accompanied by a tuba playing the bass notes. A percussion player plays a simple beat in common time. This song is upbeat. This is an instrumental with no voices. This song can be played in Broadway shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZSGRzalgx4s.wav"} +{"id": "ZSHm7FdyxpQ", "caption": "This is a dubstep clip, with a high energy synth melody. The bass and percussion patterns are complex, with a kick drum that follows the cadence and timing of the fuzzy bass. The track is an electronic music track which can be heard in niche bars and clubs around the world.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZSHm7FdyxpQ.wav"} +{"id": "ZSItez9gTyY", "caption": "The low quality recording features loud church bells. It sounds like an intro of the recording, since the sound is slowly fading in. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZSItez9gTyY.wav"} +{"id": "ZTVMsW1h3bI", "caption": "This song contains someone strumming a melody on a mandolin while more people are whistling along. Then a mandolin, an e-bass and an acoustic guitar are playing a short melody in a lower key before breaking into the next part along with flutes and percussions. This song may be played outside by musicians performing.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZTVMsW1h3bI.wav"} +{"id": "ZTf9i8y5muo", "caption": "This is an industrial dance music piece. There is no singer in this piece. It has a strong and repetitive bass sound. The rhythmic background consists of a fast-paced electronic drum beat. The piece has an energetic atmosphere. It could be played at nightclubs or dance clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZTf9i8y5muo.wav"} +{"id": "ZU6sI1Plq50", "caption": "The low quality recording features a music box bell melody playing over soft water flowing sound effects. It sounds like a lullaby - relaxing and calming. The recording is also noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZU6sI1Plq50.wav"} +{"id": "ZUcHBeueBww", "caption": "A vocalist sings this cheerful Christmas carol. The tempo is medium with an animated piano accompaniment, steady drumming, cymbals, tambourine beats, steady bass line and rhythmic acoustic guitar and melodic backup vocals;. The song is happy, fun, festive, celebratory, wishful, peppy and nostalgic. This song is a Christmas Carol.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZUcHBeueBww.wav"} +{"id": "ZUg7rRpFGvA", "caption": "The low quality recording features a shofar horn siren. It is so loud that the audio is distorting. The recording itself is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZUg7rRpFGvA.wav"} +{"id": "ZUkh168Nyus", "caption": "A male vocalist sings this smooth Soul melody. The tempo is medium with a mellow piano accompaniment, steady drum machine beats, atmospheric synthesiser and subtle bass with backup vocals. The song is soft, ambient, passionate, emotional, mellifluous ,sentimental and warm. This song is a contemporary R&B/Soul.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZUkh168Nyus.wav"} +{"id": "ZVMIk3xYaYo", "caption": "This song features the sound of synth pads. The synth is playing one chord and the volume slowly swells. There are no other instruments in this song. There is no voice in this song. This song can be played in a movie sequence when a person is actively searching for something in the dark.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZVMIk3xYaYo.wav"} +{"id": "ZV_ZbmjPpkw", "caption": "Someone is strumming chords on an e-guitar. The sound is distorted and you can also hear the clean sound of the guitar in the background. This song may be playing guitar at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZV_ZbmjPpkw.wav"} +{"id": "ZVvX2-ldhvY", "caption": "solo acoustic nylon string guitar playing in a fingerstyle Brazilian bossa nova style.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZVvX2-ldhvY.wav"} +{"id": "ZX2fVPmUidA", "caption": "The low quality recording features a live performance of a country song and it consists of harmonizing male vocals singing over groovy steel guitar, groovy mandoline melody and groovy acoustic rhythm guitar chords. There are some crowd chattering noises in the background. It sounds passionate, happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZX2fVPmUidA.wav"} +{"id": "ZX7EzqMBjfo", "caption": "This is a melodic composition on the organ. The song itself feels soothing and calming. We hear light arpeggios played which would be suitable for a lullaby or a fairytale story.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZX7EzqMBjfo.wav"} +{"id": "ZYUAY6EN05Q", "caption": "Cheery and joyous music which would fit well in a musical. Complex vocal arrangements with female background vocals, male and female lead vocalists singing in unison one octave apart. Piano, electric bass, and orchestral accompaniment drive the compound meter.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZYUAY6EN05Q.wav"} +{"id": "ZZrvO__SNtA", "caption": "This audio contains someone playing a dreamy melody on the harp. This audio is an amateur recording. You can hear white noise from the recorder. This song may be playing in an anime movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZZrvO__SNtA.wav"} +{"id": "Z_0Ta-m_-hU", "caption": "This music is an intense instrumental.The tempo is fast with vigorous violin harmony that slows down to the accompaniment of a grim Piano harmony. The music is a Ritardando and has a grim, dark, intense,serious,bleak, dreary, and dangerous vibe to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z_0Ta-m_-hU.wav"} +{"id": "Z_HT-d8W1_M", "caption": "This song is a Sitar instrumental. The tempo is slow with a beautiful violin orchestra accompaniment and keyboard harmony. This is an indo western piece with the musician playing a mellifluous lead on a sitar accompanied with a harmonic violin composition. The medley is ethereal, beautiful, peaceful, serene , calming, soothing, pleasing and ethereal.", "audio": "/zhanghaomin/datas/musiccap/music_data/Z_HT-d8W1_M.wav"} +{"id": "ZaUaqnLdg6k", "caption": "This song contains electronic drums that sound overdriven with an aggressive kick and clap sounds as snare. A male choir sample is singing a chord melody with breaks in-between. The whole thing sounds urban and epic as if something heroic is happening.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZaUaqnLdg6k.wav"} +{"id": "ZahBai58_Ec", "caption": "This is a latin folk piece performed at a home setting. There is a male vocalist singing off-key in a shout-like manner. An accordion and a ukulele are providing the melodic background for the piece. A pair of maracas is being played for the rhythmic background. The piece has a joyful atmosphere. The instrumentals can be used for sampling to put them in a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZahBai58_Ec.wav"} +{"id": "ZbdmiykoJm8", "caption": "The music features a female voice that sings in a theatrical style, similar to Broadway musicals. The bass guitar and drums blend together and play a light accompaniment. A piano can also be heard contributing to the overall accompaniment. A string section plays a long note melody that transitions into playing in unison with the singer's melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZbdmiykoJm8.wav"} +{"id": "Zbmm_hXcrA0", "caption": "The low quality recording features a pop song that consists of suspenseful synth, repetitive piano melody, filtered synth bass and sustained strings melody located in the left channel of the stereo image. It sounds uplifting, soulful and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zbmm_hXcrA0.wav"} +{"id": "Zc4rX7nbRW4", "caption": "The low quality recording features a distorted electric guitar solo melody playing. At the end of the loop, there is a short pedal tap sound. The recording is a bit noisy, but it sounds passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zc4rX7nbRW4.wav"} +{"id": "ZdqPnWEANuI", "caption": "This song contains a male voice speaking that is pitched down low with a ping pong delay changing to both sides of the speakers. A guitar is playing a neo-soul melody while a digital drum is playing a simple groove. This song may be playing while sitting in the car cruising.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZdqPnWEANuI.wav"} +{"id": "ZfR3_QJF8f4", "caption": "The excerpt features an acoustic guitar repeating the same note. You can hear two strings being plucked almost at the same time. I believe this is a recording of someone tuning their guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZfR3_QJF8f4.wav"} +{"id": "ZfSlWX1C8yY", "caption": "Someone is playing a didgeridoo along with a percussive sound. You can hear people talking in the background. This is an amateur recording. This song may be played live by someone that is busking on the streets.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZfSlWX1C8yY.wav"} +{"id": "ZgcZPBUKxd8", "caption": "A digital drum is playing a simple groove with a kick on every beat. Beeping tones that seem to come from a synthesizer come in along with the snare hit. A guitar-like sound is being played, serving as bassline. A very far sounding deep voice is playing on the right side of the speakers with a lot of reverb and delay. This song may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZgcZPBUKxd8.wav"} +{"id": "ZgooDijn2as", "caption": "A male vocalist sings this energetic song. The tempo is fast with accordion harmony, funky bass lines, vigorous drumming,rhythmic acoustic guitar and keyboard harmony. The audio is muffled making it difficult to hear the other elements in the song. This song is a live performance as there are sounds of clapping, cheering and people murmuring. This song is a vibrant,vivacious,bright, punchy, and energetic Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZgooDijn2as.wav"} +{"id": "ZhafwFYgltI", "caption": "The song is an instrumental soundtrack for a video game. The song tempo is medium with a string section,aging, cello playing a tense lower harmony, steady drumming rhythm, and ambient sounds like a bull galloping, man screaming and hood steps. The music is a soundtrack for a video game and has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZhafwFYgltI.wav"} +{"id": "Zhurw43-Y1g", "caption": "A male vocalist chants this captivating harmony. The tempo is slow with electronic music, and vocals sung melodiously to create this hypnotic music. The music is calming, soothing, healing, meditative, psychedelic, trance like, hypnotic and ethereal. The instruments used could be glass harp, a low pitched string instrument and choral vocal chanting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zhurw43-Y1g.wav"} +{"id": "ZiHlhUvmgzQ", "caption": "This is a bluegrass music piece. Two male vocals are singing melodically in the lead. The tune is played by a rich chordophone background composed of the fiddle, the mandolin and the acoustic guitar. The atmosphere of the piece is joyful and nostalgic. It has a steady tempo. The piece could be used in the soundtrack of a movie or a TV series taking place in rural USA, especially in the scenes where there is some sense of yearning. It could be playing in the background at an American diner or a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZiHlhUvmgzQ.wav"} +{"id": "ZkGQhIbEDrs", "caption": "The low quality recording features piano chords, followed by echoing plucked strings melody and smooth bass guitar. It sounds creepy, haunting and suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZkGQhIbEDrs.wav"} +{"id": "ZkfKOLp5SxU", "caption": "Someone is playing a very fat drum with a slightly open hi hat along with other people playing percussion with a lot of snare hits and a bass sound playing on every beat along with the kick. A keyboard is playing string chords. A male voice is singing/shouting with delay and reverb. This song may be playing at a celebration event.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZkfKOLp5SxU.wav"} +{"id": "ZkmtfBzpQlI", "caption": "This song contains a male voice rapping over an instrumental containing a drumbeat with a sub bass. A brass sample is playing a melody also used as a rhythmic element. An organ is panned to the right side of the speakers. Other sound samples such as a male voice singing a melody are being used. This song may be playing loud when having or needing a good elevating mood.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZkmtfBzpQlI.wav"} +{"id": "Zlbo8ygfPSM", "caption": "This is a pop-sounding jingle at the background of an instructive video. There is an electric guitar playing the main theme while the bass line is being played by a synth bass. In the rhythmic background, a very basic 4/4 beat is being played on the electronic drums. A ping sound effect signifies the end of the instruction in the video. The atmosphere is very generic and common-sounding. This piece could be used as a jingle in advertisements and tutorial videos.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zlbo8ygfPSM.wav"} +{"id": "ZleHXDirD58", "caption": "This symphonic song features an orchestra playing a variety of instruments. The main melody is played on trumpets and violins. This is accompanied by the brass section and horn section of the orchestra. Clarinets play in harmony with the violins and trumpets. A xylophone kind of instrument plays bell sounds with the same melody as the main instruments. Cellos play the bass part of the song. This is accompanied by a bass drum playing a steady count. A drum kit plays the percussion part with a marching beat. There are no voices in this song. This is an instrumental song. The feel of this song is uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZleHXDirD58.wav"} +{"id": "ZmgkpmzvL6c", "caption": "The low quality recording features a smooth buzzy bass guitar and chill, electric guitar melody playing. It is noisy and the stereo image is unbalanced, as the bass guitar is leaning toward the left channel. It sounds easygoing, chill and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZmgkpmzvL6c.wav"} +{"id": "Zmtw8tP-KFo", "caption": "The Low Quality recording features a synth key melody. It sounds suspenseful and intense. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zmtw8tP-KFo.wav"} +{"id": "ZnBvXFDWpWo", "caption": "Instrumental modern hip hop beat featuring a clap, low kick, and record scratching with virtuosity.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZnBvXFDWpWo.wav"} +{"id": "Zo9xROGuV3k", "caption": "Someone is playing an evolving rhythm on various percussion instruments. This seems to be a professional piece with a lot of dynamics. This song may be playing as a part of an orchestra performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zo9xROGuV3k.wav"} +{"id": "ZoAfkpmztww", "caption": "This audio mostly contains frighting sounding animal noises a male voice streaming and foreground noises that seem to belong to a movie. These noises get enhanced by orchestral cinematic short entries to underline the noises with more dramatic and danger.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZoAfkpmztww.wav"} +{"id": "ZocCGcJcGJE", "caption": "The low quality recording features a wide high pitched synth pad and wide low, sustained strings chords playing in the background, after which there is a thunderstruck sound effect, followed by male grunting and crowd yelling sound effects. It sounds suspenseful and intense - like a movie scene would.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZocCGcJcGJE.wav"} +{"id": "Zon9WGTwAME", "caption": "This is the background music for a fighting video. There is a faint track in the background. The use of strings and an electronic drum beat can be heard in this track. There are numerous sound effects such as an ominous laughing track, jumping and fighting sounds. The track can be used to lift samples from to use on a soundboard.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zon9WGTwAME.wav"} +{"id": "Zq92ED3IvLQ", "caption": "This song contains acoustic drums playing a simple hip hop groove along with a e-bass and e-guitars playing a simple repeating line. A male voice with a deeper voice is rapping on top of it. The song may be playing while having a BBQ in the garden with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zq92ED3IvLQ.wav"} +{"id": "ZqnbgQeeRbM", "caption": "Acoustic guitars are strumming chords while male voices are singing along. There are a lot of background noises of people talking. The recording is of very poor quality. This song may be playing at a local small town event.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZqnbgQeeRbM.wav"} +{"id": "Zs3arUuPciY", "caption": "Someone is playing tuned glass-bowls: The piece sounds mysterious, like classical music and with a lot of reverb that is overpowering the speakers. This is an amateur recording. This song may be played at a talent show.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zs3arUuPciY.wav"} +{"id": "ZsmfIMEzrQs", "caption": "The low quality recording features harmonizing mixed vocals singing over groovy bass, shimmering cymbals, soft snare hits, funky guitar melody and bright brass melody. The recording is very noisy, in mono, with some crackles in it and it sounds funky and addictive - thanks to those vocals. Sounds like something you would hear in clubs during the 60s and 70s.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZsmfIMEzrQs.wav"} +{"id": "ZsmxO0wnqdQ", "caption": "This music is instrumental. The tempo is medium with an electronic xylophone melody. The audio is of inferior quality and it sounds like it is being played outdoors. There are ambient nature sounds like birds chirping, a car engine, a loud thud and people\u2019s voices.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZsmxO0wnqdQ.wav"} +{"id": "Zt8x7tvP9Qs", "caption": "This song contains a thick acoustic drum sample playing a slow hiphop groove with a simple bassline. A female voice sample is singing while a male voice is rapping. his voice sounds doubled. This song may be playing in an urban shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zt8x7tvP9Qs.wav"} +{"id": "ZtcHktwEfAU", "caption": "The low quality recording features a folk rock song that consists of a sustained bagpipe melody and sustained synth bass, followed by funky synth keys and punchy toms. It sounds suspenseful and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZtcHktwEfAU.wav"} +{"id": "Ztlcnd14Kn4", "caption": "A male singer sings this rock melody with backup singers in vocal harmony. The song is fast tempo with a strong drumming rhythm , percussive bass line, amplified guitar playing lead. The song is energetic and romantic. The song is a retro rock song with average audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Ztlcnd14Kn4.wav"} +{"id": "ZwLfj7tvpdc", "caption": "A female singer sings this passionate melody with backup singers in vocal harmony. The song is medium tempo with a percussive bass line, groovy drumming rhythm, keyboard accompaniment and other percussive hits. The song is a retro pop love song.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZwLfj7tvpdc.wav"} +{"id": "ZwfzBagtpV0", "caption": "This song is a Latin duet. The tempo is fast with an ensemble of Latin instruments like Spanish guitar accompaniment, bright drums, congas and bongos rhythm, trombone and trumpets playing an animated melody and a whistle like wind instrument. The song is vibrant, energetic,engaging, upbeat and youthful. This song is Latin pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZwfzBagtpV0.wav"} +{"id": "Zxyfhub6nV4", "caption": "This audio holds a church bell ringing loudly with a lot of sustain. The sound is so loud that the recorded audio clips and overdrives the speaker. The audio file is of very poor recording quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zxyfhub6nV4.wav"} +{"id": "Zy4uiiy0qgA", "caption": "This pop song features a male voice singing the main melody. This is accompanied by percussion playing a simple beat in common time. A choir sings vocables in the background. A piano plays fills in between lines using jazz sequences. A bass plays the root notes of the chords. Strings and flutes can be heard playing along with the voice on the second bar in an ascending run. This song has an upbeat mood. The theme of this song is about friendship. This song can be played in a drama movie about friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zy4uiiy0qgA.wav"} +{"id": "Zy_YSROQmlE", "caption": "This is a Croatian pop music piece. There is a male vocalist singing melodically in the lead. The acoustic guitar is playing a simple tune with the bass guitar playing in the background. The rhythm is played by a basic electronic drum beat with an acoustic sound. There is a lively atmosphere to this piece. This piece could fit well in the soundtrack of a romantic comedy movie that takes place in Croatia.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zy_YSROQmlE.wav"} +{"id": "Zz1Bz1a7yPE", "caption": "The music features a group of female voices singing a melody in unison. The instrumental consists of only percussion drums, African percussion drums to be precise. A shaker can also be heard sounding on every beat. In the background one can hear water sounds. The overall atmosphere is cheerful and uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/Zz1Bz1a7yPE.wav"} +{"id": "ZzyWbehtt0M", "caption": "The low quality recording features a country blues song that consists of fruity male vocal singing over groovy electric guitar melodies, groovy bass, shimmering cymbals, mellow snare, soft kick hits and clapping. The recording is a bit noisy, as it is vintage, and it sounds passionate, groovy, uptempo and cool.", "audio": "/zhanghaomin/datas/musiccap/music_data/ZzyWbehtt0M.wav"} +{"id": "_-kssA-FOzU", "caption": "The low quality recording features footsteps, birds chirping, distant traffic and wind sound effects. At the very end there is a suspenseful, low, widely spread pad chord. It sounds like it is a sound for some kind of video, or movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/_-kssA-FOzU.wav"} +{"id": "_0-2meOf9qY", "caption": "This music is an electronic guitar instrumental. The tempo is slow with a melancholic , resounding harmony on the guitar. It is mellow, soft, poignant, sentimental and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/_0-2meOf9qY.wav"} +{"id": "_1woPC5HWSg", "caption": "The low quality recording features a live performance of a rock song and it consists of a distorted male vocal singing over repetitive electric guitar melody, groovy bass and energetic drums. It sounds crushed, distorted, loud, but it is barely audible, as it was recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/_1woPC5HWSg.wav"} +{"id": "_2P_EJsnBls", "caption": "The low quality recording features a passionate male vocal, alongside harmonizing mixed vocals, singing over acoustic rhythm guitar, accordion melody and groovy bass. It sounds passionate and joyful. The recording is noisy and in mono - the sound is coming from the right channel only.", "audio": "/zhanghaomin/datas/musiccap/music_data/_2P_EJsnBls.wav"} +{"id": "_2wFjBoreaY", "caption": "A male vocalist sings this energetic Punjabi folk song. The tempo is medium fast with an infectious tabla and Dhol percussive beat, ektara rhythm and a funky keyboard accompaniment. The song is lively, spirited, cheerful, simple, happy, playful, enthusiastic, vivacious with a festive, celebratory vibe and dance groove. This song is a Festive Punjabi Folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/_2wFjBoreaY.wav"} +{"id": "_3GnNMrDuCs", "caption": "This audio contains someone playing a piece on cello ranging from the low register up into the higher register. This song may be playing during a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/_3GnNMrDuCs.wav"} +{"id": "_3OlK_1yQOk", "caption": "The Pop song features harmonizing vocals singing over energetic crash cymbals, groovy bass guitar, wide electric guitar melody, punchy snare and soft kick hits. There is a short drum break at the very beginning of the loop. It sounds happy, nostalgic and euphoric, as it gives off vibes of a Christmas song.", "audio": "/zhanghaomin/datas/musiccap/music_data/_3OlK_1yQOk.wav"} +{"id": "_43OOP6UEw0", "caption": "This is a rap music piece played behind a rollerskating video. The sound of the skaters can be heard faintly throughout the recording. There is a male voice rapping at the forefront while other voices can be heard singing melodically in the background and ad-libbing occasionally. There is a mild keyboard playing the tune while a loud electronic drum beat is playing the rhythm. The atmosphere of this piece is groovy and urban.", "audio": "/zhanghaomin/datas/musiccap/music_data/_43OOP6UEw0.wav"} +{"id": "_5fwnVeZbvI", "caption": "A male singer sings this Telugu folk song. The tempo pop is medium with a tambourine, tabla and other south Indian percussion playing steadily, along with string instrument harmony. The song is a folk tune and probably a courtship song. The song has loud sound effects which are funny. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/_5fwnVeZbvI.wav"} +{"id": "_5w5TVK5B90", "caption": "This song contains someone playing a transverse flute in a very high pitch. Breathing sounds can be heard. This song may be playing in a live orchestra solo.", "audio": "/zhanghaomin/datas/musiccap/music_data/_5w5TVK5B90.wav"} +{"id": "_6C2ffY_-mc", "caption": "The low quality recording features a quiet bowl resonating sounds and even though the recording is so noisy and in mono, it is still calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/_6C2ffY_-mc.wav"} +{"id": "_78P-0zWJtg", "caption": "The low quality recording features a live performance of fruity male vocal singing over funky piano melody and beat played on playback that consists of punchy snare and kick hits, shimmering hi hats and smooth bass. The crowd is also singing along, harmonizing with the lead vocal. It sounds emotional and groovy, even though the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/_78P-0zWJtg.wav"} +{"id": "_8OIugVSFeE", "caption": "A male singer sings Arabic vocals with backup singers in vocal harmony. The song is medium tempo with a steady drumming rhythm, percussive bass line, keyboard accompaniment and percussive hits. The song is an Arabic dance song.", "audio": "/zhanghaomin/datas/musiccap/music_data/_8OIugVSFeE.wav"} +{"id": "_94ra2KoZGo", "caption": "This music is a lively harmonica instrumental. The tempo is medium with a spirited melody. The music is lively, clear, energetic, vibrant and breezy with a male voice at the end of the audio clip. This is probably a Harmonica tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/_94ra2KoZGo.wav"} +{"id": "_9OUh0uwDec", "caption": "The low quality recording features an afrobeat song that consists of an echoing female vocal, with autotune effect on, rapping over energetic cymbals, wide percussion rolls, stab buzzy bass, shimmering hi hats and short strings stabs. At the end of the loop, there is a flat male vocal talking over the beat. It sounds energetic and like something you would easily dance to.", "audio": "/zhanghaomin/datas/musiccap/music_data/_9OUh0uwDec.wav"} +{"id": "_ACyiKGpD8Y", "caption": "The song is an instrumental. The tempo is medium with bagpipers playing in unison, and rhythmic percussion play. The song is emotional and pays tributes to the fallen in remembrance and homage. The song has bad audio quality with ambient room noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/_ACyiKGpD8Y.wav"} +{"id": "_ALGXHquYkM", "caption": "This music is instrumental. The tempo is medium with a melodic steel pan harmony. The audio quality however is inferior and amateur,so the music is muddled. There are ambient sounds of breeze and people talking , indicating that this is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/_ALGXHquYkM.wav"} +{"id": "_AVegKwklcg", "caption": "This is a bluegrass cover of an originally heavy metal music piece. There is a male vocalist singing melodically in the lead. The tune is being played by the banjo, the mandolin and the acoustic guitar while the bass guitar is playing in the background. The atmosphere is playful and there is a rural feel to the piece. This piece could be used in the soundtrack of a comedy movie that takes place in the rural parts of the USA.", "audio": "/zhanghaomin/datas/musiccap/music_data/_AVegKwklcg.wav"} +{"id": "_AjXY9cHCxA", "caption": "Here we have a live recording of a simple motif being played on a contra alto clarinet, which has a deeper tone than other clarinets. The player coughs at the beginning of the recording, mumbles a few words softly, and then plays a simple slow motif.", "audio": "/zhanghaomin/datas/musiccap/music_data/_AjXY9cHCxA.wav"} +{"id": "_DHMdtRRJzE", "caption": "This audio contains someone playing a complex drum groove with fill-ins on cymbals and toms. An e-guitar is playing a dangerous sounding melody along with a distorted e-guitar playing a melody in a higher key and another one in a lower key. This song may be playing live at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/_DHMdtRRJzE.wav"} +{"id": "_G3lYKAITu8", "caption": "This audio contains people playing rhythms and melodies on bells with sticks. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/_G3lYKAITu8.wav"} +{"id": "_GQnXfIGNKY", "caption": "This is a live performance of an alternative R&B music piece. There is a female vocalist singing in a seductive manner in the lead. Later on, a male vocalist starts rapping. There is a groovy bass line in the background. The DJ is scratching the turntable. The rhythmic background is provided by an R&B acoustic drum beat. The atmosphere is sensual and the sound is urban. Sounds of the crowd cheering can be heard in the recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/_GQnXfIGNKY.wav"} +{"id": "_GjHL0FkYoY", "caption": "The low quality recording features a Soca song that features repetitive flat male vocal singing over wide male background grunts, repetitive buzzy synth, punchy kick, syncopated snare and wooden percussion. It sounds energetic and uptempo.", "audio": "/zhanghaomin/datas/musiccap/music_data/_GjHL0FkYoY.wav"} +{"id": "_GxqvILlmAw", "caption": "This is a dubstep piece. The rhythmic background consists of a hard-hitting electronic drum beat. A high-pitched synth is playing the main melody while a choir sample is played in the background for the chords. There is a high energy atmosphere in the piece. It could be played at nightclubs. This piece could also take place in DJ setlists.", "audio": "/zhanghaomin/datas/musiccap/music_data/_GxqvILlmAw.wav"} +{"id": "_HXMIdSiOMA", "caption": "The music excerpt features a kind of vinyl scratch solo. At one point a male voice intervention can be heard that's similar to the sound one makes when he's being punched in the stomach. In the background a drum beat runs in loop.", "audio": "/zhanghaomin/datas/musiccap/music_data/_HXMIdSiOMA.wav"} +{"id": "_HfaIP9e0ww", "caption": "This is an instrumental cover of a ballad piece. The harp is gently playing the melody with improvisational touches differing from the original version. There is a calming and soothing atmosphere to this piece. This music could be playing in the background at a hotel or a spa resort.", "audio": "/zhanghaomin/datas/musiccap/music_data/_HfaIP9e0ww.wav"} +{"id": "_IP6zlayY7k", "caption": "This is an amateur flute cover of a pop music piece. The flute is playing a gentle melody in the major key. There is a backing track that has a mellow acoustic guitar playing. The atmosphere is calming and easygoing. Although the audio quality is not that great, this piece could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/_IP6zlayY7k.wav"} +{"id": "_IkLUOsNHAA", "caption": "In this piece a timpani takes a strong loud position before other orchestral instruments are entering the musical composition. Brasses, flutes and strings are playing a rising rhythmical melody creating tension. This song may be playing in a classical chamber concert or in a scene of a superhero movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/_IkLUOsNHAA.wav"} +{"id": "_JTHtcRHxnw", "caption": "This audio contains the sound of bells ringing in different rhythm, tempo and pitch. This is an amateur recording. This may be playing in the center of a village.", "audio": "/zhanghaomin/datas/musiccap/music_data/_JTHtcRHxnw.wav"} +{"id": "_KGUrOb1qgU", "caption": "This is the recording of a gear showcase jam. There is an overdriven electric guitar playing a groovy solo with the amplified reverb effect. There is a crunchy sound. The piece can be used as the jingle of an advertisement. It could also be used for lifting electric guitar samples to be used in a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/_KGUrOb1qgU.wav"} +{"id": "_KYo_89lgf0", "caption": "The Low quality recording features a widely spread, weird mouth noises, foot stomping in the right channel and aggressive male breathing and claps in the left channel of the stereo image. There is a short accordion melody at the very beginning of the loop. It sounds very weird and aggressive, almost uncomfortable.", "audio": "/zhanghaomin/datas/musiccap/music_data/_KYo_89lgf0.wav"} +{"id": "_KaRkSyELy4", "caption": "The low quality recording features a tutorial where a fruity male vocalist is talking in-between electric guitar chords. There is a very buzzy guitar amp in the background and the recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/_KaRkSyELy4.wav"} +{"id": "_MjbdUaJcik", "caption": "The song is an instrumental. The tempo is medium with a brass section including trumpets, trombones and tubas playing in an instrumental harmony. The song is emotional and spirited. The song is western classical music piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/_MjbdUaJcik.wav"} +{"id": "_R9Ma9rjEWg", "caption": "Several ukuleles are playing the same strumming melody together with an acoustic guitar. Someone is playing a shaker slightly offbeat along to male and female voices singing. In the background you can hear noises of a public space. This song may be playing at a school presentation.", "audio": "/zhanghaomin/datas/musiccap/music_data/_R9Ma9rjEWg.wav"} +{"id": "_RLsXrr0fQo", "caption": "The low quality recording features a folk song being covered by passionate male vocal and groovy acoustic guitar melody. It sounds uplifting and a bit harsh, muddy and unbalanced as far as the stereo image goes.", "audio": "/zhanghaomin/datas/musiccap/music_data/_RLsXrr0fQo.wav"} +{"id": "_Ra1Y6K7nSs", "caption": "This reggae song features male voices singing the main melody in harmony. The clip starts off with the sound of a chalk writing on a board. This is followed by a percussion roll. The voices start singing the main melody. This is accompanied by percussion playing a reggae beat. The bass plays a reggae style bassline. The keyboard plays staccato chords in a reggae rhythm. The mood of this song is happy. This song can be played in a birthday scene in a movie when a family is on a holiday on an island.", "audio": "/zhanghaomin/datas/musiccap/music_data/_Ra1Y6K7nSs.wav"} +{"id": "_Rpn2FUAUgY", "caption": "The low quality recording features a sustained string melody, followed by woodwind and mellow marimba melodies. It sounds emotional, passionate and sad - like something you would hear in the movies, as the background music.", "audio": "/zhanghaomin/datas/musiccap/music_data/_Rpn2FUAUgY.wav"} +{"id": "_RrA-0lfIiU", "caption": "This is a live acoustic performance of an Irish folk music piece. The chords of the piece are being played by two acoustic guitars in the background while a violin is playing the main theme which is in medium-to-high range. Since the piece is being played at a pub, the sounds of the place can also be heard in the recording. There is a jovial atmosphere. This piece can be played at Irish pubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/_RrA-0lfIiU.wav"} +{"id": "_Slo8QXYOp8", "caption": "The song track is instrumental. The tempo is medium with temple bells being played to create two distinct tones with long vibrations creating clear overtones. The soundtrack is calming and deeply religious. The audio track quality is poor with ambient environment noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/_Slo8QXYOp8.wav"} +{"id": "_VmCPixy9GQ", "caption": "Ambient music full of textures. Present are a slow descending glissando from a high-pitched metallic screech, a bowed string bass, atmospheric reverb. The mood is foreboding and ominous. Good for an unsettling horror soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/_VmCPixy9GQ.wav"} +{"id": "_WYwB1qRgLM", "caption": "Orchestra music with pizzicato strings, bowed bass and cello, and a clave with reverb. The music feels stationary, like a vamp, with a sense of waiting.", "audio": "/zhanghaomin/datas/musiccap/music_data/_WYwB1qRgLM.wav"} +{"id": "_XrolyeJXDw", "caption": "The low quality recording features a classical song that consists of a wide strings melody, low brass and woodwinds melody. It sounds suspenseful and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/_XrolyeJXDw.wav"} +{"id": "_b-7P-XsnUI", "caption": "This is a classical music waltz piece played on a glass harp instrument. The melody is being played on the smaller glasses at a higher pitch while the rhythm is being played on the bigger glass at a medium pitch. The piece is being played at a cathedral which gives a nice resonance and natural reverb effect. The piece has a unique character. It can be played in the soundtracks of children's movies/TV shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/_b-7P-XsnUI.wav"} +{"id": "_b5n-mny1lM", "caption": "This is an alternative rock piece. There is a male vocal singing gently and melodically at the forefront in the medium range, while a male back vocal can be heard singing at a higher pitch. A clean sounding electric guitar is playing a mellow tune with a bass guitar holding the root notes in the background. The acoustic drums are playing a basic rock beat. There is an easygoing aura to it. This piece could be used in a food/beverage commercial. It could also be playing at a sports venue.", "audio": "/zhanghaomin/datas/musiccap/music_data/_b5n-mny1lM.wav"} +{"id": "_cf0WYQcNvk", "caption": "This is a religious music piece. There is a female vocalist singing melodically in the Portuguese language with a Brazilian accent. The piano and the violin are playing a mellow tune. The atmosphere is spiritual. Although the words give the impression it is a Christian gospel, the footage in the video belongs to the site of a syncretic movement, so one should not mistakenly take it as a gospel piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/_cf0WYQcNvk.wav"} +{"id": "_cg_IfaD1C0", "caption": "The low recording features a low, buzzy didgeridoo tone. It is mono and noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/_cg_IfaD1C0.wav"} +{"id": "_dF-ZGquRNY", "caption": "This song features a theremin being played. There is no melody to this song. There is no other instrument in this song. This sounds like the sounds of a computer on a spaceship. There is no voice in this song. This song can be played in a movie featuring an alien spaceship.", "audio": "/zhanghaomin/datas/musiccap/music_data/_dF-ZGquRNY.wav"} +{"id": "_fKntnlIYTQ", "caption": "The low quality recording features a live performance of a big band that consists of shimmering hi hats, steel pan melody, punchy snare, soft kick hits, bright brass melody, groovy double bass melody and cowbell percussion. The recording is a bit noisy and it sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/_fKntnlIYTQ.wav"} +{"id": "_gWEpDgPAho", "caption": "A male voice is singing kind of a calming lullaby in a higher pitch while you can hear sounds of painful screaming and crying that seem not to belong to the song. This is an amateur recording and not of the best audio-quality. This song may be playing in a cruel movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/_gWEpDgPAho.wav"} +{"id": "_h2rFVPCSPE", "caption": "The music excerpt features a male and a female voice singing the same melody in unison. Accompanying the singers is a sitar that plays the same note throughout - what is called a harmonic pedal. The atmosphere points towards a kind of meditation through repetitive singing, a kind of channeling state.", "audio": "/zhanghaomin/datas/musiccap/music_data/_h2rFVPCSPE.wav"} +{"id": "_hYBs0xee9Y", "caption": "The low quality recording features a passionately played electric guitar solo melody with a chorus pedal effect on. The recording is in mono and it is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/_hYBs0xee9Y.wav"} +{"id": "_kPmYc1nXuQ", "caption": "This relaxing song features the sound of pads in the background. A guitar strums a chord first then plays arpeggiated chords. At the end of the song, a piano chord is played. A wave-like synth plays one continuous note in the background. The bass plays the root notes of the chords and the note lingers. The mood of this song is relaxing. This song can be played in a spa.", "audio": "/zhanghaomin/datas/musiccap/music_data/_kPmYc1nXuQ.wav"} +{"id": "_lq8nEXh064", "caption": "The low quality recording features a lullaby that consists of soft bells melody. It sounds like a music box melody and it is relaxing, passionate and mellow.", "audio": "/zhanghaomin/datas/musiccap/music_data/_lq8nEXh064.wav"} +{"id": "_m-N4i-ge28", "caption": "The R&B song features a passionate male vocalist singing over a wide funky electric guitar melody, smooth bass guitar, punchy kick and snare hits, shimmering hi hats, snappy rimshots and soft crash cymbals. The rimshots are present in the first half of the loop, while a more energetic second part of the loop consists of punchy snare hits. It sounds emotional and heartfelt, as the vocal is slightly distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/_m-N4i-ge28.wav"} +{"id": "_mQ6KuA2p6k", "caption": "This is a remix of an Indian folk music piece. There is a male vocalist singing melodically and passionately. The rhythmic background is full of percussive elements that were emphasized by the use of electronic drums. The atmosphere is lively and jovial. This piece could be played in dance parties and also in contemporary dancing courses as an accompaniment piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/_mQ6KuA2p6k.wav"} +{"id": "_miAGxDX5FM", "caption": "This jazz song features the main melody played on a reed instrument and a guitar in unison. The melody is an ascending pattern of three notes per beat. This is accompanied by percussion playing a simple beat ending on an extended drum roll. The bass plays a descending run followed by an ascending run. The piano plays jazz chords in the background. There are no voices in this instrumental song. This song can be played in a luxury bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/_miAGxDX5FM.wav"} +{"id": "_n3r2inlqBc", "caption": "This audio contains videogame-sounds, sound-effects. You can hear water running/dripping, clicking sounds and other noises that sound like being in a big cave. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/_n3r2inlqBc.wav"} +{"id": "_n9boKzVRhs", "caption": "The low quality recording features a mono recording located only in the right channel of the stereo image. It consists of at least brass section melody, shimmering cymbals and melodic female vocals. There are some crowd chattering noises too, but it sounds fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/_n9boKzVRhs.wav"} +{"id": "_nrz_BawPMY", "caption": "A female vocalist sings this delicate harmony. The tempo is slow with an organ accompaniment. It is soft, mellow, meditative, enigmatic, mysterious, melancholic and haunting. This song is a Modern Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/_nrz_BawPMY.wav"} +{"id": "_oNLyxk08oA", "caption": "Here we have a solo bass flute player. The music sounds mystical, like in a fantasy movie about dragons and fairies. There is reverb applied to the sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/_oNLyxk08oA.wav"} +{"id": "_pU2KbHMN4Q", "caption": "This song contains an acoustic drum playing and comes to an end. Then a violin is playing the main melody together with a bass horn and other brass instruments in a higher register. A xylophone is also playing the melody in a higher octave. This song may be playing during a funny magic show.", "audio": "/zhanghaomin/datas/musiccap/music_data/_pU2KbHMN4Q.wav"} +{"id": "_qP21HqOmA0", "caption": "The low quality recording features a detuned synth lead melody played on some kind of kids toy. It sounds very digital, like an 8bit melody and the recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/_qP21HqOmA0.wav"} +{"id": "_qf0UiKtB3k", "caption": "This is a classical music piece. The piece is being performed on a harpsichord. There is a sophisticated aura to it. The piece has a medieval sound. It would fit perfectly in the soundtrack of a historical drama movie that takes place in the medieval era. It could also work well as the opening theme for a literature YouTube channel.", "audio": "/zhanghaomin/datas/musiccap/music_data/_qf0UiKtB3k.wav"} +{"id": "_u2cNlW5DxQ", "caption": "The low quality recording features a cover of a rock song and it consists of a funky acoustic bass guitar solo melody played aggressively. It sounds groovy and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/_u2cNlW5DxQ.wav"} +{"id": "_vwBe9ZXWXE", "caption": "This clip is a live recording of a complex and rapid piece being played on the trumpet. The trumpet is very high pitched and the piece ascends and descends rapidly in succession.", "audio": "/zhanghaomin/datas/musiccap/music_data/_vwBe9ZXWXE.wav"} +{"id": "_wyELLqwF3w", "caption": "This is an instrumental piece with a harmonica as the main lead melodic instrument. High pitched, wobbly sounds are played on the harmonica and contrasted by a deep and full acoustic guitar on which arpeggios are played. There's a sustained pad synth in the background which adds to the overall calming and soothing tone of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/_wyELLqwF3w.wav"} +{"id": "_x4a974Pl-A", "caption": "The low quality recording features a pop song that consists of a passionate male vocal singing over punchy kick and snare hits, shimmering shakers, synth pad, groovy bass and brass melody. It sounds passionate, emotional, energetic and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/_x4a974Pl-A.wav"} +{"id": "_xC7IXGWlk4", "caption": "This traditional music is played on didgeridoos. There are three didgeridoos being played. They are played by vibrating the lips and blowing into the instrument. This produces the droning sound. On one of the didgeridoos, a stick is being hit to form a percussive rhythm. The other didgeridoos play a melody by opening the mouth wider and narrowing the mouth in an alternate pattern. Halfway through the song, a tambourine is played. This song can be played in a movie where tribal people have a ceremony.", "audio": "/zhanghaomin/datas/musiccap/music_data/_xC7IXGWlk4.wav"} +{"id": "_xURU_-ffC4", "caption": "This song contains someone strumming chords on an acoustic guitar while playing a harmonica. This song may be playing at a local bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/_xURU_-ffC4.wav"} +{"id": "_y07ENAx2_E", "caption": "The low quality recording features a live performance of a jazz song that consists of a wide passionate, harmonizing male vocals singing over punchy snare and kick hits, shimmering hi hats, groovy bass guitar, synth pad and funky electric guitar melody. It sounds funky, groovy and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/_y07ENAx2_E.wav"} +{"id": "_yRFCl-z-EE", "caption": "The low quality recording features a traditional song that consists of wide, harmonizing female vocals singing over acoustic rhythm guitar. It sounds mellow, soft and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/_yRFCl-z-EE.wav"} +{"id": "_yWsqs9FOnU", "caption": "This is an instrumental piece consisting of an electric guitar solo which is played with the tapping technique. There is a usage of complex chords and syncopations, essential characteristics of the progressive rock genre. The guitar has a clear tone.", "audio": "/zhanghaomin/datas/musiccap/music_data/_yWsqs9FOnU.wav"} +{"id": "_yXtw_z2xf4", "caption": "This is a latin dance piece. There are two vocals taking turns singing the same line repeatedly. There is a keyboard and a trumpet playing the main melody. A fast-paced electronic percussion is playing in the rhythmic background. This is a dizzyingly high tempo song. It is very danceable. This piece can be played in latin nightclubs and latin dance courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/_yXtw_z2xf4.wav"} +{"id": "_yzcCFe-uo0", "caption": "This song is a duet of the Christmas Carol \u2018Jingle Bells\u2019 in Spanish. The tempo is medium with keyboard harmony, tambourine beats , hand percussion and accordion accompaniment . The song is cute, simple, cheerful, happy and animated.", "audio": "/zhanghaomin/datas/musiccap/music_data/_yzcCFe-uo0.wav"} +{"id": "_zQTlTCqMzs", "caption": "A male vocalist sings this powerful solo in a foreign language. The tempo is medium with a spanish guitar accompaniment. The song has minimalist music with captivating, lilting and almost haunting vocals. This is a live performance with ambient sounds of people talking. The audio quality is inferior as it is an amateur recording. This song is a Latin/Spanish Folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/_zQTlTCqMzs.wav"} +{"id": "a-11dtG7aK4", "caption": "This song has a relaxing feel. It starts off with a synth playing a chord sequence. This is followed by synth strings playing a high pitched melody. The notes fade into each other. Another synth plays the bass notes in the background. There is no percussion in this song. The mood of this song is dreamy. This song can be played in a dream sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/a-11dtG7aK4.wav"} +{"id": "a-3cZREZh3k", "caption": "The low quality recording features a marimba melody, groovy accordion chords and walking bass guitar, followed by metallic percussive elements and shimmering snare. It sounds fun and happy, even though it is probably recorded via phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/a-3cZREZh3k.wav"} +{"id": "a-P0p_UtagM", "caption": "This audio contains acoustic drums playing with an e-bass. An accordion is playing a short chord melody on the backbeat while someone is playing a flute melody completely out of tune and all over the place. This is an amateur recording. This song may be playing at home while practicing playing the flute.", "audio": "/zhanghaomin/datas/musiccap/music_data/a-P0p_UtagM.wav"} +{"id": "a2QxlP5DAYQ", "caption": "A didgeridoo is playing a rhythm full of overtones while being supported by experimental, atmospheric pad sounds. The whole recording is full of reverb, mystic sounds that are panned to the left and right side of the speakers. This song may be playing at an alternative nature festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/a2QxlP5DAYQ.wav"} +{"id": "a2Wuroc8DQU", "caption": "This clip features a melody played by violins and flutes. This is a low quality recording. There is no percussion in this song. Hand claps are played on every count. This is a folk song which has a happy mood. There is no voice in this song. This song can be used in a movie scene where somebody enters a castle to meet medieval royalty.", "audio": "/zhanghaomin/datas/musiccap/music_data/a2Wuroc8DQU.wav"} +{"id": "a4BjqKd8FsI", "caption": "This music is an instrumental with a medium fast tempo. The music is orchestral with a lively brass band harmony, violin accompaniment, xylophone beats, a bright trombone and cello bass. The music is animated, lively, playful,whimsical, perky and puckish.", "audio": "/zhanghaomin/datas/musiccap/music_data/a4BjqKd8FsI.wav"} +{"id": "a4jcJ7QZ-OQ", "caption": "This is a rock music piece consisting of three instruments. There is a distorted electric lead guitar playing a solo that is increasing from medium to high pitch. The bass guitar is providing tune in the background. There is a loud acoustic drum beat that includes a lot of fills. The song has a vigorous, high energy feel to it. This piece could be played at rock bars.", "audio": "/zhanghaomin/datas/musiccap/music_data/a4jcJ7QZ-OQ.wav"} +{"id": "aBEiuYSSEH0", "caption": "The low quality recording features a traditional song played in the beginning, after which there is a loud horn sound and wooden impact. It sounds weird, harsh and repetitive.", "audio": "/zhanghaomin/datas/musiccap/music_data/aBEiuYSSEH0.wav"} +{"id": "aBXntqgPo6Q", "caption": "Someone is playing a clean e-guitar chord and then a male voice starts to talk. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/aBXntqgPo6Q.wav"} +{"id": "aC3IBcRNyro", "caption": "This is an instrumental song featuring a french horn being played. The french horn plays the main melody. This is accompanied by a piano playing arpeggiated chords. A bass plays the root notes of the chords. There are no other instruments in this song. This is a slow tempo song. This song has a romantic and relaxing mood. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/aC3IBcRNyro.wav"} +{"id": "aCA4yiPfFIg", "caption": "The low quality recording features a hip hop song that consists of punchy snare and kick hits, shimmering hi hats and buzzy synth lead, played by a DJ that manually made beat breaks, which resulted in stuttering filter modulated synth riser. It sounds energetic and exciting thanks to that riser.", "audio": "/zhanghaomin/datas/musiccap/music_data/aCA4yiPfFIg.wav"} +{"id": "aCTm1TcL7z8", "caption": "The low quality recording features an electric guitar solo melody played over groovy bass guitar, shimmering tambourine, punchy kick and tinny wooden percussion. It sounds groovy, funky and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/aCTm1TcL7z8.wav"} +{"id": "aCUZuMblJPg", "caption": "The track would fit the funk fusion music genre. The main melodic element is a synth electric guitar that plays a solo with a lot of energy and presence. In the background a drum loop that sounds very electronic is played. The music is upbeat and simple. This song would fit a car racing video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/aCUZuMblJPg.wav"} +{"id": "aDlWOvCdNMk", "caption": "This song features an instrumental played on bagpipes. One pedal note is played continuously on the lower register while the higher notes are played to a melody. There are no other instruments in this song. There are no voices in this song. This is an instrumental song. This song can be played at a Scottish fair.", "audio": "/zhanghaomin/datas/musiccap/music_data/aDlWOvCdNMk.wav"} +{"id": "aE_CVWMWK74", "caption": "Sound from a cartoon space battle featuring a space shuttle takeoff, laser gun sounds and a rocket launcher firing. Background score is dramatic orchestral, featuring cymbal crashes and tense, dissonant string harmonies.", "audio": "/zhanghaomin/datas/musiccap/music_data/aE_CVWMWK74.wav"} +{"id": "aGMdcxeF6Ak", "caption": "A girl band sings this lively song. The tempo is medium with vibrant music. The audio quality is inferior so the music and vocals are incoherent. This is a live performance with ambient sounds of fans cheering, clapping and singing along. This song is a hit Country Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/aGMdcxeF6Ak.wav"} +{"id": "aHZdDmYFZN0", "caption": "The low quality recording features a classical song that contains a wide string melody. It sounds suspenseful and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/aHZdDmYFZN0.wav"} +{"id": "aIIEI33EUqI", "caption": "This song contains soft synth pads playing in the lower to higher register with little dreamy notes sprinkled on top. This song may be playing for a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/aIIEI33EUqI.wav"} +{"id": "aItOEVYnpHA", "caption": "The EDM song features an echoing synth lead melody, snare rolls, synth pad chords, energetic riser and some claps. In the second half of the loop, there is a filtered synth melody building up. It sounds energetic and exciting, as this is probably a build up section, after which comes a drop and like something you would hear in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/aItOEVYnpHA.wav"} +{"id": "aJHv6TV7JpY", "caption": "This pop song features a female voice singing the main melody in a foreign language. This is accompanied by an accordion playing a harmonized melody in the background. There is no percussion in this song. Minimal instruments are used in this song. The theme of this song feels romantic.", "audio": "/zhanghaomin/datas/musiccap/music_data/aJHv6TV7JpY.wav"} +{"id": "aKhM6zyL--k", "caption": "The first sound effect in this clip is the sound of old TV static. Then we hear a retro video game sound used to illustrate when the character jumps up. Then we have a sustained calming sound which is like the sound after a large bell has been rung.", "audio": "/zhanghaomin/datas/musiccap/music_data/aKhM6zyL--k.wav"} +{"id": "aLnBwjLUZao", "caption": "This blues song features a male voice singing the main melody at a comfortable pitch. This is accompanied by percussion playing a simple rock beat in common time. An overdriven guitar plays a blues riff. After one bar, the guitar and bass pause while the percussion and voice continues. The bass plays the root notes of the chords. The mood of this song is happy. This song can be played in a bar scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/aLnBwjLUZao.wav"} +{"id": "aNJEh3_Vmps", "caption": "This is a song that would be suitable as meditation music or background music for sleeping. It is calming and features sustained high pitched notes on a pad synth. The song feels ethereal and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/aNJEh3_Vmps.wav"} +{"id": "aNjtfIoVzas", "caption": "This song contains a plucked string instrument playing a melody in the higher register along with an acoustic guitar strumming chords on the backbeat and an upright bass playing a simple melody along to the lead melody. This song may be playing in a video-presentation.", "audio": "/zhanghaomin/datas/musiccap/music_data/aNjtfIoVzas.wav"} +{"id": "aO0QzRPiEC4", "caption": "The low quality recording features a rock song that consists of melancholic male vocal singing over a wide electric guitar melody, bouncy snare, groovy bass guitar and punchy kick. The recording is noisy, muddy and messy, since the frequencies are clashing with each other - drums cymbals are inaudible. Regardless, it sounds groovy, emotional and melancholic thanks to that vocal.", "audio": "/zhanghaomin/datas/musiccap/music_data/aO0QzRPiEC4.wav"} +{"id": "aOGNUGgTQ8k", "caption": "A female Arabic singer sings this beautiful melody with backup singers in vocal harmony. The song is medium tempo with a string section, Arabic percussion instruments, tambourine percussion, steady drum rhythm, groovy bass line and keyboard accompaniment. The song is romantic and celebratory in nature. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/aOGNUGgTQ8k.wav"} +{"id": "aPAa2sfhS7k", "caption": "This music is a Western Classical Instrumental. The music is fast tempo with a plethora of instrumentation. From a vigorous clarinet solo, flute, intense trumpets , violin symphony, cello, viola and French horns, this music is a treat to the ears. It is smooth, rich, full bodied, exquisite and elegant with an urgent and sombre vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/aPAa2sfhS7k.wav"} +{"id": "aPQTrv2B1sw", "caption": "The low quality recording features a live performance of a folk rock song that consists of harmonizing vocals singing over shimmering hi hats, snappy rimshots, groovy bass guitar and acoustic rhythm guitar, followed by some crowd claps. It sounds messy, muddy and distorted, but still emotional and passionate too.", "audio": "/zhanghaomin/datas/musiccap/music_data/aPQTrv2B1sw.wav"} +{"id": "aPafZ1Mx-BE", "caption": "Singers sing this prayer song in a congregational unison. The song is medium tempo with a heavily distorted harmony section. The song is of very bad quality with humming and whirring noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/aPafZ1Mx-BE.wav"} +{"id": "aQdZtz90Yzw", "caption": "This song features chords being played on a ukulele. A male voice narrates the chords being played. There is no vocal melody in this song. There are no other instruments in this song. This clip can be used in an instructional lesson for ukulele.", "audio": "/zhanghaomin/datas/musiccap/music_data/aQdZtz90Yzw.wav"} +{"id": "aRGAnD12qdw", "caption": "This song contains someone playing congas accompanied by other percussive instruments such as a woodstick sound. Male voices are singing as a choir in the background. This song may be playing live at an urban meetup.", "audio": "/zhanghaomin/datas/musiccap/music_data/aRGAnD12qdw.wav"} +{"id": "aSyRV5j2zV4", "caption": "The low quality recording features a wide choir female vocals singing, while there is a flat male vocal talking over it. It sounds like a tutorial of sorts.", "audio": "/zhanghaomin/datas/musiccap/music_data/aSyRV5j2zV4.wav"} +{"id": "aT7LGemDB40", "caption": "The song is an instrumental. The song is medium tempo with Latin percussions, guitar strumming rhythm, groovy bass line and keyboard percussions. The song is exciting and groovy. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/aT7LGemDB40.wav"} +{"id": "aTeOMq8ave8", "caption": "This is a recording that was done outdoors and later had background music placed over it. There are the sounds of footsteps, and a young male saying something unintelligible. The track placed over it is a high octane rock song with fast electric bass playing, overdriven electric guitar strumming and a rock motif on the electric guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/aTeOMq8ave8.wav"} +{"id": "aUH12rRIVDw", "caption": "This song features a wind instrument sounding like a saxophone. This is accompanied by percussion playing a simple beat. The melody of this song is jazzy. A piano plays chords. An electric piano or keyboard plays a descending lick before the instruments pause momentarily. The mood of the song is happy. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/aUH12rRIVDw.wav"} +{"id": "aURLQXt_6fE", "caption": "This is a percussion orchestra performance. There are many percussive elements in this orchestra such as the congas, the maracas, the marimba and the xylophone. There is also an acoustic drum playing in the orchestra. The atmosphere is lively.", "audio": "/zhanghaomin/datas/musiccap/music_data/aURLQXt_6fE.wav"} +{"id": "aUXKK9AmrPU", "caption": "A dark, sexy techno or acid house beat; with a repetitive synthesizer sequence with a squelchy resonant filter. The kick pattern is four on the floor with swung hi-hats and a syncopated synth bass. There is a big clap on the backbeat with a long reverb tail. The tempo is medium and the singer is male, singing in a high chest voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/aUXKK9AmrPU.wav"} +{"id": "aUvHaURNgY8", "caption": "A low sounding male voice is rapping over a fast paced drums playing a reggaeton beat along with a bass. Something like a guitar is playing the melody along. This recording is of poor audio-quality. In the background a laughter can be noticed. This song may be playing in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/aUvHaURNgY8.wav"} +{"id": "aUx0xMF9pwU", "caption": "This is a recording of a piano song being played on a speaker. There is a live audience that cheers and applauds. The song feels light and whimsical.", "audio": "/zhanghaomin/datas/musiccap/music_data/aUx0xMF9pwU.wav"} +{"id": "aVNcweinmEM", "caption": "This is an R&B music piece. There is a male vocalist singing melodically in the lead. The melody is being played by the synth sound. The rhythm is being played by an electronic drum beat which has a sound that is very similar to a 909 kit. The atmosphere is danceable and urban. This piece could be used in the soundtrack of a teenage drama movie or a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/aVNcweinmEM.wav"} +{"id": "aW6greyYuO4", "caption": "This is an orchestra playing Arabic music. The melody is played by the conjunction of multiple instruments such as violin, flute and qanun while tambourines create the percussive background of the piece. It has an oriental atmosphere that could be very fitting in a movie or a show taking place in the Middle East. It could also be a good background music for Arab cuisine restaurants.", "audio": "/zhanghaomin/datas/musiccap/music_data/aW6greyYuO4.wav"} +{"id": "aWK9CcvOK9w", "caption": "This song contains a lot of percussive elements and instruments playing a fast paced rhythm with a simple e-bass underlining the drum hits. Strings are being played along with the melody and adding some extra spice. The female voice is singing along with a lot of female and male backing vocals. The voices are panned to the left and right side of the speakers. This song may be playing at a cheerful event while celebrating.", "audio": "/zhanghaomin/datas/musiccap/music_data/aWK9CcvOK9w.wav"} +{"id": "aXDgw2fLHAA", "caption": "This clip features two jazzy songs. The first one has a fast paced melody that's led by an electric guitar which plays intricate solos. The next song is led by a clarinet, it's more slow-paced and bouncy.", "audio": "/zhanghaomin/datas/musiccap/music_data/aXDgw2fLHAA.wav"} +{"id": "aY8-pXDdwiw", "caption": "This song is a choral harmony. The tempo is slow with intense bass and an instrument that sounds like a viola. The song is grim, grave, intense, sinister; eerie; spooky; scary, chant-like, and dreary.", "audio": "/zhanghaomin/datas/musiccap/music_data/aY8-pXDdwiw.wav"} +{"id": "aYoRcnmz6ZE", "caption": "This music is instrumental. The tempo is fast with rhythmic acoustic guitar, steady drumming, keyboard harmony, groovy bass line and electric guitar accompaniment. The music is mellow,nostalgic, emotional, simple, pleasant, charming and melodic pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/aYoRcnmz6ZE.wav"} +{"id": "aYrjw3gjGuk", "caption": "The low quality recording features a resonating, distorted, crushed electro song being played on a car subwoofer. It sounds very aggressive and energetic too. There are some outdoor atmosphere sounds, since it was recorded outside.", "audio": "/zhanghaomin/datas/musiccap/music_data/aYrjw3gjGuk.wav"} +{"id": "a_r8wKJ8ePw", "caption": "This music is a high spirited acoustic guitar instrumental. The tempo is fast and the music is lively, spirited, Vibrant and vivacious with static and the sound of tapping. This music is a country style acoustic melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/a_r8wKJ8ePw.wav"} +{"id": "ab8V7MYQVyg", "caption": "A male vocalist sings this Popular 90\u2019s song. The tempo is medium fast with thumping drum beats, keyboard harmony, boomy bass and vocal backup.The song is a live performance at a concert with ambient sounds of fans screaming, clapping and singing along and responding. The audio is incoherent as it is an amateur recording. This song is a Hit 90\u2019s Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/ab8V7MYQVyg.wav"} +{"id": "acEHGV7Gq6U", "caption": "The low quality recording features wide aggressive electric guitar chords, shimmering hi hats and open hats, punchy snare, soft kick hits and distorted bass guitar. Right before the \"drop\", there is a short guitar slide, leading perfectly into it. The instrumental sounds energetic and aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/acEHGV7Gq6U.wav"} +{"id": "ac_8oRMgDz0", "caption": "This meditation song features male voices chanting in deep, low voices. This is accompanied by synth sounds playing at different pitches. One of the synths plays a droning low pitch sound. The mid and higher register sounds play instruments sounding like wind instruments. The sounds produced are ambient sounds and have a dreamy feel. The song is relaxing and calming. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/ac_8oRMgDz0.wav"} +{"id": "ad6UhYwTXXQ", "caption": "The audio contains a female voice singing carnatic tones/melody over a shrutibox/drone sound. The audio quality is decent but contains a lot of white noise. It's assumed that this is an amateur recording. This song may be playing at a music teacher's home demonstrating scales to a student.", "audio": "/zhanghaomin/datas/musiccap/music_data/ad6UhYwTXXQ.wav"} +{"id": "ad6gQQ_0evk", "caption": "A banjo is playing a solo along to an upright-bass laying a simple monotone bassline. This song may be playing in a bar with live music. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/ad6gQQ_0evk.wav"} +{"id": "adHhqDnyZv8", "caption": "This music is a rich Italian Classical Orchestra. The tempo is fast with a symphonic orchestra with a rich ,animated violin solo, complete with violin, cello viola , flute and piano accompaniment . This music is a sonic treat. It is rich, expressive, exquisite, spectacular, enthralling and captivating. This music is a Baroque classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/adHhqDnyZv8.wav"} +{"id": "adYFXYPqo2M", "caption": "This is a country music piece. There is a male vocalist singing in a preaching manner. The melody is being played by a violin, a banjo and an electric guitar while an upright bass is playing in the background. The rhythmic background consists of an accentuated acoustic drum beat. The atmosphere is lively and hard-hitting. This piece could be used in the soundtrack of a historical crime movie taking place in the US.", "audio": "/zhanghaomin/datas/musiccap/music_data/adYFXYPqo2M.wav"} +{"id": "aeDZVfGk7bk", "caption": "This audio contains someone playing a mouthwarp. Then another recording starts where someone is strumming chords on an e-guitar fingerpicking a melody. This song may be playing for a photo slide show made for the family.", "audio": "/zhanghaomin/datas/musiccap/music_data/aeDZVfGk7bk.wav"} +{"id": "aek3GoFr5MI", "caption": "This audio contains a dubstep beat with a lot of bass and aggressive synth sounds. In the background you can hear the crowd cheering. This is an amateur recording and of poor audio-quality. This song may be playing at a live dance show.", "audio": "/zhanghaomin/datas/musiccap/music_data/aek3GoFr5MI.wav"} +{"id": "aeujZtBvMFY", "caption": "This is an instrumental jazz fusion piece. Various instruments are played throughout this piece. A wide variety of key instruments such as the piano, the organ, the celeste, the rhodes, the synth and the harpsichord can be heard. The atmosphere is funky and eccentric. A vibrant array of samples can be gathered from this piece, ideally for use in the soundtrack of a goofy cartoon.", "audio": "/zhanghaomin/datas/musiccap/music_data/aeujZtBvMFY.wav"} +{"id": "afavVsmFWds", "caption": "The low recording features a soft rock song that consists of flat, echoing male vocal singing over muffled drums and reversed synth keys melody located in the left channel of the stereo image - which makes the stereo image a bit unbalanced. The drums consist of groovy snare, punchy kicks and shimmering cymbals. At the end of the loop, there is a reversed high pitched vocal riser. It sounds thin and a bit muffled overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/afavVsmFWds.wav"} +{"id": "afb7pI_01O4", "caption": "The low quality recording features a metal song that consists of aggressive electric guitar melody, distorted bass guitar, shimmering cymbals and muffled kick and snare hits. It sounds energetic, but also harsh, messy, distorted, muddy and loud, since the frequencies are clashing with each other. The volume of the song is dwindling occasionally, making it a really low quality sounding track.", "audio": "/zhanghaomin/datas/musiccap/music_data/afb7pI_01O4.wav"} +{"id": "agK1OkzW5Yg", "caption": "This meditation song features a guzheng playing the main melody. A kind of zither plays arpeggiated chords in the background. Chimes are played in between lines. This song has a Chinese melody. This song is relaxing. There are no voices in this song. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/agK1OkzW5Yg.wav"} +{"id": "agw-ujSdX0A", "caption": "This is the recording of a Pakistani marching band. The bagpipes are playing the melody. The rhythmic background is provided by a drumline that is played by the snare drums, the bass drums and the cymbals. The atmosphere is vibrant and lively. This piece could be playing in the background at a parade.", "audio": "/zhanghaomin/datas/musiccap/music_data/agw-ujSdX0A.wav"} +{"id": "aiJj3Z6pu9s", "caption": "This audio clip features the sound of water dropping. This is followed by the sound of a wild creature. The sound is creaking. Toward the end, the sound of a rat squealing is heard. This sound is from a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/aiJj3Z6pu9s.wav"} +{"id": "ajy9PM2SJ6c", "caption": "A phone ring interrupts the song then a male voice is singing along to a digital drum with a strong clapping sound and a funky bassline. This song may be playing while wearing headphones while enjoying yourself.", "audio": "/zhanghaomin/datas/musiccap/music_data/ajy9PM2SJ6c.wav"} +{"id": "ak7R0_8aKwI", "caption": "A female vocalist sings this soft melody. The tempo is slow with acoustic guitar rhythm, keyboard accompaniment, steady drumming , sound of chimes, xylophone, shakers and atmospheric synthesiser. The song is a sweet, dreamy, mellow, soothing ,lullaby for children.This song is a Nursery Rhyme.", "audio": "/zhanghaomin/datas/musiccap/music_data/ak7R0_8aKwI.wav"} +{"id": "ao-TFiShaWU", "caption": "This is an acoustic indie rock piece. There is a male vocalist singing gently in the Thai language. An acoustic guitar plays the main tune while a bass guitar is in the background. There is a piano that starts out by supporting the melody, but then wanders towards off-key notes, creating an air of conflict. The atmosphere is melancholic. This piece can be used in the soundtrack of a drama movie/TV show that takes place in Thailand.", "audio": "/zhanghaomin/datas/musiccap/music_data/ao-TFiShaWU.wav"} +{"id": "ap7xvCBtljs", "caption": "A e-guitar is playing a melody along with the e-bass. The acoustic drums are playing with a loud 8th note rhythm on the ride cymbal. Another e-guitar is playing a high pitched melody on top. This song may be playing at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/ap7xvCBtljs.wav"} +{"id": "apA0IY_5-2g", "caption": "This is a neo-soul music piece playing under the background of a dance contest. There is a male vocalist singing melodically in the lead. There is a repeating acoustic guitar sample in the beat. A strong bass sound can be heard. The rhythm consists of an electronic drum beat. There are voices shouting over the music in the video. The atmosphere is groovy and urban.", "audio": "/zhanghaomin/datas/musiccap/music_data/apA0IY_5-2g.wav"} +{"id": "aq3vov8-fw8", "caption": "This orchestral song features flutes playing the main melody. This is backed by bass played on the cello. The percussion is played on the tambourine. This song is in a compound time signature. Toward the end of the clip, the tambourine sound is played loud in a specific rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/aq3vov8-fw8.wav"} +{"id": "aqhhfkXKJ1o", "caption": "This is a solo electric guitarist playing some blues. It's a twelve bar blues progression that's intricately finger picked. It has a turnaround.", "audio": "/zhanghaomin/datas/musiccap/music_data/aqhhfkXKJ1o.wav"} +{"id": "ar4YQ_DOcyk", "caption": "A female vocalist sings this cheerful song. The tempo is fast with a peppy keyboard harmony, simple, march like drumming, steady bass line, acoustic guitar and bells chiming. The song is a foreign language but from the sound and vibe of it, it seems like a fun, happy, joyful, cheerful, warm hearted and popular folk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/ar4YQ_DOcyk.wav"} +{"id": "argBwTHDDVI", "caption": "This clip features an instruction by a male voice on how to use an effect on a synth. After the narration, three notes are played on a synth. The first one is loud, the second note is lower and softer. The third note is lower but louder in volume. There are no other instruments in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/argBwTHDDVI.wav"} +{"id": "aryufzYGhbM", "caption": "This song is in very poor audio-quality and seems to lag. A big pulsating synthesizer pad is creating tension along with some more single holding note, higher register synth pad. A riser effect tells us that this part of the song is about to break into another part that will bring relief from the created tension. A synthesizer pluck is playing a catchy repeating melody. The male voice sings/raps in the higher register a male backing voice is shouting in the background. This song may be played on a dj mix in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/aryufzYGhbM.wav"} +{"id": "as7MhTe961k", "caption": "This is a live performance of a movie music piece. The recording has a very poor quality. The saxophone is playing the main tune while the piano can be heard providing a melodic background. The atmosphere is romantic and it is probably a wedding setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/as7MhTe961k.wav"} +{"id": "asT8yaJPP1s", "caption": "This audio clip is an instrumental. The tempo is low with a subtle violin harmony, keyboard arpeggio and synthesised organ. The music is lilting, grim,incessant, intense, sad, bleak, enigmatic and ambiguous. The music sounds like the background score for a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/asT8yaJPP1s.wav"} +{"id": "asYb6iDz_kM", "caption": "This is an afrobeat music piece. There is a male vocalist singing playfully in the lead. The electric guitar is playing a groovy melody with the bass guitar playing in the background. The rhythm is being played by the acoustic drums. The atmosphere is cheerful. This piece could be used in the soundtrack of a feelgood movie taking place in Africa.", "audio": "/zhanghaomin/datas/musiccap/music_data/asYb6iDz_kM.wav"} +{"id": "atWaDoSyGgY", "caption": "This song contains someone playing acoustic drums along with an e-bass. They both sound in the foreground. A male voice is singing in the high mids and with reverb and a little delay on his voice. Then the song breaks into the next part and an e-guitar comes in with a strummed melody. This song may be playing with headphones lost in thoughts.", "audio": "/zhanghaomin/datas/musiccap/music_data/atWaDoSyGgY.wav"} +{"id": "aupCwPVWsMo", "caption": "This song contains a string section playing a short stroke melody in the lower range along to a digital acoustic drum playing a rather complex groove. Acoustic guitars are playing a melody. This song may be playing in a heroic movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/aupCwPVWsMo.wav"} +{"id": "av-1Ih0S82s", "caption": "This is a percussion instrumental. The tempo is medium with the sound of a drum roll on the Chinese Big drum or Tanggu . The beat is strong, emphatic and resounding. It has a Royal, Ceremonial or Victorious vibe to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/av-1Ih0S82s.wav"} +{"id": "awax48X8YlU", "caption": "The low quality recording features a shimmering tambourine, wooden percussive elements, followed by arpeggiated harp which serves as a transition to the second part of the loop where plucked string melody appears. It sounds groovy and traditional.", "audio": "/zhanghaomin/datas/musiccap/music_data/awax48X8YlU.wav"} +{"id": "ax8hXst_b5g", "caption": "The Urban Latin song features an echoing male vocal singing repetitive lyrics over wide reverberant percussive elements, synth flute melody, claps, \"4 on the floor\" kick pattern, shimmering shaker, groovy bass and synth keys melody. It is uptempo and it sounds energetic and addictive, like something you would hear in clubs a lot.", "audio": "/zhanghaomin/datas/musiccap/music_data/ax8hXst_b5g.wav"} +{"id": "axb48YrvRmw", "caption": "Classical music features a variety of string instruments that play a bright melody. The sound is big and orchestral. A clarinet plays a high-pitched melody in the foreground. The atmosphere of the song is positive and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/axb48YrvRmw.wav"} +{"id": "axqtExFY5-s", "caption": "This is an instrument review jam that is played in the style of flamenco music. There is an acoustic guitar being played while a male voice gives his opinion concerning the instrument. The character of the sound is sensual. The guitar sounds can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/axqtExFY5-s.wav"} +{"id": "azyNUtTHvaE", "caption": "A female voice is singing very clear and a high pitched melody. She got a lot of reverb on her voice. A string section is supporting her. This song may be playing in a post-apocalyptic movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/azyNUtTHvaE.wav"} +{"id": "b-7oO1Rw-fo", "caption": "This funk pop song features a male voice singing at a high pitch. The style of singing is rapping in this section. This is accompanied by a kick drum. The kick drum plays on every count of the bar for two bars followed by doubling the beat for the next two bars. In the gaps of the lines, a voice sings vocables. After two bars, the bass plays an ascending run. A siren sound is played in the background ascending along with the bass. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/b-7oO1Rw-fo.wav"} +{"id": "b-Cr0EWwaTk", "caption": "The low quality recording features a hip hop song that consists of flat male vocals, alongside echoing whispering vocals, rapping over shimmering hi hats, punchy kick, boomy 808 bass, claps, quiet snare hits and arpeggiated synth melody. The song sounds energetic, especially because of the uptempo hi hat triplets.", "audio": "/zhanghaomin/datas/musiccap/music_data/b-Cr0EWwaTk.wav"} +{"id": "b-Y-AjW6MJ0", "caption": "The low quality recording features a rock song that consists of a flat male vocal and flat female vocal talking, followed by punchy kick and snare hits, shimmering hi hats, energetic crash hits, wide electric guitar chords, groovy bass guitar and synth lead melody. It sounds energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/b-Y-AjW6MJ0.wav"} +{"id": "b0dVykd2i6g", "caption": "This is a pop/soft rock music piece. There is a male vocalist singing melodically. The main melody is being performed by the piano with the strings' sound holding notes in the background. A solid bass line can be heard. A slow tempo acoustic drum beat is keeping the rhythm. The atmosphere is easygoing. This piece could be used in the soundtrack of a romantic comedy, especially during the scenes where the male protagonist is feeling regret for his actions.", "audio": "/zhanghaomin/datas/musiccap/music_data/b0dVykd2i6g.wav"} +{"id": "b12xqPnM0So", "caption": "The low quality recording features a live performance of a folk song that consists of a woodwind melody, followed by accordion melody, trumpet melody, metallic percussion and groovy bass. It sounds passionate and cultural.", "audio": "/zhanghaomin/datas/musiccap/music_data/b12xqPnM0So.wav"} +{"id": "b1j-hD9zs6Q", "caption": "Someone is playing a flute in the mid to high range taking the lead-melody accompanied by a piano playing along and spicing up the melody. An e-bass is building the foundation together with an acoustic drum being played in the background with fill-ins on the toms. This song may be playing at the end of an emotional movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/b1j-hD9zs6Q.wav"} +{"id": "b2-izZk5_BM", "caption": "This is a Romanian pop music piece. There is a male vocalist singing with autotune. The melody is being played by a synth sound. There is a bass guitar playing a simple bass line while the rhythmic background consists of a slow tempo electronic drum beat. The atmosphere is sentimental. This piece could be used in the soundtrack of a Romanian soap opera, especially during romantic scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/b2-izZk5_BM.wav"} +{"id": "b2XAPiRUoN4", "caption": "This is a marching parade of hundreds of Scottish bagpipe players. They are all playing the same melody with the exact same pitch. The song itself feels somewhat encouraging and positive.", "audio": "/zhanghaomin/datas/musiccap/music_data/b2XAPiRUoN4.wav"} +{"id": "b4FomUpNaJE", "caption": "The Folk song features a flat, echoing male vocal talking over addictive accordion melody, wide piano chords, groovy bass, \"4 on the floor\" kick pattern, tinny percussive elements, energetic open hats, shimmering shakers and offbeat electric guitar chords. It sounds uplifting and low quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/b4FomUpNaJE.wav"} +{"id": "b62RgDBmly8", "caption": "This song contains a full orchestra playing a melody with long and short strings; flutes adding short melodies on top and a cymbal hit to close the phrase. A mixed choir is singing opera then a male solo singer takes over with a higher voice. This song may be playing in a musical or theater opera performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/b62RgDBmly8.wav"} +{"id": "b6hr31Qaemg", "caption": "This is a vocal performance from a soap opera soundtrack. There is a female vocalist that is singing with a heavily manipulated voice, most probably through the use of a vocoder. The volume of the track is unnecessarily loud and it peaks frequently. There is an unsettling atmosphere. It could be used in the soundtrack of a horror movie where the protagonist is slowly losing touch with reality.", "audio": "/zhanghaomin/datas/musiccap/music_data/b6hr31Qaemg.wav"} +{"id": "b8cgQBzBXi8", "caption": "This music is an Electronic instrumental. The tempo is fast with an electrifying drum rhythm, funky bass lines, synthesiser articulation, cymbals rides, digital drums and electronically arranged sounds. The music is an energetic, high-powered, energetic, enthusiastic, intense, and explosive EDM/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/b8cgQBzBXi8.wav"} +{"id": "b8okzVltB5Q", "caption": "This rock and roll song is a live recording of low quality. This features a male voice singing the main melody. This is accompanied by percussion playing a simple melody in common time. The bass plays a rock and roll bassline. The keyboard plays chords and fills using a piano tone. An acoustic guitar plays chords. A voice from the crowd sings a quirky sound at the beginning of the second bar. This song can be used in a retro movie in a music festival or carnival scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/b8okzVltB5Q.wav"} +{"id": "b98BJ36K1wo", "caption": "This audio contains someone playing an acoustic drum with a fast paced and complex rhythm. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/b98BJ36K1wo.wav"} +{"id": "b9rgWct9ivI", "caption": "This is a series of clips - a compilation. The compilation is separated by the telephone beep tone. One of the clips is orchestral strings playing a motif that would be used when something shocking or suspenseful happens. The other clip contains a jazzy saxophone motif. There is also a sultry woman speaking sassily with some upbeat percussion under her vocal.", "audio": "/zhanghaomin/datas/musiccap/music_data/b9rgWct9ivI.wav"} +{"id": "b9yT3nGcD_I", "caption": "This song contains digital drums with a loud kick on every beat and a snare hit on the 2 and 4. A synthbass is playing a simple melody. While sound-effect hits are adding rhythmic diversity along with a fast arpeggio sound that is fading out. This song may be playing at the disco.", "audio": "/zhanghaomin/datas/musiccap/music_data/b9yT3nGcD_I.wav"} +{"id": "bAJrcYJgllE", "caption": "This clip is an instrumental. The tempo is fast with high pitched, dissonant sounds that are digitally and electronically arranged. There is no melody or beat to this music.", "audio": "/zhanghaomin/datas/musiccap/music_data/bAJrcYJgllE.wav"} +{"id": "bBGcQ2-W768", "caption": "The Soft Rock song features a flat male vocal singing over arpeggiated electric guitar melody, punchy kick, groovy bass, shimmering hi hats and snappy rimshots. It sounds emotional and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/bBGcQ2-W768.wav"} +{"id": "bBfi3iEu9fk", "caption": "The low quality recording features a mellow arpeggiated piano melody over which there is a theremin solo melody playing. It sounds sad, emotional and passionate. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/bBfi3iEu9fk.wav"} +{"id": "bBy0NCoCEHc", "caption": "The low quality recording features a live performance of a traditional song and it consists of a bell melody, followed by wooden percussion. There are some flat male vocals talking, after which there are harmonizing male vocals singing over it. It sounds passionate, even though the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/bBy0NCoCEHc.wav"} +{"id": "bHNdoIWxXDk", "caption": "A bell choir is playing a composition. The range of the instruments goes from lower sounding instruments being used as percussive hits to mid and high range bells playing chords and melodies that sound a little bizarre at some points. This song may be playing in a local church as a presentation.", "audio": "/zhanghaomin/datas/musiccap/music_data/bHNdoIWxXDk.wav"} +{"id": "bHiRX6QYwEk", "caption": "A feminist plays this intriguing instrumental. The tempo is fast with keyboard accompaniment, steady drumming, rhythmic acoustic guitar, lively piano harmony , steady bass lines and shakers. The music is sharp, height pitched and almost like a female soprano vocalising. The song is energetic, spirited, melodic, animated, unique, skilful, engaging, ethereal and captivating;", "audio": "/zhanghaomin/datas/musiccap/music_data/bHiRX6QYwEk.wav"} +{"id": "bJ6e9Ja1ahQ", "caption": "A male vocalist sings this melodic, age old Christmas carol in French in Baritone. The tempo is slow with a violin symphony, the piano accompaniment, keyboard harmony; rhythmic acoustic guitar and steady drumming . The song is mellow, sentimental, emotional, nostalgic, pleasant ,dulcet and mellifluous .", "audio": "/zhanghaomin/datas/musiccap/music_data/bJ6e9Ja1ahQ.wav"} +{"id": "bJVogLOURmc", "caption": "The low quality recording features a drums solo that contains manic tom rolls and a ride cymbal one shot at the end. There was an exhale sound once the player finished his performance. The recording is very noisy, in mono and it sounds aggressive and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/bJVogLOURmc.wav"} +{"id": "bKS_m7JObxg", "caption": "The low quality recording features an acoustic guitar tuning. It sounds repetitive, almost like a robot is playing it.", "audio": "/zhanghaomin/datas/musiccap/music_data/bKS_m7JObxg.wav"} +{"id": "bKm2_67xtVs", "caption": "The Rock song features a sustained strings melody, groovy bass, electric guitar melodies, punchy snare, shimmering hi hats, mellow kick hits and acoustic rhythm guitar. It sounds soulful and like something you would hear during the 70s. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/bKm2_67xtVs.wav"} +{"id": "bLjOJRg2P_Q", "caption": "The Country song features a passionate male vocalist singing over accordion melody, groovy bass, layered \"4 on the floor\" kick and cowbell pattern, soft crash cymbal, shimmering shakers and acoustic rhythm guitar. It sounds fun and happy, even though the song is poorly mixed, as it sounds a bit boomy.", "audio": "/zhanghaomin/datas/musiccap/music_data/bLjOJRg2P_Q.wav"} +{"id": "bNW18IztiZY", "caption": "The low quality recording features a trap song playing in the background that contains stuttering snares, scratching effects and male vocals that occasionally change the pitch, while there are male exciting screams, hyping it out. The recording is very noisy, mostly from the wind and it sounds like it was recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/bNW18IztiZY.wav"} +{"id": "bNvp4y9WSGM", "caption": "This music is an animated instrumental. The tempo is very fast with a violin playing a very vigorous and upbeat amplified violin harmony with synthesiser arrangements and punchy digital drumming.The music is pulsating, energetic, enthusiastic, throbbing, youthful,powerful, compelling, engaging and untiring. The audio quality is inferior and there are sounds of hustling,people clapping along, chatting and cheering Indicating that this is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/bNvp4y9WSGM.wav"} +{"id": "bOOJRGRy0zc", "caption": "These two rap songs contain acoustic drums/digital drums playing a simple beat and a beat with a 16th hihat. Strings and bells are playing the main melody. On top of that the male voice of each song is rapping over the instrumental. These songs may be played while riding in your car or while playing sports.", "audio": "/zhanghaomin/datas/musiccap/music_data/bOOJRGRy0zc.wav"} +{"id": "bPWbeWf5xNI", "caption": "A female singer sings this beautiful love song with backup singers in vocal harmony. The song is medium tempo with a steady drumming rhythm, percussive bass line, autoharp accompaniment, guitar rhythm and keyboard accompaniment. The song has poor audio quality and makes an excellent wedding dance song.", "audio": "/zhanghaomin/datas/musiccap/music_data/bPWbeWf5xNI.wav"} +{"id": "bPYbRSI16IY", "caption": "The low quality recording features a filter modulated synth bass, after which there is a short snippet of flat male vocals talking over sea waves sounds in the background. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/bPYbRSI16IY.wav"} +{"id": "bQ9vpp_yXvk", "caption": "This song features the main melody sung by a choir. This is accompanied by the string section and brass section featuring violins and trumpets. Hand claps are heard on every count. Orchestral percussion plays in the background. As the quality of audio is low, many instruments cannot be heard. This song can be played in a celebration.", "audio": "/zhanghaomin/datas/musiccap/music_data/bQ9vpp_yXvk.wav"} +{"id": "bSX5-VPL8rE", "caption": "Make the singer sing this Latin rap song in vocal harmony. The song is medium tempo with a steady drum drumming rhythm, keyboard accompaniment, string section harmony, percussive bass line and machine gunshot sounds. The song is story telling and violent in nature. The song has bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/bSX5-VPL8rE.wav"} +{"id": "bTLgeqCaYMY", "caption": "The low quality recording features groovy drums played on vinyl, judging by the wide vinyl crackles and scratching effect. There is also a buzzy static noise, right after the female laugh that can be heard in the background. Sounds like it is recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/bTLgeqCaYMY.wav"} +{"id": "bTVl2GeNfqI", "caption": "A male singer sings this screaming metal vocal. The song is medium tempo with strong metal drumming, guitar rhythm, groovy bass line and mic feedback tone.The song is energetic and an adrenaline rush. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/bTVl2GeNfqI.wav"} +{"id": "bTlp5Qr99RY", "caption": "The low quality recording features a salsa song that consists of a passionate male vocal singing over shimmering chime bells, wooden percussion, shimmering shakers and groovy piano melody. It sounds passionate, emotional and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/bTlp5Qr99RY.wav"} +{"id": "bTuKGXDrqdQ", "caption": "The song is an instrumental with male vocalist chanting. The song is medium tempo with a didgeridoo playing percussively along with a guitar accompaniment. The song is meditative and has both aboriginal and Indian music influences . The audio quality is bad and it is a live audience performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/bTuKGXDrqdQ.wav"} +{"id": "bVc7-sZAi6s", "caption": "This is a pop music piece. There is a female vocalist singing melodically at the forefront with muffled repetitions of the same voice in the back. The simple and repeated theme is being played by a piano while the rhythmic background consists of an electronic drum beat with loud kick beats. There is a melancholic aura to this piece and a sense of resentment. This piece could be used in the soundtrack of a drama movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/bVc7-sZAi6s.wav"} +{"id": "bVtHAk5w2Z8", "caption": "This is a kids song in the style of pop punk. There is a male vocalist singing in a playful manner. It is joined occasionally by a robotic voice and the roars of a lion. The electric guitar and the bass guitar are playing a simple theme. The rhythmic background consists of a fast tempo acoustic drum beat. The atmosphere is cheerful. It could go well in the soundtrack of a kids show.", "audio": "/zhanghaomin/datas/musiccap/music_data/bVtHAk5w2Z8.wav"} +{"id": "bY_EvbARc5Y", "caption": "This composition is playing a xylophone playing a repeating melody progression that serves as a foundation playing lower notes while playing a higher pitched melody. The whole song is full of reverb. This song may be playing in a dreamy and quiet movie scene or while falling asleep.", "audio": "/zhanghaomin/datas/musiccap/music_data/bY_EvbARc5Y.wav"} +{"id": "bYwoYjbPm-I", "caption": "This music is an electric guitar instrumental. The tempo is slow with an amplified guitar solo riff. The audio quality is inferior so the sound is muffled, boomy and garbled. There is disturbance in the background with the sound of static and a man talking incessantly in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/bYwoYjbPm-I.wav"} +{"id": "bZJoTauRldE", "caption": "A male singer sings this passionate vocal. The song is medium tempo with a groovy bass line, steady drumming rhythm and a violin playing a solo. The song is a live performance by a folk singer. The song has a bad audio quality issue.", "audio": "/zhanghaomin/datas/musiccap/music_data/bZJoTauRldE.wav"} +{"id": "bZXQlQnleL4", "caption": "This is a classical style of music played by a brass quintet. The instruments featured include the trombone, tuba, french horn and trumpets. The motif they play is repeated, and it has a celebratory feel - as if for a big occasion.", "audio": "/zhanghaomin/datas/musiccap/music_data/bZXQlQnleL4.wav"} +{"id": "bZuXMxR2S4U", "caption": "This song consists of three main elements - there is an angelic female humming vocal, a bass guitar which intricately follows the melody of the humming, and an atmospheric synth pad. The song generally has a soothing and relaxing vibe that feels almost transcendental.", "audio": "/zhanghaomin/datas/musiccap/music_data/bZuXMxR2S4U.wav"} +{"id": "ba3QPheW8mI", "caption": "The low quality recording features a compilation of mumbling male vocal, screaming male sound effect, glass shattering sound effects alongside metallic hits, male grunts and reverberant impact. The recording ends with the applause. In-between every single sound there is a loud static sound - which makes it sound like the channels are changing on a TV. It sounds chaotic and manic.", "audio": "/zhanghaomin/datas/musiccap/music_data/ba3QPheW8mI.wav"} +{"id": "ba5xPgcHN_0", "caption": "The low quality recording features a chiptune remix of a pop song and it consists of high pitched female vocal singing over, groovy piano melody, smooth synth bass, claps, shimmering hi hats and punchy kick. At the very end of the loop, there is a snare roll. It sounds energetic, fun, happy and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ba5xPgcHN_0.wav"} +{"id": "bciw4Tqp6h4", "caption": "The low quality recording features a flat male talking over background music that consists of a saxophone melody played over shimmering hi hats, snappy rimshots, groovy piano melody, mellow bells melody and simple bass. It sounds happy, fun and easygoing - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/bciw4Tqp6h4.wav"} +{"id": "bcybO-SMY5E", "caption": "This rap song features a male voice rapping the words. This is accompanied by programmed percussion playing a rap beat. The sound of a cash register is played in the background. The voice has a defiant feel. A harmonic sound is played in the background which sounds like octaves being played on an overdriven guitar. This song can be used at the entrance of a WWE star.", "audio": "/zhanghaomin/datas/musiccap/music_data/bcybO-SMY5E.wav"} +{"id": "bf8JlTKzOs8", "caption": "This is an educational kids music piece. There is a female vocalist singing in a childlike manner in the Korean language. The keyboard is playing the melody while there is a bass guitar playing in the background. The rhythm is provided by a simple acoustic drum beat. The atmosphere is lively. This piece could be played for science-related classes at schools in Korea.", "audio": "/zhanghaomin/datas/musiccap/music_data/bf8JlTKzOs8.wav"} +{"id": "bg_QoesbfOA", "caption": "This is a Pakistani Sufi music piece. There is a female voice singing in a devoted manner. A bass tune can be heard supporting the vocals. The rhythm is performed by a membranous percussion, most probably a def. The atmosphere is religious. This piece could be played at Sufi religious events.", "audio": "/zhanghaomin/datas/musiccap/music_data/bg_QoesbfOA.wav"} +{"id": "bha-d3HXdMI", "caption": "The low quality recording features an electric guitar melody playing with reverb pedal effect on. The player turns the pedal off in the second half of the loop, as it is probably a comparison tutorial. It is noisy, mono and buzzy.", "audio": "/zhanghaomin/datas/musiccap/music_data/bha-d3HXdMI.wav"} +{"id": "bkQrvXXIRng", "caption": "Someone is playing acoustic drums with a lot of loud cymbal hits along with a screaming male vocal. A distorted e-guitar is playing long low notes. The atmosphere sounds dangerous and aggressive. This song may be playing in the band room practicing drumming.", "audio": "/zhanghaomin/datas/musiccap/music_data/bkQrvXXIRng.wav"} +{"id": "bkXrQyDbKtk", "caption": "This song features a choir singing a Christian hymn. The voices sing one note followed by a higher note followed by a descending pattern. The female voices sing the soprano and alto voices. The male voices sing tenor and bass parts. There are no instruments in this song. This song is an acapella song. This song can be played in a church.", "audio": "/zhanghaomin/datas/musiccap/music_data/bkXrQyDbKtk.wav"} +{"id": "bkYWnzw_5Bs", "caption": "The low quality recording features a cover of a R&B song that contains passionate female vocals, alongside background harmonizing female vocals, singing over punchy kick, claps, groovy bass, smooth keys and short strings chords. It sounds romantic, emotional and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/bkYWnzw_5Bs.wav"} +{"id": "bkzGHRpx5MM", "caption": "This is an instrumental progressive rock piece. The only instrument being played in the piece is a clean sounding electric guitar. There is a gently played guitar solo that gives a mellow aura. The atmosphere is dreamy. This piece could be used in the soundtrack of a movie or a TV show at a dream/flashback sequence. It could be playing in the background at a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/bkzGHRpx5MM.wav"} +{"id": "bl-eQ8XD5CY", "caption": "This song is an instrumental. The tempo of the background music is slow , with electric guitar harmony and rhythmic drum with loud chaotic, dissonant sounds. The music is out of sync as the unidentifiable sounds are accelerated.", "audio": "/zhanghaomin/datas/musiccap/music_data/bl-eQ8XD5CY.wav"} +{"id": "bl8PgmZ9iOc", "caption": "The low quality recording features a flat male vocal talking, alongside some claps and snare rolls. It sounds like an interview and the recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/bl8PgmZ9iOc.wav"} +{"id": "blsYgo-B1k8", "caption": "A male vocalist sings the Lord\u2019s Prayer. The tempo is medium with Keyboard harmony, steady drumming, groovy basslines, rhythmic guitar,beat of shakers, vocal backup and a trumpet flourish. The music is simple, rhythmic, pleasant, catchy, soulful and punchy Reggae. There are sounds of people clapping and cheering in the background indicating that this is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/blsYgo-B1k8.wav"} +{"id": "bm5IT7e2vvI", "caption": "This is a Mexican folk music piece. The main theme is played by a marimba. There is a bass guitar in the background. The acoustic drums and the latin percussion provide the rhythmic background for the piece. It has a very playful atmosphere. The music could definitely be used in a children's movie/TV show or an advertisement targeted at kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/bm5IT7e2vvI.wav"} +{"id": "bmVd2Zj8_Cc", "caption": "This dance pop song features a male voice singing the main melody in a foreign language. This is accompanied by percussion playing a dance beat. The percussion is programmed. The bass plays the root notes of the chords. Synth sounds are played in the background. Bowed lute play fills in between lines to give this song a middle-eastern feel. This song can be played in a club. The mood of this song is flirty.", "audio": "/zhanghaomin/datas/musiccap/music_data/bmVd2Zj8_Cc.wav"} +{"id": "bpKbpKZB0Q0", "caption": "This is an amateur recording of a percussive jam over a backing track that has the acoustic guitar and hollering male vocals singing in the Spanish language, iconic features of latin folk music. Two pairs of maracas are being played to create the rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/bpKbpKZB0Q0.wav"} +{"id": "bpaq5wQKOkU", "caption": "This is a music production tutorial video. There is a male voice teaching a sound design technique. There is an electronic snare drum beat speeding up with a shifting pitch. A simple synth tune is playing in the background. The sounds used in the video are very common, so it would not be worth the hassle to sample these sounds. Instead, parts of the track could be used in advertisement jingles.", "audio": "/zhanghaomin/datas/musiccap/music_data/bpaq5wQKOkU.wav"} +{"id": "bpwO0lbJPF4", "caption": "The low quality recording features a rock song that consists of filtered echoing flat male vocals, energetic muffled drums, energetic cymbals, snare rolls, uptempo electric guitar melody and groovy bass. It sounds manic and muffled, like it lacks the bass and overall frequency balance.", "audio": "/zhanghaomin/datas/musiccap/music_data/bpwO0lbJPF4.wav"} +{"id": "bqMgL5qmZ-k", "caption": "This instrumental song features a didgeridoo being played by the vibrating of the lips. This features a continuous droning sound inter-spread with bass sounds. This is accompanied by a handpan playing the percussion and backing notes. This song can be played in a movie featuring a tribal initiation ritual.", "audio": "/zhanghaomin/datas/musiccap/music_data/bqMgL5qmZ-k.wav"} +{"id": "bqPCtwibgPg", "caption": "This audio is an instrumental. The tempo is medium with an acoustic guitar monotone rhythm with a male voice giving instructions. The notes went from low to high. This clip is instructional audio on how to tune a guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/bqPCtwibgPg.wav"} +{"id": "bqeVxA97TQU", "caption": "This techno song features a synth playing the main melody. It is based on chord structures. The bass plays the root notes of the chords. The percussion is programmed. The kick plays on every count and the hi-hat plays on the 'and' of every count. After four bars, the kick plays an eighth note rhythm. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/bqeVxA97TQU.wav"} +{"id": "bqvl7IbPteU", "caption": "This music is an electric guitar instrumental. The tempo is medium with a loud and energetic riff . The audio quality is inferior as it is a Home recording ,which is why the music is boomy and there are sounds of people talking in the background and some static.", "audio": "/zhanghaomin/datas/musiccap/music_data/bqvl7IbPteU.wav"} +{"id": "br4A2uNud50", "caption": "This music is a lively instrumental. The tempo is fast with bright trumpet harmony of French horns, trumpets accompaniment and a steady, punchy bass drum rhythm. The music is upbeat, punchy, buoyant, spirited, lively and vivacious. The audio quality is an amateur recording. This music is a live performance with ambient sounds of people clapping and cheering .", "audio": "/zhanghaomin/datas/musiccap/music_data/br4A2uNud50.wav"} +{"id": "brEMnFXsTqo", "caption": "This is an electronic music piece with characteristics of the German industrial scene. A sharp synth is playing the main theme while there is a faint high-pitched pad in the background. A transition effect is used before the drum beat starts. The rhythmic background is provided by a medium tempo electronic drum beat. There is an eerie atmosphere to this piece. It could be used in the soundtrack of a dystopian-future themed movie or a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/brEMnFXsTqo.wav"} +{"id": "bsz_enSJSVk", "caption": "This is a clip which sees a solo bass guitarist play a series of motifs in a bluesy style. The playing oscillates between a low phrase and high notes to which the player slides down.", "audio": "/zhanghaomin/datas/musiccap/music_data/bsz_enSJSVk.wav"} +{"id": "bt7rDryN7G4", "caption": "This music is an electronic guitar instrumental. The tempo is medium with a harmonious electric guitar lead, steady drumming, subtle bass ,tambourine beats and synthesiser arrangement. The music is a pleasant, soothing, unhurried, calm, romantic, sentimental , sedate and lingering Electric Guitar, soft pop instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/bt7rDryN7G4.wav"} +{"id": "bt8iHoIf2mo", "caption": "The song is an instrumental. The song is slow tempo with a philharmonic orchestra playing a string section harmony, lower register harmony Ina lilting manner. The song is emotional and heartfelt. The song is a movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/bt8iHoIf2mo.wav"} +{"id": "bwHPVG6vbNQ", "caption": "The low quality recording features a live performance where the song is played on playback and it consists of sustained strings and piano melody, energetic crash cymbals, shimmering hi hats and toms roll, over which passionate male vocal and harmonizing background female vocals are singing. It sounds emotional, passionate and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/bwHPVG6vbNQ.wav"} +{"id": "bxF2vxTzlvo", "caption": "This is a pop music piece. There is a female vocalist singing melodically in the lead. The acoustic guitar is playing the main tune while the bass guitar is playing in the background. The rhythm is provided by a slow tempo acoustic drum beat. The atmosphere is emotional. This piece could be used in the soundtrack of a romance movie where the characters are missing each other at night.", "audio": "/zhanghaomin/datas/musiccap/music_data/bxF2vxTzlvo.wav"} +{"id": "bxZeGrM_0ac", "caption": "The low quality recording features a jazz song that consists of a saxophone solo melody played over hollow snare, groovy double bass, shimmering hi hats, shimmering shakers and brass melody. It sounds uptempo, groovy and passionate - like something you would hear in a jazz club.", "audio": "/zhanghaomin/datas/musiccap/music_data/bxZeGrM_0ac.wav"} +{"id": "bxoJOfGx3hM", "caption": "The low quality recording features a female opera vocalist singing over sustained strings. There is tinny metallic percussive foley at one point in the loop. It is a bit quiet, but it also sounds dynamic, emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/bxoJOfGx3hM.wav"} +{"id": "by57LpTlGbs", "caption": "This reggae song features a male voice singing vocals at a high pitch, almost screaming. This is accompanied by percussion playing a reggae beat. The bass plays a groovy lick and plays a chromatic run of five notes to reach the note to start the chorus. A guitar strums one chord on alternate counts. This song can be played in a Caribbean themed party.", "audio": "/zhanghaomin/datas/musiccap/music_data/by57LpTlGbs.wav"} +{"id": "bzOeufhFITk", "caption": "The low quality recording features a jingle that consists of harmonizing vocals talking over snare roll, toms roll, brass melody and groovy bass, after which there is a folk song that starts playing. The folk song contains strings melody, bouncy snare, shimmering hi hats and synth keys chords. It sounds energetic and exciting, and like something you would hear on some TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/bzOeufhFITk.wav"} +{"id": "bztxC9EFfCk", "caption": "A male vocalist sings this youthful Electro rock . The tempo is fast with an intense electric guitar feedback, hard hitting drumming, synthesiser arrangements and electronic sound articulation. The song is high-powered, punchy, intense, youthful,ambient, buoyant, passionate and psychedelic with a dance groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/bztxC9EFfCk.wav"} +{"id": "c-85TtcfVSI", "caption": "The low quality recording features a passionate male vocal, alongside harmonizing background vocals, singing over tinny snares, snappy rimshots, shimmering hi hats, groovy bass and electric guitar chords. It sounds groovy and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/c-85TtcfVSI.wav"} +{"id": "c-8SLUH5pp4", "caption": "This music is instrumental. The tempo is medium with a loud , distorted electric guitar harmony. The audio is inferior quality and the sound is raw, loud , unpleasant , boisterous and harsh. There is some noise, like a subdued song playing in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/c-8SLUH5pp4.wav"} +{"id": "c1hLduV1p88", "caption": "This song contains digital drums playing a simple dubstep groove with a strong snare sound. A subbass along with an aggressive synth sound playing the same melody one octave higher. This song may be playing in a Dubstep/Drum&Bass club.", "audio": "/zhanghaomin/datas/musiccap/music_data/c1hLduV1p88.wav"} +{"id": "c2akbbdS7I4", "caption": "This is an EDM/techno music piece with a loud synth lead. There is a strong bass and an upbeat electronic drum beat in the background creating an atmosphere of high energy which is essential to electronic dance music. This music could be used in nightclubs, techno DJ sets and EDM venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/c2akbbdS7I4.wav"} +{"id": "c3T1gWSVp6c", "caption": "The low quality recording features a regional Mexican song that consists of a passionate male vocal singing over brass melody, wooden percussions, tinny metallic percussions, groovy piano melody and groovy bass. It sounds joyful, happy and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/c3T1gWSVp6c.wav"} +{"id": "c4ftOyl3j_Y", "caption": "A solo timpani performance played with mallets featuring rolls and complex rhythms on two drums. The music feels serious, even militant.", "audio": "/zhanghaomin/datas/musiccap/music_data/c4ftOyl3j_Y.wav"} +{"id": "c5NGOcNyF4g", "caption": "This music is a lively instrumental. The tempo is fast with an animated clarinet lead, lively spanish guitar rhythm, ukulele accompaniment and bright tambourine /pandeireta beats. The music is upbeat, buoyant, peppy, cheerful, happy, playful and fun Latin Clarinet Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/c5NGOcNyF4g.wav"} +{"id": "c6Fiz5IznkU", "caption": "The low quality recording features an electric guitar melody played with a chorus effect on. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/c6Fiz5IznkU.wav"} +{"id": "c7IL4fDqs_I", "caption": "Someone is trying out different effect sounds with his e-guitar. There is a lot of delay/echo happening. It does not play a musical composition but rather exploring.", "audio": "/zhanghaomin/datas/musiccap/music_data/c7IL4fDqs_I.wav"} +{"id": "c8gD6153aNI", "caption": "This song features a drum solo being played. The hi-hat, snare, kick and toms are played in this clip. There are no other instruments in this song. There are no voices in this song. This song can be played in an instruction video.", "audio": "/zhanghaomin/datas/musiccap/music_data/c8gD6153aNI.wav"} +{"id": "c8uE3Q8p9Jo", "caption": "This instrumental song features a theremin being played. There seems to be another synth playing at the intro. The sound produced is eerie. A ring modulator tone is played through this audio clip. There are no voices in this clip. There are no other instruments in this clip. This song can be played in a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/c8uE3Q8p9Jo.wav"} +{"id": "c9JyKnsegog", "caption": "This song features the sound of a music box. It sounds like a melody of bells playing in compound time. There are no voices in this song. There are no other instruments. The song has a dreamy feel. This song can be used in a dream sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/c9JyKnsegog.wav"} +{"id": "c9h4p6325Xo", "caption": "A male vocalist sings this lilting melody. The tempo is medium with keyboard harmony, groovy bass line, steady drumming and mandolin harmony. The song is emotional, romantic, soulful, sentimental and soothing. This song is Regional Pop,", "audio": "/zhanghaomin/datas/musiccap/music_data/c9h4p6325Xo.wav"} +{"id": "c9tRbWSk7c4", "caption": "This song is a vocalisation by a female singer. The tempo is medium with an upbeat electronic guitar harmony, funky bass guitar, slick drumming and acoustic guitar accompaniment. The music is simple, engaging, pleasant, melodic, engaging and has a perky groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/c9tRbWSk7c4.wav"} +{"id": "cADT8fUucLQ", "caption": "A male vocalist sings this melodious pop song. The tempo is medium with piano accompaniment, rhythmic acoustic guitar, groovy bass line ,steady drumming and energetic vocal backup. The song is spirited, youthful, vivacious, popular, bright and engaging. The song is a live performance and there are sounds of people cheering, hooting hysterically and singing along. This song is a hit in K-Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/cADT8fUucLQ.wav"} +{"id": "cBd0yZ27dtA", "caption": "The song is a latin american dance song suitable for salsa dancing. There are brass instruments, traditional percussion instruments like bongo drums, and the male vocal group sings in a cheery way in Spanish.", "audio": "/zhanghaomin/datas/musiccap/music_data/cBd0yZ27dtA.wav"} +{"id": "cCyfADwHiWs", "caption": "This is a nu-metal/alternative metal music piece. There is a male vocalist singing in a harsh, shout-like manner in the lead. The main melody is being played by a distorted electric guitar with a strong bass guitar backing. There are various electronic elements such as a crowd cheering sample and an evolving synth sound adding texture to the piece. The rhythmic background consisted of a loud metal acoustic drum beat and secondary percussive elements such as steel percussion. The atmosphere is energetic and violent. This piece could be used in the soundtrack of an action-filled/shootout video game. It could also be playing in the background at a metal bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/cCyfADwHiWs.wav"} +{"id": "cF7317DK0NQ", "caption": "Someone is playing a melody in the higher midrange on a cello. In the background you can hear someone playing along on a cembalo. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/cF7317DK0NQ.wav"} +{"id": "cFIZraIPAXE", "caption": "This music is instrumental. The tempo is medium fast with synthesiser arrangements , digital drums and electronic music . The music is upbeat, pulsating, youthful, buoyant, exciting, punchy , psychedelic and has propulsive beats with a dance groove. This music is EDM/Techno.", "audio": "/zhanghaomin/datas/musiccap/music_data/cFIZraIPAXE.wav"} +{"id": "cG1dpyC8gV4", "caption": "This clip features two male voices in conversation. The sound of a tabla is played. There is no music in this clip. There are no other instruments in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/cG1dpyC8gV4.wav"} +{"id": "cGUhG5PZp0A", "caption": "This is an amateur recording of a vocal cover. There is a male vocalist singing out-of-tune over a pop music piece playing in the background while driving a car. In the backing track there is a female vocal. A strong bass could be heard. There are also strings barely audible from the poor acoustics of the setting. Overall, it is a recording of poor quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/cGUhG5PZp0A.wav"} +{"id": "cGorUmWMrwo", "caption": "This music is instrumental. The tempo is slow with an acoustic guitar harmony, loud electric guitar feedback and fiddle. The music is intense, rugged, vivid, melancholic, pensive, raw, powerful, emphatic and strong. This music is classic Blues Country Music.", "audio": "/zhanghaomin/datas/musiccap/music_data/cGorUmWMrwo.wav"} +{"id": "cGrQw46ftj0", "caption": "The low quality recording features an acoustic rhythm guitar melody, arpeggiated harp melody, simple bass and sustained strings melody. It sounds soulful and passionate - like a traditional song.", "audio": "/zhanghaomin/datas/musiccap/music_data/cGrQw46ftj0.wav"} +{"id": "cHGziT0hrZU", "caption": "A male vocalist sings this energetic Rock and Roll song. The song is fast tempo with enthusiastic electric guitar, hard hitting drums, groovy bass lines and keyboard harmony. The song is vibrant, high energy, powerfully,passionate, emphatic, vehement, intense and youthful. This song is classic rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/cHGziT0hrZU.wav"} +{"id": "cHMDIt3-TsE", "caption": "This clip features an electric guitar being played. This electric guitar has a distortion effect. A chorus effect is also added. The distortion guitar starts off with a descending lick on the pentatonic scale followed by palm muted power chords. A few double stops are played and at the end, a string bend is played. There are no other instruments in this song. There is no voice in this clip. This song can be used in a demo of a chorus effects pedal.", "audio": "/zhanghaomin/datas/musiccap/music_data/cHMDIt3-TsE.wav"} +{"id": "cJ80eZY03Yg", "caption": "The low quality recording features a live performance of an orchestra and it consists of loud brass melody, mellow woodwinds melody, suspenseful violin melody and muffled percussion. It sounds epic, powerful and passionate. The recording is in mono, a bit noisy and it is reverberant as it was performed in a large concert hall.", "audio": "/zhanghaomin/datas/musiccap/music_data/cJ80eZY03Yg.wav"} +{"id": "cJD5JFWnxNo", "caption": "This song contains a female kid's voice singing with a little reverb and delay in her voice. An e-bass is playing a simple line along with a piano playing major chords. Panned to both sides of the speakers you can hear different percussive elements such as ride cymbal hits, shaker and bongos. Another keyboard sound is playing the main melody taking turns with the singer. Some twinkling sound adds single notes on top to round up the lullaby. This song may be playing for a kids tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/cJD5JFWnxNo.wav"} +{"id": "cKmK-nFdMXM", "caption": "Someone is playing a dynamic piece on timpanis. There is a lot of reverb in this recording. This song may be playing as part of a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/cKmK-nFdMXM.wav"} +{"id": "cLIump75aC0", "caption": "This amateur recording features low quality audio. The main sound heard is that of tap dancing to a song. The song features a male voice singing the main melody. The rest of the instruments are not clearly audible. A bass plays the root notes of the chords. The percussion plays a simple beat. Other instruments are not audible.", "audio": "/zhanghaomin/datas/musiccap/music_data/cLIump75aC0.wav"} +{"id": "cMhajmOBr0c", "caption": "The clip is of a Christian worship song - a gospel song. It's a powerful ballad with violins which add an uplifting emotional effect. The male singer has a smooth and gentle voice. There's an uplifting and soulful choir performing backing vocals.", "audio": "/zhanghaomin/datas/musiccap/music_data/cMhajmOBr0c.wav"} +{"id": "cOgNXgF21u4", "caption": "The low quality song features a cover of a ballad song and it consists of arpeggiated acoustic guitar melody and passionate male vocal singing over it. The recording is very noisy and in mono, like it was recorded with a phone, but regardless it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/cOgNXgF21u4.wav"} +{"id": "cOsm3r-xKEE", "caption": "The low quality recording features a reggae song that consists of a flat male vocal, alongside harmonizing background male vocals, singing over shimmering shakers, offbeat piano chords, brass melody, wide toms, tinny echoing snare and punchy kick layered with it. It sounds upbeat and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/cOsm3r-xKEE.wav"} +{"id": "cQWJeYfyw8Y", "caption": "This feels like a romantic ballad. The bansuri plays a soothing melody and the male vocalist comes in with a beautiful and gentle voice. This is an Indian song and it is emotional and brings about stillness. The acoustic guitar plays arpeggios.", "audio": "/zhanghaomin/datas/musiccap/music_data/cQWJeYfyw8Y.wav"} +{"id": "cQX-WgT0ACQ", "caption": "A guitarist is tuning his guitar making string noises, peg sounds and fretboard noises. The audio is very bad with a boomy low end. The conversation is engaging and keeps the crowds occupied as the guitarist gets ready for the next song.", "audio": "/zhanghaomin/datas/musiccap/music_data/cQX-WgT0ACQ.wav"} +{"id": "cQpK9zs_uv0", "caption": "This is the live performance of a percussion piece. There is a playful sounding jazz steel pan solo being performed on stage. The atmosphere is easygoing. This piece could be used during tropical scenery shots in a movie with a summer/vacation theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/cQpK9zs_uv0.wav"} +{"id": "cS2gRhH6it4", "caption": "This is a Hindu music piece. There is a female vocalist singing at a medium-to-high pitch in a devotional manner. A sitar provides a melodic background. The tabla is being played in the rhythmic background. The atmosphere is spiritual. This piece could be played at religious events and online content related to Hindu religion.", "audio": "/zhanghaomin/datas/musiccap/music_data/cS2gRhH6it4.wav"} +{"id": "cSBRb4KF5xs", "caption": "The song is an instrumental. The song is in medium tempo with a cello playing percussively, a clarinet in melody and supported in harmony by a bass clarinet and a trombone. The song is a rock song cover played live. The song is engaging and rich in quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/cSBRb4KF5xs.wav"} +{"id": "cT-KZPVpU9M", "caption": "The low quality recording features a flat male vocal talking over a classical song that consists of sustained strings melody. It sounds dramatic and suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/cT-KZPVpU9M.wav"} +{"id": "cTJqIkSuf6s", "caption": "The low quality recording features a live performance of a rock song and it consists of flat male vocal singing over arpeggiated electric guitar melody, groovy bass guitar, shimmering hi hats, snappy rimshots and punchy kicks. In the background, there are some crowd singing and crowd cheering noises. It sounds emotional and a bit addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/cTJqIkSuf6s.wav"} +{"id": "cTzJlLzN-xU", "caption": "A male vocalist sings this famous Beatle\u2019s song in Country style. The tempo is medium with an auto harp accompaniment, groovy bass line, keyboard harmony, female vocal backup and sound of clapping and cheering indicating that this is a live performance . The song is cheerful, melodious, engaging, energetic,youthful and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/cTzJlLzN-xU.wav"} +{"id": "cWOohqFud6g", "caption": "The low quality recording features a DJ scratching a vinyl of a jungle song that consists of punchy kick and snare hits layered with energetic crash cymbal and groovy bass. The song sounds thin as it is probably playing on a speaker. The recording itself is noisy and in mono. It sounds energetic and aggressive overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/cWOohqFud6g.wav"} +{"id": "cWvkOY6OKss", "caption": "This song features a cello being played at the higher pitches. Toward the end, a few wrong notes are played and a scratchy sound is heard. There are no other instruments in this song. There is no voice in this song. This song can be played in a children's animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/cWvkOY6OKss.wav"} +{"id": "cX926M1_LqM", "caption": "The low quality recording features a groovy synth keys melody and synth keys bass playing together. It sounds jazzy, funky, boomy and the recording is noisy and in mono. Sounds like something you would hear in jazz bars.", "audio": "/zhanghaomin/datas/musiccap/music_data/cX926M1_LqM.wav"} +{"id": "cXEJWtj2kT8", "caption": "This song features a bass guitar. Slap bass is played. The riff is repetitive. There are no other instruments in this song. The tempo of this song is moderate. There are no voices in this song. This bass piece can be played in a funk song.", "audio": "/zhanghaomin/datas/musiccap/music_data/cXEJWtj2kT8.wav"} +{"id": "cY3g6N5Sokk", "caption": "A female singer sings this iconic pop cover. The song is slow tempo with a piano accompaniment, strong drum hit and low pitched keyboard harmony. The song is tense and mysterious. The song is a modern pop cover and has poor audio quality with hissing and buzzing tones.", "audio": "/zhanghaomin/datas/musiccap/music_data/cY3g6N5Sokk.wav"} +{"id": "cYRsnYEPIiM", "caption": "This is a marching band piece performed by an orchestra. There are trumpets playing the main theme while tuba and cello are playing the bass notes. There is also a constant string part holding the root notes of the melody. The snare drums are playing an accentuated, militaristic drum line. There is an epic atmosphere that gives a call-to-action feeling. This piece could be used in the soundtracks of action movies and war movies in particular. It could also be used in the soundtracks of video games from the action and first-person-shootout genres.", "audio": "/zhanghaomin/datas/musiccap/music_data/cYRsnYEPIiM.wav"} +{"id": "cYSW6Y884dA", "caption": "The low quality recording features wide acoustic guitar melodies playing over shimmering hi hats, followed by acoustic bass guitar. It sounds passionate and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/cYSW6Y884dA.wav"} +{"id": "c_a74UO2ftg", "caption": "This is a four on the floor style of production. The song is a drum and bass type of song with a bright and fuzzy synth to add a melodic element. The first part of the song feels suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/c_a74UO2ftg.wav"} +{"id": "ca-rGWC4xPc", "caption": "The low quality recording features a pop song played on playback while a male vocalist is mumbling over it. The song consists of a groovy bass, shimmering hi hats, punchy kick and snare hits, mellow bell melody, and flat repetitive female vocals singing over it. The recording is noisy, which is very audible at the very end of the loop where there is a finger licking sound. It still sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/ca-rGWC4xPc.wav"} +{"id": "caFMauLQvd4", "caption": "Someone is playing a didgeridoo while someone is playing a flute melody in the high-to midrange dropping down in pitch. You can hear something that sounds like percussion but without a steady rhythm. In the background birds are chirping. This song may be playing gathered around a bonfire.", "audio": "/zhanghaomin/datas/musiccap/music_data/caFMauLQvd4.wav"} +{"id": "cabjr3xtcR4", "caption": "This song contains digital drums with a kick on every beat and an open hi hat on the backbeat. A synth bass is playing a melody along with an e-bass. A male voice is singing along with a male backing singer. The crowd is cheering and singing along. This is an amateur recording and of poor audio-quality. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/cabjr3xtcR4.wav"} +{"id": "cbq6Q2htPRM", "caption": "The music contains an energetic female voice which is sharp and clear. It is between rapping and singing. In the background are electronic music effects, at medium to high pitch. The atmosphere is smooth and confident. A drum kit plays a mid tempo pattern and It is very digital sounding.", "audio": "/zhanghaomin/datas/musiccap/music_data/cbq6Q2htPRM.wav"} +{"id": "ccsgja0XsWE", "caption": "This music is an energetic instrumental. The tempo is fast with a synthesizer groove followed by instructions in a male voice and with another synthesiser groove. This is a synthesiser, demonstration, review or tutorial on how to add layers to a sound track. The music is energetic, youthful, enthusiastic, high-spirited , funky and pulsating.", "audio": "/zhanghaomin/datas/musiccap/music_data/ccsgja0XsWE.wav"} +{"id": "cd5BIQoHyPI", "caption": "A fast techno four on the floor beat with a repetitive driving bass, wild synthesizer sounds processed with delay. An energetic feeling that might be considered acid house.", "audio": "/zhanghaomin/datas/musiccap/music_data/cd5BIQoHyPI.wav"} +{"id": "cdIvqn14xgI", "caption": "This music is instrumental. The tempo is fast with a droning melody of didgeridoo. The music is complex, powerful, emphatic and the droning tone makes it trippy, psychedelic, meditative and hypnotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/cdIvqn14xgI.wav"} +{"id": "cdUk-F-5NCI", "caption": "This music is an electric guitar instrumental. The tempo is fast with an enthusiastic electric guitar riff with the voice of a man giving instructions. The music is powerful,emphatic, loud, groovy, youthful, skillful and engaging. This clip is an electric guitar lesson/tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/cdUk-F-5NCI.wav"} +{"id": "ce03XKuyDtk", "caption": "The low quality recording features a wide electric guitar arpeggiated melody. The recording is noisy and it sounds like some kind of tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/ce03XKuyDtk.wav"} +{"id": "cf-IIqhveKw", "caption": "This is an edited version of a pop music piece. The song is in minor key which gives it a melancholic aura. There is a male vocalist singing emotionally in a sigh-like manner accompanied with a piano tune and atmospheric strings in the background. However, due to the artificially added gain, the piece is too loud and the audio is distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/cf-IIqhveKw.wav"} +{"id": "cfeTMVWFHLo", "caption": "This is a live recording of a quartet. The group consists of upright bass, cello, acoustic guitar and flute. The instrumental has a pop feel to it, with the flute playing the melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/cfeTMVWFHLo.wav"} +{"id": "chfTjqlrFQQ", "caption": "This song is a crossover of a reggae song with a soul song. This features a male voice singing the main melody. It starts off with the voice which is accompanied by the guitar, bass and percussion playing in the pause between lines. During the pause, a synth sound is played which is modulated by a ring modulator. After the pause, the voice starts the main melody. Trumpets play a melody. The bass and percussion continue to play with a reggae feel. Female backing voices sing vocables. This song is relaxing. This song can be played at the end of a war movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/chfTjqlrFQQ.wav"} +{"id": "chw8sAKOM5k", "caption": "The song is a middle eastern pop ballad with a singer who sounds emotional and reflective. The song is at a medium tempo. There is a violin embellishment, piano, and some relaxed pop drumming. This song would be heard in a middle eastern movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/chw8sAKOM5k.wav"} +{"id": "chwqnnaiYXw", "caption": "This is a classical music piece. The french horn is playing the main melody in a gentle manner. In the meantime, the piano is playing a backing tune. There is a serene atmosphere to this piece. This music could go well in the soundtrack of a still life TV series. It could also be playing in the background at a classy restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/chwqnnaiYXw.wav"} +{"id": "ciJOulWFhfA", "caption": "The low quality recording features a jazz song being played in a big room and it consists of a saxophone solo melody over groovy drums. Due to frequency clashing, it sounds muddy and muffled and it has an unbalanced stereo image, as it was probably recorded with a poor quality microphone. It is still energetic and easygoing at the same time - thanks to that saxophone.", "audio": "/zhanghaomin/datas/musiccap/music_data/ciJOulWFhfA.wav"} +{"id": "cjTrK-kA6x0", "caption": "The low quality recording features a short snippet of breathy flute melody at the beginning of the loop, followed by birds chirping and water flowing sounds, due to the fact that it was recorded outdoors. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/cjTrK-kA6x0.wav"} +{"id": "ckOe-8qdaew", "caption": "A male singer sings this cool spirited melody. The song is medium tempo with a steady drumming rhythm, guitar playing lead, guitar strumming, strong bass line and various percussion hits. The song is exciting and energetic. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/ckOe-8qdaew.wav"} +{"id": "clefr8E-iZQ", "caption": "Someone is playing an e-guitar with different effects over an acoustic drumgroove. Some of the sounds are panned to the right and left side of the speakers. This song may be playing at home practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/clefr8E-iZQ.wav"} +{"id": "cm62raVagEE", "caption": "The classical music features an intense brass section, followed by energetic drums, repetitive suspenseful woodwinds and wide strings melody. It sounds cinematic, epic, powerful, intense and suspenseful - like a background music for a very dynamic scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/cm62raVagEE.wav"} +{"id": "cmJj7SxQEp8", "caption": "This reggae song features a male voice singing the main melody. This is accompanied by percussion playing a reggae beat. The bass plays a single note on the fourth count of each bar. There are no other instruments in this song. This song can be played in a club as a dance song.", "audio": "/zhanghaomin/datas/musiccap/music_data/cmJj7SxQEp8.wav"} +{"id": "cn-SilfYLZo", "caption": "The song is an instrumental. The tempo is medium with footstep like percussion, mysterious bell tones, tremolo effects, string section harmony, crescendoing tones and various percussion hits. The song is suspenseful and ominous. The song is a movie soundtrack with bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/cn-SilfYLZo.wav"} +{"id": "cnmedj0fYTQ", "caption": "A distorted and arpeggiated e-guitar sequence is repeating the same phrase while a female voice is streaming with an effect on her voice. She sounds aggressive and frustrated. This song may be playing in an aggressive, fast paced action-movie chasing scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/cnmedj0fYTQ.wav"} +{"id": "cnvmLwFZr28", "caption": "This is a Korean indie rock piece. There is a male vocalist in the lead singing melodically. The main tune is being played by an acoustic guitar with an electric guitar and a bass guitar backing. There is a 4/4 slow tempo acoustic drum beat playing in the rhythmic background. The atmosphere is easygoing. This piece could be used in the soundtrack of a drama movie or TV series that takes place in Korea.", "audio": "/zhanghaomin/datas/musiccap/music_data/cnvmLwFZr28.wav"} +{"id": "coG_EznBmzE", "caption": "This music is an electronic instrumental. The tempo is medium fast with digitally arranged music. The music is futuristic, enigmatic, psychedelic, contemporary, and ambient with a dance groove. This is contemporary EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/coG_EznBmzE.wav"} +{"id": "colnyHv9CAA", "caption": "This country song features a male voice singing in a Southern accent. The main melody is a typical country melody. This is accompanied by a violin playing backing notes. The guitar strums chords. The double bass plays the root note and lower fifth of the chords. This song has a happy mood. At the end, there are multiple male voices singing one word together. This song can be played in a happy Country Western movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/colnyHv9CAA.wav"} +{"id": "cor2HckYTE8", "caption": "This song features a mellotron playing a melody using a descending bassline. The higher notes stay the same for the first six counts and then change to a descending pattern. This is followed by short arpeggiated notes. The quality of the recording is low. There are no other instruments in this song. This song can be played in a practice session for somebody learning the keyboard.", "audio": "/zhanghaomin/datas/musiccap/music_data/cor2HckYTE8.wav"} +{"id": "cp8t27oT_ww", "caption": "The song is an instrumental. The tempo is medium with a guitar accompaniment and leads into a strong drumming rhythm and bass line. The song is exciting and energetic. The song is a movie soundtrack for a travel show or a documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/cp8t27oT_ww.wav"} +{"id": "cqeVEFFzz7E", "caption": "Loud sound effects such as smoldering sounds, water splashing, and an explosion. Quick scene transition sound as well a short male laugh. Background score is mellow orchestral featuring a string pad with an oboe taking the lead melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/cqeVEFFzz7E.wav"} +{"id": "cqolOXDF86g", "caption": "Some digital kicks with a lot of punch and a strong snare sound can be heard. This is no musical composition or rhythm. it sounds more like someone is trying out sounds. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/cqolOXDF86g.wav"} +{"id": "crToMuDxmL8", "caption": "This music is a lively country music instrumental. The tempo is fast and upbeat with a banjo, and an instrument that sounds like a fiddle. The instrument is like pedal steel being played like a fiddle.the music is vibrant, vigorous, vivacious, cheerful, happy, sunny, happy and upbeat. This music is classic Country Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/crToMuDxmL8.wav"} +{"id": "cs-zcTX2tRA", "caption": "A female child singer sings this soaring melody. The song is medium tempo with a steady drum rhythm, groovy bass line, piano accompaniment and keyboard harmony. The song is lilting and inspiring. The song is a pop song with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/cs-zcTX2tRA.wav"} +{"id": "ctJI7pCbxAo", "caption": "This pop song features a male voice singing the main melody. Other voices sing backing vocals using the same melody. This is accompanied by programmed percussion playing a dance beat. A wave synth plays a repetitive melody. The bass plays the root notes of the chords. Toward the end of the song, a tabla is played. The mood of this song is happy. This song can be played in a club as a dance song.", "audio": "/zhanghaomin/datas/musiccap/music_data/ctJI7pCbxAo.wav"} +{"id": "cu0k3Uclp1I", "caption": "This is a live recording. We hear a set of Indian bagpipes, otherwise known as mashak, playing a complex motif. There are two singers doing open-mouthed humming in contrasting high and low pitches simultaneously. We hear the applause and cheering of a crowd as well. At the beginning, a male speaker and female speaker each make some comments in a South Asian language.", "audio": "/zhanghaomin/datas/musiccap/music_data/cu0k3Uclp1I.wav"} +{"id": "d-AcpHG7OjU", "caption": "This is an instrumental percussion piece recording. There is a drummer playing rudiments in rapid procession on a practice pad. A loud metronome beep can be heard close by. This piece could be used in rudimentary education during drum lessons.", "audio": "/zhanghaomin/datas/musiccap/music_data/d-AcpHG7OjU.wav"} +{"id": "d-KxsdWX9xE", "caption": "The low quality recording features a blues song that consists of filtered monotone male vocal singing over groovy bass, groovy organ keys, chords, soft kick hits, punchy snare and shimmering cymbals. The song is poorly mixed, as the vocals are not so much in the face as they should be, probably because the bass is eating the other elements - making it sound boomy.", "audio": "/zhanghaomin/datas/musiccap/music_data/d-KxsdWX9xE.wav"} +{"id": "d0Uz_RnRV88", "caption": "The low quality recording features a cover of a rock song that consists of repetitive acoustic rhythm guitars chord progressions. The progression is played a bit sloppy and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/d0Uz_RnRV88.wav"} +{"id": "d1VB1vA-UsI", "caption": "This piece contains a modified didgeridoo sound. Sound effects were made to create an atmosphere that is unnatural and ominous. This sound could be used in an outer space dystopian sci-fi movie. It could also be used in a video game that involves robots/automated mechanisms.", "audio": "/zhanghaomin/datas/musiccap/music_data/d1VB1vA-UsI.wav"} +{"id": "d1nz5tZckSA", "caption": "Trio recorded live in a concert hall with a loud upright bass, piano and acoustic guitar playing a solo. Jazz feel and chord progression with no drums. Heartfelt performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/d1nz5tZckSA.wav"} +{"id": "d20qTsF6ll8", "caption": "A male vocalist sings this upbeat retro song. The tempo is medium with an infectious electronic guitar, hard hitting drums, rhythmic acoustic guitar and funky bass. The song is rhythmic, groovy, upbeat, catchy, and energetic. This song is Retro Rock and Roll.", "audio": "/zhanghaomin/datas/musiccap/music_data/d20qTsF6ll8.wav"} +{"id": "d2gHgzfC-Oo", "caption": "The low quality recording features a cover of a rock song and it consists of an electric guitar feedback playing over a live performance instrumental that has crowd cheering, crowd clapping noises, smooth bass guitar, repetitive synth bells melody, punchy snare and kick hits and shimmering tambourine. It sounds emotional and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/d2gHgzfC-Oo.wav"} +{"id": "d352jaSSiFw", "caption": "The song is background audio of an animated tv show. The song is idyllic and performed by an orchestra with organ playing lead, flutes and rhythm section. The song is of average audio quality. The audio track is animated and cartoon-like.", "audio": "/zhanghaomin/datas/musiccap/music_data/d352jaSSiFw.wav"} +{"id": "d6-bQMCz7j0", "caption": "This audio contains a deep voice processed with a vocoder singing a melody. The voice is chopped at different points creating a rhythm that reminds of technomusic. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/d6-bQMCz7j0.wav"} +{"id": "d61plJ66vE8", "caption": "The low quality recording features a fruity male vocal singing over steel drums melody, electric guitar melody, brass stabs, punchy kick and snare hits, energetic crash cymbal, groovy bass, shimmering shakers and sustained organ keys chord. It sounds joyful, happy and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/d61plJ66vE8.wav"} +{"id": "d6nURbq86zM", "caption": "The song is an instrumental. The tempo is medium with different sized bells played with gongs producing various tones with vibrato and echo effects. The sounds are very meditational and therapeutic in nature. The audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/d6nURbq86zM.wav"} +{"id": "d6w3d9S1LVM", "caption": "This is a metalcore/post-hardcore music piece. There is a male vocal singing using the vocal fry technique. A distant piano melody can be heard. There is an electronic drum beat with a heavy reverb effect. Later on, a string sound starts playing and adds texture to the melodic background. The atmosphere is dramatic and rebellious. This piece can be used in the soundtrack of a teenage drama movie, especially where one of the characters is experiencing a breaking point.", "audio": "/zhanghaomin/datas/musiccap/music_data/d6w3d9S1LVM.wav"} +{"id": "d9Oa-2_r2j0", "caption": "The low quality recording features an acoustic guitar tuning string by string. It sounds a bit harsh and loud. Sounds like a tutorial for tuning a guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/d9Oa-2_r2j0.wav"} +{"id": "d9r_kYpOvW8", "caption": "The song is an instrumental. The song is slow tempo with an organist playing a tune on a church organ and sounds of switches being turned on and off. The song is emotional and sounds devotional in nature. The audio quality is poor with ambient room sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/d9r_kYpOvW8.wav"} +{"id": "dAAwzwexvUQ", "caption": "A female singer sings this vocal monologue. The song is medium tempo with a groovy moog bass line, electro mix keyboard harmony tones, steady drumming rhythm and very quirky electronic tones. The song is groovy and retro dance music.", "audio": "/zhanghaomin/datas/musiccap/music_data/dAAwzwexvUQ.wav"} +{"id": "dBAeAk7dXnU", "caption": "This song comes from a music box. The backing melody is repetitive which is played in a set of three notes followed by a set of two notes. The main melody is high pitched and sounds like bells. There are no other instruments in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/dBAeAk7dXnU.wav"} +{"id": "dCCh6POPUeA", "caption": "This song contains acoustic drums playing together with an e-bass. An accordion is playing the main melody together with a flute playing in a higher register. This song may be playing while waiting in line for a phone call.", "audio": "/zhanghaomin/datas/musiccap/music_data/dCCh6POPUeA.wav"} +{"id": "dDKUjMHerLs", "caption": "A male Russian singer sings this rap vocals with a female backup singer in vocal harmony. The song is fast tempo with techno drumming rhythm, percussive bass line, keyboard accompaniment and sonic effects. The song is a techno dance hit. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/dDKUjMHerLs.wav"} +{"id": "dEc7tV30KJo", "caption": "Female singers sing in funny animated vocals. The song is medium tempo with a groovy bass line, keyboard accompaniment, arpeggiated harmony tones and steady drumming rhythm. The song is cheerful and energetic. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/dEc7tV30KJo.wav"} +{"id": "dHDosntsNho", "caption": "A female singer sings in a huge arena live along with crowds singing along with her in vocals. The song is medium tempo with steady drumming rhyme and giant drum rolls, violin playing solo, a brass band section and orchestra playing along. The song is energetic, cheerful and highly popular. The audio quality is very poor with heavy ambient crowd noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/dHDosntsNho.wav"} +{"id": "dHGAXJ9RPJs", "caption": "A male vocalist sings this spirited Rock song. The tempo is fast with an upbeat Amplified keyboard harmony, hard hitting drums, punchy bass lines and a dominating electric guitar accompaniment. The vocals are subdued for a Rock song. The song is youthful, vibrant, energetic, enthusiastic, buoyant, punchy and vivacious. This song is Classic Hard Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/dHGAXJ9RPJs.wav"} +{"id": "dIPW9gLGSx8", "caption": "This is a Russian hardbass piece played in the background of a scissor sharpening video. The piece has a repeated theme being played by a synth bass while an electronic drum beat holds the rhythmic background. The atmosphere of the piece in the background is aggressive with industrial characteristics.", "audio": "/zhanghaomin/datas/musiccap/music_data/dIPW9gLGSx8.wav"} +{"id": "dKJk3JavNzo", "caption": "A male vocalist sings this lively African song. The tempo is fast with synthesiser arrangements, bright drumming and African percussive instruments. This song is a happy, cheerful, colourful, infectious ,captivating Nigerian Music.", "audio": "/zhanghaomin/datas/musiccap/music_data/dKJk3JavNzo.wav"} +{"id": "dLUobee5JEs", "caption": "This music is an electronic instrumental.the tempo is slow and monotone with synthesiser arrangements. The harmony is monotone with sounds of an ambulance siren, sighing or yawning in the background. The music is trippy, trance like, hallucinatory and psychedelic.", "audio": "/zhanghaomin/datas/musiccap/music_data/dLUobee5JEs.wav"} +{"id": "dMAp3dvs3kE", "caption": "This is a rock music piece with a leading male vocal. The electric guitar is playing the main melody while a simple rock beat is being played by the acoustic drums as the rhythmic background. It has the definitive qualities of 70s American rock music. It could be used in a movie taking place in the 70s. It could also be played at a rock bar or a sports bar in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/dMAp3dvs3kE.wav"} +{"id": "dMfKImuNJjA", "caption": "The low quality recording features muffled gunshots over a wide, low synth pad, reversed crash cymbal and haunting male vocals. It sounds suspenseful, intense and dramatic.", "audio": "/zhanghaomin/datas/musiccap/music_data/dMfKImuNJjA.wav"} +{"id": "dNK9bD3LNCc", "caption": "The low quality recording features a live performance of a country song that consists of a steel guitar melody, acoustic rhythm guitar chords and a walking bass guitar. There are some crowd noises in the background by which we can conclude that it is a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/dNK9bD3LNCc.wav"} +{"id": "dNOHIxD0j_Q", "caption": "This music is an animated instrumental. The. Tempo is fast with an intense electric guitar feedback, powerful backup vocalisation, boomy bass drops, intense drumming, tambourine or shaker beats, keyboard harmony and electric guitar riff. The music is engaging, bustling, energetic, melodious and seems to be burgeoning and increasing. The vocalisation is the backbone of this music, giving it an intense, mystical, impactful and enigmatic vibe. This music is Alternative Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/dNOHIxD0j_Q.wav"} +{"id": "dNQh2iLVAoY", "caption": "This audio contains someone playing a theremin. Playing around with the pitch. This may be playing in a comedic act.", "audio": "/zhanghaomin/datas/musiccap/music_data/dNQh2iLVAoY.wav"} +{"id": "dO3VsX4rKNc", "caption": "This heavy metal song features distortion guitars. One guitar plays power chords. Another guitar is playing a repetitive riff using palm muted arpeggiated notes. The keyboard plays chords in the background. The bass plays the root notes of the chords. The percussion plays a simple beat in common time. It starts off playing the kick and crash followed by three beats on the kick and ride. After four bars, a rock drum roll is played. This song can be played in a superhero movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/dO3VsX4rKNc.wav"} +{"id": "dPCj4WhTZ3c", "caption": "E-guitars are fingerpicking two different melodies in an arpeggio fashion while another distorted e-guitar is playing the main melody along with a -ebass breaking into the next part with the drums playing a loud groove with toms and crash cymbals. Before that part a male voice was talking before breaking into loud screaming in a deeper voice. This song may be playing live at a rock concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/dPCj4WhTZ3c.wav"} +{"id": "dPM24O4my-Q", "caption": "The low quality recording features a car engine, tire screeching and pulsating, filter mod synth sound effects, followed by string melody. The weird arrangement of sounds is making it sound chaotic. Sounds like a sync sound for cartoons.", "audio": "/zhanghaomin/datas/musiccap/music_data/dPM24O4my-Q.wav"} +{"id": "dS8AZdmn8Wk", "caption": "The low quality recording features a live performance of a classical song and it consists of sustained cello melody played over passionate piano melody, after which there is a plucked cello melody. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/dS8AZdmn8Wk.wav"} +{"id": "dSJpZQ8u_xY", "caption": "The Hindu Devotional Music features wide mixed harmonized vocals singing a very addictive cadence, followed by flat male vocal, wooden percussive elements and wide sustained synth pad chords. It sounds emotional, passionate and addictive - like something you would sing along to, even if you do now know the words.", "audio": "/zhanghaomin/datas/musiccap/music_data/dSJpZQ8u_xY.wav"} +{"id": "dSs4xfvATjc", "caption": "The Metal song features wide aggressive distorted electric guitars, punchy kick and snare hits, energetic crash cymbals, simple hi hats, groovy bass guitar, sustained synth pad melody and passionate female vocals singing over it. It sounds energetic, powerful, manic and aggressive - especially in the first part of the loop where there is a drum break.", "audio": "/zhanghaomin/datas/musiccap/music_data/dSs4xfvATjc.wav"} +{"id": "dSyue3RJllA", "caption": "This music is instrumental. The tempo is slow with an Oud solo. The music is minimalist, simple, melancholic, nostalgic, emotional, wistful, pensive; poignant and intense. This is Middle Eastern classical music.", "audio": "/zhanghaomin/datas/musiccap/music_data/dSyue3RJllA.wav"} +{"id": "dT7uHHQEYHQ", "caption": "The low quality recording features a pop song that consists of harmonizing vocals singing over punchy snare and kick hits and shimmering cymbals. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/dT7uHHQEYHQ.wav"} +{"id": "dTVkk4GSmNA", "caption": "A male voice is singing loud and soulfully. A saxophone is playing a slight variation of the singer's melody. A piano is playing bluesy/jazzy chord chops accompanied by an electric organ playing along with the melody. Panned to the left side of the speaker, a e-guitar is playing one single chord as a rhythmic element. The e-bass is playing a line along with a simple rimshot and shakers that are barely noticeable. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/dTVkk4GSmNA.wav"} +{"id": "dTsOP7Nfnpg", "caption": "The clip features a popular jingle played in a low-quality polyphonic style. There is an outdoor ambiance to the clip. The sounds are bright, high pitched, tinny.", "audio": "/zhanghaomin/datas/musiccap/music_data/dTsOP7Nfnpg.wav"} +{"id": "dUhE6H72Qpg", "caption": "The song is an instrumental. The song is medium tempo with ethereal harmony tones that fade gently. The song is psychedelic and soul searching. The song quality is poor. The song is very emotional and haunting.", "audio": "/zhanghaomin/datas/musiccap/music_data/dUhE6H72Qpg.wav"} +{"id": "dUlQepCYXgw", "caption": "This song features a flute playing the main melody. The flute plays staccato notes and allows only the last note to be sustained. This is accompanied by a cello playing the same melody in the lower register. There are no voices in this song. This song is an instrumental. This folk song features no other instruments. This song can be played in an animation movie featuring fairies.", "audio": "/zhanghaomin/datas/musiccap/music_data/dUlQepCYXgw.wav"} +{"id": "dVUgd8ot6BE", "caption": "This clip features 2 distortion guitars playing a metal song. A high pitched male voice sings the main melody. This is accompanied by percussion playing a simple rock beat in common time. A bass guitar plays a bassline with a descending run. The distortion guitars play power chords followed by a guitar lick. One of the guitars plays one chord a little after the other guitar making it sound dissonant. This song can be played in an action movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/dVUgd8ot6BE.wav"} +{"id": "dW4eW0Xreik", "caption": "The low quality recording features a live performance of a rock song and it features a passionate male vocal singing over groovy double bass, acoustic rhythm guitar, plucked violin melody and simple piano chords. It sounds reverberant, emotional, groovy and smooth - like something you would sing along to at the concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/dW4eW0Xreik.wav"} +{"id": "dYVy7moyQCc", "caption": "This music is instrumental. The tempo is fast with a spirited didgeridoo harmony. The music is droning, rhythmic, deep and rich with the rhythmic tapping /clapping. This is street busking with ambient sounds of people talking, bicycle bells and feet scuffling. The music is droning, hypnotic, meditative, trance and engaging.", "audio": "/zhanghaomin/datas/musiccap/music_data/dYVy7moyQCc.wav"} +{"id": "dakJh2CdT9Q", "caption": "This is an ominous, haunting, mysterious track which would do well in a horror movie or game. There's a chilling piano motif, some knocking sounds and a low sustained synth that almost sounds like orchestral cello.", "audio": "/zhanghaomin/datas/musiccap/music_data/dakJh2CdT9Q.wav"} +{"id": "dalyCstquy8", "caption": "This pop song features a female voice singing the main melody. Female voices sing backing vocals in between lines at the beginning. After three bars, the female voices sing in harmony with the main voice. This is accompanied by programmed percussion playing a simple beat. The snare is played on the third count of every bar. Synth strings play an epic style melody in the background. The bass plays the root notes of the chords. A piano plays a descending run in the first bar. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/dalyCstquy8.wav"} +{"id": "darQBSIlol8", "caption": "This is an ambient music piece. A low-to-mid range ambient synth is constantly holding a single note. There are moderate volume environmental sounds of a water stream and the singing of the birds. This is a very calming piece. This piece can be used in the background of meditation videos. It could also be used in scenery shots in documentaries.", "audio": "/zhanghaomin/datas/musiccap/music_data/darQBSIlol8.wav"} +{"id": "dbBlYyaFKTQ", "caption": "The low quality recording features a classical song that consists of a brass solo melody played over sustained brass melody and short flute lick. It sounds emotional, joyful and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/dbBlYyaFKTQ.wav"} +{"id": "dbenNuhAW_I", "caption": "This is a Vedic music piece. There are female vocals singing in a devotional manner. There is a veena playing a repeated theme for the melody. The rhythmic background is being provided by the tabla. The atmosphere is religious. This piece could be playing in the background at Hindu religious events.", "audio": "/zhanghaomin/datas/musiccap/music_data/dbenNuhAW_I.wav"} +{"id": "dbftWJH0OvA", "caption": "This music is instrumental. The tempo is slow and steady with a droning monotone , crystal bowl harmony. The sound is sharp, repetitive, incessant, relaxing, trance, therapeutic , hypnotic vibrations used in meditation or sound healing/therapy.", "audio": "/zhanghaomin/datas/musiccap/music_data/dbftWJH0OvA.wav"} +{"id": "dbldb9tq8ng", "caption": "The Soft rock song features a mellow female vocal singing the same melody as the lead electric guitar, followed by widely spread acoustic rhythm guitars, simple bass, soft kick hits, punchy snare, simple hi hats, shimmering open hats and energetic crash cymbals. There is a short snare roll at some point in the loop. The stereo bass guitar is what makes the stereo image imbalance and therefore the song sounds lower in quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/dbldb9tq8ng.wav"} +{"id": "dcY062mkf9g", "caption": "This slow pop song features a female voice singing the main melody. This is accompanied by a keyboard playing the chords in the background. The cello plays the low end notes. The voice has a calming tone. There is no percussion in this song. This song can be played in a dream sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/dcY062mkf9g.wav"} +{"id": "dcgwxlK3VVk", "caption": "Classic sped up video game music with vacuum sounds juxtaposed by 80's hard rock hair metal and thunder sounds effects.", "audio": "/zhanghaomin/datas/musiccap/music_data/dcgwxlK3VVk.wav"} +{"id": "deIj55UAxeo", "caption": "This is a rock music piece. The male vocalist is singing melodically in the Spanish language. The keyboard is playing the chords of the song while the electric guitar joins with the occasional fills. There is a relatively quiet bass guitar supporting them in the background. The acoustic drums provide a basic rock beat for the rhythm. It has an easygoing feeling. This piece could be used in a teenage drama taking place in a Spanish-speaking country.", "audio": "/zhanghaomin/datas/musiccap/music_data/deIj55UAxeo.wav"} +{"id": "dh9XweTn6rI", "caption": "The low quality recording features a pop song that consists of filtered, wide female vocal singing over mellow piano chords, sustained strings melody and filtered drums located in the left channel of the stereo image. At the very beginning there is a snap sound and at the end, there is a short snippet of another section which contains punchy kicks layered with energetic crash cymbals and arpeggiated synth melody. It sounds emotional and energetic, even though it sounds kind of papery and thin, since it lacks lower frequencies.", "audio": "/zhanghaomin/datas/musiccap/music_data/dh9XweTn6rI.wav"} +{"id": "diSfkEkTVkE", "caption": "The song is an instrumental. The tempo is medium with a DJ creating cool rhythmic structures; groovy drum rhythm, percussion hits, grunge tones and staccato notes. The song is exciting and energetic. The song is a techno dance tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/diSfkEkTVkE.wav"} +{"id": "dj-DWiV1z9g", "caption": "This audio contains someone playing a complex groove on tablas along with someone playing a solo on a zitar with the same complex rhythm. This song may be playing in a live concert having a little solo together with instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/dj-DWiV1z9g.wav"} +{"id": "dkGXJ6BlCd4", "caption": "This song is full of fast paced rhythm being played by percussion and a drumset. An e-guitar is playing a fast repeating melody with little changes along with an e-piano playing chords and melody. The e-bass is playing a groove along with the drums that sounds inviting to dance along. In the background you can hear voices cheering. This song may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/dkGXJ6BlCd4.wav"} +{"id": "dl1ljByerd8", "caption": "The low quality recording features a live performance of a traditional song and it consists of flat male vocal and reverberant fruity male vocal singing over smooth bass and strings melody. It sounds very muddy, muffled and there is a harsh microphone feedback sound. The recording is noisy itself.", "audio": "/zhanghaomin/datas/musiccap/music_data/dl1ljByerd8.wav"} +{"id": "dlhlQKTz3Vs", "caption": "This audio contains a male voice talking when someone starts playing a melody in the lower mid-range on a saxophone. This song may be playing live during a saxophone class.", "audio": "/zhanghaomin/datas/musiccap/music_data/dlhlQKTz3Vs.wav"} +{"id": "doHRurF8bf8", "caption": "A male Hindi singer sings this tragic romantic song. The song is medium tempo with a strong percussion line with tablas and other Indian percussion, strong bass line and a sitar or guitar playing accompaniment. The song is sad yet romantic. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/doHRurF8bf8.wav"} +{"id": "doX8FjlNPf8", "caption": "Someone is playing tablas and a tambourine along with string instruments playing a melody in the background. The male higher register voice is singing the same melody as the string instruments. This song may be playing in an old hindi movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/doX8FjlNPf8.wav"} +{"id": "doab948Y_X4", "caption": "Audio of an artificial solo guitar tuning two single notes, Ab and Db, one note at a time. No other instrumentation. For guitar tuning.", "audio": "/zhanghaomin/datas/musiccap/music_data/doab948Y_X4.wav"} +{"id": "dqJSTTS7HTY", "caption": "Someone is playing an acoustic guitar while a male voice in the mid range is singing accompanied by kids singing with him. This is an amateur recording. This song may be playing live in a school during music class.", "audio": "/zhanghaomin/datas/musiccap/music_data/dqJSTTS7HTY.wav"} +{"id": "dqQgzsNpwoQ", "caption": "The low quality recording features an orchestra playing classical music and it consists of a mellow brass melody and soft strings melody. There are also some floor crackling sounds, while the recording is noisy itself. It sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/dqQgzsNpwoQ.wav"} +{"id": "dql-sQqgVXI", "caption": "There is a high-pitched computer-like sound effect in the piece. It gives this cold, uneasy feeling. It could be used in a cyberpunk video game or a dystopian movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/dql-sQqgVXI.wav"} +{"id": "drJaSu3AWhQ", "caption": "The low quality recording features a funky blues acoustic guitar melody. The recording is in mono, a bit noisy, reverberant - as it was probably recorded with a phone and it sounds passionate. There are also some strings creaking sounds, while the player is playing the instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/drJaSu3AWhQ.wav"} +{"id": "drqKxGmdf8Y", "caption": "The low quality recording features a live performance of a folk song and it consists of harmonica solo melody over acoustic rhythm guitar chord progression. It sounds happy and fun. The recording is noisy and a bit reverberant as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/drqKxGmdf8Y.wav"} +{"id": "dsU3B0W3TMs", "caption": "The music features a glockenspiel playing a melody that starts off with a few notes and then develops into a fast-note arpeggio melody. Electronic sounds accompany the glockenspiel with a style that combines bass notes on beats one and three and chords on beats two and four. The whole atmosphere is playful.", "audio": "/zhanghaomin/datas/musiccap/music_data/dsU3B0W3TMs.wav"} +{"id": "dsVzafZik3c", "caption": "This is an R&B/hip-hop music piece. There is a female vocalist singing melodically. The melody is being played by the keyboard which has a crisp sound. There is a strong bass sound in the background. The rhythm is provided by a loud acoustic drum beat. The atmosphere is hip and urban. This piece could be used in the soundtrack of a drama movie that takes place in the big city.", "audio": "/zhanghaomin/datas/musiccap/music_data/dsVzafZik3c.wav"} +{"id": "dsf3agfkJDY", "caption": "This song contains digital, dubstep drums with a straight hi hat playing 8th notes. An aggressive bass sound full of modulation and other samples is playing a melody with a lot of pitch shifts and stutter effects. A voice sample is being used with a lot of reverb and delay as an atmospheric element. Some sounds are being arpeggiated playing a fast melody before leaving the scenario again. This song may be playing in an extreme sports advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/dsf3agfkJDY.wav"} +{"id": "dsibOgkezN8", "caption": "An acoustic guitar and a piano are playing the same chords as single notes with strings underlining the composition. A female voice is singing, sounding fragile and sad. This song may be playing during a sad movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/dsibOgkezN8.wav"} +{"id": "duMRKOb4E2w", "caption": "This audio contains a lot of people playing a complex snare roll groove in synchronicity along with people playing bass drums. The bass drums are overloading the speakers of the recording. This composition may be playing for an army celebration.", "audio": "/zhanghaomin/datas/musiccap/music_data/duMRKOb4E2w.wav"} +{"id": "dvDSgmqbrM0", "caption": "The low quality recording features an afrobeats song played on speaker in a medium size room, and it consists at least syncopated rimshots, shimmering open hats, synth keys melody, groovy bass, repetitive male vocal melody and harmonizing vocals layered with it. Even though the recording is noisy, thin, messy and in mono, it still sounds groovy and like something you would want to dance to.", "audio": "/zhanghaomin/datas/musiccap/music_data/dvDSgmqbrM0.wav"} +{"id": "dw4YwJppiec", "caption": "This song has a cool vibe to it. The singer has a warm and suave tone to his voice and vocal delivery. This is an alternative rock song, with a slow tempo. It gives off a cool and aloof vibe. There's reverb and echo on the singer's vocal.", "audio": "/zhanghaomin/datas/musiccap/music_data/dw4YwJppiec.wav"} +{"id": "dwAo0dKCyBI", "caption": "A male vocalist sings this rap. The tempo is medium with the keyboard harmony, digital drum rhythm and boomy bass. The song is passionate, youthful, emotional, buoyant, insightful, intense and story telling in a rhythmic patter. This song is contemporary Rap/Hip.", "audio": "/zhanghaomin/datas/musiccap/music_data/dwAo0dKCyBI.wav"} +{"id": "dwFtlQLdbq0", "caption": "This is a chant to a deity that is venerated in Yoruba, Candomble and Santeria religions. There are many people chanting in a devotional manner to this deity. There are a lot of percussive elements playing intertwined syncopations. The conflict of all the sounds and voices make the piece sound like a scene from a pandemonium. This piece can be used in a nightmare sequence at a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/dwFtlQLdbq0.wav"} +{"id": "dwSj0Rr3vFc", "caption": "A string section is playing a melody in the mid to high register. A bansuri flute is playing the same melody along. Digital and acoustic drum/percussion elements are playing a beat that does not occupy a lot of space. A male voice is singing at a higher pitch. This song may be playing in a hindi-movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/dwSj0Rr3vFc.wav"} +{"id": "dy_yFZ6dL34", "caption": "This is a meditation piece. There are waves in the background sounding similar to sine waves. There is an evolving synth signifying a passage. There are various sound effects, especially in high pitch. There is a hypnotizing aura. This piece could be used in the background of a meditation video.", "audio": "/zhanghaomin/datas/musiccap/music_data/dy_yFZ6dL34.wav"} +{"id": "dzPPmuFUicc", "caption": "The low quality recording features a country song that consists of a passionate male vocal singing over arpeggiated acoustic guitar melody, acoustic rhythm guitar chords, mandoline guitar melody and groovy bass. It sounds passionate, joyful and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/dzPPmuFUicc.wav"} +{"id": "dzW5M4sCphI", "caption": "A live recording of a brass ensemble in a chamber style arrangement. Natural reverb from a recital hall is present. The music features counterpoint amongst the different instruments, and the mood is stately and noble.", "audio": "/zhanghaomin/datas/musiccap/music_data/dzW5M4sCphI.wav"} +{"id": "dztizAgcQ08", "caption": "This is a live performance of an art song piece. There is a male vocalist singing as if he is performing a role at a theater play. The grand piano is playing a melodic accompaniment piece in the background to support the vocals. The words are derived from English literature.", "audio": "/zhanghaomin/datas/musiccap/music_data/dztizAgcQ08.wav"} +{"id": "e1KHGfMekek", "caption": "Punk rock with a country twang, featuring an acoustic guitar strumming, an overdriven electric guitar playing lead, multiple male vocalists, male background vocals and a simple chord progression. The drums play an uptempo country beat, or \"train beat\" more specifically. The kind of band you might hear at a pub in a semi-rural suburb.", "audio": "/zhanghaomin/datas/musiccap/music_data/e1KHGfMekek.wav"} +{"id": "e1PG31QlQmc", "caption": "The low quality recording features a live performance of a folk song that consists of an echoing passionate male vocal singing over sustained strings melody, acoustic guitar melody and some crowd cheering and whistling sounds in the background. It sounds joyful, passionate and emotional overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/e1PG31QlQmc.wav"} +{"id": "e1sWvJsGOAc", "caption": "This is an exciting, epic cinematic orchestral piece. This kind of music would be used for a scene involving a chase or something thrilling. There are tubas, trombones, trumpets and french horns playing the same exciting motif.", "audio": "/zhanghaomin/datas/musiccap/music_data/e1sWvJsGOAc.wav"} +{"id": "e2tZmQI8ICw", "caption": "This song is a romantic duet.the tempo is medium with a soft keyboard harmony, steady drumming, violin harmony, chimes, Cajun beat, bongos rhythm, steady bass line and acoustic guitar .the song is a proposal song.it is romantic, emotional, passionate, soft, ambient, mellifluous and dulcet. This song is a Soft Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/e2tZmQI8ICw.wav"} +{"id": "e4EwrAN6lvU", "caption": "A male singer sings this passionate melody accompanied by crowds who are singing along and cheering. The song is in medium tempo with a strong drumming rhythm, cymbals crashing, steady bass line and keyboard accompaniment. The song has extremely bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/e4EwrAN6lvU.wav"} +{"id": "e4R2O7XpIXU", "caption": "The excerpt starts off with a brief silence after which a sound effect and two metallic sounds can be heard. After this section comes another brief silence and then a kind of light club/electronic music starts to play for a few seconds. Adding all of this up it sounds as if this isn't an actual song but rather background music and sound effects for a presentation of some sorts.", "audio": "/zhanghaomin/datas/musiccap/music_data/e4R2O7XpIXU.wav"} +{"id": "e4abjaPD9R0", "caption": "The Soft Metal song features a flat male vocal, alongside harmonizing male background vocals, singing over energetic cymbals, electric guitar melodies, distorted bass, punchy kick and snare hits and wide manic toms. It sounds aggressive and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/e4abjaPD9R0.wav"} +{"id": "e57SBRbMXbI", "caption": "This piece of audio contains a modern pop song with drums, effects panned to left and right, a female voice singing with delay before changing into a totally different song that sounds more like a fast paced country song with a synthesizer- melody; acoustic drums and a banjo playing a fast melody along. This recording is also full of voice samples, a tiger or lion roaring, a telephone ringing. According to all these sounds and fast paced changes, it can be assumed that this recording is best played at a comedic television show for kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/e57SBRbMXbI.wav"} +{"id": "e5SK6olIYcY", "caption": "This is a live recording of a traditional church choir singing Christmas carols. The music, in some ways, feels ethereal and like what is seen in movies about what heaven would be like.", "audio": "/zhanghaomin/datas/musiccap/music_data/e5SK6olIYcY.wav"} +{"id": "e6lTl9JIW5Y", "caption": "The low quality recording features a jazz performance that consists of saxophone solo melody played over shimmering cymbals, followed by trombone melody and walking double bass. It sounds warm, but dark, due to the poor quality microphone it was recorded with.", "audio": "/zhanghaomin/datas/musiccap/music_data/e6lTl9JIW5Y.wav"} +{"id": "e7WPFeDPFB4", "caption": "A male vocalist sings this alap or raga. The tempo is medium with a rhythmic mridangam accompaniment. The song is vocalised with the vocalist singing a melody using notes not lyrics. It is engaging, energetic and controlled. This song is a Carnatic Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/e7WPFeDPFB4.wav"} +{"id": "e8wnUU5pIWE", "caption": "A female singer sings this emotional melody. The song is medium tempo with a guitar accompaniment and a subtle bass line with no percussion instruments. The song is emotional and romantic. The song is a wedding song.", "audio": "/zhanghaomin/datas/musiccap/music_data/e8wnUU5pIWE.wav"} +{"id": "e8xkukid_2o", "caption": "solo overdriven electric guitar playing arpeggios slowly through a tremolo effect. roots rock feel.", "audio": "/zhanghaomin/datas/musiccap/music_data/e8xkukid_2o.wav"} +{"id": "e9ptOl22Duc", "caption": "The low quality recording features a clarinet solo melody and bass clarinet melody playing. It sounds passionate and joyful, while the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/e9ptOl22Duc.wav"} +{"id": "eAFKjP7o1as", "caption": "This is the live performance of a Baroque music performance. There is a male vocalist singing at a very high pitch. The melody is being played by a harpsichord. There is a medieval sound to this piece. It could be used in the soundtrack of historical dramas that take place in Medieval Europe.", "audio": "/zhanghaomin/datas/musiccap/music_data/eAFKjP7o1as.wav"} +{"id": "eBF0zRHCbZE", "caption": "Acoustic guitars are strumming chords while a male voice is singing with his full voice but not loud. A bass is supported along with some very soft percussion that are barely noticeable. This song may be playing with friends at a bonfire.", "audio": "/zhanghaomin/datas/musiccap/music_data/eBF0zRHCbZE.wav"} +{"id": "eBlyC9bJacs", "caption": "A digital melody is playing a lullaby. This is an amateur recording with poor audio-quality. This song may be playing to bring children to sleep.", "audio": "/zhanghaomin/datas/musiccap/music_data/eBlyC9bJacs.wav"} +{"id": "eCyMTN6Hg5k", "caption": "This music is an intense electronic instrumental . The tempo is slow with electric guitar,acoustic guitar and synthesiser arrangements. The music is grim, intense, boomy, serious, fervent and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/eCyMTN6Hg5k.wav"} +{"id": "eHeUipPZHIc", "caption": "The song is an instrumental. The song is medium tempo and has a delightful flute solo with keyboard accompaniment groovy bass line and a groovy drumming rhythm. The song has a poor recording quality. The song's middle eastern folk music vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/eHeUipPZHIc.wav"} +{"id": "eI4PbSh6g_Y", "caption": "This is a low quality recording. This song features steel pans playing together. There are no voices in this song. The steel pans are accompanied by cymbals and other percussion playing a Latino beat. This music has a Caribbean feel and is upbeat. The mood of this song is happy. This song can be played at a dance party with a Caribbean theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/eI4PbSh6g_Y.wav"} +{"id": "eISYX9koocM", "caption": "The low quality recording features a live performance of a traditional pop song and it consists of an addictive female vocal singing over punchy kick and snare hits, groovy bass, electric guitar melody, strings melody and wooden percussion. There is a short snare roll, right before the bass drops. It sounds messy, a bit harsh, distorted, but also passionate, addictive and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/eISYX9koocM.wav"} +{"id": "eJFZuX0WHgk", "caption": "This is a pop rock music piece being performed in the studio. There is a male vocalist singing melodically in the lead. The electric guitar is playing a simple tune with the bass guitar in the background. The acoustic drums are playing an upbeat rhythm with off-beat hi-hat strokes. The atmosphere is energetic. This piece could be used as the opening theme of a Korean teenage drama TV series.", "audio": "/zhanghaomin/datas/musiccap/music_data/eJFZuX0WHgk.wav"} +{"id": "eM0PkfqGmIE", "caption": "The song is an instrumental. The song is medium fast tempo with a bass guitar soloist playing a cool accompaniment groove with no other instrumentation. The song is passionate and energetic. The song is a bass guitar demo or a home music video.", "audio": "/zhanghaomin/datas/musiccap/music_data/eM0PkfqGmIE.wav"} +{"id": "eOmQbJljnqE", "caption": "The low quality song features a country song that consists of an acoustic rhythm guitar chord progression over which a mellow male vocal is singing. The recording got noisy at the end of the loop, which sounded like a microphone was turned on. It sounds vintage, warm, happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/eOmQbJljnqE.wav"} +{"id": "eQHQWb6FCio", "caption": "A child sings this playful melody accompanied by an adult in vocal harmony. The song is medium tempo with a steady drumming rhythm, tambourine percussion , keyboard harmony, horns playing and a playful keyboard bass line. The song is cheerful and playful. The song is an anime tv show tune or a children\u2019s song.", "audio": "/zhanghaomin/datas/musiccap/music_data/eQHQWb6FCio.wav"} +{"id": "eQTK2fo3RoE", "caption": "The instrumental music features a piano playing a romantic song. A group of strings accompany the pianist with warm harmonies. The overall atmosphere is romantic and touching.", "audio": "/zhanghaomin/datas/musiccap/music_data/eQTK2fo3RoE.wav"} +{"id": "eRiGPyewJpI", "caption": "The low quality recording features a muffled crowd talking in the background while there is a horn melody, alongside horn siren sound playing. It sounds like a traditional thing to do.", "audio": "/zhanghaomin/datas/musiccap/music_data/eRiGPyewJpI.wav"} +{"id": "eSIxvnEQ6R0", "caption": "The low quality recording features a traditional song that consists of mellow synth pad chords, wide plucked echoing strings, wobbly percussion, wooden percussion and shimmering tambourine. It sounds happy and joyful - like something you would hear at some traditional festivals.", "audio": "/zhanghaomin/datas/musiccap/music_data/eSIxvnEQ6R0.wav"} +{"id": "eSesh6vnek8", "caption": "The Pop song features a passionate female vocal singing over synth keys melody, sustained synth strings chords, groovy bass guitar, shimmering shakers and tinny percussive elements. The second section has only vocals, synth keys, shimmering shakers and some tinny percussion, as it is a way calmer section. It sounds uplifting, emotional and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/eSesh6vnek8.wav"} +{"id": "eSsadT6mh7g", "caption": "The low quality recording features some camera shuttering sound effects and a jazz song playing in the background. The song consists of a cool saxophone solo melody over groovy bass, easygoing electric guitar chords in the left channel of the stereo image and energetic drums. It sounds easygoing and energetic at the same time.", "audio": "/zhanghaomin/datas/musiccap/music_data/eSsadT6mh7g.wav"} +{"id": "eStzDzEopDI", "caption": "The low quality recording features a traditional song sung by harmonizing female vocals over breathy flute melody and wooden percussion. It sounds harsh, muddy, passionate and soulful, as audio is distorted due to poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/eStzDzEopDI.wav"} +{"id": "eUZ-v8GEcNk", "caption": "The low quality recording features a metal song that consists of screaming male vocal singing over widely spread electric guitar riffs, distorted bass guitar, energetic cymbals and short snare rolls. It sounds loud, aggressive, energetic and manic - as every metal song should sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/eUZ-v8GEcNk.wav"} +{"id": "eVjcfdxSFKQ", "caption": "This music is an aggressive instrumental. The tempo is fast with hard hitting, vigorous drumming, keyboard harmony and synthesiser arrangements with siren sounds and a menacing, deep growl. The music is angry, aggressive, passionate, extreme,scary, sinister, suspenseful, gothic , hostile, belligerent, violent and combative. This music is Death metal/Death Core.", "audio": "/zhanghaomin/datas/musiccap/music_data/eVjcfdxSFKQ.wav"} +{"id": "eW8se7t0s-U", "caption": "The low quality recording features a classical song that consists of arpeggiated, soft piano melody, wide sustained string melody and a tom hit at the very beginning of the recording. The song is slowly fading in, by which we can conclude that it is an intro section of the song. It sounds cinematic, emotional, soft, mellow and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/eW8se7t0s-U.wav"} +{"id": "eWGGj4duzIo", "caption": "This is an acoustic live performance of an alternative music piece. There is a female vocalist singing melodically at a soprano range. In the melodic background, there is an acoustic guitar playing a simple tune. The piece has an emotion-filled atmosphere. It could be used in the soundtrack of a drama movie or a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/eWGGj4duzIo.wav"} +{"id": "eWNERam16Hg", "caption": "This is an Indian film music piece. It is an instrumental piece. There is a sitar playing the melody. The tabla percussion is keeping the rhythm in the background. The atmosphere is lively. This piece is a good folk dance accompaniment piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/eWNERam16Hg.wav"} +{"id": "eWSA0xubW7I", "caption": "This is a Punjabi film music piece. At first, the melody is being played by the accordion. Then, it is being played by the flute. In the background, a bass guitar is playing. The rhythm is provided by the percussion. The atmosphere is vibrant. This piece could be used as an accompaniment piece for a folk dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/eWSA0xubW7I.wav"} +{"id": "eWqD_VOympU", "caption": "This suspenseful song features synth sounds. At the beginning, a synth plays a constant sound in the background. Another synth plays a swell with a vibrato effect. After it pauses, a shaker is played. The mood of this song is eerie and suspenseful. This song can be played in a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/eWqD_VOympU.wav"} +{"id": "eWwWwoQLtVg", "caption": "This is a lullaby piece. There is a female voice singing softly with accentuations at specific parts. An acoustic guitar provides a melodic background. The song is played on a major scale, giving it an added soothing effect. This piece could be used in a playlist meant for babies to listen to before they go to sleep.", "audio": "/zhanghaomin/datas/musiccap/music_data/eWwWwoQLtVg.wav"} +{"id": "eX1Hynef5Rc", "caption": "The low quality recording features a hip hop song that contains a phone dialing sound effects, alongside filtered female vocal talking as the user is busy on the phone. In the second half of the loop, there are punchy kicks and snare hits playing. It sounds groovy and energetic overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/eX1Hynef5Rc.wav"} +{"id": "eXWBC3XfiXY", "caption": "The low quality recording features a soft rock song that consists of harmonizing mixed vocals singing passionately over mellow piano chords, soft synth pad chords, boomy kick and reverberant claps. It sounds boomy, muddy and dull, as the low frequencies are clashing, bu it is also emotional regardless.", "audio": "/zhanghaomin/datas/musiccap/music_data/eXWBC3XfiXY.wav"} +{"id": "eXrJL1VUQNE", "caption": "The song is an instrumental. The tempo is medium with a percussive Arabic percussion groove, tambourine percussions, percussive bass line and a ethnic wind instrument playing an enthusiastic solo. The song has folk music influences and reminds us of a desert journey. The song audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/eXrJL1VUQNE.wav"} +{"id": "eYngZ5It0b8", "caption": "The low quality recording features a harmonizing staccato vocals melody sung over groovy piano melody, wide shimmering shakers, punchy kick, thin snare hits and some nice sound effects in the background. It sounds fun and happy - almost like a jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/eYngZ5It0b8.wav"} +{"id": "eZ8yopmYtPM", "caption": "This is a jingle piece in the background of a toy advertisement. The toy is a cash register toy, so there are a lot of beeping sounds. There is a synth playing the main tune that is constantly rising up to a higher note while a piano is playing staccato chords alongside it. A cymbal-heavy electronic drum beat can be heard. The atmosphere is uneasy. Samples could be lifted from this track to be used in beat-making or in the soundtrack of a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/eZ8yopmYtPM.wav"} +{"id": "eZC1AP_JjXM", "caption": "This is a wedding march that belongs to Scottish folk music. It is an instrumental piece. The tune is being played by the French bagpipes at a medium-to-high pitch. The atmosphere is cheerful. This piece could be playing at a Scottish wedding. It could also be included in the soundtrack of a historical drama movie during wedding scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/eZC1AP_JjXM.wav"} +{"id": "eZE0RmJESFU", "caption": "A Latin club track with a thumping bass and a funky feel. The kick snare pattern is simple and the hi-hat is busy playing steady 16th notes. Distorted electric guitar plays a lead melody along with the autotuned harmonized male background vocals. The lead vocals feature a male and female duo singing in harmony, while synth strings fill in the beat with short chords.", "audio": "/zhanghaomin/datas/musiccap/music_data/eZE0RmJESFU.wav"} +{"id": "eZNnuRvrZDU", "caption": "The Classical song features wide sustained strings and subtle mellow piano chords. It sounds sad and emotional - like something you would hear in the video games, as a background music for a sad scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/eZNnuRvrZDU.wav"} +{"id": "eZrrzGgTpfk", "caption": "This audio seems to contain two songs. In the beginning someone is strumming chords on acoustic drums while a male voice is singing in a high pitch. Then the song switches to a robotic voice sample singing. Then a digital drum comes in with a fat kick and bass sound creating the base together with the vocal sample. In the background you can hear scratching sounds. This song may be playing while working out.", "audio": "/zhanghaomin/datas/musiccap/music_data/eZrrzGgTpfk.wav"} +{"id": "e_W17jp40G4", "caption": "The low quality recording features a passionate male vocal singing over a wooden percussive element and sustained strings melody. It sounds emotional, passionate - like a traditional middle eastern song.", "audio": "/zhanghaomin/datas/musiccap/music_data/e_W17jp40G4.wav"} +{"id": "eayGg2OlHOw", "caption": "The low quality recording features a live performance of a mellow classical piano melody and sustained passionate violin melody playing together. It is very noisy and there are some crackling noises, widely spread in the background. Sounds passionate, emotional and it seems like it was recorded with one stereo pair of microphones.", "audio": "/zhanghaomin/datas/musiccap/music_data/eayGg2OlHOw.wav"} +{"id": "ecS6SJGkhIw", "caption": "The low quality recording features a flat girl vocal talking over a folk song that consists of an arpeggiated guitar melody played over groovy bass, shimmering shakers and \"4 on the floor\" kick pattern. There are some birds chirping sounds in the background. It sounds energetic, fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ecS6SJGkhIw.wav"} +{"id": "echeYDYFhlY", "caption": "This is a folk rock/alternative music piece. There is a male vocalist singing melodically in the lead. The main tune is played by the acoustic guitar with a rather quiet bass line in the background. There is a timid acoustic drum beat in the rhythmic background. The atmosphere is sentimental and melancholic. This piece could be used in the soundtrack of a drama TV series, especially during a scene where the episode would end with the characters daydreaming.", "audio": "/zhanghaomin/datas/musiccap/music_data/echeYDYFhlY.wav"} +{"id": "ed-1zAOr9PQ", "caption": "This clip is an amateur recording. There is an upbeat song playing softly with the male vocalist singing a spirited song to the accompaniment of what sounds like a keyboard and guitar. The song is incoherent so it is difficult to hear the finer elements of the song. There are other sounds that superimpose the song, like a white noise at the beginning followed by the sounds of someone sniffing, tapping, a door closing, people talking, footsteps and thudding. This is an amateur home video.", "audio": "/zhanghaomin/datas/musiccap/music_data/ed-1zAOr9PQ.wav"} +{"id": "edKvAj0fYxQ", "caption": "The Alternative/Indie song cover features an acoustic ensemble that includes acoustic guitar chord progression, still guitar melody and tinny double bass playing it. It sounds narrow due to the fact that it is a mono recording. Everything, including the double bass, sounds kind of tinny and reverberant, because it was most likely recorded with one mono, room microphone. The sound could definitely be better, but it does not fall into the category of a low quality recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/edKvAj0fYxQ.wav"} +{"id": "eezaOfrLOkM", "caption": "The low quality recording features an orchestra live performance and it contains a mellow brass section melody, sustained strings melody, soft piano chords and smooth double bass. It sounds easygoing and happy, like something you would listen to while trying to relax.", "audio": "/zhanghaomin/datas/musiccap/music_data/eezaOfrLOkM.wav"} +{"id": "efTVnvwI2PQ", "caption": "This is a live recording to which music was later added. The main audio in the clip includes a squeaky toy being repeatedly pressed. The song that was later added is a slow ballad that includes piano and violin.", "audio": "/zhanghaomin/datas/musiccap/music_data/efTVnvwI2PQ.wav"} +{"id": "ehJKd9HLA04", "caption": "This music is a lively instrumental. The tempo is fast with a spirited violin which is most likely a pochette playing a spirited harmony. The music is upbeat, catchy, happy,cheerful, engaging and energetic. This instrumental is a folk song instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/ehJKd9HLA04.wav"} +{"id": "eiFyXXqd9Rk", "caption": "This is a live acoustic performance of a rock music song. There is a male vocalist singing at a medium-to-high pitch in a melodic manner while two acoustic guitars are carrying the background with a simple tune composed of only four chords. The music might be played at a bar in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/eiFyXXqd9Rk.wav"} +{"id": "eiUjc4UPnSs", "caption": "The low quality recording features a pop song that consists of mellow female vocals, followed by female background vocals, singing over punchy kicks, claps, shimmering open hats, stuttering hi hats, buzzy synth bass and wide synth pad chords. It sounds aggressive, bright, punchy, energetic and kind of manic due to those hi hats.", "audio": "/zhanghaomin/datas/musiccap/music_data/eiUjc4UPnSs.wav"} +{"id": "eiyyoUt64Zc", "caption": "a latin jazz ensemble performing in a recital hall. A trumpet solo is accompanied by acoustic bass, syncopated drums and piano. The rhythm is upbeat and danceable. You can hear the reverb of the recital hall as well as audience sounds, someone sneezing.", "audio": "/zhanghaomin/datas/musiccap/music_data/eiyyoUt64Zc.wav"} +{"id": "em7akjDUsWk", "caption": "Someone is strumming an acoustic guitar while a male voice is singing along. This may be playing at a bonfire.", "audio": "/zhanghaomin/datas/musiccap/music_data/em7akjDUsWk.wav"} +{"id": "emDU4QvdwVk", "caption": "The song sounds orchestrated. There is a string section playing swells and rising tremolos along to an acoustic piano playing minor chords. A cello is playing long low notes on top of that a saxophone is playing two notes to end the phrase. A deep and far percussive hit comes in every fourth count. The female singer's voice sounds sensitive and melancholic. There are female backing voices singing along. The whole composition is full of big reverb. This song may be playing at the end of a sad movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/emDU4QvdwVk.wav"} +{"id": "emP2Sg9QEg4", "caption": "This instrumental clip features a theremin being played. This is backed by acoustic plucking chords. There is no percussion in this song. There are no voices in this song. This is a slow tempo song and the melody is haunting. This song can be used in a dream sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/emP2Sg9QEg4.wav"} +{"id": "en0haa37gnk", "caption": "This music is instrumental. The tempo is slow with a droning vibration of a metal bowl called the Tibetan bowl or singing bowl. The music is a single note drone with vibrations and resonance. It is calming, meditative, stress relieving, meditative and soothing.", "audio": "/zhanghaomin/datas/musiccap/music_data/en0haa37gnk.wav"} +{"id": "en56uOGTwzg", "caption": "This is a beatbox performance played on a flute. There is a flushing sound effect in the beginning of the recording and then the performance begins. There is an eccentric feel to the piece. The sound effect in the beginning could be used in a soundboard while the flute can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/en56uOGTwzg.wav"} +{"id": "entThp930cw", "caption": "This house music features percussion being played to a Latin beat. There are no other instruments in this song. There are no voices in this song. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/entThp930cw.wav"} +{"id": "erHadqauC8A", "caption": "This song is a simple instrumental. The tempo is medium with a lively tempo and melodic violin accompaniment. The tune is simple,refreshing, emphatic and mellifluous.", "audio": "/zhanghaomin/datas/musiccap/music_data/erHadqauC8A.wav"} +{"id": "esIzFH7vYLY", "caption": "A male vocalist sings this spirited song. The tempo is fast with a bright keyboard harmony, boomy bass drops, infectious drumming and atmospheric synthesiser and a vocal riff. The electronic arrangements and synthesised sounds give it a psychedelic, trippy, hypnotic vibe. It is perky, buoyant, thumping, youthful, vivacious with a dance groove. This song is an EDM/Synth Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/esIzFH7vYLY.wav"} +{"id": "etmmUjsRNRs", "caption": "This folk song features a male voice singing the main melody. This is accompanied by an acoustic guitar. A shaker plays in place of the percussion. Violins play a melody in the background. The mood of this song is romantic. This song can be played in a flashback scene of a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/etmmUjsRNRs.wav"} +{"id": "euAQCWBX6ns", "caption": "A male singer sings this cheerful melody with backup singers in vocal harmony. The song is medium tempo with a reggae style drum and guitar accompaniment, guitar lead and a groovy bass line. The song is romantic and cheerful . The song is a Latin pop dance song. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/euAQCWBX6ns.wav"} +{"id": "evG8CQRCdV8", "caption": "The music features a female voice singing a repeating melody. The drums play a light repeating rhythm. A synth bass is playing long notes and sliding in-between them. An electronic sound imitating a sort of electronic organ is playing two chords per beat. The music invites the listener to dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/evG8CQRCdV8.wav"} +{"id": "ev_YCCuGVSs", "caption": "Medium tempo rock drum beat with a half time feel, using only two chords played by acoustic guitar arpeggios, piano chords and a male singer. The mood is sentimental.", "audio": "/zhanghaomin/datas/musiccap/music_data/ev_YCCuGVSs.wav"} +{"id": "evscfdO-oSY", "caption": "A male vocalist sings this simple melody. The tempo is medium with a pleasant keyboard harmony, slick drumming, steady bass lines and an melodic electric guitar harmony. The song is a simple, insistent rhythm,recurring beat, youthful , emotional, sentimental and passionate classic Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/evscfdO-oSY.wav"} +{"id": "evy2azZk3kE", "caption": "This audio contains a harp playing a fast melody along with a cuatro strumming chords. An e-bass is playing an almost walking bassline along with a high pitch stick hit playing a rhythm. A male voice is singing loud and in a higher pitch than other male voices are responding singing in harmonie. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/evy2azZk3kE.wav"} +{"id": "ew-7SwLcHBg", "caption": "The song is an instrumental piece. The song is fast tempo with a glass harpist playing an extremely intricate solo with no other instrumentation . The song is magical and mysterious. The song is a live performance with ambient sounds of people talking in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/ew-7SwLcHBg.wav"} +{"id": "ewI4q7_4TBQ", "caption": "The song is a country rock song with a charged up, potent sound. The guitar is grungry, and gives punchy and gritty energy. The singer has a smooth voice and sings with charisma and suave charm.", "audio": "/zhanghaomin/datas/musiccap/music_data/ewI4q7_4TBQ.wav"} +{"id": "exD5okdopWc", "caption": "The low quality recording features a folk song that consists of passionate male vocal singing over shimmering shakers, smooth bass, sustained strings melody and groovy piano melody. It sounds emotional, soulful and passionate - like something you would hear in movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/exD5okdopWc.wav"} +{"id": "eyFBIA_HOmE", "caption": "The low quality recording features a steel guitar solo melody playing over smooth instrumental on playback that consists of snappy rimshots, wide acoustic rhythm guitar, groovy piano chords, soft bass guitar, soft kick hits and shimmering hi hats. It sounds easygoing and chill - something you would hear in a restaurant or a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/eyFBIA_HOmE.wav"} +{"id": "eyY6f4iQDH4", "caption": "This song features an electric guitar. A male voice is narrating about the major scale. The guitar plays a descending scale pattern from the high note in the scale to the low note. There are no other instruments in this song. There is no vocal melody in this song. This can be played for an instructional video on playing the guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/eyY6f4iQDH4.wav"} +{"id": "ezayBI_xOVk", "caption": "The song is an instrumental. A bass guitarist is trying to tune his guitar with a tuning module creating bass tones that are played haphazardly. The song audio quality is very poor. .", "audio": "/zhanghaomin/datas/musiccap/music_data/ezayBI_xOVk.wav"} +{"id": "f1NV9qTjOv8", "caption": "Someone is playing a fast melody on bagpipes in the lower higher register accompanied by a base drone sound. This song may be playing during a traditional ceremony or event.", "audio": "/zhanghaomin/datas/musiccap/music_data/f1NV9qTjOv8.wav"} +{"id": "f1UMPPWbCrU", "caption": "This is the recording of a radio play. There is a male voice narrating a story. As a transition piece, the bassoon plays a tune implying mystery and the brass section starts playing a little after. There is a theatrical aura to this piece. It could be used in the soundtrack of a movie as background music during scene transitions.", "audio": "/zhanghaomin/datas/musiccap/music_data/f1UMPPWbCrU.wav"} +{"id": "f1_YKSYgtbI", "caption": "This is a repeated chord progression that's arpeggiated on an electric guitar. The guitar signal has a chorus pedal effect applied to it, and so it doesn't sound like a clean tone. The arpeggio itself is mellow yet uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/f1_YKSYgtbI.wav"} +{"id": "f3l6KnC8930", "caption": "A female voice is singing, sounding sensual while an acoustic piano is playing a ballad with a change in keys and strings being played with long strokes. The song sounds sensual and dramatic. You can hear some clicking sounds in the recording. This song may be played at a karaoke bar. This song seems to be an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/f3l6KnC8930.wav"} +{"id": "f4jW2H6V7gk", "caption": "A male singer sings this exciting melody with female backup singers in vocal harmony. The song is medium fast tempo with a strong bass line, steady drumming rhythm, keyboard accompaniment and a car horn playing percussively. The song has pretty bad audio quality. The song is a retro hip hop dance tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/f4jW2H6V7gk.wav"} +{"id": "f5eMUCSZCjc", "caption": "The low quality recording features a metal song that consists of wide aggressive, distorted electric guitars, distorted bass, clean electric guitar solo melody, energetic crash cymbals, punchy snare, double pedal kick and throaty male vocal talking and screaming over it. There are some energetic snare rolls that serve as a breakbeat and transition to the next section. It sounds energetic, aggressive and manic. Putting the vocal so low in the mix, makes it a low quality sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/f5eMUCSZCjc.wav"} +{"id": "f6H0TMWDaZg", "caption": "Someone is scratching turntables to a backing track coming out of a speaker. This is an amateur recording. This song may be playing at home practicing alone.", "audio": "/zhanghaomin/datas/musiccap/music_data/f6H0TMWDaZg.wav"} +{"id": "f6wrXzvByrg", "caption": "This folk song is a duet and features a male and a female voice singing in harmony. This is accompanied by an acoustic guitar strumming chords. A banjo player fills in between lines. There is no percussion in this song. The mood of this song is happy and upbeat. This song can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/f6wrXzvByrg.wav"} +{"id": "f7OQTtTdgrA", "caption": "This song features the sound of a theremin. It starts off with the sound of a heartbeat played on the theremin itself. Then four ascending notes are played. There is a kind of continuous pad sound playing in the background. There are no other instruments in this song. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/f7OQTtTdgrA.wav"} +{"id": "f8QGA4vN6HY", "caption": "The song is an instrumental. The tempo is fast with a groovy jazz drumming rhythm with good brush works, strong bass line, piano accompaniment and various percussion hits. The song is groovy and energetic. The song is jazz fusion.", "audio": "/zhanghaomin/datas/musiccap/music_data/f8QGA4vN6HY.wav"} +{"id": "f8fUFmjqXZo", "caption": "The low quality recording features a creepy music box melody followed by high pitched buzz, wide distorted low tone sounds and some growling noises. It sounds dark, suspenseful and intense - it almost feels like listening to a horror film.", "audio": "/zhanghaomin/datas/musiccap/music_data/f8fUFmjqXZo.wav"} +{"id": "f8nysknTFUo", "caption": "A female vocalist sings this spirited rap. The tempo is medium with punchy drumming and synthesiser arrangements. The song is youthful,energetic,spirited with a catchy recurring vocal riff. The song is an Electro Rap/Hip-Hop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/f8nysknTFUo.wav"} +{"id": "fAHYe-qmFnU", "caption": "This clip starts with the sound of scribbling on a piece of paper. This is followed by an epic orchestral song. This has a string section playing notes on a high register. The bass plays the root notes of the chords. The bass drum plays strokes. Male voices sing in baritone like a choir.", "audio": "/zhanghaomin/datas/musiccap/music_data/fAHYe-qmFnU.wav"} +{"id": "fAfk9yrGhWw", "caption": "This instrumental song features a guitar playing a lick. This is a joyful melody played on the guitar with a delay effect. There is no percussion and no other instruments in this song. There are no voices in this song. At the end, the noise threshold of the guitar is crossed and the hum can be heard. This song is relaxing and can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/fAfk9yrGhWw.wav"} +{"id": "fBEGBuO3RXg", "caption": "This song is an orchestral piece. The tempo is slow with the vocalist singing in soprano,alto, mezzo, treble and bass harmony. The song is intense, grim, sinister, indicative of danger, eerie, enigmatic, out worldly and mesmerising. There are incoherent vocal riffs and sounds towards the end of this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/fBEGBuO3RXg.wav"} +{"id": "fD1xB9lDbPQ", "caption": "This song contains a male acapella group singing and beatboxing creating harmonies, bass and singers in the higher register. This song may be playing live for a talent show.", "audio": "/zhanghaomin/datas/musiccap/music_data/fD1xB9lDbPQ.wav"} +{"id": "fDMbNCdGXBc", "caption": "The low quality recording features a country song being played on an acoustic rhythm guitar and raw male vocal singing over it. It sounds passionate and emotional, even though the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/fDMbNCdGXBc.wav"} +{"id": "fE7tbn6Fnw4", "caption": "The low quality recording features a classical song that consists of a harpsichord melody played over strings and brass melody. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/fE7tbn6Fnw4.wav"} +{"id": "fEFeRM5bT8o", "caption": "The low quality recording features a Christmas song that consists of harmonizing vocals singing over synth bell melody, flute lick, groovy bass, acoustic rhythm guitar, shimmering bells, shimmering shakers and piano melody. It sounds happy, fun, euphoric, nostalgic and exciting - just like every Christmas song should sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/fEFeRM5bT8o.wav"} +{"id": "fEHsR679g1M", "caption": "This music is a high energy Rock and Roll. The tempo is fast with a vivacious electric guitar melody, punchy drumming, animated trumpets, funky bass line, keyboard and acoustic guitar accompaniment . The music is high energy, vivacious, bright, groovy,enthusiastic and animated Rock and Roll instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/fEHsR679g1M.wav"} +{"id": "fESsP6ZnVKA", "caption": "The excerpt features a synth sound playing a few notes and then a short melody. Throughout the passage and from time to time the synth sound slides from one note to another. This doesn't sound like music but instead it does sound like someone's playing around with a synth sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/fESsP6ZnVKA.wav"} +{"id": "fEfe8jznp5Q", "caption": "This recording is full of digital game noises along with short instrumentation sounds. Then a country song starts to play a composition in a very bad quality along with duck sounds. Nature sounds like water and birds chirping can be noticed. This recording is of poor audio quality and may be playing for a simple videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/fEfe8jznp5Q.wav"} +{"id": "fFYMsrMGQtU", "caption": "The clip features calm instrumentation, led by a theremin. The percussion is simple and derivative of hip hop. The tune is a sort of calm, soothing kind.", "audio": "/zhanghaomin/datas/musiccap/music_data/fFYMsrMGQtU.wav"} +{"id": "fH9CY48sfJY", "caption": "The low quality recording features a compilation of a few different recordings that mostly consist of female vocals talking with each other and a loud crowd talking in the background. However, in the first section, there are also some claps and female vocals mumbling a song. The arrangement of the recordings is weird, but in context it probably makes sense.", "audio": "/zhanghaomin/datas/musiccap/music_data/fH9CY48sfJY.wav"} +{"id": "fHNAxa0QaOM", "caption": "This instrumental clip features a bass guitar playing a repetitive lick. This is accompanied by a shaker and a tambourine. After one bar, the tambourine stops playing. There are no voices in this song. There is no percussion in this song. The mood of this song is trippy. It can be used in a bank robbery movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/fHNAxa0QaOM.wav"} +{"id": "fJ6ZeWYfLjA", "caption": "This comedy song features a male voice singing the main melody followed by another male continuing the melody. This is accompanied by a piano playing staccato chords in a melody similar to the voices. A choir sings vocables in harmony in the background. There are no other instruments in this song. This song can be played in a comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/fJ6ZeWYfLjA.wav"} +{"id": "fKni4PUSxu4", "caption": "This song contains an acoustic piano playing a melody in the mid- to high range along with a simple bassline playing long notes. A saxophone is playing a loud melody in a higher key. In the background you can hear strings and some fast percussive rolls. THe audio contains white noise. This song may be playing on a romantic date.", "audio": "/zhanghaomin/datas/musiccap/music_data/fKni4PUSxu4.wav"} +{"id": "fM8elJ4jkic", "caption": "The low quality recording features a live performance that consists of bagpipes melodies. It sounds soulful, passionate, cultural and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/fM8elJ4jkic.wav"} +{"id": "fPIG7nrpgec", "caption": "The low quality recording features shimmering bells that slowly fade out, leading into a funky electric guitar melody. It sounds cool and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/fPIG7nrpgec.wav"} +{"id": "fPYeqTFc3IQ", "caption": "A female vocalist sings this spirited latin song.the tempo is medium fast with an animated piano accompaniment, rhythmic congas and bongos, funky bass line and bright trumpet harmony. The song is lively, spirited, upbeat, catchy, vivacious;vibrant and peppy with a salsa dance groove. This song is Latin Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/fPYeqTFc3IQ.wav"} +{"id": "fPYxUa1ZVAY", "caption": "This is an instrumental flute music piece. The flute is playing a gentle melody while an acoustic guitar is playing an arpeggio in the background. There is a calming, relaxing atmosphere. This piece would fit perfectly in the background of a meditation video. It could also be used in the soundtrack of a documentary during serene scenery shots.", "audio": "/zhanghaomin/datas/musiccap/music_data/fPYxUa1ZVAY.wav"} +{"id": "fQiSoVDFRjo", "caption": "This alternative rock song features a male voice singing the main melody at a high pitch. Other male voices sing in harmony after the main voice pauses. This is accompanied by powerful percussion playing a rock beat in common time. Distortion guitars play power chords. One of the guitars plays the same melody as the backing voices on the lead guitar. The bass plays the root notes of the chords. This song is played at a moderate tempo. The mood of this song is upbeat. This song can be played in a Transformers style movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/fQiSoVDFRjo.wav"} +{"id": "fRpJfrfjoZo", "caption": "The song is an instrumental music section. The song is medium tempo with a string section playing percussively with violins and cellos in harmony, flute playing a melancholic solo, percussive hits and steady bass line. The song is full of suspense and passion. The song is a Tamil movie instrumental soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/fRpJfrfjoZo.wav"} +{"id": "fSJ4qAPHaVM", "caption": "The low quality recording features an echoing electric guitar arpeggiated melody. At the very end of the loop, the guitar is pitched and bent down. It is noisy and in mono and it sounds like someone is trying out guitar amp effects.", "audio": "/zhanghaomin/datas/musiccap/music_data/fSJ4qAPHaVM.wav"} +{"id": "fTGZEmn3BY4", "caption": "This is a style of Hindustani classical music performance which involves a calm and soothing musical performance. There is a male singer singing open-mouthed syllables.", "audio": "/zhanghaomin/datas/musiccap/music_data/fTGZEmn3BY4.wav"} +{"id": "fU9woCZqemw", "caption": "The low quality recording features a shimmering bell melody, followed by some stuttering swing sound effects. It sounds passionate and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/fU9woCZqemw.wav"} +{"id": "fUC45bzOOJw", "caption": "The low quality recording features laser, buzzy and metallic sound effects with a haunting background music, which makes it sound like it was recorded in a game room. The recording is noisy, mono, distorted and it sounds creepy.", "audio": "/zhanghaomin/datas/musiccap/music_data/fUC45bzOOJw.wav"} +{"id": "fWfQxB2pVrc", "caption": "This folk song features a harmonica playing the main melody. This is accompanied by an acoustic guitar strumming chords. There are no other instruments in this song. This is an instrumental song. There are no voices in this song. The mood of this song is upbeat and happy. This song can be played in a movie scene involving a highway drive.", "audio": "/zhanghaomin/datas/musiccap/music_data/fWfQxB2pVrc.wav"} +{"id": "fWu8vVSSkNQ", "caption": "The low quality recording features a shofar tone played so loudly that the recording is distorted and harsh, aside from being already noisy itself. It is also in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/fWu8vVSSkNQ.wav"} +{"id": "fWwV7o4VjEQ", "caption": "An acoustic drum with a lot of reverb is playing a minimalistic slow groove along with an e-bass playing long single notes. A synth hit comes in for a moment and then an e-guitar is talking over it with a melody. The male voice sings with a lot of reverb, reverb and a chorus/flanger on his voice. The whole recording is full of reverb and the voice of the singer is using a ping pong delay. This song may be playing on a lazy day at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/fWwV7o4VjEQ.wav"} +{"id": "fWypK9RHJJI", "caption": "A male singer sings this reggae melody with a live audience. The song is medium tempo with a groovy drum rhythm, trumpet playing rhythmically, guitar playing accompaniment and a groovy bass line. The song is exciting and cheerful. The song is a modern reggae tune and played in both a live audience situation and studio recording quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/fWypK9RHJJI.wav"} +{"id": "fX8A5Uxc8R0", "caption": "Someone is playing an e-bass along with somebody playing percussion with fast rhythms. A male voice is singing in a higher register. This is an amateur recording and of poor audio-quality. This song may be playing in a live scenario.", "audio": "/zhanghaomin/datas/musiccap/music_data/fX8A5Uxc8R0.wav"} +{"id": "fXhN3_gGpQw", "caption": "A male singer sings this rock melody. The song is medium fast tempo with a strong rock drumming rhythm, percussive bass line, distorted guitars playing rhythm and lead along with tambourine percussion. The song is energetic and cheerful. The song is a rock song with an average quality audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/fXhN3_gGpQw.wav"} +{"id": "fYk2U9yJvps", "caption": "The Electro song features a widely spread intimate percussive elements, stuttering hi hats, soft shakers, synth pad chords, groovy bass and punchy snare and kick hits. It sounds relaxing, calming and kind of satisfying, as it literally sounds like liquid dripping through the stereo image.", "audio": "/zhanghaomin/datas/musiccap/music_data/fYk2U9yJvps.wav"} +{"id": "fYvUB-qy4IM", "caption": "This slow rock song features a male voice singing the main melody. This song starts off with a guitar playing hammer ons over three chords. The main part of the song starts off after this sequence. It starts off with a drum roll and a pentatonic run on the guitar. The voice comes in after the roll and the bass starts playing with the voice. The bass plays the root notes of the chords. The voice sings an emotional line. This song can be played in a movie based on the hippie culture.", "audio": "/zhanghaomin/datas/musiccap/music_data/fYvUB-qy4IM.wav"} +{"id": "fZjQBgPD1Ys", "caption": "This is a rock opera piece that is being sung by a female vocalist in a medium-to-high pitch range. There is an orchestra playing the melody in the background composed of strings, flute and a piano. The atmosphere of the piece is dreamy and sentimental. It could be used in the soundtrack of a fairytale movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/fZjQBgPD1Ys.wav"} +{"id": "fZyq2pM2-dI", "caption": "The low quality recording features a traditional song that consists of at least steel guitar melody, wooden percussive elements and flat male vocal singing over it. The recording is very noisy and the stereo image is unbalanced - pretty much destroyed. It sounds vintage.", "audio": "/zhanghaomin/datas/musiccap/music_data/fZyq2pM2-dI.wav"} +{"id": "f_NR19LpA_E", "caption": "This music is a mellow instrumental. The tempo is slow with a mellifluous flute harmony with trumpet, trombone tuba accompaniment , lively drumming and bass cello. The music is playful, sunny, melodic, animated and pleasant.", "audio": "/zhanghaomin/datas/musiccap/music_data/f_NR19LpA_E.wav"} +{"id": "fa0lR26K23E", "caption": "The low quality recording features a shimmering bells alongside mellow sustained brass melody and tinny bells melody. It gives off nostalgic and euphoric vibes and it also sounds soft and mellow - almost like a lullaby.", "audio": "/zhanghaomin/datas/musiccap/music_data/fa0lR26K23E.wav"} +{"id": "fcpVyvn5vKk", "caption": "This is a stringed quartet playing a piece that feels positive and happy. The instruments are violin and cello and the style of playing is reminiscent of Indian style violin playing.", "audio": "/zhanghaomin/datas/musiccap/music_data/fcpVyvn5vKk.wav"} +{"id": "fe10sxFSz_I", "caption": "This audio contains someone playing a harp picking a tremolo melody. A female opera voice starts singing along in a higher pitch. This is an amateur recording. You can hear recording noises and the whole audio is panned to the left side of the speakers. This song may be playing in a theaterhouse.", "audio": "/zhanghaomin/datas/musiccap/music_data/fe10sxFSz_I.wav"} +{"id": "feC0L9MtghM", "caption": "Solo sitar using microtonality, droning and string bending. The music is hypnotic and meditative and there is the sound of tape hiss and warble in the recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/feC0L9MtghM.wav"} +{"id": "fer_4HvG3aY", "caption": "The song is an instrumental track for a live performance act. The song is medium tempo with a male singer singing to a strong drumming rhythm, groovy bass line, keyboard accompaniment along with an amateur playing tambourine percussion. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/fer_4HvG3aY.wav"} +{"id": "fgCTFyzKQtk", "caption": "The music features a female voice singing a melody while being accompanied by a harp and strings synth played on a keyboard. The music has a ternary feel which is being emphasized by the harp that plays 3 equal notes every beat. The keyboard strings synth plays harmony as well as a melody that towards the end of the music excerpt is played in unison with the singer's melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/fgCTFyzKQtk.wav"} +{"id": "fhWzjWZqzvs", "caption": "The low quality recording features a Northern Soul song that consists of passionate female vocal singing over groovy piano chords, groovy bass, shimmering tambourine layered with punchy snare hits, muddy kick hits and groovy church organ melody. It sounds thin, but also easygoing, nostalgic, sentimental and passionate - like something you would hear in clubs during 60s and 70s.", "audio": "/zhanghaomin/datas/musiccap/music_data/fhWzjWZqzvs.wav"} +{"id": "fhs7AkJsYao", "caption": "This is an instrumental rock-sounding gear showcase jam. There is an electric guitar playing improvised disconnected riffs with varying accentuations. There is an echo delay pedal being used on the guitar that makes the notes being played echo repeatedly in a fading manner. Due to the usage of numerous riffs, an electric guitar sample could be lifted from this piece to be used in a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/fhs7AkJsYao.wav"} +{"id": "fiAcNMpd2vM", "caption": "The low quality recording features a live performance of a folk song that consists of a passionate male vocal singing over groovy bass, woodwind melody, punchy snare and wooden percussion. It sounds joyful, energetic and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/fiAcNMpd2vM.wav"} +{"id": "fjj9NJX8GB0", "caption": "This recording contains breaking and shooting sounds. There is also a lot of deep rumbling noise. The whole audio is panned to the right side of the speakers. This is an amateur recording and of poor audio-quality. This audio may be playing in a video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/fjj9NJX8GB0.wav"} +{"id": "fjxD32KIHgE", "caption": "Solo percussion playing additive rhythms and polyrhythms.", "audio": "/zhanghaomin/datas/musiccap/music_data/fjxD32KIHgE.wav"} +{"id": "fkgaF6Oj5Q4", "caption": "The folk music features a bouzouki playing a Greek traditional song. An acoustic guitar accompanies the bouzouki with two strummed chords every measure. Two pairs of bongos or one of bongos and one of congas provide rhythmic variety and drive the pulse of the music.", "audio": "/zhanghaomin/datas/musiccap/music_data/fkgaF6Oj5Q4.wav"} +{"id": "flLjMZMydXc", "caption": "This is an instrumental folk song with the melody played both by a banjo and a violin at the same time. The combination of these instruments creates a very American, western-movie type of atmosphere. It could be used in opening sequences of movies/shows taking place in rural USA.", "audio": "/zhanghaomin/datas/musiccap/music_data/flLjMZMydXc.wav"} +{"id": "fmHbWq-7-iQ", "caption": "The low quality recording features a soft metal song that consists of muffled male vocals, alongside wide background melodic male vocals, singing over filtered synth pad, uptempo toms rolls, punchy snare and kick hits and shimmering cymbals. It sounds energetic and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/fmHbWq-7-iQ.wav"} +{"id": "fow1TC_MpHs", "caption": "This music is a flamenco piece. There are two acoustic guitars, one playing the leading arpeggio melody and the other creating the rhythmic background by strumming the chords. The characteristics of the song makes it clear that it is influenced by Spanish music. It could be used in a thriller movie soundtrack or as a flamenco dance accompaniment piece for dancing courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/fow1TC_MpHs.wav"} +{"id": "fp0oCFL6w4o", "caption": "This is a live performance of a rock music piece. There are male vocals singing melodically. The electric guitar is playing the main tune. The bass guitar is playing a simple bass line. In the rhythmic background, there is a simple acoustic drum beat. The atmosphere is cheerful. This piece can be used in the soundtrack of a feelgood TV series during the credits.", "audio": "/zhanghaomin/datas/musiccap/music_data/fp0oCFL6w4o.wav"} +{"id": "fpVlYpgTKZI", "caption": "The Alternative/Indie song features an echoing, passionate female vocal singing over groovy, buzzy synth bass, punchy kick, soft claps, tinny offbeat percussion and synth keys chords that appear at the end of the loop. It sounds groovy, energetic, passionate and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/fpVlYpgTKZI.wav"} +{"id": "fpbtmY9VfCw", "caption": "This is an electronic house music piece. There is a melodic pad playing a repeated tune for the melody. The strong bass and the loud electronic drums are playing as the essential backbone of the house music genre. There is a male voice sample that repeats the same word. There is a female voice sample that speaks occasionally. The atmosphere is energetic. This piece could be playing at nightclubs or dance clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/fpbtmY9VfCw.wav"} +{"id": "fpdgtpBOh-c", "caption": "This slow pop ballad features two cellos playing in harmony. One cello plays the high notes. The second cello plays the bass notes. This is accompanied by a piano playing chords in the background. The mood of this song is romantic. There are no voices in this song. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/fpdgtpBOh-c.wav"} +{"id": "frqnZb8Ssjo", "caption": "This clip features a drum kit being played. Different parts of the drum kit are played. At the beginning, a female narrates the process in one line following which different parts of the kit are struck. This sound can be played in a drum test scenario.", "audio": "/zhanghaomin/datas/musiccap/music_data/frqnZb8Ssjo.wav"} +{"id": "fsTVRca31nI", "caption": "The rock music features a nasal male voice. The voice follows a strummed electric guitar with a clean sound. The bass is backing the guitar strumms. The beat is made first with ticking sounds but then it's played by a drum kit.", "audio": "/zhanghaomin/datas/musiccap/music_data/fsTVRca31nI.wav"} +{"id": "fsXQHyg5qDI", "caption": "This song features a male giving instructions on playing a guitar. A distortion guitar is playing the root note and the fifth. After the instruction, the root note and the fifth is played individually. This song features only the male instruction voice and no vocal melody. There are no other instruments in this song. There is no percussion in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/fsXQHyg5qDI.wav"} +{"id": "fsXfBoNcLeM", "caption": "The Pop song features a flat female vocal rapping, alongside passionate background female vocal singing, over straight piano chords, simple synth bass, wide distorted synth and wide synth brass chords, followed by groovy hi hats, punchy kick and snare hits. It sounds uplifting and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/fsXfBoNcLeM.wav"} +{"id": "ftKCLRd9_no", "caption": "The low quality recording features a flat male talking singing over ukulele chord progression, after which the flat male vocal is talking. It sounds like a tutorial and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ftKCLRd9_no.wav"} +{"id": "ftaHv79hRoY", "caption": "The song is an instrumental tune. The song is medium tempo with a steady drumming rhythm, groovy bass line, trumpets playing, brass band section and keyboard harmony. The song is exciting and energetic. The song is a tv show tune and has fun jazz roots.", "audio": "/zhanghaomin/datas/musiccap/music_data/ftaHv79hRoY.wav"} +{"id": "fvTh5m9RHZw", "caption": "This is an instrument comedy music piece. There is a clarinet playing a goofy tune. Then, the clarinet stops and the strings section starts playing a dramatic melody. This piece could be sampled to be used as instrumentals in an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/fvTh5m9RHZw.wav"} +{"id": "fvhbI-7e89s", "caption": "The excerpt starts off with 2 seconds of background music after which one can hear a lot of belching of various pitches.", "audio": "/zhanghaomin/datas/musiccap/music_data/fvhbI-7e89s.wav"} +{"id": "fvpDYGzdRmo", "caption": "The song is an instrumental. The tempo is medium with a recorder being played with a lot of heart, accompanied by string section harmony. The song is emotional and has a lot of spirit. The song is a western classical music masterpiece.", "audio": "/zhanghaomin/datas/musiccap/music_data/fvpDYGzdRmo.wav"} +{"id": "fvw3Bi0GONA", "caption": "The music features a group of female and male voices singing a melody in unison. An acoustic guitar is accompanying the group with strummed chords and a tambourine is highlighting every beat. The overall atmosphere is joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/fvw3Bi0GONA.wav"} +{"id": "fwXh_lMOqu0", "caption": "The low quality recording features a flat male vocal talking, after which he starts playing a harmonica. There are some wooden impact sounds. The recording is mono and noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/fwXh_lMOqu0.wav"} +{"id": "fw_cFbj9eHQ", "caption": "This audio contains a lot of people playing a percussive instrument. You can also hear stick hits. It seems like they're all playing the same rhythmic pattern. This song may be playing live in a drumming school.", "audio": "/zhanghaomin/datas/musiccap/music_data/fw_cFbj9eHQ.wav"} +{"id": "fxdWwzdeY_o", "caption": "The song is a rock track that features distorted and energetic guitar strumming chords. A secondary guitar does a solo melody in the foreground. A drum kit plays a typical upbeat rock pattern with an energetic mood. A bass adds deepness to the track while playing the same progression as the strummed guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/fxdWwzdeY_o.wav"} +{"id": "fxznho_kNPY", "caption": "The song is an instrumental. The song is medium tempo with a violin, viola, cello playing a string harmony accompanied by an acoustic guitar strumming chords. The song is a western classical music piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/fxznho_kNPY.wav"} +{"id": "fyLctn3jNUs", "caption": "This audio contains a female voice speaking. Then a loud theremin tone comes in, rising and falling in pitch. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/fyLctn3jNUs.wav"} +{"id": "g-9SK0or81c", "caption": "This clip features a melody played on a bass guitar. The bass uses tremolo. A series of effects are used on the bass. Harmonics are played on the bass. No other instruments are used in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/g-9SK0or81c.wav"} +{"id": "g-ZOluGhMoA", "caption": "This is hardcore electronic music piece. The rhythmic background consists of a fast tempo electronic drum beat with a crisp sound. There is an aggressive fuzzy bass. The atmosphere is energetic. This piece could be used in the soundtrack of a mobile car racing game.", "audio": "/zhanghaomin/datas/musiccap/music_data/g-ZOluGhMoA.wav"} +{"id": "g-ghr5fAVpE", "caption": "The low quality recording features a didgeridoo playing in a room. The recording is noisy and there are sniffing sounds from the player, as he is trying to catch his breath.", "audio": "/zhanghaomin/datas/musiccap/music_data/g-ghr5fAVpE.wav"} +{"id": "g0AXzsecS5M", "caption": "The vocalist raps in a way that is more like a spoken story. The song is upbeat and energetic. The genre of music would be suitably described as rave or jungle music. It's an intense feeling song. The drum beat is simple and comes underneath a variety of sound effects like sirens and beeps.", "audio": "/zhanghaomin/datas/musiccap/music_data/g0AXzsecS5M.wav"} +{"id": "g0WLA0BKxOc", "caption": "Someone is playing a fast shred solo on a distorted e-guitar with a lot of reverb and delay panning to both sides of the speakers. This song may be playing in a youtube video showing off your progress.", "audio": "/zhanghaomin/datas/musiccap/music_data/g0WLA0BKxOc.wav"} +{"id": "g0aOPWwNMFQ", "caption": "This piano song features a piano playing the backing chords. A violin plays the main melody. The melody is romantic but turns eerie at the end. There are no other instruments in this song. A male voice narrates two words toward the end of the song. This song can be played in a promotional video.", "audio": "/zhanghaomin/datas/musiccap/music_data/g0aOPWwNMFQ.wav"} +{"id": "g0scnRzoo9M", "caption": "The ballad song features a mellow female vocal singing over a mellow organ keys melody, groovy hi hats, soft snare and kick hits and smooth bass. It sounds emotional, heartfelt and romantic - like something you would hear at a wedding.", "audio": "/zhanghaomin/datas/musiccap/music_data/g0scnRzoo9M.wav"} +{"id": "g2H8i_TuhgI", "caption": "This is a classical music piece in the style of a military march. There is a wind orchestra playing the melody. In the rhythmic background, marching band elements such as the snare drum, the bass drum, the cymbal and the triangle can be heard. There is an epic atmosphere. This piece would fit perfectly in the soundtrack of a war video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/g2H8i_TuhgI.wav"} +{"id": "g4xhZgKwiNo", "caption": "A male vocalist sings this classic song. The tempo is slow with guitar accompaniment. The song has minimal instruments and is mellow, soft, sentimental, emotional, nostalgic, calming, soothing and mellifluous with vocal emphasis. This song is classic pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/g4xhZgKwiNo.wav"} +{"id": "g6f-LxiT9Eo", "caption": "The song is an instrumental. The song is medium tempo with a groovy bass line, rock drumming, tambourine percussion, guitar rhythm and guitar lead. The song is adventurous and emotional. The song is classic rock and has a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/g6f-LxiT9Eo.wav"} +{"id": "g75kz9ffcg0", "caption": "A male singer sings this screaming metal melody. The song is medium fast tempo with a fast metal drumming rhythm, percussive bass line and guitars playing accompaniment. The song is rebellious and highly spirited. The audio quality is very poor and vintage.", "audio": "/zhanghaomin/datas/musiccap/music_data/g75kz9ffcg0.wav"} +{"id": "g8USMvt9np0", "caption": "Sounds like the intro to a children's program. Children's music featuring vibraphone, a children's choir and old tape static in the background. It has a happy, bright feel.", "audio": "/zhanghaomin/datas/musiccap/music_data/g8USMvt9np0.wav"} +{"id": "g8XTU3OalGs", "caption": "This clip features a synth being played. The tone is that of an electric piano. This synth plays the bass notes as well as the treble notes. This song has no other instruments. This is an instrumental song with no voices. This song can be played in an instructional video for synthesizers.", "audio": "/zhanghaomin/datas/musiccap/music_data/g8XTU3OalGs.wav"} +{"id": "gAQiARaliPA", "caption": "This is an upbeat Arabic dance pop song. There's an energetic male singer with a heavily autotuned voice who sings to the beat. The beat features a four on the floor kick drum pattern and hi-hats being played in a pattern of 16th notes. There's a rapid repeated synth melody riff. The song would be heard at a dance club.", "audio": "/zhanghaomin/datas/musiccap/music_data/gAQiARaliPA.wav"} +{"id": "gAURHUoIK0M", "caption": "A live recording of an instrumental piano trio. The recording is boomy and low fidelity. The drumming is active and the piano playing is pretty. The drum kit features a sidestick. Electric bass is also present. Crowd noise can be heard. Sounds like gospel music that might be heard at a church service.", "audio": "/zhanghaomin/datas/musiccap/music_data/gAURHUoIK0M.wav"} +{"id": "gBuLpP4klvI", "caption": "A female vocalist sings this chirpy song. The tempo is medium with a melodic electric guitar harmony, acoustic guitar lead, sprightly drumming, funky bass lines and peppy backup. The song is youthful, perky, cheerful, vivacious ,bubbly and in a foreign language.This song is teen pop/ Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/gBuLpP4klvI.wav"} +{"id": "gCSShNsw-_A", "caption": "The song is an instrumental. The tempo is medium fast with strong metal drumming, groovy bass line, distorted guitar playing rhythm and cymbals crashing. The song is high on adrenaline and exciting. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/gCSShNsw-_A.wav"} +{"id": "gD6UoStqCsg", "caption": "A synthesizer pluck sounds in playing a melody while a synthesizer pad rises from the background as a filter opens and reveals the full force of the synthesizer pad along with a synthetic bass underlining the rise. This song may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/gD6UoStqCsg.wav"} +{"id": "gDm4IphrlYg", "caption": "The low quality recording features a sizzling glassy melody arpeggiated in high pitch register. Sounds mystical and it gives off some euphoric Christmas feelings. There are also some tapping noises, mostly in the left channel of the stereo image.", "audio": "/zhanghaomin/datas/musiccap/music_data/gDm4IphrlYg.wav"} +{"id": "gDnJoHpSL4M", "caption": "A lot of tambourines are playing in synchronicity. In between the rhythm a choir is singing a short phrase. This song may be played as a tutorial to follow along.", "audio": "/zhanghaomin/datas/musiccap/music_data/gDnJoHpSL4M.wav"} +{"id": "gDzi8N3BYMw", "caption": "This is a japanese jazz music piece that is used in an anime soundtrack. There is a female lead vocal singing gently in the lead. The melody is being played by the piano, the electric guitar and the upright bass. In the rhythmic background, there is an acoustic jazz drum beat in the style of swing. There is an exhilarating atmosphere, full of rich sounds. The mix is perfect. This piece could be used in the soundtrack of a romance/drama movie as well as its original use in an anime. It could also be playing in the background at a coffee shop or a classy restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/gDzi8N3BYMw.wav"} +{"id": "gEYTdeQiFv8", "caption": "This is an Omani traditional music piece performed live on the street. The melody is being performed by the bagpipes. The atmosphere is vibrant and lively. This piece could be used in the soundtrack of a historical drama that takes place in the Gulf region during British imperial rule.", "audio": "/zhanghaomin/datas/musiccap/music_data/gEYTdeQiFv8.wav"} +{"id": "gEvCUcZ6w88", "caption": "A female vocalist sings this enthusiastic song.The tempo is medium with loud , emphatic vocals and subdued music in the background .The song is a karaoke with enthusiastic drumming, melodious violin harmony, keyboard accompaniment, groovy bass line and rhythmic acoustic guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/gEvCUcZ6w88.wav"} +{"id": "gFxLnprPgv4", "caption": "The music features a melody being played in unison by a piano and a group of strings. At the same time these two also fill up the music space with harmony. A type of drum that resembles the taiko drum but I think is smaller in size can be heard in the background. In the background a synth pad provides soft harmony.", "audio": "/zhanghaomin/datas/musiccap/music_data/gFxLnprPgv4.wav"} +{"id": "gHWMKew9Xq0", "caption": "Stoic music featuring steady acoustic guitar arpeggios, a clave, and a measured female singer. There is a slight tape hiss. The source material may be old.", "audio": "/zhanghaomin/datas/musiccap/music_data/gHWMKew9Xq0.wav"} +{"id": "gI-ovjTWBzo", "caption": "This song contains a male voice loudly singing in a higher key. A flutelike instrument is playing a melody out of tune accompanied by an accordion sound. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/gI-ovjTWBzo.wav"} +{"id": "gIFg6jvXgb4", "caption": "This clip features a low and reverberating synth, and then a bright and futuristic and spacey synth. The low synth sounds like a landing space ship.", "audio": "/zhanghaomin/datas/musiccap/music_data/gIFg6jvXgb4.wav"} +{"id": "gIQ4QrKXjCc", "caption": "This is an instrumental progressive/math rock piece. The electric guitar is playing a complex solo with rapid procession of notes using the tapping technique. There is a reverberating piano sample in the background. The atmosphere is trippy. This piece can be used in the soundtrack of a video game that takes place in outer space.", "audio": "/zhanghaomin/datas/musiccap/music_data/gIQ4QrKXjCc.wav"} +{"id": "gMgN50wSnNc", "caption": "This salsa song features a female voice singing the main melody. This is accompanied by percussion on a drum kit as well as on a congo. The congo gives this song the salsa feel. The drum kit plays the cowbell and high pitched snare drum to add more of the salsa vibe. The bass plays groovy fills. Trumpets, trombones and saxophones play fills in between lines. They play in harmony. A piano plays jazzy chords in the background. This song can be played in a dance club for a salsa night.", "audio": "/zhanghaomin/datas/musiccap/music_data/gMgN50wSnNc.wav"} +{"id": "gNjeps3EbJA", "caption": "The low quality recording features a live performance of a folk song and it contains harmonized mixed vocals singing over groovy bass, groovy accordion melody and arpeggiated acoustic guitar solo melody. The recording took place outdoors, since there was some crowd chattering and nature sounds. It sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/gNjeps3EbJA.wav"} +{"id": "gNpzuFPu6q8", "caption": "The low quality recording features a passionate female vocalist singing over wooden percussion, synth lead melody and plucked strings melody playing in the background. It sounds passionate, emotional, joyful and traditional.", "audio": "/zhanghaomin/datas/musiccap/music_data/gNpzuFPu6q8.wav"} +{"id": "gOhONZR_F7c", "caption": "A string digital drum is playing a simple groove along with a shaker sound. A piano is playing a neo-soul melody while a high pitched vocal sample is panning to both sides of the speakers. It almost sounds like a plucked strings instrument. On top of that a male voice is singing in a higher pitch. This song may be playing being on a date with someone you started going out with.", "audio": "/zhanghaomin/datas/musiccap/music_data/gOhONZR_F7c.wav"} +{"id": "gRGiTueWUVI", "caption": "This song is a salsa song, with various layers of upbeat percussion which are suitable for dancing. There are bongo drums and maracas, played at a medium to high tempo. The vocalist has a dainty voice and sings in almost a high pitched voice in almost a whisper. There are brass instruments, especially trumpet and the song would be suitable for a salsa party.", "audio": "/zhanghaomin/datas/musiccap/music_data/gRGiTueWUVI.wav"} +{"id": "gRn6OjQf2ZQ", "caption": "The song is upbeat, groovy and jazzy. The main percussive elements are created by live tap dancing on a stage, as well as more base oriented percussion from a cajon drum. There's a grand piano playing an intricate melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/gRn6OjQf2ZQ.wav"} +{"id": "gTO00a-LFYs", "caption": "This music is instrumental. The tempo is slow with synthesiser arrangements. There are sounds of howling winds and footsteps and a droning cello harmony. The music is eerie, spooky, terrifying, sinister, dangerous and scary.", "audio": "/zhanghaomin/datas/musiccap/music_data/gTO00a-LFYs.wav"} +{"id": "gTX4SG70cEY", "caption": "A male vocalist sings this sad melody. The tempo is slow with an acoustic guitar accompaniment and a droning keyboard harmony. The song is soft ,mellow, sad, emotional, sentimental, regretful , lonely and poignant. This song is an Alternative Rock/Indie.", "audio": "/zhanghaomin/datas/musiccap/music_data/gTX4SG70cEY.wav"} +{"id": "gVMoI2ukbtc", "caption": "This is an R&B/pop music piece. There is a female vocalist singing melodically in the lead. The melody is being played on the electric guitar. The bass guitar is playing in the background. The rhythmic background consists of an electronic drum beat. The atmosphere is easygoing and generic. This piece could work well as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/gVMoI2ukbtc.wav"} +{"id": "gW33LYEvoaw", "caption": "solo harmonic playing a single high note and bending it down a half step. This is followed by a male voice over.", "audio": "/zhanghaomin/datas/musiccap/music_data/gW33LYEvoaw.wav"} +{"id": "gWRfk8nCcPs", "caption": "This reggae song features a male voice. He sings the first line and laughs at the end of the first sentence. He continues to sing the melody. The voice is accompanied by programmed percussion playing a simple beat. The bass plays the root notes of the chords. A keyboard plays chords in the background with a reggae feel. Another keyboard plays a fill in between lines. At the end, backing singers sing in harmony. This song has a holiday mood. This song can be played in a holiday movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/gWRfk8nCcPs.wav"} +{"id": "gX9OuOKLLTQ", "caption": "This music is an instrumental tutorial. A male musician is keeping count in French to the drone-like tune of a French Horn. The audio is not clear and has a lot of static.", "audio": "/zhanghaomin/datas/musiccap/music_data/gX9OuOKLLTQ.wav"} +{"id": "gXOyw8a4_Xs", "caption": "Someone is strumming chords on an acoustic guitar singing along with a male voice in the higher register. male backing vocalists are supporting the singer. A piano is playing supportive chords along with congas and a tambourine. This is an amateur recording but of decent quality. This song may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/gXOyw8a4_Xs.wav"} +{"id": "gXzqZIoM5g8", "caption": "The low quality recording features a metal song that consists male vocals with a wide echoing effect on, wide filter modulated electric guitar chords, noisy snare hits, punchy kick and pulsating synth riser that appears towards the end of the loop. It sounds exciting, as it prepares the listener for an energetic drop.", "audio": "/zhanghaomin/datas/musiccap/music_data/gXzqZIoM5g8.wav"} +{"id": "g_bgmnJ1b_g", "caption": "The low quality recording features an acoustic guitar blues melody. The recording is very noisy, roomy and you can hear cars passing by in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/g_bgmnJ1b_g.wav"} +{"id": "gb8PG-5i5YI", "caption": "The song is an instrumental. The tempo is medium with a brass including trumpets and saxophones playing in harmony, wooden xylophones and Latin percussions play accompaniment to the band along with a male singer. The song is exciting and groovy. The audio quality is poor and probably a home recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/gb8PG-5i5YI.wav"} +{"id": "gcdqffsCWI8", "caption": "This is an instrumental latin music piece. There is a keyboard playing a few notes. The acoustic drums start playing initially by hitting a small cymbal repeatedly and then performing drum rolls on the snare drum. The drum rolls sound very much alike to the style of a marching band. Parts of this recording can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/gcdqffsCWI8.wav"} +{"id": "gdtw54I8soM", "caption": "This music is instrumental. The tempo is fast but the music is muffled as it is superimposed by a loud buzzing sound along with some tapping,scuffling, finger snapping ans tapping sounds. The music sounds like energetic Electronic music with vigorous drumming.", "audio": "/zhanghaomin/datas/musiccap/music_data/gdtw54I8soM.wav"} +{"id": "gfIqYbQQq10", "caption": "This audio contains digital drums with an open hi hat. A distorted e-guitar and an e-bass are both playing the same melody in the lower register. A synth pluck is playing a simple repeating rhythmic melody on top. You can hear the sound of glass breaking. This song may be playing at a live festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/gfIqYbQQq10.wav"} +{"id": "gffng5G4X4w", "caption": "The low quality recording features an arpeggiated electric guitar melody. It sounds passionate, fun, happy and joyful. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/gffng5G4X4w.wav"} +{"id": "ggBivmG6yHQ", "caption": "This is the live recording of a dance performance that uses a pop music piece as accompaniment. There is a male and a female vocalist singing melodically. The tune of the piece is being played by the electric guitar, the bass guitar and the synth. There is an upbeat acoustic drum beat in the rhythmic background. The audience can be heard clapping to the beat. The atmosphere is loud and lively. It could work well as the backing track in a modern dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/ggBivmG6yHQ.wav"} +{"id": "ghW2xZMvpIQ", "caption": "A female vocalist sings this soft melody. The tempo is slow with violin harmony, keyboard accompaniment, saxophone, digital drum, tabla and tambourine beats. The song is mellow, soft, melodic, soothing, calming , devotional and euphonious. This song is a Tamil Christian Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/ghW2xZMvpIQ.wav"} +{"id": "giPa2vVEyVc", "caption": "This is a Sikh religious music piece. The male vocalist is singing in the Hindi language in a devoted manner. There is an organ in the background playing the melody accompanying the male vocal. Electronic drums and electronic percussion provide the rhythmic background for the piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/giPa2vVEyVc.wav"} +{"id": "gigxzYegRqM", "caption": "A male singer sings this cool melody in the background with a bunch of female singers singing a little jig in a different key. The song is medium tempo with steady drumming, tambourine percussion, trumpets blaring, strong bass line and a piano accompaniment. The song serves as a background music to a group of females singing a jig in a different key. The song is a modern pop dance tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/gigxzYegRqM.wav"} +{"id": "gjJWbtCShqo", "caption": "This slow rock song starts off with a male voice that pauses after one word. This is accompanied by percussion playing a marching beat. Synth strings play chords in the background. Bass notes follow the root notes of the chords. After the voice pauses, a repetitive melody is played on the synth and the chords change on the other instruments. The percussion continues to play the marching beat. This song can be played in a war scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/gjJWbtCShqo.wav"} +{"id": "gjujPd1lP8E", "caption": "A digital kick in playing on every beat along with short voice samples with breathy sounds that sound seductive. Then the song changes into someone fingerpicking an acoustic guitar along to someone playing an acoustic snare/hihat with brushes. This first song may be playing in a club and the second one at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/gjujPd1lP8E.wav"} +{"id": "gkB4KBHBV9g", "caption": "A male vocalist sings a soft melody in a foreign language. The tempo is slow with a piano harmony . The vocals are soft and subdued with ambient background sounds. The song is simple, mellow , melancholic and soft. This song is soft pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/gkB4KBHBV9g.wav"} +{"id": "gkMbHlNAFig", "caption": "This is a cover of a pop music piece. There is a male vocalist singing melodically. The melody is being played by the acoustic guitar and the electric guitar while the bass guitar is playing in the background. The rhythm is provided by a slow tempo acoustic drum beat. There is a mellow atmosphere in this piece. It could be used in the soundtrack of a drama TV series.", "audio": "/zhanghaomin/datas/musiccap/music_data/gkMbHlNAFig.wav"} +{"id": "go_7i6WvfeE", "caption": "The song is an instrumental. The song is medium tempo with a pensive bass solo followed by string distortion guitar rhythm and a strong drum entry crash. The death metal song is tense and builds anticipation. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/go_7i6WvfeE.wav"} +{"id": "gp1DYuoQH08", "caption": "This is a live performance of a jazz ballad music piece. The accordion is playing a solo as the main melody. There is an acoustic guitar playing the chords of the piece. The bass line is being played by the upright bass. The atmosphere is gentle. This piece is the perfect music to be played in the background at a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/gp1DYuoQH08.wav"} +{"id": "gp7j9o2x9co", "caption": "This amateur recording features two guitars being played. One guitar is playing a blues rhythm. The other guitar is strumming the main chord once and then playing fills on the higher register. This is accompanied by a tambourine as the percussion. There are no voices in this song. This is an instrumental blues rock song. The mood of this song is suspenseful. This song can be used in a detective movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/gp7j9o2x9co.wav"} +{"id": "gpEU6RafUf0", "caption": "The song track is an instrumental. The tempo is medium, with a guitarist demonstrating a guitar effects reverb pedal by playing related instrumental phrases. The song is trippy and exciting. The audio quality is poor as it\u2019s an amateur home recording .", "audio": "/zhanghaomin/datas/musiccap/music_data/gpEU6RafUf0.wav"} +{"id": "gpNzFsxwy5k", "caption": "The low quality recording features a Chiptune music that consists of a high pitched vocal singing over groovy synth keys, synth lead melody, laser synth effects, punchy kick, claps, shimmering hi hats and groovy synth bass. It sounds energetic, fun, happy and joyful - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/gpNzFsxwy5k.wav"} +{"id": "gqROBgF7_DU", "caption": "The low quality recording features an aggressive sound of synth feedback. In the second half of the loop, the sound is very noisy. It is loud and it sounds really harsh.", "audio": "/zhanghaomin/datas/musiccap/music_data/gqROBgF7_DU.wav"} +{"id": "gqkqzqCHM3A", "caption": "This meditation song features a melody played on a flute. The tone of the flute is tremulous. This is accompanied by a Veena playing a repetitive melody. There are no other instruments in this song. There are no voices in this song. The mood of this song is relaxing and calming. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/gqkqzqCHM3A.wav"} +{"id": "grE0lwTsSPg", "caption": "This is an upbeat, soulful and funky song. It's got a catchy and fast paced rhythm which makes it good to dance to. The singer has a raspy and energetic voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/grE0lwTsSPg.wav"} +{"id": "grisjVTZeTk", "caption": "This music is an electronic instrumental. The tempo is fast with synthesiser articulation, electronically arranged music and digital drumming . The music is a vigorous, vivacious, energetic, hypnotic, psychedelic, new age, trance like and trippy. This is used in EDM/ Techno Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/grisjVTZeTk.wav"} +{"id": "gsBXngKgy-Q", "caption": "Salsa music featuring heavy percussion including timbale, bongos, guiro among others, a brass section with trumpet and trombone. The music features full band melodies and drum breaks with complex chord progressions and group male vocals.", "audio": "/zhanghaomin/datas/musiccap/music_data/gsBXngKgy-Q.wav"} +{"id": "gsEk62Efbh4", "caption": "This salsa song contains percussive elements as maracas,cowbell and bongos creating a typical salsa rhythm spread across both sides of the speakers. An e-bass is playing a complex walking bassline. An acoustic piano is playing a melody up and down the scales along with backing vocals singing in harmony as a countermelody to the male lead voice singing in the midrange. This song may be playing in a latin bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/gsEk62Efbh4.wav"} +{"id": "gsIB8HjsRtw", "caption": "The low quality recording features a live performance of a folk song that contains an accordion melody playing over acoustic rhythm guitar, groovy bass, punchy kick and snare hits, shimmering cymbals, saxophone and trumpet melody. It sounds passionate and easygoing, even though the recording is noisy and the stereo image is unbalanced, due to the fact that the sound is leaning towards the left channel.", "audio": "/zhanghaomin/datas/musiccap/music_data/gsIB8HjsRtw.wav"} +{"id": "guRyU4B5LlA", "caption": "This is a cover performance of a pop music song. There is a male vocalist singing very loudly, but at the same time slightly out of tune. The piano track plays the melody, however there is a poor transposition of the piano sound making it sound corrupted.", "audio": "/zhanghaomin/datas/musiccap/music_data/guRyU4B5LlA.wav"} +{"id": "guYWKdxrtIg", "caption": "This music is an electric guitar solo. The tempo is medium fast with an animated electric guitar riff without any accompaniment. The music is loud, powerful, rhythmic and youthful with a bit of static or white noise .", "audio": "/zhanghaomin/datas/musiccap/music_data/guYWKdxrtIg.wav"} +{"id": "gwBfZJ5IGOA", "caption": "The Low Quality Recording features a widely spread simple strings melody. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/gwBfZJ5IGOA.wav"} +{"id": "gxAyZk01T3k", "caption": "This song contains someone playing a melody on a flute panning to the right side of the speakers. A lower synth drone pad is underlining the flute along with more synth pad sounds and wind. Then a soft riser comes in and a digital drum starts playing along to a synth bass sound. This song may be playing in an indie movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/gxAyZk01T3k.wav"} +{"id": "gxzU5EqNL14", "caption": "The low quality recording features a live performance of a flamenco song sung by passionate male vocalists and followed by aggressive strumming of flamenco rhythm guitar. It is reverberant and noisy, as it was probably recorded with a phone, and it sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/gxzU5EqNL14.wav"} +{"id": "gy6R280ZUMQ", "caption": "This is a dance song which would fit in the afrobeats genre. There's a rhythmic vibrant synth with a fuzzy tone playing the main instrumental melody. There's also a groovy bassline. The percussion includes intermittent hits on a bongo drum, clapping hands, and a kick drum. This would be a good afrobeats club song.", "audio": "/zhanghaomin/datas/musiccap/music_data/gy6R280ZUMQ.wav"} +{"id": "gz-4W-uEzhc", "caption": "The Reggae song features harmonizing male vocals singing over wooden percussion, punchy snare and kick hits, claps, groovy bass, offbeat piano chords, followed by flat male vocals. It sounds energetic, happy, fun, groovy and funky.", "audio": "/zhanghaomin/datas/musiccap/music_data/gz-4W-uEzhc.wav"} +{"id": "h-2KO5ufrcw", "caption": "The low quality recording features an electro song that consists stuttering \"4 on the floor\" kick pattern, punchy snare, shimmering hi hats and open hats, soft crash cymbal, repetitive synth melody, spacey, echoing synth lead melody, buzzy synth bass and fading out stuttering female vocal sound effects. It is reverberant, messy, crushed and thin, as the frequencies are clashing with each other, but it still sounds energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/h-2KO5ufrcw.wav"} +{"id": "h-3DrDQC62k", "caption": "This clip features a drum solo being played on a rock drum kit. The snare, kick, toms, hi-hat and splash are being struck. A pattern is played on this percussion. There are no other instruments in this song. There are no voices in this song. This song can be played in a drum instruction video.", "audio": "/zhanghaomin/datas/musiccap/music_data/h-3DrDQC62k.wav"} +{"id": "h0-6U948u7Y", "caption": "This is a Nepali music piece. There is a string instrument and a local flute playing the melody. The rhythmic background is provided by percussion. It has a vibrant, dreamy feeling to it. This piece could be used in a dream sequence of a movie or TV show taking place in South Asian countries.", "audio": "/zhanghaomin/datas/musiccap/music_data/h0-6U948u7Y.wav"} +{"id": "h2f_CKjQQg8", "caption": "The song is instrumental. The song is medium tempo with an electric guitar lead, groovy bass line, steady drumming rhythm, cymbal crashes and keyboard harmony. The song is exciting and energetic. The song is a rock tune with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/h2f_CKjQQg8.wav"} +{"id": "h542YbZuwkQ", "caption": "This song is from a game. This clip starts with the sound of fireballs. This is followed by distant blasting sounds. A stringed instrument plays chords at a high pitch. There is no percussion in this song. There are no other instruments in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/h542YbZuwkQ.wav"} +{"id": "h6Y0KDtUNHw", "caption": "This music is instrumental. The tempo is medium with an intense didgeridoo harmony, violin melody and keyboard accompaniment. The music is eerie,suspenseful; grim, sinister, scary and spooky. It is the sound track of a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/h6Y0KDtUNHw.wav"} +{"id": "h7DOBV43UPQ", "caption": "This song features a high pitched whistling instrument. At the beginning, two hand claps are played. The high pitched whistling instrument plays a high pitched sound, then goes lower and again goes high to an almost ear deafening shriek. This is accompanied by programmed percussion playing a simple beat. There are no voices in this song and no other instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/h7DOBV43UPQ.wav"} +{"id": "h7ty6D1LunA", "caption": "The low quality recording features house music generated from a digital drum machine. It consists of boomy synth bass played over shimmering hi hats, snappy snare and punchy kick. It sounds groovy and a bit dull.", "audio": "/zhanghaomin/datas/musiccap/music_data/h7ty6D1LunA.wav"} +{"id": "h8JS_FEF_fY", "caption": "The song radiates the sound of late 2000s and early 2010s R&B. There are various synths and pads used, some of which are rhythmic and wobbly. The singer has a soulful voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/h8JS_FEF_fY.wav"} +{"id": "h9zF09TMgLU", "caption": "This song contains a drumbeat with a funky bassline. A male voice is singing in a higher range. in the background you can hear different voice samples and scratching. This song may be playing while cruising down the street in your car.", "audio": "/zhanghaomin/datas/musiccap/music_data/h9zF09TMgLU.wav"} +{"id": "hBQFoDI3NMI", "caption": "This music is an Electric Guitar instrumental. The tempo is fast with a dissonant background score . There is the sound of people talking in the background. The music is superimposed on a track which doesn\u2019t seem to be in sync. The lead however is powerful, loud, intense and emphatic. This is a Rock Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/hBQFoDI3NMI.wav"} +{"id": "hBT0bbJl1dU", "caption": "The low quality recording features a groovy piano melody, mellow cello melody and brass melody. It sounds emotional and passionate, while the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/hBT0bbJl1dU.wav"} +{"id": "hCELSy7hVKE", "caption": "The low quality recording features an arpeggiated theremin melody being played. The recording is noisy, in mono and it sounds weird and gives off some spacey vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/hCELSy7hVKE.wav"} +{"id": "hCIB1E60Nbw", "caption": "The Electro song features a punchy \"4 on the floor\" kick pattern, shimmering open hats, tinny wide minimal percussions, low groovy bass, simple electric guitar melody and reverberant snappy rimshots. It sounds dark, energetic, suspenseful and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/hCIB1E60Nbw.wav"} +{"id": "hDsA_ky9Hfw", "caption": "The song is an upbeat, soulful song which has a motif repeated on a woodwind instrument. The song would be suitable for some mellow dancing. The singer has a raspy voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/hDsA_ky9Hfw.wav"} +{"id": "hDzmNYd_eaA", "caption": "The low quality recording features a cover with a steel drums tropical melody that plays over the playback instrumental in the background that consists of groovy bass, claps, \"4 on the floor\" kick pattern, shimmering shakers and tinny percussive elements. It sounds tropical, exotic and groovy, but it also has an unbalanced stereo image.", "audio": "/zhanghaomin/datas/musiccap/music_data/hDzmNYd_eaA.wav"} +{"id": "hFj0KUzofNg", "caption": "This clip features a live recording of low quality. The song is mixed into a video clip. The sound of crowd cheering is heard. The song features a male voice using a vocoder. The song is in the techno genre. The percussion is programmed and plays a techno beat. The bass plays simple root notes of chords. Synth bursts are played at the beginning and at the end of the song. The referee whistle is heard toward the middle of the clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/hFj0KUzofNg.wav"} +{"id": "hFqZZrj0rnM", "caption": "The low quality recording features a live performance of shoe tapping over a jazz song that consists of passionate female vocal singing over smooth bass and groovy key chords. There are crowd clapping sounds in the background. The actual sounds of shoe tappings is widely spread in the stereo image and it is reverberant, as it was probably performed in a huge space.", "audio": "/zhanghaomin/datas/musiccap/music_data/hFqZZrj0rnM.wav"} +{"id": "hH6thMA3640", "caption": "This is a bluegrass music piece. The acoustic guitar follows an offbeat strumming pattern, providing a rhythmic background. The violin and the banjo take turns to play rapid, upbeat solos. The atmosphere is very lively. This piece could be used at a definitively American setting such as a rodeo venue.", "audio": "/zhanghaomin/datas/musiccap/music_data/hH6thMA3640.wav"} +{"id": "hHS5C0RKa8A", "caption": "The R&B song features a melancholic female vocal singing over mellow piano melody, electric guitar chords, synth lead melody, groovy bass, organ keys chords, shimmering hi hats, punchy snare and soft kick hits. It sounds emotional, passionate and heartfelt.", "audio": "/zhanghaomin/datas/musiccap/music_data/hHS5C0RKa8A.wav"} +{"id": "hHb0Eq1I7Fk", "caption": "This is a synth-pop piece played in the background of a skateboarding video. There is a male vocalist singing in an emotionally distant manner. There is a keyboard and an electric guitar playing the melody with the bass guitar playing a repetitive bass line in the background. The acoustic drums are playing a simple beat. Skateboarding sounds from the video can be heard very clearly. The recording has an urban atmosphere.", "audio": "/zhanghaomin/datas/musiccap/music_data/hHb0Eq1I7Fk.wav"} +{"id": "hHqrcLiKJRg", "caption": "This is the live performance of a bluegrass gospel music piece. There are male vocals synchronously harmony singing which is called a \"stack\" in bluegrass music. The melody is being played by the fiddle, the banjo, the acoustic guitar and the mandolin. There is a cozy atmosphere in this piece. It could be playing in the background of an American roadside diner. This piece could also be played at a Christian religious event.", "audio": "/zhanghaomin/datas/musiccap/music_data/hHqrcLiKJRg.wav"} +{"id": "hIEj8msjg8E", "caption": "This music is instrumental. The tempo is fast with a hypnotic harmony of the didgeridoo. The music is unique, catchy,engaging, mesmerising and hypnotic because of the continuous droning. This music is a Didgeridoo instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/hIEj8msjg8E.wav"} +{"id": "hKSg3zFB2dE", "caption": "The Rock song features a passionate male vocal, layered with harmonizing background male vocals, singing over electric rhythm guitar chords spread widely in the stereo image, thin snare, energetic crash, groovy bass, shimmering hi hats and punchy kick hits. The drums are very reverberant, which is probably the reason why they sound softer. It sounds addictive, thanks to those harmonizing vocals, and energetic overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/hKSg3zFB2dE.wav"} +{"id": "hLn4HokDEmM", "caption": "Audio from two songs of EDM music featuring four on the floor kick pattern, synthesized pan flute, syncopated synth chords sidechained to the kick, piano and hand percussion.", "audio": "/zhanghaomin/datas/musiccap/music_data/hLn4HokDEmM.wav"} +{"id": "hLwMYygjRfI", "caption": "This amateur recording features a guitar plucking chords. This is accompanied by percussion playing an outro beat. The recording is of low quality. The bass plays one note on the first count of each bar. There are no voices in the song. This song can be played in a highway scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/hLwMYygjRfI.wav"} +{"id": "hM88FG1_D5Q", "caption": "The low quality recording features harmonizing male vocals singing over a song played on playback, followed by a flat male vocal talking. At the end of the recording, there is a male laughter. It sounds fun and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/hM88FG1_D5Q.wav"} +{"id": "hNKTrKk4hZs", "caption": "This music is a grim instrumental. The tempo is slow with a Violin symphony. The deep bass of the cello to the accompaniment of a steady, droning violin melody and the sound of a ringing bell give it a very intense and serious vibe. The music is enthralling, powerful,impactful, intense, sinister, scary and anticipatory. This is an orchestral harmony.", "audio": "/zhanghaomin/datas/musiccap/music_data/hNKTrKk4hZs.wav"} +{"id": "hOSzGYKaJGE", "caption": "The low quality recording features a rock song that consists of an electric guitar melody, smooth bass, shimmering shakers, snappy rimshots and soft male vocals singing over it. The recording is really noisy and in mono. It sounds cool, groovy and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/hOSzGYKaJGE.wav"} +{"id": "hPIh5RYA-5M", "caption": "This music is instrumental. The tempo is fast with vigours, intense drumming, electronic sounds like shooting, blasts, boomy bass and Rapid clicking sound . The music is loud,boisterous, aggressive, insistent, intense and clamorous . This is video game music.", "audio": "/zhanghaomin/datas/musiccap/music_data/hPIh5RYA-5M.wav"} +{"id": "hQ5OBio4Cy0", "caption": "The low quality recording features a live performance of percussive elements, sitar guitar melody, sustained strings melody, groovy percussive elements and flute solo melody. The recording is noisy and it sounds compressed and loud.", "audio": "/zhanghaomin/datas/musiccap/music_data/hQ5OBio4Cy0.wav"} +{"id": "hRQJgZVxRX0", "caption": "This is the recording of a gear showcase. There is a male voice advertising an effect amp. The distorted electric guitar is playing a crunchy-sounding riff with the added effect of the chorus amp. The atmosphere is hard-hitting. Some parts of this recording could be used in heavy guitar samples for beat-making. Such parts could also work in sections of an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/hRQJgZVxRX0.wav"} +{"id": "hRbukCd6N68", "caption": "This is a chiptune piece. The only instrument being used in this track is a granular synth playing the melody at a medium-to-high pitch. It is an analog sounding piece. There is a nostalgic atmosphere to it. This piece could be used in the soundtracks of cartoons and arcade video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/hRbukCd6N68.wav"} +{"id": "hSK405L-DlQ", "caption": "The acoustic drums are playing a groove with crash hits and a bass that sounds distorted while a female voice is singing. Then a male singer with an effect on his voice is almost screaming while an e-guitar is playing a melody. This song may be playing in a rock&roll bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/hSK405L-DlQ.wav"} +{"id": "hSSzn4bIwZg", "caption": "The low quality recording features an orchestra playing arpeggiated harp melody, low sustained strings and mellow flute melody. It sounds mystical, mellow and calming. The recording is a bit noisy too.", "audio": "/zhanghaomin/datas/musiccap/music_data/hSSzn4bIwZg.wav"} +{"id": "hTAWbHXCJ2A", "caption": "This song contains a male voice singing in a higher pitch, a digital drum string playing a simple repeating melody. This song may be playing at home having a romantic time with your partner dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/hTAWbHXCJ2A.wav"} +{"id": "hTNKYJ6suII", "caption": "The low quality recording features a baby goat bleating sound effects and regional Mexican song, that consists of wide acoustic guitar chords, groovy piano melody, drum roll, bagpipe melody and groovy, playing in the background. It sounds fun and happy and it seems like it is some kind of animal related TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/hTNKYJ6suII.wav"} +{"id": "hTPxqUtlLdo", "caption": "Someone is playing a melody on a sitar along with a tabla providing rhythms. This song may be playing in a movie scene in the desert.", "audio": "/zhanghaomin/datas/musiccap/music_data/hTPxqUtlLdo.wav"} +{"id": "hTlIqICkbW8", "caption": "The low quality recording features an indie folk song that consists of wide harmonizing male vocals and acoustic rhythm guitar. In the second half of the loop, the lead female vocal appears, creating a perfect harmony with the previously mentioned male vocals. It sounds passionate, emotional and sad.", "audio": "/zhanghaomin/datas/musiccap/music_data/hTlIqICkbW8.wav"} +{"id": "hUcuXIvDN2E", "caption": "The low quality recording features a groovy bass guitar playing with guitar pedal chorus effect. In the first half of the loop, there is a modulated chorus effect, while in the second part, there is a classic chorus effect on.", "audio": "/zhanghaomin/datas/musiccap/music_data/hUcuXIvDN2E.wav"} +{"id": "hVPQu1UJ2N8", "caption": "The low quality recording features a traditional song that consists of wooden percussive elements, addictive accordion melody, smooth bass and some metallic buzzing sounds. Even though it is mono and noisy, it still sounds soulful and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/hVPQu1UJ2N8.wav"} +{"id": "hVVrl9FkKnY", "caption": "This is an instrumental rock music piece recording in the style of blues. There is an electric guitar playing a solo using the shredding technique. The backing track consists of a piano, a bass guitar and acoustic drums. There is a groovy feel to it. Parts of this recording could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/hVVrl9FkKnY.wav"} +{"id": "hVikKRODjbI", "caption": "This music is an animated instrumental. The tempo is fast with a playful trumpet harmony, trombone, synthesised sounds and sounds of glass shattering,punching and grunting. This music is a background score for an animated movie for kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/hVikKRODjbI.wav"} +{"id": "hWiAoE4u4y8", "caption": "This is an alternative metal music piece. There is a male vocal singing loudly initially with a cleaner character and then with a heavy vocal fry. The distorted electric guitar is playing a heavy riff with the bass guitar in the background. The rhythmic background consists of an aggressive acoustic drum metal beat. The atmosphere is rebellious and violent. This piece can be used in the soundtrack of an action video game or a thriller movie during scenes of a face-off or a combat.", "audio": "/zhanghaomin/datas/musiccap/music_data/hWiAoE4u4y8.wav"} +{"id": "hXLo1l5gS-I", "caption": "This is an instrumental harp cover of a heavy metal music piece. The atmosphere of the recording is lively. This piece could be used in the soundtrack of an arcade video game. It could also be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/hXLo1l5gS-I.wav"} +{"id": "hYlSisv-VRU", "caption": "A male vocalist sings this powerful pop. The tempo is medium fast with an emphatic and groovy bass line, lively trumpet harmony, piano accompaniment, electric guitar rhythm, tambourine beats and infectious drums. The song is lively,spirited, engaging, vivacious,passionate, compelling and ambient with powerful vocals . This Song is an R&B/Funk.", "audio": "/zhanghaomin/datas/musiccap/music_data/hYlSisv-VRU.wav"} +{"id": "hYy0na5oUzE", "caption": "This is a latin pop music piece with a salsa beat. There is a male vocalist singing melodically in the lead. The melody is being played by an orchestra composed of the trumpet, the piano and the bass guitar. The rhythmic background is provided by a mild acoustic drum beat with heavy use of latin percussive elements. The piece has a sensual atmosphere. This music could go well in a Latin American soap opera soundtrack where there is a hopeless situation for one of the characters.", "audio": "/zhanghaomin/datas/musiccap/music_data/hYy0na5oUzE.wav"} +{"id": "hZfCziBaGTI", "caption": "This music features a ukulele being played. Only one string is played for tuning. This clip can be used to tune the G string of the ukulele. There are no voices in this clip. There are no other instruments in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/hZfCziBaGTI.wav"} +{"id": "hbCaMcbT8to", "caption": "This is an acoustic cover of a rock music piece. There is an acoustic guitar playing a gentle melody. The piece has a slow tempo. The atmosphere is sentimental. This piece can be included in the soundtrack of a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/hbCaMcbT8to.wav"} +{"id": "hbqdthlv6CU", "caption": "This is a live recording of an italian song that is primarily played on the accordions. We have a male vocalist with a mature voice, who sings in a tone that feels a little bit sombre. The music itself has a romantic feeling to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/hbqdthlv6CU.wav"} +{"id": "hdlnugbWjKA", "caption": "A young female vocalist sings this upbeat country song. The tempo is fast with keyboard harmony,enthusiastic drumming , rhythmic accompaniment of acoustic guitar, mandolin, fiddle, resonator, auto harp and dobro and tambourine beats. The song is fresh, youthful, energetic, vivacious, catchy, upbeat, simple and peppy. This song is Country Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/hdlnugbWjKA.wav"} +{"id": "heZw1TTrtTU", "caption": "This clip is an instrumental with dissonant sounds like whirring, an engine starting, door bell or elevator bell , clattering and rustling. This is an amateur home recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/heZw1TTrtTU.wav"} +{"id": "hgGCfJoYDUU", "caption": "The song is an instrumental. The tempo is medium with a booming bass line, grooving drum rhythm, sweeping keyboard harmony, sonic sound effects, and pin pong ball sound effects. The song has trance vibes and is very groovy. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/hgGCfJoYDUU.wav"} +{"id": "hgJK2ZDgWtU", "caption": "This is the recording of a DJ performance. The DJ is performing on a turntable using the scratching technique. The beat in the background has a repeating male vocal sample and a groovy bass sound. The rhythmic background consists of an electronic drum beat. The atmosphere is urban. This piece could be used in the soundtrack of a teenage drama TV series that takes place in the ghettos of a big city.", "audio": "/zhanghaomin/datas/musiccap/music_data/hgJK2ZDgWtU.wav"} +{"id": "hgitRq_0410", "caption": "The low quality recording features a live performance that consists of an acoustic flamenco guitar melody. The recording is very noisy and buzzy, but you can still hear the passion and the emotion.", "audio": "/zhanghaomin/datas/musiccap/music_data/hgitRq_0410.wav"} +{"id": "hhU78ykPr5w", "caption": "The low quality recording features a house music that consists an echoing female scream and reverberant flat male vocal over repetitive percussive synth melody, wooden percussions, groovy bass, shimmering hi hats, reversed snare hits and punchy \"4 on the floor\" kick pattern. It sounds hypnotic, energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/hhU78ykPr5w.wav"} +{"id": "hhVFK9tYu84", "caption": "This is a live blues-rock performance. The saxophone is playing a solo section, and the electric guitar repeats an arpeggio. This song would be suitable in a blues bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/hhVFK9tYu84.wav"} +{"id": "hheF-AgCqIg", "caption": "Someone is strumming a melody on the mandolin. The audio-quality is very poor and you can hear a high frequency ringing in the recording. This song may be playing while practicing at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/hheF-AgCqIg.wav"} +{"id": "hhohfEC82JI", "caption": "A male singer sings this animated melody . The song is medium tempo with a groovy bass , keyboard accompaniment and steady drumming rhythm. The song is cheerful and animated and designed as educational material for little children.", "audio": "/zhanghaomin/datas/musiccap/music_data/hhohfEC82JI.wav"} +{"id": "hj7VJnNq6A4", "caption": "This song is a mixture of punk rock with acoustic drums with crash hits, e-guitar playing low notes along with the bassline, a male voice aggressively, loud screaming and digital higher pitched sample sounds being panned to the left and right side of the speakers. This song may be playing at a live concert in an underground club.", "audio": "/zhanghaomin/datas/musiccap/music_data/hj7VJnNq6A4.wav"} +{"id": "hjrl1KHEuqE", "caption": "This song contains digital drums playing a groove together with an e-bass. Different fast paced synth sounds are playing a rhythmic melody along to the drums. Violas are playing a countermelody to the male voices singing a melody creating a harmony. This song may be playing in a movie scene where someone is driving with a partner on a motorbike.", "audio": "/zhanghaomin/datas/musiccap/music_data/hjrl1KHEuqE.wav"} +{"id": "hk-1KRWTM-4", "caption": "Here we have a live recording of a performance by a female singer/songwriter. She plays simple chords with a simple rhythm on the guitar, while she sings with a vibrant and youthful voice. The song is a pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/hk-1KRWTM-4.wav"} +{"id": "hkWOAj09_dY", "caption": "This audio contains a string section playing a romantic ballad. Violin and viola are playing the lead melody while celli are playing a rhythmic melody in the background. This song may be playing live for a wedding.", "audio": "/zhanghaomin/datas/musiccap/music_data/hkWOAj09_dY.wav"} +{"id": "hkWcUtga1lw", "caption": "The song is an instrumental. The song is medium tempo with a violin playing a solo with a piano accompaniment. The song is emotional and positive. The song is a classic western hit and has poor audio quality in general.", "audio": "/zhanghaomin/datas/musiccap/music_data/hkWcUtga1lw.wav"} +{"id": "hlHb9HwNxk8", "caption": "The low quality recording features a live performance of an opera that consists of a passionate female vocal singing over strings melody, brass melody and mellow percussion. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/hlHb9HwNxk8.wav"} +{"id": "hlbjpc48Vrs", "caption": "The recording starts with a synth pad sound in the higher register and also with a tunes airy sounds slowly pitching down. Then a separate techno song starts playing with a monotone digital drum groove. The kick is overdriven and has some punch to it. The fast hihat sounds are panned to the left and right side of the speakers. This song may be playing in a night club.", "audio": "/zhanghaomin/datas/musiccap/music_data/hlbjpc48Vrs.wav"} +{"id": "hlquKjPgxmY", "caption": "This is a Christian pop piece. There is a telephone sound effect in the opening. There is a female vocalist singing melodically as the lead. The melody is being played on the acoustic guitar and the keyboard. The rhythm is provided by an electronic drum beat. There is a modern feel to this piece. It could be used in the background of social media content related to Christianity.", "audio": "/zhanghaomin/datas/musiccap/music_data/hlquKjPgxmY.wav"} +{"id": "hm0SeoNSGkc", "caption": "The low quality recording features a live performance of an arpeggiated acoustic guitar melody and plucked harp melody. It sounds mellow, soft, easygoing and the recording is really noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/hm0SeoNSGkc.wav"} +{"id": "hmkPWxTIwwU", "caption": "This music is an electronic instrumental. The tempo is fast with punchy drumming rhythm, keyboard harmony, vigorous guitar rhythm and electronically arranged sounds like a dissonant booming drum, water bubbling, hissing and whistle like instrument playing harmony. The song is youthful, energetic, enthusiastic, vigorous, vivacious and youthful with a dance groove. This music is EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/hmkPWxTIwwU.wav"} +{"id": "hnlVKC7rxdg", "caption": "This symphonic song features french horns playing in harmony. The notes played are descending and they finally fade away. There are no other instruments in this song. There are no voices in this song. This song can be played in a dream sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/hnlVKC7rxdg.wav"} +{"id": "hoPnrbKOEl8", "caption": "The instrumental music features a sort of calm before the storm. In the low register one can barely hear a double bass playing a long note softly. Another stringed instrument plays a short melody that fades out. A bigger group of strings then play a short long-note melody. The music is playing softly, almost quiet. This could work well as music for a movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/hoPnrbKOEl8.wav"} +{"id": "hpiFoinUgvY", "caption": "The Latin/African song features a flat, echoing male vocals singing over exotic percussive elements and groovy bass. It sounds easygoing and low quality as it is recorded in mono and the vocals are kind of distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/hpiFoinUgvY.wav"} +{"id": "hqCJarP-nVI", "caption": "This music is instrumental. The tempo is medium with a beautiful Harpsichord rendition. The music is a famous Western Classical composition by an Italian composer. The music is engaging, enthralling, rich, deep, passionate baroque music.", "audio": "/zhanghaomin/datas/musiccap/music_data/hqCJarP-nVI.wav"} +{"id": "hqQvatf1RUY", "caption": "A male voice is rapping in a higher pitch while having backing voices creating a harmony. There is some delay in his voice. A synth melody/arpeggio is playing in the middle range getting louder while a warm digital kick sound is holding the rhythm. A cymbal sound is coming in to make it clear that the song will break into the next part. This song may be playing in a music video.", "audio": "/zhanghaomin/datas/musiccap/music_data/hqQvatf1RUY.wav"} +{"id": "hrCf8rMBtA8", "caption": "The low quality recording features a pop song that consists of a passionate male vocal, alongside harmonizing vocals, singing over wide claps, layered with shimmering tambourine, groovy bass and straight piano melody. It sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/hrCf8rMBtA8.wav"} +{"id": "hrOP9swUpyA", "caption": "The low quality recording features an acoustic rhythm guitar and flat female vocal singing on top of it. There is a lot of reverb on vocals, which makes it sound too separate from the guitar. The guitar, in the second half of the loop, is played a bit sloppy.", "audio": "/zhanghaomin/datas/musiccap/music_data/hrOP9swUpyA.wav"} +{"id": "hu5pjj1KzK8", "caption": "The low quality recording features an echoing theremin melody, slowly fading out, over growly synth bass. It sounds suspenseful and haunting - like something you would hear in horror movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/hu5pjj1KzK8.wav"} +{"id": "hu6sChY-Yps", "caption": "The low quality recording features a DJ scratching the vinyl of a hip hop song that consists of punchy kick and snare, repetitive wooden percussive elements, shimmering hi hats and open hats and soft crash cymbals. It sounds manic, energetic and kind of muffled, since it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/hu6sChY-Yps.wav"} +{"id": "hvmCuosF0Xo", "caption": "This track is characterised by a leading melody that is played on an instrument which sounds like it would be suitable in a video game like Super Mario Brothers. Behind this instrument, there is a grungy, fuzzy and dirty electric guitar being played. The drummer plays a simple beat to allow the melody to shine. The song has an energizing feel to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/hvmCuosF0Xo.wav"} +{"id": "hwSOjoHFLn4", "caption": "This is a post-grunge/pop punk music piece. There is a male vocalist singing melodically in the lead. The main melody is being played by the electric guitar in the major key with the bass guitar backing it. The rhythmic background consists of an acoustic drum beat. The atmosphere is energetic and cheerful. This piece could be used in the soundtrack of a comedy TV series as the opening theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/hwSOjoHFLn4.wav"} +{"id": "hwe6y-jSqdQ", "caption": "The low quality recording features a compilation of rock songs in-between which there is a flat male vocal talking. At the very beginning there is a short snippet of a groovy piano melody and fruity male vocal singing over it. After that, there is an even shorter snippet of a song that consists of acoustic rhythm guitar and a male vocalist singing over it. And at the end of the loop, there is a fade in into a flat male vocal singing with background vocals over punchy kick, punchy snare, shimmering cymbals, distorted bass guitar and electric guitar melody. Overall it sounds weird and chaotic, due to the arrangement of the sounds, but it is also energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/hwe6y-jSqdQ.wav"} +{"id": "hwp7wCKIXg4", "caption": "The low quality recording features a reverberant groovy piano melody. It sounds like a cover and it is energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/hwp7wCKIXg4.wav"} +{"id": "hyGuS5WiPk8", "caption": "This composition contains percussion and percussive hits taking the main focus. A string section is playing a short melody along with flutes/oboes. This song sounds cinematic and may be playing in a dangerous movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/hyGuS5WiPk8.wav"} +{"id": "hzr2aY33EuI", "caption": "This is an instrumental rock and roll music piece. An overdriven electric guitar is playing the melody while a bass guitar is playing the background. There is a basic rock drum beat keeping the rhythmic structure. There is a groovy, easygoing atmosphere. This music could be played in the background at a rock bar or a sports venue.", "audio": "/zhanghaomin/datas/musiccap/music_data/hzr2aY33EuI.wav"} +{"id": "hzznbzry5R8", "caption": "The song is an instrumental. The song is medium tempo, with an acoustic guitar playing blues, strong drumming rhythm, walking bass line and keyboard harmony. The song is exciting and has a dance rhythm. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/hzznbzry5R8.wav"} +{"id": "i3zayf6Hiog", "caption": "Classical music features a full orchestra playing beautiful sustained strings melody, arpeggiated brass melodies, shimmering bells, pumping drums and energetic cymbals. It sounds like a background movie soundtrack - mystical, epic, uplifting and suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/i3zayf6Hiog.wav"} +{"id": "i6WtNBpRll0", "caption": "A male rapper sings this emotional melody. The song is medium tempo with a steady techno drumming rhythm, strong bass line, various percussion hits, piano playing accompaniment and synth horns playing countermelody. The song is emotional and storytelling in nature. The song is a modern hip hop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/i6WtNBpRll0.wav"} +{"id": "i6dFcfV64RE", "caption": "The low quality recording features a live performance of a classical cover of a rock song that consists of a cello strings melody playing.The recording is noisy, slightly distorted and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/i6dFcfV64RE.wav"} +{"id": "i6k1yiyO5jQ", "caption": "The romantic music features a male voice singing a melody. An acoustic guitar accompanies the singer by playing chords. The drums play a light rhythm. Other percussion instruments such as triangles can be heard.", "audio": "/zhanghaomin/datas/musiccap/music_data/i6k1yiyO5jQ.wav"} +{"id": "i70a79YhlMk", "caption": "This is the live performance of a Mexican folk music piece. In the beginning, there is a female voice giving an introductory speech in the Spanish language. Then, the arpa jarocha (which is a Mexican harp) and the ukulele start playing a lively and relaxed tune. The atmosphere is vibrant. This piece could be used in the soundtrack of a Mexican soap opera during scenes of calmer temperament.", "audio": "/zhanghaomin/datas/musiccap/music_data/i70a79YhlMk.wav"} +{"id": "i8PFu7AiwaE", "caption": "The low quality recording features a 6/8 conga percussion rhythm. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/i8PFu7AiwaE.wav"} +{"id": "i8bt6Mb0rUc", "caption": "The low quality recording features a huge orchestra playing drums alongside a tiny percussive element in the first half of the loop. In the second half, drums are played at half time. It sounds groovy, percussive, suspenseful and intense - like a background soundtrack for an action movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/i8bt6Mb0rUc.wav"} +{"id": "iBH5X5SKirU", "caption": "This jazz song features a guitar solo. This is accompanied by percussion playing a simple beat. An acoustic guitar strums chords on each count of the bar. The bass plays the root notes of the chords. There are no voices in this song. The song has a happy mood. This song can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/iBH5X5SKirU.wav"} +{"id": "iBezxlI_f_c", "caption": "The music features a female voice singing a melody in an unusual way. She's being accompanied by a usual setup: drums, bass guitar, electric guitar. The drummer relies more on the hi-hat and less on the other parts of the drum kit. The electric guitar strums chords.", "audio": "/zhanghaomin/datas/musiccap/music_data/iBezxlI_f_c.wav"} +{"id": "iBh37YAaHMU", "caption": "This audio contains a complex and funky acoustic drum groove along with a repeating bassline. The clean e-guitar is playing along with the bass in the lower register. A tambourine adds flavor to the drums. This song may be playing at a breakdance battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/iBh37YAaHMU.wav"} +{"id": "iCHskFoUvbw", "caption": "The low quality recording features a live performance of a rock song that features wide electric guitar chords, distorted bass, reverberant toms, punchy kick hits and energetic crash cymbals. There are a few electric guitar slides. The recording is very noisy and it sounds energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/iCHskFoUvbw.wav"} +{"id": "iCIa_pmLDqs", "caption": "The low quality recording features a cover of a ragtime song and it consists of arpeggiated acoustic guitar melody. The recording is noisy, but it sounds happy and fun regardless.", "audio": "/zhanghaomin/datas/musiccap/music_data/iCIa_pmLDqs.wav"} +{"id": "iDvva_WCo-I", "caption": "The low quality recording features a didgeridoo melody played on top of shimmering shakers, plucked strings melody and low percussive hits. It sounds groovy, passionate and on an average ear, weird.", "audio": "/zhanghaomin/datas/musiccap/music_data/iDvva_WCo-I.wav"} +{"id": "iEMTTKA7NxU", "caption": "The low quality recording features a ballad song sung by passionate female vocalists over groovy, mellow piano chords and shimmering shakers and tambourine. It sounds emotional and heartfelt - like something you would sing to your partner, out of love.", "audio": "/zhanghaomin/datas/musiccap/music_data/iEMTTKA7NxU.wav"} +{"id": "iEQwupwwp0s", "caption": "This song is a Retro Hindi movie song. The tempo is fast with rhythmic guitar, vigorous guitar, keyboard harmony, congas and bongos. The music is minimalistic and simple with speech like singing. The song is playful, cheerful, upbeat, youthful and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/iEQwupwwp0s.wav"} +{"id": "iEcWlreXhGc", "caption": "This is the type of horn that would be heard in a distant battlecry. The clip features just this war horn sitting on top of a deep, low ringing and sustained bass. There is reverb applied to the sound of the horn.", "audio": "/zhanghaomin/datas/musiccap/music_data/iEcWlreXhGc.wav"} +{"id": "iFSaNmZyPQo", "caption": "This pop rock song features a female voice singing the main melody. The song starts off with the sound of folding paper. Then the voice starts singing. This is accompanied by rock drums playing the kick drum. The snare is struck at every alternate count. The reverb effect is added to the percussion. There are no other instruments in this song. This song has a happy mood. This song can be played in an intro scene of a coming-of-age movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/iFSaNmZyPQo.wav"} +{"id": "iFWtsT5zRKo", "caption": "The low quality recording features a rock song that consists of harmonizing male vocals singing over groovy piano melody, groovy bass guitar, electric guitar melody, punchy snare, soft kick hits and shimmering hi-hats. There is a short snare roll that serves as a transition into a new section. It sounds groovy and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/iFWtsT5zRKo.wav"} +{"id": "iHXUaVWi7kE", "caption": "This audio contains a very high pitched sound played with a synthesizer. Then another synthesizer sound that sounds a little bit like cleaning a window. This song may be playing at home experimenting sounds with a synthesizer.", "audio": "/zhanghaomin/datas/musiccap/music_data/iHXUaVWi7kE.wav"} +{"id": "iHYOaGNdweo", "caption": "The low quality recording features an electro song played on a small device that reproduces thin, mono sounds, especially since it was recorded with a phone. The song consists of a repetitive synth melody, flat male vocal, \"4 on the floor\" kick pattern, claps and shimmering shakers. There are some papery sound effects too. Overall it is noisy and it sounds fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/iHYOaGNdweo.wav"} +{"id": "iLIBaMceZQc", "caption": "This is a classical music piece that is being performed live by a philharmonic orchestra. There is a wide array of instruments in the brass and the strings sections playing an epic tune. There is a grandiose atmosphere to this piece. It could be used in the soundtrack of an adventure movie where the protagonist begins his odyssey and explores wonderful scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/iLIBaMceZQc.wav"} +{"id": "iMTHDuW_xKc", "caption": "The low quality recording features an indie song that consists of a mellow piano melody, punchy kick and snare hits, wide toms and shimmering hi-hats. As the kick is leaning to the left and the snare to the right - it makes the stereo image unbalanced. Overall it sounds groovy, suspenseful and reverberant.", "audio": "/zhanghaomin/datas/musiccap/music_data/iMTHDuW_xKc.wav"} +{"id": "iMmYVLSb1IY", "caption": "This instrumental song features a piano melody playing at an odd time signature. After two bars, the piano melody shifts by one semi-tone. This is accompanied by the sound of hissing and crying voices. There are ghostly sounds being played in the background. The theme of this song is scary. This song can be used in a horror movie. A sound like that of a fast clock is played in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/iMmYVLSb1IY.wav"} +{"id": "iP46w2o_HCk", "caption": "This song contains acoustic drums playing a simple rhythm along with an e-bass. The same rhythmic pattern gets played by an acoustic guitar and e-guitar strumming chords. In the background female voices are happily screaming to the sound of waves. This song may be playing for an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/iP46w2o_HCk.wav"} +{"id": "iQ7qeIrssds", "caption": "This clip features a guitar being tuned. The first note played is the open note on the D string. Then the third string, G, is plucked three times. There are no other instruments in this clip. This is a low quality recording and sounds of birds can be faintly heard in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/iQ7qeIrssds.wav"} +{"id": "iQAXwX28LLw", "caption": "This is the intro part of a hip-hop beat. There is a rising pattern coming from a synth bass that has its low-pass filter getting dragged to higher frequencies. There is a hype feel to it. This part of the beat can be sampled and looped to be used in the soundtrack of a video game when the main character is simply walking around or exploring the area.", "audio": "/zhanghaomin/datas/musiccap/music_data/iQAXwX28LLw.wav"} +{"id": "iQJvAXOohoU", "caption": "This song would be suitable as the soundtrack to a coming of age movie. It is an alternative rock/indie rock song which features a crunchy electric guitar progression as its main basis. There's a high pitched, sustained beeping tone in the background which almost sounds like it is part of an organ.", "audio": "/zhanghaomin/datas/musiccap/music_data/iQJvAXOohoU.wav"} +{"id": "iQfPmJ19ZUc", "caption": "This is a song from a game. It features the main melody being played by a wind instrument. Stringed instruments play staccato notes in the background. The sound of a person running can be heard. The sound of running water is playing. A door is being opened and a squeaky sound is heard when the door is closed. There is no percussion in this song and no voices. The bass notes are loud and unclear. The quality of this recording is low. This is an instrumental song.", "audio": "/zhanghaomin/datas/musiccap/music_data/iQfPmJ19ZUc.wav"} +{"id": "iS-iTbHndw8", "caption": "A female singer sings this passionate melody with backup singers in vocal harmony. The tempo is medium and gradually slows down towards the end. The drumming rhythm is steady and retards to the end with a percussive bass line and keyboard accompaniment. The song is a retro disco or R&B love song. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/iS-iTbHndw8.wav"} +{"id": "iS8YQGp2_ng", "caption": "This is a comedic electronic remix. It is a commercial that was transformed into a hip-hop beat. The male voice narrating in the original video was put through an autotune effect to give the impression that he is rapping the words. There is a keyboard and a synth bass in the melodic background while an electronic drum beat provides the rhythmic background. The atmosphere in this piece is amusing. The tempo of the piece is slightly fast-paced.", "audio": "/zhanghaomin/datas/musiccap/music_data/iS8YQGp2_ng.wav"} +{"id": "iSETDHfErjU", "caption": "This song contains digital drums playing along with a funky synth bassline. Other synth sounds are playing pads and a lead melody. This song sounds like it was made for dancing. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/iSETDHfErjU.wav"} +{"id": "iSw-5EjXgXc", "caption": "This file contains a guitar tuner playing every single string repeating it for a while before jumping to the next one. This tune may be playing at home tuning your guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/iSw-5EjXgXc.wav"} +{"id": "iTV3Otwq_dI", "caption": "Someone is scratching along to a hip hop style backing song containing digital drums and a synth arpeggio sound playing in the midrange. Two male voices are speaking. This song may be playing while practicing scratching.", "audio": "/zhanghaomin/datas/musiccap/music_data/iTV3Otwq_dI.wav"} +{"id": "iTWZsfVCyBs", "caption": "The low quality recording features a breathy reverberant flute melody played over a low sustained piano bass note in the background. It sounds mystical, calming and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/iTWZsfVCyBs.wav"} +{"id": "iUHqyjf3NcQ", "caption": "The low quality recording features a live performance that consists of a Spanish guitar solo melody, groovy double bass and acoustic rhythm guitar chords. The recording is noisy, in mono and it sounds passionate and uptempo - like something you would dance to with your friends in a latin club.", "audio": "/zhanghaomin/datas/musiccap/music_data/iUHqyjf3NcQ.wav"} +{"id": "iUxy2s5d60o", "caption": "A saxophonist plays a phrase on the alto sax and explains the movement. The song is medium tempo with no other instrumentation. The audio quality is poor and serves as an online music tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/iUxy2s5d60o.wav"} +{"id": "iVBNoH6XgW4", "caption": "The two main elements in this clip are a futuristic sounding synth arpeggio melody being repeated. There's a laser gun sound effect being fired off repeatedly. There's also a low droning synth sound that's sustained throughout the clip. This clip could feature in a spacey video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/iVBNoH6XgW4.wav"} +{"id": "iX53Jb72Nwk", "caption": "These are sound effects taken from a movie trailer. There is a container door closing in the beginning. Then a monster can be heard roaring loudly. Numerous other effects were used to create an ominous feeling. The atmosphere is horrifying. Samples from this track can be lifted to be used in beat-making. These samples could also be used in horror movies or video games.", "audio": "/zhanghaomin/datas/musiccap/music_data/iX53Jb72Nwk.wav"} +{"id": "iX_a2Ct0ya8", "caption": "This is an acapella performance with a beautiful male pop vocal that has a combination of airy and raspy qualities. The song would fit in the pop genre. The clip features non-verbal ad libs such as grunts and other vocal exclamations.", "audio": "/zhanghaomin/datas/musiccap/music_data/iX_a2Ct0ya8.wav"} +{"id": "iXgEQj1Fs7g", "caption": "This is a low quality recording. This features a middle-eastern song played on an oud. This is accompanied by middle-eastern percussion instruments. A female voice starts to sing at the end of the clip. This song can be played in a middle-eastern souk scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/iXgEQj1Fs7g.wav"} +{"id": "iYWvaxU5OXk", "caption": "This clip features a cello playing the melody. The sound of this cello ranges from mid range to bass pitch. There are no other instruments. There are no voices in this clip. This is an instrumental song. This song can be played in a detective theme movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/iYWvaxU5OXk.wav"} +{"id": "iZjIuV_cTe8", "caption": "This folk song features a reed instrument playing the main melody. A similar melody is played on a percussion instrument by a skilled percussionist. Another percussion instrument plays a tabla-sounding instrument. Cymbals also play a melody keeping time with the melody being played. The end of the song features an ascending run on the reed and the harmonized percussion.", "audio": "/zhanghaomin/datas/musiccap/music_data/iZjIuV_cTe8.wav"} +{"id": "i_G_0vgEYJg", "caption": "A female vocalist sings this lilting melody. The tempo is slow with the vocalist yodelling to the accompaniment of a violin symphony and brass band . The cello and plucking of violin strings adds a dense bass layer and the subtle flutes and trumpets harmony compliment the vocals. The effect is ethereal, celestial, enthralling, enigmatic, melodic and beautiful.", "audio": "/zhanghaomin/datas/musiccap/music_data/i_G_0vgEYJg.wav"} +{"id": "i_NNY_mgxIs", "caption": "This song contains a digital drums playing a four on the floor groove with a big kick sound on every beat. A e-guitar is strumming rhythmic funky chords. Towards the end you can hear a synth string playing in a high register. This song may be playing for a advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/i_NNY_mgxIs.wav"} +{"id": "i_d4JFg-zT0", "caption": "This is a Finnish pop piece. There is a male vocalist singing melodically in the Finnish language. In the background, a clean guitar and a groovy bass guitar can be heard playing the theme with the accompaniment of a keyboard. An 80s disco type beat is being played by the acoustic drums in the rhythmic background. There is a danceable aura to it. This piece could be used in the soundtrack of teenage dramas taking place in Finland. It could also be used in retro-themed disco party playlists.", "audio": "/zhanghaomin/datas/musiccap/music_data/i_d4JFg-zT0.wav"} +{"id": "ia6-da2KdI0", "caption": "The low quality recording features an electro song playing in the background, while there is a muffled male vocal being interviewed. It sounds muffled and loud. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ia6-da2KdI0.wav"} +{"id": "iaDrtIon6FU", "caption": "This song is a male vocal harmony. The tempo is medium with banjo and guitar accompaniment. The song is merry, naughty, suggestive and harmless fun with the sound of stifled laughter in the background and with the expletives drowned with the sound of a beep. This song is Country pop/Country Folk.", "audio": "/zhanghaomin/datas/musiccap/music_data/iaDrtIon6FU.wav"} +{"id": "iaRDUksPv50", "caption": "This music is an electronic instrumental. The tempo is medium with an intense electronic boom and sound of something collapsing or tumbling. The clip starts with the angry voice of a child talking in a foreign language.", "audio": "/zhanghaomin/datas/musiccap/music_data/iaRDUksPv50.wav"} +{"id": "iaonijK95qA", "caption": "The song is an instrumental. The tempo is slow with a synth trumpet playing a lilting melody with supporting keyboard synth accompaniment and no percussion. The song is emotional and powerful. The song is a movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/iaonijK95qA.wav"} +{"id": "ib8pMT_ug7o", "caption": "The low quality recording features an electric guitar melody. It sounds mellow, chill and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/ib8pMT_ug7o.wav"} +{"id": "icomsHXY8YA", "caption": "The low quality recording features a reggae song sung by emotional male vocalists, followed by percussive elements, groovy bass, offbeat electric guitar and organ chords. There are some crowd noises in the background. The audio is crackling, making it low quality, but regardless it sounds easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/icomsHXY8YA.wav"} +{"id": "id5ibIqjRto", "caption": "A female vocalist sings this spirited pop song. The tempo is fast with vigorous drumming, animated electric guitar harmony, keyboard accompaniment and groovy bass lines along with backup vocals. The first bit of the song is sung in foreign language. The song is energetic, youthful, passionate, vibrant and vivacious with a dance groove. This song is Teen Pop/Pop Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/id5ibIqjRto.wav"} +{"id": "idUZsNLnyDg", "caption": "Someone is playing a e-guitar melody and strumming chords using a lot of reverb and delay over a drum backing track. This is an amateur recording. This song may be playing at home practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/idUZsNLnyDg.wav"} +{"id": "idVCpQaByc4", "caption": "This progressive rock song features male voices singing the chords of the song. This is followed by a male voice singing the main melody. The remaining male voices sing backing voices which are the arpeggiated chords of the song. A shaker is played at the beginning of the song. There are no other instruments. This song is at a moderate tempo. This is an amateur recording. The sounds of the crowd clapping and cheering are also heard in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/idVCpQaByc4.wav"} +{"id": "ieEPKa3HiGo", "caption": "The low quality recording features a tutorial where a flat male vocalist is talking, after which he plays an arpeggiated acoustic guitar melody. The recording is extremely noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ieEPKa3HiGo.wav"} +{"id": "iePMcLYozYY", "caption": "The low quality recording features a buzzy bass guitar playing. It sounds passionate, even though the recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/iePMcLYozYY.wav"} +{"id": "ihCl2ImrOYE", "caption": "This music is instrumental. The tempo is slow with the resounding vibrations of the cello , flute or recorder melody with a female voice talking about Spinal treatment . The music is soft, soothing, meditative,hypnotic, calming, droning, recurring and insistent. This clip is a documentary or tutorial on spinal treatment superimposed on the instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/ihCl2ImrOYE.wav"} +{"id": "ihJT65fZaHY", "caption": "This is a gear review jam video. There is a male voice describing the tone that he achieves from using an amp with the electric guitar. The said amp applies an echo effect to the electric guitar, making it sound more dreamy. The performer is playing a simple tune. This piece could be sampled for use in an advertisement jingle or in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/ihJT65fZaHY.wav"} +{"id": "ik-fXNjxw58", "caption": "The low quality recording features a reverberant snare roll, followed by wide low toms hits. At the very end of the loop, there is a short snippet of breathy flute melody. It sounds intense and suspenseful.", "audio": "/zhanghaomin/datas/musiccap/music_data/ik-fXNjxw58.wav"} +{"id": "ikEuQPSBY-0", "caption": "This song contains a piano playing a minor chord progression. In the background you can hear a synth lead pad playing kind of an easy arpeggio melody. Panned to the right side of the speakers you can hear strings playing a melody in the midrange. A male voice is singing in the midrange breaking his voice into headvoice. This song may be playing on loud speakers when alone at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/ikEuQPSBY-0.wav"} +{"id": "ikJKSqnTylI", "caption": "Someone is playing a classical piece on the acoustic piano while someone is playing/singing along with a kazoo. This song may be playing in a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/ikJKSqnTylI.wav"} +{"id": "imIFtW4O5S0", "caption": "This song contains someone playing a blues melody on the acoustic piano along with an e-guitar and an e-bass. The acoustic drums are playing a constant rhythm while male deep voice is backed by higher sounding male voices singing harmonies along with him. Then a male voice starts talking that seems not to be part of the musical composition. This song may be playing in a cafe.", "audio": "/zhanghaomin/datas/musiccap/music_data/imIFtW4O5S0.wav"} +{"id": "iqEQBCrOLWc", "caption": "This folk rock song features two male voices singing in harmony. This is accompanied by a guitar playing a fingerpicking pattern. The bass plays the root notes of the chords. There is no percussion in this song. The voices are calming and the song is relaxing to listen to. The voice sings in a story-telling mood. This song can be played in a coming of age movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/iqEQBCrOLWc.wav"} +{"id": "iqOPJWWKo90", "caption": "The low quality recording features a lullaby sung by passionate male vocalists over an arpeggiated acoustic guitar melody. It sounds mellow, soft, sad and so emotional that you forget about how noisy the recording actually is.", "audio": "/zhanghaomin/datas/musiccap/music_data/iqOPJWWKo90.wav"} +{"id": "itT0_RhSipQ", "caption": "The soundtrack is mysterious and builds anticipation. The tempo is medium with male actors vocalising a monologue, along with a terse string section harmony. The soundtrack builds anticipation and fear. The audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/itT0_RhSipQ.wav"} +{"id": "itgeNVRhBKs", "caption": "This music is a lively instrumental. The tempo is fast with an animated trumpet harmony, infectious drumming, groovy bass lines and synthesiser arrangement. The Brass lead, harmony and flourish is the main layer of this instrumental . The music is youthful, buoyant, fresh, cheerful, happy and energetic. This instrumental is an Urban Blues.", "audio": "/zhanghaomin/datas/musiccap/music_data/itgeNVRhBKs.wav"} +{"id": "iuNpXisjsLY", "caption": "The acoustic drums sound thick and played with deep tom hits. The electric bass is running through some effect, maybe an overdrive light distortion.The female voice is singing with some delay on her voice. This song may be playing in a bar downtown.", "audio": "/zhanghaomin/datas/musiccap/music_data/iuNpXisjsLY.wav"} +{"id": "ivymRS3iEZk", "caption": "The low quality recording features a sustained didgeridoo melody being played. It sounds low, suspenseful and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ivymRS3iEZk.wav"} +{"id": "izVCz3P43p8", "caption": "The low quality recording features a passionate electric guitar solo melody being played. It is a bit reverberant too.", "audio": "/zhanghaomin/datas/musiccap/music_data/izVCz3P43p8.wav"} +{"id": "j-93krRXAaY", "caption": "This instrumental music is relaxing. It features a slow melody played on a harp. A flute continues to play a melody with the harp playing in the background. A male voice talks in the end in a narrative tone. This music can be played in a dream sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/j-93krRXAaY.wav"} +{"id": "j-TVVmVmygg", "caption": "The low quality recording features an arpeggiated acoustic guitar melody and some cars passing by sounds in the background. It sounds heartfelt, emotional and sad. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/j-TVVmVmygg.wav"} +{"id": "j0FynYzQvcM", "caption": "This music clip is an instrumental. The tempo is slow with a violin playing sharp ,sudden notes. The scale change is random with no harmony or melody. This music sounds like a violin being tuned.", "audio": "/zhanghaomin/datas/musiccap/music_data/j0FynYzQvcM.wav"} +{"id": "j0UMI2DrnMA", "caption": "This song contains an upright bass playing a simple bassline along with an acoustic guitar strumming chords and a mandolin playing a fast paced melody. A violin is ending the phrase in the mid range. Then male and female voices are singing with the female voice being the lead voice. In the background you can hear the crowd laughing. This song may be playing as a local concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/j0UMI2DrnMA.wav"} +{"id": "j3a60_lwWjE", "caption": "someone is playing a didgeridoo beatboxing at the same time. Changing up rhythms sounding complex and skillfull. This is an amateur recording. This song may be playing in a talent show.", "audio": "/zhanghaomin/datas/musiccap/music_data/j3a60_lwWjE.wav"} +{"id": "j3lH_Tevw5o", "caption": "A male ukulele player plays this emotional solo. The song is medium tempo with no other instrumentation than an ukulele playing. The song is emotional and poignant. The song is an instrumental tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/j3lH_Tevw5o.wav"} +{"id": "j43Dwqzd8w8", "caption": "This beat contains a bassline that stands out also serving as melody. A rather complex digital drum is played along with male and female short vocal samples. A little tabla samples spices up the rhythm section along with a synthesizer hit. This instrumental is full of rhythmic elements. This song may be playing at home practicing rapping.", "audio": "/zhanghaomin/datas/musiccap/music_data/j43Dwqzd8w8.wav"} +{"id": "j4A1ObGurUk", "caption": "This clip is an amateur attempt at beatboxing. The tempo is medium and the beat is Catchy but it is a failed attempt at imitating digital drums. There is a female voice speaking in foreign language.", "audio": "/zhanghaomin/datas/musiccap/music_data/j4A1ObGurUk.wav"} +{"id": "j5R0hwX27Gk", "caption": "The low quality recording features a breathy flute melody, violin melody and arpeggiated harp melody. It sounds joyful, emotional and passionate. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/j5R0hwX27Gk.wav"} +{"id": "j6O_U9EseKQ", "caption": "The low quality recording features aggressive metallic and wooden percussion played chaotically. The recording is noisy, loud and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/j6O_U9EseKQ.wav"} +{"id": "j7AxC1RpjcE", "caption": "The low quality recording features a tinny mellow rubber impact over a muffled song played on playback in the background. It sounds messy and the recording is very noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/j7AxC1RpjcE.wav"} +{"id": "j8FYy5YfK7k", "caption": "This is a soul/R&B music piece. There is a trio of two male vocalists and a female vocalist singing melodically. The keyboard is holding the chords in the background while the electric guitar and the bass guitar are playing a groovy tune. The rhythmic background contains an electronic drum beat. The atmosphere is urban. The piece could be played during a retro-themed party at a nightclub.", "audio": "/zhanghaomin/datas/musiccap/music_data/j8FYy5YfK7k.wav"} +{"id": "j8z9a9A8LV4", "caption": "A male voice speaks in a menacing voice over a pop song in the background. The song is fast tempo with synthesiser articulation , digital arrangements and electronic sounds with subtle male vocals. The music is upbeat, energetic, enthusiastic, youthful, chilling, vibrating, exciting and pulsating. This song is a hit by Dance Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/j8z9a9A8LV4.wav"} +{"id": "j9UZv0GOJ_I", "caption": "This is a traditional Korean song featuring a motif played on a stringed instrument known as a gayageum. The percussion is simple and traditional.", "audio": "/zhanghaomin/datas/musiccap/music_data/j9UZv0GOJ_I.wav"} +{"id": "j9hAUlz5kQs", "caption": "Distorted, low fidelity house music live recorded from a nightclub featuring a boomy, blown out bass, male vocal sample and a woman shouting. Poorly recorded music for a boozy night out.", "audio": "/zhanghaomin/datas/musiccap/music_data/j9hAUlz5kQs.wav"} +{"id": "jBmP7xTI_TA", "caption": "This audio contains someone playing a modern piece of music on an acoustic piano. This song may be playing live in a bar with a piano.", "audio": "/zhanghaomin/datas/musiccap/music_data/jBmP7xTI_TA.wav"} +{"id": "jD0nqkyuHPg", "caption": "The low quality recording features a hip hop song that consists of a mellow arpeggiated piano melody played over sustained strings melody, chime bell and filtered male vocal in the first half of the loop. In the second half the beat drops and it consists of a punchy kick and snare hits, shimmering hi hats and passionate female vocals singing over. It sounds passionate, groovy and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/jD0nqkyuHPg.wav"} +{"id": "jFek2xLbEww", "caption": "A male singer raises this passionate melody. The song is medium tempo with an acoustic guitar accompaniment, groovy bass line and a subtle drumming rhythm. The song is passionate and relaxing. The song is played live and has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/jFek2xLbEww.wav"} +{"id": "jHEBYrI8zHE", "caption": "This is a Greek folk music piece. There is a male vocalist singing melodically and with a lot of articulation. The clarinet is playing the main theme while there is an electric guitar playing a backing tune. The rhythmic background consists of a percussion line that sounds very much like the toubeleki. There is a vibrant atmosphere. This piece could be playing in the background at a Greek cuisine restaurant or a Greek tavern.", "audio": "/zhanghaomin/datas/musiccap/music_data/jHEBYrI8zHE.wav"} +{"id": "jIoDR_eskaU", "caption": "This low quality audio features a male voice singing the main melody. This is accompanied by percussion playing a simple but fast paced beat. Trumpets are featured in this song playing fills at high pitch. This song can be played in an aerobics workout session where fast movements are required.", "audio": "/zhanghaomin/datas/musiccap/music_data/jIoDR_eskaU.wav"} +{"id": "jKWl63gozLE", "caption": "A female vocalist sings this pop song in a foreign language. The tempo is medium with karaoke music and vocal backup. The audio quality is inferior and the music is incoherent except for a violin harmony and piano accompaniment. This song is an amateur home video.", "audio": "/zhanghaomin/datas/musiccap/music_data/jKWl63gozLE.wav"} +{"id": "jKjj66pRXZA", "caption": "This clip features aboriginal music. This music is produced through a didgeridoo. There is no percussion in this song. There are no voices singing this song. This song can be played in a movie scene where people are navigating the tribal areas of an uninhabited island.", "audio": "/zhanghaomin/datas/musiccap/music_data/jKjj66pRXZA.wav"} +{"id": "jOkHEMsCCFc", "caption": "Someone is playing a shofar in a very high pitch using rhythmic techniques. There is some reverb of the room in the recording. This song may be playing while enjoying your instrument at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/jOkHEMsCCFc.wav"} +{"id": "jP4M9V_Ka8k", "caption": "The low quality recording features a big band song that consists of an addictive trumpet melody, simple woodwind melody, groovy trombone and muffled drums that include snare and crash hits. Overall it sounds dull and muffled, but still happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/jP4M9V_Ka8k.wav"} +{"id": "jPBg5cR8XeA", "caption": "This music is instrumental. The tempo is fast with a loud, lively keyboard , hard hitting drums and electric guitar melody. The audio is muffled so it is hard to hear the other instruments. This performance is live with ambient sounds of audience cheering, clapping and singing along. This music is a Christmas Carol instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/jPBg5cR8XeA.wav"} +{"id": "jPOWgfA0zAo", "caption": "The low quality recording features a passionate male vocal, alongside passionate female vocal in the left channel of the stereo image, singing over shimmering hi hats, which are also in the left channel, widely spread funky electric guitar chords, synth keys melody in the right channel, groovy bass, wooden percussions and mellow rimshots. It sounds happy, joyful, easygoing and chill.", "audio": "/zhanghaomin/datas/musiccap/music_data/jPOWgfA0zAo.wav"} +{"id": "jPROsr_K710", "caption": "The low quality recording features a Christian Music that contains wide harmonizing vocals singing over shimmering hi hats, simple punchy kick and organ keys playing in the background. It sounds messy, as the vocals are way too loud, relative to the other instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/jPROsr_K710.wav"} +{"id": "jQYSfy4DzIc", "caption": "A male singer sings this hip hop dance song. The tempo is medium tempo with a groovy bass line, keyboard harmony and reggae inspired drumming rhythm. The song is story telling and romantic in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/jQYSfy4DzIc.wav"} +{"id": "jR_wBfxgZwE", "caption": "The low quality recording features laughing male sounds over sloppy drums that contain energetic crash cymbal hits and toms percussion. It sounds exciting, even though the recording is noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/jR_wBfxgZwE.wav"} +{"id": "jS9u6X6TQmk", "caption": "The song is an instrumental. The tempo is slow with a classical guitar playing harmony style with a subtle bass line and no other instrumentation. The song is emotional and relaxing. The audio quality is worth average.", "audio": "/zhanghaomin/datas/musiccap/music_data/jS9u6X6TQmk.wav"} +{"id": "jUJNETNCxh0", "caption": "This song is a percussion instrumental. The tempo is fast with intense and rapid drum rhythm along with sound rhythmic clashing of cymbals with sound of clapping in the background and a man grunting. The music is animated,vigorous ,energetic, and enthusiastic.", "audio": "/zhanghaomin/datas/musiccap/music_data/jUJNETNCxh0.wav"} +{"id": "jV8kq0MpWMU", "caption": "This is an ASMR clip which features a sound that is crackly and fuzzy. We also hear the ambient tone of a room - possibly an air conditioner in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/jV8kq0MpWMU.wav"} +{"id": "jWQu301CEp8", "caption": "A female voice is singing in a high key along to a piano supported with the suited chords. This is an amateur recording. This song may be playing in a musical.", "audio": "/zhanghaomin/datas/musiccap/music_data/jWQu301CEp8.wav"} +{"id": "jWTm17KZGI8", "caption": "The low quality recording features a traditional song that consists of passionate male vocals singing over wooden percussion, claps, repetitive plucked strings melody and accordion melody. The percussion and plucked strings are in the left channel, while the other elements are in the right channel of the stereo image. It sounds passionate and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/jWTm17KZGI8.wav"} +{"id": "jXi1dFAB0n8", "caption": "This is an electronic dance music piece. It is an instrumental piece. There is an ambient synth holding a note in the background while a melodic pad is playing the main tune. The rhythmic background consists of a medium tempo electronic drum beat. The atmosphere is danceable and trippy. This piece could be playing in the background at a nightclub or a dance club. It could also work well in the soundtrack of a sci-fi video game with a dystopian future setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/jXi1dFAB0n8.wav"} +{"id": "jZi0VVWt72E", "caption": "The low quality recording features a tutorial where a flat male vocal is talking in between harmonica tones. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/jZi0VVWt72E.wav"} +{"id": "jZkHpNnXLB0", "caption": "This song contains mallet instruments playing a fast melody in the mid and high register along with low notes as bassline. The marimba is full of reverb. Then a bass drum comes in playing on every beat. This song may be playing in an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/jZkHpNnXLB0.wav"} +{"id": "jaJdPUAv6N0", "caption": "The low quality recording features a tutorial where a flat male vocalist is talking in-between punchy electro kick and synth hi hat. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/jaJdPUAv6N0.wav"} +{"id": "jbe3VM-5xdc", "caption": "An e-bass is playing a funky bassline with a drumbeat that sounds like the high frequencies have been filtered out. You can hear a lot of background noises that do not belong to the recording. Such as a dog barking, glass shattering, a male voice shouting and a female voice singing. All these sounds are using a reverb. This song may be playing as part of a movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/jbe3VM-5xdc.wav"} +{"id": "jbyVJdDlo2Q", "caption": "The low quality recording features a didgeridoo melody played outside, along with some birds chirping and crickets sounds. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/jbyVJdDlo2Q.wav"} +{"id": "jcZQhxb5lyw", "caption": "The low quality recording features a harmonizing female vocals singing. It sounds passionate, emotional and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/jcZQhxb5lyw.wav"} +{"id": "jd1IS7N3u0I", "caption": "This features two clips from country songs. The first song is upbeat, and suitable for rhythmic and groovy dancing. The second song is slower and features a group of male vocalists harmonising. The overall feeling is a country midwestern feel.", "audio": "/zhanghaomin/datas/musiccap/music_data/jd1IS7N3u0I.wav"} +{"id": "jd94Ox7KJ9Q", "caption": "The Afrobeats song features a fruity male vocal rapping over stuttering and echoing siren sounds effects, echoing laser effects, punchy kick and snare hits, shimmering hi hats, smooth bass and short strings hits. It sounds groovy, energetic and chaotic due to the many siren sound effects.", "audio": "/zhanghaomin/datas/musiccap/music_data/jd94Ox7KJ9Q.wav"} +{"id": "jdEbwMS9xqo", "caption": "The low quality recording features a live performance of a metal song that features a flat male vocal talking, repetitive cowbell percussion and manic drums. The recording is loud, messy, distorted, muffled and it sounds aggressive and uptempo.", "audio": "/zhanghaomin/datas/musiccap/music_data/jdEbwMS9xqo.wav"} +{"id": "je1amtXOKF4", "caption": "The low quality recording features a sustained strings melody over which there is a mellow arpeggiated harp melody being played. It sounds spooky, haunting and emotional - like something you would hear in thriller mystery movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/je1amtXOKF4.wav"} +{"id": "je96vkMY60c", "caption": "The low quality recording features an intense, suspenseful movie scene that consists of panicked female breathing, whining and mellow wide synth chords playing in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/je96vkMY60c.wav"} +{"id": "jfxTOlXF3Kk", "caption": "This audio contains a violent and tense cinematic composition. Evolving synth pads are played in a higher key with an aggressive overdrive bass sound with reverb. Then you can hear a machine gun shooting. This song may be playing for an action video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/jfxTOlXF3Kk.wav"} +{"id": "jhQpTVVUQ9E", "caption": "The instrumental contains digital drums repeating a simple groove that is mostly kick and snare that sounds like a strong clap. In the background synthesizer sounds playing melodies all over the place being panned to the left and right side of the speakers. Male voices singing in a higher key and overlapping each other. The bass sounds digital and soft. This song may be playing while practicing dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/jhQpTVVUQ9E.wav"} +{"id": "jhgX0OOoytQ", "caption": "This is a hmong pop music piece. There is a male vocalist singing melodically in the lead. The melody is being played by the piano, the acoustic guitar and the bass guitar. The rhythm is being played on the acoustic drums. There is a sentimental, romantic feel to it. The piece could be used in a romantic movie/TV show with a Hmong-language speaking setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/jhgX0OOoytQ.wav"} +{"id": "jhsce15byHc", "caption": "This song contains bellsound playing a melody with a lot of reverb and lasting overtones. A strongly processed male voice is singing long low notes with a monotone melody. Panning from the right to the left side of the speakers. This song may be playing while meditating.", "audio": "/zhanghaomin/datas/musiccap/music_data/jhsce15byHc.wav"} +{"id": "ji5wvUUQjHY", "caption": "This is a classical music piece from the romantic era. The piece is being performed by the double bass. There is a melancholic atmosphere to the piece. The overall feel is dark and dramatic. This piece could be used in the soundtrack of an art movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/ji5wvUUQjHY.wav"} +{"id": "jjNxc9Zf9s8", "caption": "This music is instrumental. The tempo is slow with an electric guitar harmony. It is mellow, sad, sentimental,sombre, poignant and emotional. This music is a movie theme melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/jjNxc9Zf9s8.wav"} +{"id": "jjYXRmE19lQ", "caption": "This music is instrumental. The tempo is fast with an enthralling harpsichord melody. The music is an energetic, high-powered, vibrant, vivacious and melodious western classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/jjYXRmE19lQ.wav"} +{"id": "jjg0TCq3wbY", "caption": "The low quality recording features a passionate female vocalist singing over a hollow piano melody. It sounds thin and noisy, and you can really hear the unprofessional recording technique, especially in vocals.", "audio": "/zhanghaomin/datas/musiccap/music_data/jjg0TCq3wbY.wav"} +{"id": "jlIbJVfnHB4", "caption": "A male singer sings this passionate melody with backup singers in vocal harmony. The song is medium tempo with a slick drumming rhythm, keyboard accompaniment, beep tones, strong bass line and slick percussion hits. The song is groovy and story telling in nature. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/jlIbJVfnHB4.wav"} +{"id": "jlmCu2GMoG4", "caption": "This recording is full of flutes and string instruments played with a bow. All of them are playing melodies spread across the sides of the speakers. Someone is playing a percussion instrument and a male voice is singing in a higher key. To me it sounds overloaded with too many melodies playing at the same time. This song may be playing in a traditional presentation.", "audio": "/zhanghaomin/datas/musiccap/music_data/jlmCu2GMoG4.wav"} +{"id": "jmPmqzxlOTY", "caption": "This is an EDM inspired instrumental house/techno beat with a four on the floor kick pattern, shuffled hi hats, a repetitive synth bassline, synth chords with delay, drum machine tom melody and claps on the backbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/jmPmqzxlOTY.wav"} +{"id": "joLyjgORwDo", "caption": "This is a Bali folk music piece. The instruments that are used are mostly percussive in nature traditional to the music of Bali such as gamelan, kendang and gong. There is a hypnotic atmosphere in this piece. It could be used in dream/hypnosis sequences in the soundtracks of movies and TV shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/joLyjgORwDo.wav"} +{"id": "jqiD3VeM_hY", "caption": "The low quality recording features a mixed background vocals singing over acoustic rhythm guitar. There is also a child talking over the song. The recording is noisy and muffled, but it sounds fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/jqiD3VeM_hY.wav"} +{"id": "jrwhxVnvMdk", "caption": "The music is a country song instrumental. The tempo is slow with an auto harp harmony and lively acoustic guitar accompaniment. The music is soft, mellow, mellifluous,dulcet, sentimental, simple and nostalgic.", "audio": "/zhanghaomin/datas/musiccap/music_data/jrwhxVnvMdk.wav"} +{"id": "jtRse-cDB18", "caption": "A female singer sings this traditional melody. The song is medium tempo with a clicking percussion rhythm, guitar strumming accompaniment and tap dancing tones. The song is energetic and passionate. The song has very poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/jtRse-cDB18.wav"} +{"id": "jtwRKyQ8-lg", "caption": "This is a hip-hop/dancehall music piece. There is a repeating female vocal sample in the lead. The piano is playing the chords of the song. There is a groovy bass guitar in the background. The rhythm is provided by an acoustic drum beat with a lot of rhythmic sound effects applied to give it more of a swing feel. The atmosphere of the piece is chill and urban. This piece could be the opening theme of a sit-com taking place in the big city.", "audio": "/zhanghaomin/datas/musiccap/music_data/jtwRKyQ8-lg.wav"} +{"id": "jx27p7k2lSw", "caption": "An e-piano is playing a melody and chords with a lot of tremolo while thin, airy synth pads are playing long evolving sounds. A male voice is singing in a higher register with effects on his voice. It sounds like a voice sample. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/jx27p7k2lSw.wav"} +{"id": "jy0gitU1BFA", "caption": "A hip hop dance song with female vocals plays as a dance track for three dancers. The song is fast tempo with faint audio signal with a lot of ambient room noises like footsteps sounds,body movements sounds and ambient room noise. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/jy0gitU1BFA.wav"} +{"id": "jzij1UX73kU", "caption": "The low quality recording features an ambient song that consists of a wide sustained synth pad, followed by mellow sustained strings. It sounds relaxing, calming and like something you would listen to in a yoga session.", "audio": "/zhanghaomin/datas/musiccap/music_data/jzij1UX73kU.wav"} +{"id": "k-89m72W0j8", "caption": "The Low Quality recording features a person trying to tune an acoustic guitar and background nature ambient sounds that include birds chirping, distant and unclear chatting and wind blowing sounds. You could tell that it is low quality by the amount of noise in the recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/k-89m72W0j8.wav"} +{"id": "k-J2-Ou1Fm8", "caption": "Single sounds, noises and melodies being played with a lot of reverb and delay. Long waving notes, deep drum hits; a processed choir melody and a piano playing a chord with effects on it. The whole composition sounds very atmospherically dark and scary. This song may be playing in a videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/k-J2-Ou1Fm8.wav"} +{"id": "k-LkhT4HAiE", "caption": "The song is an instrumental. The tempo is medium fast tempo with deep bass hits, synth voice harmony, keyboard harmony, and strong drumming rhythm. The song is deep trance and very groovy. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/k-LkhT4HAiE.wav"} +{"id": "k2uiJXN3L6E", "caption": "The excerpt features an electric guitar playing a descending melody note by note with a slight distortion effect on. This doesn't sound like actual music but more like an exercise.", "audio": "/zhanghaomin/datas/musiccap/music_data/k2uiJXN3L6E.wav"} +{"id": "k3A5xX8yfig", "caption": "A male singer sings this soaring melody. The song is medium tempo with a guitar accompaniment, strong bass line and a violin accompaniment. The song quality is poor and badly deteriorated. The song is a romantic love song from a Tamil movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/k3A5xX8yfig.wav"} +{"id": "k4kbpRRRgcQ", "caption": "This contemporary gospel song features a female voice. When the voice reaches a high pitch, she sings in falsetto. This is accompanied by percussion playing the floor tom and kick. The splash cymbal is played on the fourth count of the bars. A piano plays arpeggiated chords in the background. Synth pads play chords in the background filling the musicscape. This gospel song is emotional. This song can be played in a worship session in church.", "audio": "/zhanghaomin/datas/musiccap/music_data/k4kbpRRRgcQ.wav"} +{"id": "k4ttuqKjiw0", "caption": "This audio contains a simple drum groove along with a bassline playing long notes. A piano and keyboard are playing chords and melodies panned to the left and right side of the speakers. Male voices are singing a melody together. Some in the mid and high range and one as a bass voice. This audio may be playing at a celebration event.", "audio": "/zhanghaomin/datas/musiccap/music_data/k4ttuqKjiw0.wav"} +{"id": "k5kPBsMFlOc", "caption": "The low quality recording features a live performance of shimmering shakers, acoustic rhythm guitar and arpeggiated harp melody. It sounds tropical and exotic even though the recording is very noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/k5kPBsMFlOc.wav"} +{"id": "k6F3gc8f8kI", "caption": "The low quality recording features a flat male talking, after which there are harmonizing clarinet melodies playing. It sounds soulful and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/k6F3gc8f8kI.wav"} +{"id": "k8AE-vqWbm4", "caption": "This audio contains a male church choir singing from the low register up into the mid-higher register. An acoustic piano is providing single notes walking up the keybed. This song may be playing in a church sung by a male choir.", "audio": "/zhanghaomin/datas/musiccap/music_data/k8AE-vqWbm4.wav"} +{"id": "k9w2aaNKenE", "caption": "The low quality recording features a happy sounding background song playing in the background and some plastic impact, breaking and plastic scraping sound effects. It seems like it is a tutorial for a kids game.", "audio": "/zhanghaomin/datas/musiccap/music_data/k9w2aaNKenE.wav"} +{"id": "kAAGkKPVgZ8", "caption": "The low quality recording features a pop song that consists of a passionate, echoing female vocal singing over punchy kick, groovy bass, repetitive synth lead melody and some claps. It sounds energetic, passionate and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/kAAGkKPVgZ8.wav"} +{"id": "kAE7Ceg4VgQ", "caption": "This is a low audio clip. This song is a contemporary gospel song. This song features a male voice. This is accompanied by a tambourine and hand claps. The bass plays the root notes of the chords. The piano plays chords and fills. The sounds of the crowd are heard in this clip. The tempo of this song is moderate.", "audio": "/zhanghaomin/datas/musiccap/music_data/kAE7Ceg4VgQ.wav"} +{"id": "kCsmvK06SCA", "caption": "This music is an enthralling Sitar instrumental. The tempo is fast with an animated and melodic Sitar lead Harmony and tanpura accompaniment. The music is based on Hindustani Classical notes. It is captivating, intense, mellifluous, engaging,and fervent.", "audio": "/zhanghaomin/datas/musiccap/music_data/kCsmvK06SCA.wav"} +{"id": "kGo-dAQXtsA", "caption": "someone is playing a distorted e-guitar. Playing a melody using finger tapping. This is an amateur recording. This song may be playing at home practicing finger tapping guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/kGo-dAQXtsA.wav"} +{"id": "kH-F9JzC7eE", "caption": "solo ukelele playing in free time in a demonstrative manner with a female voiceover.", "audio": "/zhanghaomin/datas/musiccap/music_data/kH-F9JzC7eE.wav"} +{"id": "kIEEDYowZhA", "caption": "The low quality recording features a short snippet of flat male vocals, followed by steel guitar melodies. It sounds passionate, even though the recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/kIEEDYowZhA.wav"} +{"id": "kKPGTMdz99A", "caption": "This audio contains a synth drone playing in the lower midrange and other synthesizer sounds on top. One of them is playing a melody in a higher pitch. A female voice is talking along to the music. The whole recording is full of reverb. This song may be playing during meditation or while falling asleep.", "audio": "/zhanghaomin/datas/musiccap/music_data/kKPGTMdz99A.wav"} +{"id": "kKihNQ44dDQ", "caption": "The song is an instrumental. The tempo is slow with an electric guitar playing lead and a strong bass line in a rhythmic manner. The song is strong and mysterious like a secret agent movie theme. The song is recorded at home and has an average sound quality. The song is a music demo.", "audio": "/zhanghaomin/datas/musiccap/music_data/kKihNQ44dDQ.wav"} +{"id": "kMK10SknFAI", "caption": "A synthesizer is playing soothing pad sounds with a lot of reverb. In the background you can hear external noises and some water sounds. This may be playing in a videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/kMK10SknFAI.wav"} +{"id": "kMNL4Y4XMhc", "caption": "This is a classical music piece performed by an orchestra. There is a wide ranging brass section that has the french horn as the lead playing the melody. In the percussive background there are the tubular bells which give the piece a festive feel. The atmosphere is vibrant. This piece would fit perfectly in the soundtrack of a Christmas movie either as the opening theme or during the scenes where there is a preparation going on.", "audio": "/zhanghaomin/datas/musiccap/music_data/kMNL4Y4XMhc.wav"} +{"id": "kMmjr8deHis", "caption": "The low quality recording features a folk song that consists of an echoing male chant over punchy kick and snare hits, wooden percussion, addictive strings and brass melodies and simple bass. It sounds traditional, addictive, passionate and energetic. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/kMmjr8deHis.wav"} +{"id": "kOBh4NZ4wZQ", "caption": "A male vocalist sings this smooth Soul song. The tempo is medium with a groovy bass line, trombone harmony, electric guitar rhythm, slick drumming, vocal backup, congas and tambourine beats with smooth vocal backup. The song is soft, rich, elegant, ambient and smooth. This music is a Funk pop/Soul.", "audio": "/zhanghaomin/datas/musiccap/music_data/kOBh4NZ4wZQ.wav"} +{"id": "kOREaTKeyZw", "caption": "This audio contains someone playing a piece of music on a bagpipe. The music sounds traditional. This song may be playing at a folksfest.", "audio": "/zhanghaomin/datas/musiccap/music_data/kOREaTKeyZw.wav"} +{"id": "kQw2NQ_eqyg", "caption": "A female singer sings this cool melody with backup singers in vocal harmony. The song is medium tempo with a groovy bass line and guitar rhythm, steady drums g rhythm and keyboard harmony. The song is catchy and has a dance groove. The song is a retro dance hit. The song has a poor audio quality issue.", "audio": "/zhanghaomin/datas/musiccap/music_data/kQw2NQ_eqyg.wav"} +{"id": "kR2yBlL6nFU", "caption": "The low quality, mono recording features a classical song performed by sad violin melody and harpsichord. The recording is noisy and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/kR2yBlL6nFU.wav"} +{"id": "kSKXtXXAD70", "caption": "The low quality recording features a printer that produces printing sounds and some muffled music playing in the background, probably on a radio. It is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/kSKXtXXAD70.wav"} +{"id": "kSdH9z8snac", "caption": "The low quality recording features a cover of a soft rock song and it consists of a mellow electric guitar melody. The recording is a bit noisy. It sounds like an intro section of the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/kSdH9z8snac.wav"} +{"id": "kT0KMsfD4d8", "caption": "This song is a spirited instrumental. The tempo is fast with enthusiastic brass harmony , with trumpet flourish, trombone and violins, cello and viola playing an upbeat melody along with vigorous drumming, piano accompaniment and cheerful, animated choral backup. The song is animated, vibrant, energetic and full of life. The sound of the hooves of horses and whistling indicates that this is Country music.", "audio": "/zhanghaomin/datas/musiccap/music_data/kT0KMsfD4d8.wav"} +{"id": "kTBlMy4dtC0", "caption": "A male singer sings this cheerful children\u2019s song. The song is medium tempo with reggae inspired drumming rhythm, guitar accompaniment, groovy bass line and keyboard harmony. The song is exciting and cheerful. The song is a children\u2019s dance song.", "audio": "/zhanghaomin/datas/musiccap/music_data/kTBlMy4dtC0.wav"} +{"id": "kTyI2unrdv0", "caption": "This song contains a piano playing minor chords with a lot of reverb, a synthesizer playing a countermelody with short notes and something like a processed and cut voice sample that gets repeated in a very short and rhythmical ways serving as percussive element and is panned to the left and the right side of the speakers along with white noise processed with delay. For a moment a short digital bass sound is coming in. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/kTyI2unrdv0.wav"} +{"id": "kUQ1xfK82Q0", "caption": "A lot of percussive instruments are being played and panned to the left and right side of the speakers. A funky bassline is repeating the same pattern with fill-ins. An acoustic guitar is strumming funky chords and another guitar-like instrument is playing a melody on top. Male voices are singing in unison and kids voices are responding as backing vocals. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/kUQ1xfK82Q0.wav"} +{"id": "kVYXcbvw9u4", "caption": "This music is an electronic instrumental; the tempo is medium with a solo electric guitar lead and no accompanying instruments. The music is melodic, rhythmic, and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/kVYXcbvw9u4.wav"} +{"id": "kVaQA3PhSio", "caption": "The low quality recording features a short snippet of echoing effect at the beginning, after which there is a theremin swell. It sounds suspenseful, intense and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/kVaQA3PhSio.wav"} +{"id": "kVuG_F3qCuY", "caption": "An acoustic drum set is playing a shuffle groove with hits on the ride along with an e-bass playing a blues walking bassline. Someone is playing a slide-e-guitar. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/kVuG_F3qCuY.wav"} +{"id": "kX5bTiq5eBo", "caption": "The song is a hip hop song with a violin motif playing the most prominent role in the instrumental. The drum beat is a simple boom bap beat. The rapper has a raspy voice and he sounds emboldened regarding his message. The violin riff is repeated throughout the song.", "audio": "/zhanghaomin/datas/musiccap/music_data/kX5bTiq5eBo.wav"} +{"id": "kYrJadZmjm0", "caption": "This is a house song, meant for dancing. The synths are played rapidly for the build-up and then the song drops into a section where it's mostly the low, rumbling, futuristic pad and the house drum beat. This song would be heard at house dance parties.", "audio": "/zhanghaomin/datas/musiccap/music_data/kYrJadZmjm0.wav"} +{"id": "kZBFQAQI7Pg", "caption": "A male vocalist sings this energetic song. The tempo is fast with boomy bass lines, steady drumming, keyboard harmony and enthusiastic electric guitar riff with vocal backup. The audio quality is very bad and the song is muffled and muddy. This song is a live performance with ambient sounds of people clapping and cheering.", "audio": "/zhanghaomin/datas/musiccap/music_data/kZBFQAQI7Pg.wav"} +{"id": "kZPz8ExTzBk", "caption": "A male beatboxer creates a cool groove with animated sounds like grunting and mouth percussion. The song is medium tempo with no other instrumentation. The song is energetic and passionate. The song has bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/kZPz8ExTzBk.wav"} +{"id": "kZYBpOwNGZU", "caption": "Two e-guitars playing a melody. An electric bass is playing the rootnotes. They run through a chorus/vibrato effect. This song may be playing at home building a song with a loopstation.", "audio": "/zhanghaomin/datas/musiccap/music_data/kZYBpOwNGZU.wav"} +{"id": "k_ET0i2y0Ow", "caption": "This audio contains someone playing a classical piece on a cembalo. This song may be playing live in a theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/k_ET0i2y0Ow.wav"} +{"id": "kaabXWuPWRg", "caption": "This music clip is an electric guitar solo lead instrumental. The tempo is fast with the guitarist playing a very emphatic, intense riff. No other instruments have been used. The music is loud, intense, engaging and catchy.", "audio": "/zhanghaomin/datas/musiccap/music_data/kaabXWuPWRg.wav"} +{"id": "kbAMGp-TKJo", "caption": "The low quality recording features a live performance that contains harmonizing male vocals singing over repetitive synth keys and electric guitar melody, followed by groovy bass, shimmering hats and punchy \"4 on the floor\" kick pattern. The recording is noisy, distorted and crushed, but it sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/kbAMGp-TKJo.wav"} +{"id": "kbCh5HrmgN0", "caption": "A steeldrum-orchestra in playing a composition containing bass sounds, mid range chords and melodies in the higher register. This sounds soothing. This song may be playing as a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/kbCh5HrmgN0.wav"} +{"id": "kbquMoJrhC0", "caption": "The low quality recording features a folk song sung by passionate echoing male vocals over mellow organ keys, chords and sitar melody. It sounds narrow, because it was recorded with a mono microphone setup, but it is also very passionate, regardless.", "audio": "/zhanghaomin/datas/musiccap/music_data/kbquMoJrhC0.wav"} +{"id": "kcTwJwdLTSo", "caption": "This is a piece by a classical orchestra. The melody is mainly led by string instruments such as violins and cellos. The piece elicits feelings of sadness, and can initiate a desire to reflect. The piece ends on an uplifting high note, which could be used as a sign that better days are to come.", "audio": "/zhanghaomin/datas/musiccap/music_data/kcTwJwdLTSo.wav"} +{"id": "kdxW11WBlQE", "caption": "This song contains a fast and silent jazz drum rhythm with a fast groove on the ride. Someone is playing an arpeggio melody on an acoustic piano in the midrange, adding a little melody on top being played in the upper register. A upright bass is playing a walking bassline. A saxophone is playing the main melody. This song may be playing live as a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/kdxW11WBlQE.wav"} +{"id": "keHCWa6XfGY", "caption": "This is an Indian classical music piece. The female vocals are singing in a syncopated manner at the same time with the rhythmic background of the tabla, the cajon and the acoustic drums. The melodic background is provided by a sitar. The piece is used as an accompaniment for the kathak dance. It could be used for the same task in dancing courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/keHCWa6XfGY.wav"} +{"id": "keIvA2wSPZc", "caption": "A male vocalist sings this soft country song. The tempo is slow with a gentle acoustic guitar and resonator rhythm, subtle keyboard, soft drumming, tambourine beats and soft auto harp strains. The vocals are mellow, gentle, sentimental, emotional, poignant, melancholic and nostalgic. This song is a Classic Country song.", "audio": "/zhanghaomin/datas/musiccap/music_data/keIvA2wSPZc.wav"} +{"id": "kepd6_X_vS4", "caption": "The low quality recording features a bowl scraping resonance tone over which there is a deep male vocal hum. The recording is in mono, noisy and it sounds calming and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/kepd6_X_vS4.wav"} +{"id": "kf-U7I0-DdA", "caption": "A female singer sings this lilting melody. The song is medium tempo with a string section playing an emotional harmony, piano accompaniment and steady bass line playing rhythmically. The song is emotional and heartfelt. The song is a movie soundtrack but has a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/kf-U7I0-DdA.wav"} +{"id": "kg8FwhL_fqs", "caption": "The music is purely instrumental and it features two acoustic guitars. One of them is playing a melody in the high register while the other one is providing accompaniment by strumming chords.", "audio": "/zhanghaomin/datas/musiccap/music_data/kg8FwhL_fqs.wav"} +{"id": "kgf4GdKlSWs", "caption": "Here we hear a calm acoustic rendition of a song. The ukulele is played in a simple, chord-based way, and the female singer has a gentle and soothing voice. She also performs in a way that radiates tranquility.", "audio": "/zhanghaomin/datas/musiccap/music_data/kgf4GdKlSWs.wav"} +{"id": "kgvx9drZXpk", "caption": "This song contains a female voice singing along to a piano playing chords and the melody along. An acoustic drum is playing together with an e-bass. In the background you can hear an organ and a background choir. This song may be playing in a church.", "audio": "/zhanghaomin/datas/musiccap/music_data/kgvx9drZXpk.wav"} +{"id": "kh6rmFg3U4k", "caption": "The low quality recording features a resonating bell in one shot. It sounds mellow, soft, calming, relaxing and hypnotic - like something you would listen to while meditating.", "audio": "/zhanghaomin/datas/musiccap/music_data/kh6rmFg3U4k.wav"} +{"id": "khQN5ylb3H0", "caption": "Big band jazz style music featuring a lead clarinetist soloing over a walking bassline, electric jazz guitar, a wind section, brass, string section, and a choir.", "audio": "/zhanghaomin/datas/musiccap/music_data/khQN5ylb3H0.wav"} +{"id": "khVk4pTS0bE", "caption": "This is a soothing Italian ballad. The leading instruments are a harmonica and acoustic guitar on which arpeggios are played. The singer has a silky baritone voice, and captures the reflective and tranquil nature of the song with his performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/khVk4pTS0bE.wav"} +{"id": "kiu-40_T5nY", "caption": "A male vocalist sings this mesmerising song. The tempo is slow with synthesiser articulation. The song is meditative, ethereal,mesmerising,captivating, futuristic, hypnotic and psychedelic. The incessant vocal riff and droning music give it a trance vibe. This song is a Trap Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/kiu-40_T5nY.wav"} +{"id": "kjcXM60HrRA", "caption": "Two male voices are singing loudly together: One backing the other one. A e-guitar can be heard at the end of the phrase. In the background a e-bass and an acoustic drum can be heard but they get overthrown by the sound of the cheering and Screaming crowd. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/kjcXM60HrRA.wav"} +{"id": "kjmmzA6i5rk", "caption": "A male singer sings this pop melody with backup singers with vocal harmony. The song is medium, with a keyboard accompaniment , steady drumming rhythm and strong bass line. The song is passionate and cheerful. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/kjmmzA6i5rk.wav"} +{"id": "kjn6I3AurgE", "caption": "Someone is playing a clean e-guitar that is doubled and panned to both sides of the speakers. A female voice is singing in the mid to high range. This song may be playing at a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/kjn6I3AurgE.wav"} +{"id": "kkOGbgGJLF4", "caption": "A male vocalist sings this spirited song. The tempo is medium fast with an acoustic and electric guitar flourish with a bass cello. This bit is the end of the song as the musician plays a closing riff and the sound of clapping and cheering can be heard. This song is an enthusiastic live performance of an energetic Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/kkOGbgGJLF4.wav"} +{"id": "kka6zUtE3h8", "caption": "This is a pop soul/modern r&b piece that is sung by a mellow male vocal in medium pitch. The main tune is played by the acoustic guitar with the bass guitar and the ambient synth supporting the melody in the background. There is a calm and simple acoustic drum beat in the rhythmic background. The song is played on a major scale giving it a positive, optimistic atmosphere. This piece could be used in a romantic setting. It could also be playing in the background of a coffee house or a bookstore.", "audio": "/zhanghaomin/datas/musiccap/music_data/kka6zUtE3h8.wav"} +{"id": "kkjNpwNcMWI", "caption": "A female vocalist sings this spirited song. The tempo is fast with an animated keyboard harmony, groovy bass lines, electric guitar, tenor and alto saxophone accompaniment, enthusiastic drumming and tambourine beats with vocal backup. The song is energetic, upbeat, youthful, enthusiastic with emphatic vocals. This song is contemporary alternative rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/kkjNpwNcMWI.wav"} +{"id": "kko1uYyqJ_o", "caption": "This is an amateur recording of a solo banjo player. The piece is played in the major scale, creating a friendly, calming atmosphere giving it a definitive characteristic of a folk song. It could be used as background music in pastoral content, touristic videos of rural locations.", "audio": "/zhanghaomin/datas/musiccap/music_data/kko1uYyqJ_o.wav"} +{"id": "kmZFn-CQ19A", "caption": "This audio contains someone playing an acoustic guitar fingerstyle. An upright bass is playing a line in the background. This song may be playing guitar to someone.", "audio": "/zhanghaomin/datas/musiccap/music_data/kmZFn-CQ19A.wav"} +{"id": "kmmK69N3Om0", "caption": "This clip is regal, momentous, big, impressive. We hear a loud bang on the timpani percussion instrument, followed by a motif on the french horn. This is the type of piece that would be played for the arrival of a king, or the return of an epic war hero.", "audio": "/zhanghaomin/datas/musiccap/music_data/kmmK69N3Om0.wav"} +{"id": "knQuxZj9rTA", "caption": "The recording is full of natural sounds. Birds chirping, a river running and wind shaking the leaves. Then a percussive mid range instrument comes in with a steady repetitive rhythm. This instrument seems to be recorded in another environment than the natural sounds. The sound quality is different. This is not a professional recording. This song may be playing for a documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/knQuxZj9rTA.wav"} +{"id": "kp5OxEzxuSg", "caption": "This electronic music is played on a drum kit. This song also uses a processor to make electronic sounds. The percussion plays the ride continuously followed by the hi-hat continuously. Deep bass sounds are played on the electronic console. There are other animated sounds like the sound of an alien space ship played in this song. This song has no other instruments. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/kp5OxEzxuSg.wav"} +{"id": "kpsYSXR1wao", "caption": "This music is a spirited Latin music instrumental. The tempo is fast with a lively accordion harmony, spirited congas beat and guiro accompaniment. The music is happy, vivacious, upbeat, vigorous, cheerful , celebratory and cheerful with ambient outdoor sounds like wind, people talking, clapping and a lot of static indicating that this is a live performance. The audio quality is inferior and this looks like an amateur home recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/kpsYSXR1wao.wav"} +{"id": "ksImihlU3qM", "caption": "The low quality recording features a groovy piano and plucked strings melody playing over some animal sound effects. Some of the sounds that can be heard are chickens, cats and sheep sound effects. It sounds happy and fun, like something a kid would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/ksImihlU3qM.wav"} +{"id": "ksYM8YzzWXo", "caption": "This music is an electronic instrumental. The tempo is medium with a steady, rhythmic keyboard harmony, simple drumming and groovy bass lines. There are sounds of crashing, glass breaking, explosions or gunshots in the background superimposing over the music. The sounds are in stark contrast to the melodious music, with the crashing and shooting giving it an aggressive vibe;", "audio": "/zhanghaomin/datas/musiccap/music_data/ksYM8YzzWXo.wav"} +{"id": "ktTrTDQidsE", "caption": "The low quality recording features a groovy Spanish acoustic guitar. It sounds very noisy, vintage and the guitar was recorded in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ktTrTDQidsE.wav"} +{"id": "ktw_J6ZW0MM", "caption": "A male voice is singing with reverb and delay in his voice. An acoustic drum is playing a faster groove on the piano, a tambourine can be heard. An electric bass is playing repeating notes without a lot of changes. A brass section is repeating a theme while keyboards and a guitar are playing along. This song may be playing live in-between an entertainment-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/ktw_J6ZW0MM.wav"} +{"id": "kuj0Oi2_7yU", "caption": "After a clicking sound and e-guitar slide up the fretboard someone is playing a melody on an e-guitar. White noise from the recording can be heard. This song may be playing in a guitar class.", "audio": "/zhanghaomin/datas/musiccap/music_data/kuj0Oi2_7yU.wav"} +{"id": "kvIt_9P79Ro", "caption": "The low quality recording features a soft rock song playing over pigs oinks sound effects. The song contains a short drum break at the beginning, punchy snare, simple kick pattern, smooth bass guitar, wide acoustic rhythm guitar, shimmering cymbals and flat female vocals singing over it. Sounds like it is some kind of documentary about pigs, as the song is playing in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/kvIt_9P79Ro.wav"} +{"id": "kw2wPVxUgQY", "caption": "This is the live recording of a boy band performing a pop music piece. The male vocals are singing melodically. There is a keyboard and a bass guitar playing in the background. The rhythm is provided by the acoustic drums. The atmosphere is emotional. This piece could be included in the soundtrack of a teenage romance/drama movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/kw2wPVxUgQY.wav"} +{"id": "l-RdHtsYWBY", "caption": "This is a Scottish folk music rendition of a rock music piece. It is an instrumental piece. The Scottish bagpipes are playing the melody while the rhythmic background is provided by a bodhran frame drum. The atmosphere is energetic and lively. The audio quality of the piece is quite poor. Still, it could be used in a comedy movie as a song playing from the radio.", "audio": "/zhanghaomin/datas/musiccap/music_data/l-RdHtsYWBY.wav"} +{"id": "l0fCHZhKEDA", "caption": "The low quality recording features a groovy piano organ keys in the left channel and organ keys lead melody played in the right and the middle channel of the stereo image, followed by groovy bass, shimmering hi hats and soft kick hits. It sounds happy and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/l0fCHZhKEDA.wav"} +{"id": "l1coM570kVw", "caption": "The low quality recording features a live performance of a soul song and it consists of passionate male vocal singing over playback instrumentals. The instrumental consists of a shimmering tambourine layered with punchy snare hits, soft kick hits, some toms rolls, groovy bass, electric guitar melody and harmonizing male vocals. It sounds emotional, soulful, hopeful and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/l1coM570kVw.wav"} +{"id": "l21xSYRR_Xc", "caption": "The low quality recording features a flat male vocal talking in-between resonating shofar melody. It sounds like a traditional instrument and it is reverberant, as it was probably recorded in a medium size room.", "audio": "/zhanghaomin/datas/musiccap/music_data/l21xSYRR_Xc.wav"} +{"id": "l3YrliBpOdM", "caption": "This is an instrument lesson recording. The same tune is being played repeatedly on a harmonica to present a technique on how to play it. The male instructor gives occasional descriptions about the technique.", "audio": "/zhanghaomin/datas/musiccap/music_data/l3YrliBpOdM.wav"} +{"id": "l3pK8prEnrQ", "caption": "A female vocalist sings an enthralling electronic melody. The tempo is medium with heavily synthesised instrumentation and vocals. The synthesiser articulated music and heavy bass synth add intensity and dense layers to the music giving it a psychedelic, trippy, hallucinatory, enigmatic and trance like vibe. This song is an EDM/Synth Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/l3pK8prEnrQ.wav"} +{"id": "l5QPXVIxxwk", "caption": "The music features a piano playing short interventions/melodies. A bass guitar (could be synth too) plays long notes. In the background, but very noticeable, is an electronic sound playing one long note throughout the music excerpt. The overall atmosphere is introspective.", "audio": "/zhanghaomin/datas/musiccap/music_data/l5QPXVIxxwk.wav"} +{"id": "l6LUPlmua6I", "caption": "This is a funk/disco music piece. There is a male vocalist singing melodically in the lead. The melody is being played by the keyboard with the backing of the electric guitar and the bass guitar. The rhythm is being played by the acoustic drums. The atmosphere is groovy. This piece could be played at a retro-themed party at a dance club.", "audio": "/zhanghaomin/datas/musiccap/music_data/l6LUPlmua6I.wav"} +{"id": "l8P2wU-JyI8", "caption": "This folk song features a male voice singing the main melody. The voice is loud and not modulated. This is accompanied by a violin and a harp. The violins are playing high pitched notes. The harp is playing a repetitive phrase. There is no percussion in the song. This song can be played in a village style movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/l8P2wU-JyI8.wav"} +{"id": "l9vYSBR9nio", "caption": "A male vocalist sings this melodic pop song.The tempo is medium with energetic drumming, keyboard harmony, groovy bass lines, electric guitar harmony, acoustic guitar rhythm and dissonant tambourine beats. The is soft, calming, mellow, sentimental, emotional and nostalgic. This song is Pop Rock/Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/l9vYSBR9nio.wav"} +{"id": "lAMiOhScSPg", "caption": "This is an R&B/neo-soul music piece. There is a male vocalist in the lead singing melodically. The main tune is being played by the electric guitar and the keyboard. There is a strong and groovy bass sound. The rhythmic background consists of a slow tempo electronic drum beat. The atmosphere is sentimental. This piece could be used in the soundtrack of a romantic comedy movie that takes place in the big city, especially during the scenes where a character is going through the feeling of heartbreak.", "audio": "/zhanghaomin/datas/musiccap/music_data/lAMiOhScSPg.wav"} +{"id": "lBSS2AbA560", "caption": "Here we have a flute which has a lot of echo and reverb applied to it. The music is relaxing, serene, tranquil. It would be suitable as meditation music.", "audio": "/zhanghaomin/datas/musiccap/music_data/lBSS2AbA560.wav"} +{"id": "lBtAULJAFp0", "caption": "Someone is playing an acoustic guitar finger picking a melody. On top of that, a distorted e-guitar is playing a solo melody with delay on it. This song may be playing at home creating a song in a DAW.", "audio": "/zhanghaomin/datas/musiccap/music_data/lBtAULJAFp0.wav"} +{"id": "lDABsoatahM", "caption": "This is an instrumental music piece with Chinese characteristics. The main tune is being played by a small xiao flute. There is a mellow acoustic guitar backing keeping a repeated theme in the background. The song is played on a major scale, giving it a feeling of hopefulness. The atmosphere of the song is soothing. This piece could be played as an opening soundtrack for a romantic anime movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/lDABsoatahM.wav"} +{"id": "lDCDayKyOQA", "caption": "The low quality recording features a jazz song playing on a speaker and it consists of groovy hi hats, brass melody, bells melody, punchy snare and smooth trombone. The recording is noisy and it sounds thin and like it is played in a lobby.", "audio": "/zhanghaomin/datas/musiccap/music_data/lDCDayKyOQA.wav"} +{"id": "lDGQu122JdU", "caption": "The song is an instrumental. The tempo is medium with a quartzophone being played delicately by an expert producing ethereal pulsating tones of music. The song is emotional and beautiful. The audio quality with ambient nature sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/lDGQu122JdU.wav"} +{"id": "lDnYXLGEEFQ", "caption": "The low quality recording features a woodblock one shot. The recording is in mono, noisy and it sounds like a tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/lDnYXLGEEFQ.wav"} +{"id": "lDsQWSf1h3I", "caption": "A full orchestra is playing a descending melody with a string section, a horn section and oboes. Then you can hear something falling to the ground and breaking. This may be playing in a sad disnemovie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/lDsQWSf1h3I.wav"} +{"id": "lFv1MJSSWNs", "caption": "There is a kids music piece playing from a small speaker. It is a robotic voice singing about brushing teeth. At the same time, a kid brushing his teeth can be heard. A female voice talks to the kid telling him to keep on brushing.", "audio": "/zhanghaomin/datas/musiccap/music_data/lFv1MJSSWNs.wav"} +{"id": "lGaA1dJQ0AQ", "caption": "This song is an electronic instrumental. The song is fast tempo with vigorous drumming and electronic instrumentation and synthesiser articulation with catchy synthesised vocal riff which. The song is upbeat, vibrant, vivacious, vigorous, psychedelic, enigmatic and youthful with a trance like dance vibe. This song is an EDM/Synth pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/lGaA1dJQ0AQ.wav"} +{"id": "lHlOSsnP48c", "caption": "The low quality recording features an uptempo rock song that consists of suspenseful electric guitar melody, punchy snare, simple kick pattern, groovy bass guitar, tinny percussive elements and passionate male vocal singing over it. The recording is in mono and it sounds energetic, groovy and like something you would dance to with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/lHlOSsnP48c.wav"} +{"id": "lI8aGjIb8Jg", "caption": "The low quality recording features a cover of a regional Mexican song and it consists of a passionate male vocalist singing over acoustic rhythm guitar. There are some crowd chattering and asphalt sounds in the background. The recording is noisy, in mono and it sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/lI8aGjIb8Jg.wav"} +{"id": "lIBsL97sUmY", "caption": "A male vocalist sings this soft pop. The tempo is medium with an acoustic guitar accompaniment and sound of static in the background. The song has simple lyrics and melody . It is informative and educational. This song is a Children\u2019s song/Alternative Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/lIBsL97sUmY.wav"} +{"id": "lIEnbqr3O34", "caption": "This is an Arabian themed instrumental music piece. The tune is played by a virtual eastern-sounding instrument while there is a virtual strings backing for the bass notes. The rhythmic background consists of a repeated percussion beat. There is an intriguing feel coming from the back-and-forth movement of the tune. The piece could be used in an eastern historical drama.", "audio": "/zhanghaomin/datas/musiccap/music_data/lIEnbqr3O34.wav"} +{"id": "lNg2y6SRZPo", "caption": "The song is an instrumental. The tempo is fast with trumpets playing percussively along with other brass instruments, piano accompaniment, groovy bass line jazz drumming rhythm. The song is energetic and passionate. The song is a retro big band jazz classic with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/lNg2y6SRZPo.wav"} +{"id": "lOIzOWKd47E", "caption": "The low quality recording features a rock song that consists of groovy electric guitar chord progression, smooth bass guitar, punchy snare and kick hits, shimmering hi hats and flat female vocals singing over it. At the end of the first half of the loop, there is a short snare roll alongside glissando organ keys melody, sliding perfectly into the next section, which begins with the energetic crash hit. It sounds energetic, groovy, and kind of vintage and warm, since it really sounds old - especially because the song is in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/lOIzOWKd47E.wav"} +{"id": "lPFsijo8xYs", "caption": "This is an electronic dance music piece. The tune is being played with a melodic bell preset. There is a medium-pitched synth holding the chords in the background. The rhythm is provided by a crisp electronic drum beat. The atmosphere is vibrant. This piece could be playing at a nightclub. It could also be included in the soundtrack of a movie taking place in winter.", "audio": "/zhanghaomin/datas/musiccap/music_data/lPFsijo8xYs.wav"} +{"id": "lR8am4rK7qQ", "caption": "Male and female singers sing this vocal harmony. The song is medium tempo with a groovy bass-line, keyboard accompaniment, guitar rhythm and a steady drumming rhythm with clapping percussions. The song is exciting and groovy. The song is a classic pop hit cover with an average quality sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/lR8am4rK7qQ.wav"} +{"id": "lRC2lurjPBw", "caption": "This is a recording of bells with a resonant sound. The sound induces a calming, relaxing effect. This piece would suit perfectly as a background track for a meditation video. It could also be playing in the background at a spa.", "audio": "/zhanghaomin/datas/musiccap/music_data/lRC2lurjPBw.wav"} +{"id": "lRTeWmoeen4", "caption": "This is a reggaeton/latin pop piece in the chipmunk style. There is a melodic pad and a keyboard playing the melody. The rhythmic background consists of an electronic drum beat. There is a comedic atmosphere. This piece could be used in the background of funny social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/lRTeWmoeen4.wav"} +{"id": "lSb7Y-_3to8", "caption": "This is a classical music piece performed on the claviorgan instrument. The piece has a mellow atmosphere with a unique sound. This piece could be used in the soundtrack of a historical drama TV series during the scenes where the characters are walking inside the royal courtyard. The piece could also be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/lSb7Y-_3to8.wav"} +{"id": "lSbCqHZy_l4", "caption": "The low quality recording features a fruity male vocal talking, after which he starts singing over harmonizing choir, groovy bass, mellow piano melody, shimmering cymbals, punchy kick, punchy tom and snappy rimshots. It sounds emotional, soulful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/lSbCqHZy_l4.wav"} +{"id": "lTAfSpsyTSI", "caption": "This symphonic song features the string section and brass section playing the main melody. The instruments are playing different parts in harmony. At the beginning, the instruments play a two note descending sequence in which the second note is allowed to ring. Then one note is played and allowed to sustain for six counts followed by a bass note that is played for the remaining counts. A snare plays a pattern during this last sustain. A cymbal is also played at the end of this phrase. There are no voices in this song. This is an instrumental song. This song can be played in a movie about a voyage.", "audio": "/zhanghaomin/datas/musiccap/music_data/lTAfSpsyTSI.wav"} +{"id": "lTLsL94ABRs", "caption": "This is the live performance of an Ethiopian folk music piece. There is a female vocalist singing melodically at the forefront while clapping the beat. The tune is being played by an Ethiopian one-string chordophone called masenqo. There is an authentic and cheerful atmosphere. The sound is minimalistic. This piece could be playing in the background at a coffee house or an Ethiopian cuisine restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/lTLsL94ABRs.wav"} +{"id": "lTOzGIOIfq0", "caption": "The song is a movie soundtrack. Violins play in a mysterious harmony while ambient room noises are heard. Groaning, screams of agony, shouts, metal cupboards falling, glass shattering and wrecking noses are heard. The track is an animated movie sound track and of poor quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/lTOzGIOIfq0.wav"} +{"id": "lTuEsrVV6Uw", "caption": "This is an instrumental percussion piece performed by an orchestra. There is a marimba playing the main melody at the forefront while bell percussion adds texture around it. There is a timpani that plays a loud drum line that is accentuated by occasional cymbal hits. The atmosphere is lighthearted. This piece would fit perfectly in the soundtrack of an arcade video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/lTuEsrVV6Uw.wav"} +{"id": "lUp9WnLYetg", "caption": "The song is an instrumental. The tempo is medium with an aborigine playing a didgeridoo and a tapping rhythm in a percussive manner. The audio quality is bad with ambient crowd talking sounds. The music is traditional and deeply meditative in nature.", "audio": "/zhanghaomin/datas/musiccap/music_data/lUp9WnLYetg.wav"} +{"id": "lV0-LMVpZLg", "caption": "This pop ballad features two male voices singing in octaves. This is accompanied by percussion playing a simple beat. A bass plays the root notes of the chords. A piano plays the chords by striking them just once per bar. When the voice pauses between verses, another voice sings descending pattern vocables in falsetto. When the main voice resumes, a synth fill is played along with a muted guitar. The rest of the instruments continue to play their respective parts. This song has a romantic mood. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/lV0-LMVpZLg.wav"} +{"id": "lXrypwLQO3U", "caption": "The Disco song features a passionate female vocalist singing over a funky electric guitar melody, groovy bass, punchy kick and claps. It sounds passionate, funky and groovy - like something you would hear in clubs during the 80s.", "audio": "/zhanghaomin/datas/musiccap/music_data/lXrypwLQO3U.wav"} +{"id": "lYJAqOpp6RM", "caption": "This is a middle eastern pop song, with traditional elements such as the habban. The percussion is also traditional and may involve the use of a bendir. The singer sounds calm and has some autotune applied to his vocal.", "audio": "/zhanghaomin/datas/musiccap/music_data/lYJAqOpp6RM.wav"} +{"id": "lYtoy8sa-Q0", "caption": "This audio contains someone playing a melody on an organ in the mid- to higher range. This song may be playing in a church.", "audio": "/zhanghaomin/datas/musiccap/music_data/lYtoy8sa-Q0.wav"} +{"id": "lZavPVn7O4Q", "caption": "This is the remix of an Original Pilipino Music (OPM) Christmas song. The female vocalist is singing melodically and in a festive manner. The melody is being played by a strings section while the rhythm consists of an electronic drum beat with heavy usage of percussive elements. The atmosphere is cheerful. This piece could be played at Christmas events in the Philippines.", "audio": "/zhanghaomin/datas/musiccap/music_data/lZavPVn7O4Q.wav"} +{"id": "laVgKAcv8XA", "caption": "The low quality recording features a synth wave disco instrumental that consists of punchy \"4 on the floor\" kick patter, reverberant snare hits, shimmering hi hats, widely spread high pitched synth lead, groovy synth bass and repetitive percussive element. It is noisy, but also energetic and groovy- like something you would hear in a disco club.", "audio": "/zhanghaomin/datas/musiccap/music_data/laVgKAcv8XA.wav"} +{"id": "lbB2VQYIMo0", "caption": "This is a dance music compilation. There is a variety of music pieces ranging from pop to electronic to folk. The sounds made by the shoes of the dancers can also be heard. The atmosphere is rather random. Parts of this recording could be lifted as samples to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/lbB2VQYIMo0.wav"} +{"id": "lePP2BaZhJU", "caption": "This pop rock song features a guitar riff being played. This guitar has a chorus effect added to the sound. Another guitar plays one chord in a three stroke grouping. The bass plays only one note throughout the song. This is accompanied by percussion playing a simple beat in common time. There are no voices in this song. This is an instrumental song. This song can be played in a movie with sports as the focus.", "audio": "/zhanghaomin/datas/musiccap/music_data/lePP2BaZhJU.wav"} +{"id": "leiPemYDg-8", "caption": "This clip feels like a magical fairytale. It features layers of violin that are somewhat orchestral in their arrangement, on top of acoustic guitar arpeggios that cut through the legato violin melodies. At the beginning, there is a warm synth that sounds a little bit like an accordion - rapid chord stabs are played there in eighth notes.", "audio": "/zhanghaomin/datas/musiccap/music_data/leiPemYDg-8.wav"} +{"id": "lfCWGQ6URds", "caption": "This audio contains someone playing a complex and fast rhythm on the tambourine. Also playing percussive. This song may be playing at a traditional ceremony.", "audio": "/zhanghaomin/datas/musiccap/music_data/lfCWGQ6URds.wav"} +{"id": "lh6ACdwNlyk", "caption": "This orchestral music features violins playing the main melody using staccato notes. The volume of the violins increases over time in the song. The bass plays a booming note on the alternate count of every bar. The bass resonates like a heartbeat. A single percussion beat is played on the second count of the second bar. There is the sound of a victory chant in the background. This song is at a slow tempo. This song can be used in the trailer of an epic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/lh6ACdwNlyk.wav"} +{"id": "lhizlCmlbYY", "caption": "This is an instrument which creates sounds that are similar to laser beams. It sounds futuristic and like something that would be heard in a sci-fi movie. There's a slight crackle to the sounds and they are high-pitched.", "audio": "/zhanghaomin/datas/musiccap/music_data/lhizlCmlbYY.wav"} +{"id": "liagR7x12O4", "caption": "Latin electronic music with a Cumbia feel featuring an autotuned male vocal, female vocal response and syncopated drum pattern with a large room ambience which is muffling the music.", "audio": "/zhanghaomin/datas/musiccap/music_data/liagR7x12O4.wav"} +{"id": "liuCTk2nPG8", "caption": "This is a famous disco piece. There are female vocals singing the lyrics joyfully. The main tune is played in major scale by a keyboard while it is supported by a syncopated synth bass in the background. The rhythm is kept by a repetitive electronic drum beat accompanied by percussion. The atmosphere is groovy and danceable. It is perfect for an 80s themed party setlist. It could also be playing in the background of an 80s themed bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/liuCTk2nPG8.wav"} +{"id": "lmrzR9cSMRY", "caption": "An acoustic piano is playing a melody along with a flute-sound and an acoustic guitar picking two notes repeatedly. Then the song breaks softly into a new part as the acoustic guitar and piano are fading out. In the background you can hear some insects chirping. Now an electric piano sound is playing a melody along with a male voice singing. His voice sounds sensitive. This song may be playing for a movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/lmrzR9cSMRY.wav"} +{"id": "lnJdWXRgjKo", "caption": "The song is an instrumental. The tempo is slow with a strong bass line, guitar accompaniment, violin accompaniment and Arabic horn instrument playing melancholic. The song is sad and tragic. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/lnJdWXRgjKo.wav"} +{"id": "lnYOC9tKUBs", "caption": "A synthesizer lead sound is being played loudly and not in tune with the background music that sounds like a folklore song. This song may be playing at home practicing.", "audio": "/zhanghaomin/datas/musiccap/music_data/lnYOC9tKUBs.wav"} +{"id": "lnnlghshsVo", "caption": "The low quality recording features a live performance of a bagpipes melody. It sounds traditional, passionate and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/lnnlghshsVo.wav"} +{"id": "loyHHBilYPM", "caption": "The low quality recording features a steel drums melody played over punchy kick and snare hits, shimmering hi hats and groovy bass. It sounds exotic and joyful. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/loyHHBilYPM.wav"} +{"id": "lpHa-S_x1LA", "caption": "This classical Hindustani song features the sitar playing the main melody. Open strings are continuously played with fretted strings providing the main melody of this song. This is accompanied by a tabla playing a classical rhythm. There are no other instruments in this song. There are no voices in this song. This song can be played for an Indian traditional dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/lpHa-S_x1LA.wav"} +{"id": "lqCx0HgF1ZM", "caption": "This is an acoustic performance of a k-pop piece. The lead is a male vocal that is singing gently and melodically in the Korean language. He is also playing an acoustic guitar as the melodic background of the piece. The song is in the major scale which gives it this positive and uplifting aura. This piece could be used in the soundtrack of a coming-of-age/teenage drama TV series that takes place in Korea. It could also be playing in the background of a coffee house.", "audio": "/zhanghaomin/datas/musiccap/music_data/lqCx0HgF1ZM.wav"} +{"id": "lqeAf-DqE3I", "caption": "The song is an instrumental. The song is medium tempo with steel pan playing melody, guitar strumming and steady percussion rhythm. The song is exciting and calming. The song is a live band performing tropical Caribbean tunes.", "audio": "/zhanghaomin/datas/musiccap/music_data/lqeAf-DqE3I.wav"} +{"id": "lrk00BNiuD4", "caption": "A male vocalist sings this soft melody. The tempo is medium with smooth guitar, keyboard harmony, steady bass slide and synthesiser arrangements. The song is mellow, romantic, emotional, soothing; ambient. There is a hooting sound like a fog horn with a male voice talking over the song. This song is a R&B/Soul song.", "audio": "/zhanghaomin/datas/musiccap/music_data/lrk00BNiuD4.wav"} +{"id": "ltZCJ7aPtO0", "caption": "An acoustic piano is playing a ballad with a lot of chord changes and a male voice singing in the higher register. The whole song sounds slightly sad or sensitive. The audio-quality is very bad, it is not very clear to hear if there are other instruments playing in the background. Also is the recording full of big reverb as being played in a big hall. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/ltZCJ7aPtO0.wav"} +{"id": "ltysCJWnvsI", "caption": "A male vocalist sings this spirited song. The tempo is medium fast with enthusiastic trumpet, funky keyboard harmony, groovy bass lines, slick drumming and piano accompaniment. The song is simple,spirited, enthusiastic, energetic and buoyant. This song is an R&B/Soul.", "audio": "/zhanghaomin/datas/musiccap/music_data/ltysCJWnvsI.wav"} +{"id": "lvktro0asjs", "caption": "The Pop song features a flat male vocal, alongside wide harmonizing background vocals, singing over punchy kick and snare hits, shimmering hi hats, energetic crash cymbals, groovy piano chords and widely spread acoustic guitar melody. It sounds smooth, uplifting and addictive thanks to those harmonizing vocals.", "audio": "/zhanghaomin/datas/musiccap/music_data/lvktro0asjs.wav"} +{"id": "lwQVcLxFBIQ", "caption": "A male voice is singing in the mid range accompanied by acoustic drums with a groove on the ride cymbal and a bass playing a simple line. In the background you can hear a keyboard playing short chords while a trumpet is playing its own melody at the end of the singer's phrases. This song may be playing in a repair workshop.", "audio": "/zhanghaomin/datas/musiccap/music_data/lwQVcLxFBIQ.wav"} +{"id": "lwdDm3UO5WM", "caption": "The low quality recording features a live performance of a traditional song and it consists of passionate female vocal singing over subtle strings melody. It is a bit reverberant as it was recorded in a larger room, but also relaxing and calming - like something you would meditate to.", "audio": "/zhanghaomin/datas/musiccap/music_data/lwdDm3UO5WM.wav"} +{"id": "lymmNwQA0WA", "caption": "This song contains a fast drum&bass drum that gets supported by a bass and a synthlead sound on top of it. Both play the same melody. Some different samples get drowned in. They sound like dog-barks that have been processed with effects and a lower bitrate. In the background different sound-effects are rising up in pitch. This song sounds hectic and energetic. This song may be playing in a dance club.", "audio": "/zhanghaomin/datas/musiccap/music_data/lymmNwQA0WA.wav"} +{"id": "m--xEFqqrLc", "caption": "The song is an instrumental. The song is medium tempo with a tenor saxophone playing a lilting melody in legato style. The song has no other instrumentation support. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/m--xEFqqrLc.wav"} +{"id": "m-NM_tIWjxs", "caption": "This song contains a four on the floor kick with a monotone and simple bassline. This song is produced in lower sound quality and the recording is clipping a little bit. This song may be played at a private houseparty.", "audio": "/zhanghaomin/datas/musiccap/music_data/m-NM_tIWjxs.wav"} +{"id": "m-S-yqzlOj4", "caption": "The Electro song features a \"4 on the floor\" kick pattern, punchy snare, claps, groovy bass, metallic percussion and repetitive male vocal singing over it. It sounds groovy and energetic - like something you would hear in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/m-S-yqzlOj4.wav"} +{"id": "m-e3w2yZ6sM", "caption": "A male singer sings this rock melody. The tempo is medium with a groovy bass line, guitar rhythm , keyboard accompaniment, and heavy rock drumming with cymbals crashing. The song is energetic and passionate. The song is a retro pop-rock song.", "audio": "/zhanghaomin/datas/musiccap/music_data/m-e3w2yZ6sM.wav"} +{"id": "m-eyGzf9Ux4", "caption": "This is a Christian gospel music piece. There is a female vocalist singing melodically. An acoustic guitar and an electric guitar are playing in the melodic background. The atmosphere is religious. This piece could be used as a background music for Christian social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/m-eyGzf9Ux4.wav"} +{"id": "m-xxD1fGPnU", "caption": "This is an alternative rock piece. There is a male vocal singing at a low-to-medium pitch. There is a groovy electric guitar riff playing the main melody. There is a strong bass guitar playing alongside it. In the rhythmic background, there is a simple acoustic drum beat. There is a generic, urban atmosphere. This piece could be used in advertisement jingles and in the soundtracks of teenage drama movies and TV shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/m-xxD1fGPnU.wav"} +{"id": "m0FhT3UnXjA", "caption": "Someone is playing high single long notes on a harmonica along to a metronome sound. Then a male voice starts speaking. This audio may be playing as a harmonica tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/m0FhT3UnXjA.wav"} +{"id": "m1ov6te6jK8", "caption": "This song features a male voice singing the main melody. The instruments lend an Indian tonality to the song. The song starts with a flute solo backed by a tabla and a stringed instrument that sounds like a santoor. This is followed by a violin solo backed by the tabla as percussion. The bass plays the root notes of the chords. The male voice starts singing after the violin solo. This song has a gospel feel. The voice is mellow and carries emotion.", "audio": "/zhanghaomin/datas/musiccap/music_data/m1ov6te6jK8.wav"} +{"id": "m3uiITzeM70", "caption": "A male vocalist sings this spirited song. The tempo is fast with a fast keyboard harmony, boomy bass line, rhythmic drums, steel drums,congas and bongos, cymbal ride and sound of clapping. The song is upbeat, punchy, buoyant, spirited, energetic and youthful with a dance groove. This song is Latin Urbano.", "audio": "/zhanghaomin/datas/musiccap/music_data/m3uiITzeM70.wav"} +{"id": "m4Dj_vTsAt0", "caption": "The low quality recording features a hip hop song that consists of synth keys melody, punchy kick, punchy muffled snare, shimmering open hat and shakers and short toms roll. It sounds groovy and easygoing, like something you would listen to when riding a car.", "audio": "/zhanghaomin/datas/musiccap/music_data/m4Dj_vTsAt0.wav"} +{"id": "m4bBsvuS4EU", "caption": "The song's instrumental tempo is slow with various percussive hits, harp playing and a French horn playing a gentle yet strong melody. The song is emotional and full of hope. The song is an adventure movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/m4bBsvuS4EU.wav"} +{"id": "m7i4g_o-znQ", "caption": "This is a high-octane blues song, with layers of intricate bluesy acoustic guitar playing. There's a slide guitar involved, and other layers of potent intense guitar playing. There's a distant filtered vocal hum which sounds like it is coming through a telephone.", "audio": "/zhanghaomin/datas/musiccap/music_data/m7i4g_o-znQ.wav"} +{"id": "m8-aK8egg84", "caption": "Solo harmonica playing blues licks, followed by a male voiceover.", "audio": "/zhanghaomin/datas/musiccap/music_data/m8-aK8egg84.wav"} +{"id": "m8poFnEbvW8", "caption": "The low quality recording features distorted electric guitar chords playing over rock songs played on playback. It sounds messy and harsh, as the frequencies of the room and the actual sound of the guitar and song are clashing with each other.", "audio": "/zhanghaomin/datas/musiccap/music_data/m8poFnEbvW8.wav"} +{"id": "m9MQdg0k1t0", "caption": "A male singer sings with a female backup singer in vocal harmony. The song is medium tempo with a yodelling medley and guitar strumming rhythm and no other instrumentation. The song is exciting and passionate. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/m9MQdg0k1t0.wav"} +{"id": "m9tnNkon_iw", "caption": "This clip is a sound of scratching or scraping using binaural sound. The effect is a 3D stereo sound sensation. The sounds are clear and lucid as if hearing it live. This clip is a demonstration of Binaural sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/m9tnNkon_iw.wav"} +{"id": "mAmaUI7_uZ0", "caption": "Amateur produced hip hop music with out of tune male and female vocals and amateur vocal production. The backing track is a trap beat with a synthesizer arpeggio.", "audio": "/zhanghaomin/datas/musiccap/music_data/mAmaUI7_uZ0.wav"} +{"id": "mB2FAS0DNkk", "caption": "The low quality recording features a live performance of a pop song that contains flat male vocals talking on a microphone over a song played on playback and some crowd cheering noises. The song consists of a \"4 on the floor\" kick pattern, energetic cymbals, groovy synth bass, claps and synth lead melody. It sounds happy, joyful and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/mB2FAS0DNkk.wav"} +{"id": "mBG-st0VUXs", "caption": "A solo trumpet playing an energetic staccato melody with dramatic glissandi. The trumpet has been processed to add a stereo delay effect and reverb. The tone is very bright.", "audio": "/zhanghaomin/datas/musiccap/music_data/mBG-st0VUXs.wav"} +{"id": "mBNdDQamtXA", "caption": "This is a multitrack acapella cover of a rock opera music piece. The same vocalist is singing different harmonies in separate tracks to create the aura of a magical experience. Usage of multiple tracks creates a vibrant atmosphere.", "audio": "/zhanghaomin/datas/musiccap/music_data/mBNdDQamtXA.wav"} +{"id": "mBRr_TqLDf4", "caption": "This classic pop song features a female voice singing the main melody. This is accompanied by electronic drums playing the snare. The snare is played alternating between 1 beat and two beats for every count in each bar. The bass plays a groovy lick using the root notes of the chords. Hand caps are played at different intervals in this song. At the end, a synth plays a chord, a lower chord and back to the first chord. This song has a happy feel. This song can be played in a retro movie scene involving a casino.", "audio": "/zhanghaomin/datas/musiccap/music_data/mBRr_TqLDf4.wav"} +{"id": "mCjsuxzcl2k", "caption": "This music is a Chinese instrumental. It has a fast tempo with energetic Chinese big drums, Chinese cymbals called zhongcha,and a string instrument accompaniment. The music is spirited, enthusiastic, ceremonial, celebratory and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/mCjsuxzcl2k.wav"} +{"id": "mFcHGbnNtSQ", "caption": "The low quality recording features a live performance of a jazz song and it consists of a passionate female vocalist singing over groovy piano melody, saxophone melody, groovy bass, shimmering hi hats, punchy snare and soft kick hits. It sounds passionate, soulful and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/mFcHGbnNtSQ.wav"} +{"id": "mFp1nrnlGx4", "caption": "The low quality recording features a cajon percussive rhythm played, after which there is a flat male vocal talking. It is noisy, mono, reverberant and it sounds like a tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/mFp1nrnlGx4.wav"} +{"id": "mGU4ZRstxpY", "caption": "This slow rock song features a male voice singing the main melody. This is accompanied by other voices singing vocables in the background. The percussion plays a simple beat in common time. The bass plays the root notes of the chords. A synth plays a repetitive chord in staccato. A piano plays some high pitched notes in between lines. This song can be played in a movie scene at a harbour at night.", "audio": "/zhanghaomin/datas/musiccap/music_data/mGU4ZRstxpY.wav"} +{"id": "mJuJfKbcJcw", "caption": "A male vocalist sings this dulcet melody. The tempo is soft with acoustic guitar, resonator, fiddle, mandolin, banjo, dobro and auto harp accompaniment, steady drumming, tambourine beats , fingers snapping and funky bass lines. The song is soft, mellow, dulcet, emotional, sentimental, soothing , pleasant and simple. The song is Country Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/mJuJfKbcJcw.wav"} +{"id": "mKIapkfnAGY", "caption": "This audio contains two people playing accordion. One is playing the foundation as rhythmical chords while the other person is playing the lead melody in a higher pitch. This song may be playing live in the countryside.", "audio": "/zhanghaomin/datas/musiccap/music_data/mKIapkfnAGY.wav"} +{"id": "mLaon9oK1OA", "caption": "This is a latin pop song with a chipmunk effect. There is a female and a male vocal singing melodically but at a higher pitch than the original. An acoustic guitar and a bass guitar play in the melodic background while a latin electronic drum beat is in the rhythmic background. The piece is very danceable. The piece could be used at a children's dancing course as an accompaniment. It could also be used in the background of funny social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/mLaon9oK1OA.wav"} +{"id": "mLm8upEhc_s", "caption": "This song is an instrumental. The tempo is low with a keyboard harmony at the onset, followed by a bit of white noise. There are sounds of hissing,beeping, rattling, water splashing, thudding and frog croak. The sounds are synth articulations.", "audio": "/zhanghaomin/datas/musiccap/music_data/mLm8upEhc_s.wav"} +{"id": "mMT1kEejAG8", "caption": "low fidelity recording of a solo electric guitar with a distorted tone playing fast notes with aggressive vibrato and whammy bar for dive bombs. The mood is frenetic and wild. The style would fit in an 80's heavy metal band.", "audio": "/zhanghaomin/datas/musiccap/music_data/mMT1kEejAG8.wav"} +{"id": "mMf4vJFT8Fw", "caption": "This is an instructive track to tune a guitar at double drop D tuning. A repeated single note for each string is being played. This track could be used for unnatural sounding guitar samples.", "audio": "/zhanghaomin/datas/musiccap/music_data/mMf4vJFT8Fw.wav"} +{"id": "mOFyRCMlXIo", "caption": "This clip brings about the sensation of building up to something. It features an arpeggiated melody on the piano, and timpani drum rolls. The audio quality is low.", "audio": "/zhanghaomin/datas/musiccap/music_data/mOFyRCMlXIo.wav"} +{"id": "mOmYcOBqhwo", "caption": "The low quality recording features a groovy tabla percussion playing. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/mOmYcOBqhwo.wav"} +{"id": "mOn13E68Td0", "caption": "A male singer sings in an animated manner. The song is medium fast tempo with a steady drumming rhythm, brass band accompaniment, groovy bass line and guitar strumming rhythm. The song is exciting and cheerful. The song is an animated children\u2019s show tune, but a poor recording of the actual show.", "audio": "/zhanghaomin/datas/musiccap/music_data/mOn13E68Td0.wav"} +{"id": "mPaRs96jtFY", "caption": "The low quality recording features an electric guitar tuning. The recording is gated so every time the guitar string is plucked it is very noisy, while in-between it is a complete silence.", "audio": "/zhanghaomin/datas/musiccap/music_data/mPaRs96jtFY.wav"} +{"id": "mQ1E8rx2dnI", "caption": "The low quality recording features a cover of a regional Mexican song and it consists of harmonizing female vocals singing over a mellow harp melody and flamenco acoustic guitar melody. It sounds raw, emotional and passionate. The recording is a bit noisy and there are some car rev noises in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/mQ1E8rx2dnI.wav"} +{"id": "mQM3Fd3eN9E", "caption": "The low quality recording features a song that consists of harmonized children vocals singing over bouncy snare, saxophone solo melody, groovy bass, shimmering open hats and \"4 on the floor\" kick pattern. There are some laughing, high pitched tire screeches and car engine sound effects in the background. The recording is very noisy and the song is quiet and thin, as it lacks bass frequencies, but it still sounds fun and happy - like something you would hear in TV shows for kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/mQM3Fd3eN9E.wav"} +{"id": "mQWht9mv7sE", "caption": "A synth is playing an arpeggio pluck with a lot of reverb rising and falling in velocity. Another synth sound is playing pads and a sub bassline. This song is full of synth sounds creating a soothing and adventurous atmosphere. This song may be playing at a festival during two songs for a buildup.", "audio": "/zhanghaomin/datas/musiccap/music_data/mQWht9mv7sE.wav"} +{"id": "mRKud6yP4iU", "caption": "The low quality recording features a traditional song that consists of a passionate woodwind melody playing over wide sustained strings, acoustic guitar chords and dissonant string melody. It sounds joyful, weird and hypnotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/mRKud6yP4iU.wav"} +{"id": "mU6cfEWw5Og", "caption": "The low quality recording features a flat male vocal talking, after which there is a shimmering tambourine being played. The recording is noisy and the stereo image is unbalanced, as the audio is slightly leaning towards the right channel of the stereo image.", "audio": "/zhanghaomin/datas/musiccap/music_data/mU6cfEWw5Og.wav"} +{"id": "mW0B1sipLBI", "caption": "This is the cover of a neo-soul/funk music piece. The vocal track of the original piece is replaced by a theremin playing the main melody. The keyboard and the electric guitar are playing in the melodic background. The rhythmic background consists of a medium tempo electronic drum beat. The atmosphere is groovy. There is an interesting feel to it. This piece could be used in the soundtrack of a cartoon or an animation movie. It could also work well as a background music for intriguing social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/mW0B1sipLBI.wav"} +{"id": "mW5_chAgg8c", "caption": "The low quality recording features an acoustic rhythm guitar being aggressively strummed, while producing some happy sounding melodies. The guitar sounds a bit hollow, almost as if it is recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/mW5_chAgg8c.wav"} +{"id": "mWL9_WIbykw", "caption": "This is a synthwave music piece. It is an instrumental piece. There is an analog sounding synth playing a mellow tune. An overall feeling of nostalgia can be felt from this piece. It could be used in the soundtrack of a drama movie that is about a protagonist who cannot adapt to modernity.", "audio": "/zhanghaomin/datas/musiccap/music_data/mWL9_WIbykw.wav"} +{"id": "mWuX--EEq2E", "caption": "This is a live performance of a Greek folk music piece. There is an orchestra performing the piece. There is a floghera flute playing the main tune while the oud and the bass guitar are playing in the background. The rhythm is being played by the acoustic drums. After the shout coming from a male voice, the orchestra starts accelerating. The atmosphere is lively. This piece could be playing in the background at a seaside Greek tavern.", "audio": "/zhanghaomin/datas/musiccap/music_data/mWuX--EEq2E.wav"} +{"id": "mZNNWTrvGoA", "caption": "This is a trombone performance piece for an audition. The tune being played resembles something that would be heard at the royal court of a western kingdom. The atmosphere is dramatic. This piece could be used in the soundtrack of a historical drama movie, especially during the scenes where the king is attending a feast.", "audio": "/zhanghaomin/datas/musiccap/music_data/mZNNWTrvGoA.wav"} +{"id": "maZ3b5w6xVI", "caption": "The low quality recording features a loud church bells playing. The recording is in mono and it is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/maZ3b5w6xVI.wav"} +{"id": "macnXLRXbHU", "caption": "The low quality recording features a harmonica solo melody over soft double bass and arpeggiated acoustic guitar melody. It sounds emotional, passionate and heartfelt.", "audio": "/zhanghaomin/datas/musiccap/music_data/macnXLRXbHU.wav"} +{"id": "maeSHVZX8xc", "caption": "The low quality recording features a gospel song that contains a harmonizing mixed vocals singing. The recording is a bit noisy and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/maeSHVZX8xc.wav"} +{"id": "mcAsO331Z9s", "caption": "This music is an upbeat instrumental. The tempo is fast with a plethora of instruments like trumpets, congas, bongos, steel drum, accordion,saxophone, keyboard,and electric guitar. The music is perky, buoyant, high spirited, enthusiastic, energetic with complex harmonies. This music is a contemporary take in Traditional Latin folk music.", "audio": "/zhanghaomin/datas/musiccap/music_data/mcAsO331Z9s.wav"} +{"id": "mdOZIOc8SA4", "caption": "This song contains a lot of synth pad and drone sounds creating a meditative atmosphere. Then a deep soft bass sound comes in. A piano is playing a slow melody with a lot of reverb. A flute sound is playing a simple melody on top and a pluck instrument is playing another short melody. Then a digital female choir sounding pad comes in. This song may be playing during a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/mdOZIOc8SA4.wav"} +{"id": "merGvga39Yo", "caption": "The song is an instrumental. The tempo is medium fast with a guitar playing lead with a guitar effects pedal producing a distorted grunge tone. The song is energetic and passionate with no other instrumentation. The song audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/merGvga39Yo.wav"} +{"id": "mfZMcNmLxWM", "caption": "This music clip is an instrumental with gamelan instrumental lead along with a hand percussion. The tempo is medium with melodic sounds and harmony from the striking of metal bowls or plates. The music is soft, melodious, calming, engaging and interesting and sounds a lot like a xylophone.", "audio": "/zhanghaomin/datas/musiccap/music_data/mfZMcNmLxWM.wav"} +{"id": "mhqHHQ1gSvM", "caption": "Heavily distorted with poor audio quality, this low fidelity music features syncopation and odd meters, a repetitive tom tom drum, electric bass guitar, synthesized brass sounds, a male singer, and an international flavor. Sounds like it could be middle eastern or south Asian.", "audio": "/zhanghaomin/datas/musiccap/music_data/mhqHHQ1gSvM.wav"} +{"id": "mhru3GXbkHY", "caption": "The low quality recording features an orchestral music that consists of a wide string melody, followed by mellow brass, wide brass melody and shimmering cymbals. It sounds suspenseful and intense - like something that you would hear in the background of a movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/mhru3GXbkHY.wav"} +{"id": "mixc4NV5IBE", "caption": "This instrumental is an EDM. The tempo is fast with drum machine beats and electronically produced music and sounds.The audio quality is inferior, however the beat melody can be heard. The music is youthful, pulsating, enthusiastic, electric, repetitive, insistent,recurring,trippy , hypnotic, and psychedelic. The thumpy bass and punchy drum beats give it a high energy Dance vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/mixc4NV5IBE.wav"} +{"id": "mjZylz3nCwQ", "caption": "The low quality recording features an orchestral music played by wide violin melody and low cello. It sounds emotional and passionate - like something you would hear in old cartoons.", "audio": "/zhanghaomin/datas/musiccap/music_data/mjZylz3nCwQ.wav"} +{"id": "mlpTCec4igo", "caption": "The low quality recording features a country song that contains harmonizing vocals singing over electric guitar solo melody, smooth bass guitar, acoustic rhythm guitar, snappy rimshots, shimmering hi hats and soft kick hits. It sounds soulful, emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/mlpTCec4igo.wav"} +{"id": "mlrarQ5nVlU", "caption": "The low quality recording features a live performance of a classical song that consists of a woodwinds melody, sustained strings melody and double bass melody. It sounds passionate and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/mlrarQ5nVlU.wav"} +{"id": "mnSP_ONVS7k", "caption": "This is an indie rap/hip-hop music piece. There is male voice rapping rapidly over a beat. The beat has a plucked strings sample for the melody. The rhythmic background is a normal tempo hip-hop beat played on the acoustic drums. There is also a speech sample used in the beat. The atmosphere is groovy and crisp. This piece would fit perfectly in the soundtrack of a crime movie/TV series that takes place in the big city. It could also be used in the soundtrack of a crime/shootout video game. It could be playing at sports venues as well.", "audio": "/zhanghaomin/datas/musiccap/music_data/mnSP_ONVS7k.wav"} +{"id": "mpikDeSk-mM", "caption": "A female singer sings this cool dance melody. The song is medium-fast tempo with a cool dance groove, percussive bass line, steady dance rhythm, keyboard accompaniment and various percussion hits. The song is groovy and proper electronic dance music hit,", "audio": "/zhanghaomin/datas/musiccap/music_data/mpikDeSk-mM.wav"} +{"id": "mpymEs4Mcw8", "caption": "This African beat song features a male voice singing the main melody. Other voices sing one word after each line. This is accompanied by percussion playing an African dance beat. The bass plays a groovy bassline. A flute plays the same melody as the main voice. This song has a happy mood. This song can be played in a dance party.", "audio": "/zhanghaomin/datas/musiccap/music_data/mpymEs4Mcw8.wav"} +{"id": "mq_b6QKVsuc", "caption": "A female vocalist sings this soft melody. The tempo is slow with acoustic guitar accompaniment. The guitar sound is muffled. The song is sad,poignant, melancholic, sentimental,emotional and lonely. This song is Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/mq_b6QKVsuc.wav"} +{"id": "mqyeBqaUeN8", "caption": "This is a Brazilian samba piece used as a jingle. The male vocals are singing in a shouting-like manner, repeating a slogan. There is a heavy use of syncopated latin percussion in the rhythmic background. The acoustic guitar and the bass guitar in the background support the melodic structure of the vocals.", "audio": "/zhanghaomin/datas/musiccap/music_data/mqyeBqaUeN8.wav"} +{"id": "msnm_tYXcYw", "caption": "This audio contains someone playing a melody on steeldrums along to a backing track containing an e-bass playing a melody along with an e-guitar. A kick is being played on every beat. This song may be played on the streets by a busker.", "audio": "/zhanghaomin/datas/musiccap/music_data/msnm_tYXcYw.wav"} +{"id": "mtapmFDmImA", "caption": "Here we have a pair of differently calibrated Tibetan bowls being played. They sound similar to bells and they create a high pitched resonating sound after the initial transient hit. The sounds are relaxing and would be suitable for a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/mtapmFDmImA.wav"} +{"id": "mu0dlj8ibA4", "caption": "The low quality recording features an organ keys melody played over playback instrumental that consists of groovy bass, plucked melody and some wooden percussion. It sounds weird, bouncy, happy and the recording is very noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/mu0dlj8ibA4.wav"} +{"id": "muwIU0BHXE0", "caption": "A kids voice is singing along to a funky bassline and little trumpet slides along with sound effects that could belong to a tv show. This audio is an amateur recording and of poor audio-quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/muwIU0BHXE0.wav"} +{"id": "mvZLlJpyDyc", "caption": "A female vocalist sings this ethereal melody. The tempo is slow with a beautiful flute harmony, melodious piano accompaniment, Arabic guitar and groovy bass lines. The song has no lyrics with ethereal vocalisation. It is soft, mellifluous, calming, pleasant,enigmatic, celestial and ethereal with a middle eastern feel.", "audio": "/zhanghaomin/datas/musiccap/music_data/mvZLlJpyDyc.wav"} +{"id": "mwLrABPxvgA", "caption": "The low quality recording features a live performance of steel drums. It sounds exotic, passionate and emotional, even though the recording is noisy and has some audio popping sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/mwLrABPxvgA.wav"} +{"id": "mwqluX7sXXU", "caption": "This music is a Jazz instrumental. The tempo is medium fast with lively trumpets, groovy bass lines, infectious drumming, sound of bells and chimes at the end followed by the voice of a female speaking. The music is spirited, ambient, complex, fun, informal, active,smooth and airy and emphatic.", "audio": "/zhanghaomin/datas/musiccap/music_data/mwqluX7sXXU.wav"} +{"id": "mwwnfWgV_5U", "caption": "This is a power metal/speed metal music piece. The melody is being performed by the distorted electric guitar and the keyboard while the bass guitar is playing in the background. The rhythmic background consists of a loud metal acoustic drum beat. The atmosphere is aggressive and upbeat. This music would suit perfectly in the soundtrack of an adventure video game. It could also work well in the soundtrack of an action-filled cartoon series.", "audio": "/zhanghaomin/datas/musiccap/music_data/mwwnfWgV_5U.wav"} +{"id": "mx7kjFY7ALs", "caption": "A male vocalist sings this Classical song. The tempo is fast with animated ghatam, mridangam and tabla accompaniment and violin harmony. The vocals are classical notes and lyrics in a South Indian language. The song has three layers, the melody, percussion and drone. This song is a devotional Carnatic Classical song.", "audio": "/zhanghaomin/datas/musiccap/music_data/mx7kjFY7ALs.wav"} +{"id": "myGef3nriL8", "caption": "This is an instructive recording about body percussion. In the beginning, there is a backing track that has the sitar and the tabla in it. Then, the music stops and a boy starts talking about body percussion in the Italian language. The part where the backing track is playing could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/myGef3nriL8.wav"} +{"id": "myGffB4WcF8", "caption": "This is a classical music piece. It is being performed on the harpsichord. The piece is in the minor key. The atmosphere is gentle and it has a medieval sound. This piece could be used in the soundtrack of a medieval era historical drama TV series during the scenes where the characters are taking a stroll through the meadows.", "audio": "/zhanghaomin/datas/musiccap/music_data/myGffB4WcF8.wav"} +{"id": "mzDq-abtAKs", "caption": "This song is an electronic instrumental. The audio quality is poor so the music is incoherent. The song has an electronic harmony, slick drumming, dissonant buzzing and bubbling sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/mzDq-abtAKs.wav"} +{"id": "n16ZUTfZtDM", "caption": "The low quality recording features an ambient song that consists of a wide mellow synth pad and echoing bells. It sounds relaxing, calming and easygoing.", "audio": "/zhanghaomin/datas/musiccap/music_data/n16ZUTfZtDM.wav"} +{"id": "n179cK8EubU", "caption": "This is a gear showcase jam. There is a male voice talking in between the sounds giving information about a reverb pedal. There is an electric guitar playing random tunes with the reverb effect. The tunes in the recording are simple. Sounds from this recording could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/n179cK8EubU.wav"} +{"id": "n1HBKct6rto", "caption": "This music is a lively EDM. The tempo is fast with heavy synthesiser articulation, insistent tambourine beats,punchy digital drum arrangements, heavy bass and heavily auto tuned vocals. The music is a buoyant, youthful, energetic,pulsating, electrifying EDM.", "audio": "/zhanghaomin/datas/musiccap/music_data/n1HBKct6rto.wav"} +{"id": "n1PTn_NH_K0", "caption": "This is a gear showcase video demonstrating the sound difference when an electric guitar is connected to an amp. The electric guitar is playing simple tunes. A male voice is describing the applied effect. Sounds from this piece can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/n1PTn_NH_K0.wav"} +{"id": "n1fY-23ffl0", "caption": "This song is a pleasant love song duet. The tempo is medium with acoustic guitar and ukulele accompaniment.the song is mellow, soft, emotional, romantic, nostalgic. This song is Country/Folk pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/n1fY-23ffl0.wav"} +{"id": "n3EeS2mVU5w", "caption": "Solo nylon string acoustic guitar played fingerstyle in a flamenco tradition. The guitar has lower bass notes than a regular 6 string guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/n3EeS2mVU5w.wav"} +{"id": "n3QsFeGadEE", "caption": "This song features synth sounds. There is no particular melody. There is no percussion and no voices. This sounds like sounds from outer space. When the first note is played, a ring modulated sound is played in the background. The same pattern is found in the third, fourth and fifth notes. This song can be played in a movie featuring an outer space theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/n3QsFeGadEE.wav"} +{"id": "n3X8RGZsGg4", "caption": "The low quality recording features a hip hop song that consists of groovy bass, groovy piano chords, shimmering hi-hats and punchy kick and snare hits over sword slicing, blood spillage and grunting sound effects. Overall the song is very groovy, bright and judging by the volume of the sounds, it could be an Animated Music Video.", "audio": "/zhanghaomin/datas/musiccap/music_data/n3X8RGZsGg4.wav"} +{"id": "n4PBoAedWVA", "caption": "A male vocalist sings this Soft Rock. The tempo is slow with electronic arrangements,steady drumming, groovy bass line , and syncopated keyboard harmony. The background instruments play a dissonant melody. This song is a mellow, youthful, punchy, buoyant, Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/n4PBoAedWVA.wav"} +{"id": "n4QSYx4wVQg", "caption": "Quirky surf rock music featuring a retro organ playing a simple melody and twangy electric guitar with female background vocals and a male lead vocal. The mood is fun and silly.", "audio": "/zhanghaomin/datas/musiccap/music_data/n4QSYx4wVQg.wav"} +{"id": "n615BjoN7fI", "caption": "A female vocalist sings this vibrant song. The tempo is fast with synthesiser articulation, enthusiastic digital drum beats, electronic arrangements and sound of police siren in the background. The song is youthful, energetic, vivacious, simple, fun, engaging, groovy,with powerful and emphatic vocals. This song is Electro Pop/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/n615BjoN7fI.wav"} +{"id": "n7yLkcSfiuM", "caption": "This low quality recording features an electropop song. At the beginning, there is a shooting sound. This is followed by cartoon voices. A fast paced vocal chop sequence is used for the main voice. Toward the end, another quirky voice joins in with another vocal chop sequence. This is accompanied by programmed percussion playing an electropop beat. A synth plays a repetitive lick. The bass follows the root notes of the chords. This song can be played at a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/n7yLkcSfiuM.wav"} +{"id": "n87PCgYm6mE", "caption": "The low quality recording features an experimental song that consists of wide synth pad chords, wide echoing & shimmering hi hats and filtered echoing acid bass melody that slowly fade in, in the second half of the loop. There are also some subtle crackles, as the recording is a bit noisy. It sounds mystical, hypnotic and haunting.", "audio": "/zhanghaomin/datas/musiccap/music_data/n87PCgYm6mE.wav"} +{"id": "nAKUDXMeWeQ", "caption": "A male African tribal singer sings this melody with female backup singers in vocal harmony. The song is medium tempo with percussive African drums in rhythm and other percussion hits. The song is energetic and devotional in nature. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/nAKUDXMeWeQ.wav"} +{"id": "nB2Lf5TTmBs", "caption": "This is an instrumental meditation music piece. The only instrument being played is a set of Tibetan singing bowls. The bowls are rung at different frequencies, giving resonant sounds. The atmosphere of the recording is calming and relaxing. This piece is the perfect background track for a meditation video or a meditation session at a wellness center. It could also be playing in the background at a spa.", "audio": "/zhanghaomin/datas/musiccap/music_data/nB2Lf5TTmBs.wav"} +{"id": "nBSMh7pgn2o", "caption": "Chipmunk style pitched up male vocals over a slow rock drum beat, sliding electric bass guitar, acoustic guitar and bongos. Heavy use of delay on the vocal.", "audio": "/zhanghaomin/datas/musiccap/music_data/nBSMh7pgn2o.wav"} +{"id": "nBiHncFD0dM", "caption": "This is a traditional middle eastern song from an older era. The recording quality suggests that this is a vintage song. There is a group of children singing the same melody in unison, and then there is a male with a soothing vocal. The song comes in at a medium tempo and is suitable for dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/nBiHncFD0dM.wav"} +{"id": "nEOPm7TeydY", "caption": "The low quality recording features an Eastern pop song that contains echoing autotune male vocal singing over wooden percussion and shimmering shakers. It sounds distorted, crushed, harsh and messy, as it was probably recorded with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/nEOPm7TeydY.wav"} +{"id": "nFkmTa4oY84", "caption": "Whilst this clip is mellow, it feels like the song has a general sense of budding energy. On the bass guitar we have a simple three note motif repeated across different chords. The singer has a seductive, airy and sultry female voice. In the background, we hear an atmospheric, futuristic pad synth.", "audio": "/zhanghaomin/datas/musiccap/music_data/nFkmTa4oY84.wav"} +{"id": "nFoktpUVeVw", "caption": "This song contains a tabla rhythm spread across both sides of the speakers. An acoustic guitar melody panned to the right side of the speakers. Far in the background you can hear clapping as part of the song. A male voice is singing in a higher register than a violin takes over playing a melody in a higher register with reverb and a little delay. This song may be playing in a lovely movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/nFoktpUVeVw.wav"} +{"id": "nH_lVl3a3Uw", "caption": "The instrumental latin music features a big band. The trumpets, saxophones and trombones play the same melody but on different pitches. The percussion section includes a drum kit played in the latin style and a pair of congas. A piano accompanies the brass section and blends in with the rest of the band. An electronic sound can be heard playing the same note throughout the music excerpt.", "audio": "/zhanghaomin/datas/musiccap/music_data/nH_lVl3a3Uw.wav"} +{"id": "nIL_xrqjo1g", "caption": "This is a classical music performance. There is a gentle piano tune playing in the background while there is a theremin playing the main melody. The performance has a unique feel to it. The atmosphere is out of the ordinary but also heart-touching. This piece could be used in the soundtrack of an animation movie/TV series.", "audio": "/zhanghaomin/datas/musiccap/music_data/nIL_xrqjo1g.wav"} +{"id": "nJ3tuDmcdTs", "caption": "This song contains someone playing an accordion melody and chords along with an acoustic guitar strumming the same chords. Someone is playing an acoustic instrument while a male voice is singing in a higher key. This song may be playing in the countryside.", "audio": "/zhanghaomin/datas/musiccap/music_data/nJ3tuDmcdTs.wav"} +{"id": "nJaezskegdc", "caption": "The low quality recording features passionate female harmonizing vocals, alongside wide staccato female vocals melodies singing over some claps. It sounds passionate and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/nJaezskegdc.wav"} +{"id": "nL4zx0-mi14", "caption": "This song is a classical composition played on a harpsichord. This features the notes played on the higher register and the bass notes played on the same instrument. There are no other instruments in this song. This song has no voices. It is an instrumental song. This song can be played to honor royalty.", "audio": "/zhanghaomin/datas/musiccap/music_data/nL4zx0-mi14.wav"} +{"id": "nONXdP6T3pc", "caption": "The low quality recording features a traditional pop song that consists of harmonized vocals singing over breathy flute melody, groovy bass, wooden percussion, strings melody and acoustic guitar chords. It sounds happy and fun - like a song you would hear in a TV commercial.", "audio": "/zhanghaomin/datas/musiccap/music_data/nONXdP6T3pc.wav"} +{"id": "nP05Sf4Fgac", "caption": "A blues rock power trio with electric bass and overdriven electric guitar playing a riff together and the drummer playing a backdoor shuffle. It is instrumental with a swung rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/nP05Sf4Fgac.wav"} +{"id": "nPlDt1R8Qfc", "caption": "This music is instrumental. The tempo is slow with a flute playing a melodic lead harmony and later joined by a rhythmic acoustic guitar. The song is dulcet, warm, peaceful; calming, meditative,pensive, contemplative, deliberate, mellifluous and euphonious. This music is an Indian Classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/nPlDt1R8Qfc.wav"} +{"id": "nSBDyxxscks", "caption": "This recording contains gargling noises to which a lot of female voices sing along. In the background you can hear a full pop song that serves as background music. The recording is full of fast popping noises. This seems to be an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/nSBDyxxscks.wav"} +{"id": "nSLxQLYYoNE", "caption": "The low quality recording features a R&B song that consists of flat male vocals, alongside filtered background male vocals, singing over punchy kick and snare hits, shimmering cymbals, uptempo hi hats, distorted bass and repetitive synth lead melody. It sounds messy, as the frequencies are clashing with each other, but also energetic, emotional and addictive - like something you would quickly learn to sing along.", "audio": "/zhanghaomin/datas/musiccap/music_data/nSLxQLYYoNE.wav"} +{"id": "nSinUcyFFqg", "caption": "A female pop star sings this lilting melody. The song is medium tempo with a piano playing accompaniment with a subtle bass line. The song is emotional and inspiring. The song is a modern pop hit played to a live audience. The song audio quality is poor and deteriorated.", "audio": "/zhanghaomin/datas/musiccap/music_data/nSinUcyFFqg.wav"} +{"id": "nT1YAP4Vy9s", "caption": "This is a Christian rock/CCM piece. There is a male vocalist singing melodically. The main melody is being played by the acoustic guitar. The electric guitar, the piano and the bass guitar are playing in the background. The rhythm consists of an easygoing acoustic drum beat. The atmosphere is religious. This piece could be used in the soundtrack of a gospel movie. It could also be playing in the background at a Christian religious event.", "audio": "/zhanghaomin/datas/musiccap/music_data/nT1YAP4Vy9s.wav"} +{"id": "nT_R3O0OK6U", "caption": "The song is an instrumental. The tempo is medium fast with a percussive bass line, super fast metal drumming with cymbal crashes and fast drum rolls and a distorted guitar playing a virtuoso lead. The song is energetic and animated. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/nT_R3O0OK6U.wav"} +{"id": "nTtxF9Wyw6o", "caption": "This recording contains a rock song at the beginning with a sound effect of something crashing into rocks. Then a fast change comes and a big aggressive synthesizer sound is playing a low melody along with some sound-effects. This song may be playing as an intro to a tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/nTtxF9Wyw6o.wav"} +{"id": "nU7x170OvJ4", "caption": "This is a bluesy country style song played on a lap steel guitar. There is a walking bassline, and slide guitar being played. The singer has a burly, calm voice. The song would be heard in an old school bar in Texas - which might be called a \"saloon\".", "audio": "/zhanghaomin/datas/musiccap/music_data/nU7x170OvJ4.wav"} +{"id": "nUs5SJyQPnM", "caption": "This music is an Indian classical instrumental. The tempo is fast with an animated Sitar lead, supported with rhythmic beats of lively tabla and dholak , along with a soft and subtle keyboard accompaniment. The music is upbeat, vibrant, vivacious, vigorous , engaging and captivating. This instrumental is a Hindustani classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/nUs5SJyQPnM.wav"} +{"id": "nVSDv46ARvY", "caption": "The low quality recording features a live performance of a classical song that consists of an arpeggiated harp melody and breathy flute melody. It sounds soulful, emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/nVSDv46ARvY.wav"} +{"id": "nVsAyArtEh0", "caption": "The music features an electric guitar playing what sounds to be a solo over a backing track or an actual recording of a song. The notes played in this passage are played fast. The vocabulary used by the guitarist resembles that of the jazz-fusion genre.", "audio": "/zhanghaomin/datas/musiccap/music_data/nVsAyArtEh0.wav"} +{"id": "nW6Naj6eeI4", "caption": "This audio contains acoustic drums playing something like a reggae groove along with an e-bass. A e-guitar strumming chords, piano, organ saxophones and trumpets are playing a short melody on the backbeat giving this song its reggae feeling. In-between the instruments are playing a short loud melody to break into the next part. The instruments are spread across the sides of the speakers. This audio may be playing in an urban coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/nW6Naj6eeI4.wav"} +{"id": "nXfqAzdu8IY", "caption": "The low quality recording features a traditional song that consists of a breathy flute melody playing over wide acoustic guitar chords. It sounds addictive, joyful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/nXfqAzdu8IY.wav"} +{"id": "nY4tpb8O_Rg", "caption": "A bass trombone is playing a melody while violas and violins support with a long melody in the mid and higher register. This song may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/nY4tpb8O_Rg.wav"} +{"id": "nYO8n62Piys", "caption": "This is an acapella version of a swing jazz music piece that was performed with various layers of a vocal synth software called vocaloid. Three different harmonies can be heard from this vocal synth. There is a bass guitar playing a walking bass line in the background. The rhythmic background consists of finger clicks and a swing jazz beat performed with brushes on a snare drum. The atmosphere is cheerful but eerie. This piece could be used in the soundtrack of an arcade/analog type video game. It could also work well in the soundtrack of an anime.", "audio": "/zhanghaomin/datas/musiccap/music_data/nYO8n62Piys.wav"} +{"id": "nZ19mW-TMRk", "caption": "A male singer sings this passionate and emotional melody. The song is medium tempo with a groovy bass line, steady drumming rhythm, piano accompaniment and an emotional string section harmony. The song is inspiring and emotional. The song is a Christmas classic and movie soundtrack. The audio quality is poor with a lot of hissing noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/nZ19mW-TMRk.wav"} +{"id": "nZ5_UUUS8X8", "caption": "The low quality recording features a person trying out the guitar effect pedal while playing some melodies on an electric guitar. There are huge reverb effects in the first part of the loop and reverse effects in the second part. It sounds a bit noisy too.", "audio": "/zhanghaomin/datas/musiccap/music_data/nZ5_UUUS8X8.wav"} +{"id": "nZOgoVEud_w", "caption": "The cover of a rock song consists of soft male vocal singing over shimmering cymbals, punchy snare and kick hits, groovy bass guitar, addictive synth keys melody and electric guitar melody. It sounds energetic, but yet mellow and addictive - thanks to that cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/nZOgoVEud_w.wav"} +{"id": "nZQZ7CpXqAU", "caption": "The low quality recording features a tutorial that consists of a french horn melody played in-between flat male vocal talking. The recording is noisy, mono and quiet.", "audio": "/zhanghaomin/datas/musiccap/music_data/nZQZ7CpXqAU.wav"} +{"id": "nZmhIHZINL8", "caption": "The low quality recording features an arpeggiated electric guitar melody that changes pitch occasionally. The recording is very noisy and in mono, but it sounds passionate and like something John Lenon would sing to.", "audio": "/zhanghaomin/datas/musiccap/music_data/nZmhIHZINL8.wav"} +{"id": "n_REM0fSVrA", "caption": "This is the recording of an acoustic drum solo. The drummer is playing a groovy beat with a lot of different fills. This piece could be sampled and looped to be used in the background of a hip-hop beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/n_REM0fSVrA.wav"} +{"id": "n_boIyhZqWc", "caption": "This bollywood song features a female voice singing the main melody. This is accompanied by a tabla and other percussion playing a staccato beat. A guitar strums chords in staccato following the percussion in the breaks. Another guitar plays arpeggiated chords. A piano plays in the background. The bass walks down playing a descending bassline. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/n_boIyhZqWc.wav"} +{"id": "naZE-MvNpaI", "caption": "This song is an amateur recording of a live performance. This features a female voice singing the main melody. This is accompanied by a distortion guitar playing power chords. The percussion plays a simple rock beat. The sound of crowd whistles are heard in this clip. Other instruments are not audible as the quality of the audio is low. This song can be played in a romantic comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/naZE-MvNpaI.wav"} +{"id": "navn7jCBp_o", "caption": "The low quality recording features a hip hop instrumental that consists of punchy kick, claps, repetitive synth chords, addictive plucked strings melody and tinny wooden percussive elements. It sounds groovy and very addictive, due to that string melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/navn7jCBp_o.wav"} +{"id": "nbIwdOQ7D8A", "caption": "The low quality recording features an electro song that contains distorted, repetitive female vocals over pulsating buzzy bass, wide percussive elements, shimmering cymbals, punchy \"4 on the floor\" kick pattern, claps and syncopated simple synth lead melody. It sounds hypnotic, mainly because of the repetitiveness - especially of the synth lead. It also sounds energetic, uptempo and distorted - like something you would hear in clubs during the 00s.", "audio": "/zhanghaomin/datas/musiccap/music_data/nbIwdOQ7D8A.wav"} +{"id": "nbYdiazwUQo", "caption": "A tropical feeling electronic pop track with heavily processed autotuned vocals hard panned left right and center. The cumbia beat, lots of percussion, synthesizer melody and a syncopated bass give the music a light, friendly, and youthful vibe;", "audio": "/zhanghaomin/datas/musiccap/music_data/nbYdiazwUQo.wav"} +{"id": "nb_7c2xPKYA", "caption": "This song is a low quality live recording. This features an older female voice singing the main melody. This is accompanied by a tenor guitar playing two chords in a repeated rhythm. A male voice sings a fill after a line by the female voice. There is no percussion in this song. There are no other instruments. This is a celebration song sung in a foreign language.", "audio": "/zhanghaomin/datas/musiccap/music_data/nb_7c2xPKYA.wav"} +{"id": "nbb8vmfjHJs", "caption": "The song is an instrumental. The tempo is fast with a fast metal drumming rhythm, complete with cymbal crashes, distorted guitar lead, guitar playing rhythm, and percussive bass line. The song is a death metal song ending with a bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/nbb8vmfjHJs.wav"} +{"id": "nc6h6rC3wdk", "caption": "A male voice is singing with a mid-melody. Different synthesizer sounds are playing arpeggios being used as bassline and other sounds as melody in the mid range and higher register. An acoustic sounding kick is playing on every beat. This song may be playing in a synth retro movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/nc6h6rC3wdk.wav"} +{"id": "ncMDKMEFhnM", "caption": "This is a street performance of a church hymn. It is being performed by a choir singing melodically in a devotional manner. The atmosphere is religious. The audio quality is a bit poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/ncMDKMEFhnM.wav"} +{"id": "ndjLkbP6Y9Y", "caption": "This music is an instrumental with a melancholic piano melody, mesmerising sound of chimes, simple keyboard harmony and a burgeoning cello note. The music is calming, meditative, nostalgic, emotional, sentimental, mellow, soothing and ambient.", "audio": "/zhanghaomin/datas/musiccap/music_data/ndjLkbP6Y9Y.wav"} +{"id": "negr4U79PUE", "caption": "This music is a grim instrumental. The tempo is slow with a sombre electric guitar melody with atmospheric synthesiser and mood digital drums. The music is serious, intense, melancholy, pensive, cheerless, sinister and dark.", "audio": "/zhanghaomin/datas/musiccap/music_data/negr4U79PUE.wav"} +{"id": "nf3LGAL1LZc", "caption": "The low quality recording features a crowd harmonized singing over loud wooden percussion. The recording is noisy, in mono and it sounds energetic, joyful and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/nf3LGAL1LZc.wav"} +{"id": "ng9Dpk4qiP4", "caption": "The low quality recording features a didgeridoo melody. It sounds boomy and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ng9Dpk4qiP4.wav"} +{"id": "nj6N7m8SeK4", "caption": "The music starts off with male backing vocals making way for the main male singer. Throughout the music excerpt a drum rhythmic accompaniment can be heard. The quality of the recording is low and so it's not clear if other instruments take part in accompanying the singer.", "audio": "/zhanghaomin/datas/musiccap/music_data/nj6N7m8SeK4.wav"} +{"id": "njFM8DvmPVU", "caption": "A male singer sings this rock melody. The song is medium tempo with a rock drumming rhythm, percussive bass line, distorted guitar accompaniment and keyboard accompaniment. The song is exciting and energetic. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/njFM8DvmPVU.wav"} +{"id": "njybD3PNrlc", "caption": "The song is an instrumental. The tempo is medium with a tabla playing percussion, Veena and other stringed instruments playing harmony. The audio quality of the video is very poor. The song is a classical Carnatic music tune.", "audio": "/zhanghaomin/datas/musiccap/music_data/njybD3PNrlc.wav"} +{"id": "nkSRzaqpOCQ", "caption": "This instrumental song features a flute playing a high pitched melody. The melody starts off with one high pitched staccato note. After a brief pause, the flute plays two ascending notes in which the second note is sustained. Then a third higher note is played followed by a descending run of four more notes and ending on one higher note. There are no other instruments in this song. There is no percussion in this song. This song has a relaxing mood. This song can be played at a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/nkSRzaqpOCQ.wav"} +{"id": "nlWXsfjHeA8", "caption": "A male vocalist sings this Jazz melody. The tempo is medium with a jazz style piano and drumming, groovy bass line, tambourine beats and vocal backup. The harmony is syncopated and complex. It is ambient, atmospheric, punchy, emphatic and enjoyable.", "audio": "/zhanghaomin/datas/musiccap/music_data/nlWXsfjHeA8.wav"} +{"id": "nn2TnOGCHDI", "caption": "This music is instrumental . The tempo is medium fast with the sound of a conch shell or shell trumpet playing a victorious drone. The music is loud, clear, deep and is often used in religious and sacred rituals in Hinduism and Buddhism. There are sounds of phone dealing and ringing. This music is superimposed on the sound of male talking and children cheering in unison.", "audio": "/zhanghaomin/datas/musiccap/music_data/nn2TnOGCHDI.wav"} +{"id": "nnS7TXfTHOE", "caption": "An e-guitar takes the fast paced lead melody accompanied by another guitar strumming chords on the offbeat. The drums are playing a rhythm that motivates me to dance. This song may be playing somewhere on a street-performance in an Asian country.", "audio": "/zhanghaomin/datas/musiccap/music_data/nnS7TXfTHOE.wav"} +{"id": "nnUva-yCR08", "caption": "The low quality recording features a loud, buzzing saw machine cutting wood. There is a muffled rock song playing in the background. The recording is mono and noisy. It sounds like it is a tutorial video.", "audio": "/zhanghaomin/datas/musiccap/music_data/nnUva-yCR08.wav"} +{"id": "nnc6m1pBJ4c", "caption": "This is a Hindi film music piece. Initially, there is a female voice crying. Afterwards, an orchestra made up of a flute, a string element, a sitar and a piano starts playing an emotional tune. The atmosphere of the piece is heart-touching. It could be used in the soundtracks of Bollywood movies during heartbreaking scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/nnc6m1pBJ4c.wav"} +{"id": "noLrCDzAp5M", "caption": "The Hip Hip song features an autotune male vocal, alongside harmonizing background vocals, singing over boomy 808 bass, snappy rimshots, synth pad chords, synth organ keys chords and tinny hi hats. It sounds groovy and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/noLrCDzAp5M.wav"} +{"id": "nqcVA89BD6I", "caption": "This song features an electric guitar played using a clean tone. Octaves are played in this clip. The first note is a slide up two frets followed by an ascending lick using octaves throughout the song. There are no other instruments in this song. A buzz is heard probably from the hi-gain amp that is being used. There is no voice in this song. This song can be used in a guitar instruction video.", "audio": "/zhanghaomin/datas/musiccap/music_data/nqcVA89BD6I.wav"} +{"id": "nqd7mXvHupU", "caption": "The low quality recording features a live performance of a country song and it consists of banjo solo melody and electric guitar melody going back and forth, energetic drums, groovy bass and sustained strings melody playing in the background. The recording is noisy and in mono, and it sounds energetic and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/nqd7mXvHupU.wav"} +{"id": "nr9oLIsbDyQ", "caption": "This is a tutorial involving the french horn. We have an American male speaking, giving instruction related to the french horn instrument. At a point in the clip, the musician plays one note on the horn.", "audio": "/zhanghaomin/datas/musiccap/music_data/nr9oLIsbDyQ.wav"} +{"id": "nrcfdP6LrLo", "caption": "The low quality recording features a hip hop song that consists of flat male vocals talking over reverberant female vocal melody, punchy snare and kick hits, shimmering hi hats, groovy bass and mellow piano chord progression. It has a lot of reverb on it and it sounds easygoing, chill and groovy - like something you would listen to on a car ride.", "audio": "/zhanghaomin/datas/musiccap/music_data/nrcfdP6LrLo.wav"} +{"id": "nrj2zTr7U0o", "caption": "The song is an instrumental. The tempo is medium with a maestro percussionist performing a solo drum solo in front of a live audience. The song is exciting and gripping. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/nrj2zTr7U0o.wav"} +{"id": "nsxaoH9DjDo", "caption": "This is a jam performed on a homemade theremin instrument. There are irritatingly high-pitched sounds coming from the theremin. The atmosphere is creepy and unsettling. The sounds in this recording could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/nsxaoH9DjDo.wav"} +{"id": "nt2rvdC75uY", "caption": "This instrumental pop song features the main melody played on bells. This is accompanied by percussion playing a simple beat. A tambourine plays continuously in the background and the accents are on the alternate counts when counting 8 in a bar. A ukulele plays chords in the background. An accordion sound is also heard faintly in the background. There are no voices in this song. This song has a happy and uplifting mood. This song can be played in a happy scene in a children's movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/nt2rvdC75uY.wav"} +{"id": "ntfyeC178Tg", "caption": "The low quality recording features a boomy xylophone melody that gives off fun and happy vibes. Due to a huge amount of low frequencies, the recording sounds muddy as well.", "audio": "/zhanghaomin/datas/musiccap/music_data/ntfyeC178Tg.wav"} +{"id": "nu_Bl8Pz6PE", "caption": "This music is instrumental. The tempo is fast with a groovy drumming rhythm with bass drums, snares, cymbals and a Cowbell. The rhythm is upbeat, catchy, punchy and buoyant. This music is a Drumming lesson/ tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/nu_Bl8Pz6PE.wav"} +{"id": "nv1hWkBbG0g", "caption": "This song contains digital drums with percussive elements such as a cowbell and synth sounds used as short percussion in a higher pitch and also a high pitched voice sample. A male voice is rapping in a higher pitch. This song may be playing while driving in your car.", "audio": "/zhanghaomin/datas/musiccap/music_data/nv1hWkBbG0g.wav"} +{"id": "nvBPPOzcW-A", "caption": "The ambient auto shop sounds with the sound of compressed air hissing over the background of muffled radio music of what sounds to be a hip hop drum beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/nvBPPOzcW-A.wav"} +{"id": "nvRd4xgEWbw", "caption": "The low quality recording features a rock song that consists of a melancholic male vocal singing over punchy kick and snare hits, shimmering ride cymbals, groovy bass guitar and acoustic rhythm guitar. It sounds emotional and heartfelt.", "audio": "/zhanghaomin/datas/musiccap/music_data/nvRd4xgEWbw.wav"} +{"id": "nvoGwmKh6NI", "caption": "The low quality recording features a techno song that consists of DJ scratching sound effects, groovy bass, buzzy synth leads, punchy \"4 on the floor\" kick pattern, shimmering hi hats and some claps. It sounds energetic, aggressive and weird - due to those synth lead \"screams\".", "audio": "/zhanghaomin/datas/musiccap/music_data/nvoGwmKh6NI.wav"} +{"id": "nvrMO6TDu2g", "caption": "This song contains a female voice singing in the mid to higher register sounding sensual and sad. She is singing along to a backing track containing acoustic drums playing along with an e-bass. Castanets typical for latin music, an acoustic guitar, plucked and long notes being played by strings giving the song a feeling of flamenco music. In the background you can hear the crowd giving applause. This song may be playing as a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/nvrMO6TDu2g.wav"} +{"id": "nvuxMnSHHtg", "caption": "The track features a cinematic ambience with different sound effects like waves or earthquake sounds. In the foreground there's a bright piano playing a melody with a positive vibe. The track sounds like an extract from a video game,", "audio": "/zhanghaomin/datas/musiccap/music_data/nvuxMnSHHtg.wav"} +{"id": "nvvXOfLs-ng", "caption": "The low quality recording features an Enka song that consists of a steel guitar solo melody, mellow bell chord progression, sustained strings melody and sustained brass melody. The recording is noisy and in mono, and it sounds emotional, heartfelt and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/nvvXOfLs-ng.wav"} +{"id": "nxdHojfss_A", "caption": "This is a cinematic classical music piece. There is a piano playing the chords while the strings are holding the melodic background. There is a mysterious ambient synth sound coming and going. A repetitive low-to-mid frequency percussive sound effect is being played to imply the sound of whales. The atmosphere of the piece is reminiscent of both underwater and outer space at the same time. That is why it could be used in science fiction movies and shows that have an aquatic or outer space setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/nxdHojfss_A.wav"} +{"id": "nyLpME6YH20", "caption": "This is a ska punk music piece. There is a male vocalist with a raspy voice singing in the Spanish language. The keyboard and the electric guitar are playing the melody while there is a bass guitar playing in the background. The rhythm consists of fast tempo acoustic drum beats. The atmosphere is lively. This piece can be played at sports venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/nyLpME6YH20.wav"} +{"id": "nyjXFx0GSX8", "caption": "We hear the bright ringing of two metal objects clanging against each other. This is the bright metallic sound of steel ringing. In the distance, we faintly hear a country rock song. Specifically, we hear a country rock guitar riff being played in the background. There is also the sound of a non-steel object being placed on a surface.", "audio": "/zhanghaomin/datas/musiccap/music_data/nyjXFx0GSX8.wav"} +{"id": "nzdlPYd8XUs", "caption": "This is a bright and twangy twelve bar blues song. We hear some intricate piano playing, a bright and warm electric guitar on which chords are being played, and a groovy walking bassline. This song would be suitable in a blues bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/nzdlPYd8XUs.wav"} +{"id": "nzpnWuk3RjU", "caption": "This song is a lively Jazz instrumental. The tempo is medium with a spirited piano harmony, syncopated drum rhythm and groovy bass lines. The music is ambient, lively, engaging and catchy with complex chords, irregular beats, improvisations , syncopation and creative freedom for improvisations.", "audio": "/zhanghaomin/datas/musiccap/music_data/nzpnWuk3RjU.wav"} +{"id": "o-ISARPUGlo", "caption": "This is a live performance of a soulful R&B song with two main instruments being at the core. There is a guitarist playing percussively and the electric piano is being used to play some bright and airy chords. The singer has a soulful and full bodied voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/o-ISARPUGlo.wav"} +{"id": "o-ZTQP5CFCg", "caption": "The song is fast paced, grungy and intense. It has an overwhelmingly fuzzy and distorted sound that's characteristic of much of old school techno music.", "audio": "/zhanghaomin/datas/musiccap/music_data/o-ZTQP5CFCg.wav"} +{"id": "o1E579RL33w", "caption": "The song is an instrumental. The song is medium tempo with an accordion playing in an accompaniment style with both medley and harmony and no other instrumentation. The music is romantic and melancholic. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/o1E579RL33w.wav"} +{"id": "o2bqT0ZTz7E", "caption": "This audio contains a male voice singing a harmony with another voice both in the mid to higher register. Then a e-piano comes in playing a minor chord. This song may be playing live during a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/o2bqT0ZTz7E.wav"} +{"id": "o6ZQNr0Tpz4", "caption": "The low quality recording features an ambient song that consists of a wide sustained string melody going left and right through the stereo image. There are tinny wooden sounds in the background, as the recording is a bit noisy. Even though it is calming and relaxing, it is a bit disturbing too.", "audio": "/zhanghaomin/datas/musiccap/music_data/o6ZQNr0Tpz4.wav"} +{"id": "o8FsD7l5er4", "caption": "The low quality recording features a soul song that consists of reverberant passionate male vocal singing over sustained brass melody, followed by short brass melody and energetic, barely audible energetic drums. The recording is very noisy and thin, as it lacks low frequencies, but it sounds passionate and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/o8FsD7l5er4.wav"} +{"id": "oARFeTnImOg", "caption": "This is a live recording which features strums of a single chord on a ukulele. At points in the clip, there is the voice of someone who is speaking. The recording is of a low-quality, and thus the audio has a slight fuzzy sound the whole way through.", "audio": "/zhanghaomin/datas/musiccap/music_data/oARFeTnImOg.wav"} +{"id": "oBBTqXQFTiA", "caption": "The low quality recording features a live performance of a pop song that consists of harmonizing male vocals singing over punchy kick and snare, shimmering hi hats, groovy bass, brass melody and electric guitar melody. There are some crowd clapping and cheering sounds in the background. It sounds energetic, exciting and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/oBBTqXQFTiA.wav"} +{"id": "oBwt8T8P8Zs", "caption": "The Jazz song features reverberant saxophones and trumpet melodies playing over groovy double bass, groovy piano melody, shimmering cymbals and soft kick hits. It sounds uptempo, groovy and passionate, like something you would hear in traditional jazz bars.", "audio": "/zhanghaomin/datas/musiccap/music_data/oBwt8T8P8Zs.wav"} +{"id": "oC0e8GXYy_4", "caption": "The song is an instrumental. The tempo is medium with a keyboard accompaniment, sonic effects, various percussion hits, strong bass line and synth pad section. The song is eerie and full of tension. The song is tv show theme and has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/oC0e8GXYy_4.wav"} +{"id": "oD0Xp--xxjE", "caption": "This music is a percussion solo. The tempo is fast with the drummer playing an energetic solo. The beat is vigorous, enthusiastic, spirited, infectious and punchy with a flourish of cymbals.", "audio": "/zhanghaomin/datas/musiccap/music_data/oD0Xp--xxjE.wav"} +{"id": "oEJ5bh-OIuU", "caption": "This song features two female voices. One of the voices sings an 'ooh' throughout the song. The second voice sings an 'ah' in places. The first time the 'ah' is sung, it is in a dissonant harmony. The second one is in the scale. This is accompanied by a guitar playing arpeggiated chords. There are no lyrics in this song, but only lyrics. There is no percussion in this song. This song can be played in a movie scene where a person is confused after having been forced to make a tough decision.", "audio": "/zhanghaomin/datas/musiccap/music_data/oEJ5bh-OIuU.wav"} +{"id": "oFCzd9bJo9A", "caption": "The song contains a flutesound, brass-section, e-bass and some lower register keys all playing the same funky and repetitive melody. The drums are holding a straight rhythm while the hits on the ride are played in a light swing. This song may be played at a rollerblade disco.", "audio": "/zhanghaomin/datas/musiccap/music_data/oFCzd9bJo9A.wav"} +{"id": "oGbNzR_lpSk", "caption": "The low quality recording features a loud wind and water splashing sound effects, while there is a widely spread electric guitar melody and marimba, followed by smooth bass, soft kick, shimmering shakers and tambourine playing in the background. It is noisy and it sounds like it was recorded with the phone, while the music was added in post production.", "audio": "/zhanghaomin/datas/musiccap/music_data/oGbNzR_lpSk.wav"} +{"id": "oJ0rdNlghn4", "caption": "The rock music features a bass guitar playing a repeating melody with a distortion effect in the really-low pitch register. A set of drums is accompanying the bassist with a well-rooted and repeating rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/oJ0rdNlghn4.wav"} +{"id": "oJyyNWuyig4", "caption": "The song is an instrumental. The tempo is medium and has a piano accompaniment. The song has a lot of ambient noises like hissing, breathing and hushed tones. The song is emotional but of poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/oJyyNWuyig4.wav"} +{"id": "oKab6-syQD4", "caption": "This song contains an acoustic drum playing along to a e-guitar strumming chords before breaking into a more silent part with the e-bass repeating the same note. The e-guitar is playing a simple short melody with delay. Then a deeper male voice is singing and the crowd starts cheering. This recording is in bad audio-quality. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/oKab6-syQD4.wav"} +{"id": "oMZcsGUi8ZE", "caption": "This clip features a synchronised playing of some traditional South Asian horned instruments. The horns are played in unison, at a high pitch, and create the sensation of a royal and momentous occasion.", "audio": "/zhanghaomin/datas/musiccap/music_data/oMZcsGUi8ZE.wav"} +{"id": "oMgSuyPBINs", "caption": "This audio contains someone playing a classical piece on a harpsichord. This song may be playing live at a concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/oMgSuyPBINs.wav"} +{"id": "oN9_GYDkNcM", "caption": "This is a comedy music piece in the style of a Christmas song. It is an instrumental piece. There is a rhythmic background that is composed of percussive elements. The sleigh bells can be heard very distinctively. The melody is played by a lute in a slightly out-of-sync manner while a tuba is playing the bass line. The piece has a tongue-in-cheek feel to it. This piece could fit well in the soundtrack of a Christmas-themed comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/oN9_GYDkNcM.wav"} +{"id": "oNggxSyyyq8", "caption": "This audio contains a lot of different percussive instruments spread to both sides of the speakers. In the background you can hear a laughing sample in a high pitch. A male voice is singing in a higher pitch than a female voice takes over singing. A doorbell is ringing. An acoustic guitar is strumming chords. This song may be playing at an open air festival where everybody can dance along.", "audio": "/zhanghaomin/datas/musiccap/music_data/oNggxSyyyq8.wav"} +{"id": "oNqBsQiNoAU", "caption": "This song contains a female acapella choir singing together a melody in minor along with a piano. A e-guitar panned to the ride side of the speakers is providing a supporting melody. This song may be playing as a live performance in a theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/oNqBsQiNoAU.wav"} +{"id": "oNryELagQUM", "caption": "A female singer sings this beautiful melody. The tempo is medium with a string section harmony and a strong bass line. The audio quality is poor. The song is a retro pop hit with inspiring and romantic vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/oNryELagQUM.wav"} +{"id": "oOiwmRV1PBk", "caption": "This music clip is a loud, boomy drum beat. The tempo is slow with the powerful and rhythmic beat of the Big Chinese drum. It is loud, resonating, vibrating and powerful and sounds ceremonial, celebratory and royal and used for announcements.", "audio": "/zhanghaomin/datas/musiccap/music_data/oOiwmRV1PBk.wav"} +{"id": "oOlMzQpK690", "caption": "Someone is playing a distorted e-guitar solo along to a backing track containing a strummed acoustic guitar and a simple drum groove. This recording is of poor audio-quality. This song may be playing at home practicing guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/oOlMzQpK690.wav"} +{"id": "oPiyXhxRGe4", "caption": "This is an amateur cover of a grunge rock music piece. Both the recording and the playing are of poor quality. There is a male vocalist singing in a grunt-like manner as the lead. A crunchy riff is being played by the distorted electric guitar and the bass guitar while the acoustic drums are playing a simple rock beat. The atmosphere is rebellious and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/oPiyXhxRGe4.wav"} +{"id": "oRHKVmQ138Q", "caption": "This music is an Electronic music instrumental. The tempo is medium with synthesiser arrangements , electronic xylophone harmony and digital drum beats. The music is soothing, punchy, groovy, hypnotic and engaging. This music is Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/oRHKVmQ138Q.wav"} +{"id": "oRUdvu3Qo-E", "caption": "The song is an instrumental. The song is medium fast tempo with a groovy bass line, energetic drumming, and tap dancers in a percussive groove. The song is entertaining and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/oRUdvu3Qo-E.wav"} +{"id": "oRVivXC83hA", "caption": "This song contains digital drums with a soft sub bass playing along every kick hit. An acoustic guitar/sitar is playing a melody with a synth sound playing a high counter melody panned to the left side of the speakers. A synth pad is playing a long note melody in a higher register. A female voice is singing the main melody. Her voice is doubled and backing voices are adding harmonies. This song may be playing in a hip-hop club.", "audio": "/zhanghaomin/datas/musiccap/music_data/oRVivXC83hA.wav"} +{"id": "oSDZZHN77PI", "caption": "The low quality recording features a tutorial where a flat male vocalist is talking after a clean electric guitar chord is played. Judging by the short snippet at the end of the loop, there is a guitar pedal effect that changes the preset of the guitar sound. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/oSDZZHN77PI.wav"} +{"id": "oSg1VJHiPOE", "caption": "The song has a generally cheerful, happy-go-lucky vibe to it. It's got a male vocalist who has a zesty and vibrant voice, as well as a female vocalist that brings power to the song as well. There's a brass motif that follows one of the phrases by the male vocalist, and the drumming is generally upbeat and jazzy.", "audio": "/zhanghaomin/datas/musiccap/music_data/oSg1VJHiPOE.wav"} +{"id": "oSoP9Is0UH4", "caption": "A male vocalist sings this melodious contemporary Christian song. The tempo is medium with punchy drumming, keyboard accompaniment ,vigorous violin harmony, steady bass line and synth arrangements. The song is peppy, appealing to the youth, melodious, mellow and sincere.", "audio": "/zhanghaomin/datas/musiccap/music_data/oSoP9Is0UH4.wav"} +{"id": "oT6ud0OdR_E", "caption": "The excerpt is actually a song collage and it features third songs. In the first one a male voice is singing and the song has a dance feel to it. In the second song a male voice is singing and being backed by male voices at the same time. The instruments used are more close to the rock genre. The third song lasts for a few milliseconds and so it's hard to notice anything about it.", "audio": "/zhanghaomin/datas/musiccap/music_data/oT6ud0OdR_E.wav"} +{"id": "oTXKGrB3bCA", "caption": "This is an instrumental live downtempo music piece performance with deep house elements. There is a synth bass lead while the medium-pitch strings hold the melodic background. An occasional piano riff can be heard every now and then. There is a mid tempo electronic drum beat in the rhythmic background. It has a very groovy mood. This piece could be played during earlier hours at a nightclub. It could also be used in a tech device advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/oTXKGrB3bCA.wav"} +{"id": "oTzTZqDOIt0", "caption": "A female vocalist sings this upbeat electronic pop song. The tempo is fast with enthusiastic synthesiser arrangements, groovy drumming. The music is electronically arranged and has a youthful, vivacious, enthusiastic, buoyant dance groove. This music is upbeat Electronic Dance music.", "audio": "/zhanghaomin/datas/musiccap/music_data/oTzTZqDOIt0.wav"} +{"id": "oUp-acoLyvU", "caption": "This song contains an orchestra playing a melody in the mid to high range with a string section decreasing in volume.Oboes/flutes are playing another melody on top with a low timpani hit in the background. This song may be playing at the end of an emotional adventure movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/oUp-acoLyvU.wav"} +{"id": "oVhhEku6ECA", "caption": "Someone is playing an acoustic drumset with an open hi-hat and fast aggressive fill-ins. An e-bass is playing a simple bassline along. In the background you can hear strings playing a melody while an e-guitar is playing an arpeggio melody on top. In the background you can hear people cheering and singer/singers at the end of a phrase. This song may be playing in a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/oVhhEku6ECA.wav"} +{"id": "oXBGZoBYaLY", "caption": "This song is an instrumental. The tempo is medium with the melody of an oboe and percussion rhythm like the bongos and the sound of a waterfall and faint female vocals in the background.the sound quality of the song is inferior and the sounds are distorted and muffled This song is an instrumental pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/oXBGZoBYaLY.wav"} +{"id": "oYECB7KFJgU", "caption": "Male singers sing this vocal harmony. The song is medium tempo with steady drumming rhythm, cello playing the bass line, guitars strumming rhythm and various percussion hits. The song is chaotic and exciting. The song is an amateur band playing a retro pop song with audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/oYECB7KFJgU.wav"} +{"id": "oYEzy8gH6q8", "caption": "This music is an electric guitar instrumental. The tempo is very fast with the guitarist playing a very animated riff rapidly with a lot of dexterity. There is no accompaniment except for the sound of rhythmic clicking which could be percussion or just the sound of fingers moving along the guitar rapidly. The audio quality is inferior so the sounds are sharp, piercing , loud and a little unpleasant to the ear.", "audio": "/zhanghaomin/datas/musiccap/music_data/oYEzy8gH6q8.wav"} +{"id": "oZF73R89bk0", "caption": "This audio contains a loud and strong digital drum almost sounding like an acoustic drum set. A bass sound rich in harmonica is serving as bassline while a short female shouting voice sample is repeatedly being played as a rhythmic element. This song may be playing for a dance battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/oZF73R89bk0.wav"} +{"id": "oZScu7DU5qk", "caption": "The music features for the most part an instrumental, however, towards the end of the music excerpt a female voice sings a short melody. The passage starts off with a synth sound playing a melody that's doubled in unison by the bass guitar. After that a sampled brass sound plays a repeating melody. Throughout the music one can hear a drum set taking an active part in shaping the pulse and flow of the music.", "audio": "/zhanghaomin/datas/musiccap/music_data/oZScu7DU5qk.wav"} +{"id": "oZoJ26C6LrU", "caption": "This audio is an animated movie clip. There are ambient street sounds like footsteps, car brakes being slammed, car crashing, police van or ambulance siren and a song at the end.", "audio": "/zhanghaomin/datas/musiccap/music_data/oZoJ26C6LrU.wav"} +{"id": "oZrMoZeJ8Ng", "caption": "This game music starts off with the sound of something that sounds like the fading sound of a giant's footsteps. An orchestral sound plays as well and the sounds take a pause while electronic percussion is played. This song can be played in a game lobby.", "audio": "/zhanghaomin/datas/musiccap/music_data/oZrMoZeJ8Ng.wav"} +{"id": "oag3I4VRXyM", "caption": "A female singer sings this beautiful melody with male and female backup singers in vocal harmony. The song is medium tempo with an acoustic guitar playing rhythm and strong string bass line with no percussion instrumentation. The song is emotional and heartfelt. The song has acapella influences and is soulful. The song is of poor audio recording quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/oag3I4VRXyM.wav"} +{"id": "ocCIB2bPq_Y", "caption": "This audio contains someone playing a classical piece on a cembalo.\nThis song may be playing at a theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/ocCIB2bPq_Y.wav"} +{"id": "oczJZV87k9A", "caption": "A male voice is singing loud and in a higher register while a flute is playing a counter melody. Percussions are playing a fast paced groove along with a soft minimalistic bass. In the background you can hear a synth pad playing chords. This song may be playing in a oriental barber shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/oczJZV87k9A.wav"} +{"id": "odzi_VK8m3k", "caption": "This is a jingle piece playing in the background of a loud toy helicopter video. The video is a bit dated and therefore the sound quality is quite poor. The instrumentation of the piece is barely audible. There is a keyboard playing the melody with a bass guitar and a drum backing. The piece is made up of common sounds and it has a generic aura to it. The sounds from this recording could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/odzi_VK8m3k.wav"} +{"id": "ogOTksL2Vas", "caption": "This song contains a male voice singing a drone sound in the lower register while other male voices are singing a harmonic melody in the mid-range. This song may be playing live in a church.", "audio": "/zhanghaomin/datas/musiccap/music_data/ogOTksL2Vas.wav"} +{"id": "oh0EWEvJI90", "caption": "This song contains digital drums playing a ragga groove with a light pitch shifting sub bass on the kick and snare. A soft synth pad is creating an atmosphere. A deep male voice is singing/rapping over the instrumental. This song may be playing in an urban club.", "audio": "/zhanghaomin/datas/musiccap/music_data/oh0EWEvJI90.wav"} +{"id": "oh5XmtSAOuM", "caption": "The low quality recording features a blues song that consists of throaty male vocals, alongside harmonizing male vocals, singing over electric guitar melody, brass melody, shimmering hi hats, punchy snare and kick hits and walking double bass. It is a bit noisy and it sounds funky, groovy, happy, fun and vintage - like something you would want to dance to.", "audio": "/zhanghaomin/datas/musiccap/music_data/oh5XmtSAOuM.wav"} +{"id": "ohBNHUUGD3Q", "caption": "A male voice is singing loud and soulful while a e-bass takes the major role of the instrumental serving with a percussive rhythm along with a e-guitar strumming short chords where a snare could have been. Male backing vocals singing harmonies in the background. The recording sounds old and therefore not of the best quality. This song may be playing while eating a romantic dinner with your partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/ohBNHUUGD3Q.wav"} +{"id": "ohikUtjUN7c", "caption": "This is a live performance of a Hindustani classical music piece. There is a male vocalist singing passionately in the lead. The melody is being played by a gentle harmonium tune. The rhythmic background is provided by the tabla percussion. The atmosphere is vibrant. This piece could be used in the soundtrack of a movie with a North Indian setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/ohikUtjUN7c.wav"} +{"id": "ojdqgnmcgYM", "caption": "The low quality recording features a pop song that consists a passionate female lead vocal, alongside harmonizing female vocal, singing over groovy synth bas, claps, shimmering hi hats, punchy \"4 on the floor\" kick pattern, electric guitar melody and short groovy synth keys chords. It sounds energetic, groovy and addictive. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ojdqgnmcgYM.wav"} +{"id": "ojwVhlh-P1U", "caption": "Here we have several standing crystal bells being played. They produce a sustained, ringing, high pitched frequency that would be suitable for meditative and relaxed environments. The woman sings a short, open-mouthed melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/ojwVhlh-P1U.wav"} +{"id": "okAn7kjxmes", "caption": "This is an alternative rock piece. The main theme is played through power chords by a distorted electric guitar. In the background, a bass guitar is playing a groovy bass line. The rhythmic background is provided by loud acoustic drums playing a rock drum beat with frequent usage of rapid fills. The atmosphere of the song is aggressive and rebellious. It could be used in the soundtrack of a teenage drama or a crime series.", "audio": "/zhanghaomin/datas/musiccap/music_data/okAn7kjxmes.wav"} +{"id": "on18CWdmxn8", "caption": "The Pop song features a filtered male vocal, alongside flat male vocal, singing over some claps, boomy kick hits, laser synth riser and addictive synth lead melody. There are also some male laughing sounds. It sounds addictive, groovy and exciting - like something you would hear in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/on18CWdmxn8.wav"} +{"id": "opu2tXoVNKU", "caption": "A male vocalist sings this beautiful Reggae song. The tempo is medium with a keyboard harmony, punchy and infectious bass line and funky drumming with harmonic vocal backup. The song talks about world peace, kindness towards humankind and unity. The song is inspirational, passionate, youthful, emotional,persuasive,impactful, melodic , engaging and captivating.", "audio": "/zhanghaomin/datas/musiccap/music_data/opu2tXoVNKU.wav"} +{"id": "oqMlq2zWr0c", "caption": "This music is a violin instrumental. The tempo is medium fast with the violins going from lively to soft with a romantic piano melody and acoustic guitar accompaniment. The music is orchestral with a dulcet violin symphony. It is pleasant, mellifluous, passionate, romantic; euphonious, emotional, sweet and engaging. This music is a contemporary orchestra .", "audio": "/zhanghaomin/datas/musiccap/music_data/oqMlq2zWr0c.wav"} +{"id": "oswsd_r-GI8", "caption": "This Spanish rock song features a male voice singing the main melody. This is accompanied by rock percussion playing a simple beat. The bass plays the root notes of the chords. A guitar strums chords with upstrokes. A trumpet, saxophone and trombone plays fills in between verses. An organ pays fills at every alternate count. The mood of this song is happy and upbeat. This song can be played in a comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/oswsd_r-GI8.wav"} +{"id": "ot6SpwD1hzk", "caption": "This is a glam rock/classic rock music piece. There is a male vocalist singing melodically. The main theme is being played by the electric guitar while the bass guitar is playing in the background. The rhythm is provided by a rock acoustic drum beat. There is a loud vinyl hiss because of how aged the record is. The atmosphere is groovy. This piece could be playing in the background of a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/ot6SpwD1hzk.wav"} +{"id": "otVPTo72q4w", "caption": "This music is instrumental. The tempo is slow with a harmonious melody of string instruments, percussion and wind instruments which sound like the Indian Sarangi, dhol or madal , shakers and a flute. The music is classical, simple, enchanting and melodic. This song is a Folk song Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/otVPTo72q4w.wav"} +{"id": "ou3LJpAM4mk", "caption": "This audio contains a digital reggaeton beat that uses some acoustic samples. In the background you can hear a soft bass playing along with the kick. A lot of male voices are rapping/speaking providing backing vocals that are spread across both sides of the speakers. This song may be playing at a party outside on the streets.", "audio": "/zhanghaomin/datas/musiccap/music_data/ou3LJpAM4mk.wav"} +{"id": "ouVuF-y8bog", "caption": "This music is an electric guitar instrumental. The tempo is medium with a smooth electric guitar lead harmony. The music is clear, emphatic, smooth, groovy, youthful, crisp, edgy and dominant.", "audio": "/zhanghaomin/datas/musiccap/music_data/ouVuF-y8bog.wav"} +{"id": "ovVrS-q3Rzk", "caption": "This is a clip containing vinyl or deck scratching. The DJ manipulates the deck back and forth to create scratching sound effects which have a melodic and percussive type of vibe. There's a mellow synth on which a simple progression is being played, and a simple hip hop drum beat is being played.", "audio": "/zhanghaomin/datas/musiccap/music_data/ovVrS-q3Rzk.wav"} +{"id": "ovomUNSo_uo", "caption": "The low quality recording features a live performance of blues songs and it consists of a harmonica solo melody played over groovy bass, punchy snare, shimmering cymbals and electric guitar melody. As it was recorded with a phone, there are some whistling crowd noises, aside from the fact that the recording is in mono and noisy. It still sounds energetic and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/ovomUNSo_uo.wav"} +{"id": "ow12iGt8z5Q", "caption": "The low quality recording features a wide harmonizing vocals singing over wide toms, groovy bass, punchy snare, energetic crash cymbal, thin kick hits and buzzy synth lead melody. It sounds passionate and addictive thanks to that synth lead. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ow12iGt8z5Q.wav"} +{"id": "ow7xqVk8Wjs", "caption": "This is a Persian folk music piece in the style of an opera. The female vocalist is singing at a high-pitch in a manner that is filled with emotion. There is a piano in the background that occasionally supports the melody. This is a heart-touching piece. This piece could be used in the soundtracks of tragedy/drama movies, especially the ones that take place in the Middle East. It could also be used in a video game to create an aura of suspense and anticipation.", "audio": "/zhanghaomin/datas/musiccap/music_data/ow7xqVk8Wjs.wav"} +{"id": "oxZjkE984Uo", "caption": "The low quality recording features a dubstep song that consists of buzzy, manic synth bass, punchy kick, slapping claps and high pitched laser riser. At the end of the loop, there is a short snippet of a much calmer section that consists of mellow claps, stuttering hi hats and arpeggiated dark piano melody. Overall it sounds aggressive and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/oxZjkE984Uo.wav"} +{"id": "oxhFIoExrMk", "caption": "A male Latin singer sings this romantic melody. The song is medium tempo with an acoustic guitar accompaniment with no other instrumentation. The song is emotional and passionate. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/oxhFIoExrMk.wav"} +{"id": "oyAAhjGTNvQ", "caption": "This bluegrass song starts off with a male voice making an announcement. The music starts to play. The banjo plays an introductory bluegrass lick. This is accompanied by an acoustic guitar strumming chords. The double bass plays the root note and the fifth of the chord. The mandolin plays the rhythm section in the song. There is no vocal melody in this song. There is no percussion in this song. This song can be played in a movie with a Western theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/oyAAhjGTNvQ.wav"} +{"id": "oynXCFZWxnI", "caption": "This slow song features a male voice singing the main melody at a comfortable pitch. The tone of the voice is emotional. This is accompanied by a bass playing the root notes of the chords. After one line, a synth swell is played. A piano plays the backing chords. The mood of this song is sad. This song can be played in a sad scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/oynXCFZWxnI.wav"} +{"id": "oypg41SWGDc", "caption": "This is a funk remix of a hip-hop music piece. There is a male vocal rapping calmly almost as if he is just having a normal conversation with someone. There are various layers of different synths playing different melodies. The piece has a strong bass sound. The rhythm is being played by a groovy electronic drum beat. The atmosphere of the piece is danceable and the sound is urban. This piece could be playing at a retro-themed party at a nightclub.", "audio": "/zhanghaomin/datas/musiccap/music_data/oypg41SWGDc.wav"} +{"id": "ozjs2d_xlSI", "caption": "A male singer sings this soulful melody with backup singers in vocal harmony. The song is medium tempo with an organ accompaniment, steady drumming , guitar rhythm and various percussion hits. The song is story telling and passionate in nature. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/ozjs2d_xlSI.wav"} +{"id": "p0oRrGDrQQw", "caption": "French horn solo with orchestral accompaniment, woodwinds, glockenspiel and cymbals. The genre is jazz and classical.", "audio": "/zhanghaomin/datas/musiccap/music_data/p0oRrGDrQQw.wav"} +{"id": "p1-07VdP__Q", "caption": "This music is a Jazz instrumental. The tempo is slow with emphatic brass and wind instrumentation, with cello and jazz drumming. The trumpets are emphatic with a lively trombone riff. The other instruments add a rich, dense layer to the music. It is intense, complex, ambient, groovy and pleasant. This music is a Jazz instrumental.5.", "audio": "/zhanghaomin/datas/musiccap/music_data/p1-07VdP__Q.wav"} +{"id": "p1DNl8BF49U", "caption": "The low quality recording features a live performance of a jazz song and it consists of groovy double bass, trombone solo and shimmering hi-hats. The recording is a bit noisy and it sounds warm, intimate and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/p1DNl8BF49U.wav"} +{"id": "p20KE0LhL68", "caption": "A digital drum is playing a techno groove with a half open hihat sound on the offbeat and a pregnant snare. A shaker and other little rhythmic elements are spicing up the drums. A simple digital bass is playing a melody while a very short voice sample comes in along with white noise rising. The elements are slightly panned across the speakers. This song may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/p20KE0LhL68.wav"} +{"id": "p28jmA01BHo", "caption": "A male singer sings this melody with a backup singer singing rapping vocals. The song is medium tempo, with a steady drumming rhythm, groovy bass line and keyboard accompaniment. The song is groovy and exciting. The song is a retro reggae song but has a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/p28jmA01BHo.wav"} +{"id": "p2NPfU5QARc", "caption": "This bit starts with white noise followed by a tiny cymbal ride, drum beat and a keyboard harmony. This is the beginning of a song.", "audio": "/zhanghaomin/datas/musiccap/music_data/p2NPfU5QARc.wav"} +{"id": "p2fXNAPYD20", "caption": "The low quality recording features an ambient song that consists of a wide filter modulate synth pad melody going, wide mellow synth pad and short growly synth bass. At the end of the loop, there is a reverberant riser, subtly bringing the energy up. It sounds calming and relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/p2fXNAPYD20.wav"} +{"id": "p2jnUySmuvA", "caption": "This is a Hawaiian folk music rendition of a jazz music piece. There is a male vocalist singing melodically in the lead. The simple tune is being played by a mellow sounding ukulele. There is a peaceful and relaxing atmosphere. This piece could be playing in the background of a coffee shop. It could also be included in the soundtrack of a feelgood movie/TV series. Another good use would be in the background of wholesome social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/p2jnUySmuvA.wav"} +{"id": "p2sXdmex3xQ", "caption": "This music is instrumental. The tempo is slow with a melodic acoustic guitar solo. The music is soft, euphonious, dreamy, romantic , warm ,ambient and soothing. This is a Classical acoustic instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/p2sXdmex3xQ.wav"} +{"id": "p2yedR_jMTU", "caption": "Someone is playing a melody on an electric organ in a minor key. An acoustic drum is playing a simple groove with single hits on the ride. An e-bass is playing the root note of the melody accompanied by a clean e-guitar sound fingerpicking the chords. Then a deeper male voice starts singing. This song may be playing in a sad romantic movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/p2yedR_jMTU.wav"} +{"id": "p3DLHNuCYhU", "caption": "The low quality recording features a resonating mellow bell playing. It sounds relaxing, calming, soft, mellow, haunting and hypnotic. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/p3DLHNuCYhU.wav"} +{"id": "p4T1pddBia0", "caption": "This song is a Latin Football team anthem. The song is medium tempo with lively keyboard, flute harmony, synthesiser arrangements , shakers and infectious drumming. The song is youthful, energetic,encouraging, celebratory, cheerful and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/p4T1pddBia0.wav"} +{"id": "p7VmMa6cpSo", "caption": "The low quality recording features a live performance and it contains glass breaking and shattering sounds, high pitched female vocal grunt, sustained synth bass, boomy toms and punchy kick, it also includes a crowd cheering sounds. The recording is in mono, really noisy, muffled and it sounds energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/p7VmMa6cpSo.wav"} +{"id": "p8xxC2um9xQ", "caption": "The Disco song features a flat male vocal singing over a wide funky electric guitar melody, groovy bass, synth keys chords, funky synth lead melody, punchy kick, punchy snare layered with some claps and simple hi hats. It sounds passionate, funky and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/p8xxC2um9xQ.wav"} +{"id": "p9nbp0Oo1U0", "caption": "This song contains an acoustic drum playing a simple groove with heat panned to both sides of the speakers. An e-bass is playing along while someone is strumming chords on an acoustic guitar. Two male voices are singing together in harmony. A viola is joining, playing along with the singer's melody. This song may be playing while cooking at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/p9nbp0Oo1U0.wav"} +{"id": "pCW5ab3SNcQ", "caption": "This music is instrumental.The tempo is slow with a keyboard harmony, a male voice talking over the music and the sound of birds chirping. The music is playful, naughty, animated, simple and minimalist. The music style and dialogue indicate that this is an animated movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/pCW5ab3SNcQ.wav"} +{"id": "pDgWT99uaJ0", "caption": "This folk song features a quarter. The main melody starts off with the accordion playing an ascending run. This is accompanied by the bass playing the root and fifth of the chords. An acoustic guitar strums chords in waltz time. After the accordion part, the violin plays the main melody and the same instruments back the violin. This song can be played in a village fair.", "audio": "/zhanghaomin/datas/musiccap/music_data/pDgWT99uaJ0.wav"} +{"id": "pELIBvAnbkY", "caption": "The low quality recording features a R&B song that consists of a passionate female vocal, alongside wide exhale sounds and wide repetitive female vocals, singing over claps, punchy kick, shimmering hi hats, synth lead melody and simple synth bass. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/pELIBvAnbkY.wav"} +{"id": "pG6yeC3yUY4", "caption": "The song is instrumental. The tempo is medium with a piano playing solo accompaniment with no other instrumentation. Tap dancers tap to the piano accompaniment not perfectly in sync , with a lot of ambient room noises and people talking. The audio quality is very poor in this home video.", "audio": "/zhanghaomin/datas/musiccap/music_data/pG6yeC3yUY4.wav"} +{"id": "pHC25Ia8Dxo", "caption": "A male rock singer sings this climatic solo with a long sustained note. The tempo is medium with strong rock drumming, guitar rhythm; guitar lead and a percussive bass line. The song is hard rock with a lot of spirit and excitement. The audio quality is bad with a lot of ambient crowd noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/pHC25Ia8Dxo.wav"} +{"id": "pHFHsubQVpg", "caption": "This is an amateur recording of a Bavarian folk music performance. The audio quality is not that great. There is a male vocalist singing in the lead. Then, brass elements start playing a cheerful tune. There is a festive atmosphere in this recording. It could be playing in the background at an Oktoberfest event.", "audio": "/zhanghaomin/datas/musiccap/music_data/pHFHsubQVpg.wav"} +{"id": "pHj8U-3RHc4", "caption": "The low quality recording features a live performance of a pop song and it consists of a passionate boy vocal singing over wide synth melody, reversed crash riser, punchy kick and snare hits, shimmering hi hats, groovy synth bass and later sustained synth bass. There is some crowd noise and cheering sounds. It sounds addictive, energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/pHj8U-3RHc4.wav"} +{"id": "pHzjKCj9INw", "caption": "This is an instrumental piece carrying the characteristics of Carnatic music. An acoustic guitar is being played sideways to reach the musical effect of a tambura. The piece could be used as a soundtrack in movies/shows that take place in India.", "audio": "/zhanghaomin/datas/musiccap/music_data/pHzjKCj9INw.wav"} +{"id": "pIE-3sIPlvY", "caption": "This audio contains a song with a bass playing a repeating melody along with a digital drums being in the background and a synth pad sound in the higher register. Towards the end the song is getting louder. In the foreground you can hear motor racing sounds. This song may be playing for a youtube video.", "audio": "/zhanghaomin/datas/musiccap/music_data/pIE-3sIPlvY.wav"} +{"id": "pIwn0udLJXI", "caption": "This DJ song features a DJ console being used to mix music. Vinyl scratching is played in this clip. The voice is also cut as a DJ drop for this song. The percussion plays a simple steady beat in common time. This song can be played at a DJ party.", "audio": "/zhanghaomin/datas/musiccap/music_data/pIwn0udLJXI.wav"} +{"id": "pKDnn0CBIe0", "caption": "This song is an instrumental. The tempo is medium with an animated keyboard harmony and vocalisation. The music is heavily synthesised and sounds like a children\u2019s song. This song is an electronic pop/ Children\u2019s song.", "audio": "/zhanghaomin/datas/musiccap/music_data/pKDnn0CBIe0.wav"} +{"id": "pKFXFu8st9I", "caption": "This is an upbeat swing style song with a choir of brass instruments playing a vibrant motif. The motif is a sort of crescendo that announces the next segment. It would be suitable as an intro to the arrival of a character in a musical or movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/pKFXFu8st9I.wav"} +{"id": "pL71P2hVjMc", "caption": "This audio features an electric guitar. This guitar is played through an effects pedal adding reverb to the sound. A guitar lick is played with one open string and the melody on the higher register of another string. There are no other instruments in this song. There is no voice in this song. This song can be played in an instructional video on effects pedals.", "audio": "/zhanghaomin/datas/musiccap/music_data/pL71P2hVjMc.wav"} +{"id": "pLqa0cqsICA", "caption": "This music is a percussive instrumental. The tempo is fast with a vigorous, vivacious beat. It is rhythmic, pulsating, vigorous and energetic with a male voice giving instructions on drumming styles. This clip is an instruction audio/video on drumming patterns.", "audio": "/zhanghaomin/datas/musiccap/music_data/pLqa0cqsICA.wav"} +{"id": "pLqasxGYWX8", "caption": "This is a live performance of a salsa music piece. The melody is being played by loud and high-pitched trumpets with the backing of the piano and the bass guitar. In the rhythmic background, a group of latin percussive elements are playing such as cowbell and maracas. The atmosphere is vibrant and sensual. This piece could be included in the soundtrack of a romance movie that takes place in the Caribbeans or Latin America.", "audio": "/zhanghaomin/datas/musiccap/music_data/pLqasxGYWX8.wav"} +{"id": "pNlrM-GhFZU", "caption": "A male singer sings various songs in live audience situations. The songs have a different tempo and are mostly accompanied by a band. The songs are sung at live venues with people screaming and cheering. The songs are modern pop hits , recorded in poor audio quality with hissing noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/pNlrM-GhFZU.wav"} +{"id": "pOZWVSiRwv4", "caption": "The low quality recording features a live performance of a folk song and it consists of passionate female vocal singing over percussive tambourine. The recording is noisy, reverberant and the stereo image is unbalanced - leaning more towards the right channel. It sounds passionate though.", "audio": "/zhanghaomin/datas/musiccap/music_data/pOZWVSiRwv4.wav"} +{"id": "pPOUg26EXiU", "caption": "This audio contains background noises of people talking. Then the music begins involving synth pad sounds playing long drones in the lower mid range to the higher register with little sparkling tones on top playing in a high pitch. This song may be playing for a meditation session.", "audio": "/zhanghaomin/datas/musiccap/music_data/pPOUg26EXiU.wav"} +{"id": "pQWpa484HQM", "caption": "The low quality recording features a live performance of bagpipe melodies played over some percussive wooden elements. The recording is muffled, noisy, in mono and it sounds soulful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/pQWpa484HQM.wav"} +{"id": "pR87Ts3a0e8", "caption": "Someone is playing a loud acoustic drums full of kick and low tom hits sounding wild and psychedelic along with sliding e-guitars building up tension before breaking into the next part of the song with a lot of crash hits and the guitars strumming distorted chords: The e-bass is playing along one note to create tension before breaking into a bassline that gives the song more power. The instruments are panned to the left and right side of the speakers. The female voice is singing loud and in the mid-range. This song may be playing at a festival where everybody is dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/pR87Ts3a0e8.wav"} +{"id": "pS1X6Au1EAU", "caption": "This amateur folk song features a stringed instrument being played by plucking the strings. This is accompanied by a percussion that sounds like a shaker. This is a low quality recording and the sound of whistling can be heard in the background. There are no voices in the song. This song can be played in a movie featuring a visit to a village.", "audio": "/zhanghaomin/datas/musiccap/music_data/pS1X6Au1EAU.wav"} +{"id": "pSt8NwXyDlg", "caption": "This is a rocksteady/proto-reggae music piece. There is a male vocalist singing in a relaxed manner. The electric guitar and the bass guitar is playing a groovy melody while occasional synth sounds from the keyboard can be heard. The rhythmic background consists of a slow tempo reggae acoustic drum beat. The atmosphere is chill. This piece could be used in the soundtrack of a summertime movie taking place on a tropical island.", "audio": "/zhanghaomin/datas/musiccap/music_data/pSt8NwXyDlg.wav"} +{"id": "pSzTPGlNa5U", "caption": "This amateur recording features the main melody being played by a theremin. This is accompanied by a piano. There are no other instruments played in this clip. The mood of this song is relaxed. There are no voices in this song. This song can be played in a slow motion action scene in a superhero movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/pSzTPGlNa5U.wav"} +{"id": "pTzINk_nVHg", "caption": "This is a gear showcase jam. The electric guitar is being played initially without and then with the effect of a reverb pedal. There is a groovy feel to the solo that is being played. This piece can be sampled to be used as an advertisement jingle or to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/pTzINk_nVHg.wav"} +{"id": "pVfV09CDmus", "caption": "This is the sound of a shofar, a bugle-like instrument. It is blown by a person using the lips. This shofar music is playing only one note. There are no other instruments in this song. There is no voice in this song. This song is used for religious purposes.", "audio": "/zhanghaomin/datas/musiccap/music_data/pVfV09CDmus.wav"} +{"id": "pWHkmo9Kn8g", "caption": "This low quality recording features a male voice singing the main melody. This is accompanied by percussion playing a simple beat. After two bars, the percussion plays only the ride cymbal. A distortion guitar plays power chords and after two bars, lets the last chord ring. The bass plays the root notes of the chords. This song can be played in a Transformers style movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/pWHkmo9Kn8g.wav"} +{"id": "pWZqzEpygE0", "caption": "Someone is playing acoustic drums with a half open hi hat holding a simple rock groove with snare hits as fill-ins. An e-bass plays a bassline along while an e-guitar is strumming slightly distorted chords. A male voice is singing in the mid-range. The whole recording sounds clean but is not a high professional recording. This song may be playing at a local festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/pWZqzEpygE0.wav"} +{"id": "pWms_9wpRB4", "caption": "The music features a group of female voices singing the same melody in unison. The drums and bass guitar blend together and drive the pulse of the music. In the first half of the music excerpt strings play the same melody as the singers.", "audio": "/zhanghaomin/datas/musiccap/music_data/pWms_9wpRB4.wav"} +{"id": "pXz67syyse0", "caption": "This is a classical music piece performed on a baritone saxophone. The tone of the baritone saxophone resembles a cello sound. There is a tender feel to the melody being played. The atmosphere is heart-touching. This piece would fit perfectly in the soundtrack of a documentary with serene scenes such as a birdlife documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/pXz67syyse0.wav"} +{"id": "pYXx0xXZiXk", "caption": "This music is a jazz instrumental.The tempo is fast with an animated electric guitar harmony, funky drumming, groovy bass line and keyboard accompaniment. The music is complex, engaging,emphatic, groovy and syncopated with a hissing sound in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/pYXx0xXZiXk.wav"} +{"id": "pYaegEQ_wtI", "caption": "The low quality recording features a compilation of bright trumpet melodies. The recording is noisy, in mono and it sounds passionate and jazzy.", "audio": "/zhanghaomin/datas/musiccap/music_data/pYaegEQ_wtI.wav"} +{"id": "pZgzjL5wbtA", "caption": "This is a famous pop music piece played over a dance audition video. The male vocalist is singing melodically in one track at a medium pitch and singing the melody at a high pitch in another track. The melody is supported by a bass guitar playing a groovy bassline. A catchy acoustic drum beat and offbeat claps hold the rhythmic background. The atmosphere is jovial and very danceable. This piece could be used in a myriad of different ways from dance videos, online content, sports venues etc.", "audio": "/zhanghaomin/datas/musiccap/music_data/pZgzjL5wbtA.wav"} +{"id": "p_-lKpxLK3g", "caption": "This classical song features the main melody played by trumpets. This is accompanied by violins playing two note trills. A xylophone plays notes in the background. Church bells are played in the background. There is no percussion in this song. This is an instrumental song. There are no voices in this song. The mood of this song is relaxing. This song can be played in a magical scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/p_-lKpxLK3g.wav"} +{"id": "p_dE26TA8ig", "caption": "The low quality recording features a childish female vocal singing over acoustic rhythm guitar. It is a bit noisy and in mono, it sounds emotional and like a background song for some video game..", "audio": "/zhanghaomin/datas/musiccap/music_data/p_dE26TA8ig.wav"} +{"id": "p_o6NQX7lmE", "caption": "This song contains whales singing and then a piano starts playing a composition along. This may be playing in a documentary.", "audio": "/zhanghaomin/datas/musiccap/music_data/p_o6NQX7lmE.wav"} +{"id": "paeNnR33i5Q", "caption": "This is the live performance of a progressive metal music piece. The electric guitar is playing a complex solo in the lead. There is a bass guitar playing in the background. The rhythm is played by the acoustic drums. There is an agitated feel to the piece. This piece could be playing in the background at a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/paeNnR33i5Q.wav"} +{"id": "pbVYSktQ5jE", "caption": "The low quality recording features a punk song that contains flat male vocal singing over punchy kick and snare hits, shimmering cymbals, wide electric guitars and groovy bass guitar. It sounds energetic, exciting and upbeat - like something you would jump to at concerts.", "audio": "/zhanghaomin/datas/musiccap/music_data/pbVYSktQ5jE.wav"} +{"id": "pcOPueObfWs", "caption": "The low quality recording features a filtered monster growl, followed by a wide arpeggiated synth. It sounds spooky and haunting.", "audio": "/zhanghaomin/datas/musiccap/music_data/pcOPueObfWs.wav"} +{"id": "pdIAN6lMXSU", "caption": "This song contains a digital techno drum with a kick on every beat. A sub-bass is inviting to dance along with synth pluck sounds playing a melody in a higher key along with a female voice. A very low pitched male voice sample comes in for a moment before a synth pad sound playing in the midrange comes in. This song may be playing in a techno club.", "audio": "/zhanghaomin/datas/musiccap/music_data/pdIAN6lMXSU.wav"} +{"id": "pdOskdFwRPg", "caption": "This song features a drum solo. The drum solo has the accents on the cowbell. The tempo of this song is fast. The hi-hat accentuates the counts and is played in eighth note pattern. There are no other instruments in this song. This song can be played in an instructional video.", "audio": "/zhanghaomin/datas/musiccap/music_data/pdOskdFwRPg.wav"} +{"id": "pejDm3j4Y-I", "caption": "The low quality recording features repetitive buzzy strings and wooden percussion performing live. There is an unwanted male cough at one point in the loop. The recording is very noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/pejDm3j4Y-I.wav"} +{"id": "piY4mt4F9xg", "caption": "This folk song features a female voice. This is accompanied by percussion played on the Congas. An acoustic guitar strums the chords. The bass plays a running bassline providing fills and giving depth to the low end of the musicscape. An organ plays chords in the background. The song has a hippie feel. This song can be used in a retro movie with a hippie movement theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/piY4mt4F9xg.wav"} +{"id": "piyYJ2l_h8Q", "caption": "This is a rock-n-roll music piece. There is a male vocalist in the lead singing in a gritty manner. The electric guitar is playing a simple tune with the backing of the bass guitar. The rhythmic background consists of a basic upbeat acoustic rock drum beat. There is a groovy feel to this piece. It could be playing in the background at a rock bar. It could also be used in the soundtrack of a feelgood movie during road trip scenes.", "audio": "/zhanghaomin/datas/musiccap/music_data/piyYJ2l_h8Q.wav"} +{"id": "pmdoDcNBt0E", "caption": "The low quality recording features a live performance of a pop song that consists of groovy synth bass, punchy snare, soft hi hats, heartbeat kick pattern, mellow sustained string melody and passionate female vocal singing over it. It sounds emotional, passionate and groovy thanks to that synth bass.", "audio": "/zhanghaomin/datas/musiccap/music_data/pmdoDcNBt0E.wav"} +{"id": "pn6toTLXAck", "caption": "This song is an animated instrumental. The tempo is fast with synthesiser arrangements, intense drumming, groovy bass lines and digital sound effects. The music is upbeat, catchy, compelling, youthful, psychedelic, trance like and intense with an upbeat dance groove. This song is contemporary Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/pn6toTLXAck.wav"} +{"id": "pnh_C1w4yGc", "caption": "The low quality recording features a flat male vocal talking over an electro song that consists of a punchy \"4 on the floor\" kick pattern, short snare hit and offbeat shimmering hi hats. In the second part of the loop, the electro song is being scratched by a DJ. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/pnh_C1w4yGc.wav"} +{"id": "poxsF3-HeP0", "caption": "A male vocalist sings this catchy song. The tempo is fast with synthesiser arrangement, punchy digital drum beats, groovy bass line and melodic vocal backup. The music has a repetitive, catchy vocal riff. It is youthful, punchy, bouncy, thumping, pulsating, and throbbing with soulful vocals and a dance groove. This music is Deep House/Techno pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/poxsF3-HeP0.wav"} +{"id": "pp6eSGANq0Y", "caption": "A female vocalist sings this spirited song. The tempo is fast with enthusiastic electric guitar harmony, slick drumming, groovy bass lines and synthesiser arrangements. The song is energetic, youthful, fun, pulsating, engaging and emphatic. This song is Alternative Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/pp6eSGANq0Y.wav"} +{"id": "ppAT0f2YCyM", "caption": "This song is a duet sung in a two part harmony in a foreign language. The tempo is slow with a male voice chanting a call to which the response is this melodious harmony. The song is soothing, calming, delicate, charming and melodic. This could possibly be a religious ritual.", "audio": "/zhanghaomin/datas/musiccap/music_data/ppAT0f2YCyM.wav"} +{"id": "pqsU95TNNP8", "caption": "The low quality recording features a cover of a pop song and it features passionate female vocal singing over acoustic rhythm guitar. There is a quiet playback playing in the background - it sounds like it is coming from headphones. The recording is a bit resonant and noisy, but it sounds emotional and heartfelt regardless.", "audio": "/zhanghaomin/datas/musiccap/music_data/pqsU95TNNP8.wav"} +{"id": "pte5jvRKwsA", "caption": "This is a live recording of an instrumentalist playing a didgeridoo. The melody is rapid and bouncy.", "audio": "/zhanghaomin/datas/musiccap/music_data/pte5jvRKwsA.wav"} +{"id": "puAclKsCbes", "caption": "This is a fun, upbeat country folk song. We hear a banjo player strum rapidly and then go on to do a solo. We hear cheering and clapping fans, intricate basslines and acoustic guitars being rapidly strummed. It's a fun, uptempo song that would be heard in a barnyard.", "audio": "/zhanghaomin/datas/musiccap/music_data/puAclKsCbes.wav"} +{"id": "pvxx3aokwCU", "caption": "This is an instrument showcase jam. The steel drums are being played in a gentle manner. Then, a male voice starts describing the features of the steel drums. The instrument has a relaxing timbre. The parts where it is being played can be sampled for use in the background of meditation videos.", "audio": "/zhanghaomin/datas/musiccap/music_data/pvxx3aokwCU.wav"} +{"id": "pwX5SArqGKU", "caption": "This pop rock song features a male voice singing the main melody. A backing male voice sings the last part of the line in harmony. This is accompanied by a piano playing staccato chords. There is a momentary silence of instruments except the percussion after the chords are struck. An acoustic guitar plays chords in the background. A bass guitar plays the root notes of the chords. The percussion plays a simple beat in common time and finishes the bar with a roll. Then the drum plays with the beat with an open hi-hat. The mood of this song is happy. This song can be played in a coming of age movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/pwX5SArqGKU.wav"} +{"id": "pxEmmUYLHrE", "caption": "The low quality recording features a picked mandolin solo melody. Even though the recording is noisy and in mono, it gives off joyful and happy vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/pxEmmUYLHrE.wav"} +{"id": "pyumNmhV4_s", "caption": "This is a punk rock piece. There is a male vocal singing with a nasal singing technique. There is a distorted electric guitar playing the main theme. The bass guitar is playing a simple, repetitive bass line. The acoustic drums are playing a fast-paced skank beat. There is a defiant, rebellious feel to the piece. It could be used in the soundtrack of a high school drama movie or a TV series.", "audio": "/zhanghaomin/datas/musiccap/music_data/pyumNmhV4_s.wav"} +{"id": "pz8P96myUZk", "caption": "This contemporary gospel song features a female voice singing the main melody. This is accompanied by percussion playing a simple beat in common time. The bass plays the root nots of the chords. An electric guitar plays fills in between lines. The quality of this audio is low and other instruments cannot be easily identified. This song can be played in a Christian movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/pz8P96myUZk.wav"} +{"id": "pzm90xLX9HM", "caption": "The low quality recording features a live performance of a traditional song and it consists of passionate male vocal, alongside passionate background male vocal singing over sustained accordion melody and some tinny percussive elements. Even though it is a bit distorted, mono and noisy, it still sounds soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/pzm90xLX9HM.wav"} +{"id": "pzpg2-jYu6k", "caption": "This song contains a male voice singing in the midrange while percussion instruments such a triangle and drums are playing a rhythm along with an e-bass. A baritone saxophone is playing a melody and someone is strumming chords and a melody on an acoustic guitar. This is an amateur recording. You can hear a high frequency tone from the recording and the sound is lagging. This song may be playing on the radio in a small village.", "audio": "/zhanghaomin/datas/musiccap/music_data/pzpg2-jYu6k.wav"} +{"id": "q-86OQ3HZ4o", "caption": "This music is a mesmerising Chinese instrumental. The tempo is medium with a melodious Chinese harp or Guzheng with rhythmic pipa, violin harmony and Chinese percussion instruments. The music is soft, soothing, calming, ethereal, meditative, mellifluous,euphonious and enchanting.", "audio": "/zhanghaomin/datas/musiccap/music_data/q-86OQ3HZ4o.wav"} +{"id": "q-sJu8CoZts", "caption": "A male vocalist sings this high energy Country Song. The tempo is fast with animated Banjo, fiddle, auto harp, acoustic guitar and cello. The song is cheerful, happy, enthusiastic, fervent, pulsating, buoyant and animated with vocalising and backup. This song is a spirited Country Folk Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/q-sJu8CoZts.wav"} +{"id": "q4PfLl3JVfg", "caption": "The Ambient song features a wide synth pad melody and wide smooth, sustained pad chord playing together. It sounds very relaxing, calming and hypnotic - it kind of makes you sleepy.", "audio": "/zhanghaomin/datas/musiccap/music_data/q4PfLl3JVfg.wav"} +{"id": "q6GBCmLxNIk", "caption": "The song is an instrumental. The tempo is medium with a string section accompanying the first violin playing a melancholic melody. The song is emotional and melancholic. The song is a classic western classical music piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/q6GBCmLxNIk.wav"} +{"id": "q7U8p-m8J3s", "caption": "The song is an instrumental. The tempo is medium with a wood block percussion and a didgeridoo playing percussively. The song is spiritual and emotional in nature. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/q7U8p-m8J3s.wav"} +{"id": "q7s7C4oNlFo", "caption": "This is an intuitive folk/neo-folk music piece. There is a female vocalist singing over multiple tracks, one being the minor harmonies of the other. There is an acoustic guitar playing a gentle, simple tune. The atmosphere of this piece is heart-touching. The music could fit very well in the soundtrack of a drama movie or a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/q7s7C4oNlFo.wav"} +{"id": "q7sK_xrJz-k", "caption": "The low quality recording features a flat male vocal talking over electric guitar melody and sustained strings, with some metallic impact sound and stuttering vocal sound effect. It sounds funny and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/q7sK_xrJz-k.wav"} +{"id": "q87TmUmVg0Y", "caption": "This is a live performance of a pop rock music piece. Two male vocals are singing melodically at the same time. There is a piano playing an upbeat melody while the bass guitar plays a simple bass line in the background. The piece has a joyful aura to it. This piece could be used in the soundtrack of a sit-com during the scenes of a character happily walking through the city.", "audio": "/zhanghaomin/datas/musiccap/music_data/q87TmUmVg0Y.wav"} +{"id": "q9DzO_I4dXg", "caption": "This is an electronic music piece performed by a DJ. There is a heavy use of the turntable adding the repeated scratching effect. A male voice sample can be heard alongside the scratching. In the backing track there is an electric guitar playing the melody while a simple electronic drum beat provides the rhythmic background.", "audio": "/zhanghaomin/datas/musiccap/music_data/q9DzO_I4dXg.wav"} +{"id": "q9Gh-zh-5Ig", "caption": "Energetic, fun latin salsa music with a fast tempo that includes busy percussion, a brass section, piano, group male vocals.", "audio": "/zhanghaomin/datas/musiccap/music_data/q9Gh-zh-5Ig.wav"} +{"id": "q9zAlMM-A9I", "caption": "A full orchestra is playing a slow dramatic, emotional and soft composition. In the background whispering can be heard. This is an amateur recording. This song may be playing at a theater dancing ballet.", "audio": "/zhanghaomin/datas/musiccap/music_data/q9zAlMM-A9I.wav"} +{"id": "qAgZ__fk9LY", "caption": "This slow blues song features a solo played on a guitar. The tempo of this song is slow. This is accompanied by percussion playing a simple beat. The bass follows the 12 bar blues pattern. The piano plays chords in the background. The mood of this song is romantic and the pattern played on the guitar is similar to a call-response theme. This song can be played in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/qAgZ__fk9LY.wav"} +{"id": "qAr3mFkEvco", "caption": "The low quality recording features a pop song that contains repetitive, excited male vocals talking over energetic beats, filter mod synth chords, repetitive cowbell and high pitched synth bells melody. It sounds chaotic, fun and happy - like a parody song.", "audio": "/zhanghaomin/datas/musiccap/music_data/qAr3mFkEvco.wav"} +{"id": "qBe_D8Gg5lA", "caption": "The song is an instrumental. The bagpipes play together in unison and march to the sounds of crowds cheering and other ambient sounds. The song is patriotic like a victory march. The song has very bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/qBe_D8Gg5lA.wav"} +{"id": "qCUJ-8AlecY", "caption": "This is a drumline stick trick recording. A drummer is playing rudiments on a snare pad in an acrobatic manner. There is a rapid procession of single and double strokes. This piece could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/qCUJ-8AlecY.wav"} +{"id": "qDSvHlHbAqM", "caption": "A female vocalist sings this sweet Country song. The music is fast with lively banjo, mandolin, acoustic guitar , dobro and Auto harp harmony, steady bass and rhythmic drumming . The song is emotional, sentimental, pensive, reflective, with a catchy beat. This song is classic Country Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/qDSvHlHbAqM.wav"} +{"id": "qDiTICmdUQg", "caption": "The Rock song features a doubled flat male vocals singing over wide electric guitar chords, groovy bass guitar, energetic cymbals, punchy snare hits and heartbeat kick pattern. It lacks low frequencies, therefore it sounds thin, hollow and harsh, but regardless, also energetic and aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/qDiTICmdUQg.wav"} +{"id": "qDjeY72KaSo", "caption": "A Chinese zither plucked string instrument, or guzheng covering a popular western song with virtuosity, tremolo picking and string bending over a steady rock beat. East meets west.", "audio": "/zhanghaomin/datas/musiccap/music_data/qDjeY72KaSo.wav"} +{"id": "qEGNzCWQdqo", "caption": "A brass section is playing a melody along with a lead trumpet. In the background you can hear strings playing in the mid to high range. An upright bass is holding the rhythmic side of the song. A piano is playing the same melody as the male singer. This song may be playing in a retro bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/qEGNzCWQdqo.wav"} +{"id": "qEJ_jxZzt7k", "caption": "The low quality recording features a cover of a song and it consists of an addictive electric guitar melody played over barely audible playback. The recording is very noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/qEJ_jxZzt7k.wav"} +{"id": "qET3h3w35EA", "caption": "The Regional Mexican song features a passionate female vocal singing over groovy piano melody, wide muffled brass section melody layered with soft crashes and percussive elements. The recording is low quality and vintage, but it still sounds passionate and emotional - like something you would dance to in a latin pub.", "audio": "/zhanghaomin/datas/musiccap/music_data/qET3h3w35EA.wav"} +{"id": "qFTMEVccUMg", "caption": "The low quality recording features a squeaking sound, followed by shimmering bells. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/qFTMEVccUMg.wav"} +{"id": "qFo_gRhW6dQ", "caption": "This is a yoga music piece. There is a male vocal humming a gentle tune. The acoustic guitar is playing a simple arpeggio in the background. There is a calming atmosphere. This piece could fit well during meditation sessions.", "audio": "/zhanghaomin/datas/musiccap/music_data/qFo_gRhW6dQ.wav"} +{"id": "qFrvkOOR2HQ", "caption": "The low quality recording features a man talking in the background over woodwind melody and wooden percussion. It sounds like a traditional folk song and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/qFrvkOOR2HQ.wav"} +{"id": "qHRRWdWvjxI", "caption": "Lead clarinetist playing a melody with an eastern scale accompanied by wind ensemble, cymbals and drums.", "audio": "/zhanghaomin/datas/musiccap/music_data/qHRRWdWvjxI.wav"} +{"id": "qI-Ji4gtBPM", "caption": "The low quality recording features an electro song that contains soft male vocal singing over punchy \"4 on the floor\" kick pattern, shimmering hi hats and open hats, claps, groovy acid synth bass and mellow synth pad chords. It sounds energetic, groovy and hypnotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/qI-Ji4gtBPM.wav"} +{"id": "qIxpfaeZ-zs", "caption": "A male Arab singer sings this cool melody. The tempo is medium with Arabic percussion instruments and various stringed instruments. The song is passionate and romantic. The song has bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/qIxpfaeZ-zs.wav"} +{"id": "qKOsbyT8GCU", "caption": "A male deep voice is singing along to an accordion sound and a choir providing backing vocals. This song sounds cheerful. This is an amateur recording and of poor audio-quality. This song may be playing at a celebration.", "audio": "/zhanghaomin/datas/musiccap/music_data/qKOsbyT8GCU.wav"} +{"id": "qKXhSGaudtk", "caption": "The low quality recording features a traditional song that contains a wide string melody, wooden percussion and some noisy sound in the background. It gives relaxing vibes, even though the percussion and strings are a bit aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/qKXhSGaudtk.wav"} +{"id": "qLWWDHLJBBQ", "caption": "A song is played in the background containing a brass melody. In the foreground you can hear a lot of clicking noises that do not belong to the music. This is an amateur recording. This song may be playing in a casino.", "audio": "/zhanghaomin/datas/musiccap/music_data/qLWWDHLJBBQ.wav"} +{"id": "qM8F6ECriRc", "caption": "The low quality recording features a traditional pop song that consists of a flat male vocal, alongside exciting background vocals, singing over claps, wooden percussive elements, groovy bass and acoustic guitar melody. It sounds energetic, addictive, fun and joyful - like something you would hear at more traditional parties.", "audio": "/zhanghaomin/datas/musiccap/music_data/qM8F6ECriRc.wav"} +{"id": "qMbGFWz9who", "caption": "A male singer sings this classic pop song. The tempo is fast with keyboard harmony, violins,infectious drumming,funky bass guitar and synthesiser arrangement. There are sounds of static, tapping and a baby crying loudly superimposed on the song. The audio quality is inferior and the recording is amateur. This song is Retro Rock and Roll.", "audio": "/zhanghaomin/datas/musiccap/music_data/qMbGFWz9who.wav"} +{"id": "qMd2DTyF9EE", "caption": "This is the live performance of an Irish folk music piece. There is no singer. The fiddle is playing an upbeat solo while the bass guitar is playing a complex bass line using the tapping technique. The atmosphere is joyful. This piece could be used in the soundtrack of a documentary that has scenes of rapid movement.", "audio": "/zhanghaomin/datas/musiccap/music_data/qMd2DTyF9EE.wav"} +{"id": "qOSdHmfwLF4", "caption": "The low quality recording features a children song that consists a passionate female vocal singing over, punchy snare located in the right channel, shimmering tambourine in the right channel of the stereo image, shimmering bells melody, shimmering acoustic rhythm guitar chords, simple bass and coughing sound in the beginning. It sounds fun, happy and joyful - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/qOSdHmfwLF4.wav"} +{"id": "qOTk01gmrRo", "caption": "This is a breakbeat from a DJ set performance. The DJ is using the turntable to repeat the male vocal sample and add the scratching effect. In the background, the electronic drums and a strong bass are providing the rhythmic background at a medium tempo. It has a groovy, urban atmosphere. This performance could be used in a crime movie or a TV show with an urban ghetto setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/qOTk01gmrRo.wav"} +{"id": "qRCjs90-1RQ", "caption": "The male voice singing sounds emotional and sad while a piano is playing a minor chord progression along with an acoustic guitar strumming chords. Then a fat sounding acoustic drum comes in with a simple groove along with an e-bass. This song may be playing on headphones while sitting in the bus riding downtown being lost in thoughts.", "audio": "/zhanghaomin/datas/musiccap/music_data/qRCjs90-1RQ.wav"} +{"id": "qRLRLp-KTFs", "caption": "This is an instrumental didgeridoo piece performed on the street. The didgeridoo is played at a low-to-medium range while the player is performing a simple rhythmic pattern with the use of percussion at the same time. The atmosphere is eccentric. This recording can be used in the soundtrack of a movie that has a tribal setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/qRLRLp-KTFs.wav"} +{"id": "qRgefptkDeo", "caption": "This folk song features a clarinet playing the main melody. A trumpet plays a similar melody in harmony. This is accompanied by a tuba playing the bass notes. An acoustic guitar plays chords for this song. There are no voices in this song. This is an instrumental song. There is no percussion in this song. This song can be played at an Oktoberfest party.", "audio": "/zhanghaomin/datas/musiccap/music_data/qRgefptkDeo.wav"} +{"id": "qUWYzx7pBSw", "caption": "This song contains a complex drum groove with fill-ins and a loud groove on the ride cymbal. A distorted e-bass is playing a simple fast bassline along with a distorted e-guitar playing lower notes along with the bass. This song may be playing in a car racing video-game.", "audio": "/zhanghaomin/datas/musiccap/music_data/qUWYzx7pBSw.wav"} +{"id": "qVT6GX1KHUY", "caption": "This music is a Country song instrumental. The tempo is medium with a pedal steel guitar lead harmony with steady drumming and keyboard accompaniment. The music is a simple,minimalist, sweet, dulcet, sentimental, nostalgic, soothing, pleasant and mellifluous , classic Country music instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/qVT6GX1KHUY.wav"} +{"id": "qV_VxEAXXDU", "caption": "This music is instrumental. It is the sound of a bell playing incessantly. The sound is loud, booming, vibrating, resounding and resonating.", "audio": "/zhanghaomin/datas/musiccap/music_data/qV_VxEAXXDU.wav"} +{"id": "qVdBBOpSoN4", "caption": "A female vocalist sings this powerful Hard rock song. The tempo is medium fast with a vigorous electric guitar feedback, synthesiser articulation and electronic arrangement. The song is youthful, powerful, intense, boisterous, compelling, psychedelic, boomy , punchy and impactful. This song is a Hard Rock/heavy Metal song.", "audio": "/zhanghaomin/datas/musiccap/music_data/qVdBBOpSoN4.wav"} +{"id": "qVgVh9t_7ac", "caption": "The low quality recording features a chiptune melody playing with whistling and car honking sound effects along with it. It sounds very noisy and thin, like it was recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/qVgVh9t_7ac.wav"} +{"id": "qVgnzJuGDBE", "caption": "This music is instrumental. The tempo is slow with a smooth saxophone harmony, groovy bassline, syncopated piano and jazz style drumming. The music is soothing, atmospheric, soothing, lively, romantic, compelling and informal. This music is a Jazz instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/qVgnzJuGDBE.wav"} +{"id": "qVuxCN3JpiM", "caption": "Someone is playing acoustic drums with a lot of fill-ins before breaking into the next part of the song. A e-guitar and e-bass are playing the same melody/chords to elevate the energy. Female voices are singing in harmony before a male voice starts to scream in a higher register and then starts rapping. The e-guitar then is playing, almost clean sound, melody. This song may be playing with headphones while skating.", "audio": "/zhanghaomin/datas/musiccap/music_data/qVuxCN3JpiM.wav"} +{"id": "qW4kBJsudLI", "caption": "This recording was done live, and the audio quality is poor. The style is country gospel or country worship music. There's a banjo being used to play arpeggios, and acoustic guitar strumming. The singer has a twangy and full-bodied female country voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/qW4kBJsudLI.wav"} +{"id": "qXSG2uq2tNw", "caption": "This song is an animated vocalisation. The tempo is fast with a lively piano accompaniment, accordion harmony, cello rhythm, hard hitting drums, groovy bass lines, hand percussion beats and xylophone. The music is upbeat, energetic,enthusiastic, high-spirited and vivacious. This is a live performance with ambient sounds of people talking and general bustling. The audio quality is inferior. This song is a live Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/qXSG2uq2tNw.wav"} +{"id": "qXgSlhWbWLU", "caption": "The song is a modern pop song performed live performance. A female sings this melody with a strong drumming rhythm. The song is highly distorted with high noise levels and distortion. The song is a rock classic and performed live in front of a noisy audience.", "audio": "/zhanghaomin/datas/musiccap/music_data/qXgSlhWbWLU.wav"} +{"id": "qZ_-5JplSVg", "caption": "The Gospel song features a choir singing over shimmering cymbals, soft hi-hats, smooth bass, arpeggiated acoustic guitar melody, sustained strings melody and emotional piano chords. It sounds passionate and heartfelt as the instrumentation is played dynamically, as the listener can really feel the softness of the instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/qZ_-5JplSVg.wav"} +{"id": "qZkM3QaeaUM", "caption": "The low quality recording features a mellow piano melody, slowly arpeggiated acoustic guitar melody and sustained soft strings melody. It sounds sad and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/qZkM3QaeaUM.wav"} +{"id": "qaQjG9SwORU", "caption": "A quiet recording of two female singers participating in a yodeling call and response section, accompanied by accordion, drum kit, bass and guitar playing a steady oompah beat. The chord progression is simple and the mood is fun and silly.", "audio": "/zhanghaomin/datas/musiccap/music_data/qaQjG9SwORU.wav"} +{"id": "qbIPQGY8RRA", "caption": "A group of male vocalists sing this folk song in a foreign language. The tempo is fast with minimalist instruments like a lively acoustic guitar harmony, shakers and tambourine beat;The vocals are energetic, youthful, earnest, cheerful , happy, simple and chirpy.", "audio": "/zhanghaomin/datas/musiccap/music_data/qbIPQGY8RRA.wav"} +{"id": "qbexOeoH5hg", "caption": "The rock song features a passionate male vocal, alongside harmonizing background vocal, singing over tremolo electric guitar located in the left channel, arpeggiated electric guitar melody in the right channel of the stereo image, shimmering tambourine, groovy bass guitar, punchy kick and snare hits, reverberant percussive hit and energetic crash cymbal. It sounds groovy, energetic and kind of addictive thanks to that cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/qbexOeoH5hg.wav"} +{"id": "qc1DaM4kdO0", "caption": "The low quality recording features a sloppy, digital piano melody. The recording is extremely noisy, in mono, with some crackles at the end of the loop, and it sounds like a person is rehearsing the melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/qc1DaM4kdO0.wav"} +{"id": "qcjzfHmQvxg", "caption": "The low quality recording features a flat female vocal talking over breathy flute melody. As soon as the female starts talking, the flute melody lowers in volume. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/qcjzfHmQvxg.wav"} +{"id": "qdWTfyysMN8", "caption": "An e-guitar is playing a single note of a chord creating an arpeggio with an echo/delay-effect. The whole composition sounds soothing and relaxing. This may be relaxing in your room with headphones.", "audio": "/zhanghaomin/datas/musiccap/music_data/qdWTfyysMN8.wav"} +{"id": "qeoYWM1uYPI", "caption": "The low quality recording features an electro song that consists of reversed hi hats, followed by shimmering 2 step hi hats and \"4 on the floor\" kick pattern playing on top of it. It sounds groovy and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/qeoYWM1uYPI.wav"} +{"id": "qfVIeq7s6tw", "caption": "The song is an instrumental. The song is medium fast tempo with a didgeridoo playing percussively with no other instrumentation. The song is played passionately and spirited. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/qfVIeq7s6tw.wav"} +{"id": "qfwTbBprDVU", "caption": "This is a dancehall/reggae music piece. There is a female vocalist singing in a rap-like manner with a Jamaican accent in the lead. The melody is being played by two layers of electric guitar with a bass guitar backing. The rhythm is being played by the electronic drums. An airy synth sound can be heard very faintly in the distance. The atmosphere is chill. This piece can be used in the soundtrack of a summer movie during scenes where everybody is relaxing.", "audio": "/zhanghaomin/datas/musiccap/music_data/qfwTbBprDVU.wav"} +{"id": "qh-4EDX4agQ", "caption": "The song is an instrumental. The song is medium tempo with a horn player playing a deer horn in a repeated manner. The song is spiritual and customary. The song has bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/qh-4EDX4agQ.wav"} +{"id": "qie2k2gZ7wA", "caption": "The rock music features a screaming male voice singing a melody. One of the electric guitars accompanies the singer with strummed chords while the other, for the second part of the music excerpt, plays a melody. Both guitars have a distortion effect on. The drums play a well grounded rhythm and together with the bass guitar drive the pulse of the music. The quality of the audio recording is not that good, most probably this is an old live recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/qie2k2gZ7wA.wav"} +{"id": "qjH068GOmQ4", "caption": "The low quality recording features a drum & bass song that consists of a repetitive female vocal sound effect, growl synth bass, manic percussions, shimmering hi hats, punchy kick and snare hits and echoing synth pad. It sounds energetic, aggressive and manic - like something you would hear in underground clubs during the 00s.", "audio": "/zhanghaomin/datas/musiccap/music_data/qjH068GOmQ4.wav"} +{"id": "qjJ41iwU9LY", "caption": "The low quality recording features a pop song that consists of harmonizing vocals singing over pulsating synth lead melody, groovy bass, \"4 on the floor\" kick pattern, punchy snare, shimmering hi hats and some wooden percussive elements. It sounds energetic and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/qjJ41iwU9LY.wav"} +{"id": "qknDM3pcoD0", "caption": "This song carries a powerful air of conviction with it that is aided by the singer's soulful performance. It's a heartbreak song and although it feels sad, it also feels like a reclamation of power. It's a live performance with a full band including guitarists, violinists, a pianist and a drummer who plays a pop beat. The genre for this song could be classified as pop-soul.", "audio": "/zhanghaomin/datas/musiccap/music_data/qknDM3pcoD0.wav"} +{"id": "ql7aH8wF6JM", "caption": "The music is purely instrumental and it features a 12-string acoustic guitar playing the same note over and over. Since it's a 12-string guitar the note can be heard played twice really fast. I guess a better name would be tuning instead of melody, because it sounds as if the guitarist is trying to tune the 2 strings to play the same note together.", "audio": "/zhanghaomin/datas/musiccap/music_data/ql7aH8wF6JM.wav"} +{"id": "qlWEAm4AUTU", "caption": "Audio of a percussion instrument playing by itself. Sounds like a tambourine, riq, or pandeiro, playing a steady beat, alternating between a cymbal sound and a bongo drum sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/qlWEAm4AUTU.wav"} +{"id": "qlk02ytcnPU", "caption": "This song is an instrumental. The tempo is low with a xylophone like instrument harmony, sound of clock ticking and papers rustling . The music is spooky, eerie, suspenseful and sinister. This song is Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/qlk02ytcnPU.wav"} +{"id": "qlklggFvAZs", "caption": "This is a contemporary reggae song. The vocalist has a smooth and silky voice, the song sounds romantic and intimate. We hear electric guitar chord stabs on the off-beats which characterise the reggae pop style. There are also licks on the electric guitar and a simple drum beat suitable for laid-back dancing. The song has a tropical feel.", "audio": "/zhanghaomin/datas/musiccap/music_data/qlklggFvAZs.wav"} +{"id": "qlqJF5yPmUc", "caption": "fast tapping in rhythm. The sounds are clicking. There is a metronome sound present as well. The rhythm is regimented.", "audio": "/zhanghaomin/datas/musiccap/music_data/qlqJF5yPmUc.wav"} +{"id": "qm8sJxsZ5VY", "caption": "The song is an instrumental. The song has ambient room noises like hair trimming tones and funny tones. The song has slick drumming rhythm, groovy bass line, guitar rhythm and keyboard accompaniment. The song is groovy and funny. The song is a soundtrack for a funny prank video.", "audio": "/zhanghaomin/datas/musiccap/music_data/qm8sJxsZ5VY.wav"} +{"id": "qmR9O2oZCWc", "caption": "This audio contains someone playing a soothing melody on a harp. This piece sounds a little bit melancholic. This song may be playing at a little concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/qmR9O2oZCWc.wav"} +{"id": "qni67aUJbw4", "caption": "The song is an instrumental. The song is medium tempo with a steady drumming rhythm, cymbals crashing, piano accompaniment and a xylophone playing a cool melody. The song is emotional and passionate. The song is an ad jingle for a technology solutions company.", "audio": "/zhanghaomin/datas/musiccap/music_data/qni67aUJbw4.wav"} +{"id": "qoBC2wimalI", "caption": "This music is instrumental . The tempo is slow with an Oboe playing a monotone note and synthesised sound of heavy rainfall. The music has minimal instruments and has a creepy, scary, sinister, unnatural vibe.", "audio": "/zhanghaomin/datas/musiccap/music_data/qoBC2wimalI.wav"} +{"id": "qp4Ubx7WOAQ", "caption": "The clip is a combination of various sound effects. First, we have a fire crackling and this continues throughout the clip. Then we have the sounds of hard objects falling on a wooden floor, and then the sound of glass breaking. What follows is a retro video game beeping sound effect, a grungy electric guitar power chord sequence, and simple rock drumming along with a bassline that matches the chords.", "audio": "/zhanghaomin/datas/musiccap/music_data/qp4Ubx7WOAQ.wav"} +{"id": "qpN3Aqrr8mg", "caption": "This audio contains someone playing a xylophone sound and rattles. This is an amateur recording. You can hear clicking and recording noises. This audio may be playing demonstrating specific sounds on a device.", "audio": "/zhanghaomin/datas/musiccap/music_data/qpN3Aqrr8mg.wav"} +{"id": "qpt3umHYfmY", "caption": "A female singer sings this soulful melody with backup singers in vocal harmony. The song is fast tempo with a quick drumming rhythm, percussive bass line, guitar strumming rhythm and keyboard accompaniment. The song has black gospel roots.", "audio": "/zhanghaomin/datas/musiccap/music_data/qpt3umHYfmY.wav"} +{"id": "qpwjSTEaswI", "caption": "This folk dubstep features female voices singing the main melody. This is accompanied by percussion playing a dubstep beat. The tempo of the beat is fast, incorporating shuffles. A jaw harp plays a quirky sound in the background. The tempo of the song is fast. At the beginning, there is no bass. Toward the end, the bass plays while the percussion gets louder. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/qpwjSTEaswI.wav"} +{"id": "qrP_H87vFpo", "caption": "The jazz music features a piano improvising with somewhat thick textures. A double bass plays a laid-back melody in the low register, for the most time with one note every two beats. The drummer plays a light rhythm employing a brush technique, rather than using sticks. The music has a swing feel to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/qrP_H87vFpo.wav"} +{"id": "qrY7PW5guxk", "caption": "This is a Haiti dance music piece. There is a male vocalist singing melodically in the Creole language. The brass, the keyboard and the bass guitar are the melodic elements of this piece. In the rhythmic background, the acoustic drums and percussive elements are playing a latin type beat. The atmosphere of the piece is chill and easygoing. This piece could be played at Caribbean bars and dance clubs. It could also be used as an accompaniment piece for dancing courses.", "audio": "/zhanghaomin/datas/musiccap/music_data/qrY7PW5guxk.wav"} +{"id": "qrzNABqN420", "caption": "The low quality recording features a rock song that consists of a passionate female vocal singing over punchy kick and snare hits, shimmering hi hats, wide electric guitar melody and groovy bass guitar. It sounds energetic and addictive in the first half of the loop, while in the second part it's mellow and softer.", "audio": "/zhanghaomin/datas/musiccap/music_data/qrzNABqN420.wav"} +{"id": "qsFfUzErXqw", "caption": "The song is instrumental. The tempo is medium with sitars and other stringed instruments playing in unison, tabla percussions and a harmonium playing the lead. The song is a classic hindustaani instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/qsFfUzErXqw.wav"} +{"id": "qsRPTMXFGsA", "caption": "A male Latin singer sings this passionate melody. The song is medium tempo with various Latin percussions, groovy bass line, keyboard harmony and a guitar playing lead. The song is romantic and a classic Latin dance groove. The song is a Latin dance hit with a deteriorating audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/qsRPTMXFGsA.wav"} +{"id": "qtNTHnXOQew", "caption": "The low quality recording features an electro song played live and it consists of at least a punchy snare and a boomy bass. There are some crowd cheering noises in the background. It sounds muffled, energetic, aggressive and distorted as the recording is very noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/qtNTHnXOQew.wav"} +{"id": "qtnE1hnCD0M", "caption": "The low quality recording features a loud, gliding synth bass, muffled snare and kick hits, tinny hi hats and shimmering ride cymbals. There is a busy line sound effect and its rhythm is offbeat relative to the song. It sounds generic - like a song from a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/qtnE1hnCD0M.wav"} +{"id": "qutPvh6TFd8", "caption": "This song features two harps playing a melody. In the beginning, both harps play the harp complimenting each other. After one bar, one of the harps plays the higher repetitive phrase and the other harp plays the lower register notes. This song has a happy mood. There are no other instruments in this song. There are no voices in this song. This song can be played in an inspirational video.", "audio": "/zhanghaomin/datas/musiccap/music_data/qutPvh6TFd8.wav"} +{"id": "qwGT6wvYdLo", "caption": "The Rock Orchestra song features energetic crash cymbals, punchy kick and snare hits, groovy bass, wide electric guitar chords and simple strings melody. It sounds epic, powerful and energetic - like a theme song for an opening track of some anime.", "audio": "/zhanghaomin/datas/musiccap/music_data/qwGT6wvYdLo.wav"} +{"id": "qwI32Si0ipE", "caption": "The low quality recording features a live performance of a pop song and it consists of passionate male vocal singing over synth keys melody, shimmering riser, simple hi hats, punchy kick and snare hits and synth pad chords. There were some widely spread crowd claps and cheering as they were excited. It sounds energetic, exciting and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/qwI32Si0ipE.wav"} +{"id": "qwOLhVbuhpM", "caption": "This is a live recording of an instrumental electronic music beat. The rhythmic foundation of the beat consists of a simple medium tempo electronic drum beat. There are sounds coming from the background resembling a restaurant. It is a minimal-sounding groovy beat that is also danceable. With the removal of ambient sounds and a clean mix, this track could be used in the soundtrack of a TV show with an urban setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/qwOLhVbuhpM.wav"} +{"id": "qwz7oLASJqg", "caption": "This song features a pop song being sung by male voices in acapella . The voices sing the different parts of a choir. They are singing vocables and not words. The voices sing in harmony. Voices are singing the bass; alto and tenor parts. The mood of this song is romantic. This is an amateur recording. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/qwz7oLASJqg.wav"} +{"id": "qxOPhByaK_M", "caption": "The low quality recording features a sustained string melody, tinny shimmering bells and addictive piano melody, complementing each other. At the very end of the loop there is a short snippet of flat female vocal narrating. At some point during the loop, there is a subtle unwanted low frequency sputter, which definitely makes this recording low quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/qxOPhByaK_M.wav"} +{"id": "qxWVr67g6yY", "caption": "This is the live performance of a pop music piece. It is an amateur recording. There are male vocals singing melodically. An electric guitar strums a chord for the ending of a song while the sounds of the cymbals can be heard from the acoustic drums. The cheers of the crowd can be heard even more than the music itself. This recording could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/qxWVr67g6yY.wav"} +{"id": "qyCea2TuUV4", "caption": "The low quality recording features a live performance of a folk song and it consists of acoustic guitar solo melody, followed by banjo melody. The recording is noisy, there are some natural sounds - since it was performed outdoors and the stereo image is unbalanced due to the fact that the instruments are leaning towards the right channel of the stereo image. It still sounds passionate and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/qyCea2TuUV4.wav"} +{"id": "r-PBeJiE5sc", "caption": "This is an instrumental percussion piece. There is a wide variety of percussion instruments. There is a marimba playing a playful melody. The acoustic drums and steel percussion provide the remainder of the rhythmic background. The atmosphere is lively and energetic. This piece could be used in the soundtrack of a comedy movie or TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/r-PBeJiE5sc.wav"} +{"id": "r0I-G70gyo0", "caption": "A male voice is speaking. In the background you can hear other voices. Then someone starts playing a bagpipe in a higher register underlaying its own drone. This song may be played on the streets by a busker.", "audio": "/zhanghaomin/datas/musiccap/music_data/r0I-G70gyo0.wav"} +{"id": "r0Xvr8maR34", "caption": "This orchestral song features the main melody played by trumpets. The brass section plays a repetitive melody and the chords behind the melody change. This is backed by the string section. Cellos and violas are playing the bass notes. This is an instrumental song with no voices. The song has a victorious mood. This song can be played when there is a grand entrance of a King into his castle.", "audio": "/zhanghaomin/datas/musiccap/music_data/r0Xvr8maR34.wav"} +{"id": "r1W1z_31Obw", "caption": "This is an electronic dance/house music piece. There are female vocals singing melodically. The melody is being played by the keyboard with the electric guitar samples in the background. The rhythm consists of an electronic drum beat and electronic percussive elements. The atmosphere is danceable and energetic. This piece could be used in the soundtrack of a romantic comedy movie, especially during the scenes where a character is hesitating to open up to their crush.", "audio": "/zhanghaomin/datas/musiccap/music_data/r1W1z_31Obw.wav"} +{"id": "r2gYE6-cGx8", "caption": "This clip would be suitable for a movie soundtrack during a scene that is thrilling, intense, exciting and fueled with adrenaline. The music is played by an orchestra, with several layers of violin and brass instruments. The song brings about an atmosphere that invites action.", "audio": "/zhanghaomin/datas/musiccap/music_data/r2gYE6-cGx8.wav"} +{"id": "r43WrKA6ppI", "caption": "This is an instructive flamenco guitar piece. The player is depicting how the piece must be played by starting it slow and eventually getting faster. The theme is repeated by the player.", "audio": "/zhanghaomin/datas/musiccap/music_data/r43WrKA6ppI.wav"} +{"id": "r4G71I1dFpA", "caption": "The low quality recording features a soft echoing female vocal singing over mellow piano chords, mellow synth pad chords and reverberant percussion. It sounds soft, mellow, passionate, emotional and sad.", "audio": "/zhanghaomin/datas/musiccap/music_data/r4G71I1dFpA.wav"} +{"id": "r4JRDHYukZ4", "caption": "A male singer sings this emotional melody. The song is medium tempo with a steady drumming rhythm, accordion accompaniment and people singing together in unison. The song is emotional and sentimental. The song audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/r4JRDHYukZ4.wav"} +{"id": "r4nPBNL3D0E", "caption": "A male vocalist sings this lively Rock song. The tempo is fast with bright trumpet harmony, groovy bass, infectious drumming , electric guitar and vocal backup. The music is upbeat, groovy, funky, high-spirited, vibrant and enthusiastic. This song is Retro Rock and Roll.", "audio": "/zhanghaomin/datas/musiccap/music_data/r4nPBNL3D0E.wav"} +{"id": "r5xTmK2Fq1w", "caption": "The low quality recording features a reggae song that consists of flat male vocals, alongside filtered, echoing male vocal and doubling background vocals, singing over punchy kick and snare hits, energetic crash cymbals, tinny wooden percussions, groovy bass and synth keys chords. It sounds energetic, as it is upbeat and addictive, thanks to the cadence.", "audio": "/zhanghaomin/datas/musiccap/music_data/r5xTmK2Fq1w.wav"} +{"id": "r6QD2E-YesI", "caption": "The low quality recording features a reverberant sound of boomy bass guitar, muffled drums, simple electric guitar chords and melodic male vocal singing over it. It sounds like it was recorded on a phone, since it is mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/r6QD2E-YesI.wav"} +{"id": "r6yGS_yQmj4", "caption": "The song is experimental and instrumental. The song has varying tempos consisting of beep tones controlled by manipulating electric currents. The song is non musical and borders on being noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/r6yGS_yQmj4.wav"} +{"id": "r7Ve8ExE8YY", "caption": "This song contains a female voice singing over a digital drum and synthesizer pad being used as a melodic and strongly rhythmic instrument. An orchestral hit is being used to play a very strong and full melody in-between the synth parts. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/r7Ve8ExE8YY.wav"} +{"id": "r8B3-yBc-4U", "caption": "The low quality recording features a live performance of a soft rock song that consists of acoustic rhythm guitar and flat male vocals singing over it. The crowd is loudly chattering in the background. It sounds noisy, dull and distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/r8B3-yBc-4U.wav"} +{"id": "r9AxQfXYLEs", "caption": "Someone is playing an acoustic drum set with a lot of different percussive sounds such as tambourine, cowbell and congos. A male voice is speaking as if explaining something. This song may be playing in a drumming class.", "audio": "/zhanghaomin/datas/musiccap/music_data/r9AxQfXYLEs.wav"} +{"id": "rC4PNZ1XOmU", "caption": "The low quality recording features a metal song that consists of wide aggressive electric guitar chords, distorted bass guitar, punchy snare and kick hits alongside some snare rolls, synth keys melody and energetic crash cymbals. There are some glass hits and metallic object sound effects. It sounds chaotic, distorted, aggressive and muddy, since the frequencies are clashing with each other.", "audio": "/zhanghaomin/datas/musiccap/music_data/rC4PNZ1XOmU.wav"} +{"id": "rDusaHYR69g", "caption": "This clip is two different tracks. The first one is a female vocalist singing a nursery rhyme with lively drums, tambourine beats and vocal backup. The second track is a child singing a song with a playful piano accompaniment . The songs are children\u2019s nursery rhymes.", "audio": "/zhanghaomin/datas/musiccap/music_data/rDusaHYR69g.wav"} +{"id": "rE7S4nLrThs", "caption": "A string ensemble is playing a sad melody together with a female choir singing. The recording is full of reverb and sounds very atmospheric and epic. This song may be playing in a sad movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/rE7S4nLrThs.wav"} +{"id": "rFE_bKOr1W0", "caption": "The low quality recording features a cover of a classical song played on buzzy harpsichord melody. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/rFE_bKOr1W0.wav"} +{"id": "rFwJ2L-geWw", "caption": "The music excerpt features a piano playing a repeating melody in the background. Finger snaps can be heard playing the same rhythm that the piano does. In the background a noise similar to a vacuum cleaner can be heard. It sounds as if this whole thing was recorded with a phone or by an amateur.", "audio": "/zhanghaomin/datas/musiccap/music_data/rFwJ2L-geWw.wav"} +{"id": "rGEJVUcFA2U", "caption": "The low quality recording features a club house song that consists of groovy 808 bass, crispy claps, shimmering muffled shakers and high pitched harmonizing male vocals singing over it. The recording is thin and it sounds groovy, fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/rGEJVUcFA2U.wav"} +{"id": "rG_6MS6_K6g", "caption": "A male voice is rapping in a higher pitch and with reverb and delay on his voice. An acoustic drum sample is playing a simple hip hop groove along with a tambourine like sound. The hihat is panned to the right side of the speakers. An e-bass is playing along. A clean e-guitar sample is being repeated as a melodic and rhythmic element. This song may be playing at home while cleaning the house.", "audio": "/zhanghaomin/datas/musiccap/music_data/rG_6MS6_K6g.wav"} +{"id": "rGgvqyHKI4Y", "caption": "This song features a shofar being played. It starts off with a sustained note followed by a higher note. After a short pause, the melody is repeated but the first note is shortened and the second, higher note is sustained. There are no other instruments in this song. This song has religious significance. This song can be played at the call of battle in a historical movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/rGgvqyHKI4Y.wav"} +{"id": "rJZgUpzqAyY", "caption": "An e-bass is playing a bluesy bassline along with acoustic drums with a slightly open hihat. An electric piano/organ is playing one short chord as a rhythmic element adding reggae vibes along with a e-guitar strumming fast chords on the offbeat. The guitar is running through a chorus effect. The male voices are singing a simple melody. This song may be playing at a live concert before a sports-event.", "audio": "/zhanghaomin/datas/musiccap/music_data/rJZgUpzqAyY.wav"} +{"id": "rKRI5UcIICI", "caption": "This is an acoustic drum solo performance. The drummer is playing rapid and complex fills with a heavy use of cowbells. There is a clear latin music influence in this solo. It has an energetic aura. Parts of this performance could be sampled in use for beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/rKRI5UcIICI.wav"} +{"id": "rKfpCiJf9do", "caption": "The low quality recording features a traditional song that consists of wide wooden percussion, arpeggiated strings melody and breathy flute melody layered with brass melody. It sounds soulful, mystical and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/rKfpCiJf9do.wav"} +{"id": "rLBGxAj9D14", "caption": "This music is an upbeat instrumental . The tempo is fast with a funky harmonica melody leading to a pre-recorded track with infectious drumming, double bass and keyboard harmony. The track is muffled and incoherent. The music is. Catchy, lively, cheerful, perky, funky, happy, vivacious, vibrant and groovy. This music is a Blues Boogie instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/rLBGxAj9D14.wav"} +{"id": "rLQ93N6RJC0", "caption": "A male vocalist sings this catchy pop song. The tempo is medium fast with funky drumming, spirited acoustic guitar accompaniment, rhythmic clapping, steady bass line and keyboard harmony. The song is melodic, perky, peppy, youthful, playful, enthusiastic and fun. This is Indie Pop/Indie Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/rLQ93N6RJC0.wav"} +{"id": "rLtXML8Y5wo", "caption": "The low quality recording features a shimmering bell melody that sounds haunting. There is a metallic impact. The recording sounds very noisy as it was probably recorded with a bad quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/rLtXML8Y5wo.wav"} +{"id": "rNJ0C44bOac", "caption": "This clip features low quality audio. A synth plays the main melody. The bass plays the root notes of the chords. This is accompanied by programmed percussion playing a simple beat. A constant beep is heard in the foreground, which doubles in tempo at the end of the clip. The instruments cannot be heard clearly due to the beeping sound over the instruments.", "audio": "/zhanghaomin/datas/musiccap/music_data/rNJ0C44bOac.wav"} +{"id": "rNKJXwMz9XQ", "caption": "The jingle features a dolphin and deep water sound effects, followed by fading out strings and tinny shimmering bells. At the very end of the loop, there is a snippet of acoustic rhythm guitar and kick hits. The Sound effects are moving left-right throughout the stereo image. It sounds like something to use as an intro.", "audio": "/zhanghaomin/datas/musiccap/music_data/rNKJXwMz9XQ.wav"} +{"id": "rNUtYf6EdW8", "caption": "The low quality recording features a classical song that consists of a suspenseful brass melody, sustained strings and dynamic low percussion roll. It sounds suspenseful, dramatic and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/rNUtYf6EdW8.wav"} +{"id": "rOOBAGxxjBk", "caption": "This music is a lively instrumental. The tempo is fast with the charming harmony of trumpet, saxophone, tuba and a rhythmic accordion accompaniment. The music is fresh, spirited,lively, pleasant, merry, cheerful, charming and entertaining. This music is a classical piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/rOOBAGxxjBk.wav"} +{"id": "rPAB0ymJGco", "caption": "This is a loud heavy metal piece that is played as a soundtrack for a video game with sound effects of fire and a dinosaur roaring in the beginning. There is a distorted electric guitar playing a simple tune while loud acoustic drums provide a heavy metal beat as the rhythmic background. The theme has a very violent feel to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/rPAB0ymJGco.wav"} +{"id": "rQcecqZtGvE", "caption": "This orchestral song features a brass band. The main melody is played on the trumpet. The bass is played on a tuba. There are other brass instruments playing in harmony in the background. There is no percussion in this song. There is no voice in this song. The mood of this song is victorious. This song can be played when a champion takes the podium in a classic event such as fencing or an equestrian event.", "audio": "/zhanghaomin/datas/musiccap/music_data/rQcecqZtGvE.wav"} +{"id": "rQeikHMQGOM", "caption": "This song features the brass section of a symphonic orchestra. The melody is played on trumpets. It is accompanied by a trombone and a brass horn playing individual parts. This song is at a slow tempo and has a relaxing feel. There are no voices in this song. There is no percussion in this song. This song can be played when a hero is returning victorious from a battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/rQeikHMQGOM.wav"} +{"id": "rS8oECcQBCk", "caption": "This is an advertisement video for a rhythm machine. Firstly, it is shown playing behind a bass guitar jam. Then, it is shown playing behind an acoustic guitar jam. A male voice is describing the benefits and functions of the rhythm machine. The parts where the instruments can be heard without the interruption of the voice can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/rS8oECcQBCk.wav"} +{"id": "rTBQmP6Vt0g", "caption": "This song is an instrumental. The tempo is medium fast with enthusiastic drumming, congas and canon rhythm,electronic guitar harmony, keyboard accompaniment and a wind instrument playing a melodious harmony. There is the sound of chattering in the background. The audio is of inferior quality and muddled. The song is energetic, spirited and melodic with a catchy dance groove.", "audio": "/zhanghaomin/datas/musiccap/music_data/rTBQmP6Vt0g.wav"} +{"id": "rUIGOcQMaSE", "caption": "The Corporate instrumental contains wide plucked strings, simple bells, punchy, roomy kick hits and soft rimshots. At the very end of the video there is a shimmering tambourine. Judging by the silence at the end, it could be said that this is an outro of the jingle. It sounds happy, fun and uplifting, like any corporate sound should sound like.", "audio": "/zhanghaomin/datas/musiccap/music_data/rUIGOcQMaSE.wav"} +{"id": "rVDojJcQdE0", "caption": "This recording contains two songs. Both of them have a digital drum playing along with a sub bass and a wide synthesizer lead melody. On one a male voice is singing in a higher register. on the other a female voice is singing with female backing voices. These songs may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/rVDojJcQdE0.wav"} +{"id": "rVdI-aD9pq8", "caption": "This song is played on the bamboo flute. The melody is simple and traditional. The sound is tremulous. There are no other instruments in this song. There are no voices in this song. This song can be played in a children's kung fu animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/rVdI-aD9pq8.wav"} +{"id": "rVymW4Nb4NU", "caption": "The low quality recording features an alarm beeping sound effect, after which the hip hop song starts playing and it has a stuttering DJ scratching sound effect. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/rVymW4Nb4NU.wav"} +{"id": "rW5YKFsiWM8", "caption": "The song is an instrumental. The tempo is slow with an Indian flute or bansuri playing soulfully to the keyboard accompaniment, sitar accompaniment and a tabla player waiting to join in. The music is soulful and emotional. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/rW5YKFsiWM8.wav"} +{"id": "rWitVrXe5tg", "caption": "The low quality recording features an ambient classical song that consists of sustained strings, chords, slow arpeggiated guitar melody and smooth bass. It sounds sad, melancholic and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/rWitVrXe5tg.wav"} +{"id": "rY9zjr9T_WI", "caption": "This is a kids music piece. There is a keyboard playing the main tune while the wind chimes and the xylophone can be heard adding texture. There are sound effects such as clicks and a clown horn. A female voice says \"ice cream\". The atmosphere is goofy and generic. This piece could be used in the background of an educational video about ice cream meant for kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/rY9zjr9T_WI.wav"} +{"id": "r_KdRKquXsM", "caption": "This audio contains a composition played by brass instruments such as trumpets playing a melody in the higher range along with a deeper horn and a bass horn. This song may be playing at a theater presenting this composition.", "audio": "/zhanghaomin/datas/musiccap/music_data/r_KdRKquXsM.wav"} +{"id": "r_TgaHCsYB0", "caption": "This is a clip of a piece on the timpani orchestral percussion instruments. The drummer repeats the same motif twice. The sound of the drums is regal and grand.", "audio": "/zhanghaomin/datas/musiccap/music_data/r_TgaHCsYB0.wav"} +{"id": "raM8Lp0aGCk", "caption": "Someone is playing soft and warm sounding chords on an analog synthesizer slowly opening up a filter letting higher frequencies pass. Someone is playing a melody along on a theremin. Both are playing in the mid to higher range. This song may be playing live.", "audio": "/zhanghaomin/datas/musiccap/music_data/raM8Lp0aGCk.wav"} +{"id": "rccs9c1gteQ", "caption": "This song starts with a lot of high pitched noise that is arpeggiated. Then a male voice starts singing in the mid-range along to a synth bass, pad and pluck sounds. This song may be playing recorded music at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/rccs9c1gteQ.wav"} +{"id": "rez5KDmIZoc", "caption": "The low quality recording features a muffled female soft vocal singing over sustained strings melody and arpeggiated acoustic guitar melody. It sounds mellow, soft and sad - even though the quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/rez5KDmIZoc.wav"} +{"id": "rfQ94EXIpTc", "caption": "This music is a pleasant instrumental. The music is slow tempo with a soft cello and guitar duet with a whistle melody. The song is mellow, soothing, calming , dulcet, warm and relaxing in contrast to the background noises of people talking and walking. The musicians are buskers.", "audio": "/zhanghaomin/datas/musiccap/music_data/rfQ94EXIpTc.wav"} +{"id": "rfa-iUp5UQc", "caption": "This is an intricate country guitar performance. The guitarist plays slide guitar. The playing is complex. There is a tambourine as a percussive element on every beat. It's a live recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/rfa-iUp5UQc.wav"} +{"id": "rfah0bhmYkc", "caption": "The song is an instrumental. The song is medium tempo with an overdriven guitar playing a jarring lead in rhythmic fashion and guitar over tones that sound like bell tones. The song is aggressive and experimental. The song is a modern rock intro.", "audio": "/zhanghaomin/datas/musiccap/music_data/rfah0bhmYkc.wav"} +{"id": "rgWm0-a0kAo", "caption": "This is an instrumental lounge music piece. There is a vague melody with reverberations of an ambient synth and occasional chord strumming from an electric guitar. The electronic drum hits are spread out at a low tempo. The general feeling of this song is chill yet also trippy at the same time. This piece could be used in a technological device release video. It could also be used in scenery shots in a movie or a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/rgWm0-a0kAo.wav"} +{"id": "rh0vBy1JD8A", "caption": "The low quality recording features a soft rock song sung by passionate male vocals followed by muffled acoustic rhythm guitar. It sounds emotional and like it was recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/rh0vBy1JD8A.wav"} +{"id": "rh2D2OSxyw0", "caption": "The low quality recording features an uptempo song, that consists of groovy bass and punchy kick and snare hits, being aggressively scratched by a DJ. It is very reverberant, as the sound diffuses and reflects in the space that the DJ is playing.", "audio": "/zhanghaomin/datas/musiccap/music_data/rh2D2OSxyw0.wav"} +{"id": "rizanOQM61k", "caption": "The low quality recording features passionate harmonizing choir vocals, alongside fruity male vocals. It sounds passionate, traditional and joyful. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/rizanOQM61k.wav"} +{"id": "rkQPSAHNoeI", "caption": "This is an alternative rock music piece. There is a male vocalist singing melodically. The electric guitar is playing a simple and catchy tune while the bass guitar plays a groovy bass line in the background. The rhythm is provided by an acoustic drum beat. This piece could be used in the soundtrack of a teenage drama or a high school TV series.", "audio": "/zhanghaomin/datas/musiccap/music_data/rkQPSAHNoeI.wav"} +{"id": "rkapTdi8NTQ", "caption": "The Hip Hop song features a flat male vocal rapping over reverberant snaps, reverberant addictive plucked synth melody, smooth sub bass, punchy kick, low toms roll and a riser. It sounds smooth, groovy and easygoing - like something you would listen to in a car.", "audio": "/zhanghaomin/datas/musiccap/music_data/rkapTdi8NTQ.wav"} +{"id": "rmKh9uaikTU", "caption": "The low quality recording features a live performance of a rock song that consists of flat male vocal singing over a wide electric guitar melody, groovy keys chords, located in the right channel of the stereo image, smooth bass guitar, shimmering open hats and hi hats and punchy kick and snare hits. It sounds groovy, funky and easygoing - like something you could lightly dance to.", "audio": "/zhanghaomin/datas/musiccap/music_data/rmKh9uaikTU.wav"} +{"id": "rnOIXOGfSUE", "caption": "This is a low quality recording of a rock song. The main lead melody is sung by a male voice. Other male voices sing vocables in the background in between lines. A string ensemble plays fills in the background with an ascending lick in between lines. The percussion plays a simple rock beat in common time with snare strokes on every alternate count. The bass plays the root notes of the chords. The mood of this song is motivational. Other instruments cannot be identified due to the low audio quality. This song can be played at the end credits of a superhero movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/rnOIXOGfSUE.wav"} +{"id": "rn_v88OiRks", "caption": "This audio clip features an instruction of playing the guitar. An electric guitar plays a descending pentatonic run at two different places on the guitar to give a different feel. The voice narrates the process of playing the notes. This is followed by a double stop which is played seven times with a string bend on the eighth time. This can be used in an instruction video.", "audio": "/zhanghaomin/datas/musiccap/music_data/rn_v88OiRks.wav"} +{"id": "rnuGOQ-aSjs", "caption": "Solo latin percussion music featuring congas, cowbells, and timbales, performing complex rhythms.", "audio": "/zhanghaomin/datas/musiccap/music_data/rnuGOQ-aSjs.wav"} +{"id": "rrAIuGMTqtA", "caption": "This is a recording of an electric guitar, first with a chord being strummed and allowed to ring out, then with licks being played. The guitarist plays a blues lick with the guitar producing a clean and compressed tone.", "audio": "/zhanghaomin/datas/musiccap/music_data/rrAIuGMTqtA.wav"} +{"id": "rrWQd5SZK74", "caption": "The low quality recording features a live performance of a regional Mexican song that consists of reverberant, high register, passionate male vocal singing over acoustic rhythm guitar and widely spread, groovy claps. It sounds passionate, traditional and emotional. Judging by the reverb, it was probably played in some huge concert hall.", "audio": "/zhanghaomin/datas/musiccap/music_data/rrWQd5SZK74.wav"} +{"id": "rs5ecH8Lh3s", "caption": "This is an energetic rock music piece with a female vocalist singing in the Spanish language. The repeated theme is played by a strong electric bass guitar. There is a loud and simple rock drum beat in the background. A distorted electric guitar can also be heard holding a sustained note. All these components result in a rebellious atmosphere. This song could be used in rock bars.", "audio": "/zhanghaomin/datas/musiccap/music_data/rs5ecH8Lh3s.wav"} +{"id": "rsCQ1PIGcm0", "caption": "This low quality recording begins with an organ chord and an animal grunting sound at a mid range pitch. This is followed by the sound of a machine gun and the sound of an animal grunting again. There are no other musical instruments in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/rsCQ1PIGcm0.wav"} +{"id": "rsvHQCTgHvg", "caption": "This song contains a lot of digital orchestra instruments. Celli is playing a short bowed stroke chord providing rhythm along with other cello sounds being picked in the mid range. A flute is playing a melody on top. Other string instruments are playing a plucked arpeggio melody. While timpani and cymbals are adding hits. The instruments are spread across both sides of the speakers. This song may be playing in an arcade/adventure video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/rsvHQCTgHvg.wav"} +{"id": "ryEXhKy1QUI", "caption": "Male voice over with a solo oboe melody in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/ryEXhKy1QUI.wav"} +{"id": "rzVNYg3nClo", "caption": "The low quality recording features in-game sound effects and background orchestral music. The in-game sounds are weird high pitched grunts, female grunts, swoosh sound effects, hitting sound effects and laser sound effects. The background music consists of wide strings melody, woodwinds melody and low staccato brass melody. It sounds suspenseful, intense, dramatic and there is a constant noise in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/rzVNYg3nClo.wav"} +{"id": "s1JHUf3Q_F0", "caption": "This reggae song features a male voice singing the main melody. Another voice is singing in harmony with the main voice. This is accompanied by reggae percussion. A timbale is played on every third count. Jam blocks are also played in the background. The bass plays a funky bassline with a reggae feel. Synth sounds are played in the background. This song can be played in a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/s1JHUf3Q_F0.wav"} +{"id": "s1QeDT7jqHQ", "caption": "The low quality recording features multiple layers of french horn melodies. It sounds passionate, a bit muddy and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/s1QeDT7jqHQ.wav"} +{"id": "s1c8RF7lKv0", "caption": "Here we have a live recording of a song intro which is likely played by an orchestra. We hear vibrant brass instruments which create an air of importance about the moment. In the background, there are hundreds or thousands of fans screaming, and we hear a teen screaming really close to the recording device. The audio quality is low.", "audio": "/zhanghaomin/datas/musiccap/music_data/s1c8RF7lKv0.wav"} +{"id": "s1eMgmzCMDM", "caption": "This low quality audio features too much noise. The instruments are not audible due to the noise.", "audio": "/zhanghaomin/datas/musiccap/music_data/s1eMgmzCMDM.wav"} +{"id": "s1l4Zjqoqdg", "caption": "This is a gear showcase jam. The only instrument that is being played is a clean sounding electric guitar playing a mellow solo. A delay effect pedal is applied on the guitar. The atmosphere is calm and dreamy. This piece could be used in an advertisement jingle. It could also be playing in the background at a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/s1l4Zjqoqdg.wav"} +{"id": "s25X6KwBpxw", "caption": "This is a poor quality recording of a yodeling music piece. There is a male vocalist singing rapidly with the yodeling technique. The melody is being played by an accordion. There is a bass guitar playing in the background. The rhythm is provided by an upbeat acoustic drum beat. The atmosphere is cheerful. Despite the quality issue of the recording, it would suit well as a rural radio station music playing inside the car in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/s25X6KwBpxw.wav"} +{"id": "s2GctT6NuyQ", "caption": "This is an amateur recording of a guitar solo for a rock music piece. The solo is being played on an overdriven electric guitar while the piano and the bass guitar in the backing track play the main tune. There is a 6/8 rock beat played on the acoustic drums for the rhythm section. There is a raw feel to it. The piece can be used to gather electric guitar samples to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/s2GctT6NuyQ.wav"} +{"id": "s2O2xaRfje0", "caption": "This is an instrumental progressive rock music piece. There is an electric guitar playing complex tunes and chords with a pitch shifting effect. There is a psychedelic feel to this track. Parts of this recording could be used in an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/s2O2xaRfje0.wav"} +{"id": "s2iIZ2WNuKY", "caption": "This music is instrumental. The tempo is fast with a melodious harmony with synthesiser arrangements, drumming, tambourine beats and some unidentifiable instruments.The audio quality is inferior with an incoherent audio. The music style is Asian/ Chinese.", "audio": "/zhanghaomin/datas/musiccap/music_data/s2iIZ2WNuKY.wav"} +{"id": "s3Q8pVDY7ZI", "caption": "This is a Spanish Christmas song with child vocalists. The song has a jolly and positive vibe to it. There are string instruments and brass instruments. The brass plays a three note motif that is vibrant and positive.", "audio": "/zhanghaomin/datas/musiccap/music_data/s3Q8pVDY7ZI.wav"} +{"id": "s4PN7iTLdVM", "caption": "An acoustic drum is playing a latin groove with a cowbell sound and bongos playing along with a bassline underlining. Someone is playing a melody on a steeldrum. The female voice starts singing the same melody. Male voices are supporting her with shouting sounds. The crowd is cheering and clapping along. This song may be playing at a summer festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/s4PN7iTLdVM.wav"} +{"id": "s59pQGs7Q3E", "caption": "This composition contains ambient noise sounds such as a bass pad drone sound, very fast ringing high frequencies and a rhythmic chime sound. The elements are spread across both sides of the speakers.", "audio": "/zhanghaomin/datas/musiccap/music_data/s59pQGs7Q3E.wav"} +{"id": "s5kz8qg4B2Y", "caption": "The low quality recording features a live performance of a rock song that consists of a passionate male vocal, followed by passionate female vocal singing over shimmering cymbals, mellow snare and kick hits, electric guitar melody and groovy bass guitar. It sounds distant, reverberant, but also energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/s5kz8qg4B2Y.wav"} +{"id": "s5wdG7xbTNg", "caption": "The low quality, mono recording features reverberant wooden toms, played after long silence, which makes it weird.", "audio": "/zhanghaomin/datas/musiccap/music_data/s5wdG7xbTNg.wav"} +{"id": "s6U8DtBK3Us", "caption": "The low quality recording features a rock song that consists of harmonizing background vocals, alongside passionate male vocals, singing over, at least, punchy snare, simple hi hats, smooth bass, thin kick and punchy snare hits. The recording is so noisy that the actual song can barely be heard, but regardless it sounds vintage, energetic and uplifting.", "audio": "/zhanghaomin/datas/musiccap/music_data/s6U8DtBK3Us.wav"} +{"id": "s72505MIhz8", "caption": "The low quality recording features a flat male vocal talking, after which an accordion melody starts playing. It sounds joyful and happy, even though the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/s72505MIhz8.wav"} +{"id": "s7VkXHiULz8", "caption": "This heavy metal song features a male voice singing the main melody. This voice sings in an angry tone. The voice is shrieking. This is accompanied by percussion playing an aggressive rock beat. The distortion guitar plays a riff which starts off on the root note and then plays higher notes in the scale descending back to the root note. The bass plays the root notes of the chords. The mood of this song is anger. This song can be played in an action sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/s7VkXHiULz8.wav"} +{"id": "sC7T0sEG6ek", "caption": "The Epic Rock song features a punchy snare, punchy hollow kick hits, wide electric guitar chords, simple bass guitar, energetic cymbals, arpeggiated filtered melody, arpeggiated violin and arpeggiated synth melody over which there is a whispering male vocal at one point. It sounds like something you would hear at the end of an action movie, while credits are rolling.", "audio": "/zhanghaomin/datas/musiccap/music_data/sC7T0sEG6ek.wav"} +{"id": "sDX_95H0f9Q", "caption": "Here we have a couple of musicians playing bagpipes live, and in the background there is the vehicle engine sound of a supercar. The video was recorded outside as we hear the ambient noise of a city.", "audio": "/zhanghaomin/datas/musiccap/music_data/sDX_95H0f9Q.wav"} +{"id": "sDoV3sMgDhE", "caption": "The low quality recording features a short snippet of theremin solo melody, after which there is a complete silence, as the performer turned off his microphone. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/sDoV3sMgDhE.wav"} +{"id": "sEGxoHiAPiQ", "caption": "The low quality recording features a clean electric guitar chord progression that has some effects on it. It sounds slightly detuned and it has a slight wobble effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/sEGxoHiAPiQ.wav"} +{"id": "sEIn8YYD9jw", "caption": "This song features a harmonica playing the main melody. This is accompanied by percussion playing a simple beat with the focus on the snare. The bass plays the root note of the chord. Due to the low quality of the audio, the other instruments cannot be heard. T.", "audio": "/zhanghaomin/datas/musiccap/music_data/sEIn8YYD9jw.wav"} +{"id": "sETUDPPoDuo", "caption": "This music is an electronic instrumental. The tempo is fast with heavily synthesised music and electronic arrangements with heavy reverb and surround sound. The music is droning, incessant, trippy, hypnotic and trance like. This is an EDM/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/sETUDPPoDuo.wav"} +{"id": "sGAYO93RR5Q", "caption": "This instrumental funk song is a low quality recording. This song starts off with a bass playing a funky and groovy lick accompanied by a percussion playing a fill. Then a synth plays a lead using string sounds. This is accompanied by distortion guitars playing power chords. The bass continues to play funky fills and the percussion continues to play a fast beat. This song can be played in an action sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/sGAYO93RR5Q.wav"} +{"id": "sGM6xX5laFU", "caption": "This music is instrumental. The tempo is slow with an intense violin harmony with heavy bass cello. The music is intense, serious, grim, spooky, eerie, terrifying and spine chilling and sounds like the soundtrack of a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/sGM6xX5laFU.wav"} +{"id": "sGVzzQLcT0U", "caption": "The low quality recording features a passionate electric guitar lick played over electric guitar chords. It sounds emotional, soulful and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/sGVzzQLcT0U.wav"} +{"id": "sH_nDqYVq5E", "caption": "Percussions are playing together with a clarinet that takes the lead melody with very long notes. A bowed instrument is playing along with little fill-ins. An electric bass is playing a rather funky groove. The whole song sounds like it was made for dancing joyfully.", "audio": "/zhanghaomin/datas/musiccap/music_data/sH_nDqYVq5E.wav"} +{"id": "sHbGsZUsisE", "caption": "This heavy metal song features a male voice singing the main melody. The song starts with male voices singing 'hey, hey'. This is accompanied by aggressive percussion playing a rock beat. A distortion guitar is playing lead fills and another distortion guitar playing power chords. The bass plays the root notes of the chords. Another voice comes in and is screaming at a high pitch. This is accompanied by continuous snare hits for 8 bars. The main voice starts singing at this time and is accompanied by rock percussion. The bass plays the same root notes once again and the distortion guitar plays a riff in the background. The other guitar continues to play lead fills. The mood of this song is defiant. This song can be played in a rebel themed movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/sHbGsZUsisE.wav"} +{"id": "sIA-IuTI7AY", "caption": "The low quality recording features a pop folk song that consists of passionate female vocal singing over repetitive flute licks, stuttering hi hats, groovy piano chords, claps and a riser sweep. It sounds energetic and kind of addictive, thanks to those interesting melodies and a fairly repetitive female vocal.", "audio": "/zhanghaomin/datas/musiccap/music_data/sIA-IuTI7AY.wav"} +{"id": "sIItIq_W3eE", "caption": "The Electro song features a harmonizing passionate male vocals, with widely spread and dynamic echo effect on it, singing over groovy bass, groovy piano chords, synth keys and filtered \"4 on the floor\" kick pattern. It sounds exciting, easygoing and addictive - like something you would hear in a DJ set as a warm up.", "audio": "/zhanghaomin/datas/musiccap/music_data/sIItIq_W3eE.wav"} +{"id": "sJzb2AhqkSg", "caption": "This is a pop/soft rock music piece. There is a female vocalist singing melodically in the lead. The keyboard is playing the main tune while the bass guitar plays in the background. The rhythm is being provided by an acoustic drum beat. The atmosphere is lighthearted. The piece has a slow tempo. The song is in major key. This piece could be used in the soundtrack of a romantic comedy movie, especially during the scenes where the characters are reminiscing about the good old days.", "audio": "/zhanghaomin/datas/musiccap/music_data/sJzb2AhqkSg.wav"} +{"id": "sK6ltq0-zgY", "caption": "The low quality recording features a crumpling bag sound effect, followed by wide sad, dark arpeggiated bells melody and mellow synth keys chord progression. Overall it sounds sad, emotional and weird - since there is a very bad sample of crumpling bag sound effect over such a beautiful melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/sK6ltq0-zgY.wav"} +{"id": "sL01xTmV_Fc", "caption": "This is an emotional ballad played on the theremin. The audio quality is poor, but still we feel the sad and sombre effects of the melody played by the performer.", "audio": "/zhanghaomin/datas/musiccap/music_data/sL01xTmV_Fc.wav"} +{"id": "sMNuJy4f4A0", "caption": "This is a soap opera theme music. There is a clarinet playing the main tune with the acoustic guitar and the bass guitar in the backing. There is a melodic pad that can be heard. An acoustic sounding electronic cymbal and wind chimes strokes are playing every now and then. There is a sentimental atmosphere to this piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/sMNuJy4f4A0.wav"} +{"id": "sOJSjVp6UTc", "caption": "This music is instrumental. The tempo is slow with a single note played on a horn-like instrument . The instrument sounds like a Jewish Ram\u2019s horn. It is loud, emphatic, and authoritative with the sound of running water in the background . It is a celebratory,festive ritual music for making announcements. This music is Ritual music.", "audio": "/zhanghaomin/datas/musiccap/music_data/sOJSjVp6UTc.wav"} +{"id": "sOSU7p9pLjs", "caption": "An acoustic guitar is strumming chords along with a male voice rapping that gets backing vocals from a female voice for a moment. A lot of people are clapping and cheering. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/sOSU7p9pLjs.wav"} +{"id": "sOyHkcK_lOA", "caption": "A male vocalist sings this peppy Latin pop song.the tempo is medium with animated trumpets, keyboard harmony and percussions rhythms of bongos, congas and subtle drums. The song is muffled and there are sounds in the background of people talking, cheering, the sound of clinking, scuffling and tapping. The song is super imposed by the background sounds. This song is a latin pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/sOyHkcK_lOA.wav"} +{"id": "sQMzHk9MRAI", "caption": "This song contains an orchestra playing an epic sounding piece. Trumpets are playing the main melody along with a brass section providing chords, other string instruments are playing a short melody with the bow and someone is playing marching snares before a cymbal roll comes in and flutes are taking over along with strings in the background. This song may be playing in a war hero movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/sQMzHk9MRAI.wav"} +{"id": "sR8rlTIU8_Y", "caption": "A male and female singer sing this vocal duet with a choral vocal harmony. The song is medium tempo with a groovy bass line, steady drumming rhythm, guitar lead, guitars playing rhythm and keyboard harmony. The song is devotional and congregational. The song is a Christian praise and worship song with poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/sR8rlTIU8_Y.wav"} +{"id": "sRxUm-ziCBo", "caption": "This song features a harp playing the main melody. This melody is calming and relaxing. This song can be played in a meditation center. There are no other instruments in this song. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/sRxUm-ziCBo.wav"} +{"id": "sSavMIH-e-w", "caption": "The Jazz song features a saxophone solo melody playing over shimmering hi hats, groovy bass and shimmering bells melody. It sounds passionate, soft, mellow and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/sSavMIH-e-w.wav"} +{"id": "sTcaIARuemA", "caption": "The low quality recording features a live performance of a song that is barely audible due to distorted sound, loud cheering crowd and female screams. There is definitely at least a boomy bass, punchy kick and snare hits and energetic cymbals, alongside some vocals singing over it. It sounds messy and muddy, but also emotional and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/sTcaIARuemA.wav"} +{"id": "sU08gu2zJ4c", "caption": "The Electro song features a passionate female vocalist singing over wide synth pad chords, mellow synth keys, shimmering hi hats, \"4 on the floor\" kick pattern and haunting synth lead melody. It sounds addictive and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/sU08gu2zJ4c.wav"} +{"id": "sUh43prJYMM", "caption": "This music is an animated instrumental. The tempo is fast with a lively cello bass line , viola and violin harmony with a lead strung instrument which is either an Auto Harp or electric guitar. There is a child\u2019s voice superimposed on the music with incoherent words and a lot of static. The music is lively, intense,playful, fun, cheerful, animated and breezy. This music is an animated Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/sUh43prJYMM.wav"} +{"id": "sUjAb0SfppQ", "caption": "The low quality recording features a tutorial where a flat male vocalist talks, followed by echoing, uptempo electric guitar melody. The recording is really noisy and the actual sound is leaning towards the right channel - which makes the stereo image unbalanced.", "audio": "/zhanghaomin/datas/musiccap/music_data/sUjAb0SfppQ.wav"} +{"id": "sVF7NNvdoJc", "caption": "The low quality recording features a traditional song that consists of reverberant, fruity male vocal singing over wooden & percussive elements, sizzling triangle hits, sustained strings melody, plucked strings melody and breathy flute melody. It sounds soulful, passionate, emotional, calming and relaxing - like something you would hear in a small village in a foreign country, full of joy and innocence.", "audio": "/zhanghaomin/datas/musiccap/music_data/sVF7NNvdoJc.wav"} +{"id": "sXwa1Akj1t0", "caption": "The Latin Urban song features an echoing male lead vocal, alongside wide harmonizing harmonizing background vocals and echoing ad libs, rapping over \"4 on the floor kick\" pattern, smooth bass, syncopated snare, shimmering cymbals and wide shimmering shakers, followed by arpeggiated synth keys melody. It sounds uplifting, happy and like something you would dance to with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/sXwa1Akj1t0.wav"} +{"id": "sYIymaJi6tc", "caption": "This is the acoustic version of a hard rock piece performed by an orchestra of ukulele players. There are two male vocalists and one female vocalist singing melodically. The different sections of the tune are all being played by a separate ukulele. The atmosphere is easygoing. This piece could fit well in the soundtrack of an animation movie or a comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/sYIymaJi6tc.wav"} +{"id": "sYJiHxmQWjo", "caption": "This music is two separate tracks of two Turkish Rap/Hip-Hop artists. The male and female artists sing a fast tempo, energetic, enthusiastic, spirited and youthful Rap. This is contemporary Turkish Hip-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/sYJiHxmQWjo.wav"} +{"id": "sZQ4TeLueSs", "caption": "This is a low quality audio clip. This jazz song features percussion playing a Latin style beat. A chindong is being played along with the main percussion. This instrument has a 'tin' sound. There are no other instruments in this song. The male singer narrates one line in the course of this song. This is an instrumental song. The mood of this song is happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/sZQ4TeLueSs.wav"} +{"id": "sZuhztdaFYA", "caption": "The low quality recording features an electro song that consists of flat male vocals, alongside widely spread male barking onomatopoeia, singing over shimmering shakers, sizzling triangle, tinny cowbell, punchy kick, punchy snare and groovy bass. It sounds energetic and addictive, even though it is a bit repetitive.", "audio": "/zhanghaomin/datas/musiccap/music_data/sZuhztdaFYA.wav"} +{"id": "sZwZ2fOWWSg", "caption": "A female vocalist sings this captivating melody. The tempo is medium with enthusiastic drumming, soft keyboard harmony, steady bass lines and a middle eastern instrument. The song is rhythmic, catchy, peppy, vivacious and has a dance groove. This song is a Regional Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/sZwZ2fOWWSg.wav"} +{"id": "s_BKo_1LzJM", "caption": "The Electro song features a repetitive male vocal singing over shimmering hi hats, tom rolls, wide claps, groovy kick, pulsating synth lead melody and groovy synth bass, which glues everything together. Even though the vocal is repetitive, it sounds very addictive and energetic in context.", "audio": "/zhanghaomin/datas/musiccap/music_data/s_BKo_1LzJM.wav"} +{"id": "s_LMd1_XN1w", "caption": "This song is a classical music instrumental. The two main instruments it features are piano and violin - the piano plays arpeggiated chords while the violin plays legato notes. The song has a sombre and emotional tone to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/s_LMd1_XN1w.wav"} +{"id": "saEDf6EV9wg", "caption": "This is a dubstep piece. It has an electronic drum beat on the rhythmic background. There is a strong bass sound with characteristics rising from low-to-medium range. There is a high-pitched synth playing the melody. There is a loud and energetic atmosphere. This piece could be played at nightclubs. It could also be used in gaming videos or events.", "audio": "/zhanghaomin/datas/musiccap/music_data/saEDf6EV9wg.wav"} +{"id": "sbOBTkrivXM", "caption": "This hip-hop song features a male voice singing the main melody. There are other quirky voices singing in the background. This is accompanied by programmed percussion playing deep kick and snare hits. Hand claps are played on alternate counts of the bar. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/sbOBTkrivXM.wav"} +{"id": "sc7KNFUEdfY", "caption": "This song contains various orchestral instruments as a bass, plucked strings, timpani and snare hits. There are background noises, foregroundnoises as pitched voices, a river flowing and birds chirping. This music sounds like it belongs to an old videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/sc7KNFUEdfY.wav"} +{"id": "sd1gAgsXMsc", "caption": "This audio contains a big bell ringing in a steady rhythm. This is an amateur recording. This sound may be playing in a church bell tower.", "audio": "/zhanghaomin/datas/musiccap/music_data/sd1gAgsXMsc.wav"} +{"id": "sfmAeijj5cM", "caption": "This is an acoustic comedic piece. The male vocalist is singing in a manner similar to a bard, telling us a story. He is also playing the melody on a ukulele at the same time. The tune is very simple and easygoing. The atmosphere is jovial. This could be used in the soundtrack of a comedy movie or in the background of a funny video.", "audio": "/zhanghaomin/datas/musiccap/music_data/sfmAeijj5cM.wav"} +{"id": "sgJT5lIFttM", "caption": "A male singer with a rough voice sings this hip hop dance song. The song is medium tempo with a distorted electric guitar playing rhythm, keyboard accompaniment, slick drumming rhythm, telephone ring tones and various percussion hits. The song ends with a fade . The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/sgJT5lIFttM.wav"} +{"id": "sgTZHSTnU40", "caption": "An ambient instrumental piece with no drums, big reverb and complex sound design elements. Tape hiss can be heard in the background and the vibe is hazy and warm with childlike wonder.", "audio": "/zhanghaomin/datas/musiccap/music_data/sgTZHSTnU40.wav"} +{"id": "sgVqMKtUMsA", "caption": "The low quality recording features an alternative/indie song that consists of monotone male vocal singing over fat snare, energetic cymbals, energetic wide synth bass, punchy kick, reverberant synth bells melody and high pitched vocals. The instrumental is a bit pulsating as the kick comes in - almost like it was sidechained to it. It sounds energetic and sad.", "audio": "/zhanghaomin/datas/musiccap/music_data/sgVqMKtUMsA.wav"} +{"id": "sgwvhvkNELc", "caption": "A male vocalist sings this spirited song. The tempo is fast with keyboard harmony, piano accompaniment,groovy bass lines, digital drum and synthesiser arrangement. The song is catchy, enjoyable, youthful, energetic and vivacious with recurring and insistent rhythm and a dance groove. This song is a Reggae song.", "audio": "/zhanghaomin/datas/musiccap/music_data/sgwvhvkNELc.wav"} +{"id": "si_IAMPOXlQ", "caption": "This music is an intense instrumental. The tempo is medium with hard hitting drums, ceremonial big drums, amplified piano and violin harmony. The music is syncopated and intense. It is like a background score for a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/si_IAMPOXlQ.wav"} +{"id": "sjiE5CfyuHU", "caption": "This song contains an acoustic drum sample playing a groove along with an e-bass line. A high pitched sound sample is playing along with an e-piano playing single notes in a higher register. A male voice is rapping in a higher register. In-between you can hear a gunshot and a male voice shouting. This song may be playing while doing sports.", "audio": "/zhanghaomin/datas/musiccap/music_data/sjiE5CfyuHU.wav"} +{"id": "sl37XQfkJCQ", "caption": "A synthesizer pad sound, maybe analog, is rising up and down in pitch. The sound is full of frequencies.", "audio": "/zhanghaomin/datas/musiccap/music_data/sl37XQfkJCQ.wav"} +{"id": "sm7eBFHtdeA", "caption": "This orchestral song is an instrumental. There are no voices. It starts off with the string section playing a victorious melody. This is accompanied by percussion playing a simple fill. A timpani is also played. A repetitive lick is played in the background by a plucked or struck instrument. After the strings, a high pitched melody is played with a flute, This song has an epic feel and can be played at the beginning of an adventure scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/sm7eBFHtdeA.wav"} +{"id": "smU92Nu0FmY", "caption": "Synthesizers are playing pads/drones in the mid-range. You can hear water tripping sounds with a lot of reverb. A creepy voice is whispering. This song may be playing in a horror movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/smU92Nu0FmY.wav"} +{"id": "snJDZAnTMwQ", "caption": "A digital drum is playing a techno groove with a kick on every beat. A synth bass is playing a simple line along to a piano playing major chords. Panned to the sides of the speakers you can hear a xylophone like sound playing the melody along in a higher key and a marimba adding notes. A digital brass sound is adding hits to the melody. A female voice is singing in a higher key. This song may be playing in a kids tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/snJDZAnTMwQ.wav"} +{"id": "snYtQd1S12s", "caption": "The low quality recording features an uptempo chiptune song playing in the background with some synth bells sound effects. In the second half of the loop, there is a loud static noise. The recording is in mono, thin - as it lacks bass frequencies, crushed - due to the harsh mid range frequencies and it sounds like a video game sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/snYtQd1S12s.wav"} +{"id": "sp77ueBkqS0", "caption": "This music is an Electric Guitar instrumental. The tempo is medium with a pleasant electric guitar riff. The music is loud, powerful, clear, tight, intense and engaging.", "audio": "/zhanghaomin/datas/musiccap/music_data/sp77ueBkqS0.wav"} +{"id": "spyBrs3relU", "caption": "The song is an instrumental. The tempo is medium fast with two harpsichordists playing an instrument harmony with no other instrumentation. The song is exciting like a dance but has a bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/spyBrs3relU.wav"} +{"id": "srEOZzpdhs8", "caption": "The low quality recording features an arpeggiated and strummed banjo melody. The recording is noisy, in mono and the melody sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/srEOZzpdhs8.wav"} +{"id": "st92BzeUzFU", "caption": "The low quality recording features a shofar repetitive melody. The recording is in mono and so noisy that it slightly distorts the audio. It sounds soulful and reverberant.", "audio": "/zhanghaomin/datas/musiccap/music_data/st92BzeUzFU.wav"} +{"id": "stobfk1Mfjk", "caption": "The low quality recording features a widely spread, polyphonic theremin lead melody. The recording itself is very noisy, which can be heard at the very end of the loop, where a female narrator is introduced.", "audio": "/zhanghaomin/datas/musiccap/music_data/stobfk1Mfjk.wav"} +{"id": "suX7Cri4kAo", "caption": "This is a country music piece. There is a female vocalist singing melodically at the forefront. The melodic background consists of the electric guitar, the bass guitar and the piano. The rhythmic background is provided by a simple acoustic drum beat. The atmosphere is upbeat and easygoing. This piece could be playing in the background at a rock bar. It could also work well as an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/suX7Cri4kAo.wav"} +{"id": "svNayU6q3Dg", "caption": "This is a pop music piece. There is a female vocalist singing in a shout-like style. There is a flute and an electric guitar playing the melody with the bass guitar playing in the background. The rhythm is provided by a medium tempo acoustic drum beat. The tune is catchy. The piece is in the major key and there is an easygoing atmosphere to it. This piece could be used in the soundtrack of a sit-com during the credits section.", "audio": "/zhanghaomin/datas/musiccap/music_data/svNayU6q3Dg.wav"} +{"id": "swIXVQtP_TI", "caption": "The low quality recording features a cover that consists of a mandolin solo melody playing over playback instrumental that has smooth bass and acoustic rhythm guitar. The recording is noisy, in mono and it sounds passionate and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/swIXVQtP_TI.wav"} +{"id": "sxMYFYDNF_g", "caption": "This game music features an orchestra. A string section plays a melody which is in harmony with the horn section. A choir sings in the background. The percussion plays a simple beat. During this orchestral section, a voice over the radio can be heard giving instructions. The orchestral section comes to a pause and the sound of missiles being launched are played. It ends with the sound of blasts. This song can be used in a war game.", "audio": "/zhanghaomin/datas/musiccap/music_data/sxMYFYDNF_g.wav"} +{"id": "sxgMEmp5aGE", "caption": "The Traditional song features a sustained strings melody, followed by short strings melody, wide wooden percussions and shimmering shakers. It sounds soulful and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/sxgMEmp5aGE.wav"} +{"id": "sytdnmy0sRs", "caption": "The low quality recording features a gospel song that consists of harmonizing female vocals singing over groovy piano melody and some clapping. There are crowd talking noises in the background, while the recording is in mono and noisy. It sounds emotional, passionate and romantic - like something you would hear at weddings.", "audio": "/zhanghaomin/datas/musiccap/music_data/sytdnmy0sRs.wav"} +{"id": "szWQPoOH2Rw", "caption": "The Metal song features a screaming male vocal singing repetitive lyrics over distorted bass, aggressive electric guitar riff, punchy snare and kick hits, energetic cymbals and modulated acid synth lead melody. In the first half of the loop, there is a filter effect, that builds the tension before the bass drops. It sounds manic, aggressive and energetic, like something you would listen to while jumping in the mosh pit.", "audio": "/zhanghaomin/datas/musiccap/music_data/szWQPoOH2Rw.wav"} +{"id": "t-CMJ6RsZzY", "caption": "Solo ragtime piano playing a lilting instrumental section with a bouncy bass part in the left hand. The bell sound effect happens once. Good for a sunny day at a County fair or carnival.", "audio": "/zhanghaomin/datas/musiccap/music_data/t-CMJ6RsZzY.wav"} +{"id": "t-CjLfu9zCk", "caption": "The low quality recording features a live performance of flamenco guitar and acoustic guitar chord progressions. Towards the end of the loop, there are some percussive guitar taps. The recording is noisy as it was recorded outside.", "audio": "/zhanghaomin/datas/musiccap/music_data/t-CjLfu9zCk.wav"} +{"id": "t-L_PuzR67U", "caption": "This is a Swedish bridal march piece. The bagpipes are playing a festive melody. There is a ceremonial atmosphere. This piece could be played at a Swedish wedding or during a wedding scene in a Swedish historical drama movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/t-L_PuzR67U.wav"} +{"id": "t-yy7v7P0IE", "caption": "The low quality recording features a groovy slapped bass guitar melody. There are some creaking string sounds and the recording is slightly noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/t-yy7v7P0IE.wav"} +{"id": "t12O05LVSBA", "caption": "This alternative rock song features a male voice singing in a foreign language. This is accompanied by a percussion playing a simple beat with a compound time signature of 6/8. An acoustic guitar strums chords in the background. An electric guitar plays two note licks. The bass plays the root note and fifth of the chords. The mood of this song is melancholic. This is a moderate tempo song. This song can be played in a movie scene involving a long drive on the highway at night.", "audio": "/zhanghaomin/datas/musiccap/music_data/t12O05LVSBA.wav"} +{"id": "t1ULMDpL35I", "caption": "The low quality recording features a jazz live performance that consists of saxophone solo melody played over energetic cymbals, manic tom roll, punchy snare and kick hits, organ keys chords, groovy double bass and groovy piano chords. It sounds passionate and upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/t1ULMDpL35I.wav"} +{"id": "t3-xANiQrho", "caption": "This composition contains someone playing a solo melody on a horn in the mid to higher register. A string section, flutes and oboes are supported with a short rising harmony. This song may be playing live while listening to an orchestra.", "audio": "/zhanghaomin/datas/musiccap/music_data/t3-xANiQrho.wav"} +{"id": "t3758pixHZY", "caption": "The song is an instrumental. The song is medium tempo with a keyboard playing a panning harmony with no percussion. The song is emotional and haunting at the same time. The song is probably a movie soundtrack.", "audio": "/zhanghaomin/datas/musiccap/music_data/t3758pixHZY.wav"} +{"id": "t3Y9Za9roJM", "caption": "The low quality recording features a cover of a song and it consists of harmonica solo melody over arpeggiated acoustic guitar melodies played a bit sloppy. It still sounds passionate and emotional. The recording is in mono and a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/t3Y9Za9roJM.wav"} +{"id": "t5P_HJrrD64", "caption": "The low quality recording features a song that consists of a repetitive flat male vocal singing over plucked string melody, groovy bass, wooden percussion, snappy rimshots and soft kick hits. It sounds fun and happy - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/t5P_HJrrD64.wav"} +{"id": "t5RqDGLiDvo", "caption": "A male vocalist sings this violent Rock. The tempo is fast and rigorous with hard hitting drums, intense bass line and aggressive electric guitar lead with synthesiser arrangements. The song is loud, violent, thunderous,passionate, boisterous and aggressive. This song is Death Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/t5RqDGLiDvo.wav"} +{"id": "t5fW1-6iXZY", "caption": "This is an Albanian pop music piece. There are male vocals singing melodically in the Albanian language. The main theme is being played on the clarinet while there is a melodic backing composed of the acoustic guitar, the electric guitar and the bass guitar. The rhythm is provided by a laid-back acoustic drum beat. The atmosphere is lively. This piece could be used as an opening theme for an Albanian sit-com.", "audio": "/zhanghaomin/datas/musiccap/music_data/t5fW1-6iXZY.wav"} +{"id": "t637ILYjH_A", "caption": "The low quality recording features a manic, crushed music playing in the background, while there are reverberant metallic, plastic tapping and male screaming sound effects. It sounds chaotic and like a sync sound for a cartoon.", "audio": "/zhanghaomin/datas/musiccap/music_data/t637ILYjH_A.wav"} +{"id": "t6XtW3SHQNE", "caption": "The song is an instrumental. The tempo is medium fast with three accordions playing in harmony and virtuoso style , guitar strumming and other percussion instruments. The song is highly improvisational and has a bad audio quality with ambient room noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/t6XtW3SHQNE.wav"} +{"id": "t6jlx6jAb-Q", "caption": "Someone is playing a melody on an acoustic guitar and someone another melody on a oud. The two melodies complement each other. This song may be playing in a live presentation.", "audio": "/zhanghaomin/datas/musiccap/music_data/t6jlx6jAb-Q.wav"} +{"id": "t7oAteGa55g", "caption": "This song is an instrumental. The tempo is slow with vigorous drumming, keyboard and electric guitar harmony,beatboxing and the sound of a car horn .The song is vibrant, punchy, vigorous and upbeat with a dance groove. This song is a Pop Hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/t7oAteGa55g.wav"} +{"id": "t8SLY7xn7Sc", "caption": "The low quality recording features a rock song that consists of a passionate female vocal singing over shimmering hi hats, punchy snare, mellow kick hits, uptempo acoustic rhythm guitar, groovy bass and some crowd talking sounds in the background. It sounds energetic, happy and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/t8SLY7xn7Sc.wav"} +{"id": "t8os583-_JM", "caption": "The low quality recording features a cover of a latin urban song that consists of a groovy bass guitar, acoustic rhythm guitar, hand tapping and electric guitar solo playing over it in the first half of the loop, followed by harmonica solo in the second half of the loop. It sounds passionate and energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/t8os583-_JM.wav"} +{"id": "t8uF3PZ3KGQ", "caption": "This music is a soothing Chinese lute instrumental. The tempo is slow with a soft melody of the Pipa. It is melodic, zen, meditative, reflective, ponderous and calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/t8uF3PZ3KGQ.wav"} +{"id": "t9aSL2MwEDM", "caption": "This song contains a female singer singing with a lower voice. An acoustic drum is playing a simple groove with a catchy bassline. An e-guitar is playing the notes along with the bass. A keyboard is emulating an e-guitar sound by playing a little lick. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/t9aSL2MwEDM.wav"} +{"id": "tAdNaRRFFXg", "caption": "The song is an instrumental. The song is medium fast tempo with keyboard accompaniment, steady drumming rhythm, whopping sounds, strong bass line, and string synth harmony. The song is exciting and suspenseful. The song is a video arcade game soundtrack with average quality audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/tAdNaRRFFXg.wav"} +{"id": "tBKOvAiNOQE", "caption": "This is a jazz music piece. There is a piano and a trombone playing a groovy tune. The atmosphere is lively. This piece could be used as an opening theme for a nighttime talk show or a historical YouTube channel.", "audio": "/zhanghaomin/datas/musiccap/music_data/tBKOvAiNOQE.wav"} +{"id": "tDVOUsG52Jw", "caption": "This music is a simple and pleasing instrumental. The tempo is medium fast with a cheerful accordion harmony. The music is minimalist,simple, cheerful, happy, fun, carefree, jolly and lighthearted.", "audio": "/zhanghaomin/datas/musiccap/music_data/tDVOUsG52Jw.wav"} +{"id": "tDZPGf8WYmI", "caption": "This is a Christmas music piece. There is a male voice and a female voice singing melodically in the Cebuano language. The electric piano is playing the main melody while the electric guitar and the bass guitar are playing in the background. The rhythm is provided by a simple and upbeat acoustic drum beat. The atmosphere is festive and cheerful. This piece could be the opening theme of a Christmas movie that takes place in the southern Philippines.", "audio": "/zhanghaomin/datas/musiccap/music_data/tDZPGf8WYmI.wav"} +{"id": "tEZU-ZRhSoY", "caption": "The low quality recording features a harmonizing choir vocals singing over brass melody and sustained strings melody. There is a snare roll in the left channel of the stereo image. It sounds passionate, emotional and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/tEZU-ZRhSoY.wav"} +{"id": "tEdeb9eSKDI", "caption": "A male singer sings this passionate melody. The song is medium tempo with an amplified guitar playing a distant rhythm with a percussive bass line. The song has ambient noises like rain pattering down, thunder rumble sounds and ambient noise. The sound quality is poor with hissing tones. The song is an amateur metal music video.", "audio": "/zhanghaomin/datas/musiccap/music_data/tEdeb9eSKDI.wav"} +{"id": "tFVvupXoRoM", "caption": "The low quality recording features a groovy bass guitar played over a muffled, barely audible, playback instrumental. It sounds groovy and funky, even though you can hear that the player is practicing.", "audio": "/zhanghaomin/datas/musiccap/music_data/tFVvupXoRoM.wav"} +{"id": "tG5C-Smp-eY", "caption": "The low quality recording features a hip hop song that consists doubled, cool male vocals, alongside background male ad libs, rapping over jazzy piano chords, groovy kick, shimmering hi hats and soft snare hits all located in the right channel of the stereo image, making it unbalanced. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/tG5C-Smp-eY.wav"} +{"id": "tGUWSgewh0A", "caption": "The song is an instrumental. The tempo is medium with a brass band playing, trumpets blaring, tubas and trombones playing percussively, Latin percussions playing along with drum hits. The song is lively and exciting. The song is a brass band marching with a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/tGUWSgewh0A.wav"} +{"id": "tGic59TlrVg", "caption": "The Country song features a fruity male vocal singing over percussive acoustic rhythm guitar, simple bass and keys chords. It sounds emotional, passionate and heartfelt - like something you would hear in the old pubs and bars.", "audio": "/zhanghaomin/datas/musiccap/music_data/tGic59TlrVg.wav"} +{"id": "tGv_L09pf6E", "caption": "The song is a vintage recording of a church choir singing in vocal harmony. The song is medium tempo with a church organ accompanying the choir with no other instrumentation. The song is devotional and prayerful. The audio quality is highly deteriorated and is probably an amateur home video recording. The song is a classic church choir harmony.", "audio": "/zhanghaomin/datas/musiccap/music_data/tGv_L09pf6E.wav"} +{"id": "tIRHm8VhK_4", "caption": "This song contains a string instrument playing a fast and complex melody/solo while percussion instruments with a deep kick drum sound, shakers and complex clapping create a solid foundation. This song may be playing in a movie-scene in the desert.", "audio": "/zhanghaomin/datas/musiccap/music_data/tIRHm8VhK_4.wav"} +{"id": "tIS1Jaw9dCg", "caption": "This is an afrobeat music piece. There is a female vocalist singing in a seductive manner. There is an occasional male vocal sample. The keyboard is playing a minimalistic tune. There is an electronic drum beat. The atmosphere is groovy and erotic. This piece could be playing at an African nightclub.", "audio": "/zhanghaomin/datas/musiccap/music_data/tIS1Jaw9dCg.wav"} +{"id": "tJHFSRTPyew", "caption": "A female vocalist sings this spirited pop. The tempo is medium fast with percussion accompaniment like congas, bongos and drums , tambourine beats,along with amplified flute like the Ney and rhythmic oud. The music is catchy, youthful, groovy, breezy, romantic, pleasant and spirited. This music is contemporary Folk Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/tJHFSRTPyew.wav"} +{"id": "tJWduBZRJkE", "caption": "This is a chaotic mix of sound effects meant to scare the listener. There is a carousel-like tune coming from what sounds like a circus setting. Various ominous sound effects such as screaming, roaring and evil laughter can be heard in the piece. There is an ear-piercingly loud synth sound at some point. The atmosphere is creepy. This piece could be used in the soundtrack of a horror video game during a nightmare/pandemonium sequence.", "audio": "/zhanghaomin/datas/musiccap/music_data/tJWduBZRJkE.wav"} +{"id": "tKawN2sxhYc", "caption": "The song is an instrumental. The tempo is medium with a marching band rhythm, snares playing percussively , cymbals crashing, brass band harmony, trumpets blaring, trombones and tubas playing long notes. The song has a patriotic fervour and inspires. The overall sound quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/tKawN2sxhYc.wav"} +{"id": "tMICtalfpSc", "caption": "This is a vintage middle eastern song. The male singer sings passionately in Arabic, on top of a simple instrumental which features violins and a simple drum pattern. This song would be heard in an old middle eastern movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/tMICtalfpSc.wav"} +{"id": "tMMjurLqYJQ", "caption": "The low quality recording features a jazz song that consists of electric guitar melody, shimmering hi hats, snappy snare, groovy piano melody and some applause at the very beginning of the loop. The recording is noisy and it sounds passionate and reverberant.", "audio": "/zhanghaomin/datas/musiccap/music_data/tMMjurLqYJQ.wav"} +{"id": "tOb0M2k3deo", "caption": "Someone is playing a drum groove on the ride with a lot of fill-ins on toms. This song may be playing during drum practice.", "audio": "/zhanghaomin/datas/musiccap/music_data/tOb0M2k3deo.wav"} +{"id": "tOnjlUzqSC4", "caption": "This is a sad, emotional piano song. Initially, we hear the low pitch and high pitch notes played in unison. The low notes then serve as a bass backing for the treble. The song would suit a sad scene in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/tOnjlUzqSC4.wav"} +{"id": "tPJMr890HeE", "caption": "This audio is of a low quality recording. It is a hip-hop song featuring a male voice singing the main melody. This is accompanied by a female voice singing vocals in an angelic voice in the background. Programmed percussion plays a simple beat with the hi-hat being struck at every count. The bass plays the root notes of the chords. The bass notes are allowed to ring. This song has a slow tempo. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/tPJMr890HeE.wav"} +{"id": "tPVsTFGWU5Q", "caption": "The Dubstep song features a punchy kick and snare hits, groovy hi hats, aggressive synth bass and mellow bells melody played in the beginning. It sounds energetic and haunting.", "audio": "/zhanghaomin/datas/musiccap/music_data/tPVsTFGWU5Q.wav"} +{"id": "tQ1Nl4Dy2aI", "caption": "This is a Czech rap music piece. There is a male voice rapping in the Czech language. There is a medium-pitch synth playing the melody. The medium tempo electronic drum beat carries the rhythmic background. The atmosphere of the piece is loud and aggressive. This piece could be used in the soundtrack of a crime movie taking place in Central Europe.", "audio": "/zhanghaomin/datas/musiccap/music_data/tQ1Nl4Dy2aI.wav"} +{"id": "tRA-5inwlMI", "caption": "This is a gospel piece used as an accompaniment to a tambourine dance. There is a female vocalist singing. There is an electric guitar and a xylophone playing the melody. The tune is not very clear due to the quality of the recording. The atmosphere is religious. Samples could be lifted from this recording to be used in a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/tRA-5inwlMI.wav"} +{"id": "tUBTRs7Avk0", "caption": "This is an electronic/downtempo house music piece. There is a male vocalist singing melodically under heavy effects. There is a synth and an acoustic guitar playing the repeated main tune. The rhythmic background consists of an acoustic drum beat. The atmosphere is trippy. This piece could be used in the soundtrack of an animation movie, especially during vivid dream sequences.", "audio": "/zhanghaomin/datas/musiccap/music_data/tUBTRs7Avk0.wav"} +{"id": "tUJ_ZniLjhc", "caption": "A female singer sings this sad Country song. The tempo is medium with a Harmonica harmony, steady bass line, acoustic guitar, auto harp and dobro accompaniment. The song is soft, mellow, sad, poignant, emotional, sentimental and despondent with a melodious tune. This Song is a classic Country Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/tUJ_ZniLjhc.wav"} +{"id": "tUSnod37b9Q", "caption": "This audio contains someone plucking a simple bassline on an upright bass while you can hear a percussive brushing sound. Then the playing stops and a male voice starts speaking. This song may be playing in a video-tutorial.", "audio": "/zhanghaomin/datas/musiccap/music_data/tUSnod37b9Q.wav"} +{"id": "tUZB_Xf1m6k", "caption": "A male voice is singing a melody in the midrange sounding like having fun while doing so. Backing vocals are shouting at the end of his phrase. In the background you can hear the instruments playing funky melodies; rhythms and grooves. What stands out is a flute playing a flute melody sounding like a traditional chinese melody and digital strings are playing in the midrange. This song may be playing celebrating graduation with costumes.", "audio": "/zhanghaomin/datas/musiccap/music_data/tUZB_Xf1m6k.wav"} +{"id": "tUppIOzUo2Q", "caption": "A lo-fi pluck, bell sound is playing an arpeggio melody. It sounds dreamy and melancholic. This song may be playing in a sequence of a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/tUppIOzUo2Q.wav"} +{"id": "tV2m7HFJprU", "caption": "This soul funk song features a female voice singing the main melody using vocals. This is accompanied by female voices singing backing vocals. The percussion plays a simple beat in common time. The bass plays a funky bassline. The trumpet plays a repetitive fill in the background. Due to the low quality of audio, other instruments are not audible. This song is a classic disco song and can be played in a disco.", "audio": "/zhanghaomin/datas/musiccap/music_data/tV2m7HFJprU.wav"} +{"id": "tV3rvUSlVnY", "caption": "This music is a cheerful instrumental. The tempo is medium with the lead harmony on a Xylophone, energetic drumming, keyboard accompaniment and rhythmic acoustic guitar. The audio quality is inferior and the music is muffled and muddy. There are background sounds like people talking, laughing and ambient nature sounds like a breeze. The music is fun, youthful, simple, enjoyable, chirpy and vivacious.", "audio": "/zhanghaomin/datas/musiccap/music_data/tV3rvUSlVnY.wav"} +{"id": "tW7478HnmCs", "caption": "This symphonic song features a melody played on cellos and violins in the beginning. A similar melody is played on the harpsichord soon after. The harpsichord plays the melody as well as the bass notes. There is no percussion in this song. This song has no voices. This is an instrumental song which can be played at a black tie event.", "audio": "/zhanghaomin/datas/musiccap/music_data/tW7478HnmCs.wav"} +{"id": "tWByqbOvYQE", "caption": "The low quality recording features a live performance and it consists of groovy strings chords, addictive strings melody, breathy flute melody, simple bass and wooden percussive elements. It is a bit noisy, roomy, mono, but still addictive and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/tWByqbOvYQE.wav"} +{"id": "tWexzTJPxQs", "caption": "The low quality recording features a children's song that consists of organ keys chords, groovy piano chords, light snare hits, soft kick hits, shimmering hi hats, and flute melody. There are some squeaky sound effects, alongside plastic foley effects and outdoor ambience sounds. It sounds fun and happy, like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/tWexzTJPxQs.wav"} +{"id": "tWseBEYhE1M", "caption": "This children's song features truck sounds. This is accompanied by a keyboard playing a melody using a flute-like sound. A twinkling melody is played in the background. The percussion is programmed. The percussion plays a simple beat. The bass plays the root and fifth notes of the chords. The mood of the song is happy. There are no voices in this song. This song can be used in a children's animated movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/tWseBEYhE1M.wav"} +{"id": "tWwvTUm9RXs", "caption": "The low quality recording features a tutorial that consists of a flat male vocal talking over snappy wooden snare one shots. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/tWwvTUm9RXs.wav"} +{"id": "tYq21a42Mvg", "caption": "This instrument is a low quality audio recording. The instruments are not audible.", "audio": "/zhanghaomin/datas/musiccap/music_data/tYq21a42Mvg.wav"} +{"id": "tZgww16UyU8", "caption": "The Hip Hop song features a flat male vocal rapping over arpeggiated piano melody, sustained high pitched violin melody, punchy snare and kick hits, simple hi hats, boomy bass and soft crash cymbal. It sounds heartfelt, emotional and sad.", "audio": "/zhanghaomin/datas/musiccap/music_data/tZgww16UyU8.wav"} +{"id": "tbovKStEnME", "caption": "The song is an instrumental. The tempo is medium with an accordion player, guitar rhythm, flute player and other percussion playing in harmony. The song is groovy and has gypsy flavour to it. The song audio quality is poor with ambient crowd noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/tbovKStEnME.wav"} +{"id": "tc7crRl2JqA", "caption": "This is a rocksteady music piece. There is a male vocalist with a Jamaican accent singing in a relaxed manner. The melody is being played by an electric guitar and a keyboard with a groovy bass guitar joining them in the background. The acoustic drums are playing a slow tempo reggae beat in the rhythmic background. The atmosphere is chill and tropical. This piece could be used in the soundtrack of a romance movie with a tropical setting. It could also be playing in the background at a beach or a seaside restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/tc7crRl2JqA.wav"} +{"id": "tcOHcop3sCQ", "caption": "The low quality recording features a soft rock song sung by a flat male vocal over mellow, acoustic rhythm guitar chords. It sounds vintage and therefore nostalgic, emotional, sentimental and warm. The recording is a bit noisy and in mono as well.", "audio": "/zhanghaomin/datas/musiccap/music_data/tcOHcop3sCQ.wav"} +{"id": "tdTT6rmkk9M", "caption": "Someone is playing a kick on every beat along with little fill-ins on toms, cymbals and hihat. An e-bass is playing long notes along with an acoustic guitar finger picking chords while another guitar is playing higher pitched notes in a tremolo. A male voice is singing in a higher pitch sounding grateful. An atmospheric synth pad sound is rising in the background processed with a lot of reverb. This song may be playing with headphones enjoying a beautiful day.", "audio": "/zhanghaomin/datas/musiccap/music_data/tdTT6rmkk9M.wav"} +{"id": "tdrz4EkIsow", "caption": "A female vocalist sings this pleasant chant. The song is medium fast tempo with groovy basslines, mellifluous flute, steel pan beat,small hand cymbals and synthesiser arrangement. The song is sweet, melodic, hypnotic, enthralling, enigmatic, trance-like, trippy and psychedelic. This song is a contemporary indian worship song.", "audio": "/zhanghaomin/datas/musiccap/music_data/tdrz4EkIsow.wav"} +{"id": "teyDfFbVMSY", "caption": "This is a live performance of a religious song. There is a male vocalist singing melodically as the lead. The main melody is being played by the keyboard with the electric guitar and the bass guitar in the background. The rhythmic background is provided by the electronic drums and the electronic percussion. The piece has movements reminiscent of Jewish music.", "audio": "/zhanghaomin/datas/musiccap/music_data/teyDfFbVMSY.wav"} +{"id": "thHSYzhoLo4", "caption": "A male vocalist sings this soft melody. The tempo is slow with a mellow keyboard harmony, steady drumming, subtle bass line and acoustic guitar accompaniment. The song is soft, romantic, melodic, emotional , sentimental, melancholic and pleasant. This song is classic Soft Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/thHSYzhoLo4.wav"} +{"id": "tjQTZM-sqS0", "caption": "This song features a drum solo. The solo starts with 4 strokes on the kick drum followed by three strokes on the snare and cymbals together. Then the kick is played in groups of three strokes and the hi-hat is and snare is played in a repetitive pattern. This song has no other instruments and no voices. This song can be played in an instructional video.", "audio": "/zhanghaomin/datas/musiccap/music_data/tjQTZM-sqS0.wav"} +{"id": "tju-t_Bz_W8", "caption": "This is an R&B and hip hop inspired instrumental. The drum pattern is 808 kick heavy and typically found in hip hop. The main melodic instruments are the fuzzy bass which plays long sustained notes, and there's also a beeping synth which sounds like the tones of old morse code machines. There are sound effects like a laughing man, children chanting, and a muffled shouting sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/tju-t_Bz_W8.wav"} +{"id": "tk4s-nlhmEQ", "caption": "A baby cries in pain followed by a slowed down version of the audio that sounds like a groan. The sound track has an Arabian flavour to it with a traditional horn playing melody with a keyboard harmony and no percussion. The audio quality is extremely poor and highly distorted.", "audio": "/zhanghaomin/datas/musiccap/music_data/tk4s-nlhmEQ.wav"} +{"id": "tlDBOenCGV4", "caption": "The low quality recording features wooden percussion playing in the right channel, shimmering xylophone playing in the left channel and dissonant bells chords in the middle of the stereo image. It sounds suspenseful and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/tlDBOenCGV4.wav"} +{"id": "tllFsEPv7Ls", "caption": "The Electro song features a punchy \"4 on the floor\" kick pattern perfectly complemented by groovy bass, followed by tinny laser percussive sound effects, shimmering cymbals, claps and echoing pulsating synth lead melody. Sounds energetic, a bit addictive thanks to that synth lead and something like you would hear in electronic dance music clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/tllFsEPv7Ls.wav"} +{"id": "tmabzx6yxqs", "caption": "This kids song features groovy synth keys, chords, simple piano melody, echoing and wide pig oink sound effects, shimmering shakers, muffled claps, soft kick hits and groovy bass. It sounds fun and happy - like something that children would listen to in their favorite tv shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/tmabzx6yxqs.wav"} +{"id": "tmpVzeD_M5s", "caption": "This clip is an instrumental. The tempo is slow with the sound of an acoustic guitar being tuned. This is a tutorial on how to tune a guitar.", "audio": "/zhanghaomin/datas/musiccap/music_data/tmpVzeD_M5s.wav"} +{"id": "tnDUwvxQU3k", "caption": "The low quality recording features a funk/soul song that consists of a passionate female vocal singing over groovy bass guitar, wide strings chords, low repetitive plucked strings melody, punchy snare layered with claps, soft kicks and shimmering cymbals. It sounds emotional, passionate and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/tnDUwvxQU3k.wav"} +{"id": "tnJb9WyhCUc", "caption": "The low quality recording features a hydraulophone melody played alongside water leaking sound. The recording is wide, noisy and it sounds relaxing and calming.", "audio": "/zhanghaomin/datas/musiccap/music_data/tnJb9WyhCUc.wav"} +{"id": "tnSM-SnE5Lk", "caption": "The low quality recording features a distant brass melody and loud impact, after which there are church bells sounds. It is noisy and in mono and it sounds like a compilation.", "audio": "/zhanghaomin/datas/musiccap/music_data/tnSM-SnE5Lk.wav"} +{"id": "too9MtXBwts", "caption": "A sweet, melancholy sounding soft rock song with a male singer accompanied by acoustic guitar strumming, a cello counter melody, piano, simple electric bass, and a slow rock drum beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/too9MtXBwts.wav"} +{"id": "tpamd6BKYU4", "caption": "This children's song features a male voice singing the main melody. Children repeat numbers after the main voice sings. This is accompanied by percussion playing a simple beat. The bass plays a groovy bassline. A keyboard plays in the background. A sound like a marimba plays individual notes in an ascending order followed by descending notes. An organ plays chords in the background. The mood of this song is happy. This song can be played in a children's educational animation movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/tpamd6BKYU4.wav"} +{"id": "tpnvHb9ZhlU", "caption": "The low quality recording features an electro song that consists of a \"4 on the floor\" kick pattern and widely spread repetitive synth melody. The recording is crackly and it sounds hypnotic and energetic as the synth lead is moving left and right throughout the stereo image.", "audio": "/zhanghaomin/datas/musiccap/music_data/tpnvHb9ZhlU.wav"} +{"id": "tr2iVjsu4xs", "caption": "This song features a brass quintet. The bass notes are played on a tuba. The main melody is played on the trumpets. This is backed by the trombone and French horn. There are no other instruments in this song. There are no voices in this song. This song is an instrumental song with an epic feel. This song can be played when a victorious protagonist enters the city after a battle in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/tr2iVjsu4xs.wav"} +{"id": "tsdNl72WVs4", "caption": "The low quality recording features a steel guitar melody, followed by accordion melody. There are some popping sounds and it sounds passionate, happy and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/tsdNl72WVs4.wav"} +{"id": "tt5-i1R78ms", "caption": "This is a trap music piece done in the style of Michael Jackson. There is a male vocalist singing in a very accentuated manner. In the rhythmic background loud electronic drums can be heard with the cicada beat on the hihats which is essential to the trap scene. There is a strong electronic bass sound accompanied every now and then by an electric guitar sample.", "audio": "/zhanghaomin/datas/musiccap/music_data/tt5-i1R78ms.wav"} +{"id": "tu3IrmT_2xk", "caption": "In this clip we have a man speaking Hebrew, followed by the sound of a high pitched traditional horn. In the background, there are unidentifiable noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/tu3IrmT_2xk.wav"} +{"id": "tuoBmxts5Xo", "caption": "The low quality recording features a live performance of a jazz song that consists of a tenor sax solo melody playing over mellow piano chords, sustained strings, groovy bass, snappy rimshots, shimmering hi hats and punchy kicks. It sounds emotional, passionate and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/tuoBmxts5Xo.wav"} +{"id": "tv14XEQcY0c", "caption": "This is an Azerbaijani folk music piece. It is an instrumental piece. The only instrument being played is a garmon which has a sound that resembles an accordion. There is a lively atmosphere in the recording. This piece can be played in the soundtrack of a documentary that takes place in the Caucasus region. It could also be used in the soundtrack of an Azerbaijani soap opera.", "audio": "/zhanghaomin/datas/musiccap/music_data/tv14XEQcY0c.wav"} +{"id": "tvcJENqxr1c", "caption": "The low quality recording features a high pitched, sped up audio playing in the background, followed by arpeggiated electric guitar melody and smooth bass guitar. Even though the sped up audio sounds weird, the guitar melodies are emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/tvcJENqxr1c.wav"} +{"id": "tvqvuGywD8U", "caption": "This audio contains someone blowing a shofar horn with a lot of reverb and a long release time. Panned to the right side of the speakers you can hear water dripping. This song may be playing while doing something like qigong.", "audio": "/zhanghaomin/datas/musiccap/music_data/tvqvuGywD8U.wav"} +{"id": "tw0BGErgupk", "caption": "This hip-hop song features a high pitched voice sounding like a cartoon voice singing the main melody. The quality of the recording is low and some of the instruments cannot be identified. The voice is accompanied by a flute in the beginning and then a piano fill. A synth plays chords in the background. This song can be played in an animated movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/tw0BGErgupk.wav"} +{"id": "tw8-TlQBcBA", "caption": "This is an electropop/synth-pop music piece. It is an instrumental piece. There is a crunchy sounding electric guitar tune at the forefront. The rhythmic background consists of an aggressive acoustic drum beat. The atmosphere is hard-hitting. This piece could be playing in the soundtrack of a coming-of-age drama movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/tw8-TlQBcBA.wav"} +{"id": "tyAXjOihm6g", "caption": "The low quality recording features groovy wooden percussion. The recording is in mono, noisy and it sounds boomy.", "audio": "/zhanghaomin/datas/musiccap/music_data/tyAXjOihm6g.wav"} +{"id": "tz2TlSMmTp4", "caption": "A lot of high frequencies that are produced by an e-bass and two distorted electric guitars are running through amps that are sounding highly overdriven. The drums silently build up the atmosphere before all instruments are loudly breaking into the next part of the song. The drums with crash hits and the guitars and bass with one single low note while a male voice is screaming. This song may be playing at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/tz2TlSMmTp4.wav"} +{"id": "u0CgRmXMXNc", "caption": "This is the recording of a bell ringing lesson video. There is a set of three small church bells being played in various ways. There is a male voice speaking in an instructive manner on how to ring the bells. He is speaking in the Russian language. This recording can be sampled for use in beat-making. The bell sample could also fit well as a sound effect in a cartoon or a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/u0CgRmXMXNc.wav"} +{"id": "u0lm58cet1g", "caption": "This is a pop/disco music piece. There is a male vocalist singing melodically in the lead while the main tune is being played by the saxophone. In the rhythmic background, there is an electronic drum beat with percussive elements surrounding it. The atmosphere is energetic and danceable. This piece could be playing in the background at a dance club during a retro-themed night.", "audio": "/zhanghaomin/datas/musiccap/music_data/u0lm58cet1g.wav"} +{"id": "u1a5eyk-9ig", "caption": "The low quality recording features a kids song sung by harmonizing kids vocals over shimmering bells, claps, synth keys melody, groovy bass and shimmering hi hats in the right channel of the stereo image. It sounds fun, happy, addictive, thanks to that cadence, and like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/u1a5eyk-9ig.wav"} +{"id": "u3n2OcpEC48", "caption": "The low quality recording features a suspenseful tone of didgeridoo. The recording is mono and noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/u3n2OcpEC48.wav"} +{"id": "u3pYqyLM0f4", "caption": "The song is an instrumental. The song is medium fast tempo with a strong techno drum rhythm, groovy bass line, keyboard harmony and percussion hits. The song is exciting and groovy for dance. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/u3pYqyLM0f4.wav"} +{"id": "u3yOMK8SuRI", "caption": "This song is a simple instrumental. The tempo slows with the sound of clapping followed by a soft and mellow ukelele melody. This is a home video of a Ukelele instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/u3yOMK8SuRI.wav"} +{"id": "u68Ghaf_Phs", "caption": "This folk song features a variety of instruments. The main melody is played on a violin, flute and accordion. The double bass plays a running bass pattern. An acoustic guitar strums chords. A hammered dulcimer plays parts that give a percussive feel. There are no voices in this song. This is an instrumental song. This song can be played in a luxurious and lively brunch.", "audio": "/zhanghaomin/datas/musiccap/music_data/u68Ghaf_Phs.wav"} +{"id": "u6tgeRXOxnU", "caption": "A male vocalist sings this energetic rap. The tempo is fast with electronic music and synthesiser arrangements with digital drum rhythm and boomy bass. The song is upbeat, energetic, buoyant, punchy and youthful with a bright dance groove. This song is an EDM/Synth pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/u6tgeRXOxnU.wav"} +{"id": "u8aB6EALonk", "caption": "The song is an instrumental. The song is in medium tempo with a harpist playing a beautiful cascade of notes while the orchestra watches. The song is exciting and passionate. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/u8aB6EALonk.wav"} +{"id": "u9n4R78UBtA", "caption": "This music is an electronic instrumental. The tempo is fast with atmospheric synthesiser, digital drum arrangements and an insistent, recurring female vocalisation. The music is upbeat, youthful, trance, trippy, hypnotic, psychedelic, incessant, and enthusiastic EDM/Synth Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/u9n4R78UBtA.wav"} +{"id": "uA-JpZppFsc", "caption": "The low quality recording features an accordion melody with some plastic tapping keys along the way. It sounds soulful and passionate and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/uA-JpZppFsc.wav"} +{"id": "uARzr9CAemI", "caption": "The Electro song features a resonant synth melody, repetitive synth melody and widely spread, mellow synth pad chords playing. It sounds relaxing and calming, like something you would listen to while chilling.", "audio": "/zhanghaomin/datas/musiccap/music_data/uARzr9CAemI.wav"} +{"id": "uAYPacrJnyQ", "caption": "The song has a futuristic kind of feel. It's a synth pop song with a female vocalist who has a robotic filter and autotune applied to her voice. The feel of the song is sort of epic and progressive. It's action-oriented and feels like something cool is about to happen.", "audio": "/zhanghaomin/datas/musiccap/music_data/uAYPacrJnyQ.wav"} +{"id": "uAgizG1hYw0", "caption": "The low quality recording features a rock song that contains filtered female vocal singing over loud and harsh electric guitar chords, energetic drums and buzzy bass guitar. It sounds chaotic due to the bad mix and since the drums are panned in an unconventional way - making the stereo image unbalanced. It sounds harsh, but also energetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/uAgizG1hYw0.wav"} +{"id": "uBENjCPS8LI", "caption": "A digital drum is playing a simple groove along with an e-bass. An organ is playing long chords with a lot of reverb. On top of that male voices sing a melody in harmony. Their voices sound high. This song may be playing with headphones while running.", "audio": "/zhanghaomin/datas/musiccap/music_data/uBENjCPS8LI.wav"} +{"id": "uCCdUB7D10U", "caption": "The song is an instrumental. The tempo is medium with a steady drum march rhythm, steady bass line, keyboard harmony and a synth string section. The song is Eros\u2019s and emotional. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/uCCdUB7D10U.wav"} +{"id": "uCXI7dgABHI", "caption": "The low quality recording features a groovy cajon percussion, electric guitar chords and groovy synth bass. It sounds groovy and funky.", "audio": "/zhanghaomin/datas/musiccap/music_data/uCXI7dgABHI.wav"} +{"id": "uDqVzJtaxOc", "caption": "This is a sound effect showcase recording. A bunch of different effects are applied to what is sounding similar to a sine wave. The sounds are robotic and bizarre. Certain parts of the recording can be lifted from the recording to be used as FX samples.", "audio": "/zhanghaomin/datas/musiccap/music_data/uDqVzJtaxOc.wav"} +{"id": "uE3BHXXiCFs", "caption": "The low quality recording features an afrobeats song that consists of a flat male vocal rapping over punchy 808 bass, strings melody, shimmering hi hats, claps and some snare rolls. It sounds addictive, bouncy and groovy thanks to that rhythm.", "audio": "/zhanghaomin/datas/musiccap/music_data/uE3BHXXiCFs.wav"} +{"id": "uF1KTW5rT-s", "caption": "The low quality recording features a live performance that consists of shimmering shakers, wooden percussion, breathy flute melody and passionate female vocals singing over it. It sounds very addictive, due to the lead vocal cadence. It is a bit reverberant, as it was recorded in a larger room, with a low quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/uF1KTW5rT-s.wav"} +{"id": "uGQ7QnKqeY4", "caption": "This is an excerpt from a cartoon that involves sound effects resembling an intro to a minimal techno song. There is a breathing sound coming from one of the characters. There is also a glass sound effect. There is an overarching sci-fi character to the sounds.", "audio": "/zhanghaomin/datas/musiccap/music_data/uGQ7QnKqeY4.wav"} +{"id": "uGfd3xanwro", "caption": "This audio contains people playing percussive instruments in the background. In the foreground you can hear someone playing a flute in a higher pitch. The sound of the flute is overdriving the speakers of the recording completely. This recording is of very poor audio-quality. This song may be playing while celebrating.", "audio": "/zhanghaomin/datas/musiccap/music_data/uGfd3xanwro.wav"} +{"id": "uHgpDP_4Lsc", "caption": "A female singer sings this beautiful wedding song for the bride. The song is a medium tempo with traditional Indian instruments like the tabla playing percussion and stringed instruments playing rhythm. The song is heartfelt and emotional. The song is a mehendi ceremony song or a bridal preparation song for her wedding,", "audio": "/zhanghaomin/datas/musiccap/music_data/uHgpDP_4Lsc.wav"} +{"id": "uJPW9BEhU6Y", "caption": "The low quality recording features a boomy hip hop song with repetitive synth lead melody playing in the background, while there are some bouncing ball sound effects and plastic impact foley effects. It sounds like someone is hitting a plastic object on a wooden surface.", "audio": "/zhanghaomin/datas/musiccap/music_data/uJPW9BEhU6Y.wav"} +{"id": "uKGo4phKqLM", "caption": "The music excerpt features a male voice that's speaking instead of singing. A latin music percussion section is driving the pulse of the music. Trumpets can be heard playing short melodies and also accents that stop and start the music. The tempo of the music is pretty fast. At one point the crowd can be heard cheering. The quality of the audio recording is not that good, which leads me to believe it was recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/uKGo4phKqLM.wav"} +{"id": "uLp6z37bfVE", "caption": "A lot of very active church bells ringing together.", "audio": "/zhanghaomin/datas/musiccap/music_data/uLp6z37bfVE.wav"} +{"id": "uNUx8rqcy0M", "caption": "The Low quality recording features a reverberant female vocal singing beautiful melodies over widely spread acoustic rhythm guitars chord progressions. It sounds passionate and emotional thanks to that female vocal.", "audio": "/zhanghaomin/datas/musiccap/music_data/uNUx8rqcy0M.wav"} +{"id": "uPGasFKZSBo", "caption": "The recording is done live, in a moving vehicle. The vehicle sound is heard. There is a tambourine for percussion, a crunchy electric guitar being played as the melodic instrument, and the singer has an enigmatic and charming style. The song is an alternative rock song that feels positive and magnetic.", "audio": "/zhanghaomin/datas/musiccap/music_data/uPGasFKZSBo.wav"} +{"id": "uQE3fLdzpKs", "caption": "This audio contains someone playing tao percussion with fast drumrolls. In the background you can hear other noises. This is an amateur recording. This song may be playing live at a traditional performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/uQE3fLdzpKs.wav"} +{"id": "uQTCfT5XDzQ", "caption": "This music is an electric guitar instrumental. The tempo is slow with an electric guitar lead and harmony of a popular song. No other instrument is used. It is mellow, pleasant, nostalgic, soft , mellifluous and soothing.", "audio": "/zhanghaomin/datas/musiccap/music_data/uQTCfT5XDzQ.wav"} +{"id": "uRA5Ue30fsY", "caption": "This is an Oriental dance music piece. It is an instrumental piece. There is an oud and a new flute playing the melody. The rhythmic background is composed of percussive elements such as the def and the tambourine. The atmosphere is exotic and sensual. This piece could be used in the soundtrack of movies that take place in the Middle East region.", "audio": "/zhanghaomin/datas/musiccap/music_data/uRA5Ue30fsY.wav"} +{"id": "uS2kPLvEo6A", "caption": "This is a live performance of the Tibetan singing bowls. The performer is repeatedly striking the bowls with a small hammer and making them vibrate with resonant sound. These sounds create a calming, relaxing aura. This piece would make a perfect background track for a meditation video.", "audio": "/zhanghaomin/datas/musiccap/music_data/uS2kPLvEo6A.wav"} +{"id": "uSZQGP_i3gs", "caption": "The Electro song features repetitive echoing bells, simple piano chords, groovy bass and huge down sweep. It sounds exciting, chill and easygoing - like the drop is incoming.", "audio": "/zhanghaomin/datas/musiccap/music_data/uSZQGP_i3gs.wav"} +{"id": "uT-S_JC_GzU", "caption": "The song is an instrumental. The song is medium tempo with a groovy bass line and a guitar synth tone playing melody. The song is exciting and adventurous in nature. The song is a video game song track.", "audio": "/zhanghaomin/datas/musiccap/music_data/uT-S_JC_GzU.wav"} +{"id": "uTfLf1Y8hhM", "caption": "A female voice is singing soulfully. She gets support from several backing vocals singing harmonies along. A tambourine is holding the rhythm along with a bassline and a e-guitar giving the song a reggae feeling. This song may be playing in a car. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/uTfLf1Y8hhM.wav"} +{"id": "uUNlJ4KZTPE", "caption": "This ambient song features synth pads playing in the background. Synth sounds are layered to give a wave-like feel. There is no percussion in this song. Bells are played at intervals. Toward the end, a mid-range flute sound is played. The sound of rattles are played in the background. This song has an ethereal feel. This song is meditative and can be used in a meditation or yoga session.", "audio": "/zhanghaomin/datas/musiccap/music_data/uUNlJ4KZTPE.wav"} +{"id": "uUoEB3DBSjo", "caption": "harsh sounding drumline music with a screechy bagpipe, active bass drum, marching snare drum. The sound is loud and grating.", "audio": "/zhanghaomin/datas/musiccap/music_data/uUoEB3DBSjo.wav"} +{"id": "uXMMzpgrY2g", "caption": "This song sounds fun to dance along. It has digital and acoustic percussion, a catchy bassline/synthesizer sound and a male singer that sounds to be in a good mood. This song may be playing and dancing along.", "audio": "/zhanghaomin/datas/musiccap/music_data/uXMMzpgrY2g.wav"} +{"id": "uYCAxX2F6DA", "caption": "This audio contains someone playing a tibetan bowl ringing in a high pitch. This may be playing during meditation.", "audio": "/zhanghaomin/datas/musiccap/music_data/uYCAxX2F6DA.wav"} +{"id": "uYCMVgUAwnM", "caption": "A male voice is rapping/singing in a higher pitch. His voice is strongly processed with effects. Also with autotune. The instrumental contains digital drums with a strong kick with a subbass. With every hit a synthesizer pad is playing along. This is an amateur recording. This song may be playing in a recording studio.", "audio": "/zhanghaomin/datas/musiccap/music_data/uYCMVgUAwnM.wav"} +{"id": "uYYpqx0rzok", "caption": "A jukebox is playing a folk melody in a very bad audio-quality along with some plastic clapping sounds. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/uYYpqx0rzok.wav"} +{"id": "uZHE9b1WDuM", "caption": "The song is an instrumental. The tempo is fast , with a philharmonic orchestra consisting of string section, rhythm section and horns accompanying a virtuoso wooden xylophone playing this western classical hit. The song is energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/uZHE9b1WDuM.wav"} +{"id": "uZesGREO0eI", "caption": "A male vocalist sings this dulcet, soulful song in a foreign language. The tempo is medium with bass guitar lead and acoustic guitar accompaniment. The song is minimalist instruments with vocal emphasis. It is a soft, emotional, sentimental, mellifluous, soulful, soothing, calming, pleasant , warm and tender Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/uZesGREO0eI.wav"} +{"id": "u_TfWvyYY0Y", "caption": "This instrumental is a Heavy Metal instrumental. The tempo is fast with hard hitting drumming, furious and vigorous amplified keyboard playing a harmony, electric bass guitar and electric guitar accompaniment. The music is intense, grim, compelling, passionate, powerful and harmonious. The vibe of the music is serious, sinister, grim and steely. This is used in Hard Rock/Heavy Metal.", "audio": "/zhanghaomin/datas/musiccap/music_data/u_TfWvyYY0Y.wav"} +{"id": "ua0hgl8fi0I", "caption": "The low quality recording features a live performance of a classical song that consists of sustained strings and flute melody. There are some chair crackling noises, as well as camera shuttering sounds. It sounds emotional and passionate, and the recording itself is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/ua0hgl8fi0I.wav"} +{"id": "ucSF9NIxK8A", "caption": "The low quality recording features a traditional song sung by harmonizing female vocals and followed by wooden percussion, short flute licks and mellow piano chords. It sounds addictive and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/ucSF9NIxK8A.wav"} +{"id": "udQQrQB-gr4", "caption": "The Industrial Rock song features a groovy bass, punchy snare, groovy kick pattern, shimmering cymbals, addictive electric guitar melody and arpeggiated synth keys melody playing. It sounds energetic and emotional - like something you would jump to at concerts.", "audio": "/zhanghaomin/datas/musiccap/music_data/udQQrQB-gr4.wav"} +{"id": "ue1sgGEvkwE", "caption": "This music is an Electronic instrumental. The tempo is fast with vigorous electronic and heavily synthesised music using DL mixer, turn table and drum machines.The Ustica is youthful, futuristic, contemporary, vigorous, groovy, psychedelic, trance, hypnotic ,boomy and pulsating. This music is an Electronica/Tech House.", "audio": "/zhanghaomin/datas/musiccap/music_data/ue1sgGEvkwE.wav"} +{"id": "uegzZWp6Y4w", "caption": "This song features a male voice narrating a story in the beginning. This is followed by a drum roll in a marching beat style. A bass note is played which is the root note of the chord. An organ strikes a chord and plays it staccato style. A guitar also strikes a chord. There are no other instruments in this song. This song can be played in a movie trailer.", "audio": "/zhanghaomin/datas/musiccap/music_data/uegzZWp6Y4w.wav"} +{"id": "ui6ERk-AySw", "caption": "This is the live performance of an indietronica music piece. The melody is being played by the electric guitars and the bass guitar. The rhythmic background consists of a fast tempo acoustic drum beat. The atmosphere is melancholic. This piece could be used in the soundtrack of a drama movie that takes place in a city setting.", "audio": "/zhanghaomin/datas/musiccap/music_data/ui6ERk-AySw.wav"} +{"id": "uiHyWdYkBvY", "caption": "This is a glam metal/heavy metal ballad. There is a male vocal and male back vocals singing melodically. The melody is being played on an electric guitar with a chorus effect applied alongside a bass guitar. The rhythmic background consists of a rock acoustic drum beat.The atmosphere is both hard-hitting and sentimental at the same time. This piece could be playing in the background of a rock/metal bar. It could also be included in the soundtrack of an 80s themed romance movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/uiHyWdYkBvY.wav"} +{"id": "uknhELOFYmY", "caption": "Some big and bold percussion instruments, namely timpanis, are used in this piece and create a bold and magnetic atmosphere. There is an intricate piano melody that comes in after the rhythmic percussive intro. The song fits into the east asian part of the world.", "audio": "/zhanghaomin/datas/musiccap/music_data/uknhELOFYmY.wav"} +{"id": "un-OXLWhvDc", "caption": "This song contains someone playing blues on a clean e-guitar. Then a male voice starts singing calmly and with a mid ranged voice. This song may be playing in a road-movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/un-OXLWhvDc.wav"} +{"id": "uoZ9Rs4E-6Y", "caption": "This song is played on a harpsichord. The harpsichord plays the bass and treble notes. This is a classical composition. There are no other instruments in this song. There are no voices in this song. This song can be used when a member of royalty arrives at a palace.", "audio": "/zhanghaomin/datas/musiccap/music_data/uoZ9Rs4E-6Y.wav"} +{"id": "uoee1ikakWY", "caption": "This is an amateur low-resolution recording of an electric guitar with the chorus pedal effect. The player keeps on strumming chords to show the effect of the pedal. This piece could be used as an old-fashioned rock guitar sample for a beat.", "audio": "/zhanghaomin/datas/musiccap/music_data/uoee1ikakWY.wav"} +{"id": "uqAY4lCUcRY", "caption": "This audio contains a brass band playing a slow melody. Some are playing a layer of a long chord in the mid to higher register. on top of that a trumpet is leading a melody than other trumpets are coming in giving a loud answer. This song may be played live, performed by part of an orchestra.", "audio": "/zhanghaomin/datas/musiccap/music_data/uqAY4lCUcRY.wav"} +{"id": "uqUNGNZoxrg", "caption": "This is a DJ performance piece. The DJ is scratching the turntable over a breakbeat sample. The constantly shifting electronic drums are in the rhythmic background. There is a beat repeat effect added on the beat in the background. The atmosphere is urban. This piece could be playing in the background of a basketball skills compilation video.", "audio": "/zhanghaomin/datas/musiccap/music_data/uqUNGNZoxrg.wav"} +{"id": "ura8EjHjGC4", "caption": "Someone is scratching along with a backing track that contains a strong kick, a snare and a dark sounding melody. This is an amateur recording. This song may be playing at home practicing scratching.", "audio": "/zhanghaomin/datas/musiccap/music_data/ura8EjHjGC4.wav"} +{"id": "usrzF-0GbLY", "caption": "The low quality recording features a live performance with flat male vocals talking over electric guitar solo melody, shimmering and bright drums cymbals, snappy rimshots, groovy bass and simple piano chord progression. Sounds fun and groovy - like something you would dance to with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/usrzF-0GbLY.wav"} +{"id": "uuHTPvG-BYI", "caption": "This audio sample features tribal music played using only percussion and voices. There are no other instruments. The percussion is played by hand and has a tribal feel. The female voices sing in a foreign language. There are fills sung by male voices in harmony. The feel of the song is one of celebration. The tempo of the song is moderate. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/uuHTPvG-BYI.wav"} +{"id": "uwPeQy7ZtGo", "caption": "This music is instrumental. The tempo is slow with an electronic keyboard playing a simple, high pitched harmony. There are sounds in the background like whirring, whooshing and clicking. The music is not very clear as the audio clip is muffled, but it sounds like video game music or the music Ina child\u2019s electronic toy.", "audio": "/zhanghaomin/datas/musiccap/music_data/uwPeQy7ZtGo.wav"} +{"id": "uxLY3CBoPo8", "caption": "This song features an electric guitar playing the main melody. The guitar plays three ascending chords. Each chord is strummed once at the beginning of the bar. The tremolo bar is used to give the sound a tremulous effect. There are no other instruments in this song. There are no voices in this song. This is an instrumental song. This song can be played in a guitar instruction video.", "audio": "/zhanghaomin/datas/musiccap/music_data/uxLY3CBoPo8.wav"} +{"id": "uy3nQ9VYE-Q", "caption": "A digital drum is playing a simple groove with a digital bass. An e-piano is playing 2 chords to add some color to the song. A male voice is rapping with light adults in the background. In the background a female voice sample is coming in singing a little melody. This song may be playing in a car slowly riding down the streets.", "audio": "/zhanghaomin/datas/musiccap/music_data/uy3nQ9VYE-Q.wav"} +{"id": "v0tYHz5mk4I", "caption": "The music features a female voice singing with a reverb effect and out of tune. An acoustic guitar accompanies the singer with chords and arpeggios. In the background a synth sound that resembles an instrument with strings plays arpeggios.", "audio": "/zhanghaomin/datas/musiccap/music_data/v0tYHz5mk4I.wav"} +{"id": "v1EDTMRmJlY", "caption": "The low quality recording features a reggae song that consists of passionate male vocal singing over offbeat, widely spread guitar chords, groovy bass, punchy kick hits, punchy snare hits layered with claps, bouncy wooden percussions and echoing brass melody. It gives off happy and fun vibes - as every reggae song should.", "audio": "/zhanghaomin/datas/musiccap/music_data/v1EDTMRmJlY.wav"} +{"id": "v29jCrlSCmE", "caption": "A fast rock drum beat with cowbell and muffled singer with heavy vocal processing. Two electric guitars holding chords, electric bass and drum set.", "audio": "/zhanghaomin/datas/musiccap/music_data/v29jCrlSCmE.wav"} +{"id": "v2Ng8iGwf40", "caption": "This song features sounds from a game. A groovy bassline is played. This is accompanied by percussion playing a simple rhythm. A violin fill is played in the background. Quirky sounds are played in the foreground depicting some actions like jumping and crossing game levels. Birds can be heard chirping in the background. There is the sound of a waterfall toward the end of the clip. Bubble bursting sounds are played when the character collects some rewards. There are no lyrics in this song and no words being sung.", "audio": "/zhanghaomin/datas/musiccap/music_data/v2Ng8iGwf40.wav"} +{"id": "v3wR3aIQ23w", "caption": "This song contains digital drums with an overdrive kick going together with a digital bass. Another synth sub bass is playing a melody. On top of that a lofi bitrate sound is playing a melody in the higher register. This song may be playing during a videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/v3wR3aIQ23w.wav"} +{"id": "v4sANJkuwP4", "caption": "This symphonic song features an orchestra. At the beginning, a French horn plays a melody. This is followed by a harmony played by the string section and brass section. There is no percussion in this song. This song is uplifting. The mood of this song is suspenseful. This song can be played in a movie where a dangerous scene is taking place.", "audio": "/zhanghaomin/datas/musiccap/music_data/v4sANJkuwP4.wav"} +{"id": "v582kPp43Mg", "caption": "This orchestral song features male voices singing the main melody. The song starts off with a marching beat played on snare drums. When the voices start to sing, the feeling is one of victory. This is accompanied by percussion playing a marching beat. There are instruments playing staccato notes. The bass is played on a stringed instrument and it follows the root notes of the chords. This song is played at a moderate tempo. This is a patriotic song.", "audio": "/zhanghaomin/datas/musiccap/music_data/v582kPp43Mg.wav"} +{"id": "v592zQpuaJA", "caption": "The low quality recording features a resonating bowl sound, followed by mellow metallic percussion. The recording is noisy and it sounds a bit harsh and disturbing.", "audio": "/zhanghaomin/datas/musiccap/music_data/v592zQpuaJA.wav"} +{"id": "v5SsASLy2c8", "caption": "This audio contains people playing saxophones in all ranges and with a fast melody. This song may be playing as part of an orchestral performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/v5SsASLy2c8.wav"} +{"id": "v5nB2OJnCko", "caption": "The track is instrumental. The tempo changes building suspense, violins trilling, string section harmony, brass section plays percussively and piano plays suspenseful notes. This is a movie soundtrack. The audio quality is average.", "audio": "/zhanghaomin/datas/musiccap/music_data/v5nB2OJnCko.wav"} +{"id": "v6A7Iggebm4", "caption": "The low quality recording features a cover of a rock song sung by passionate female vocalists, followed by acoustic rhythm guitar chord progression and shimmering shaker. It is a bit reverberant and noisy, as they are playing in a room. It gives off happy and fun vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/v6A7Iggebm4.wav"} +{"id": "v88cAXP03As", "caption": "A female voice is singing with a little bit of reverb and delay on her voice. A synth pad is playing a soft string drone sound in the mid-range. An acoustic guitar is playing an arpeggio melody along with a synth pluck sound walking down a scale and another pluck sound playing a melody on top. All of them have different rhythm structures and seem to play against each other but fitting perfectly together. The sounds are spread across both sides of the speakers. This song may be playing in a ceremony at a festival.", "audio": "/zhanghaomin/datas/musiccap/music_data/v88cAXP03As.wav"} +{"id": "v8bBrrXUpdo", "caption": "The low quality recording features a national anthem sung by harmonizing girls' vocals. It sounds passionate and emotional. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/v8bBrrXUpdo.wav"} +{"id": "v9TTtjEngjY", "caption": "The music track is that of a band marching in the streets. The tempo is medium with a Band march, playing percussion in a steady rhythm accompanied by flutes playing in unison. The song has bad audio quality with ambient noises of people talking and other street noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/v9TTtjEngjY.wav"} +{"id": "vBkDLBO-Aok", "caption": "The low quality recording features a quacking ducks sound effects as an intro, after which comes a manically played drum roll that includes snares and toms, leading into the wide electric guitars, punchy kick, energetic crash cymbal, shimmering hi hats and fat bass guitar. At the very beginning, there is a short audio crackle that makes this recording's quality low.", "audio": "/zhanghaomin/datas/musiccap/music_data/vBkDLBO-Aok.wav"} +{"id": "vBw99ghST1g", "caption": "The low quality recording features a classical song that consists of an aggressive brass melody, punchy percussion hits, mellow low percussions and hollow flute melody playing over it. It sounds vintage, suspenseful, reverberant, intense and the recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/vBw99ghST1g.wav"} +{"id": "vByuZEzCZJg", "caption": "This is a Latin American dance song in the salsa style. We hear layers of upbeat, rhythmic percussion that's suitable for dancing. Maracas, bongos, and a groovy and complex bassline coupled with a melodic instrument make for a vibrant and fun party/dance song.", "audio": "/zhanghaomin/datas/musiccap/music_data/vByuZEzCZJg.wav"} +{"id": "vDmUlgsDOP4", "caption": "This audio contains a drum playing with a lot of toms. A distorted e-guitar is playing a solo melody. In the background panned to the right side of the speakers you can hear a keyboard playing minor chords in the higher mid-range. This song may be playing while sitting in your room dancing for yourself.", "audio": "/zhanghaomin/datas/musiccap/music_data/vDmUlgsDOP4.wav"} +{"id": "vDrbslhtX8o", "caption": "The jazz music features a swing band playing in the background. In the foreground one can hear tap dancing sounds and the crowd cheering. This and the low audio quality leads me to believe this is a recording of a live tap dancing show.", "audio": "/zhanghaomin/datas/musiccap/music_data/vDrbslhtX8o.wav"} +{"id": "vEMNk-lbGTE", "caption": "This hip-hop song features a male voice rapping the main lyrics. This is accompanied by programmed percussion playing a simple beat. Hand claps are played on every alternate count. The synth plays a repetitive melody in loop. The bass plays the root notes of the chords in harmony with the synth. This is a moderate tempo song. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/vEMNk-lbGTE.wav"} +{"id": "vEN9szBPBkw", "caption": "This rock and roll song features a male voice singing the main melody. This is accompanied by percussion playing a simple beat in common time. An overdriven guitar plays chords with licks in between lines. The bass plays the root notes of the chords. The mood of this song is happy. This song can be played in a movie scene when the protagonist is walking into a hotel prior to a fight scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/vEN9szBPBkw.wav"} +{"id": "vEl7ImwLlrA", "caption": "This slow jazz song features a sliding melody played on the trombone. The accordion plays chords. The piano plays a repetitive lick in the background on the high registers. The contrabass plays the root notes of the chords and also plays percussion by striking the body of the instrument. After one bar, the instruments pause for two counts. After that, the accordion resumes playing. There are no voices in this song. This is an instrumental song. This song is seductive. This song can be played in a movie scene where a man is trying to seduce a woman at a bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/vEl7ImwLlrA.wav"} +{"id": "vEt13GxzDKk", "caption": "A female vocalist sings this happy Indian wedding song. The tempo is medium fast with a cheerful dholak and a rhythmic shaker made of ghungaroos. The song is a minimalist, cheerful, happy, festive, celebratory and joyful song sung during Punjabi wedding rituals.", "audio": "/zhanghaomin/datas/musiccap/music_data/vEt13GxzDKk.wav"} +{"id": "vG0FGgJlDGw", "caption": "This instrumental song features a tuba and a clarinet. The tuba plays the bass part of the song. The clarinet plays the high notes. This song does not have any voices. There is no percussion in this song. This song can be played in a comedy movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/vG0FGgJlDGw.wav"} +{"id": "vG0QJ3bjfqk", "caption": "This is an instrument review recording. There is a piano playing a sentimental tune while a male voice is narrating his experience with the instrument. From the parts where the voice is absent, there are tunes with a movie music feel to them. These lines could be sampled and added to the soundtrack of a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/vG0QJ3bjfqk.wav"} +{"id": "vK9x7UQ9Y7k", "caption": "A male vocalist sings this meditative chant. The tempo is slow with keyboard harmony, steady drumming, rhythmic acoustic guitar,tambourine and female vocal backup. The song is a vocal riff of a chant sung melodiously. It is calming, peaceful, meditative, pensive, soothing, prayerful and devotional. This song is sung during Hindu festivities or Pujas.", "audio": "/zhanghaomin/datas/musiccap/music_data/vK9x7UQ9Y7k.wav"} +{"id": "vKNGqQ3GRB8", "caption": "This song features an electric guitar playing arpeggiated chords. There are open strings being played in the arpeggios. A chorus effect is added to the guitar sound. At the end of the song, one guitar chord is played. There are no voices in this song. This is an instrumental song. There are no other instruments in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/vKNGqQ3GRB8.wav"} +{"id": "vKjC5HTH22o", "caption": "This is a Mexican folk music piece. There is a male vocal singing at a very elevated volume that resembles shouting. There is a brass melody playing alongside the vocal. The atmosphere of the piece is playful. The best use for this piece could be as an accompaniment for a folk dance. It could also be used in the soundtrack of a comedy movie or a TV show that takes place in Mexico.", "audio": "/zhanghaomin/datas/musiccap/music_data/vKjC5HTH22o.wav"} +{"id": "vMU7ZKY2Eso", "caption": "A male vocalist sings this lively Latino song. The tempo is fast with an animated piano accompaniment, bright trumpets, energetic and rhythmic drumming, groovy bass and keyboard. The song is energetic, lively, buoyant, bouncy, vibrant and vivacious with a dance groove. This song is Latin Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/vMU7ZKY2Eso.wav"} +{"id": "vNPL092rPgQ", "caption": "This song is a male voice beatboxing with a child singing an upbeat, catchy vocal riff in a foreign language . The tempo is fast with an upbeat rhythm. The song is energetic, engaging and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/vNPL092rPgQ.wav"} +{"id": "vNPx6RS8PiM", "caption": "This song contains someone playing a bass-ukulele along to a piano playing jazzy chords along with a soft jazz piano. The main melody is being played by an alto saxophone. This song may be playing in a jazz lounge bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/vNPx6RS8PiM.wav"} +{"id": "vNZ3JS1LjDc", "caption": "The low quality recording features a flat male lead vocal, alongside harmonizing background vocals, singing over, staccato background vocals, groovy bass, wooden percussion, shimmering shakers and \"4 on the floor\" kick pattern. At the very end of the loop, there is a dark arpeggiated bell melody. Overall, it sounds happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/vNZ3JS1LjDc.wav"} +{"id": "vOAXAoHtl7o", "caption": "This song is an instrumental. The tempo is medium with lively trumpets, trombone ,enthusiastic percussion like the snare, cymbals and bass drum, tambourine , an intense and bright string harmony of violins, viola and cello. The music is intense, serious and is gradually building up. This is an Orchestral piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/vOAXAoHtl7o.wav"} +{"id": "vOU-qA25xNM", "caption": "The low quality recording features a ceramic bowl tone getting progressively louder, while there are some metallic ball impacts in the background. The recording is a bit noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/vOU-qA25xNM.wav"} +{"id": "vOiDwXo-SuM", "caption": "This clip features a guitar song. An overdriven guitar is struck at the beginning. This is followed by an electric guitar strumming two chords once each. The chords are strummed with a light overdrive sound. There are no other instruments in this song. A male voice talks in a narrative tone at the end of the segment.", "audio": "/zhanghaomin/datas/musiccap/music_data/vOiDwXo-SuM.wav"} +{"id": "vQ09gQBt1IU", "caption": "This audio contains a lot of percussion such as shakers panned to both sides of the speakers. An organ is playing a melody panned to the left side and a digital trumpet/guitar sound is playing a melody panned to the right side of the speakers. A soft percussion sound is creating a bassline while male voices are singing as a choir and a main singer in the foreground. This song may be playing as a live performance in an african country.", "audio": "/zhanghaomin/datas/musiccap/music_data/vQ09gQBt1IU.wav"} +{"id": "vQHKa69Mkzo", "caption": "This clip is an instrumental. The tempo is fast with no harmony. There is a sinister synthesised music playing in the background to the sounds of a male voice screaming in pain, an airplane flying, crashing, exploding, blasts, tumbling and scraping and the sound of a bird or cricket . The sinister music incessantly plays in the background. The vibe of this audio is sinister, spooky, eerie, haunting, dangerous and destructive.", "audio": "/zhanghaomin/datas/musiccap/music_data/vQHKa69Mkzo.wav"} +{"id": "vQcB6NI7cMo", "caption": "The low quality recording features a mellow female vocal narrating over a wide soft dark synth pad. There is a constant buzzy noise in the background. It sounds suspenseful, calming and hypnotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/vQcB6NI7cMo.wav"} +{"id": "vStedb9LiDk", "caption": "This is a Somali pop music piece. There are multiple layers of the keyboard providing the melodic structure. The rhythmic structure is provided by an electronic drum beat. The atmosphere is energetic and danceable. This piece could be used in the soundtrack of a Somali sit-com as the opening theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/vStedb9LiDk.wav"} +{"id": "vTXb8P7sAFY", "caption": "This audio contains a string section playing long notes in the lower register and some strings are playing a dissonant melody that is creating more tension. This composition may be playing in a horror movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/vTXb8P7sAFY.wav"} +{"id": "vVNWjq9byoQ", "caption": "A male vocalist sings this song in a foreign language. The tempo is fast with rhythmic oud , steady drumming, shofar and strong vocal backup. The audio is muffled and incoherent making it difficult to hear the other instruments used. This song is a Middle Eastern Pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/vVNWjq9byoQ.wav"} +{"id": "vWM2qG-nU-Y", "caption": "This is a Christian gospel music. There is a male vocalist singing melodically. The melody is being played by the piano with a strings section accompaniment. The atmosphere is spiritual and sentimental. This piece could be playing in the background of Christian social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/vWM2qG-nU-Y.wav"} +{"id": "vWiq7n4yTAw", "caption": "This instrumental song is played on a didgeridoo. This is a continuous drone sound which is resonant and played in a low pitch. There is no percussion in this song. The instrument is played in a repetitive pattern producing low sounds with higher pitched vibrating sounds inter-spread in between notes. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/vWiq7n4yTAw.wav"} +{"id": "vXtk2JEP0zM", "caption": "This clip features a rhythm played on a tambourine. It starts off with a galloping rhythm which is sped up. At the end, the tambourine is not struck and only the jingles are allowed to ring. There are no other instruments in this song. There are no voices in this song. This song can be played in a folk gathering.", "audio": "/zhanghaomin/datas/musiccap/music_data/vXtk2JEP0zM.wav"} +{"id": "vYP60jdTupc", "caption": "An e-bass and strings are playing a simple melody to elevate the atmosphere. In the background an acoustic piano is playing a melody along with the drums. Then a female voice starts singing while the crowd starts cheering. This song may be playing live during a tv-show.", "audio": "/zhanghaomin/datas/musiccap/music_data/vYP60jdTupc.wav"} +{"id": "vZ9IanI59gE", "caption": "This folk song features a male voice singing the main melody. This is accompanied by a tabla and dhol playing the percussion. A keyboard plays fills after the voice pauses. The other instruments are not audible due to the low audio quality. This song can be played at a Hindu religious gathering.", "audio": "/zhanghaomin/datas/musiccap/music_data/vZ9IanI59gE.wav"} +{"id": "vZUup6rK728", "caption": "The low quality recording features a live performance that consists of a theremin solo melody played over arpeggiated piano melody. It sounds sad, emotional and passionate, even though the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/vZUup6rK728.wav"} +{"id": "vd1dgdxlA94", "caption": "The low quality recording features a bagpipe solo melody with some crowd noises in the background. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/vd1dgdxlA94.wav"} +{"id": "vf3n40mDLHw", "caption": "This music is a percussive instrumental. The tempo is medium fast with an Electronic drum kit using snare, bass drum and cymbal to create a rhythmic riff. The sound is plied and controlled. This music is a demo video or a tutorial on how to play electronic drums.", "audio": "/zhanghaomin/datas/musiccap/music_data/vf3n40mDLHw.wav"} +{"id": "vfMEPOl1Wqw", "caption": "The song is an instrumental. The tempo is medium with a violinist playing a poignant melody with pizzicato played at the beginning. The song is emotional and poignant. The song is a YouTube music video.", "audio": "/zhanghaomin/datas/musiccap/music_data/vfMEPOl1Wqw.wav"} +{"id": "vfscNjNneZg", "caption": "This is an electronic afrobeat music piece. The electronic percussive elements are providing the rhythmic background. The keyboard is playing a repeated theme in a rising pattern. There is a brief shouting male vocal sample in the distance. The atmosphere is energetic. This piece could be playing at a nightclub or a dance club.", "audio": "/zhanghaomin/datas/musiccap/music_data/vfscNjNneZg.wav"} +{"id": "vgpV6F9tge8", "caption": "Someone is playing an acoustic guitar along with someone playing a solo melody on top with another plucked string instrument. They are accompanied by someone playing a djembe or another percussive instrument. This song may be playing sitting around a bonfire.", "audio": "/zhanghaomin/datas/musiccap/music_data/vgpV6F9tge8.wav"} +{"id": "vhTWW5Bx15Q", "caption": "This is a radio program recording from Romania. There is a male vocal rapping Romanian while another is beatboxing. Then, the rapper starts talking in a radio announcement voice. This recording could be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/vhTWW5Bx15Q.wav"} +{"id": "vispMqNJ1j8", "caption": "The low quality recording features a didgeridoo melody played outside, alongside some birds chirping and tinny wooden impacts sounds. The recording is noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/vispMqNJ1j8.wav"} +{"id": "vjW8wmF5VWc", "caption": "The Hip Hop song features an echoing male vocal, alongside exciting background male vocals, singing over shimmering bells, echoing synth lead melody, punchy kick, snaps and short 808 bass. It sounds groovy and addictive - like something you would hear in clubs and on a radio.", "audio": "/zhanghaomin/datas/musiccap/music_data/vjW8wmF5VWc.wav"} +{"id": "vmBkZflwViA", "caption": "This is a classical music piece performance. It is meant to be played at a wedding. There is an organ playing a simple and festive tune. There is an atmosphere of celebration in this piece. This music would fit perfectly with weddings. Organ samples could also be lifted from this recording to be used in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/vmBkZflwViA.wav"} +{"id": "vmVOWilkmOA", "caption": "The Recording features a live performance of a classical song played on harpsichord. It is emotional, passionate and a bit spooky, as it sounds like a vampire theme song.", "audio": "/zhanghaomin/datas/musiccap/music_data/vmVOWilkmOA.wav"} +{"id": "vmz9kAEiTSc", "caption": "Synthesizers are playing pads. There is a low pad sound serving as bass, mid and high string pad sounds. A low male voice is singing. The whole recording has reverb on it. This song may be playing while meditating.", "audio": "/zhanghaomin/datas/musiccap/music_data/vmz9kAEiTSc.wav"} +{"id": "vnwKpQeza3A", "caption": "This is a recording of two didgeridoos. They are playing low notes and create a very low vibrational tone. There is a melody, but it is not easily recognizable.", "audio": "/zhanghaomin/datas/musiccap/music_data/vnwKpQeza3A.wav"} +{"id": "vo-o3dG8Oq0", "caption": "Here we have a compilation of songs led by accordions. The first clip is more of a folk ballad with a cheery and uplifting tone to it, the second clip is an emotional ballad.", "audio": "/zhanghaomin/datas/musiccap/music_data/vo-o3dG8Oq0.wav"} +{"id": "vo7BYs1OqbM", "caption": "Live performance of a girl band group, featuring surf guitar and a go-go beat that transitions to modern pop production with loud bass and electronic drum breaks. Audio is low fidelity. Would be popular with teenage girls.", "audio": "/zhanghaomin/datas/musiccap/music_data/vo7BYs1OqbM.wav"} +{"id": "vp6p45b-038", "caption": "This song contains a evolving synth pad sound in the higher register with noise. A piano is playing a sad minor chord progression in the mid range. Then a strong industrial sounding digital drum comes. This song may be playing in a very sad movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/vp6p45b-038.wav"} +{"id": "vpU4XIISXtM", "caption": "The Electro song features a \"4 on the floor\" boomy 808 bass, shimmering shakers, muffled syncopated snare, repetitive short male vocal chants, high pitched female vocal and frequency sweep riser. It sounds funny, groovy and energetic. The drums are stuttering at one point, which serves as a transition to the next section.", "audio": "/zhanghaomin/datas/musiccap/music_data/vpU4XIISXtM.wav"} +{"id": "vpcEBryyej4", "caption": "The low quality recording features a live performance of a folk song that consists of a saxophone solo melody, accordion melody and acoustic rhythm guitar. It sounds passionate and soulful. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/vpcEBryyej4.wav"} +{"id": "vqRFzhWik2c", "caption": "A male vocalist sings this catchy Hip-Hop. The tempo is medium with an acoustic guitar riff, boomy bass drops, punchy drumming, digital beats and synthesiser arrangement with enthusiastic vocal backup. The song is youthful, buoyant, punchy, groovy, pulsating with a dance groove. This song is Contemporary Hip-Hop.", "audio": "/zhanghaomin/datas/musiccap/music_data/vqRFzhWik2c.wav"} +{"id": "vrMmkVV4SOE", "caption": "An organ is playing low notes serving as a bassline while a drummer is hitting the drums with a lot of fill-ins losing the rhythm and shouting. This recording is of poor quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/vrMmkVV4SOE.wav"} +{"id": "vrNQbCbBlLY", "caption": "This is a middle eastern song with a rapid and intricate accordion melody as the main basis. The song would be suitable as a backing track for a belly dancer. There's a traditional percussion instrument in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/vrNQbCbBlLY.wav"} +{"id": "vrxT5jhqu0Q", "caption": "This is the live recording of a dance piece. The dancer can be heard stepping her foot on the ground and clapping her hands in a rhythmic fashion. The recording is a bit poor in quality, but samples could be lifted to be used in beats.", "audio": "/zhanghaomin/datas/musiccap/music_data/vrxT5jhqu0Q.wav"} +{"id": "vsDriIwNAmU", "caption": "The recording is of tubular bells being played live. The melody is descending and the melodic tone of the tubular bells is preceded by a slight transient.", "audio": "/zhanghaomin/datas/musiccap/music_data/vsDriIwNAmU.wav"} +{"id": "vsXs3GUrw64", "caption": "This music is instrumental. The tempo is medium fast with an incessant droning of the didgeridoo, sound of a timer ticking and male vocals like a chant. The music is eerie, creepy, spooky, sinister, scary, hypnotic, trance like and fear inducing with resounding effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/vsXs3GUrw64.wav"} +{"id": "vtVfl5Ff5lw", "caption": "The track is an upbeat blues song that features falsetto and raspy male vocals. A drum kit plays an energetic and happy beat. A bass guitar follows the rhythm and adds a bouncy vibe to the song. The overall sound of the instruments is bright and happy. A guitar follows the bass and the drum kit.", "audio": "/zhanghaomin/datas/musiccap/music_data/vtVfl5Ff5lw.wav"} +{"id": "vtnuHbHbveg", "caption": "A male and child sing in animated vocals. The song is medium tempo with western classical music influences, flute harmony, keyboard accompaniment, standing bass line and piano accompaniment. The song is positive and cheerful with an onus on children\u2019s education.", "audio": "/zhanghaomin/datas/musiccap/music_data/vtnuHbHbveg.wav"} +{"id": "vukJyd8xt0I", "caption": "virtuosic solo ukelele playing a chord melody in free time.", "audio": "/zhanghaomin/datas/musiccap/music_data/vukJyd8xt0I.wav"} +{"id": "vvfs2TUj-D4", "caption": "This is a Christian rock piece. There is a male vocalist in the lead singing gently and melodically. A mild-tempered electric guitar is playing the main theme. There is a bass guitar holding the root notes. The rhythmic background is provided by the acoustic drums. This song has a mellow and hopeful atmosphere. Due to being religious in nature, this piece could be played in the background of Christian religious content. It could also be played at Christian religious events.", "audio": "/zhanghaomin/datas/musiccap/music_data/vvfs2TUj-D4.wav"} +{"id": "vx5iuWuE2Ng", "caption": "This song contains acoustic drums playing a groove along with an e-bass and a tambourine. A brass section is playing along with the drum fills and the bongos. A piano is playing a melody together with a guitar strumming chords in the mid range. The male singer sounds loud and soulful. This song may be playing in a rollerblade disco.", "audio": "/zhanghaomin/datas/musiccap/music_data/vx5iuWuE2Ng.wav"} +{"id": "vxIF3B4YqW8", "caption": "This is an R&B/soul music piece. There is a female vocal singing at a high pitch joined by a male vocal singing at a medium pitch and a female choir backing. The beat has a repeating electric guitar tune. There is a groovy bass line. The rhythm is provided by an electronic drum beat. The atmosphere is emotional and grandiose. This piece could be playing in the background at a memorial event.", "audio": "/zhanghaomin/datas/musiccap/music_data/vxIF3B4YqW8.wav"} +{"id": "vy2gUzgmBzQ", "caption": "This goth metal song features a male voice singing the main melody. The voice is deep. Toward the end, there are other male voices singing vocables. This is accompanied by heavy percussion using a five-beat common time pattern played on floor toms with a shuffle note each note creating a triplet feel. The distortion guitars play heavy descending chord riffs using palm muting technique. The bass guitar plays the root notes of the chords. At the background, there is an high pitched sound played on a synth that gives this song an eerie feel. This song can be played at the end credits of a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/vy2gUzgmBzQ.wav"} +{"id": "vyNstX5b1V8", "caption": "This song features an electric guitar. The guitar starts off with a descending pentatonic run. A descending slide is played followed by a moderate tempo blues lick. There are no other instruments in this song. There is no voice in this song. This is an instrumental song with a blues mood. This song can be played as an instructional blues song.", "audio": "/zhanghaomin/datas/musiccap/music_data/vyNstX5b1V8.wav"} +{"id": "vykrv5BaW-s", "caption": "This song contains someone playing a melody with a flute in a higher register. The flute sounds offkey. An e-guitar is fingerpicking two chords. In the background you can hear percussive instruments and an e-bass. A male voice is talking/shouting sounding as if he wants to motivate the listener. This song may be playing live in a big bar or during an event in a latin.american country.", "audio": "/zhanghaomin/datas/musiccap/music_data/vykrv5BaW-s.wav"} +{"id": "w-YAUcPl-HU", "caption": "The low quality recording features a sad soft rock song that consists of an acoustic rhythm guitar chord progression over which the reverberant female vocalist sings. The recording is very noisy and it sounds sad and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/w-YAUcPl-HU.wav"} +{"id": "w-qG-P9E1U4", "caption": "This is the recording of video game gameplay. Initially, sounds of footsteps on wood can be heard. Then, a childish voice can be heard wailing. Afterwards, a tune starts playing on a small keyboard and a xylophone. It sounds generic and circus-like. Sounds from this recording can be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/w-qG-P9E1U4.wav"} +{"id": "w09XinexaIY", "caption": "The low quality recording features synchronized wooden percussion. It is noisy, in mono and it sounds upbeat.", "audio": "/zhanghaomin/datas/musiccap/music_data/w09XinexaIY.wav"} +{"id": "w0A-4EbkVz8", "caption": "This is a live performance classical music piece played by a chamber orchestra. It is in the style of a tarantella, which is a genre of Italian folk music. The strings section is playing the melody with a cello as the lead. The atmosphere is lively and elegant. It could be used in the soundtrack of a movie especially during a scene involving a pursuit, a face-off or a duel.", "audio": "/zhanghaomin/datas/musiccap/music_data/w0A-4EbkVz8.wav"} +{"id": "w0QJT6ywza0", "caption": "A chic 80's pop/R&B song that is an influence on the synthpop of today. Features a male vocalist singing in falsetto, doubled vocals and lush vocal harmonies, a driving beat, low toms, a sharp electronic clap, synth pads and a steady synth bassline.", "audio": "/zhanghaomin/datas/musiccap/music_data/w0QJT6ywza0.wav"} +{"id": "w0yHqPxybQE", "caption": "This song features a synth playing the main melody. The synth plays a heavenly voice with a pad like backing. There are no other instruments in this song. There is no voice in this song. The mood of this song is relaxing. This song can be played in a meditation center.", "audio": "/zhanghaomin/datas/musiccap/music_data/w0yHqPxybQE.wav"} +{"id": "w2MeQg3W7Po", "caption": "This audio contains a huge amount of people playing a melody on the bagpipes while others are playing a kick sound on every beat. This song may be playing live during a big public event.", "audio": "/zhanghaomin/datas/musiccap/music_data/w2MeQg3W7Po.wav"} +{"id": "w2vMywh5Nto", "caption": "The excerpt features a mandolin playing a folk song. This is the only musical instrument playing, there aren't others or any voices singing. The character of the song is joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/w2vMywh5Nto.wav"} +{"id": "w35p3oCU0g4", "caption": "The low quality recording features a bagpipe melody, drum rolls and some man shouting sound. The recording is in mono and it is a bit noisy, as it was recorded outdoors.", "audio": "/zhanghaomin/datas/musiccap/music_data/w35p3oCU0g4.wav"} +{"id": "w3QIsHxQfPE", "caption": "This song is an animated Children\u2019s Song. The tempo is fast with many singing different parts. The song is simple and happy with spirited backup vocals, female, male and child vocals with an animated keyboard harmony, rhythmic drumming , acoustic guitar and choral harmony. The song is light, peppy, engaging and is designed for toddlers and children. The audio is a home recording and the song is muffled.", "audio": "/zhanghaomin/datas/musiccap/music_data/w3QIsHxQfPE.wav"} +{"id": "w41gqTFYh08", "caption": "This song contains a minor chord composition on a acoustic piano. The drums is playing a slow groove with lot of pauses and a snapping snare sound. On top of that a male voice is singing in a higher pitch sounding sad. Male backing vocals are providing harmonie and support. This song may be playing with headphones during a breakup with a partner.", "audio": "/zhanghaomin/datas/musiccap/music_data/w41gqTFYh08.wav"} +{"id": "w4Z1QuBOMWU", "caption": "The song is an instrumental. The tempo is medium with a guitarist playing traditional flamenco style guitar in a rhumba rhythm. The song has a Latin dance groove and sounds delightful. The song has a poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/w4Z1QuBOMWU.wav"} +{"id": "w4ayJNZ5w5o", "caption": "The low quality recording features an electric guitar solo melody played with some sliding techniques. It sounds cool, passionate and the recording is noisy and in mono, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/w4ayJNZ5w5o.wav"} +{"id": "w5EbmsPfGSo", "caption": "A drum is playing a lot of crash hits with fast and accurate snare rolls along to a backing track that contains an e-guitar playing a riff in a lower key. This song may be playing at a studio practicing.", "audio": "/zhanghaomin/datas/musiccap/music_data/w5EbmsPfGSo.wav"} +{"id": "w5qf9O6c20o", "caption": "An acoustic piano is playing a sad sounding composition while someone is playing a synthesizer lead-sound that sounds like someone crying. You can hear a lot of white noise in the recording. This seems to be an amateur recording. This song may be playing on a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/w5qf9O6c20o.wav"} +{"id": "w62KGC7um_Y", "caption": "Cheery, upbeat Latin music featuring a lively male singer, busy percussion including hand percussion like bongos and congas as well as cowbell and more. String bass plays a syncopated tumbao rhythm while a brass section accompanies a trombone.", "audio": "/zhanghaomin/datas/musiccap/music_data/w62KGC7um_Y.wav"} +{"id": "w6MtzUCl4vM", "caption": "This song contains digital drums playing a hiphop kinda feel along with a bassline. The most energy comes from the male voice singing with autotune and a lot of backing voices cheering and singing along: Then a male voice starts rapping. The backing voices are spread across the both sides of the speakers. This song may be playing outside chilling with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/w6MtzUCl4vM.wav"} +{"id": "w6zHc6nRJ0o", "caption": "The Metal song features a repetitive, aggressive male vocal screaming over wide, aggressive electric guitar chords, distorted bass guitar, punchy snare and kick hits and energetic cymbals. There is a toms roll at the end of the loop. It sounds aggressive, energetic and manic - like something you would jump into a mosh pit at the concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/w6zHc6nRJ0o.wav"} +{"id": "w8c7JFU6by4", "caption": "The Urban Latin song features a harmonizing male vocals singing over \"4 on the floor\" kick pattern, shimmering hi hats, syncopated snare hits layered with simple synth lead melody and buzzy synth bass. It sounds energetic and addictive, like something you would hear in clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/w8c7JFU6by4.wav"} +{"id": "w9CxACZ5Oi0", "caption": "This is a Western music piece performed live by an orchestra. There is a mandolin playing the main melody. Many strummed instruments such as acoustic guitar and ukulele are being played in the melodic background. These sounds evoke an adventurous feeling This piece could be used in the soundtrack of a Western movie/TV series. It could also suit well in the soundtrack of a wild west themed video game like Red Dead Redemption.", "audio": "/zhanghaomin/datas/musiccap/music_data/w9CxACZ5Oi0.wav"} +{"id": "w9EGDo9Yybc", "caption": "This is an excerpt from a TV series. There are female voices that can be heard. There is a walking sound. The birds are singing. There is a mellow flute tune being played. Various sounds can be sampled from this recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/w9EGDo9Yybc.wav"} +{"id": "wBe5tW8iJew", "caption": "The song is an instrumental. The song is slow tempo with a violin and cello playing a duet with no other instrumentation. The song is emotional and extremely heartfelt. The song is a western classical music hit.", "audio": "/zhanghaomin/datas/musiccap/music_data/wBe5tW8iJew.wav"} +{"id": "wBozBh7BR6k", "caption": "This is the theme of a cartoon. There is a female vocalist singing merrily at a medium-to-high pitch in the Japanese language. The melody is being played on the strings and the piano while a simple on-beat bass line can be heard being played in the background. There is a simple 4/4 acoustic drum beat for the rhythm. The piece has an uplifting atmosphere. This piece could be used in the soundtrack of a children's movie. It could also be used in anime soundtracks.", "audio": "/zhanghaomin/datas/musiccap/music_data/wBozBh7BR6k.wav"} +{"id": "wC0mY7NzihY", "caption": "The low quality recording features a digital piano, funky chords played over punchy kick, fat snare and shimmering hi hats. The digital piano uses a wah pedal effect, which makes it sound funky and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/wC0mY7NzihY.wav"} +{"id": "wDpz90boBzU", "caption": "This audio contains drums playing a loud groove with cymbals and an e-guitar playing a melody in the lower key. Male voices are singing loud while sounding happy. Another male voice that appears to come from the crowd is singing along. This is an amateur recording. This song may be playing loud while celebrating with friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/wDpz90boBzU.wav"} +{"id": "wEHRmd84Dwc", "caption": "This is a latin music piece in the style of tango. It is an instrumental piece. The only instrument being played is an accordion. The accordion is playing a joyful tune. This piece could be playing in the background at an Iberian coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/wEHRmd84Dwc.wav"} +{"id": "wFTlySgdWX4", "caption": "The low quality recording features a live performance of a traditional song that consists of wooden percussive instruments, steel guitar melody and shimmering bells melody. The recording is in mono and it sounds really noisy, messy and muddy, since the frequencies of the instruments are clashing with each other.", "audio": "/zhanghaomin/datas/musiccap/music_data/wFTlySgdWX4.wav"} +{"id": "wGievbsKUnk", "caption": "This song features a female voice singing the main melody. This is accompanied by a harp on which chords are being played. There are no other instruments in this song. This song can be played in a romantic movie. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/wGievbsKUnk.wav"} +{"id": "wIP7AqIOU1s", "caption": "A male vocalist sings this song. The tempo is medium with loud boomy singing.the audio quality is bad so the music and vocals are muffled. There are traces of tambourine beat, trumpet or some brass instrument,keyboard accompaniment, people talking, chanting and clapping. It is chaotic, confusing and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/wIP7AqIOU1s.wav"} +{"id": "wKE9STHwX-Q", "caption": "This is a rock music piece. There is a male vocalist singing melodically in the lead. A clean sounding electric is playing the main tune while a piano later joins in for texture. There is a mild sounding bass guitar. A basic rock acoustic drum beat provides the rhythmic structure. There is a gloomy aura to this song. It could be used in the soundtracks of drama movies and TV shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/wKE9STHwX-Q.wav"} +{"id": "wKoFJHb2BoI", "caption": "Someone is playing a solo on a clean e-guitar along with a backing track that sounds like a slow soulful, sad ballad with strings,bass, acoustic drums and an e-guitar strumming single chords as a rhythmic instrument. This song may be played outside by a busker.", "audio": "/zhanghaomin/datas/musiccap/music_data/wKoFJHb2BoI.wav"} +{"id": "wL4HaT8rEVU", "caption": "This slow rock song features a guitar playing arpeggiated chords. The guitar has added effects of chorus and reverb. The bass plays a descending run in the scale of the chords. The percussion plays the different cymbals one after the other. The recording quality is low. There are no voices in this song. This song can be played in a dreamy sequence of a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/wL4HaT8rEVU.wav"} +{"id": "wLITXWAuZy0", "caption": "The low quality recording features a shimmering chime bell, breathy flute melody, mellow piano chords and sustained strings melody. It sounds easygoing, calming and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/wLITXWAuZy0.wav"} +{"id": "wLQiZ-0VW4c", "caption": "This music is an electric guitar instrumental. The tempo is slow with an electric guitar harmony and a subdued, incoherent background score. This music is classic Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/wLQiZ-0VW4c.wav"} +{"id": "wMHBhCVv--g", "caption": "This techno song features a male voice singing the main melody. A female voice is heard singing vocables in the background. In the beginning of this clip, the voice is accompanied by a programmed percussion playing the kick at every count and the snare at alternate counts. A synth is playing the same melody as the main voice. A siren is playing in the background. After two bars of eight counts, the percussion plays a roll and the bass plays a groovy bassline. The synth plays a ring modulated sound. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/wMHBhCVv--g.wav"} +{"id": "wMN-Xp9IMUw", "caption": "This is an Afro-cuban music piece in the style of rumba. It is a live performance. There is a male vocal and a choir singing in a joyful manner. The rhythmic background is composed of Afro-Cuban percussive elements such as the shekere and the conga. The atmosphere is lively and vibrant. This piece could be used as an accompaniment piece for a rumba dance course.", "audio": "/zhanghaomin/datas/musiccap/music_data/wMN-Xp9IMUw.wav"} +{"id": "wMelBK3yArA", "caption": "A sample of an alto saxophone playing a repeating melody is being played. At the end some percussive hit comes in with a riser. The whole song sounds upbeat and invites the body to pulse. This song may be playing at a festival with a DJ on stage.", "audio": "/zhanghaomin/datas/musiccap/music_data/wMelBK3yArA.wav"} +{"id": "wMi_0eEIpcM", "caption": "This is a live recording from a rock music concert. There is an electric guitar playing the rhythm section upfront with a loud drum background. A harmonica solo is being played over the guitar and the drums. The song carries a playful and energetic atmosphere. This music could be played at a bar, especially a rock bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/wMi_0eEIpcM.wav"} +{"id": "wPmTJWybq_E", "caption": "A male singer leads backup singers into a gospel song in vocal harmony. The tempo is medium with a groovy bass line , organ accompaniment, tambourine percussion, guitar strumming and keyboard accompaniment. The song is prayerful and spirited. The song has bad audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/wPmTJWybq_E.wav"} +{"id": "wQN7fRaPl2A", "caption": "A female vocalist sings this classic Spanish song. The tempo is medium with a lively accordion harmony, guiro , congas and bongos rhythm, steady bass line, and acoustic guitar accompaniment. The music is simple, light, happy, joyful, cheerful, celebratory and spirited with vocal backup.There are sounds of people cheering in the background. This is a Classic Latin Folk Song.", "audio": "/zhanghaomin/datas/musiccap/music_data/wQN7fRaPl2A.wav"} +{"id": "wQhycJsKSPE", "caption": "A man narrates a repair technique for a French horn. The song plays at medium tempo, with a brass section playing in an orchestra. The song is medium tempo and plays a soundtrack for the repair video.", "audio": "/zhanghaomin/datas/musiccap/music_data/wQhycJsKSPE.wav"} +{"id": "wR7n4Gg-_ac", "caption": "This is a movie music piece. Initially, sound effects related to the movie such as explosions and sirens can be heard. A male voice can be heard gasping. There is an orchestra made up of a brass section, a string section and a choir singing at a high pitch. The atmosphere is ominous. This piece could be used in the soundtrack of a horror movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/wR7n4Gg-_ac.wav"} +{"id": "wRWxsKN394Q", "caption": "This audio contains a musical composition played by a big horn section and a lot of flutes. Someone is playing a simple and loud groove on the drums. In the background you can hear someone playing a marimba. This song may be playing live at a big sports event.", "audio": "/zhanghaomin/datas/musiccap/music_data/wRWxsKN394Q.wav"} +{"id": "wS4d-q9H4NE", "caption": "This song is a drum solo. The hi-hat is played in eighths on the one, two and four counts of the bar. This drum is playing a syncopated rhythm. On the third count, the snare is played. The cowbell is played five times in 2 bars of eight counts. There are no other instruments in this song. There are no voices in this song. This song can be played as an instruction for syncopated drumming patterns.", "audio": "/zhanghaomin/datas/musiccap/music_data/wS4d-q9H4NE.wav"} +{"id": "wSeT9dlfDTc", "caption": "The low quality recording features a cover of a classical song that consists of a harpsichord melody. It sounds passionate and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/wSeT9dlfDTc.wav"} +{"id": "wT2Y0DCq5LI", "caption": "This is an American folk music piece. There is a male vocal singing melodically as the lead and there is a male back vocal accompanying the lead in different harmonies. The melody is composed of a rich amalgam of chordophones such as the fiddle, the acoustic guitar, the bass guitar and the banjo. The atmosphere is easygoing but melancholic. This piece could be playing in the background at an American diner or a pub. It could also work well in the soundtrack of a movie taking place in rural USA.", "audio": "/zhanghaomin/datas/musiccap/music_data/wT2Y0DCq5LI.wav"} +{"id": "wTPI3MHqxSQ", "caption": "A synthesized string lead melody is accompanied by digital piano accompaniment and chimes. The tempo is slow and steady and the feeling is light and airy.", "audio": "/zhanghaomin/datas/musiccap/music_data/wTPI3MHqxSQ.wav"} +{"id": "wXWpkfGfZD8", "caption": "This is an electronic DJ set in the style of Jamaican reggae music. There is a DJ performing over a track that has a groovy beat being played by the electric guitar and the electronic drums. There is a tropical atmosphere. Samples could be lifted from this recording to be used in the beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/wXWpkfGfZD8.wav"} +{"id": "wXmIm6Bq3Tc", "caption": "The music features a mix between jazz and soul music. The instrumental is easygoing and fun. A male singer with a seductive and appealing voice sings a fun melody. A saxophone plays a melody in the background that adds texture to the instrumental. The music is a live recording of a performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/wXmIm6Bq3Tc.wav"} +{"id": "wYtd_Sq2-Tw", "caption": "This song features an electric guitar playing arpeggiated chords. The guitar is playing with a flanger effect added to change the tone. There are no other instruments in this song. There are no voices in this song. This is an instrumental song. This song can be used in an instructional video on an effects processor.", "audio": "/zhanghaomin/datas/musiccap/music_data/wYtd_Sq2-Tw.wav"} +{"id": "wZopmfXTtxw", "caption": "The Disco song features a widely spread electric guitar chord progression, acoustic rhythm guitar, shimmering shakers, tinny percussive elements, followed by simple kick pattern, punchy snare and groovy bass guitar, over which sings the flat male vocal. It sounds energetic, fun and exciting, as it is something you would definitely hear in clubs during 70s and 80s.", "audio": "/zhanghaomin/datas/musiccap/music_data/wZopmfXTtxw.wav"} +{"id": "w_XFNKSRgKI", "caption": "Hand percussion accompanies a male singer and violin doubling a melody with a constant regular rhythm. Mood is hypnotic and trance inducing. Features additive rhythms and odd meters.", "audio": "/zhanghaomin/datas/musiccap/music_data/w_XFNKSRgKI.wav"} +{"id": "w_z9oSn-eIM", "caption": "This is a classical music performance. The piece is played by a classical piano which is complex with rising and falling sequences. The atmosphere is filled with emotion and passion. This heart-touching piece could certainly be used in the soundtrack of a drama movie or a TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/w_z9oSn-eIM.wav"} +{"id": "wc4UEh8wvCA", "caption": "This slow rock song starts with an acoustic guitar playing chords in fingerstyle. For each chord, a pedal bass note is played while the higher pitch notes are played in a repeated sequence of three notes being played one after the other. A male voice sings the main melody. There are no other instruments in this song. This song can be played in a movie scene where a car is driving across a deserted highway.", "audio": "/zhanghaomin/datas/musiccap/music_data/wc4UEh8wvCA.wav"} +{"id": "wcLPCMoy5hk", "caption": "The low quality recording features a tutorial where a flat male vocal is talking in-between notes of alto saxophone. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/wcLPCMoy5hk.wav"} +{"id": "weJKl-6TiDQ", "caption": "The low quality recording features a pop song that consists of groovy synth keys, punchy snare and kick hits, simple hi hats, shimmering open hats, smooth sub bass, arpeggiated echoing synth lead and wide synth pad chords. It sounds energetic and a bit repetitive - like something you would hear in a TV commercial, as background music.", "audio": "/zhanghaomin/datas/musiccap/music_data/weJKl-6TiDQ.wav"} +{"id": "wgIf0FX6WzI", "caption": "This song contains a soft synth pad playing long notes. With every drum kick hit a bell sounding instrument is playing a repeating melody. A male voice is singing a melody or mantra. The whole recording is full of reverb and not of the best sound-quality. This song may be playing while slowly moving/dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/wgIf0FX6WzI.wav"} +{"id": "wg_kYW4xvz4", "caption": "The low quality recording features a hip hop song played on a speaker that features groovy piano melody, synth lead melody, strings power chords, punchy snare, shimmering shakers, claps and punchy kick hits. It sounds noisy and thin as it lacks bass frequencies.", "audio": "/zhanghaomin/datas/musiccap/music_data/wg_kYW4xvz4.wav"} +{"id": "whIj6mrUGzQ", "caption": "Someone is playing an acoustic guitar while a female voice is singing/yodeling in a higher pitch. in the background voices can be heard. This is an amateur recording. This song may be playing at a local folk-event.", "audio": "/zhanghaomin/datas/musiccap/music_data/whIj6mrUGzQ.wav"} +{"id": "whZygh228yw", "caption": "The song is an instrumental piece. The song is medium tempo with a furiously playing timpani percussion, string section playing, horns playing and low pitched harmony that evokes danger and suspense. The song is a modern western classical instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/whZygh228yw.wav"} +{"id": "wj4ukZFNEgs", "caption": "A male vocalist sings this upbeat Latin pop song. The tempo is fast with infectious drumming, groovy bass line,electric guitar, keyboard harmony, acoustic guitar, shakers,synthesiser arrangement and digital drumming. The song is youthful , energetic,enthusiastic, animated,fervent, pulsating, electrifying ,exciting,and buoyant. This song is a Latin Urbano.", "audio": "/zhanghaomin/datas/musiccap/music_data/wj4ukZFNEgs.wav"} +{"id": "woVby8SBWDI", "caption": "This low quality audio features a female voice singing the main melody. Other voices sing backing vocals in this song. Other instruments cannot be heard due to the low quality of audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/woVby8SBWDI.wav"} +{"id": "woyCm7d2UIM", "caption": "This is the recording of a latin dance music piece. It has a male vocalist singing the same word repeatedly at a medium-to-high pitch. There is an accordion playing the melody and a bass guitar in the background. The electronic drums play a latin beat for the rhythm. There is a constant rising and accelerating pattern in the piece. The sound of people shouting can be heard in the recording. The atmosphere is very loud and vibrant.", "audio": "/zhanghaomin/datas/musiccap/music_data/woyCm7d2UIM.wav"} +{"id": "wraN7rWUsfI", "caption": "This audio includes a woman making unintelligible animal sounds with her voice. The audio is recorded live in low quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/wraN7rWUsfI.wav"} +{"id": "wsJ5ZLKiPzs", "caption": "Someone is playing a cowbell along with other percussion such as congas along to a pumping bassline. A piano and a brass section are playing a countermelody to the female and male voices singing. In the background you can hear people cheering and whistling. This is an amateur recording and of poor audio-quality. This song may be playing on a dancefloor.", "audio": "/zhanghaomin/datas/musiccap/music_data/wsJ5ZLKiPzs.wav"} +{"id": "wsdH6cv4YkA", "caption": "The Dance/Electronic song features a repetitive synth keys melody, synth guitar lick, distorted synth bass that perfectly complements the \"4 on the floor\" kick pattern, punchy snare hits layered with claps, simple \"2 step\" hi hat pattern, shimmering shakers, repetitive, pulsating synth pad chord progression and groovy synth keys chord progression. At the end of the first part of the loop, there is a short, reversed crash riser, where the drums subtly fade out, followed by energetic crash at the beginning of the second part of the loop, where the drums are brought back again. It sounds energetic and like something you would hear in clubs during the 00s.", "audio": "/zhanghaomin/datas/musiccap/music_data/wsdH6cv4YkA.wav"} +{"id": "wt-f7K_suBc", "caption": "The Regional Mexican song features a passionate male vocal singing over repetitive acoustic guitar chord and groovy bass, after which there are shimmering shakers and accordion melody playing. It sounds passionate, emotional and soulful.", "audio": "/zhanghaomin/datas/musiccap/music_data/wt-f7K_suBc.wav"} +{"id": "wv6YaiCGPi0", "caption": "A male vocalist sings this devotional song. The tempo is medium with acoustic guitar rhythm, steady keyboard harmony, synthesised violin harmony and xylophone like sound and soft tambourine beats. The song is a soothing, calm, peaceful, meditative, Indian classical devotional chant.", "audio": "/zhanghaomin/datas/musiccap/music_data/wv6YaiCGPi0.wav"} +{"id": "wwHi10qX8u8", "caption": "This funk song features trumpets playing the main melody. The bass plays the same melody on the lower octave. This is accompanied by percussion playing a simple beat. The beat is groovy. Guitars play a funky rhythm using muting technique and playing funk style chords. The trumpet starts off playing a descending sequence of four notes followed by an ascending sequence of three notes. In between lines, the trumpet plays on note in a staccato style. This song has a happy mood. This song can be played in a casino scene in a movie. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/wwHi10qX8u8.wav"} +{"id": "wwbATvWFaLY", "caption": "This is a French opera music piece. It is an instrumental piece. There are two harpsichords performing the piece. There is a medieval sound to the piece. It has a dramatic and grandiose feel. This piece could be used in the soundtrack of a movie or a TV series that takes place in the medieval era, especially during scenes of intrigue.", "audio": "/zhanghaomin/datas/musiccap/music_data/wwbATvWFaLY.wav"} +{"id": "wxKtBDKasgM", "caption": "The song is a black metal band which features a heavily distorted, sustained guitar chord. The male voice is croaky, raspy, deep and fuzzy. There is a soft choral vocal in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/wxKtBDKasgM.wav"} +{"id": "wz-7sy_Rin4", "caption": "The low quality recording features a muffled trumpet melody playing. There is a random male laughing sound. The recording is very noisy and in mono. It sounds like an intro of a video.", "audio": "/zhanghaomin/datas/musiccap/music_data/wz-7sy_Rin4.wav"} +{"id": "x-ob6_6f4jQ", "caption": "This is an instrumental heavy metal piece. The distorted electric guitar is playing an aggressive riff while accompanied by a bass guitar. In the rhythmic background, there is a slow but hard-hitting heavy metal beat played on the acoustic drums. The atmosphere is loud and violent. This piece can be used in the soundtrack of a movie/TV show involving crime. It could also be played at a rock bar or a sports venue.", "audio": "/zhanghaomin/datas/musiccap/music_data/x-ob6_6f4jQ.wav"} +{"id": "x14jW4c8YnQ", "caption": "The low quality recording features an orchestral live performance of a classical song and it contains a wide french horn melody playing over a wide string melody. It sounds easygoing, passionate, dynamic and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/x14jW4c8YnQ.wav"} +{"id": "x1KyLxsnJY0", "caption": "This dance song features a female voice singing the main melody. This is accompanied by programmed percussion playing a simple beat which starts off with a drum roll. The bass plays the root notes of the chords. A synth plays chords in the background. This song has an upbeat mood. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/x1KyLxsnJY0.wav"} +{"id": "x1S2oreZBWU", "caption": "This is an R&B/disco funk music piece. There are multiple layers of a female vocalist singing melodically. The melody is being played by the electric guitar while the bass guitar is playing a groovy bass line. There is a funky acoustic drum beat in the background. The atmosphere is hip and the piece is very danceable. The piece could be playing for a 70s night at a dance club.", "audio": "/zhanghaomin/datas/musiccap/music_data/x1S2oreZBWU.wav"} +{"id": "x1x54MgStxQ", "caption": "A male singer sings this delightful melody. The song is medium tempo with a ukulele accompaniment, steady drumming rhythm with various percussions like clapping and tambourine along with a keyboard accompaniment. The song is emotional and groovy. The song is a local Indian language pop song, most probably a Bengali pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/x1x54MgStxQ.wav"} +{"id": "x22NHqwKSNE", "caption": "The low quality recording features a live performance of steel drums, followed by energetic drums in the background. It sounds exotic, passionate, energetic and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/x22NHqwKSNE.wav"} +{"id": "x6FbyqrK0g0", "caption": "Techno or house music with a four on the floor kick pattern, off beat hi-hat pattern, synth chords with delay and a chopped vocal sample. It is mid-tempo and minimal for dancing.", "audio": "/zhanghaomin/datas/musiccap/music_data/x6FbyqrK0g0.wav"} +{"id": "x6U1gX5a_4M", "caption": "The low quality recording features a hip hop song that consists of a flat male vocal, alongside some background male vocals, rapping over punchy kick and snare hits, shimmering hi hats, funky electric guitar, brass melody, groovy synth keys melody and groovy bass. It sounds energetic, groovy and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/x6U1gX5a_4M.wav"} +{"id": "x7tOPTm31tQ", "caption": "This song contains a male voice repeating the same melody in a loop while another male voice is singing on top in a higher register. An acoustic drum is holding a four on the floor groove with a kick on every beat. The e-bass and e-guitar are playing along to the loop, repeating themselves. This song may be playing at a live concert downtown.", "audio": "/zhanghaomin/datas/musiccap/music_data/x7tOPTm31tQ.wav"} +{"id": "x85BtdoxRek", "caption": "This is a hip-hop music piece. There is a male vocal rapping in the lead. The beat has a brass sample and a female voice sample. There is a strong bass sound. The rhythmic background is composed of a hip-hop electronic drum beat. There is an urban atmosphere. This piece could be playing in the soundtrack of a car street-racing video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/x85BtdoxRek.wav"} +{"id": "x9bcsYF_by8", "caption": "This symphonic song features a melody played on a cello. This is accompanied by violins playing in the background. It starts off as a slow tempo song. After a brief pause, the instruments play staccato notes at a faster tempo. There is no percussion in this song. There are no voices in this song. This is a classical instrumental piece. This song can be played in a luxury watch advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/x9bcsYF_by8.wav"} +{"id": "x9xXU30ktcY", "caption": "The low quality recording features a DJ scratching the vinyl of a hip hop song. There is a crowd talking in the background. The recording sounds muffled, noisy and it is in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/x9xXU30ktcY.wav"} +{"id": "xBDcJKb-9vk", "caption": "This is a new age piece. There is a flute playing the main melody with a lot of staccato notes. The rhythmic background consists of a medium tempo electronic drum beat with percussive elements all over the spectrum. There is a playful atmosphere to the piece. This piece can be used in the soundtrack of a children's TV show or an advertisement jingle.", "audio": "/zhanghaomin/datas/musiccap/music_data/xBDcJKb-9vk.wav"} +{"id": "xCLzxuZE3yg", "caption": "This music is instrumental. The tempo is fast with a groovy didgeridoo harmony with percussion accompaniment. The music is upbeat, catchy, funky, unconventional, engaging, punchy and fun. This music is a Didgeridoo instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/xCLzxuZE3yg.wav"} +{"id": "xGHN0kphhWM", "caption": "This is a sextet of french horn players. The piece sounds inspiring and uplifting and would be fitting for a movie soundtrack in a moment where the lead character has just accomplished something great or saved the day. It's an emotive and cinematic piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/xGHN0kphhWM.wav"} +{"id": "xIbSUwO43Ig", "caption": "This is a percussion piece playing in the background of an advertorial video. It is an instrumental piece. There is a very simple conga beat playing and then a cymbal hit can be heard, only for the conga beat to keep on playing afterwards. There is a basic feel to it. It can be playing in the background of a tutorial or a review video. It could also be sampled for use in beat-making.", "audio": "/zhanghaomin/datas/musiccap/music_data/xIbSUwO43Ig.wav"} +{"id": "xIdWJyhWueE", "caption": "A piano is playing chords in the left hand in the midrange while repeating the same two notes in the higher register. A female voice is singing a melody over the chords. This song is an amateur recording. This song may be playing in a musical.", "audio": "/zhanghaomin/datas/musiccap/music_data/xIdWJyhWueE.wav"} +{"id": "xJ63DJzzvnA", "caption": "The low quality recording features a live performance of a gospel song that consists of harmonizing vocals singing over acoustic rhythm guitar, groovy bass guitar, shimmering hi hats and punchy toms. It gives off happy and fun vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/xJ63DJzzvnA.wav"} +{"id": "xJMTA3Ay5FI", "caption": "This is a contemporary classical music performance. The piece is being played on the grand piano with an accentuated playing style. There is a lot of emphasis on the notes. The atmosphere is dramatic. Parts of this piece could be included in the soundtrack of a documentary. It could also be used in the soundtrack of a mystery/horror video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/xJMTA3Ay5FI.wav"} +{"id": "xJYBA7VTkHA", "caption": "Someone is playing a loud melody on a steeldrum along to a backing track with a lot of percussion and an upright bass. This song may be playing at a beach concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/xJYBA7VTkHA.wav"} +{"id": "xKEJ6fVhb8w", "caption": "This song contains someone playing a bass drum instrument along with someone playing a triangle. A female voice is shouting while a flute is playing the main melody in a very high key. This song may be playing at a theater performance in an Asian country.", "audio": "/zhanghaomin/datas/musiccap/music_data/xKEJ6fVhb8w.wav"} +{"id": "xKc_9B3RiOc", "caption": "This song is an instrumental. The tempo is medium with a melodious lead on the electric guitar, steady drumming, groovy bass lines and acoustic guitar accompaniment. The melody is simple, mellow, pleasant, melancholic, nostalgic and ambient. This instrumental song is a Classic Rock and Roll.", "audio": "/zhanghaomin/datas/musiccap/music_data/xKc_9B3RiOc.wav"} +{"id": "xKrdOZAp2w0", "caption": "Calming ambient synth pads and synthesized bell sounds combined with ocean sounds and bird sounds. Meant to inspire tranquility. No drums.", "audio": "/zhanghaomin/datas/musiccap/music_data/xKrdOZAp2w0.wav"} +{"id": "xL7Krm6FSWE", "caption": "A male singer sings this vocals with a vocoder. The song is medium tempo with a groovy techno drumming rhythm and keyboard accompaniment. The song is passionate but an amateurish production. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/xL7Krm6FSWE.wav"} +{"id": "xLQF7S41XLE", "caption": "These are sounds from a movie. There is a metal object falling to pieces on the ground. There is a cinematic string sequence that gives a dramatic atmosphere to the track. There is also a feeling of suspense. This could be playing in the soundtrack of an action-filled movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/xLQF7S41XLE.wav"} +{"id": "xLZp-3_71Vs", "caption": "The low quality recording features a passionately arpeggiated electric guitar melody. The recording is noisy and at the end, there is a subtle inhale through the nose. The audio suddenly distorts in the middle of the loop.", "audio": "/zhanghaomin/datas/musiccap/music_data/xLZp-3_71Vs.wav"} +{"id": "xM4p5pmRAxM", "caption": "This is a live performance of a classical music piece. There is a grand piano playing dramatically in minor keys. The piece has a grandiose and mysterious aura to it. This piece could be used in the soundtrack of a horror movie. It could also be used in a horror video game theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/xM4p5pmRAxM.wav"} +{"id": "xMCLKME4hAY", "caption": "This audio contains someone playing a clean e-guitar melody that sounds soothing. This song may be playing at a little living room concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/xMCLKME4hAY.wav"} +{"id": "xMsgBL9Sunw", "caption": "This is an east asian type of romantic ballad. The song has a relaxing, calm feeling to it and is aided by the ethereal sounds of the chinese flute. We hear ethnic drums like bongos, and constant hi-hat playing.", "audio": "/zhanghaomin/datas/musiccap/music_data/xMsgBL9Sunw.wav"} +{"id": "xN9tKWgXLI4", "caption": "The song is instrumental. The tempo is medium with keyboard accompaniment, string pad harmony, steady drumming and a strong bass line. The song is spirited and easy listening and serves as a background to a glass sculpture making video. There is hammering and glass cracking noises with ambient room sounds. The overall sound quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/xN9tKWgXLI4.wav"} +{"id": "xNn2UdI-kvA", "caption": "A male singer sings this beautiful melody. The tempo is fast with a guitar strumming rhythm, strong bass line, violin playing countermelody, steady drumming rhythm and a guitar playing accompaniment. The song is fresh, innocent and romantic with a lot of heart. The song is a modern love song.", "audio": "/zhanghaomin/datas/musiccap/music_data/xNn2UdI-kvA.wav"} +{"id": "xR2p3UED4VU", "caption": "This is the live performance of a Romanian folk music piece. It is instrumental. There is an accordion playing the leading melody while the fiddle, acoustic guitar and the upright bass play in the background. There is a percussive element in the rhythmic background. The atmosphere is lively and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/xR2p3UED4VU.wav"} +{"id": "xRfbWrI03gc", "caption": "Someone is playing a Theremin on a very high pitch going up in pitch and with a lot of vibrato. This song may be playing at home while enjoying your instrument.", "audio": "/zhanghaomin/datas/musiccap/music_data/xRfbWrI03gc.wav"} +{"id": "xSDkn9PtQm0", "caption": "Someone is playing a composition using a minor chord with a lot of reverb. In the background you can hear soft strings underlining the song then a high violin comes in. A female voice is singing softly and sensitively. You can hear her breathing and mouth noises in the recording. Her voice is also full of reverb. This song may be playing in an emotional and sensitive/sad movie-scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/xSDkn9PtQm0.wav"} +{"id": "xSmmTveNPSM", "caption": "This audio contains someone playing a didgeridoo and a rattle sound. In the background you can hear birds chirping. This song may be played live by a busker.", "audio": "/zhanghaomin/datas/musiccap/music_data/xSmmTveNPSM.wav"} +{"id": "xUMzNtC2ITA", "caption": "This is the live performance of an indie rock/post-punk piece. There is a male vocalist in the lead. The tune is being played by the electric guitar and the bass guitar while an electronic sound effect that resembles a laser is adding texture. There is a fast and slightly off-tempo acoustic drum beat playing in the rhythmic background. The atmosphere is energetic. The piece could be playing in the soundtrack of a teenage drama TV series.", "audio": "/zhanghaomin/datas/musiccap/music_data/xUMzNtC2ITA.wav"} +{"id": "xUVvBF9BWdg", "caption": "A male singer sings this jazz melody with the backup singer in vocal harmony. The song is medium tempo, with saxophone harmony, ska drumming rhythm and a good bass line. The song is entertaining and groovy. The song is a classic jazz tune played in ska style.", "audio": "/zhanghaomin/datas/musiccap/music_data/xUVvBF9BWdg.wav"} +{"id": "xUmMfewERLg", "caption": "The low quality recording features a flat male vocal talking, after which there is an explosion sound effect, followed by resonating bells and loud percussive impact. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/xUmMfewERLg.wav"} +{"id": "xVab_CbwecE", "caption": "This song features a bass guitar playing a groovy lick at a high pitch. This is followed by a rock and roll pattern. This starts off on a high sequence. This is played for two bars followed by a sequence on a lower part of the bass. This song can be played in an instructional video for bass. There are no voices in this song. There are no other instruments in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/xVab_CbwecE.wav"} +{"id": "xVi1wNljxjk", "caption": "The low quality recording features synth strings in the left channel, synth keys melody, synth bells melody in the right channel of the stereo image, groovy bass, shimmering hi hats and mellow snare. It sounds digital, but it gives off happy and fun vibes.", "audio": "/zhanghaomin/datas/musiccap/music_data/xVi1wNljxjk.wav"} +{"id": "xWmcax3aX5U", "caption": "The low quality recording features a boomy wooden percussion one shot, after which a flat female vocal is talking. It sounds like some sort of tutorial and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/xWmcax3aX5U.wav"} +{"id": "xXRGgPVnkqk", "caption": "This is a tutorial on how to use the conga percussion instrument. The American tutor narrates his actions as he plays. There are two tones - the open tone is lower and the closed tone is higher pitched.", "audio": "/zhanghaomin/datas/musiccap/music_data/xXRGgPVnkqk.wav"} +{"id": "xZSioXdxo4Y", "caption": "The song is an instrumental. The tempo is medium with an electric guitar playing a blues solo with an effects pedal and amplifier. The solo is heartfelt and has a lot of soul and spirit to it. The audio quality is bad.", "audio": "/zhanghaomin/datas/musiccap/music_data/xZSioXdxo4Y.wav"} +{"id": "xZTlnE6IcYQ", "caption": "This is a harmonica cover of a soul music piece. The harmonica plays a groovy solo. In the melodic background, there is a keyboard and a bass guitar. The rhythm is provided by the acoustic drums. The atmosphere is uplifting. The song is in major key.", "audio": "/zhanghaomin/datas/musiccap/music_data/xZTlnE6IcYQ.wav"} +{"id": "xZukWGb52BI", "caption": "This amateur recording features a trumpet playing the main melody. The song starts with a string section playing a chord and fading away. The trumpet starts to play the melody. This is backed by a stringed instrument plucking chords. This sounds like a harp or an acoustic guitar. The mood of this song is romantic. This song can be played in a romantic movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/xZukWGb52BI.wav"} +{"id": "xb07gLlmkL8", "caption": "This music is instrumental. The tempo is medium with atmospheric synthesiser, soft keyboard harmony and subtle bass lines in the background. The music is progressive with a lot of digital sounds giving it a psychedelic,meditative, trippy, trance like vibe. This instrumental is Synth Rock/Progressive Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/xb07gLlmkL8.wav"} +{"id": "xe9vDoF8TQM", "caption": "The low quality recording features a folk song that consists of flat male vocals, alongside harmonizing female vocals, singing over groovy bass, strings melody, shimmering hi hats, and \"4 on the floor\" kick pattern. It sounds energetic, happy and fun.", "audio": "/zhanghaomin/datas/musiccap/music_data/xe9vDoF8TQM.wav"} +{"id": "xeHt-R5ScmI", "caption": "This sounds like an instrumental intro. It starts with a bowling sound effect as well as the sound of a tape player speeding up, producing both a high-pitched whine and a low-pitched vocal sounding effect. This leads into a slightly swung, overdriven electric guitar riff.", "audio": "/zhanghaomin/datas/musiccap/music_data/xeHt-R5ScmI.wav"} +{"id": "xgXd06kKFIQ", "caption": "This excerpt can barely be called musical. It starts off with 6 seconds of silence, after which a white noise can be heard, followed by three notes played in the lower register of a marimba. All this leads me to believe that the three notes we heard have a jingle-like purpose before a TV show starts. You would also hear something similar when an elevator reaches a particular floor.", "audio": "/zhanghaomin/datas/musiccap/music_data/xgXd06kKFIQ.wav"} +{"id": "xgwzTQ8vnso", "caption": "A synthesizer is playing a loud and wide pad sound that gets modulated while a soft and deep kick is playing every beat. This is an amateur recording. This song may be playing giving someone a tutorial on a synthesizer.", "audio": "/zhanghaomin/datas/musiccap/music_data/xgwzTQ8vnso.wav"} +{"id": "xhOsZuB_Zqc", "caption": "Groovy, funky world music with a male vocalist, deep bass, syncopated percussion and synthesizer chords and a clean electric guitar with a chorus effect.", "audio": "/zhanghaomin/datas/musiccap/music_data/xhOsZuB_Zqc.wav"} +{"id": "xiN6XwZNEJo", "caption": "The low quality recording features an energetic drums solo that consists of punchy snare, tom and kick hits, alongside repetitive cowbell. There is a flat male vocal talking right before the solo. It sounds like a tutorial. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/xiN6XwZNEJo.wav"} +{"id": "xk4U8BembHM", "caption": "The Rock song features a shimmering hi hats, energetic crash cymbal, punchy kick and snare hits, groovy bass guitar and wide electric guitars melodies playing on top of them. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/xk4U8BembHM.wav"} +{"id": "xl4FJzeU0YA", "caption": "This is a sped-up trap remix of an R&B music piece. There is a female vocalist singing melodically with her vocal sample used in beat repeats. There is a hollering sample added alongside it. The beat has a strong synth bass with a repeating acoustic guitar sample playing every now and then. The electronic drum beat is slightly fast-paced and filled with cicada hi-hats. The atmosphere is loud and upbeat. This piece could be used as an accompaniment piece at a modern break dance course. It could also be played at nightclubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/xl4FJzeU0YA.wav"} +{"id": "xlxxWFENWr8", "caption": "The song is an instrumental. The tempo is slow with a choir harmonising and creating ethereal chants, string section and a philharmonic orchestra harmony backing. The song is ethereal and magical. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/xlxxWFENWr8.wav"} +{"id": "xmSMAmnoRug", "caption": "This is a Christian gospel music piece. There is a male vocalist singing passionately in the lead with a male choir that is at a relatively higher pitch than him singing in the back. The main melody is played by the keyboard and the electric guitar. There is a bass guitar that can be heard. The acoustic drums are playing an upbeat rhythm. The atmosphere is religious. This piece could be played at Christian religious events.", "audio": "/zhanghaomin/datas/musiccap/music_data/xmSMAmnoRug.wav"} +{"id": "xmaVWayBvaY", "caption": "This music is a lively drum instrumental. The tempo is fast with an enthusiastic drum routine. It is loud, rhythmic, catchy and intense.", "audio": "/zhanghaomin/datas/musiccap/music_data/xmaVWayBvaY.wav"} +{"id": "xqjpWi83CWM", "caption": "This song comes with a male voice singing in a higher key and strings playing the same melody in the background in the midrange. A timpani hit is playing along with the drums. This song may be playing in a latin country where someone is cleaning the house with open doors and windows listening to this song in a very loud volume.", "audio": "/zhanghaomin/datas/musiccap/music_data/xqjpWi83CWM.wav"} +{"id": "xrbIZTswt3c", "caption": "The low quality recording features a live performance of a traditional song that consists of leg tapping sounds, giving a rhythm to a bagpipe melody. There are some laughing sounds in the background. It sounds passionate and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/xrbIZTswt3c.wav"} +{"id": "xrqDoBor2dk", "caption": "The low quality recording features an alternative/indie song that consists of electric guitar chords, groovy repetitive bass guitar, harsh electric guitar solo, percussive toms and shimmering shakers. It sounds muffled, harsh, groovy and it is uptempo and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/xrqDoBor2dk.wav"} +{"id": "xsLJe043ar4", "caption": "Thissong contains two acoustic guitars panned to both sides of the speakers finger picking a repeating melody. In the background a synth pad/drone is playing a continuous chord in the mid- to high range. A female voice is adding a vocal melody in a higher register along with different flute sounds repeating the same melody. The elements are spread across the sides of the speakers. A shaker is holding the rhythmic part with reverb. This song may be playing for a slow ecstatic dance.", "audio": "/zhanghaomin/datas/musiccap/music_data/xsLJe043ar4.wav"} +{"id": "xseL3oZc7pY", "caption": "This is a comedy music piece. The male vocals are singing in a funny manner in the Hindi language. The rhythm is being played by percussive elements such as the tabla and the kanjira. The atmosphere is amusing. This piece could be used in the background of a comedy skit.", "audio": "/zhanghaomin/datas/musiccap/music_data/xseL3oZc7pY.wav"} +{"id": "xt6V3Ic72nE", "caption": "This is the live performance of a reggae piece. There is a male vocal hollering while a younger sounding male vocal is singing in a Jamaican accent. An electric guitar is strumming chords in staccato while a bass guitar is playing a groovy bass line. In the rhythmic background, there is an acoustic drum playing a reggae beat. The atmosphere is chill. This piece could be played at beach parties and in the soundtracks of summer vacation-themed movies or TV shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/xt6V3Ic72nE.wav"} +{"id": "xtGmrLOsjHk", "caption": "The low quality recording contains a muffled strings section and a muffled passionate female opera singer, singing over it. The recording is noisy and in mono, and judging by the tone of it, old - which makes it vintage. It sounds emotional, warm and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/xtGmrLOsjHk.wav"} +{"id": "xtllXrdFAFQ", "caption": "This music is instrumental. The tempo is fast with a spirited harpsichord, contrasting melancholic violin harmony, flute, cello , viola and piano accompaniment. The music is complex, syncopated , melancholic, wistful, anxious and restless. This music is a Western Classical Piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/xtllXrdFAFQ.wav"} +{"id": "xuepy6SFOf8", "caption": "A synthesizer is playing a rhythmic, simple bassline. A male vocal sample that seems to be processed and pitched down is being played with a delay. Then a riser noise comes in sounding like wind that is getting stronger. This song may be playing while playing at a play-station with your friends.", "audio": "/zhanghaomin/datas/musiccap/music_data/xuepy6SFOf8.wav"} +{"id": "xuxKtxzq2Cs", "caption": "This is a techno remix of a polka music piece. There is a female vocalist singing and yodeling. Once the remix kicks in, the male vocal sample can be heard singing a bass line. There is a loud electronic drum beat for the rhythmic background. The vocals have a slight sidechain effect on kick drum hits. The atmosphere is playful. The piece is in low resolution. This piece can be used in the background of funny social media content.", "audio": "/zhanghaomin/datas/musiccap/music_data/xuxKtxzq2Cs.wav"} +{"id": "xvryKn-V-JM", "caption": "A professionally trained operatic male singer singing a difficult, high melody accompanied by organ and electric piano.", "audio": "/zhanghaomin/datas/musiccap/music_data/xvryKn-V-JM.wav"} +{"id": "xx1RccwlF5g", "caption": "The song is an instrumental. The tempo is slow with an organ playing sustained chords. The audio quality is poor with a lot of hissing and strong gains that are distorted. The song is background music for a home video. The song is emotional and ominous.", "audio": "/zhanghaomin/datas/musiccap/music_data/xx1RccwlF5g.wav"} +{"id": "xx3nnVzGXa0", "caption": "A musician plays this rock instrumental. The tempo is fast with an intense, emphatic electric guitar riff and enthusiastic drumming and cymbal rides in the background and tambourine beats. The music is muffled as the sound quality is inferior. The music is energetic, enthusiastic, and animated . This is a Rock instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/xx3nnVzGXa0.wav"} +{"id": "xxCnmao8FAs", "caption": "The low quality recording features a children's song played on TV that consists of funny male and female vocal singing over mellow piano chord progression and happy sounding bells melody. It is really noisy and in mono, but it sounds happy and fun - like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/xxCnmao8FAs.wav"} +{"id": "xxNroISqkt4", "caption": "The low quality recording features a passionate accordion melody playing over a shimmering tambourine. It sounds joyful, happy and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/xxNroISqkt4.wav"} +{"id": "xxRnOYSjF64", "caption": "The low quality recording features an instrumental of a pop song that consists of an addictive synth lead melody, punchy \"4 on the floor\" kick pattern, shimmering hi hats, riser and groovy bass in the first half of the loop. In the second half of the loop there is a tinny, high pitched snaps and groovy piano melody playing. It sounds energetic, exciting and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/xxRnOYSjF64.wav"} +{"id": "xyAbP5XfGz8", "caption": "The children's music sounds as if it's being played from a child's toy and recorded with a phone. The music starts playing after a rattling noise is being made and stops after a while to be activated again by the rattling sound.", "audio": "/zhanghaomin/datas/musiccap/music_data/xyAbP5XfGz8.wav"} +{"id": "xyXQ7Z1vX7E", "caption": "The low quality recording features a wide dark synth pad, metal guitar strings squeaking sound effects, creepy church bells and synth bass with a phaser effect on. It sounds dark, suspenseful and intense - like something you would hear in horror movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/xyXQ7Z1vX7E.wav"} +{"id": "xyco-5DC_K8", "caption": "This music is an Indian Classical Instrumental. The tempo is medium fast with an ensemble of a lively violin, melodic flute and rhythmic accompaniment of the Indian percussion gadam and mridangam . The music uses ragas, talas and Sruti to form a harmony. It is classic, lively, rhythmic, engaging and enthralling.", "audio": "/zhanghaomin/datas/musiccap/music_data/xyco-5DC_K8.wav"} +{"id": "xydcedfPePM", "caption": "Heavily processed girl band with multiple female singers in a pop or R&B style, using autotune, vocal hocketing, and melisma with multiple synthesizers accompanying.", "audio": "/zhanghaomin/datas/musiccap/music_data/xydcedfPePM.wav"} +{"id": "xzU6sJot-Gk", "caption": "The low quality recording features a funk song that consists of crowd cheering and crowd singing over punchy kick and snare hits, shimmering hi hats, brass melody and groovy bass. There is a shimmering bell glissando that serves as a transition into the next section. Overall it sounds funky and groovy.", "audio": "/zhanghaomin/datas/musiccap/music_data/xzU6sJot-Gk.wav"} +{"id": "xzgnLpKkvdg", "caption": "The song is an instrumental. The song is medium fast tempo with a western classic al piece featuring a string string section plays and a tambourine player practices along with background music. The song is spirited and passionate. The audio quality is very poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/xzgnLpKkvdg.wav"} +{"id": "y0w7FyJcZ8w", "caption": "The music features a melody-less section, just the accompaniment. A piano is playing chords at the beginning of every measure. The kick drum plays on beats one and three and the snare drum, which seems to have some beads on its membrane, on beats two and four. An electronic sound is playing the same harmonies that the piano is playing. Two distorted sounds can be heard in the background, one of them most probably coming from an electric guitar and the other from a synth bass.", "audio": "/zhanghaomin/datas/musiccap/music_data/y0w7FyJcZ8w.wav"} +{"id": "y3Pqe5DLvok", "caption": "The low quality recording features a live performance of groovy hi hats, wide marimba melody, shimmering shakers and a punchy kick pattern. It sounds reverberant, probably because they performed in a medium size space, exotic and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/y3Pqe5DLvok.wav"} +{"id": "y4vtzCAPv84", "caption": "The song is an instrumental. The song is medium with a DJ creating scratchy tones by scratching vinyl on a turntable. The DJ creates an eerie and syncopated rhythm. The audio is bad quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/y4vtzCAPv84.wav"} +{"id": "y516mYOT_9c", "caption": "The low quality recording features a mellow echoing synth pad keys playing. It sounds ambient, reverberant, but also relaxing and calming, like something you would put on while doing yoga or just trying to relax.", "audio": "/zhanghaomin/datas/musiccap/music_data/y516mYOT_9c.wav"} +{"id": "y5HkvusmkqM", "caption": "The low quality recording features a classical song that consists of a mellow french horn melody playing over wide strings. It is a bit noisy and it sounds passionate, easygoing and like something you would hear as a background music for old movies.", "audio": "/zhanghaomin/datas/musiccap/music_data/y5HkvusmkqM.wav"} +{"id": "y5I5pq0bXmg", "caption": "This is a live performance of a classical music piece from the baroque era. The piece is being performed on a harpsichord. There is a medieval sound to the piece. The atmosphere is dramatic. This piece could be used in the soundtrack of a historical drama movie moments before a face-off or a battle.", "audio": "/zhanghaomin/datas/musiccap/music_data/y5I5pq0bXmg.wav"} +{"id": "y6NS77HLjEE", "caption": "The song is an instrumental. The song is medium tempo with a groovy bass line, steady drumming rhythm, guitar accompaniment, saxophone playing melody and bells percussions. The song is cheerful and festive. The song is a Christmas song with a lot of fun and cheer.", "audio": "/zhanghaomin/datas/musiccap/music_data/y6NS77HLjEE.wav"} +{"id": "y6iMm7Pltq0", "caption": "Someone is playing a simple repeating melody on a zitar along with a small harp. A flute is playing the same melody in the higher mid-range. A male voice is singing along. Someone is playing tabla. This song sounds calm and repetitive. This song may be playing live at a local performance place.", "audio": "/zhanghaomin/datas/musiccap/music_data/y6iMm7Pltq0.wav"} +{"id": "y7PtSsbkGdM", "caption": "This slow blues song features a distortion guitar playing a guitar solo and the song is in 6/8 time signature. This is accompanied by a bass guitar playing a descending bassline. The percussion is playing a simple beat over a 6/8 time signature with a roll at the end of the bar. There are no voices in this song. This song can be played in a spy movie in a scene when a plan is being executed.", "audio": "/zhanghaomin/datas/musiccap/music_data/y7PtSsbkGdM.wav"} +{"id": "y8gB3-yw3tE", "caption": "This recording is full of digital scary sounds with a lot of reverb and delay. This may be playing in a scary game.", "audio": "/zhanghaomin/datas/musiccap/music_data/y8gB3-yw3tE.wav"} +{"id": "y8oi64M0IyE", "caption": "The Regional Mexican song features solo flute melody over wooden percussive elements, groovy piano melody and groovy bass. It sounds fun, happy and it is uplifting and energetic - like something you would dance to in some latin bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/y8oi64M0IyE.wav"} +{"id": "y9hdu9iMBG8", "caption": "A male musician vocalises this energetic rhythm. The tempo is fast with rhythmic beats. The music has no instrumentation. It is youthful, energetic, groovy, enthusiastic and upbeat.This music is a Vocal percussion imitation.", "audio": "/zhanghaomin/datas/musiccap/music_data/y9hdu9iMBG8.wav"} +{"id": "yAoMoKe7gj8", "caption": "This instrumental song features a harp being played. This song is in compound time of 6/8. The bass note is played on the first count of the bar. The high part plays four descending notes followed by two ascending notes in each bar. On the fourth bar, the strings are tapped on the second half of the bar to give a percussive effect. Then the melody continues. There are no other instruments in this song. There are no voices in this song. This is an amateur recording. This song can be played in a dreamy sequence in a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/yAoMoKe7gj8.wav"} +{"id": "yAqznhOhoIk", "caption": "Male singers sing this gospel tune in vocal harmony. The song is medium tempo with a guitar accompaniment . The song is devotional amid inspiring. The song is a black gospel acapella recorded live in a church with poor quality audio.", "audio": "/zhanghaomin/datas/musiccap/music_data/yAqznhOhoIk.wav"} +{"id": "yAvqiPL-ssU", "caption": "The low quality recording features a bagpipe melody, layered with an electric guitar lick and followed by punchy kick hits. In the background there are some crowd talking noises and claps. It sounds exciting and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/yAvqiPL-ssU.wav"} +{"id": "yBYd03Hr2kQ", "caption": "The low quality recording features an electric guitar melody played with a distortion pedal effect that changes its preset in the second half of the recording. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/yBYd03Hr2kQ.wav"} +{"id": "yCDloqQe65k", "caption": "The song is an instrumental. The tempo is medium with a horn player playing a traditional animal horn in a single long note which fades out. The song is poignant and emotional. The audio quality is poor.", "audio": "/zhanghaomin/datas/musiccap/music_data/yCDloqQe65k.wav"} +{"id": "yCGM8aJV6fM", "caption": "This is a techno music piece played in the background of a car video. The sounds coming from the car such as the exhaust sound can be heard in the video. The electronic music piece consists of a crisp synth sound playing a repeated theme while there is an electronic drum beat in the rhythmic background. There is an aggressive atmosphere in the piece. Samples lifted from the track could be used in the soundtrack of a car racing video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/yCGM8aJV6fM.wav"} +{"id": "yFh6J72KnCM", "caption": "This file contains a backing track with acoustic drums holding a steady groove without any changes along with a repeating bassline. A padsound is playing in the background along with a high pitched melody entering for a moment. The e-guitar is strumming rhythmically chords along with the bass walking down the fretboard. The male voice singing sounds like not being a part of the track playing. This is an amateur recording. This song may be playing at a karaoke night.", "audio": "/zhanghaomin/datas/musiccap/music_data/yFh6J72KnCM.wav"} +{"id": "yG1bzzXDIak", "caption": "The low quality recording features a wide synth pad chord, followed by quiet buzzy sound. It sounds calming and relaxing - like something you would listen to in a yoga session.", "audio": "/zhanghaomin/datas/musiccap/music_data/yG1bzzXDIak.wav"} +{"id": "yGXohnxCLCA", "caption": "The low quality recording features an ambient song that contains a flat male vocal softly talking over mellow strings and soft sea waves sounds. It sounds relaxing and calming - like something you would hear at a yoga session.", "audio": "/zhanghaomin/datas/musiccap/music_data/yGXohnxCLCA.wav"} +{"id": "yHd5DzIbWL8", "caption": "This audio contains someone playing a high pitch melody on a bagpipe. This song may be playing during a traditional live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/yHd5DzIbWL8.wav"} +{"id": "yIFP8fkq8GU", "caption": "THis song contains a piano playing a major chord progression in the midrange with the left hand playing bass notes creating a simple bassline. An acoustic drum is playing a constant groove without any big changes. A male voice is singing in a higher register getting backing vocals from another male voice. In the background you can hear the crowd cheering. It mostly sounds like female voices. This song may be playing at a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/yIFP8fkq8GU.wav"} +{"id": "yIOUPSGFqoY", "caption": "The music features a stringed instrument playing a melody. I'm not sure what instrument it is, it sounds oriental. I can say for sure it's not an acoustic guitar. This instrument has a synth delay effect on, meaning whenever a note is played, a device plays that same note with the sound of a synth.", "audio": "/zhanghaomin/datas/musiccap/music_data/yIOUPSGFqoY.wav"} +{"id": "yKx_RFUTPfI", "caption": "A digital drum is playing a hardstyle beat with a punching kick with a sub sound. Synthesizers/samples are playing industrial digital sounds as a melody. A female voice sample is singing a soulful sequence for a moment. This song may be playing in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/yKx_RFUTPfI.wav"} +{"id": "yMEMzSFbZ2s", "caption": "This audio contains someone playing a fast paced drum groove with a lot of double hits on the kick and tom. The drumming stops and then a male voice starts talking. This may be used for a drum tutorial video.", "audio": "/zhanghaomin/datas/musiccap/music_data/yMEMzSFbZ2s.wav"} +{"id": "yNIZaqTHUnc", "caption": "The low quality recording features a pop song sung by flat female vocalists singing over sustained strings melody, smooth bass, punchy snare, soft kick hits and simple hi hats. It sounds distorted and messy, since the frequencies are clashing with each other due to the bad mix. It also sounds a bit repetitive.", "audio": "/zhanghaomin/datas/musiccap/music_data/yNIZaqTHUnc.wav"} +{"id": "yO7MWuJ7zLA", "caption": "The low quality recording features a pop song that consists of passionate male vocal singing over punchy \"4 on the floor\" kick pattern, groovy accordion melody, wide tinny hi hats, claps and groovy bass. In the second half of the loop, the instrumental consists of claps, \"4 on the floor\" kick pattern without the bass, soft crash cymbal, addictive synth melody and wide chicken clucking sound effect. There is a sweep riser at the very end of the loop. It sounds fun and happy, like something kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/yO7MWuJ7zLA.wav"} +{"id": "yOJtRE-617I", "caption": "This is a street performance by a drum & pipe band. In the beginning, there is a female voice talking. Then, she starts playing the Scottish bagpipes in a joyful manner. A male voice shouts at the crowd to get them into mood and the crowd starts cheering. The atmosphere is vibrant. This piece could be used in the soundtrack of a historical drama movie that takes place in Scotland.", "audio": "/zhanghaomin/datas/musiccap/music_data/yOJtRE-617I.wav"} +{"id": "yOVaak2hemM", "caption": "This song contains acoustic drums playing along with a bass creating a folksong atmosphere along with an accordion like sounding instrument. A piano and guitar are playing a melody along with an accordion -like instrument taking the main melody from the instruments. Female voices are singing at a higher pitch. This song is in poor audio-quality. This song may be playing live at a church.", "audio": "/zhanghaomin/datas/musiccap/music_data/yOVaak2hemM.wav"} +{"id": "yPou7kokTgA", "caption": "This is a soothing traditional Indian or Eastern song that can be used as music for meditation. It is relaxing and features layered female vocals chanting \"om\". There is a bansuri melody, some rhythmic tabla playing, and an intermittent manjeera being percussively played.", "audio": "/zhanghaomin/datas/musiccap/music_data/yPou7kokTgA.wav"} +{"id": "yPzhMx3NPW4", "caption": "This disco song features male voices singing the main melody in harmony. This is accompanied by programmed percussion playing a simple beat. The bass plays funk style bass notes. A synth plays a string voice in the background with short bursts of chords. After the first line, a guitar strum is played. This song is uptempo and has a happy mood. This song can be played in a celebratory event.", "audio": "/zhanghaomin/datas/musiccap/music_data/yPzhMx3NPW4.wav"} +{"id": "yQN9gj7Vk0w", "caption": "The low quality recording features a rock song that consists of a flat male vocal, alongside background male vocals, singing over shimmering hi hats, groovy bass, punchy kick and snare hits and electric guitar melodies. It sounds energetic and emotional.", "audio": "/zhanghaomin/datas/musiccap/music_data/yQN9gj7Vk0w.wav"} +{"id": "yRU7DifuAXY", "caption": "This instrumental song features the main melody played on bells and the marimba. A timpani plays the percussion. The tempo of this song is slow. This song has no voices. The song has a celestial and dreamy feel. This song can be used in a dreamy sequence in a children's movie. There are no voices in this song.", "audio": "/zhanghaomin/datas/musiccap/music_data/yRU7DifuAXY.wav"} +{"id": "yRWndZvIAHc", "caption": "A nostalgic feeling trip hop song with an off kilter, Dilla inspired drum beat, a jazz piano playing complex chords and a male rapper.", "audio": "/zhanghaomin/datas/musiccap/music_data/yRWndZvIAHc.wav"} +{"id": "ySY5J3TDgag", "caption": "The low quality recording features a lullaby song that consists of widely spread intimate female vocals singing against each other, creating a bit of a chaotic atmosphere. There are also sustained strings melody and mellow piano melody playing in the background. The stereo image is unbalanced and it sounds soft, haunting and chaotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/ySY5J3TDgag.wav"} +{"id": "yScg02DM-jY", "caption": "The low quality recording features a string melody playing over smooth double bass, mellow piano chords and short violin melody. It sounds passionate, emotional and joyful.", "audio": "/zhanghaomin/datas/musiccap/music_data/yScg02DM-jY.wav"} +{"id": "yTc-ENutOD4", "caption": "A cheery ukulele ensemble featuring ukulele strumming and a harmonized ukulele melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/yTc-ENutOD4.wav"} +{"id": "yTq3Kr3jkvs", "caption": "The low quality recording features a didgeridoo beatboxing and it sounds crushed, distorted, but energetic - sounds like it was recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/yTq3Kr3jkvs.wav"} +{"id": "yVWk3yq3Abc", "caption": "The low quality recording features a reggae song that consists of wide harmonizing low male vocals singing over groovy bass, muffled snare, shimmering hi hats, tinny percussive elements and offbeat piano chords. The recording is noisy and it sounds easygoing and chill.", "audio": "/zhanghaomin/datas/musiccap/music_data/yVWk3yq3Abc.wav"} +{"id": "yWU0zNEy2_I", "caption": "The low quality recording features a didgeridoo melody playing outdoors. There are also some crowd chattering, water fountains and birds chirping sounds. The recording is noisy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/yWU0zNEy2_I.wav"} +{"id": "yYpfb_xV--4", "caption": "This Middle eastern folk song features a male singer singing the main melody. This is accompanied by percussion playing a simple beat. A stringed instrument plays the backing melody. A shaker plays in an eight note pattern. This song can be played at a village fair.", "audio": "/zhanghaomin/datas/musiccap/music_data/yYpfb_xV--4.wav"} +{"id": "yZNgqVInQGw", "caption": "The low quality recording features an opera live performance by detuned female vocal singing over accordion melody. It is in mono, noisy and it sounds chaotic.", "audio": "/zhanghaomin/datas/musiccap/music_data/yZNgqVInQGw.wav"} +{"id": "yZRTQX8pcMY", "caption": "This music is a percussive instrumental. The tempo is fast with a beatboxing rhythm. The beat is a vigorous, rapid, youthful, energetic, enthusiastic imitation of the drum machine. The audio quality is inferior so the music is muffled.", "audio": "/zhanghaomin/datas/musiccap/music_data/yZRTQX8pcMY.wav"} +{"id": "y_TnstfXeBQ", "caption": "This rock song features a female voice singing at a comfortable pitch. The song starts off with the voice singing vocables. This is accompanied by the overdriven guitar playing one chord three times followed by a second chord three times which is higher in pitch than the first chord. The percussion plays a role at that time. The voice continues to sing a phrase. One guitar harmonic note keeps ringing during this part. The overdriven guitar plays a descending chord pattern. The bass plays the root notes of the guitar. The percussion plays a simple beat in common time. This song can be played in a detective movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/y_TnstfXeBQ.wav"} +{"id": "y_lfY0uzmr0", "caption": "The low quality recording features an Alternative/Indie song playing in the background while there are some skateboarding sound effects and foley in front. It is obviously a skateboarding compilation video. The song consists of groovy bass, energetic drums, wide synth key chords and wide synth pad chords, while the harmonizing female vocals are singing on top of it. It sounds fun and happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/y_lfY0uzmr0.wav"} +{"id": "y_toDfeACWE", "caption": "The low quality recording features a classical song that consists of widely spread sustained strings melody and woodwind melody. It sounds vintage, calming and relaxing, like something you would hear in an easygoing movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/y_toDfeACWE.wav"} +{"id": "yaUK4XvVGTg", "caption": "This music is an electric guitar instrumental. The tempo is medium with a strong, emphatic and funky riff. There are male and female voices in a foreign language superimposed on the audio. This clip is an electronic guitar demo or lesson.", "audio": "/zhanghaomin/datas/musiccap/music_data/yaUK4XvVGTg.wav"} +{"id": "ye6O_T8YuHQ", "caption": "The low quality recording features a groovy bass guitar played over drums instrumental playback. It sounds muddy, messy and boomy, as the frequencies are clashing with each other. The recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/ye6O_T8YuHQ.wav"} +{"id": "yesyhQkYrQM", "caption": "A male vocalist sings this spirited Rock song. The tempo is fast with hard hitting drumming, punchy bass lines, electric guitar lead and keyboard harmony. The song is a vibrant, energetic, enthusiastic, engaging, catchy and upbeat Classic Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/yesyhQkYrQM.wav"} +{"id": "yeu6OEIKwws", "caption": "This is the kind of music that would be played to create a calm and mysterious ambiance. There is a bright and sustained synth and a fuzzy low-end bass synth which is used to play the melody.", "audio": "/zhanghaomin/datas/musiccap/music_data/yeu6OEIKwws.wav"} +{"id": "yfXvz2FyZ_U", "caption": "The song is of a classical style and features an intricate piano phrase alongside some passionate violin playing. The song has a certain intensity and build-up to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/yfXvz2FyZ_U.wav"} +{"id": "yfZ0z1C3blk", "caption": "The low quality recording features a melancholic electric guitar melody with echoing effects on. Even though it sounds muffled and noisy, it gives it a vintage, warm character. It kind of feels cozy listening to it.", "audio": "/zhanghaomin/datas/musiccap/music_data/yfZ0z1C3blk.wav"} +{"id": "yfaxqwNHe7w", "caption": "This Scottish folk song features bagpipes playing the main melody. This is accompanied by an accordion playing the same melody in harmony. A Scottish tenor drum plays a marching beat. A bass drum plays strokes on the count. A tambourine plays a beat in the background. This song can be played in a Scottish folk programme.", "audio": "/zhanghaomin/datas/musiccap/music_data/yfaxqwNHe7w.wav"} +{"id": "yhS-6Y8ToR8", "caption": "This electronic music features no voices. All the parts of this song are programmed. The main melody is played by a simulated plucked instrument. This is accompanied by electronic sounds in the background sounding like an alien spaceship. There are ambient sounds in the background filling the musicscape. The song has an ambient feel. This song can be played in a movie where there is travel to outer space.", "audio": "/zhanghaomin/datas/musiccap/music_data/yhS-6Y8ToR8.wav"} +{"id": "yhbpAGdv_d8", "caption": "These are sounds coming from a cartoon. Two boys are having a conversation in the Korean language. There is a spring sound effect that can be heard repeatedly. In the background, a generic orchestra piece is playing. The trumpet and the flute take turns in playing the main melody while other brass instruments and a snare drum accompanies them.", "audio": "/zhanghaomin/datas/musiccap/music_data/yhbpAGdv_d8.wav"} +{"id": "yi4-kGV30qs", "caption": "The low quality recording features a wide glass shattering sound effects layered with some synth sound effects. At the very beginning of the loop, there is a short snippet of a reverberant impact. The bad sample quality is what makes this sound low quality overall.", "audio": "/zhanghaomin/datas/musiccap/music_data/yi4-kGV30qs.wav"} +{"id": "yj4xorgrbV4", "caption": "This audio contains acoustic drums playing a groove with a lot of cymbal hits. An e-bass is holding the groove while a distorted e-guitar is playing a solo in a higher register. In the background you can hear another e-guitar playing something like an arpeggio melody in the mid-range. This song may be playing in the rehearsal band room practicing drumming to a backing song.", "audio": "/zhanghaomin/datas/musiccap/music_data/yj4xorgrbV4.wav"} +{"id": "ykkVTInYctY", "caption": "The low quality recording features a live performance with an electro song playing in the background and crowd cheering sounds. The song consists of a \"4 on the floor\" kick pattern, addictive synth bass melody, punchy snare and shimmering hi-hats. It sounds energetic and the recording is noisy as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/ykkVTInYctY.wav"} +{"id": "yl6LJDi0gi0", "caption": "A guzheng is playing a traditional melody with some notes bending while a flute is playing notes in a tremolo. In the background a string instrument is played with a bow. All the instruments are full of reverb and delay. Also are they panned to different directions of the speakers.\nThis song may be playing at a ceremonial dance or theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/yl6LJDi0gi0.wav"} +{"id": "ylKvglDzBU4", "caption": "The song is an instrumental improvisation. The song is medium fast tempo with a groovy bass line, electric guitar playing, saxophone playing, jazz drumming with percussive hits and a xylophone playing. The song is highly improvisational and energetic. The song is a modern jazz fusion or improvisation jam.", "audio": "/zhanghaomin/datas/musiccap/music_data/ylKvglDzBU4.wav"} +{"id": "ymGg5TA2YfM", "caption": "This is a country/western swing music piece. There is a male vocalist singing melodically in the lead with a story-telling attitude. The main tune is being played by the electric guitar with a bass guitar backing. The rhythm is being played by the acoustic drums. The atmosphere is easygoing. This piece could be playing in the background at an American roadside diner.", "audio": "/zhanghaomin/datas/musiccap/music_data/ymGg5TA2YfM.wav"} +{"id": "ymOjaaxRDLU", "caption": "A female vocalist sings this pop song. The tempo is fast with a lively piano accompaniment, funky bass lines, violin harmony, synthesiser and electronic arrangements and punchy drumming. The song is youthful, romantic, warm, simple and groovy. This song is an Electro Pop/ Dance pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/ymOjaaxRDLU.wav"} +{"id": "ymuRKv9iJm4", "caption": "The low quality recording features a funk song that consists of a groovy bass, shimmering hi hats, punchy snare, claps and wide arpeggiated synth strings melody. It sounds groovy, funky and addictive.", "audio": "/zhanghaomin/datas/musiccap/music_data/ymuRKv9iJm4.wav"} +{"id": "yn4-OtUmyWo", "caption": "This folk song starts off with a female voice singing the main melody. The voice has the added effect of autotune. This is accompanied by a rebab or a bowed instrument playing the same melody as the voice. Another stringed instrument is plucked, playing the same melody as the voice. The bass plays the root notes of the chords. The voice rests and other instruments come in. A clarinet plays a descending fill. Koboro percussion is played giving this song a middle-eastern feel. This song has a happy feel. It is a fusion between a folk song and a more modern beat. This song can be played as a party song.", "audio": "/zhanghaomin/datas/musiccap/music_data/yn4-OtUmyWo.wav"} +{"id": "ynWPvcGXFrM", "caption": "Violins are playing a lead melody underlined by celli playing supportive chords. A brass section is playing a countermelody while shakers and other instruments are providing rhythm. This song may be playing at a folkfest with a dancefloor.", "audio": "/zhanghaomin/datas/musiccap/music_data/ynWPvcGXFrM.wav"} +{"id": "ypg2ItQIc2c", "caption": "This piece is an instrumental. The tempo is fast with hard hitting percussion, cymbals clanging, clapping, rhythmic chanting, and shakers. It is vigorous, spirited, vibrant, energetic,intense and engaging.", "audio": "/zhanghaomin/datas/musiccap/music_data/ypg2ItQIc2c.wav"} +{"id": "yqb4GenP8gs", "caption": "This is a pop R&B song in Portuguese. The song has a cheerful and fun effect to it, and the four on the floor style helps in creating the feeling of dancing. The singers are a man and woman with smooth vocals, singing a duet - harmonically.", "audio": "/zhanghaomin/datas/musiccap/music_data/yqb4GenP8gs.wav"} +{"id": "yreWOyWr6Uk", "caption": "Someone is playing a snare with brushes along to zitars playing a repeating melody. In the background you can hear an e-bass and an acoustic guitar strumming chords. This song may be playing in a live concert.", "audio": "/zhanghaomin/datas/musiccap/music_data/yreWOyWr6Uk.wav"} +{"id": "yrme-KRBvzk", "caption": "The song is an instrumental. The tempo is medium with a cellist playing a virtuoso solo accompanied by a string section harmony, flutes in harmony and a loud banging timpani. The song is spirited and passionate with poor audio quality. The song is a western classical piece.", "audio": "/zhanghaomin/datas/musiccap/music_data/yrme-KRBvzk.wav"} +{"id": "yuWjB3XA8tc", "caption": "This is a techno song that's layered with a cacophony of sound effects like robotic sounds, fuzzy sounds, and sounds of whirring machinery. The bassline is rapid, played in 16th notes throughout the song. The beat pattern is four on the floor.", "audio": "/zhanghaomin/datas/musiccap/music_data/yuWjB3XA8tc.wav"} +{"id": "yw6uqQQF5Ig", "caption": "This fingerstyle guitar song features a guitar playing at a slow tempo. The bass notes are also played by the same guitar. The picking pattern involves a percussive style of guitar playing. There are no other instruments in this song. This is an instrumental song. There are no voices in this song. This song has a romantic feel. This song can be played in a luxury hotel lobby.", "audio": "/zhanghaomin/datas/musiccap/music_data/yw6uqQQF5Ig.wav"} +{"id": "ywuR9AfpA_E", "caption": "The low quality recording features an aggressive, distorted car engine revving sound effect and layered sustained string and synth lead riser in the background. There are some wide crackling noises, which, besides a slight distortion of the actual sound, is making this sound lower in quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/ywuR9AfpA_E.wav"} +{"id": "yx7BZ_djE-U", "caption": "The low quality recording features a live performance of a traditional song that consists of wooden percussive elements, sustained suspenseful strings melody and passionate male vocal singing over it. It sounds passionate, mystical, soulful and suspenseful, even though the recording is a bit noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/yx7BZ_djE-U.wav"} +{"id": "yzT9nsHslAk", "caption": "This is a kid song. The music sounds like it was recorded coming out of the TV with a phone which makes it sound low quality. The drum beat is fast tempo. The instruments are not very distinguishable except for an ambient synth that plays a bright melody. This is a song that could be featured in a kids TV show.", "audio": "/zhanghaomin/datas/musiccap/music_data/yzT9nsHslAk.wav"} +{"id": "yzjbAxCnt7U", "caption": "The Disco song features a passionate male vocal, alongside harmonizing background vocals, singing over sustained strings melody, piano melody, brass melody, punchy kick and snare hits, shimmering hi hats and some claps. It sounds funky, addictive and passionate - like something you would hear in clubs during the 70s.", "audio": "/zhanghaomin/datas/musiccap/music_data/yzjbAxCnt7U.wav"} +{"id": "z0w3Y8BGLQE", "caption": "This music is an acoustic instrumental. The tempo is medium with an acoustic guitar lead harmony, with minimalist instrumentation. The music is soft, soothing, pleasant, engaging, and delicate.", "audio": "/zhanghaomin/datas/musiccap/music_data/z0w3Y8BGLQE.wav"} +{"id": "z2kTJ6pQ4Uo", "caption": "This is a movie music piece. There is a female vocalist singing melodically at the forefront. There is an acoustic guitar playing the main tune with a bass guitar holding the root notes in the background. The rhythmic structure is composed of acoustic sounding drums and percussion playing a syncopated beat. There is a feeling of hope in this piece. This piece could be used in the soundtrack of an inspiring movie/TV show. It could also be played at sports venues.", "audio": "/zhanghaomin/datas/musiccap/music_data/z2kTJ6pQ4Uo.wav"} +{"id": "z31iCbkqYyw", "caption": "The Rock song features harmonizing male vocals singing over punchy kick and snare hits, energetic open hats, wide electric guitar chords and distorted bass guitar. It sounds energetic and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/z31iCbkqYyw.wav"} +{"id": "z3UCnloQGPY", "caption": "This is an instrumental movie music piece used in the background of a short film. There is a gentle melody being played by the strings and the piano. The atmosphere is eerie and enigmatic. This piece could suit well in the soundtrack of a mystery video game or a movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/z3UCnloQGPY.wav"} +{"id": "z4ewUsnIJKI", "caption": "This audio contains sound effects like horn honking and mallet instruments walking up the scale. This may be playing on a machine in a casino.", "audio": "/zhanghaomin/datas/musiccap/music_data/z4ewUsnIJKI.wav"} +{"id": "z6SNngkMAug", "caption": "A female singer sings this poignant melody. The song is slow tempo with an electric guitar buzzing harmony, piano accompaniment, steady drumming rhythm, keyboard harmony, groovy bass line and Tambour percussions. The song is emotional and melancholic. The song is a poor quality recording of a classic pop song.", "audio": "/zhanghaomin/datas/musiccap/music_data/z6SNngkMAug.wav"} +{"id": "z7vNtEcM9Bk", "caption": "The performer is snapping his fingers in rhythm with the upbeat japanese music playing in the background. The song is a j-pop song and features vibrant rhythmic synth activity and has a general dance feel to it. It's a live recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/z7vNtEcM9Bk.wav"} +{"id": "z8Wjdss5uMg", "caption": "This slow pop song features a synth playing the bass notes as well as the lead melody. The music is in 6/8 time signature. In the first bar, two chords are played. The main melody is played in the second bar. The synth accents the notes on a higher register. The bass plays at off timing. The first two notes of the bass are played on the first count and fourth count of the first bar. The next bass note is played on the first count of the second bar and the following note is played on the 'three and' count of the second bar. The mood of this song is relaxing. This song can be played in a coffee shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/z8Wjdss5uMg.wav"} +{"id": "z9UJD6O7EAE", "caption": "This recording has been done live in a room with speakers. It features a DJ scratching the desks live to create these squeaky scratching sound effects. The song is a mellow hip hop song featuring a relaxed drum beat and bassline.", "audio": "/zhanghaomin/datas/musiccap/music_data/z9UJD6O7EAE.wav"} +{"id": "z9hRQiJMnIw", "caption": "This heavy metal song features a high pitched male voice. This is accompanied by percussion playing an aggressive metal beat. The kick drum plays double kicks matching the picking pattern of the guitars. The distortion guitars play twin parts. One guitar plays the low parts while the other plays the same riff at a higher octave. The bass guitar follows the distortion guitars and plays the notes from the same riffs but ending earlier than the guitars. This song has a romantic theme. This song can be played in a superhero movie.", "audio": "/zhanghaomin/datas/musiccap/music_data/z9hRQiJMnIw.wav"} +{"id": "zCGGb7Eh_f4", "caption": "The low quality recording features a hollow male talking over a traditional strings melody, while there are sounds of people talking and some wooden impacts in the background. The recording is noisy and the volume of the song slowly goes up, as the male vocal stops talking.", "audio": "/zhanghaomin/datas/musiccap/music_data/zCGGb7Eh_f4.wav"} +{"id": "zCrpaLEq1VQ", "caption": "Someone is playing an e-bass with different effects on. Using a finger-tapping technique to play a melody/riff. This song may be playing bass at home.", "audio": "/zhanghaomin/datas/musiccap/music_data/zCrpaLEq1VQ.wav"} +{"id": "zD4PXuUkwsc", "caption": "The low quality recording features a dubstep song that contains low flat male vocal, arpeggiated synth melody, repetitive arpeggiated synth lead and build up snare roll in the first half, after which comes the drop that consists aggressive and manic wobble bass, punchy kick and snare hits, tinny hi hats and repetitive arpeggiated synth lead melody. Overall it sounds manic, energetic and aggressive.", "audio": "/zhanghaomin/datas/musiccap/music_data/zD4PXuUkwsc.wav"} +{"id": "zGBKakEGSyc", "caption": "The low quality recording features a pop song that consists passionate female vocal, alongside wide harmonizing female vocals, singing over hypnotic synth lead melody, mellow piano chords, punchy snare, bouncy syncopated snare hits, punchy kick hits, groovy bass, staccato violin melody, wide toms roll and shimmering hi hats. It sounds happy, fun and uplifting - like something you would hear on a radio.", "audio": "/zhanghaomin/datas/musiccap/music_data/zGBKakEGSyc.wav"} +{"id": "zGONTDY_rNM", "caption": "The low quality recording features a mantra song that consists of soft female vocal singing over wide, mellow synth pad chords. It sounds passionate, calming and relaxing - like something you would play while doing yoga.", "audio": "/zhanghaomin/datas/musiccap/music_data/zGONTDY_rNM.wav"} +{"id": "zNAHQYshxZk", "caption": "The low quality recording features a flat male vocal talking, after which there is a scratching vinyl sound - sort of like a tutorial on how to scratch a vinyl. The recording is mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/zNAHQYshxZk.wav"} +{"id": "zNSV9GkpRfM", "caption": "A male Latin singer sings this energetic vocal with male backup singers in vocal harmony. The song is fast tempo with quick Latin percussions, groovy bass line, keyboard accompaniment and trumpets blaring. The song is energetic and passionate. The song has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/zNSV9GkpRfM.wav"} +{"id": "zNbF006Y5x4", "caption": "This music is a lively xylophone instrumental. The tempo is medium with minimal instrumentation of a xylophone and piano harmony. The music is pleasant, melodic, quirky,a little peculiar and unusual like music in a circus for a clown act. There is also a sound of blowing or shushing in the background.", "audio": "/zhanghaomin/datas/musiccap/music_data/zNbF006Y5x4.wav"} +{"id": "zNgRUFOj3HI", "caption": "The low quality recording features a DJ scratching the vinyl of a hip hop instrumental that consists of punchy kick and snare hits and sustained filter modulated bass. The recording is muffled, noisy, mono and muddy, as it was probably recorded with a phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/zNgRUFOj3HI.wav"} +{"id": "zOvFaef41iw", "caption": "The drums are playing a funky groove together with the e-bass. An almost clean e-guitar is playing an additional melody in the background. A male and female voice are singing together accompanied by a string section in the background while a brass section is giving short and strong responses as a buildup and breakingpoint. This song may be playing at a veny-shop.", "audio": "/zhanghaomin/datas/musiccap/music_data/zOvFaef41iw.wav"} +{"id": "zPMiMXCazAI", "caption": "This instrumental song features a deep bass sound that is playing continuously in the background. A piano sequence is played which gives this song an eerie and suspenseful feel. A layer of synth swells are played when the piano sequence is played. At the end, high pitch sounds are played in the background at a low volume as if the sound source is far away from the mic. The mood of this song is suspenseful as if there is impending danger. This song can be played in the lounge of a video game.", "audio": "/zhanghaomin/datas/musiccap/music_data/zPMiMXCazAI.wav"} +{"id": "zPhuyMYy9EI", "caption": "A high pitched long note is playing along with other synthesizer pad sounds to create a bizarre and mildly creepy atmosphere. A synthesizer lead is playing a disharmonious melody. The sounds are full of reverb and delay. This song may be playing in an alien arrival movie scene.", "audio": "/zhanghaomin/datas/musiccap/music_data/zPhuyMYy9EI.wav"} +{"id": "zR4ebAuqy8w", "caption": "The music excerpt sounds as if it was recorded with a low-quality phone and so the quality of the audio is also low. A repeating melody is being played by horns from an orchestra ensemble. Strings can be heard providing harmonic context. Wind sounds as well as electronic and video game sounds can be heard in the background. It sounds as if the atmosphere is tense and a fight is going on.", "audio": "/zhanghaomin/datas/musiccap/music_data/zR4ebAuqy8w.wav"} +{"id": "zRixZ7mWwho", "caption": "This is a gear showcase jam. The only instrument being played is an electric guitar being strummed lightly. There is a chorus ensemble effect on the guitar making it sound like multiple guitars are being played at the same time. There is a dreamy atmosphere in this recording. Chorus guitar samples could be picked up from this recording. Some parts of it could also be mixed into advertisement jingles.", "audio": "/zhanghaomin/datas/musiccap/music_data/zRixZ7mWwho.wav"} +{"id": "zRpPf62Zvto", "caption": "This gospel song features a female voice singing the main melody. There are other female voices singing in harmony with the main voice. This is accompanied by simple percussion playing a minimalist beat. The bass plays the root notes of the chords with no flourishes. There are strings playing fills in the background. A piano plays arpeggiated notes in between lines. The song is sung with a passionate voice. This song can be played in a movie with a Christian theme.", "audio": "/zhanghaomin/datas/musiccap/music_data/zRpPf62Zvto.wav"} +{"id": "zSGWoXDFM64", "caption": "A male choir is at the end of a phrase before a single male voice takes over singing with a mid ranged opera voice along to a piano and an accordion. In the background the crowd is cheering,laughing and clapping. This song may be playing in a theater.", "audio": "/zhanghaomin/datas/musiccap/music_data/zSGWoXDFM64.wav"} +{"id": "zSSIGv82318", "caption": "The low quality recording features an arpeggiated electric guitar melody being played with and without phaser pedal effect. It sounds cool and the recording is noisy and in mono.", "audio": "/zhanghaomin/datas/musiccap/music_data/zSSIGv82318.wav"} +{"id": "zSq2D_GF00o", "caption": "The song is instrumental. The tempo is medium with a steady percussive rhythm, keyboard accompaniment, string section harmony and various sound effects. The song is ominous and full of suspense. The song is a movie soundtrack and has poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/zSq2D_GF00o.wav"} +{"id": "zTtZH-Q61Ik", "caption": "A female vocalist sings this beautiful pop melody. The tempo is medium fast with rhythmic acoustic guitar, keyboard harmony, electric guitar melody, straight drumming;steady bass and tambourine beats. The song is mellow, sweet, passionate,emotional, youthful, romantic, simple and tender. This song is a hit Indonesian Pop.", "audio": "/zhanghaomin/datas/musiccap/music_data/zTtZH-Q61Ik.wav"} +{"id": "zTuxNA1y6Os", "caption": "This audio contains a male voice singing in a higher pitch along to acoustic drums with an e-bass playing a melody. The e-guitar also follows that bassline. Another e-guitar is strumming chords in a higher key in the background. This song may be playing in a music video telling a story.", "audio": "/zhanghaomin/datas/musiccap/music_data/zTuxNA1y6Os.wav"} +{"id": "zU4mwg-HHoQ", "caption": "The low quality recording features opera live performance that consists of passionate female vocal singing over groovy piano melody. The recording is very noisy, in mono and very reverberant as it was probably recorded in a medium size hall, with a poor quality microphone.", "audio": "/zhanghaomin/datas/musiccap/music_data/zU4mwg-HHoQ.wav"} +{"id": "zUaZGKZIKic", "caption": "someone is playing a digital piano composition while a male voice is singing loudly a melody with long notes. In the background birds chirping and other noises can be heard. This is an amateur recording. This song may be playing in a live performance.", "audio": "/zhanghaomin/datas/musiccap/music_data/zUaZGKZIKic.wav"} +{"id": "zVA66aZOBH4", "caption": "This is the live performance of a Nepali folk music piece. It is an instrumental piece. There is a bansuri performing the melodic structure of the piece while the tabla joins briefly as the rhythm. The atmosphere is vibrant and dreamy. This piece could be used during scenery shots in the soundtrack of an adventure movie that takes place in the Himalayas.", "audio": "/zhanghaomin/datas/musiccap/music_data/zVA66aZOBH4.wav"} +{"id": "zWEznZ40k2Q", "caption": "The low quality recording features a kids song that features a shimmering bell melody, mellow cowbell and girl vocals singing over it. The recording is in mono and noisy - the audio is really crackling. It sounds fun and happy, like something that kids would listen to.", "audio": "/zhanghaomin/datas/musiccap/music_data/zWEznZ40k2Q.wav"} +{"id": "zWJC_qr2610", "caption": "The low quality recording features a live performance of a rock song and it features passionate male vocals, alongside harmonizing male vocals, singing over arpeggiated electric guitar melody, boomy bass guitar, punchy kick and snare hits and shimmering open hats. It sounds noisy and messy, as the frequencies are clashing with each other, but it is still groovy and emotional regardless.", "audio": "/zhanghaomin/datas/musiccap/music_data/zWJC_qr2610.wav"} +{"id": "zXxJymYt8Z4", "caption": "The low quality recording features a live performance of a reggae song and it consists of a fruity male vocal preparing to sing over shimmering hi hats, snappy rimshots, funky electric guitar chords and groovy bass. As it is a live performance, there are some crowd whistling and cheering noises in the background. It sounds easygoing and exciting.", "audio": "/zhanghaomin/datas/musiccap/music_data/zXxJymYt8Z4.wav"} +{"id": "zYM0gtd_PRo", "caption": "The music is a soft rock ballad with Hawaiian sounds. The melody is driven by a gliding steel pedal guitar. In the background a synth string section can be heard sustaining chords creating a relaxed ambience. The atmosphere of the song is easy going and relaxed. This is a song you would hear at a hotel lobby in Hawaii.", "audio": "/zhanghaomin/datas/musiccap/music_data/zYM0gtd_PRo.wav"} +{"id": "zYRI-R2gxUI", "caption": "This music is instrumental. The tempo is medium with a beautiful piano harmony. The music starts softly and builds up to a beautiful melody. It is mellow, romantic, warm, cheerful and pleasant. This is a Piano Instrumental.", "audio": "/zhanghaomin/datas/musiccap/music_data/zYRI-R2gxUI.wav"} +{"id": "zYUZEXCE7gw", "caption": "The Latin Jazz song features an exotic, jazzy piano melody, plucked double bass, subtle hi hats and percussive wooden elements playing as the passionate female vocalist is singing. It sounds like it was recorded with stereo room microphones, since the vocal sounds a bit \"roomy\".", "audio": "/zhanghaomin/datas/musiccap/music_data/zYUZEXCE7gw.wav"} +{"id": "zYa3ksSrCqw", "caption": "This is a Carnatic classical music piece. It is being performed live. There is a male vocalist singing in a versatile manner. The melody is being played by a Carnatic violin line. The rhythmic background is composed of the tabla percussion. The atmosphere is vibrant and the instrumentation is complex. This piece can be an educational example of a Carnatic music piece to be taught in music schools.", "audio": "/zhanghaomin/datas/musiccap/music_data/zYa3ksSrCqw.wav"} +{"id": "zYsFbF9emtI", "caption": "The low quality recording features a cover of a rock song played on bass guitar over electric guitar arpeggiated melody played on playback in the background. The recording is noisy, in mono, as it was probably recorded on a phone, and it sounds emotional and passionate.", "audio": "/zhanghaomin/datas/musiccap/music_data/zYsFbF9emtI.wav"} +{"id": "z_aUtjxgCNk", "caption": "A flute is playing a loud melody in the higher register while someone is playing a rhythm on a tabla. Percussive tambourinelike instruments serve as percussive addition along with some single bell or chime hits. This is an amateur recording and it sounds like it was recorded in a big room due to a lot of reverb. This song may be played at a live concert with people sitting in chairs being comfortable.", "audio": "/zhanghaomin/datas/musiccap/music_data/z_aUtjxgCNk.wav"} +{"id": "z_fEIZOv0JY", "caption": "This is a piece from a musical. The piano is playing a repetitive tune. There is a male vocalist singing melodically. There is a playful atmosphere to the piece. This piece could be playing in the background during activities for kids.", "audio": "/zhanghaomin/datas/musiccap/music_data/z_fEIZOv0JY.wav"} +{"id": "zaEdWwSamS0", "caption": "Different melodies are being played by bell sounds; e-piano; e-bass and in the background you can hear drone sounds and soft pads. A digital drum is playing a laid back groove. A sound-effect is coming in. The whole song sounds relaxing. This song may be playing for an advertisement.", "audio": "/zhanghaomin/datas/musiccap/music_data/zaEdWwSamS0.wav"} +{"id": "zayC5mUo7sY", "caption": "A male vocalist sings this spirited song. The tempo is fast with intense drumming, loud harmonic electric guitar feedback, bass guitar , emphatic vocals and keyboard accompaniment. The song is a loud, progressive, powerful youthful and emphatic Hard Rock song.", "audio": "/zhanghaomin/datas/musiccap/music_data/zayC5mUo7sY.wav"} +{"id": "zbCqre50eLM", "caption": "The low quality recording features a live performance that consists of harmonizing female vocals singing over mellow piano and groovy trombone melody. There are some shoe tapping sounds from performers. It sounds fun, happy, joyful and the recording is in mono and noisy.", "audio": "/zhanghaomin/datas/musiccap/music_data/zbCqre50eLM.wav"} +{"id": "zcc7dJIY7uc", "caption": "Dub reggae music featuring a drum fill, female vocal sample with effects, a smooth sine wave synth melody in the background, percussion and guitar. The mood is smooth and easy.", "audio": "/zhanghaomin/datas/musiccap/music_data/zcc7dJIY7uc.wav"} +{"id": "zd3lShuZNmU", "caption": "This is a calming and soothing piece played on the piano. It could be classified as a ballad. It is gentle and tranquil - there are mostly high notes being played.", "audio": "/zhanghaomin/datas/musiccap/music_data/zd3lShuZNmU.wav"} +{"id": "zdtVT2xwrHU", "caption": "A male voice is singing loudly with an opera technique while an acoustic drum is playing along with a e-bassline. Underlined by strings playing a melody. This song may be playing at a wedding.", "audio": "/zhanghaomin/datas/musiccap/music_data/zdtVT2xwrHU.wav"} +{"id": "zeUEOxTd8IE", "caption": "This is a K-pop music piece performed by a boy band. Initially, a male vocalist is singing in a rap-like manner. Then, it switches to another male vocal that is singing more melodically. The melody is being played by a crisp synth sound. The rhythmic background consists of an energetic electronic drum beat. There is a danceable feel to it. This piece could be playing at Korean nightclubs and dance clubs.", "audio": "/zhanghaomin/datas/musiccap/music_data/zeUEOxTd8IE.wav"} +{"id": "zfkPKRn8ah8", "caption": "This is a dancehall music piece. There is a male vocalist singing at a medium-to-high pitch with a Jamaican accent. In the background, there is a keyboard playing the main melody. The atmosphere of the piece is vibrant. This piece could be used at beach parties and summer/vacation themed movies or TV shows.", "audio": "/zhanghaomin/datas/musiccap/music_data/zfkPKRn8ah8.wav"} +{"id": "zgI-Lr6Pbcs", "caption": "The low quality recording features a haunting female vocal singing over mellow rhythm guitar chord progression. The recording is extremely noisy, as it was probably recorded with an old phone.", "audio": "/zhanghaomin/datas/musiccap/music_data/zgI-Lr6Pbcs.wav"} +{"id": "zir3uL14ijM", "caption": "The low quality recording features a passionate male vocal singing over sustained strings chords, wide electric guitar arpeggiated melody and smooth bass. It sounds easygoing, passionate and chill.", "audio": "/zhanghaomin/datas/musiccap/music_data/zir3uL14ijM.wav"} +{"id": "zixIuxzCCvs", "caption": "This is the live recording of a heavy metal music piece. The male vocalist in the lead has a powerful wide-ranged vocal. There is an overdriven electric guitar that is playing a repeated riff with a bass guitar supporting it in the background. The rhythm is provided by a loud, fast-paced metal beat on the acoustic drums. The atmosphere is hard-hitting and energetic. The piece could be playing in the background of a rock/metal bar.", "audio": "/zhanghaomin/datas/musiccap/music_data/zixIuxzCCvs.wav"} +{"id": "zj2G-KVw4N4", "caption": "This waltz song features accordions playing in harmony. Male voices sing the main melody. The voices sing in harmony. When the voices start to sing, the accordions play the same melody as the voices. The bass is played on a tuba. An acoustic guitar strums chords. A tambourine plays the part of the percussion. There are trumpets and clarinets playing in this song. This is a folk song. The mood of this song is happy.", "audio": "/zhanghaomin/datas/musiccap/music_data/zj2G-KVw4N4.wav"} +{"id": "zjZV0tvur2I", "caption": "The low quality recording features a widely spread resonating bowl tones. It sounds calming and relaxing, like something you would hear in a yoga session.", "audio": "/zhanghaomin/datas/musiccap/music_data/zjZV0tvur2I.wav"} +{"id": "zjsWFvUkh7M", "caption": "A male vocalist sings this energetic song. The tempo is fast with enthusiastic drumming , rhythmic electric and keyboard harmony. The song is muffled because of poor audio quality and several sounds that are superimposed on it. There are sounds of water, static, bubbles, scuffling and a female voice speaking. The song is incoherent but from what can be heard it sounds like Pop Rock.", "audio": "/zhanghaomin/datas/musiccap/music_data/zjsWFvUkh7M.wav"} +{"id": "zkYXE0-JsY4", "caption": "This is a hard rock clip with a metallic electric guitar riff that follows the melody of the lead vocal. Percussively, there is a four on the floor drum beat that is loud and thumping. The lead vocalist has a croaky and gritty voice.", "audio": "/zhanghaomin/datas/musiccap/music_data/zkYXE0-JsY4.wav"} +{"id": "zmbwvsdXlBU", "caption": "This dance song features a female voice singing the main melody. This is accompanied by programmed percussion playing a bass driven beat in common time. A synth plays chords in the background. The bass plays the root notes of the chords. There is a whistling sound played on a synth at the beginning of the song. This song has a happy tone. This song can be played in a club.", "audio": "/zhanghaomin/datas/musiccap/music_data/zmbwvsdXlBU.wav"} +{"id": "zopos1B6Elc", "caption": "This file contains an orchestral composition rising up while a lot of digital clicking sounds are in the foreground. This is an amateur recording. And the sounds seem to come from a different source. This song may be playing in an adventure videogame.", "audio": "/zhanghaomin/datas/musiccap/music_data/zopos1B6Elc.wav"} +{"id": "zqbHYVH6Wqo", "caption": "The song is an instrumental. The tempo is medium with traditional horn instruments playing, tambourine percussion, keyboard harmony and cymbal crashes. The song is devotional and spirited. The song has a bad audio quality with ambient crowd noises.", "audio": "/zhanghaomin/datas/musiccap/music_data/zqbHYVH6Wqo.wav"} +{"id": "zrb76mJOZQQ", "caption": "This amateur recording features the sound of two different cycle bells. The first bell is a single striking sound. The second bell has the sound of ringing. This audio clip features ambient noise as well. There are no musical instruments in this clip. There are no voices in this clip.", "audio": "/zhanghaomin/datas/musiccap/music_data/zrb76mJOZQQ.wav"} +{"id": "zrrM6Qg2Dwg", "caption": "This song features the main melody played on a steel pan. This is accompanied by programmed percussion with the hi-hat being played on the 'and' count of every bar. A bass plays the root notes of the chords in the background. Another percussion instrument plays a beat that sounds like a trotting horse. This song has a happy mood. This song can be played in a movie where a family is going on a holiday at a Caribbean island.", "audio": "/zhanghaomin/datas/musiccap/music_data/zrrM6Qg2Dwg.wav"} +{"id": "ztfegVzqeCI", "caption": "A quirky drum machine and warm synth bass provide the accompaniment for a female singer with noticeable reverb. A wild theremin with delay and wide aggressive vibrato enters to give the music a wild sci-fi feel.", "audio": "/zhanghaomin/datas/musiccap/music_data/ztfegVzqeCI.wav"} +{"id": "zu_1zpF--Zg", "caption": "This audio contains someone playing jazz chords and melody on a e-guitar along with an upright bass also creating a slapping sound as a percussive element. In the background you can hear people talking and the sound of dishes. This song may be playing in a restaurant.", "audio": "/zhanghaomin/datas/musiccap/music_data/zu_1zpF--Zg.wav"} +{"id": "zw5dkiklbhE", "caption": "This audio contains someone playing a wooden bongo cajon. This is an amateur recording.", "audio": "/zhanghaomin/datas/musiccap/music_data/zw5dkiklbhE.wav"} +{"id": "zwfo7wnXdjs", "caption": "The song is an instrumental. The song is medium tempo with various traditional Arabian stringed instruments playing in harmony along with Arabic percussion instruments. The song is traditional and emotional. The song is an ancient folk song but in poor audio quality.", "audio": "/zhanghaomin/datas/musiccap/music_data/zwfo7wnXdjs.wav"} +{"id": "zx_vcwOsDO4", "caption": "The rock music is purely instrumental and features an electric guitar with a distortion effect on. The guitarist is playing a lot of notes with virtuosity. This music excerpt would make for a really good electric guitar solo.", "audio": "/zhanghaomin/datas/musiccap/music_data/zx_vcwOsDO4.wav"} +{"id": "zyXa2tdBTGc", "caption": "The song is an instrumental. The song is slow tempo with a steady drumming rhythm, triangle percussions, piano accompaniment, String synth harmony and strong bass line. The song is emotional and deeply meditative.", "audio": "/zhanghaomin/datas/musiccap/music_data/zyXa2tdBTGc.wav"} +{"id": "zzNdwF40ID8", "caption": "This is a glitch music piece. There is a synth sound rising in pitch that resembles a triangle wave. There are granular synth samples being played randomly. A virtual percussive low-to-mid bell sound is playing a melody that resembles a marimba. There is an eerie feeling of flow. This piece could be used in the soundtracks of dystopian sci-fi movies. 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"caption": "Water running with distant speech in the background", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part21/YPWjEfOkb6ro.wav"} +{"id": "YgW7s3YAthpI", "caption": "A person gulping followed by glass tapping then liquid shaking in a container proceeded by liquid pouring before plastic thumps on paper", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part31/YgW7s3YAthpI.wav"} +{"id": "YJmWaRt8-u0s", "caption": "A motorcycle engine running idle while two men communicate with each other", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part17/YJmWaRt8-u0s.wav"} +{"id": "Y-JP1GqPEKtw", "caption": "A man talking as a power tool motor runs followed by the buzzing of an electric sanding machine", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part0/Y-JP1GqPEKtw.wav"} +{"id": "YoN0IcZaHD_8", "caption": "A man speaks followed by a tools drilling wood", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part35/YoN0IcZaHD_8.wav"} +{"id": "Y30D1tqNFHMc", "caption": "A loud white noise and then some beeping", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part4/Y30D1tqNFHMc.wav"} +{"id": "YsCzRVvu9XeY", "caption": "A rhythmic whistle plays a tune", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part37/YsCzRVvu9XeY.wav"} +{"id": "Y-Sz4z0QwEuM", "caption": "A long, loud burp", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part0/Y-Sz4z0QwEuM.wav"} +{"id": "YeXj9OAik5cc", "caption": "An idle motorbike engine running as a bird chirps in the background and wind blows into a microphone", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part30/YeXj9OAik5cc.wav"} +{"id": "YbhlhcGONisM", "caption": "A man speaks followed by thumps and clicks with some faint grunts", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part28/YbhlhcGONisM.wav"} +{"id": "YJsoBpL86R5U", "caption": "A woman talking then a child talking followed by a man talking then a goat yelling", "audio": "/zhanghaomin/datas/audiocaps/dataset/audioset/zip_audios/unbalanced_train_segments/unbalanced_train_segments_part17/YJsoBpL86R5U.wav"} diff --git a/tests/scps/tango-master/data/generate_lists.py b/tests/scps/tango-master/data/generate_lists.py new file mode 100644 index 0000000000000000000000000000000000000000..0d796c87d83f6a910e42220eaa9c55bb7777ac08 --- /dev/null +++ b/tests/scps/tango-master/data/generate_lists.py @@ -0,0 +1,46 @@ +import json +import random + + +#jsonfile = "/zhanghaomin/datas/audioset_sl/as_final.json" +#jsonfile = "/radiostorage/WavCaps/json_files/BBC_Sound_Effects/bbc_final.json" +#jsonfile = "/radiostorage/WavCaps/json_files/FreeSound/fsd_final.json" +jsonfile = "/radiostorage/WavCaps/json_files/SoundBible/sb_final.json" + + +with open(jsonfile, "r") as fr: + jsondata = json.loads(fr.read()) + print(len(jsondata["data"])) + print(jsondata["data"][0]) + +num_all = len(jsondata["data"]) + +datas = list(range(num_all)) + +random.seed(0) +random.shuffle(datas) + +#val_data = datas[:1000] +#test_data = datas[:1000] +#train_data = datas[1000:] +train_data = datas + + +#{"id": "Yb0RFKhbpFJA.wav", "caption": "Wind and a man speaking are heard, accompanied by buzzing and ticking.", "audio": "wav_path", "duration": 10.0} +#{"description": "Greengrocer Cicada (Cyclochila Virens) - close-up stridulation, almost reaching full burst. Dog in distance. Recorded in captivity.", "category": "['Nature']", "caption": "A bug is stridulating. A dog is barking in the distance.", "id": "NHU05051026", "duration": 88.84353125, "audio": "wav_path", "download_link": "https://sound-effects-media.bbcrewind.co.uk/zip/NHU05051026.wav.zip"} +#{"id": "180913", "file_name": "UK Mello.wav", "href": "/people/Tempouser/sounds/180913/", "tags": ["Standard", "ringtone", "basic", "traditional"], "description": "Standard traditional basic ringtone, in mello tone.", "author": "Tempouser", "duration": 3.204375, "download_link": "https://freesound.org/people/Tempouser/sounds/180913/download/180913__tempouser__uk-mello.wav", "caption": "A traditional ringtone is playing.", "audio": "wav_path"} +#{"title": "Airplane Landing Airport", "description": "Large commercial airplane landing at an airport runway.", "author": "Daniel Simion", "href": "2219-Airplane-Landing-Airport.html", "caption": "An airplane is landing.", "id": "2219", "duration": 14.1424375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2219&type=wav"} + + +#with open("val_audioset_sl.json", "w") as fw: +# for index in val_data: +# fw.write(json.dumps(jsondata["data"][index]) + "\n") + +#with open("test_audioset_sl.json", "w") as fw: +# for index in test_data: +# fw.write(json.dumps(jsondata["data"][index]) + "\n") + +with open("train_soundbible.json", "w") as fw: + for index in train_data: + fw.write(json.dumps(jsondata["data"][index]) + "\n") + diff --git a/tests/scps/tango-master/data/generate_lists_audiocaps.py b/tests/scps/tango-master/data/generate_lists_audiocaps.py new file mode 100644 index 0000000000000000000000000000000000000000..871e9883f86ccfe13d9f56c783e81fad92372d50 --- /dev/null +++ b/tests/scps/tango-master/data/generate_lists_audiocaps.py @@ -0,0 +1,74 @@ +import os +import json + + +wav_path = "/zhanghaomin/datas/audiocaps/dataset/audioset/" + +train_file = "/zhanghaomin/datas/audiocaps/dataset/metadata/audiocaps/datafiles/audiocaps_train_label.json" +test_file = "/zhanghaomin/datas/audiocaps/dataset/metadata/audiocaps/testset_subset/audiocaps_test_nonrepeat_subset_0.json" + + +wavs = {} +for fpath, dirs, fs in os.walk(wav_path): + for f in fs: + if f.endswith(".wav") or f.endswith(".WAV"): + utt = f.rsplit("/", 1)[-1].rsplit(".", 1)[0] + assert(utt not in wavs) + wavs[utt] = os.path.join(fpath, f) +print("wavs", len(wavs)) + + +datas = {} +with open(train_file, "r") as fr: + jsondata = json.loads(fr.read()) + print("train_file", len(jsondata["data"])) + for data in jsondata["data"]: + wav = data["wav"] + caption = data["caption"] + + utt = wav.rsplit("/", 1)[-1].rsplit(".", 1)[0] + wav = wavs[utt] + datas[utt] = (utt, wav, caption) + +with open(test_file, "r") as fr: + jsondata = json.loads(fr.read()) + print("test_file", len(jsondata["data"])) + for data in jsondata["data"]: + wav = data["wav"] + caption = data["caption"] + + utt = wav.rsplit("/", 1)[-1].rsplit(".", 1)[0] + wav = wavs[utt] + datas[utt] = (utt, wav, caption) + + +test_final = "/zhanghaomin/codes2/tango-master/data/test_audiocaps_subset.json" +test_utts = {} +test_utts_list = [] +with open(test_final, "r") as fr: + for line in fr.readlines(): + wav = json.loads(line.strip())["location"] + utt = wav.rsplit("/", 1)[-1].rsplit("_", 1)[0] + utt = "Y"+utt + assert(utt not in test_utts) + test_utts[utt] = 1 + test_utts_list.append(utt) + + +with open("/zhanghaomin/codes2/tango-master/data/audiocaps/train_audiocaps.json", "w") as fw: + for utt, (utt, wav, caption) in datas.items(): + if utt not in test_utts: + fw.write(json.dumps({"id": utt, "caption": caption, "audio": wav}) + "\n") + + +with open("/zhanghaomin/codes2/tango-master/data/audiocaps/test_audiocaps.json", "w") as fw: + for utt, (utt, wav, caption) in datas.items(): + if utt in test_utts: + fw.write(json.dumps({"id": utt, "caption": caption, "audio": wav}) + "\n") + + +os.system("mkdir audiocaps/test_wavs/") +for index, utt in enumerate(test_utts_list): + utt, wav, caption = datas[utt] + os.system("cp %s audiocaps/test_wavs/output_%s.wav" % (wav, str(index))) + diff --git a/tests/scps/tango-master/data/test_audiocaps_subset.json b/tests/scps/tango-master/data/test_audiocaps_subset.json new file mode 100644 index 0000000000000000000000000000000000000000..07445ce82103b0a29cc6a43528b9b3e4104bcb99 --- /dev/null +++ b/tests/scps/tango-master/data/test_audiocaps_subset.json @@ -0,0 +1,886 @@ +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/7fmOlUlwoNg_20.wav", "captions": "A machine is making clicking sound as people talk in the background"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/6BJ455B1aAs_0.wav", "captions": "A missile launching followed by an explosion and metal screeching as a motor hums in the background."} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/GOD8Bt5LfDE_100.wav", "captions": "A toy train running as a young boy talks followed by plastic clanking then a child laughing"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/YQSuFyFm3Lc_230.wav", "captions": "Clattering of a train is ongoing, a railroad crossing bell rings, and a train horn blows"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/VjSEIRnLAh8_30.wav", "captions": "Food sizzling with some knocking and banging followed by a woman speaking"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/DlWd7Wmdi1E_150.wav", "captions": "A man talks while several animals make noises in the background"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/YNDKuNINDOY_30.wav", "captions": "An emergency siren ringing with car horn honking"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/fsBR7e_X_0Y_40.wav", "captions": "An infant yelling as a young boy talks while a hard surface is slapped several times"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/tjCNwdOUiGc_120.wav", "captions": "A bus engine running followed by a bus horn honking"} +{"dataset": 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bell dings in the background"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/PLHXGDnig4M_3.wav", "captions": "A man talking then meowing and hissing"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/Z0IrCa4MvOA_30.wav", "captions": "Water flowing through pipes"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/14ekd4nkpwc_28.wav", "captions": "An infant crying followed by a man laughing"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/yfYNPWs7mWY_380.wav", "captions": "A man speaking, followed by a door shutting, and then the man speaks some more"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/uhSDBwVrEdo_40.wav", "captions": "The wind is blowing, and a person is whistling a tune"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/YQGW5AwDOIo_560.wav", "captions": "Motor vehicles are driving with loud engines and a person whistles"} +{"dataset": "audiocaps", "location": 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"location": "/data/deep/audioset/data/1BdG6EzzhU4_50.wav", "captions": "An engine is idling"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/gBk0XiakZCg_30.wav", "captions": "Vibrations from a powerful car speeding by"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/gBj-aAmtt7k_50.wav", "captions": "Wind noise with water splashing sounds"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/si53bsSt7Rg_30.wav", "captions": "Some ducks quack"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/gBwPYA6D3_w_30.wav", "captions": "Heavy rain is coming down and at the same time men are shouting and laughing"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/pOaclT-gd8w_60.wav", "captions": "Someone sneezes followed by several laughs"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/iyrUVxNIYAM_40.wav", "captions": "Running vehicle blowing horn"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c9MqxAvkl4_30.wav", "captions": "A man is giving a speech into a microphone that is reverberating very much"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c8fGnShaZU_10.wav", "captions": "Engine chugging and faint speech and screeching"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/HBpSv5n3K90_10.wav", "captions": "An insect buzzing at a high pitch tone continuously"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c39I7g7vRI_30.wav", "captions": "An engine is idling"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c1p0nIf4D4_30.wav", "captions": "Crickets followed by a thunder clap"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c0fG9oJ-Qg_9.wav", "captions": "A horse galloping, a person speaks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c07yPHJKzc_0.wav", "captions": "Birds are peeping, quiet thumping is occurring, and an adult female speaks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c7qCb2aWYk_120.wav", "captions": "A woman is verbalizing something then sudden a machine starts operating"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c6wlqc-or4_170.wav", "captions": "A man speaks and a power tool is in use"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/4c4B-5YpkVc_370.wav", "captions": "A helicopter is hovering very low overhead"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/uwhUwn1fiYI_560.wav", "captions": "Child speech and a man and woman talks as paper crinkles in the background"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/1Fa2f4QDkIU_10.wav", "captions": "Man speaking, engine running"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/1Fc9WqEgTe4_30.wav", "captions": "A siren on a fire engine sounds off then the horn blows"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/Vadax-Lm-Ss_0.wav", "captions": "While people talk and brief thwacking occurs in the background, an animal bleats twice and an adult male speaks in the foreground"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/1FX1FyCxoCY_30.wav", "captions": "A rushing sound is present, an adult female speaks, and several people cheer"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/1FXn-rdaq7k_30.wav", "captions": "Person trying to start a car"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/1FXr5AhqxFs_510.wav", "captions": "Man talking with drill sound after"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/1FOLZG2yNqA_80.wav", "captions": "Rain with a siren in the distance"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/1FRb6_4AKBQ_30.wav", "captions": "A dog is whimpering"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/1FTRYZDvjWU_90.wav", "captions": "A machine is hissing"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/pOMFhtRo_gU_30.wav", "captions": "Background whirring punctuated with swipe and thunderclap"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/pONs-WiLqjk_50.wav", "captions": "A person laughs with some banging and rattling"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/HW7zqURSqdo_200.wav", "captions": "People talk and laugh loudly nearby"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/pOXQNWFHJYU_150.wav", "captions": "A man speaking with light rainfall and a different man speaking in the distance"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/HC-utKUX3a4_50.wav", "captions": "Humming with a distant train horn blowing"} diff --git a/tests/scps/tango-master/data/train_soundbible.json b/tests/scps/tango-master/data/train_soundbible.json new file mode 100644 index 0000000000000000000000000000000000000000..f82e05b39043a6fd8982825ed8a696e22e355551 --- /dev/null +++ b/tests/scps/tango-master/data/train_soundbible.json @@ -0,0 +1,1232 @@ +{"title": "Spacecraft Hatch Opening", "description": "Sound of a spacecraft hatch opening. Great pressurized hatch release of air pressure and then metal lid creaking open. Almost a bit spooky. Sound requested by brooke for her class. thanks for the request.", "author": "Mike Koenig", "href": "1285-Spacecraft-Hatch-Opening.html", "caption": "A spacecraft hatch is opening.", "id": "1285", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1285&type=wav"} +{"title": "Inflating Balloon", "description": "Sound of someone inflating balloon at a party or something. Could also be used for blowing a bubble.", "author": "NFour", "href": "1410-Inflating-Balloon.html", "caption": "Someone is inflating a balloon.", "id": "1410", "duration": 2.56621875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1410&type=wav"} +{"title": "Tornado Siren II", "description": "This is another tornado siren that was recorded and then moded by SoundBible.com its your typical early warning alert system for tornados sounds like air raid siren. The preview above is just 40 seconds but the zip file is 15 minutes long, and the wav file is 5 minutes (50 MB) .Download the mp3 push play turn up the speakers and walk out of the room and see what happens :)", "author": "Delilah", "href": "1937-Tornado-Siren-II.html", "caption": "A tornado siren is sounding.", "id": "1937", "duration": 309.0111875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1937&type=wav"} +{"title": "Flush Toilet 2", "description": "Nice clean and clear recording of the toilet bowl being flushed up close.", "author": "Mike Koenig", "href": "2114-Flush-Toilet--2.html", "caption": "A toilet is being flushed.", "id": "2114", "duration": 14.5153125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2114&type=wav"} +{"title": "Bluejay Call", "description": "Sound of a BlueJay call 4x in a row. Recorded in a small pine grove near my house. Great bird sound effect for nature lovers.", "author": "Mike Koenig", "href": "1842-Bluejay-Call.html", "caption": "A bird call is repeated several times in a small pine grove.", "id": "1842", "duration": 4.93371875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1842&type=wav"} +{"title": "Dog Growl", "description": "Best dog growl sound effect ive recorded so far. Great grrrrrrowl or growling sound. can be used for wolf or dog.", "author": "Mike Koenig", "href": "1291-Dog-Growl.html", "caption": "A dog is growling.", "id": "1291", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1291&type=wav"} +{"title": "Moose Call", "description": "Female moose call recorded by the fish and Wildlife Service in Minnesota. Wildlife recordings like this from the government are automatically in the public domain.", "author": "fws.gov", "href": "1225-Moose-Call.html", "caption": "A moose is making a call.", "id": "1225", "duration": 12.9175625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1225&type=wav"} +{"title": "Monster Laugh", "description": "The sound of a monster laughing. Great for a zombie, halloween, or even mummy sound effect.", "author": "Mike Koenig", "href": "1049-Monster-Laugh.html", "caption": "A monster is laughing.", "id": "1049", "duration": 3.5603125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1049&type=wav"} +{"title": "Triangle Dinner Bell", "description": "Cowboy Triangle dinner bell sound effect. Its chow time and they are ringing the dinner bell! Requested by Jim Scully.", "author": "CowBoyTyrone", "href": "1525-Triangle-Dinner-Bell.html", "caption": "A dinner bell is ringing.", "id": "1525", "duration": 4.7915625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1525&type=wav"} +{"title": "Gutting Someone", "description": "The sound of someone or something being gutted. Hara-kiri sound effect of someone being disemboweled.", "author": "NPS", "href": "945-Gutting-Someone.html", "caption": "Someone or something is being gutted.", "id": "945", "duration": 4.3073125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=945&type=wav"} +{"title": "Raccoon", "description": "Raccoon chattering 3x in a row. Great for nature shows or something that requires a Raccoon talking or making noises.", "author": "J Dawg", "href": "1853-Raccoon.html", "caption": "A raccoon is chattering.", "id": "1853", "duration": 5.5549375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1853&type=wav"} +{"title": "Tank", "description": "Very large and loud tank driving and idling sound. Sound effect requested by Nicholas.", "author": "snottyboy", "href": "1325-Tank.html", "caption": "A tank is driving and idling.", "id": "1325", "duration": 6.016875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1325&type=wav"} +{"title": "Water Drop", "description": "Perfectly clear water drop sound effect. Great for a leaky sink, a bathtub, shower, sprinkler or any number of liquid dripping sound effects. If you like this one be sure to search for water drop using the search menu it will show you the other 2 sound effects just like this.", "author": "Mike Koenig", "href": "1126-Water-Drop.html", "caption": "A water drop is falling.", "id": "1126", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1126&type=wav"} +{"title": "Sigh", "description": "Sigh sound from someone complaining about something. Great human sounds.", "author": "Mike Koenig", "href": "773-Sigh.html", "caption": "Someone is sighing.", "id": "773", "duration": 3.10209375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=773&type=wav"} +{"title": "Doberman Pinscher", "description": "Large dog barking and growling. Huge doberman pincher recording barking just for you to troll you dog with. Created this breed around 1890 by Karl Friedrich Louis Dobermann.", "author": "Daniel Simion", "href": "2194-Doberman-Pinscher.html", "caption": "A dog is barking and growling.", "id": "2194", "duration": 14.1943125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2194&type=wav"} +{"title": "Van Sliding Door", "description": "Van door sliding close after loading or picking up kids. Sliding door on a van could be used for a closing door.", "author": "Daniel Simion", "href": "2212-Van-Sliding-Door.html", "caption": "A door is closing.", "id": "2212", "duration": 1.7129375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2212&type=wav"} +{"title": "Skateboard Ollie", "description": "Skateboarding sound effect of an Ollie. Great skater sound effects for a game like tony hawk, or skateboarding game. Skateboard and ollie requested by Dimitris.", "author": "Mike Koenig", "href": "1052-Skateboard-Ollie.html", "caption": "A skateboarder is performing an ollie.", "id": "1052", "duration": 1.7823125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1052&type=wav"} +{"title": "Zombie Stabbed", "description": "Sound of a zombie being stabbed or hit with a bat, or even combine with a gunshot for a zombie being shot. Zombie sounds requested by jordangiese.", "author": "Mike Koenig", "href": "1038-Zombie-Stabbed.html", "caption": "A zombie is being attacked.", "id": "1038", "duration": 3.89078125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1038&type=wav"} +{"title": "Blood Splattering On Wall", "description": "A great blood splattering on wall sound effect for gory movie scene or video game! Great for Halloween too!", "author": "Mike Koenig", "href": "829-Blood-Splattering-On-Wall.html", "caption": "Blood is splattering on a wall.", "id": "829", "duration": 1.08484375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=829&type=wav"} +{"title": "Hermit Thrush", "description": "Bird song of the Hermit Thrush. The Hermit Thrush is the state bird of Virginia, and has often been attributed to poetry.", "author": "nps", "href": "923-Hermit-Thrush.html", "caption": "A Hermit Thrush is singing.", "id": "923", "duration": 7.0828125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=923&type=wav"} +{"title": "Pill Bottle", "description": "Getting pills out of a bottle like the sound someone makes when they are getting out an Advil or something. Could be used for a game or movie or whatever.", "author": "Mike Koenig", "href": "1934-Pill-Bottle.html", "caption": "Pills are being dispensed from a bottle.", "id": "1934", "duration": 5.79440625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1934&type=wav"} +{"title": "Sheep", "description": "The sound of a sheep call. This is great for a farm, or for a sleepy commercial or scene. Counting sheep. Thanks Caroline for this sound.", "author": "Mike Koenig", "href": "1012-Sheep.html", "caption": "A sheep is calling.", "id": "1012", "duration": 1.13778125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1012&type=wav"} +{"title": "Fish Splashing", "description": "Fish splashing in water sound effect. Great for a nature or other scene.", "author": "Mike Koenig", "href": "546-Fish-Splashing.html", "caption": "Fish are splashing in water.", "id": "546", "duration": 2.97184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=546&type=wav"} +{"title": "Unscrew Bulb", "description": "Sound of an old school lightbulb being removed. Recording so clear you can hear the fillament shaking.", "author": "Mike Koenig", "href": "2117-Unscrew-Bulb.html", "caption": "An old lightbulb is being removed.", "id": "2117", "duration": 3.00409375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2117&type=wav"} +{"title": "Large Truck Chains", "description": "Huge truck chains used for pulling, towing, and logging. Could also be the sound of chains on a tire in the snow.", "author": "Mike Koenig", "href": "1095-Large-Truck-Chains.html", "caption": "Chains are being used for pulling, towing, and logging.", "id": "1095", "duration": 8.17209375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1095&type=wav"} +{"title": "Car Alarm", "description": "Car Alarm from City Streets. Alarm has short tweets from PDSounds.org RIP", "author": "Mike Koenig", "href": "96-Car-Alarm.html", "caption": "A car alarm is sounding.", "id": "96", "duration": 2.16815625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=96&type=wav"} +{"title": "Peeper Frogs Near Lake", "description": "Small little peeper frogs sounds near at a reservoir recorded by fws.gov", "author": "fws.gov", "href": "249-Peeper-Frogs-Near-Lake.html", "caption": "Little peeper frogs are making sounds near a reservoir.", "id": "249", "duration": 32.017, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=249&type=wav"} +{"title": "Dun Dun Dun", "description": "That super dramatic dun dun dun sound effect right before something major happens or when the plot is revealed. Requested by Tal thanks for the request.", "author": "Delsym", "href": "1623-Dun-Dun-Dun.html", "caption": "A dramatic sound effect is played.", "id": "1623", "duration": 2.3611875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1623&type=wav"} +{"title": "Hen Chicken", "description": "A great animal sound effect recorded by Caroline Ford. Thank for helping us out with the animal sound effects", "author": "Caroline Ford", "href": "1022-Hen-Chicken.html", "caption": "An animal is making a sound.", "id": "1022", "duration": 1.45125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1022&type=wav"} +{"title": "Hoot Owl", "description": "The sound a hoot owl makes when he hoots. 2 consecutive hoots from our friend the owl.", "author": "Mike Koenig", "href": "799-Hoot-Owl.html", "caption": "An owl hoots twice.", "id": "799", "duration": 2.25390625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=799&type=wav"} +{"title": "Record Player Static", "description": "Nice and clean record player static sound fx that can be used for whatever you want to use it for. Very staticy record player sound.", "author": "Mike Koenig", "href": "1674-Record-Player-Static.html", "caption": "A record player is making static noise.", "id": "1674", "duration": 14.37440625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1674&type=wav"} +{"title": "Growl", "description": "The ultimate animal growling evil sound effect. Pushed the bass up on this to make it even scarier! Great for Halloween or horror movies!", "author": "Mike Koenig", "href": "891-Growl.html", "caption": "An animal is growling.", "id": "891", "duration": 10.28646875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=891&type=wav"} +{"title": "Meadowlark", "description": "Field recording of a meadowlark song. The Meadowlark is a bird that feeds mostly on insects, and is a grassland bird belonging to the genus Sturnella", "author": "Daniel Simion", "href": "2180-Meadowlark.html", "caption": "A bird is singing.", "id": "2180", "duration": 40.64396875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2180&type=wav"} +{"title": "Rainforest Ambience", "description": "Rainforest ambience with birds and crickets sound", "author": "GlorySunz", "href": "1818-Rainforest-Ambience.html", "caption": "Birds and crickets are making sounds in a rainforest.", "id": "1818", "duration": 61.33546875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1818&type=wav"} +{"title": "Truck Air Brakes", "description": "The sound of a Trucks Air Brakes being released. Great city or traffic sound effects.", "author": "Mike Koenig", "href": "1056-Truck-Air-Brakes.html", "caption": "Air brakes are releasing.", "id": "1056", "duration": 4.476375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1056&type=wav"} +{"title": "Bear Growl And Roar", "description": "Bear growls and roars to protect its cubs", "author": "Mike Koenig", "href": "241-Bear-Growl-And-Roar.html", "caption": "A bear is growling and roaring to protect its cubs.", "id": "241", "duration": 15.529, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=241&type=wav"} +{"title": "Metal Reflect", "description": "Metal reflecting sound effect. great for simple metal ting or clank.", "author": "Mike Koenig", "href": "1273-Metal-Reflect.html", "caption": "Metal is clanking.", "id": "1273", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1273&type=wav"} +{"title": "Missile Alert", "description": "Bomb siren or missile alert. Sound issued prior to an incoming bomb or missile.", "author": "BOMB SIREN", "href": "2056-Missile-Alert.html", "caption": "A bomb siren is sounding.", "id": "2056", "duration": 21.04346875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2056&type=wav"} +{"title": "M1 Garand Single", "description": "M1 Garand Single Shot gunfire sound effect. M1 Garrand is a 30 caliber rifle, and often called Greatest Battle Implement Ever Devised. It was the first semi-automatic rifle used by the military. Sound effect requested by William Andrews. Thanks William.", "author": "battlestar10", "href": "1547-M1-Garand-Single.html", "caption": "A gun is firing.", "id": "1547", "duration": 1.567375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1547&type=wav"} +{"title": "Godzilla Walking", "description": "Godzilla walking sound effect could also be used for giant walking ogre walking or king kong walking", "author": "Marc", "href": "1721-Godzilla-Walking.html", "caption": "Something is walking heavily.", "id": "1721", "duration": 13.00446875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1721&type=wav"} +{"title": "Electrical Sweep", "description": "An electrical sweep sort of sounds like a xylophone. Nice magical or dreamy sound effect.", "author": "Sweeper", "href": "1795-Electrical-Sweep.html", "caption": "A magical or dreamy sound resembling an electrical sweep or xylophone.", "id": "1795", "duration": 5.49984375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1795&type=wav"} +{"title": "Laughter", "description": "A male vocal actor was hired to vocalize laughing or laughter for funny sounds. This is top quality audio and totally free original audio for SoundBible be sure to share and spread the word.", "author": "Mike Koenig", "href": "2010-Laughter.html", "caption": "Someone is laughing.", "id": "2010", "duration": 25.711125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2010&type=wav"} +{"title": "Baby Just Born", "description": "A just born or newborn baby cries for hs first time. Newborn crying..", "author": "Daniel Simon", "href": "2130-Baby-Just-Born.html", "caption": "A newborn baby is crying.", "id": "2130", "duration": 21.41775, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2130&type=wav"} +{"title": "Game Show Wheel Spin", "description": "Game show wheel spinning sound effect from a show like wheel of fortune or the price is right. Good sound all in all.", "author": "Mike Koenig", "href": "673-Game-Show-Wheel-Spin.html", "caption": "A game show wheel is spinning.", "id": "673", "duration": 5.25471875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=673&type=wav"} +{"title": "Kids Laughing", "description": "The sound of kids laughing. If you want more kids you can download audacity from the right side of the page and layer the sound 2, 3, or 4 times. This sound was requested by tami.", "author": "Mike Koenig", "href": "939-Kids-Laughing.html", "caption": "Kids are laughing.", "id": "939", "duration": 20.01321875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=939&type=wav"} +{"title": "Baby Boy Laugh", "description": "My son Noah when he was 3 laughing 4 times in succession he is very funny. I say when he was three but at the time of this upload he is 3 so this is just for future references.", "author": "Mike Koenig", "href": "1824-Baby-Boy-Laugh.html", "caption": "Someone is laughing.", "id": "1824", "duration": 4.3576875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1824&type=wav"} +{"title": "Groan", "description": "Groaning or in pain sound. Groan sounds used for pain or suffering or just to emphasize movement.", "author": "Mike Koenig", "href": "831-Groan.html", "caption": "Someone is groaning in pain.", "id": "831", "duration": 2.7071875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=831&type=wav"} +{"title": "Plop", "description": "3 plop or cork pop like sounds with 1 second of silence in between each. Sound of something being ejected from a tight spot, like if someone had their head stuck and then it was pulled out.", "author": "Sabine Eismayer", "href": "2018-Plop.html", "caption": "Something is being ejected from a tight spot.", "id": "2018", "duration": 3.445, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2018&type=wav"} +{"title": "Machine Gun Fire Distance", "description": "Sound of Machine Gun Fire in the Distance. This would be great for a battlefield or war zone sound effect.", "author": "JKirsch", "href": "1383-Machine-Gun-Fire-Distance.html", "caption": "Machine gun fire can be heard in the distance.", "id": "1383", "duration": 2.25234375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1383&type=wav"} +{"title": "Drill", "description": "Simple drill in a workshop. It was a craftsman drill i recorded. Great for whatever.", "author": "Mike Koenig", "href": "1074-Drill.html", "caption": "A craftsman drill is being used in a workshop.", "id": "1074", "duration": 4.72528125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1074&type=wav"} +{"title": "Crickets Chirping At Night", "description": "Relaxing sound of crickets chirping in the night. Thanks to Lisa Redfern for the sounds.", "author": "Lisa Redfern", "href": "2083-Crickets-Chirping-At-Night.html", "caption": "Crickets are chirping.", "id": "2083", "duration": 49.2930625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2083&type=wav"} +{"title": "Broom Sweeping", "description": "Clean and crisp sound of a broom sweeping the floor. Long sound effect at 34 sec. Was a request.", "author": "Mike Koenig", "href": "2104-Broom-Sweeping.html", "caption": "A broom is sweeping the floor.", "id": "2104", "duration": 34.2948125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2104&type=wav"} +{"title": "Babbling Brook", "description": "Sound of a calm and serene babbling brook. Recording of a rivulet of flowing water that joins a river.", "author": "stephan", "href": "1776-Babbling-Brook.html", "caption": "A brook is babbling.", "id": "1776", "duration": 10.9975625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1776&type=wav"} +{"title": "Mummy Zombie", "description": "A super monster. A breed of mummy zombie werewolf. OK. maybe not but its a cool evil monster sound.", "author": "Mike Koenig", "href": "1059-Mummy-Zombie.html", "caption": "A monster is growling.", "id": "1059", "duration": 2.00825, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1059&type=wav"} +{"title": "Applause", "description": "A great 5 second applause or canned laughter and crowd responses. This sound was cut from a public domain speech and converted to stereo, and then mastered for best quality.", "author": "Mike Koenig", "href": "988-Applause.html", "caption": "Applause or canned laughter and crowd responses.", "id": "988", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=988&type=wav"} +{"title": "Shotgun Reload Spas 12", "description": "This is an awesome and excellent quality reloaded of an spas 12 shotgun", "author": "RA The Sun God", "href": "1961-Shotgun-Reload-Spas-12.html", "caption": "A shotgun is being reloaded.", "id": "1961", "duration": 1.12740625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1961&type=wav"} +{"title": "Flock Seagulls", "description": "Field recording of a flock of seagulls also known as gulls, laughing gulls, or common gulls. Recording goes on for over 1 minute!", "author": "Daniel Simion", "href": "2193-Flock-Seagulls.html", "caption": "Seagulls are making noise.", "id": "2193", "duration": 61.588625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2193&type=wav"} +{"title": "Evil Laugh 2", "description": "A malicious laugh for the sneakier type.", "author": "Sound Explorer", "href": "1981-Evil-Laugh-2.html", "caption": "Someone is maliciously laughing.", "id": "1981", "duration": 2.68628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1981&type=wav"} +{"title": "Transfer Truck Idle And Drive", "description": "Pulled up to another transfer truck at a stop light and recorded it idling a little bit. The truck then drove off. great city sounds.", "author": "Stephan", "href": "704-Transfer-Truck-Idle-And-Drive.html", "caption": "A truck is idling in the city.", "id": "704", "duration": 17.2753125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=704&type=wav"} +{"title": "School Fire Alarm", "description": "Recorded during a school Fire Drill. Sound level seems to change around halfway through as though the person that was recording had moved the device closer to the alarm. Many thanks to Cullen Card for this sound.", "author": "Cullen Card", "href": "2022-School-Fire-Alarm.html", "caption": "A fire alarm is going off.", "id": "2022", "duration": 27.7300625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2022&type=wav"} +{"title": "Please Turn Off The Air", "description": "Please turn off the air a sound requested by Rhey to be used for his office.", "author": "Mike Koenig", "href": "658-Please-Turn-Off-The-Air.html", "caption": "Air is turning off.", "id": "658", "duration": 3.54709375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=658&type=wav"} +{"title": "That Mommies", "description": "My son saying that mommies. Really cute bit of sound for me to look back on in the future.", "author": "Mike Koenig", "href": "1281-That-Mommies.html", "caption": "Someone says \"that mommies\".", "id": "1281", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1281&type=wav"} +{"title": "Fireplace", "description": "Real nice fireplace sounds from a fire burning. Very small crackles and sizzle burn sound effects along with air movement.", "author": "ezwa", "href": "1543-Fireplace.html", "caption": "A fire is crackling.", "id": "1543", "duration": 25.49553125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1543&type=wav"} +{"title": "Scratching", "description": "Scratching on sandpaper sound of abrasive material being scraped on another hard surface over and over. Big thanks to Lisa Redfern for these high quality scratching sounds.", "author": "Lisa Redfern", "href": "2029-Scratching.html", "caption": "Abrasive material is being scraped on a hard surface.", "id": "2029", "duration": 16.758625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2029&type=wav"} +{"title": "Fast Bike Or Motorcycle", "description": "Great fast bike or motorcycle sound effect. This was one of those kawasaki motorcycles not a Hog or Goldwing.", "author": "Mike Koenig", "href": "615-Fast-Bike-Or-Motorcycle.html", "caption": "A bike or motorcycle is making a fast sound.", "id": "615", "duration": 3.018625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=615&type=wav"} +{"title": "Buzz Fade Out", "description": "Great clean buzz fading out sound generated by tone repetition.", "author": "Mike Koenig", "href": "1198-Buzz-Fade-Out.html", "caption": "Clean buzz fading out from tone repetition.", "id": "1198", "duration": 2.06621875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1198&type=wav"} +{"title": "Guillotine", "description": "Sound of a ninja swinging a samurai sword and cutting a limb or head off. Sound requested by Ben Carter.", "author": "Mike Koenig", "href": "1532-Guillotine.html", "caption": "A ninja is swinging a sword.", "id": "1532", "duration": 1.426625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1532&type=wav"} +{"title": "Trash Truck Reverse Beep", "description": "Sound of a Trash Truck Backing Up and beeping. Recorded outside my office during a lunch break.", "author": "Mike Koenig", "href": "1050-Trash-Truck-Reverse-Beep.html", "caption": "A trash truck is beeping.", "id": "1050", "duration": 9.7175625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1050&type=wav"} +{"title": "Machine Gun Firing", "description": "Sound of a machine gun firing at a firing range. Great for battle or war. Requested by joeballs1025.", "author": "Mike Koenig", "href": "453-Machine-Gun-Firing.html", "caption": "A machine gun is firing.", "id": "453", "duration": 4.651125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=453&type=wav"} +{"title": "Lock And Load", "description": "Lock and Load is the sound of a large machine gun clip being popped in. Lock and load", "author": "Mike Koenig", "href": "1069-Lock-And-Load.html", "caption": "A large machine gun clip is being loaded.", "id": "1069", "duration": 1.09134375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1069&type=wav"} +{"title": "Strange Static", "description": "Some static that was changed to make it sound like an alien.", "author": "KP", "href": "1564-Strange-Static.html", "caption": "Static is playing.", "id": "1564", "duration": 11.705, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1564&type=wav"} +{"title": "Glock 17 9mm", "description": "Nice glock 17 9mm being fire 13 times in rapid succession. Great for war or battle scene.", "author": "JKirsch", "href": "1389-Glock-17-9mm.html", "caption": "A gun is firing multiple times.", "id": "1389", "duration": 3.32046875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1389&type=wav"} +{"title": "Lawn Mower Fart", "description": "A funny sounding fart that sounds like a lawn mower. Beans beans good for your heart.", "author": "Mike Koenig", "href": "702-Lawn-Mower-Fart.html", "caption": "Someone is farting.", "id": "702", "duration": 1.4048125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=702&type=wav"} +{"title": "Stab", "description": "Butchers knife stabbing someone from behind sound. A great stab sound really. Great for Halloween, haunted houses, and even Christmas! OK.. skip Christmas with this one.", "author": "Caroline Ford", "href": "944-Stab.html", "caption": "A butcher's knife is stabbing someone from behind.", "id": "944", "duration": 2.0235, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=944&type=wav"} +{"title": "Clearing Throat Male", "description": "The sound of a male clearing his throat", "author": "Mike Koenig", "href": "782-Clearing-Throat-Male.html", "caption": "A male is clearing his throat.", "id": "782", "duration": 1.10878125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=782&type=wav"} +{"title": "Underwater", "description": "A great underwater sound effect. It is actually the sound of a Gulf ToadFish a rare fish that resembles a toad. Either way this sample is a great example of underwater acoustics.", "author": "Caroline Ford", "href": "908-Underwater.html", "caption": "An underwater sound of a Gulf Toadfish.", "id": "908", "duration": 2.346375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=908&type=wav"} +{"title": "Dragon Fire Breath and Roar", "description": "European Dragon Roaring and then Breathing Fire out of his mouth and burning everything around him.", "author": "Daniel Simon", "href": "2127-Dragon-Fire-Breath-and-Roar.html", "caption": "A dragon is roaring and breathing fire.", "id": "2127", "duration": 5.37465625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2127&type=wav"} +{"title": "Baby Snoring", "description": "A little baby snoring loudly. Even babies snore sometimes. If you are looking for medical advice look elsewhere this is a sound website :)", "author": "Daniel Simon", "href": "2138-Baby-Snoring.html", "caption": "A baby is snoring loudly.", "id": "2138", "duration": 29.379625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2138&type=wav"} +{"title": "Baby Gibberish", "description": "My Little baby son speaking gibberish in a restaurant called Big Als in Manteo NC", "author": "Mike Koenig", "href": "545-Baby-Gibberish.html", "caption": "A baby is speaking gibberish.", "id": "545", "duration": 8.68428125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=545&type=wav"} +{"title": "Balloon Squeaky", "description": "Sound of a balloon being squeaky. Great plastic stretching sound effect.", "author": "Mike Koenig", "href": "1111-Balloon-Squeaky.html", "caption": "A balloon is being squeaked.", "id": "1111", "duration": 1.43953125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1111&type=wav"} +{"title": "Take Picture", "description": "Sound of a camera taking a photo graph with flash included.", "author": "Ellie", "href": "1820-Take-Picture.html", "caption": "A camera is taking a photo with flash.", "id": "1820", "duration": 1.35715625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1820&type=wav"} +{"title": "Anhinga Bird", "description": "The sound of anhinga birds. This bird is also called Snakebird, Darter, American Darter, Water Turkey. This sound was requested by Anne Obrien", "author": "tamskp", "href": "864-Anhinga-Bird.html", "caption": "Anhinga birds are vocalizing.", "id": "864", "duration": 10.17865625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=864&type=wav"} +{"title": "Bluejay Call 2", "description": "This another BlueJay call apprently they do more than one same bird slightly modified bird call different location as well.", "author": "Mike Koenig", "href": "1843-Bluejay-Call-2.html", "caption": "A bird is making a slightly modified call.", "id": "1843", "duration": 7.92365625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1843&type=wav"} +{"title": "Baby Says Daddy", "description": "My little son saying Daddy Daddy. Looking for a cute kid saying Dad? Here it is. :)", "author": "Mike Koenig", "href": "467-Baby-Says-Daddy.html", "caption": "Someone is saying \"Daddy Daddy\".", "id": "467", "duration": 4.38653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=467&type=wav"} +{"title": "Barrel Exploding", "description": "An exploding barrel sound effect great for a war or battle scene. Everyone needs an exploding barrel sound now and then right? :)", "author": "Mike Koenig", "href": "576-Barrel-Exploding.html", "caption": "A barrel is exploding.", "id": "576", "duration": 6.37521875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=576&type=wav"} +{"title": "Hold Me Daddy", "description": "My son saying hold me daddy. Really cute bit of sound for me to look back on in the future.", "author": "Mike Koenig", "href": "1310-Hold-Me-Daddy.html", "caption": "Someone's child is saying \"hold me daddy.\".", "id": "1310", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1310&type=wav"} +{"title": "American Robin", "description": "The amrican robin is a common bird to the united states, and while the robin does live elsewhere there are small variations that make this bird unique.", "author": "nps.gov", "href": "903-American-Robin.html", "caption": "A bird is singing.", "id": "903", "duration": 3.46646875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=903&type=wav"} +{"title": "Fast Forward", "description": "A great sound of a camcorder or tape fast forwarding. Could be used for time travel, a fast forward scene.", "author": "Mike Koenig", "href": "624-Fast-Forward.html", "caption": "Camcorder or tape is fast forwarding.", "id": "624", "duration": 6.00009375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=624&type=wav"} +{"title": "Beach Waves", "description": "Great high resolution sounds of beach waves recorded from our trip to the beach", "author": "Mike Koenig", "href": "338-Beach-Waves.html", "caption": "Waves are crashing on a beach.", "id": "338", "duration": 22.847125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=338&type=wav"} +{"title": "Bull Frog", "description": "The sound of a large bull frog. Great nature and amphibian sound effect. Swamps and similar.", "author": "Mike Koenig", "href": "972-Bull-Frog.html", "caption": "A bullfrog is croaking.", "id": "972", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=972&type=wav"} +{"title": "Funny Boy Laugh", "description": "My son Noah again doing a few funny laughs. Hes a nut but a good kid. He sounds like he is pretending to be a baby. He does that because we think it is cute I imagine.", "author": "Mike Koenig", "href": "1825-Funny-Boy-Laugh.html", "caption": "Someone is laughing like a baby.", "id": "1825", "duration": 2.59128125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1825&type=wav"} +{"title": "Spooky Chains", "description": "Great spooky ghost chains. Great for a haunting, or haunted house sound effect. Very scary and great for Halloween that is just around the corner! Scare someone today! Ghost shackles!", "author": "Mike Koenig", "href": "1094-Spooky-Chains.html", "caption": "Ghost chains are rattling and clanking.", "id": "1094", "duration": 13.89, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1094&type=wav"} +{"title": "TV Off Air", "description": "The sound a tv station makes when it goes offline, or goes off the air.", "author": "Mike Koenig", "href": "1021-TV-Off-Air.html", "caption": "A TV station is going offline.", "id": "1021", "duration": 12.53, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1021&type=wav"} +{"title": "Old Sub Sonar", "description": "Old sub sonar in stereo. Great uboat, or wwii submarine sound effect. Sound effect recorded from pd wwii film, then mastered and put into stereo. Thanks to Mark Pancino for the request.", "author": "Mike Koenig", "href": "1185-Old-Sub-Sonar.html", "caption": "Old sub sonar pinging in stereo.", "id": "1185", "duration": 11.8421875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1185&type=wav"} +{"title": "Torpedo Impact", "description": "Torpedo impact sound effect. This sound is great for a subsurface explosion in water. Like a depth charge or torpedo impact sound.", "author": "Mike Koenig", "href": "1637-Torpedo-Impact.html", "caption": "There is an impact in water.", "id": "1637", "duration": 1.13246875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1637&type=wav"} +{"title": "Small Herd Cattle", "description": "3 or 4 cows a mooing. These heifers are from a farm down in Arizona. They are beef cattle. Great sound effect for a small herd of cattle.", "author": "BuffBill84", "href": "1568-Small-Herd-Cattle.html", "caption": "Cows are mooing.", "id": "1568", "duration": 3.80671875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1568&type=wav"} +{"title": "Buzz", "description": "An electronic buzzing noise", "author": "KP", "href": "1581-Buzz.html", "caption": "An electronic buzzing noise is heard.", "id": "1581", "duration": 7.43290625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1581&type=wav"} +{"title": "Mossberg 500 Pump Shotgun", "description": "Great mossberg 500 or 590 pump shotgun fire and pump sound effect. Great for movie or video game.", "author": "RA The Sun God", "href": "2095-Mossberg-500-Pump-Shotgun.html", "caption": "A shotgun is fired and pumped.", "id": "2095", "duration": 1.21034375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2095&type=wav"} +{"title": "Alder Flycatcher", "description": "The Alder Flycatcher is a small birg that lives in thickets. Very much like the Willow Flycatcher.", "author": "nps.gov", "href": "896-Alder-Flycatcher.html", "caption": "An Alder Flycatcher bird is singing.", "id": "896", "duration": 4.5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=896&type=wav"} +{"title": "Shot Gun", "description": "10 guage shot gun sound.nice clean shotgun blast sound effect for those in need of gun sound effects", "author": "luminalace", "href": "1706-Shot-Gun.html", "caption": "A shotgun is firing.", "id": "1706", "duration": 2.0898125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1706&type=wav"} +{"title": "Sqeaking Door 2", "description": "An even larger an more spine chilling suqeaking or creaking door. Sound modified version of Sarasprellas squeaking door sound. Thanks Sarasprella!", "author": "Sarasprella", "href": "1871-Sqeaking-Door-2.html", "caption": "A door is creaking.", "id": "1871", "duration": 14.8493125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1871&type=wav"} +{"title": "Kid Laugh Long", "description": "Me tickling my son and making him laugh for about a minute 30 seconds. If this doesnt make you crack a smile something is wrong with you.", "author": "Mike Koenig", "href": "2007-Kid-Laugh-Long.html", "caption": "Someone is tickling a child and making them laugh.", "id": "2007", "duration": 90.01940625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2007&type=wav"} +{"title": "Car Drive Away", "description": "Car revving engine and tires slipping as car speeds away.", "author": "Daniel Simion", "href": "2166-Car-Drive-Away.html", "caption": "A car is revving its engine and tires are slipping.", "id": "2166", "duration": 7.356375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2166&type=wav"} +{"title": "Driving Ambiance", "description": "Decent driving ambiance sound effect recorded from inside our family van. Great for city or a driving scene.", "author": "Mike Koenig", "href": "710-Driving-Ambiance.html", "caption": "A van is driving in the city.", "id": "710", "duration": 22.06909375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=710&type=wav"} +{"title": "Large Bubble", "description": "Sound of a large bubble breaking the surface of a lake, pond, or fish tank.", "author": "snottyboy", "href": "1345-Large-Bubble.html", "caption": "A bubble is popping.", "id": "1345", "duration": 1.1435, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1345&type=wav"} +{"title": "Bomb Explosion 1", "description": "Good bomb explosion sound with pulsing sound waves of energy", "author": "Mike Koenig", "href": "107-Bomb-Explosion-1.html", "caption": "An explosion is happening with pulsing sound waves of energy.", "id": "107", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=107&type=wav"} +{"title": "Large Angry Dog 2", "description": "A very large angry dog growling and snarling. Pretty evil. Number 2.", "author": "Mike Koenig", "href": "1504-Large-Angry-Dog-2.html", "caption": "A large dog is growling.", "id": "1504", "duration": 1.09040625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1504&type=wav"} +{"title": "Sewing Machine 2", "description": "Sound of an electric sewing machine running and sewing clothes or some other material together", "author": "Teto Yasha", "href": "1541-Sewing-Machine-2.html", "caption": "A sewing machine is running.", "id": "1541", "duration": 8.16246875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1541&type=wav"} +{"title": "Thunder Strike 3", "description": "3 of 3 thunder or lightning strikes that were recorded very clean and crisp during a very strong summer storm.", "author": "Mike Koenig", "href": "2012-Thunder-Strike-3.html", "caption": "Thunder is striking.", "id": "2012", "duration": 27.1209375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2012&type=wav"} +{"title": "Coin Drop", "description": "Various coins dropped on a table. Sounds like coins dropping into a machine. Thanks to Willem Hunt for the donation.", "author": "Willem Hunt", "href": "2081-Coin-Drop.html", "caption": "Coins are dropped on a table.", "id": "2081", "duration": 3.17978125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2081&type=wav"} +{"title": "Girl Pees In Toilet", "description": "A girl my wife to be exact peeing in the toilet", "author": "ezwa", "href": "167-Girl-Pees-In-Toilet.html", "caption": "Someone is peeing in a toilet.", "id": "167", "duration": 14.9491875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=167&type=wav"} +{"title": "Train Wheels Grinding", "description": "Train wheels grinding and clainging while a freight train passes. Some great metal on metal grinding and shreaking going on there.", "author": "Mike Koenig", "href": "1697-Train-Wheels-Grinding.html", "caption": "Train wheels are grinding and clanging.", "id": "1697", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1697&type=wav"} +{"title": "Thunder Sound FX", "description": "Amazing thunder sound lightning storm sound effects. Big thanks to Grant Evans for the sound.", "author": "Grant Evans", "href": "2053-Thunder-Sound-FX.html", "caption": "Thunder is heard during a lightning storm.", "id": "2053", "duration": 86.88909375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2053&type=wav"} +{"title": "Bear", "description": "Sound of a very large brown or grizzly bear roaring and growling in the wilderness. Great for camping or nature sounds.", "author": "Mike Koenig", "href": "1142-Bear.html", "caption": "A large brown or grizzly bear is roaring and growling.", "id": "1142", "duration": 4.10803125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1142&type=wav"} +{"title": "Suck Up", "description": "Sound of something being sucked up into a straw or intake of some sort. Could also be someone finishing a drink.", "author": "Mike Koenig", "href": "801-Suck-Up.html", "caption": "Something is being sucked up.", "id": "801", "duration": 1.16125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=801&type=wav"} +{"title": "City Ambiance", "description": "City Ambiance sound effect. Great for a movie or game that is set in an inner city or downtown area. You can clearly hear cop or ambulance sirens in the background.", "author": "lezer", "href": "1266-City-Ambiance.html", "caption": "A city is bustling.", "id": "1266", "duration": 22.6653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1266&type=wav"} +{"title": "Best Cardinal Bird Lazy", "description": "The sound of a cardinal bird call a little more lazy than the others.", "author": "PsychoBird", "href": "1475-Best-Cardinal-Bird-Lazy.html", "caption": "A cardinal bird is calling lazily.", "id": "1475", "duration": 3.29775, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1475&type=wav"} +{"title": "Small Bow Saw", "description": "Small bow saw sound effect. Person cutting small piece of wood or bone with a small bow saw.", "author": "qubodup", "href": "1649-Small-Bow-Saw.html", "caption": "Someone is cutting with a small bow saw.", "id": "1649", "duration": 8.76653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1649&type=wav"} +{"title": "Computer Start-Up", "description": "A computer starting up noise high quality. Great sound to replace windows default start up and windows default sounds.", "author": "Your Mom", "href": "1589-Computer-Start-Up.html", "caption": "A computer is starting up.", "id": "1589", "duration": 6.478375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1589&type=wav"} +{"title": "Hiccuping", "description": "Hiccuping sound effect again #2. Some drunk hiccup at a bar or just walking the street.", "author": "Mike Koenig", "href": "765-Hiccuping.html", "caption": "Someone is hiccuping.", "id": "765", "duration": 1.1764375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=765&type=wav"} +{"title": "Snoring Giant", "description": "Sound of a giant snoring. Sleeping giant sound effect made by pitching down sawing noises and slowing them down. Also amplified the sounds.", "author": "mike koenig", "href": "1603-Snoring-Giant.html", "caption": "A giant is snoring.", "id": "1603", "duration": 27.30884375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1603&type=wav"} +{"title": "Hawk Screech Valley", "description": "Sound of a hawk or eagle screeching far overhead or in some giant expanse of a valley or from a tall cliff face.", "author": "Mike Koenig", "href": "1845-Hawk-Screech-Valley.html", "caption": "A bird of prey is screeching.", "id": "1845", "duration": 5.08140625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1845&type=wav"} +{"title": "Blood Squirting", "description": "A great decapitation sound effect for gory movie scene or video game! Great for halloween too!", "author": "Mike Koenig", "href": "847-Blood-Squirting.html", "caption": "A decapitation sound effect is heard.", "id": "847", "duration": 2.608125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=847&type=wav"} +{"title": "Raptor Call", "description": "Raptor like call like the one in Jurassic Park. velociraptor call requested by Stevie15", "author": "snottyboi", "href": "1372-Raptor-Call.html", "caption": "An animal is making a raptor-like call.", "id": "1372", "duration": 3.68565625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1372&type=wav"} +{"title": "Buzzsaw", "description": "A buzz saw sound effect its pretty loud though. Original sound edited by Mike Koenig.", "author": "jaymz", "href": "1749-Buzzsaw.html", "caption": "A buzz saw is cutting.", "id": "1749", "duration": 6.98225, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1749&type=wav"} +{"title": "Horn Honk", "description": "Car, van, or truck horn honking sound effect.", "author": "Mike Koenig", "href": "1048-Horn-Honk.html", "caption": "A horn is honking.", "id": "1048", "duration": 1.75059375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1048&type=wav"} +{"title": "Large Metal Pot 1", "description": "Metal pot hit sound 1 requested by Steve metal knock or hit can be used for many things.", "author": "BlastwaveFx.com", "href": "595-Large-Metal-Pot-1.html", "caption": "A pot is hit.", "id": "595", "duration": 4.7020625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=595&type=wav"} +{"title": "Sun Roof Close", "description": "The sun roof on our van closing. Electric sun roof. Could be used for an electric motor or robot, or automated process.", "author": "Mike Koenig", "href": "788-Sun-Roof-Close.html", "caption": "A sun roof is closing.", "id": "788", "duration": 5.85928125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=788&type=wav"} +{"title": "Seal Call Zoo", "description": "Seal call sound from the Zoo", "author": "Mike Koenig", "href": "142-Seal-Call-Zoo.html", "caption": "A seal is calling.", "id": "142", "duration": 1.015875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=142&type=wav"} +{"title": "Air Break", "description": "The sound of a truck releasing its air breaks. Large hissing sound. The perfect Transfer Truck Air Breaks Sound", "author": "Mike Koenig", "href": "525-Air-Break.html", "caption": "A truck is releasing air brakes.", "id": "525", "duration": 6.92478125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=525&type=wav"} +{"title": "Glove Box Close", "description": "Sound of someone closing a glove compartment box in a nice car.", "author": "Mike Koenig", "href": "803-Glove-Box-Close.html", "caption": "Someone is closing a box.", "id": "803", "duration": 1.42803125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=803&type=wav"} +{"title": "40 Smith Wesson", "description": ".40 smith and wesson being fired out of a subcompact glock 27", "author": "Mike Koenig", "href": "2122-40-Smith-Wesson.html", "caption": "A gun is being fired.", "id": "2122", "duration": 4.60715625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2122&type=wav"} +{"title": "Ticking Clock", "description": "An old metal clock ticking noise.", "author": "KevanGC", "href": "1580-Ticking-Clock.html", "caption": "An old clock is ticking.", "id": "1580", "duration": 21.81440625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1580&type=wav"} +{"title": "Bald Eagle", "description": "A Bald Eagle recorded in yellowstone national park Wyoming. Great eagle, hawk, or any other predator bird sound effects.", "author": "Mike Koenig", "href": "981-Bald-Eagle.html", "caption": "A bald eagle or predator bird is making a sound.", "id": "981", "duration": 2.455375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=981&type=wav"} +{"title": "Glove Box Open", "description": "Sound of someone opening a glove compartment box in a nice car.", "author": "Mike Koenig", "href": "786-Glove-Box-Open.html", "caption": "Someone is opening a box.", "id": "786", "duration": 1.09134375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=786&type=wav"} +{"title": "Hubcap Falls Off Car", "description": "Sound of a hubcap as it falls off of a car. Great for a car wreck or crash scene, where you want to add a little more dimension. Could also be used for something like a manhole cover as well.", "author": "Mike Koenig", "href": "1311-Hubcap-Falls-Off-Car.html", "caption": "A hubcap is falling off a car.", "id": "1311", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1311&type=wav"} +{"title": "Whip Crack", "description": "Awesome clean whip crack sound effect. Great for indiana jones type thrillers, or just a nice sharp whip crack sound.", "author": "snottyboi", "href": "1375-Whip-Crack.html", "caption": "A whip is cracking sharply.", "id": "1375", "duration": 1.08190625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1375&type=wav"} +{"title": "0-9 Male Vocalized", "description": "We hired a male vocal actor to say the numbers 0 to 9 this the best quality audio you can get. Use this in your apps or whatever. Just give us credit and tell your friends.", "author": "Mike Koenig", "href": "2008-0-9-Male-Vocalized.html", "caption": "Someone is saying numbers.", "id": "2008", "duration": 12.198125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2008&type=wav"} +{"title": "Mosquito Ringtone", "description": "A mosquito ringtone 11kHz. Nice to put on your phones or computers and piss people off with. They wont know where the hell its coming from. Very high pitch ringing sound, sounds just like that ringing you get in your ear sometimes. Nice for pranks.", "author": "KevanGC", "href": "1591-Mosquito-Ringtone.html", "caption": "A high-pitched ringing sound is heard.", "id": "1591", "duration": 30.0930625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1591&type=wav"} +{"title": "Gear Shift Into Park", "description": "Sound of a vehicles gear shifting into park. Auto or car sound.", "author": "Mike Koenig", "href": "817-Gear-Shift-Into-Park.html", "caption": "A vehicle's gear is shifting into park.", "id": "817", "duration": 1.3505, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=817&type=wav"} +{"title": "Time Up Kids Voice", "description": "Cute time up kids voice requested by Amy. Good for some cute kids game or activity.", "author": "Mike Koenig", "href": "825-Time-Up-Kids-Voice.html", "caption": "A kid's voice is saying \"time up\".", "id": "825", "duration": 1.63678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=825&type=wav"} +{"title": "Evil Laugh Male 1", "description": "Evil Laugh Male 1 great spooky laughter", "author": "Mike Koenig", "href": "138-Evil-Laugh-Male-1.html", "caption": "Someone is laughing in an evil and spooky way.", "id": "138", "duration": 4.409, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=138&type=wav"} +{"title": "Snorting", "description": "Snort and snorting sound effect. Could be a pig or someone laughing.", "author": "Mike Koenig", "href": "796-Snorting.html", "caption": "A snorting sound effect is heard.", "id": "796", "duration": 1.055625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=796&type=wav"} +{"title": "Bedspring Squeak", "description": "The sound of a bed or bedsprings squeaking. Squeak can be used for any number of sound effect. Especially squeaky ones. :)", "author": "Mike Koenig", "href": "946-Bedspring-Squeak.html", "caption": "A bed or bedsprings is squeaking.", "id": "946", "duration": 7.01009375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=946&type=wav"} +{"title": "Car Driving", "description": "Perfect car driving sound effect. Nice car ambiance from inside the cabin of a mid size car.", "author": "stephan", "href": "1397-Car-Driving.html", "caption": "A car is driving.", "id": "1397", "duration": 31.71265625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1397&type=wav"} +{"title": "Oopsy Daisy Fart", "description": "The oopsy daisy fart is a long and drawn out fart that is any thing but a slip.", "author": "Mike Koenig", "href": "833-Oopsy-Daisy-Fart.html", "caption": "There is a fart.", "id": "833", "duration": 2.6089375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=833&type=wav"} +{"title": "Door Entry Notification", "description": "An electronic input beep followed by 3 seconds of processing silence and a voice notifying you that you have been detected and recorded", "author": "Loge the 60th", "href": "1758-Door-Entry-Notification.html", "caption": "An electronic beep is followed by a voice notification.", "id": "1758", "duration": 7.8265, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1758&type=wav"} +{"title": "Metal Grinder", "description": "Metal grinding sound from a medium size grinder. Could be a sound for sharpening a nice, forging a weapon, a factory who knows. My dad was grinding a piece of metal in hi workshop for me. A good sound have at it.", "author": "Mike Koenig", "href": "1105-Metal-Grinder.html", "caption": "Metal is being ground.", "id": "1105", "duration": 12.79075, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1105&type=wav"} +{"title": "Screaming Hawk 3", "description": "Perfect screaming hawk loud sound effect 3. Great nature sound effect.", "author": "PsychoBird", "href": "1493-Screaming-Hawk-3.html", "caption": "A hawk is screaming.", "id": "1493", "duration": 4.06134375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1493&type=wav"} +{"title": "Boat Docking", "description": "Ocracoke Island Ferry docking holding around 20 to 30 automobiles. Great mechanical sounds and a few chains jingling.", "author": "Mike Koenig", "href": "650-Boat-Docking.html", "caption": "A ferry is docking.", "id": "650", "duration": 40.52896875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=650&type=wav"} +{"title": "Gibbon Monkey", "description": "Some crazy gibbons up in trees calling down to the people and other animals on the ground.", "author": "Daniel Simon", "href": "2145-Gibbon-Monkey.html", "caption": "Gibbons are calling from trees.", "id": "2145", "duration": 5.876875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2145&type=wav"} +{"title": "Spray Bottle Of Water", "description": "Spraying water or spray bottle and recording the mist spray", "author": "Mike Koenig", "href": "326-Spray-Bottle-Of-Water.html", "caption": "Water is being sprayed.", "id": "326", "duration": 4.445875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=326&type=wav"} +{"title": "Liquid", "description": "Noise of a river or brook. Great water sound effect recorded by Caroline Ford", "author": "Caroline Ford", "href": "1444-Liquid.html", "caption": "A river or brook is making a water sound.", "id": "1444", "duration": 15.21053125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1444&type=wav"} +{"title": "I Farted", "description": "My son wants me to know that he farted, so he tells me 2x. Really funny bit from a child.", "author": "Mike Koenig", "href": "1293-I-Farted.html", "caption": "Someone's child is telling them that they farted.", "id": "1293", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1293&type=wav"} +{"title": "Evil Laugh Male 4", "description": "Evil Laugh Male 4 great spooky laughter", "author": "Mike Koenig", "href": "141-Evil-Laugh-Male-4.html", "caption": "Someone is laughing in an evil and spooky way.", "id": "141", "duration": 3.73278125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=141&type=wav"} +{"title": "Bomb", "description": "Simple loud bass heavy bomb explosion sound effect. Awesome for war, or a battle sequence.", "author": "Mike Koenig", "href": "1234-Bomb.html", "caption": "A bomb explodes with loud bass.", "id": "1234", "duration": 1.65184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1234&type=wav"} +{"title": "Chambering A Round", "description": "Glock 17 9mm Chambering A Round. High resolution recording of an actual Glock 17 9mm. Very clear gun sound.", "author": "Mike Koenig", "href": "1399-Chambering-A-Round.html", "caption": "A gun is chambering a round.", "id": "1399", "duration": 1.6950625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1399&type=wav"} +{"title": "Pin Drop", "description": "Pin dropping sound effect. So quite you can hear a pin drop. Great for a pin drop sound clip.", "author": "Mike Koenig", "href": "1073-Pin-Drop.html", "caption": "A pin is dropping, creating a very quiet sound.", "id": "1073", "duration": 1.2915, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1073&type=wav"} +{"title": "Hello Baby Girl", "description": "A little girl, my daughter to be precise, saying hello. Great little kid sound effects.", "author": "Mike Koenig", "href": "840-Hello-Baby-Girl.html", "caption": "A little girl is saying hello.", "id": "840", "duration": 1.3479375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=840&type=wav"} +{"title": "Bird In Rain", "description": "Bird singing in the rain after a large storm. This is what is sounds like when the birds come back out.", "author": "Mike Koenig", "href": "2006-Bird-In-Rain.html", "caption": "Birds are singing after rain.", "id": "2006", "duration": 47.61334375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2006&type=wav"} +{"title": "Machine Gun", "description": "A military grade machine gun firing 15 times in rapid succession.", "author": "Mike Koenig", "href": "640-Machine-Gun.html", "caption": "A machine gun is firing.", "id": "640", "duration": 4.48303125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=640&type=wav"} +{"title": "Evil Laugh Male 3", "description": "Evil Laugh Male 3 great spooky laughter", "author": "Mike Koenig", "href": "140-Evil-Laugh-Male-3.html", "caption": "Someone is laughing in an evil and spooky way.", "id": "140", "duration": 4.49015625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=140&type=wav"} +{"title": "Mindless Zombie Awakening", "description": "The sound of a mindless zombie awakening from the dead. Hes going to want to eat some human flesh soon. Zombie sounds requested by jordangiese.", "author": "Caroline Ford", "href": "1029-Mindless-Zombie-Awakening.html", "caption": "A mindless zombie is awakening.", "id": "1029", "duration": 2.8180625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1029&type=wav"} +{"title": "Brushing Wood", "description": "The sound of wood being brushed. Great contact or slight scrape sound.", "author": "Caroline Ford", "href": "884-Brushing-Wood.html", "caption": "Wood is being brushed.", "id": "884", "duration": 4.9029375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=884&type=wav"} +{"title": "Modern Battlefield", "description": "A blend of war sounds layered to create a realistic sound effect like that found on a modern day battlefield or even one from World War 2", "author": "Mike Koenig", "href": "1910-Modern-Battlefield.html", "caption": "War sounds are layered.", "id": "1910", "duration": 12, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1910&type=wav"} +{"title": "45min April Rainstorm", "description": "45 minutes of a relaxing spring rainstorm recorded April 1st 2016. This sort of audio is great to relax to or sleep to on a loop. The wav file is 400mb and the 45 minute mp3 would not render in the player so its been chopped down to 3 minutes. If you want the full 45 minutes download the wave. If you want to", "author": "Mike Koenig", "href": "2124-45min-April-Rainstorm.html", "caption": "A spring rainstorm is happening.", "id": "2124", "duration": 2438.65253125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2124&type=wav"} +{"title": "Chuckle", "description": "Me chuckling a little chuckle. Very funny sound here. Great little laugh.", "author": "Mike Koenig", "href": "767-Chuckle.html", "caption": "Someone is chuckling.", "id": "767", "duration": 1.4164375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=767&type=wav"} +{"title": "Old School Bell", "description": "Old fashion old school bell ringing on top of an old school house. Ding dong ding dong.", "author": "Daniel Simion", "href": "2185-Old-School-Bell.html", "caption": "A bell is ringing on a schoolhouse.", "id": "2185", "duration": 13.85959375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2185&type=wav"} +{"title": "Shotgun", "description": "Sound of the Mossburg 500 Pistol grip 20inch (near sawed off) tactical shotgun pumping a round into the chamber. Its that classic pump shotgun sound that says, hey i mean business. Youve all heard this sound before im sure.", "author": "Mike Koenig", "href": "1400-Shotgun.html", "caption": "A shotgun is being pumped.", "id": "1400", "duration": 1.3525625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1400&type=wav"} +{"title": "Cargo Plane Ambiance", "description": "Cargo plane ambiance from cockpit. Great for a plane or pilot scene.", "author": "Mike Koenig", "href": "490-Cargo-Plane-Ambiance.html", "caption": "Cargo plane ambiance is heard.", "id": "490", "duration": 20.7596875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=490&type=wav"} +{"title": "Lever", "description": "Mechanical sound that could fit a lever or similar device", "author": "Marianne Gagnon", "href": "1699-Lever.html", "caption": "A mechanical device is operating.", "id": "1699", "duration": 1.77634375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1699&type=wav"} +{"title": "Wild Child", "description": "A kid running around and making wild noises. I recorded my son making some crazy noises. It was late and he was tired. I have no idea what hes talking about and im not sure he does either.", "author": "Mike Koenig", "href": "708-Wild-Child.html", "caption": "A kid is making wild noises.", "id": "708", "duration": 4.36553125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=708&type=wav"} +{"title": "Basement", "description": "Sounds from basement. This is what it sounds like to be in a damp and dark basement and having someone walking overhead.", "author": "Mike Koenig", "href": "1350-Basement.html", "caption": "Someone is walking in a basement.", "id": "1350", "duration": 6.00596875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1350&type=wav"} +{"title": "Chainsaw Quick", "description": "Sound of a chainsaw quickly cutting wood in a nearby lot. sound is public domain.", "author": "ezwa", "href": "1391-Chainsaw-Quick.html", "caption": "A chainsaw is quickly cutting wood.", "id": "1391", "duration": 3.20134375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1391&type=wav"} +{"title": "Elk", "description": "The sound of a large elk bugling. This sound is public domain so enjoy.", "author": "Mike Koenig", "href": "957-Elk.html", "caption": "An elk is bugling.", "id": "957", "duration": 20.53215625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=957&type=wav"} +{"title": "Angry Squirrel", "description": "Funny angry squirrel nature sound effect. This angry squirrels chatter is super funny. Great for anything", "author": "Mike Koenig", "href": "1283-Angry-Squirrel.html", "caption": "An angry squirrel is chattering.", "id": "1283", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1283&type=wav"} +{"title": "Blowing Nose", "description": "Great blowing nose sound effect. Great for calling in sick to work. :)", "author": "Mike Koenig", "href": "776-Blowing-Nose.html", "caption": "Someone is blowing their nose.", "id": "776", "duration": 1.83596875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=776&type=wav"} +{"title": "Machine Gun Pop In Clip", "description": "Sound of a machine gun clip being put in. Another great war, battle, or military sound for movies or games.", "author": "Mike Koenig", "href": "415-Machine-Gun-Pop-In-Clip.html", "caption": "A machine gun clip is being loaded.", "id": "415", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=415&type=wav"} +{"title": "Extreme Horror FX", "description": "Extreme Horror Sound FX growling evil crawling sound scape.", "author": "Mike Koenig", "href": "409-Extreme-Horror-FX.html", "caption": "Horror sound effects are playing.", "id": "409", "duration": 15, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=409&type=wav"} +{"title": "Eating Chips", "description": "Crunchy crisp crackle sounds of me eating a tostido scoop. Wish i had some salsa.", "author": "Winston Churchill", "href": "402-Eating-Chips.html", "caption": "Someone is eating a tostido scoop.", "id": "402", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=402&type=wav"} +{"title": "Train Honk Horn Distance", "description": "Sound of a train honking its horn in the distance followed by the echoes or reverb of the honk or horn.", "author": "Mike Koenig", "href": "1694-Train-Honk-Horn-Distance.html", "caption": "A train honks in the distance.", "id": "1694", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1694&type=wav"} +{"title": "Grouse", "description": "Sound of a grouses deep booming call from the brush. This grouse sound was requested by Nertil Taflaj.", "author": "nps.gov", "href": "1181-Grouse.html", "caption": "A grouse is making a deep booming call.", "id": "1181", "duration": 1.757125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1181&type=wav"} +{"title": "Birds After Rain", "description": "After the rain passed there were some nice little birds that came out of hiding and began to make music. The WAV version and the ZIP File version include the full 1+ minute of audio but the MP3 download link is smaller, as we use this to play a preview and it is to large to auto-load on a page without delay. So basically..download the .ZIP or .WAV for the full sound. :P", "author": "Mike Koenig", "href": "1827-Birds-After-Rain.html", "caption": "Birds are making music after a rainstorm.", "id": "1827", "duration": 67.7324375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1827&type=wav"} +{"title": "Scary Demon Haunting", "description": "Multiple sfx blended together with a creepy demonic voice over for a Good Scare. Big thanks to Adam Webb from SoundBible.com for the sound donation, this audio is awesome!", "author": "Adam Webb", "href": "1883-Scary-Demon-Haunting.html", "caption": "A demonic voiceover is heard with multiple sound effects.", "id": "1883", "duration": 153.09165625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1883&type=wav"} +{"title": "Store Door Chime", "description": "Store door chime sound effect. This sound door ding was requested by danielle johnson at Southeastern Louisiana University but her email address was invalid so we hope its the correct sound. Sound was made using", "author": "Mike Koenig", "href": "1599-Store-Door-Chime.html", "caption": "A store door chime is ringing.", "id": "1599", "duration": 1.82125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1599&type=wav"} +{"title": "2 Minute Storm", "description": "This is a 2 minute clip from a summer thunder storm just recorded. At 2.31 minutes it doesnt need to be looped for movie and video scenes.", "author": "Mike Koenig", "href": "1908-2-Minute-Storm.html", "caption": "A thunderstorm is recorded.", "id": "1908", "duration": 151.70340625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1908&type=wav"} +{"title": "Police Scanner", "description": "Police scanner clicks and electric pops. Great for scanner or scanning sound effects. Could even be from military radio.", "author": "ScanMan", "href": "1641-Police-Scanner.html", "caption": "There are clicks and pops from a scanner.", "id": "1641", "duration": 2.6703125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1641&type=wav"} +{"title": "Fire", "description": "Perfect fire sound effect. Sounds of fire burning in a pit, fire barrel, house on fire, campfire, grilling food. No matter what the need this sound is great. Download in wav or mo3 format now.", "author": "Mike Koenig", "href": "1159-Fire.html", "caption": "Fire is burning in a pit, barrel, house, or campfire.", "id": "1159", "duration": 15, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1159&type=wav"} +{"title": "AR-15 Gunfire", "description": "6 shots fired in rapid succession from Bushmaster AR-15 Semi Automatic. Shots fired at indoor range so they are a bit muted. You can hear the magazine being snapped in and a few shells falling too. Pretty cool sound.", "author": "Mike Koenig", "href": "1631-AR-15-Gunfire.html", "caption": "A gun is firing rapidly.", "id": "1631", "duration": 4.65921875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1631&type=wav"} +{"title": "Crushed Ice Machine", "description": "Crushed ice machine sound from our kitchen ice maker", "author": "Mike Koenig", "href": "123-Crushed-Ice-Machine.html", "caption": "An ice maker is making a sound.", "id": "123", "duration": 16.0641875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=123&type=wav"} +{"title": "Walking In Snow", "description": "Walking in Snow sound. Ice crunches under feet. Pretty cool", "author": "Mike Koenig", "href": "660-Walking-In-Snow.html", "caption": "Snow is crunching underfoot.", "id": "660", "duration": 8.4636875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=660&type=wav"} +{"title": "Bells Tibetan Large", "description": "Large Tibetan Bells ringing in a temple. Could also use for Monastery or Monks.", "author": "Daniel Simion", "href": "2205-Bells-Tibetan-Large.html", "caption": "Bells are ringing in a temple.", "id": "2205", "duration": 18, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2205&type=wav"} +{"title": "Shake And Roll Dice", "description": "Shaking and Rolling Dice 2 on the table during a game", "author": "Mike Koenig", "href": "182-Shake-And-Roll-Dice.html", "caption": "Dice are being shaken and rolled on a table during a game.", "id": "182", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=182&type=wav"} +{"title": "Shotgun Reload Old", "description": "This is an awesome and excellent quality reloaded of an old school shotgun", "author": "RA The Sun God", "href": "1996-Shotgun-Reload-Old.html", "caption": "A shotgun is being reloaded.", "id": "1996", "duration": 1.0210625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1996&type=wav"} +{"title": "Fire Alarm", "description": "Fire alarm sound effect. This is an old school fire alarm, one of the ones that actually strikes the metal bell with a hammer. Great sound effect.", "author": "battlestar10", "href": "1550-Fire-Alarm.html", "caption": "A fire alarm is ringing.", "id": "1550", "duration": 12.07440625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1550&type=wav"} +{"title": "Background Noise", "description": "The sound of random background noise. Great to create a steady ambiance for scenes.", "author": "Mike Koenig", "href": "954-Background-Noise.html", "caption": "Background noise is present.", "id": "954", "duration": 15.16171875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=954&type=wav"} +{"title": "Tundra Swans", "description": "Swans on the frozen tundra hundreds of birds", "author": "fws.gov", "href": "275-Tundra-Swans.html", "caption": "Some swans are present.", "id": "275", "duration": 19.009, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=275&type=wav"} +{"title": "Angry Chipmunk", "description": "Angry Chipmunk cartoon sound effect. Great angry chatter for a cartoon animal or person. Cute sounds.", "author": "Mike Koenig", "href": "1268-Angry-Chipmunk.html", "caption": "An animal is chattering.", "id": "1268", "duration": 2.490375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1268&type=wav"} +{"title": "Motorbike", "description": "Motorbike sound effect. Bike or motorbike driving by on the road.", "author": "ezwa", "href": "1393-Motorbike.html", "caption": "A motorbike is driving.", "id": "1393", "duration": 7.00084375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1393&type=wav"} +{"title": "Baby Talk 2", "description": "Very cute baby babbling or baby talk sound clip. Baby says 4 sounds.", "author": "stephan", "href": "1538-Baby-Talk-2.html", "caption": "A baby is babbling.", "id": "1538", "duration": 4.66721875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1538&type=wav"} +{"title": "Toilet Flush Refill", "description": "Toilet bowl flushing in bathroom and the tank filling up again", "author": "Mike Koenig", "href": "190-Toilet-Flush-Refill.html", "caption": "A toilet bowl is flushing and the tank is filling up.", "id": "190", "duration": 40, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=190&type=wav"} +{"title": "Cow Moos 3x", "description": "A very persistent cow that keeps mooing. 3 moos in rapid succession. Sounds from a ranch down in Arizona.", "author": "BuffBill84", "href": "1703-Cow-Moos-3x.html", "caption": "A cow is mooing.", "id": "1703", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1703&type=wav"} +{"title": "Ole Bullfighter", "description": "Ole sound from a bullfighter at an arena in mexico", "author": "Mike Koenig", "href": "652-Ole-Bullfighter.html", "caption": "Someone is making an \"ole\" sound.", "id": "652", "duration": 1.39321875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=652&type=wav"} +{"title": "Electronic Chime", "description": "A nice soft beep or chime you can use for a computer event or similar. Its a beep fading out.", "author": "KevanGC", "href": "1598-Electronic-Chime.html", "caption": "A beep is fading out.", "id": "1598", "duration": 2.0898125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1598&type=wav"} +{"title": "Halloween Vocals", "description": "8 halloween vocals that would be good to use for halloween this year. Scare those little trick o treaters and thank us later.", "author": "Mike Koenig", "href": "2080-Halloween-Vocals.html", "caption": "Vocals are heard.", "id": "2080", "duration": 33.52890625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2080&type=wav"} +{"title": "Bison", "description": "The sound of a few bees recorded in Yosemite National Park. One bee can be heard louder than the others. Great for a beekeeper or similar sound effect.", "author": "nps.gov", "href": "918-Bison.html", "caption": "A few bees are buzzing.", "id": "918", "duration": 6.29553125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=918&type=wav"} +{"title": "Pouring Drink", "description": "Pouring a drink a nice cold refreshing glass of distilled water into a faux crystal glass.", "author": "Mike Koenig", "href": "2115-Pouring-Drink.html", "caption": "Water is being poured into a glass.", "id": "2115", "duration": 11.757375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2115&type=wav"} +{"title": "Intruder Alert", "description": "Cool intrusion alarm detection sound effect. Sound like a sound you would hear on some space movie like 2001 space odyssey or one of those alien movies from the 90s with Sigourney Weaver in it.", "author": "Mike Koenig", "href": "843-Intruder-Alert.html", "caption": "An intrusion alarm detection sound effect is heard.", "id": "843", "duration": 8.57234375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=843&type=wav"} +{"title": "Fog Horn", "description": "Fog horn sound effect very low and loud with extra bass for ephasis of size.", "author": "Mike Koenig", "href": "1594-Fog-Horn.html", "caption": "A fog horn is sounding.", "id": "1594", "duration": 2.31546875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1594&type=wav"} +{"title": "Please", "description": "Male asking please. A very nice request. Its actually me asking my son to say something for the recorder.", "author": "Mike Koenig", "href": "1277-Please.html", "caption": "Someone is asking politely.", "id": "1277", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1277&type=wav"} +{"title": "Table Saw Buzz", "description": "Sound of a table saw in my fathers garage. This sound is about as good ad it gets for electric saw sounds.", "author": "Mike Koenig", "href": "1100-Table-Saw-Buzz.html", "caption": "An electric saw is buzzing in a garage.", "id": "1100", "duration": 26.2050625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1100&type=wav"} +{"title": "Dropped Wooden Floor", "description": "Sound of an object being dropped on a wooden floor sound effect. A small wooden thud or impact sound can be heard.", "author": "Mike Koenig", "href": "715-Dropped-Wooden-Floor.html", "caption": "An object is dropped, making a small wooden impact sound.", "id": "715", "duration": 1.335125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=715&type=wav"} +{"title": "Mallard Duck", "description": "Mallard duck or mallard ducks plural in a small pond at a nearby park. These can be used for generic duck sounds also. If you like this sound please see sound 2.", "author": "Mike Koenig", "href": "1852-Mallard-Duck.html", "caption": "Ducks are quacking.", "id": "1852", "duration": 2.6430625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1852&type=wav"} +{"title": "Pelican Chick", "description": "Pelican chick chattering near mother pelican at sea side", "author": "fws.gov", "href": "250-Pelican-Chick.html", "caption": "A pelican chick is chattering near its mother at the seaside.", "id": "250", "duration": 8.425, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=250&type=wav"} +{"title": "Windy", "description": "Windy wind blowing 3 or howling slightly. A great nature sound requested by manoj sharma.", "author": "Mike Koenig", "href": "636-Windy.html", "caption": "Wind is blowing.", "id": "636", "duration": 14.05053125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=636&type=wav"} +{"title": "Slap", "description": "A very heavy slap to the face. Great for a backhand or even fight sound effect. Could also be used to emulate something snapping or breaking.", "author": "SoundMaster13", "href": "1948-Slap.html", "caption": "A face is being slapped heavily.", "id": "1948", "duration": 1.34678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1948&type=wav"} +{"title": "Water Splash", "description": "Water splash or splashing sound effect requested by Caroline. Great for any wet situational sound.", "author": "Mike Koenig", "href": "1460-Water-Splash.html", "caption": "Water is splashing.", "id": "1460", "duration": 1.13134375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1460&type=wav"} +{"title": "Sci Fi Robot", "description": "Sound of a classic sci-fi robot computing data. Youll know what i mean when you hear it. Requested by Bob Jackson", "author": "Mike Koenig", "href": "1317-Sci-Fi-Robot.html", "caption": "A sci-fi robot is computing.", "id": "1317", "duration": 4.13984375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1317&type=wav"} +{"title": "Bouncy Bounce", "description": "A guy saying bouncy bouncy bouncy bounce with a boinging noise in the background.", "author": "Bugs Bunny", "href": "1650-Bouncy-Bounce.html", "caption": "Someone is saying \"bouncy bouncy bouncy bounce\" with a boinging noise.", "id": "1650", "duration": 5.38125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1650&type=wav"} +{"title": "Hover Craft", "description": "Hover Craft Sound Pass by. Sound of a hovercraft driving by", "author": "Mike Koenig", "href": "539-Hover-Craft.html", "caption": "A hovercraft is passing by.", "id": "539", "duration": 10.4025625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=539&type=wav"} +{"title": "Best Helicopter Pass", "description": "This is the best helicopter sound effect i've recorded yet by far. A helicopter was scheduled to come by so i was ready to record accordingly. The .wav and .mp3 are the shorter version. The .zip file has 1.27 minutes of the helicopter coming in and passing.", "author": "Mike Koenig", "href": "1621-Best-Helicopter-Pass.html", "caption": "A helicopter is flying overhead.", "id": "1621", "duration": 19.69053125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1621&type=wav"} +{"title": "Parots Talking", "description": "Parrots talking in a local pet shop. Talking or squawking sound effect is public domain audio.", "author": "aras", "href": "1544-Parots-Talking.html", "caption": "Parrots are squawking.", "id": "1544", "duration": 2.76240625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1544&type=wav"} +{"title": "Chimpanzee", "description": "Chimpanzee or monkey making crazy monkey sounds while hopping around its cage. Great for zoo or laboratory sounds.", "author": "Mike Koenig", "href": "1188-Chimpanzee.html", "caption": "A monkey is making crazy sounds in a cage.", "id": "1188", "duration": 2.49753125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1188&type=wav"} +{"title": "I Love Daddy", "description": "A little girl, my daughter to be precise, saying i love daddy. Great little kid sound effects.", "author": "Mike Koenig", "href": "869-I-Love-Daddy.html", "caption": "A little girl is saying \"I love daddy\".", "id": "869", "duration": 1.63678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=869&type=wav"} +{"title": "M 82 Barrett 50 Cal", "description": "Huge gunshot sound from a M-82 Barrett 50 Caliber Sniper Rifle. This things sound so large you could almost use it as a tank firing sound effect.", "author": "JKirsch", "href": "1388-M-82-Barrett-50-Cal.html", "caption": "A sniper rifle is firing a huge gunshot.", "id": "1388", "duration": 3.82790625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1388&type=wav"} +{"title": "Home Phone Ringing", "description": "Our home phone ringing we are in the US so its a united states phone", "author": "fws.gov", "href": "315-Home-Phone-Ringing.html", "caption": "A phone is ringing.", "id": "315", "duration": 18.60253125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=315&type=wav"} +{"title": "Evil Laugh Male 2", "description": "Evil Laugh Male 2 great spooky laughter", "author": "Mike Koenig", "href": "139-Evil-Laugh-Male-2.html", "caption": "Someone is laughing in an evil and spooky way.", "id": "139", "duration": 3.97621875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=139&type=wav"} +{"title": "Counting To 10", "description": "My daughter counting to 10 while on vacation. Very cute.", "author": "Mike Koenig", "href": "1873-Counting-To-10.html", "caption": "Someone is counting.", "id": "1873", "duration": 7.593375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1873&type=wav"} +{"title": "Elevator Shaft Or Tunnel", "description": "Elevator Shaft or tunnel sound effect. This is a great sound that could be used for a suspense sound or an open elevator shaft or abyss.", "author": "Mike Koenig", "href": "519-Elevator-Shaft-Or-Tunnel.html", "caption": "An elevator shaft or tunnel is making a sound.", "id": "519", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=519&type=wav"} +{"title": "Massive War With Alarm", "description": "A war is going on while alarm goes off. Shooting, alarm, and ricochets.", "author": "Emmanuel Exiga", "href": "2058-Massive-War-With-Alarm.html", "caption": "A war is happening with shooting, alarms, and ricochets.", "id": "2058", "duration": 41.44434375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2058&type=wav"} +{"title": "Vehicle Alarm", "description": "The sound of a vehicle alarm or car alarm. Great warning sound effect.", "author": "Mike Koenig", "href": "888-Vehicle-Alarm.html", "caption": "A vehicle alarm is sounding.", "id": "888", "duration": 9.92653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=888&type=wav"} +{"title": "Sad Woman Crying", "description": "A very sad woman or lady crying and sobbing because of something very sad.", "author": "Daniel Simon", "href": "2133-Sad-Woman-Crying.html", "caption": "A woman is crying and sobbing.", "id": "2133", "duration": 22.646375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2133&type=wav"} +{"title": "Torch", "description": "Torch or fireball sound effect. Nice fire sizzling torch sound. Great for caves, explorers, medieval castles, dnd games.", "author": "Mike Koenig", "href": "1135-Torch.html", "caption": "A torch is sizzling.", "id": "1135", "duration": 2.17271875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1135&type=wav"} +{"title": "High Pitch Dog Whistle", "description": "Super high pitch dog whistle sound effect for 30 seconds. This file is super high pitch and your dog will hate you if you play this for too long. May be a great sound weapon for pest deterrents as well. Can be used to ward of mice, rodents, rats, stray dogs, stray cats, and even keep your street free of unwanted bums, beggars, hobos, etc :) See the 10 minute", "author": "Mike Koenig", "href": "1125-High-Pitch-Dog-Whistle.html", "caption": "A dog whistle is sounding.", "id": "1125", "duration": 63.15828125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1125&type=wav"} +{"title": "Good Nite", "description": "My daughter telling her grandfather, or papaw as they say in the south, Good Nite. Very cute sound.", "author": "Mike Koenig", "href": "620-Good-Nite.html", "caption": "Someone's daughter is saying goodnight.", "id": "620", "duration": 1.7066875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=620&type=wav"} +{"title": "22 Beretta Chamber Load", "description": "Sound made when loading a 22 Beretta pistol.", "author": "Mike Koenig", "href": "411-22-Beretta-Chamber-Load.html", "caption": "A pistol is being loaded.", "id": "411", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=411&type=wav"} +{"title": "Dog Whistle", "description": "Dog whistle super high pitch audio sample that will make you sick to your stomache and have a headache if you listen to it for too long. Turn up your speakers. Very very very annoying.", "author": "Mike Koenig", "href": "1124-Dog-Whistle.html", "caption": "A dog whistle is sounding.", "id": "1124", "duration": 19.41190625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1124&type=wav"} +{"title": "Riding NYC Subway Car", "description": "Riding on NYC Subway Car going over bumps great city ambience", "author": "Mike Koenig", "href": "386-Riding-NYC-Subway-Car.html", "caption": "A subway car is going over bumps.", "id": "386", "duration": 11.9875625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=386&type=wav"} +{"title": "Wood Hull On Boat Creaking", "description": "Sound of the wood hull on a pirate ship or other vessell creaking as it rocks.", "author": "Mike Koenig", "href": "1122-Wood-Hull-On-Boat-Creaking.html", "caption": "A vessel's hull is creaking.", "id": "1122", "duration": 2.1554375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1122&type=wav"} +{"title": "Sun Roof Open", "description": "The sun roof on our van opening. Electric sun roof. Could be used for an electric motor or robot, or automated process.", "author": "Mike Koenig", "href": "775-Sun-Roof-Open.html", "caption": "A sun roof is opening.", "id": "775", "duration": 6.32746875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=775&type=wav"} +{"title": "Snowing", "description": "Snow or snowing sound effect. snowflakes hitting the ground sound. Requested by Caroline Ford from TuxPaint", "author": "Mike Koenig", "href": "633-Snowing.html", "caption": "Snow is falling.", "id": "633", "duration": 2.54015625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=633&type=wav"} +{"title": "Spooky Drone", "description": "Nice spooky drone or pulsing wavey pad sound effect. This sound will fit perfect into a horror or alien movie.", "author": "Mike Koenig", "href": "1888-Spooky-Drone.html", "caption": "A sound effect is heard.", "id": "1888", "duration": 25.1836875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1888&type=wav"} +{"title": "Button Click Off", "description": "Sound of a button click off. Great computer sound click effect, or flash sound effect.", "author": "Mike Koenig", "href": "1294-Button-Click-Off.html", "caption": "A button is being clicked off.", "id": "1294", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1294&type=wav"} +{"title": "Car Door Open And Alarm", "description": "Sound of a Car Door Opening and the door ajar alarm, dinging.", "author": "Mike Koenig", "href": "784-Car-Door-Open-And-Alarm.html", "caption": "A car door is opening and an alarm is sounding.", "id": "784", "duration": 4.01184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=784&type=wav"} +{"title": "Fizzle", "description": "Sound of a device short circuiting or fizzling. Great for a computer or any number of electronic components. Download it its free.", "author": "Mike Koenig", "href": "1308-Fizzle.html", "caption": "A device is short circuiting or fizzling.", "id": "1308", "duration": 1.21359375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1308&type=wav"} +{"title": "Cannon", "description": "The sound of a cannon blasting. Great for pirate or cival war battle scenes.", "author": "nps.gov", "href": "909-Cannon.html", "caption": "A cannon is blasting.", "id": "909", "duration": 2.592, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=909&type=wav"} +{"title": "Ape", "description": "Very cool ape sound. Great for a zoo, or primate and monkey scene. The sound is public domain so thats a bonus.", "author": "Mike Koenig", "href": "1147-Ape.html", "caption": "An ape is making a sound.", "id": "1147", "duration": 3.4749375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1147&type=wav"} +{"title": "Auditorium Applause", "description": "Nice Auditorium Applause sound recorded live. This applause sound is public domain so you can use it for whatever you want to.", "author": "Thore", "href": "1260-Auditorium-Applause.html", "caption": "People are applauding.", "id": "1260", "duration": 17.2930625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1260&type=wav"} +{"title": "1 Person Cheering", "description": "This is a small sound of only 1 person shouting YAY Good for accomplishments or major goals for 1 person.", "author": "Jett Rifkin", "href": "2103-1-Person-Cheering.html", "caption": "Someone is shouting \"YAY.\".", "id": "2103", "duration": 1.9969375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2103&type=wav"} +{"title": "Air Wrench Short", "description": "Sound of an air wrench like that used during a NASCAR pit stop being used to remove or put a lug nut on.", "author": "Lightning McQue", "href": "1975-Air-Wrench-Short.html", "caption": "An air wrench is being used to remove or put a lug nut on.", "id": "1975", "duration": 1.5549375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1975&type=wav"} +{"title": "Large Waterfall", "description": "Large waterfall roaring over cliff as it plunges into a river.", "author": "Daniel Simion", "href": "2201-Large-Waterfall.html", "caption": "A large waterfall is roaring.", "id": "2201", "duration": 44.15759375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2201&type=wav"} +{"title": "Ice Cubes Glass", "description": "2 ice cubes are dropped into a frosted glass and slide down the side landing in a small ammount of liquid at the bottom. Very refreshing sound.", "author": "Daniel Simion", "href": "2182-Ice-Cubes-Glass.html", "caption": "Ice cubes are falling into a glass.", "id": "2182", "duration": 1.56646875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2182&type=wav"} +{"title": "Diamond Back Rattle Snake", "description": "Sound of a diamond back rattle snake shaking his rattle as a warning", "author": "Mike Koenig", "href": "219-Diamond-Back-Rattle-Snake.html", "caption": "A diamondback rattlesnake is shaking its rattle as a warning.", "id": "219", "duration": 5.2060625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=219&type=wav"} +{"title": "Comet", "description": "Sound of a Comet flying through the sky. Great astral space or science fiction sound effect. Could even be used for a rocket or missile.", "author": "Mike Koenig", "href": "1141-Comet.html", "caption": "A sound effect of a comet flying through the sky is playing.", "id": "1141", "duration": 2.79965625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1141&type=wav"} +{"title": "P90 Gun Fire", "description": "More P90 gunfire as requested by EVAN. P90 designed by Belgian firearms manufacturer FN Herstal being fired.", "author": "ruin", "href": "1448-P90-Gun-Fire.html", "caption": "More gunfire is heard from the same firearm.", "id": "1448", "duration": 2.558125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1448&type=wav"} +{"title": "Hacksaw", "description": "Recording of a hacksaw sound effect. Hacksaw cutting through wood, metal, or even bone sound.", "author": "qubodup", "href": "1590-Hacksaw.html", "caption": "A hacksaw is cutting through a material.", "id": "1590", "duration": 16.9415, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1590&type=wav"} +{"title": "Gun Shot", "description": "Gun Shot Tuned Loud 2010 525 Kb. Nice crisp loud and clear free gun shot sound effect. Doesnt get much better than this. Thanks Marvin", "author": "Marvin", "href": "2004-Gun-Shot.html", "caption": "A gun is firing.", "id": "2004", "duration": 3.04803125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2004&type=wav"} +{"title": "News Report Opening", "description": "A news report opening sound great for a news station or news intro. Just throw a voice over it and you are good. This sound was a request from Brandon. If you use this please be sure to site the artist and SoundBible.com", "author": "Mike Koenig", "href": "465-News-Report-Opening.html", "caption": "A news report sound effect.", "id": "465", "duration": 33.39175, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=465&type=wav"} +{"title": "Tidal Wave", "description": "A very large tidal wave or \trogue wave sound effect 1 requested by Lincoln", "author": "Mike Koenig", "href": "607-Tidal-Wave.html", "caption": "Sound of a very large wave.", "id": "607", "duration": 20, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=607&type=wav"} +{"title": "Huge Crowd 3", "description": "Sounds of another large crowd at a stadium with thousands of people screaming.", "author": "Mike Koenig", "href": "714-Huge-Crowd-3.html", "caption": "A large crowd is screaming.", "id": "714", "duration": 6.86225, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=714&type=wav"} +{"title": "Zombie Long Death", "description": "Zombie long death is a sound of a zombie dying. Well redying technically since he was already dead once. Zombie sounds requested by jordangiese.", "author": "Mike Koenig", "href": "1042-Zombie-Long-Death.html", "caption": "A zombie is dying.", "id": "1042", "duration": 3.36546875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1042&type=wav"} +{"title": "Spooky", "description": "Spooky Girl or ghost saying mommy. Great for a Halloween or for other scary things.", "author": "Mike Koenig", "href": "760-Spooky.html", "caption": "A girl or ghost is saying \"mommy\".", "id": "760", "duration": 4.92265625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=760&type=wav"} +{"title": "Rain Background", "description": "This is a 30 second clip of steady even rain that can easily be repeated in order to make a loop to add rain sound effects to a game or movie.", "author": "Mike Koenig", "href": "2011-Rain-Background.html", "caption": "Rain is falling steadily.", "id": "2011", "duration": 33.2974375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2011&type=wav"} +{"title": "Ship Bell", "description": "Ships bell ringing one time with slight resonance as the sound rolls accross the water and through the fog.", "author": "Mike Koenig", "href": "1746-Ship-Bell.html", "caption": "A bell is ringing.", "id": "1746", "duration": 3.7456875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1746&type=wav"} +{"title": "Helicopter Circling Back", "description": "Sound of a Helicopter Circling Back after it passes over head. Sounds like hes doubling back to find a place to land.", "author": "Mike Koenig", "href": "1893-Helicopter-Circling-Back.html", "caption": "Helicopter circling back after passing overhead.", "id": "1893", "duration": 17.94984375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1893&type=wav"} +{"title": "9mm Clip Load", "description": "9mm Clip Load gun sound recorded with my Zoom H4", "author": "Mike Koenig", "href": "410-9mm-Clip-Load.html", "caption": "A clip is being loaded into a gun.", "id": "410", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=410&type=wav"} +{"title": "Spooky Heart Beats", "description": "Heart beating with a bunch of reverb, makes this sound real spooky.", "author": "Mike Koenig", "href": "381-Spooky-Heart-Beats.html", "caption": "A heart is beating with reverb.", "id": "381", "duration": 12.16965625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=381&type=wav"} +{"title": "Large Door Slam", "description": "Very large metal or wooden door slam or slamming shut sound effect with reverb and echo.", "author": "stephan", "href": "1551-Large-Door-Slam.html", "caption": "A door is slamming shut.", "id": "1551", "duration": 4.0213125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1551&type=wav"} +{"title": "Bathroom Sink", "description": "Sound of the faucet in the bathroom being turned on running for a bit and then shutting off.", "author": "Mike Koenig", "href": "1933-Bathroom-Sink.html", "caption": "The faucet is turned on and off in a bathroom.", "id": "1933", "duration": 12.90696875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1933&type=wav"} +{"title": "Heavy Machine Gun Fire", "description": "Sound of Heavy Machine Gun Fire. This would be great for a battlefield or war zone sound effect.", "author": "JKirsch", "href": "1387-Heavy-Machine-Gun-Fire.html", "caption": "Heavy machine gun fire is occurring.", "id": "1387", "duration": 4.7045, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1387&type=wav"} +{"title": "Large Chains", "description": "Large chain sounds. Sound of them being banged and dragged around.", "author": "Mike Koenig", "href": "1101-Large-Chains.html", "caption": "Large chains are being banged and dragged around.", "id": "1101", "duration": 9.30628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1101&type=wav"} +{"title": "Thunder", "description": "Sound of thunder crackling through the air followed by a large thunder clap and then some echoes as the sounds bounce around.", "author": "Mike Koenig", "href": "1907-Thunder.html", "caption": "Thunder cracks through the air with echoes.", "id": "1907", "duration": 17.001, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1907&type=wav"} +{"title": "Ruger 357 Magnum Gun Cock", "description": "A police issue Ruger 367 Magnum gun cocking sound. Killer army, military, or battle sound for games or movies.", "author": "Mike Koenig", "href": "416-Ruger-357-Magnum-Gun-Cock.html", "caption": "A gun is cocking.", "id": "416", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=416&type=wav"} +{"title": "Strange Alien", "description": "Strange alien sound effect was originally a drill sound uploaded by Msl but the quality was not great so we warped it into some alien like sound.", "author": "Msl", "href": "2003-Strange-Alien.html", "caption": "An alien sound is heard.", "id": "2003", "duration": 31.09984375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2003&type=wav"} +{"title": "Camera Flashing", "description": "Camera flashing sound. Great for a camera flash or paparazzi sound.", "author": "Mike Koenig", "href": "534-Camera-Flashing.html", "caption": "A camera is flashing.", "id": "534", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=534&type=wav"} +{"title": "Eating", "description": "Sound of someone eating. Mmmm... im hungry for some food.", "author": "Caroline Ford", "href": "976-Eating.html", "caption": "Someone is eating.", "id": "976", "duration": 2.41396875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=976&type=wav"} +{"title": "Cop Car And Helicopter", "description": "Cop car sire and a police helicopter sound recording. Im guessing they were chasing someone that did something bad.", "author": "Mike Koenig", "href": "1076-Cop-Car-And-Helicopter.html", "caption": "A cop car siren and a police helicopter are making loud noises, possibly chasing someone.", "id": "1076", "duration": 8.72909375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1076&type=wav"} +{"title": "Having A Shower", "description": "Nicely recorded shower that is in the public domain so thats a bonus. Sounds great for any bathroom sound request.", "author": "ezwa", "href": "1584-Having-A-Shower.html", "caption": "A shower is running.", "id": "1584", "duration": 26.09746875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1584&type=wav"} +{"title": "End Of Game", "description": "The last few seconds of a basketball game for elementary kids this sound includes the ending buzzer and the crows talking.", "author": "Mike Koenig", "href": "1834-End-Of-Game.html", "caption": "An elementary basketball game ends with a buzzer and crows talking.", "id": "1834", "duration": 14.02778125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1834&type=wav"} +{"title": "Tea Pot Whistle", "description": "A tea pot also called a tea kettle or just a kettle whistling. We recorded 2 different teak pots and this includes 3 total sound files combined into 1. This sound was requested.", "author": "Mike Koenig", "href": "2126-Tea-Pot-Whistle.html", "caption": "A tea pot or kettle is whistling.", "id": "2126", "duration": 181.0586875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2126&type=wav"} +{"title": "Eaglet Bird 2", "description": "Sound of a young Eaglet Bird 2. Great nature or wilderness sound effect.", "author": "PsychoBird", "href": "1487-Eaglet-Bird-2.html", "caption": "An eaglet bird is chirping.", "id": "1487", "duration": 2.54740625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1487&type=wav"} +{"title": "Angry Giant", "description": "Giant sounds angry! Sounds like that big giant guy from the movie Troy. Great anger and strife sound.", "author": "Mike Koenig", "href": "968-Angry-Giant.html", "caption": "A giant is angry.", "id": "968", "duration": 2.1006875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=968&type=wav"} +{"title": "Stream Noise", "description": "Noise of a river or brook. Great water sound effect recorded by Caroline Ford", "author": "Caroline Ford", "href": "1434-Stream-Noise.html", "caption": "A river or brook is making a water sound.", "id": "1434", "duration": 18.17253125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1434&type=wav"} +{"title": "Ovation", "description": "Sound of an ovation or applause from large crowd at a convention. Crowd size a few hundred people.", "author": "Mike Koenig", "href": "1647-Ovation.html", "caption": "A crowd is applauding.", "id": "1647", "duration": 3.8313125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1647&type=wav"} +{"title": "Annoying Speaker Pulsing", "description": "Listen to all of it it will make you cry. This is one full minute of what may be the most annoying sound ever. Pulsing wobbling speaker sounds.", "author": "Ethan Buck", "href": "2085-Annoying-Speaker-Pulsing.html", "caption": "An annoying pulsing speaker sound is heard.", "id": "2085", "duration": 61.35640625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2085&type=wav"} +{"title": "Sawing Wood", "description": "Person sawing wood with a handsaw over and over again. Cutting a branch, plank, small tree, or plastic pipe using a handsaw. Great for a game where someone needs to create or errect objects.", "author": "Daniel Simion", "href": "2200-Sawing-Wood.html", "caption": "Someone is sawing wood with a handsaw.", "id": "2200", "duration": 11.0335, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2200&type=wav"} +{"title": "Cartoon Running", "description": "Sound of someone running fast. Its a bit cartoonish :)", "author": "Cam", "href": "1979-Cartoon-Running.html", "caption": "Someone is running fast.", "id": "1979", "duration": 3.01821875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1979&type=wav"} +{"title": "Straw Slurp 3", "description": "The sound of someone slurping something through a straw 3. Good suction or drinking beverage sound.", "author": "Mike Koenig", "href": "842-Straw-Slurp-3.html", "caption": "Someone is slurping through a straw.", "id": "842", "duration": 5.17978125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=842&type=wav"} +{"title": "Tsunami Wave 2", "description": "A very large tsunami, tidal wave, or rogue wave sound effect 1 requested by Lincoln", "author": "Mike Koenig", "href": "608-Tsunami-Wave-2.html", "caption": "Sound of a very large wave.", "id": "608", "duration": 19.420125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=608&type=wav"} +{"title": "Zombie Moan", "description": "Zombie moaning sound effect. Zombie sounds requested by jordangiese.", "author": "Mike Koenig", "href": "1035-Zombie-Moan.html", "caption": "A zombie is moaning.", "id": "1035", "duration": 1.2306875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1035&type=wav"} +{"title": "Belch", "description": "Some guy making a nasty belch or burp sound effect.", "author": "Mike Koenig", "href": "841-Belch.html", "caption": "Someone is belching or burping.", "id": "841", "duration": 1.05653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=841&type=wav"} +{"title": "AM Radio Tuning", "description": "Sony Battery-powered AM Radio Weak Signal Switches and Tuning. Changing stations on a manual radio.", "author": "SailorMoonFan", "href": "2099-AM-Radio-Tuning.html", "caption": "A manual radio is being tuned.", "id": "2099", "duration": 25.3561875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2099&type=wav"} +{"title": "Party Horn", "description": "Party horn sound effect from a birthday party last month. One large long medium pitched horn squeal.", "author": "Mike Koenig", "href": "1817-Party-Horn.html", "caption": "A party horn is squealing.", "id": "1817", "duration": 1.4359375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1817&type=wav"} +{"title": "Sports Crowd", "description": "A 40 second clip of a crowd at a sports center or sporting event. This sound effect is perfect because it doesnt have any announcer or music in the background and this makes it totally legit. football crowd requested by football allen", "author": "GoGo", "href": "1881-Sports-Crowd.html", "caption": "A crowd is cheering.", "id": "1881", "duration": 41.656625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1881&type=wav"} +{"title": "Sliding", "description": "A great sliding sound effect. Slide sounds can be used to emulate or enforce movements of objects. Pitch it up for small object slides and down for larger object slides.", "author": "Mike Koenig", "href": "671-Sliding.html", "caption": "Something is sliding.", "id": "671", "duration": 1.00271875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=671&type=wav"} +{"title": "Moose", "description": "Female moose call recorded by the fish and Wildlife Service in Minnesota. Wildlife recordings like this from the government are automatically in the public domain.", "author": "fws.gov", "href": "1227-Moose.html", "caption": "A moose is making a call.", "id": "1227", "duration": 11.2950625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1227&type=wav"} +{"title": "Elaborate Thunder", "description": "This clip details a few different thunder strike sounds. One even has that type of thunder that strikes and then you hear it echo back the original clap but only backwards.", "author": "Mike Koenig", "href": "2005-Elaborate-Thunder.html", "caption": "Thunder is striking in different ways.", "id": "2005", "duration": 115.35675, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2005&type=wav"} +{"title": "Electricity", "description": "Electricity sound effect. This sound is shocking, literally. lol. Great for an electric chair or zapping sound.", "author": "Mike Koenig", "href": "1107-Electricity.html", "caption": "Electricity sound effect.", "id": "1107", "duration": 4.705375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1107&type=wav"} +{"title": "Chamber Decompressing", "description": "Sound of an air chamber decompressing. Could be used for a spaceship, or hyperbolic chamber, or cryogenic chamber, even a space shuttle, or star trek like sound.", "author": "Mike Koenig", "href": "1288-Chamber-Decompressing.html", "caption": "An air chamber is decompressing.", "id": "1288", "duration": 3.236, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1288&type=wav"} +{"title": "Draw Bow and Fire", "description": "Sound of a bow and arrow being drawn back the tension sound of the bow and string, and the the sound of the arrow as it is being fired.", "author": "Mike Koenig", "href": "2106-Draw-Bow-and-Fire.html", "caption": "A bow and arrow is being fired.", "id": "2106", "duration": 4.23571875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2106&type=wav"} +{"title": "Chinese Gong", "description": "Chinese Gong being hit and ringing sound. Long and loud gong hit sound from an asian temple.", "author": "Daniel Simon", "href": "2148-Chinese-Gong.html", "caption": "A gong is hit and rings loudly.", "id": "2148", "duration": 11.88375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2148&type=wav"} +{"title": "Poo Poo Mommy", "description": "A little girl asking her mother if she needs to use the bathroom or in her words poo poo? My daughter talking to my wife in all reality. Cute...cute...cute.", "author": "Mike Koenig", "href": "612-Poo-Poo-Mommy.html", "caption": "Someone's daughter is asking if her mother needs to use the bathroom.", "id": "612", "duration": 1.5128125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=612&type=wav"} +{"title": "Bat", "description": "A bat or chiroptera flying by. Cool for halloween, or a spooky movie.", "author": "Mike Koenig", "href": "1132-Bat.html", "caption": "A bat is flying.", "id": "1132", "duration": 1.95175, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1132&type=wav"} +{"title": "Slide Closed", "description": "Slide closed sound effect. Great for drawer or other such sliding apparatus.", "author": "Mike Koenig", "href": "1289-Slide-Closed.html", "caption": "Something slides closed.", "id": "1289", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1289&type=wav"} +{"title": "Alligator Hissing", "description": "Alligator hisses in warning at intruder", "author": "MIke Koenig", "href": "233-Alligator-Hissing.html", "caption": "An alligator is hissing in warning.", "id": "233", "duration": 11.353, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=233&type=wav"} +{"title": "Outdoor Carnival", "description": "A carnival outdoors near the games like ring toss.", "author": "Daniel Simon", "href": "2139-Outdoor-Carnival.html", "caption": "A carnival is happening.", "id": "2139", "duration": 42.2106875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2139&type=wav"} +{"title": "Sniper Rifle", "description": "Single shot from a .50 cal. sniper rifle", "author": "Kibblesbob", "href": "1788-Sniper-Rifle.html", "caption": "Single shot from a sniper rifle.", "id": "1788", "duration": 3.06909375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1788&type=wav"} +{"title": "Wooden Thump", "description": "Sound of a large wooden object thumping or bumping something or someone. Great for wooden impact sounds or wooden thuds.", "author": "Mike Koenig", "href": "1086-Wooden-Thump.html", "caption": "A large wooden object is thumping or bumping into something.", "id": "1086", "duration": 2.7748125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1086&type=wav"} +{"title": "Lightning Strike Summer Storm", "description": "A nice lightning strike during a recent storm at our house. Very crisp and clear.", "author": "fws.gov", "href": "318-Lightning-Strike-Summer-Storm.html", "caption": "Lightning is striking.", "id": "318", "duration": 27.03453125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=318&type=wav"} +{"title": "Eaglet Bird", "description": "Sound of a young Eaglet Bird. Great nature or wilderness sound effect.", "author": "PsychoBird", "href": "1478-Eaglet-Bird.html", "caption": "A young eaglet bird is making a sound.", "id": "1478", "duration": 2.40546875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1478&type=wav"} +{"title": "Electric Motor 2", "description": "Sound of an electric motor running. Motor sounds great for machines, robots, fork lifts, and similar sound needs", "author": "Mike Koenig", "href": "500-Electric-Motor-2.html", "caption": "An electric motor is running.", "id": "500", "duration": 5.825375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=500&type=wav"} +{"title": "Sad Male", "description": "Male vocal actor was hired to vocalize sad or crying. This is the guys audio use it for a movie or game or whatever. Just give us some credit please.", "author": "Mike Koenig", "href": "2014-Sad-Male.html", "caption": "Someone is crying.", "id": "2014", "duration": 24.392875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2014&type=wav"} +{"title": "Cat Meow", "description": "Cat meow or meowing cat sound effect. Great for your feline friend sounds. Use it for whatever you like.", "author": "Mike Koenig", "href": "1287-Cat-Meow.html", "caption": "A cat is meowing.", "id": "1287", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1287&type=wav"} +{"title": "Flesh Tearing", "description": "Flesh or ligaments tearing sound great for halloween or sports scene.", "author": "Mike Koenig", "href": "752-Flesh-Tearing.html", "caption": "Something is tearing.", "id": "752", "duration": 1.612, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=752&type=wav"} +{"title": "Silly Snoring", "description": "Some silly snoring.", "author": "Snore Man", "href": "1683-Silly-Snoring.html", "caption": "Someone is snoring.", "id": "1683", "duration": 7.2620625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1683&type=wav"} +{"title": "Change Light Bulb", "description": "Sound of an old school lightbulb being changed. Recording so clear you can hear the fillament shaking.", "author": "Mike Koenig", "href": "2116-Change-Light-Bulb.html", "caption": "An old lightbulb is being changed.", "id": "2116", "duration": 4.841375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2116&type=wav"} +{"title": "Children Playing", "description": "Children playing in a pool. An indoor pool. Requested by mignon.", "author": "Mike Koenig", "href": "460-Children-Playing.html", "caption": "Children are playing in a pool.", "id": "460", "duration": 52.14696875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=460&type=wav"} +{"title": "Radio Active", "description": "Toxic radio active sound effect with geiger counter clicks. Nice radio active sound effect requested by Rico.", "author": "Mike Koenig", "href": "1113-Radio-Active.html", "caption": "A toxic radio active sound effect with geiger counter clicks.", "id": "1113", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1113&type=wav"} +{"title": "Woop Woop", "description": "A woop woop cop car siren. Thats the sound of the police, thats what that is. Whoop Whoop, or woop woop sound effect requested by Jim REwed", "author": "Mike Koenig", "href": "1377-Woop-Woop.html", "caption": "A cop car siren is making a woop woop sound.", "id": "1377", "duration": 1.47965625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1377&type=wav"} +{"title": "Horse Neigh", "description": "Horse neighing western sound effect. Great for any of your equestrian sound effect requests.", "author": "Mike Koenig", "href": "1296-Horse-Neigh.html", "caption": "A horse is neighing.", "id": "1296", "duration": 1.4, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1296&type=wav"} +{"title": "7 Days", "description": "A Deep voice saying 7 Days good for horror films", "author": "KillahChipmunk", "href": "1692-7-Days.html", "caption": "Someone is saying a phrase.", "id": "1692", "duration": 2.31075, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1692&type=wav"} +{"title": "Freight Train", "description": "A freight-Train passing by with squeaky wheels. High quality. Great for a train scene in a movie or game.", "author": "Anonymous", "href": "1618-Freight-Train.html", "caption": "A train is passing by with squeaky wheels.", "id": "1618", "duration": 16.0391875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1618&type=wav"} +{"title": "Service Bell Help", "description": "Customer ringing service bell in need of help in a store.", "author": "Daniel Simion", "href": "2218-Service-Bell-Help.html", "caption": "Someone is ringing a bell.", "id": "2218", "duration": 1.5698125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2218&type=wav"} +{"title": "Tyrannosaurus Rex ", "description": "Sound of a tyrannosaurus rex roar or roaring 2x. Great for a monster or other sound as well.", "author": "mike koenig", "href": "1782-Tyrannosaurus-Rex-.html", "caption": "Tyrannosaurus rex roar sound effect, suitable for monster sounds.", "id": "1782", "duration": 4.587, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1782&type=wav"} +{"title": "Text Message Alert 2", "description": "A text message sound or SMS alert to use on your mobile device or tablet to replace your default sound.", "author": "Daniel Simion", "href": "2155-Text-Message-Alert-2.html", "caption": "A text message alert is heard.", "id": "2155", "duration": 2.5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2155&type=wav"} +{"title": "Large Servo Motor", "description": "Servo motor or robot arm sound effect. this is a very large elect5ical motor sound.", "author": "Smoothie", "href": "1440-Large-Servo-Motor.html", "caption": "A servo motor or robot arm is making a sound.", "id": "1440", "duration": 1.307125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1440&type=wav"} +{"title": "Cha Ching Register", "description": "Cash Register Sound Cha Ching the sound of money, what dollar signs sound like", "author": "Muska666", "href": "1997-Cha-Ching-Register.html", "caption": "A cash register is making a sound.", "id": "1997", "duration": 2.0778125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1997&type=wav"} +{"title": "Mosquito Buzzing", "description": "Mosquito buzzing or flying around our campsite. tiny bug sound created by flapping its wings", "author": "Mike Koenig", "href": "398-Mosquito-Buzzing.html", "caption": "A mosquito is buzzing around.", "id": "398", "duration": 3.9965, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=398&type=wav"} +{"title": "On The Farm", "description": "Sounds like bunches of animals on a farm. Mostly goats, sheep, and a few birds.", "author": "stephan", "href": "1632-On-The-Farm.html", "caption": "Animals are making noises on a farm.", "id": "1632", "duration": 7.7845, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1632&type=wav"} +{"title": "Busy Signal", "description": "Sound of a busy signal repeating 7 or 8 times. Recorded it from my office speaker phone.", "author": "Mike Koenig", "href": "1072-Busy-Signal.html", "caption": "A busy signal is repeating several times, possibly from an office speakerphone.", "id": "1072", "duration": 9.17190625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1072&type=wav"} +{"title": "Fire Crackers", "description": "Short burst of firecrackers in my parents back yard. They small pack of black cats to be precise.", "author": "Mike Koenig", "href": "711-Fire-Crackers.html", "caption": "Firecrackers are going off.", "id": "711", "duration": 2.1883125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=711&type=wav"} +{"title": "Squishy 2", "description": "Great squishy, or squelchy sound recorded. The sound was requested by Caroline Ford", "author": "Mike Koenig", "href": "512-Squishy-2.html", "caption": "A squishy or squelchy sound is heard.", "id": "512", "duration": 1.2655, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=512&type=wav"} +{"title": "Alien Spaceship UFO", "description": "UFO or Alien Spacecraft ambience. Sound either from inside the spacecraft, or outside as the craft is landing.", "author": "Daniel Simion", "href": "2213-Alien-Spaceship-UFO.html", "caption": "There is an unidentified spacecraft's sound.", "id": "2213", "duration": 16.806375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2213&type=wav"} +{"title": "Bubble Gum Pop", "description": "Popping of bubble gum sweet fruity chewing gum. Pops 2 times.", "author": "Natalie Wendt", "href": "1977-Bubble-Gum-Pop.html", "caption": "Bubble gum is popping.", "id": "1977", "duration": 2.757, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1977&type=wav"} +{"title": "Microwave", "description": "A microwave starting running for a few seconds and turning off.", "author": "KevanGC", "href": "1602-Microwave.html", "caption": "A microwave is running and turning off.", "id": "1602", "duration": 18.07675, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1602&type=wav"} +{"title": "Little Girl", "description": "My daughter saying ABCs on it. She wants to watch some phonics dvd on the tv.", "author": "Mike Koenig", "href": "541-Little-Girl.html", "caption": "A child is reciting the ABCs.", "id": "541", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=541&type=wav"} +{"title": "Poker Chips", "description": "Poker or Casino chips clicking and clacking as they hit each other. Poker counting chips.", "author": "Daniel Simion", "href": "2204-Poker-Chips.html", "caption": "Casino chips are clicking and clacking.", "id": "2204", "duration": 1.2760625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2204&type=wav"} +{"title": "Steam Engine Running", "description": "Sound of a steam engine on a ship or other place starting and running.", "author": "John", "href": "2102-Steam-Engine-Running.html", "caption": "A steam engine is starting and running.", "id": "2102", "duration": 59.6154375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2102&type=wav"} +{"title": "Metal Clang", "description": "Nice free metal impact sound effect. Great for a cartoon impact sound effect.", "author": "battlestar10", "href": "1781-Metal-Clang.html", "caption": "Cartoon impact sound effect, resembling metal impact.", "id": "1781", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1781&type=wav"} +{"title": "Hyena Laughing", "description": "Hyena Laughing a few different times. From African savanna.", "author": "Daniel Simion", "href": "2191-Hyena-Laughing.html", "caption": "A hyena is laughing.", "id": "2191", "duration": 18.13290625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2191&type=wav"} +{"title": "Dialing Phone Number", "description": "Dialing a Number a local number as it only has 7 digits.", "author": "Mike Koenig", "href": "418-Dialing-Phone-Number.html", "caption": "Someone is dialing a number.", "id": "418", "duration": 6.88646875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=418&type=wav"} +{"title": "Hickory Dickory Dock", "description": "A kids record player plays Hickory Dickory Dock record in a grainy plinky tone.", "author": "Daniel Simon", "href": "2141-Hickory-Dickory-Dock.html", "caption": "A record player is playing a nursery rhyme.", "id": "2141", "duration": 25.8329375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2141&type=wav"} +{"title": "Robot Computing", "description": "Sound of a classic sci-fi robot computing data. Youll know what i mean when you hear it. Requested by Bob Jackson", "author": "Mike Koenig", "href": "1276-Robot-Computing.html", "caption": "A sci-fi robot is computing data.", "id": "1276", "duration": 2.7811875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1276&type=wav"} +{"title": "Straw Slurp", "description": "The sound of someone slurping something through a straw 2. Good suction or drinking beverage sound.", "author": "Mike Koenig", "href": "860-Straw-Slurp.html", "caption": "Someone is slurping through a straw.", "id": "860", "duration": 5.6749375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=860&type=wav"} +{"title": "Osprey Bird Call", "description": "The sound of an osprey a or sea hawk. This sound is public domain.", "author": "Mike Koenig", "href": "1011-Osprey-Bird-Call.html", "caption": "An osprey or sea hawk is making a sound.", "id": "1011", "duration": 3.51303125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1011&type=wav"} +{"title": "Snow Ball", "description": "Packing a Snow Ball Through and Splat. Requested by Caroline Ford from TuxPaint", "author": "Mike Koenig", "href": "630-Snow-Ball.html", "caption": "Sound of packing snow ball and splatting.", "id": "630", "duration": 5.2310625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=630&type=wav"} +{"title": "416 Barrett Sniper 3x", "description": "Sound of a .416 barrett sniper rifle being fired 3 times in a row with a bit of reverb added so the gunshot was not truncated. sounds requested by trevor browning.", "author": "Mike Koenig", "href": "1880-416-Barrett-Sniper-3x.html", "caption": "A gun is firing.", "id": "1880", "duration": 4.5286875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1880&type=wav"} +{"title": "Helicopter Against Missile", "description": "Helicopter bringing shot down by a missile. This is as amazing piece of audio big thanks to Chester Barrett for this sound.", "author": "Chester Barrett", "href": "2023-Helicopter-Against-Missile.html", "caption": "A helicopter is crashing.", "id": "2023", "duration": 10.045125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2023&type=wav"} +{"title": "Cargo Train", "description": "Cargo train running over the tracks with some metal scraping sounds and more.", "author": "Stephan Schutze", "href": "1874-Cargo-Train.html", "caption": "A train is moving and making metal scraping sounds.", "id": "1874", "duration": 45.41496875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1874&type=wav"} +{"title": "Football Crowd", "description": "Football crowd at a sports center or sporting event. This sound effect is perfect because it doesnt have any announcer or music in the background and this makes it totally legit. football crowd requested by football allen", "author": "GoGo", "href": "1882-Football-Crowd.html", "caption": "Football crowd at a sporting event.", "id": "1882", "duration": 9.73653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1882&type=wav"} +{"title": "Baby Sneeze", "description": "Baby sneezing sound from high chair in kitchen", "author": "Mike Koenig", "href": "134-Baby-Sneeze.html", "caption": "A baby is sneezing in a high chair in a kitchen.", "id": "134", "duration": 1.35684375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=134&type=wav"} +{"title": "Car Explosion", "description": "Car Explosion or Car Bomb Sound Effect with glass and metal pieces hitting the cement", "author": "Mike Koenig", "href": "106-Car-Explosion.html", "caption": "A car is exploding or a car bomb is going off.", "id": "106", "duration": 3.5004375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=106&type=wav"} +{"title": "Pouring Rain On Cement", "description": "Pouring Rain on Cement during a april shower. I need to clean my gutters.", "author": "Mike Koenig", "href": "431-Pouring-Rain-On-Cement.html", "caption": "Rain is pouring on cement.", "id": "431", "duration": 20, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=431&type=wav"} +{"title": "Sunday Church Ambiance", "description": "Sunday Church Ambiance sound effect field recording. This is a great collage of church bells ringing, and small birds chirping ever so lightly. Great sound, and it public domain as well.", "author": "lezer", "href": "1264-Sunday-Church-Ambiance.html", "caption": "Birds are chirping.", "id": "1264", "duration": 32.64746875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1264&type=wav"} +{"title": "High Definition Machine Gun", "description": "Here is a high definition machine gun sound effect. We made it by our self. Use it in your movies if you want to.", "author": "WEL", "href": "1575-High-Definition-Machine-Gun.html", "caption": "A machine gun is firing.", "id": "1575", "duration": 7.3023125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1575&type=wav"} +{"title": "Man Coughing", "description": "A man coughing 2 short coughs. A cough 2x if you will.", "author": "Mike Koenig", "href": "501-Man-Coughing.html", "caption": "Someone is coughing.", "id": "501", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=501&type=wav"} +{"title": "Aww", "description": "Aww sound from a human thinking something is cute", "author": "tamskp", "href": "836-Aww.html", "caption": "Someone is making an \"aww\" sound.", "id": "836", "duration": 1.49040625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=836&type=wav"} +{"title": "Crash Large", "description": "Sound of a very large crash sound like a car, truck, or other impact sound with glass and metal.", "author": "Tony Phillips", "href": "1172-Crash-Large.html", "caption": "Large crash sound with glass and metal.", "id": "1172", "duration": 2.7450625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1172&type=wav"} +{"title": "Huge Crowd 3", "description": "Sound of another large crowd at a stadium with thousands of people screaming.", "author": "Mike Koenig", "href": "699-Huge-Crowd-3.html", "caption": "A large crowd is screaming.", "id": "699", "duration": 6.80953125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=699&type=wav"} +{"title": "Handcuffs Clicking", "description": "Sound of handcuffs being opened and snapped into place.", "author": "Daniel Simon", "href": "2143-Handcuffs-Clicking.html", "caption": "Handcuffs are being opened and snapped shut.", "id": "2143", "duration": 19.463875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2143&type=wav"} +{"title": "Smack Lips", "description": "Someone or something is hungry and smacking its lips in anticipation.", "author": "Mike Koenig", "href": "781-Smack-Lips.html", "caption": "Someone or something is smacking its lips.", "id": "781", "duration": 3.40175, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=781&type=wav"} +{"title": "Intro", "description": "This is created fully by me in adobe soundbooth using a fan. To be used in opening title sequence of your film or whatever you so desire. Also sound a bit like a large diesel truck idling.", "author": "Mark DiAngelo", "href": "1809-Intro.html", "caption": "A sound resembling an idling diesel truck is heard.", "id": "1809", "duration": 24.6675625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1809&type=wav"} +{"title": "Hole Punch", "description": "The sound of a hole punch punching holes in paper. Big thanks to Simon Craggs for another great sound!", "author": "Simon Craggs", "href": "1969-Hole-Punch.html", "caption": "A hole punch is punching holes.", "id": "1969", "duration": 1, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1969&type=wav"} +{"title": "Toxic Goo", "description": "Toxic goo or radioactive burn. Nice radio active sound effect requested by Rico.", "author": "Mike Koenig", "href": "1112-Toxic-Goo.html", "caption": "A toxic goo or radioactive burn sound effect.", "id": "1112", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1112&type=wav"} +{"title": "Clock Strikes Twelve", "description": "A clock striking twelve. Sound of a medium size grandfather clock striking 12 o'clock, or midnight. 12 chime hit sounds.", "author": "Clock Man", "href": "1617-Clock-Strikes-Twelve.html", "caption": "A clock is striking.", "id": "1617", "duration": 23.3379375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1617&type=wav"} +{"title": "Birds In Forest", "description": "Many birds in a forest. Two many bird noises to count really. Listen and see.", "author": "Mike Koenig", "href": "547-Birds-In-Forest.html", "caption": "Many birds are making noise in a forest.", "id": "547", "duration": 3.82634375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=547&type=wav"} +{"title": "Elephant", "description": "Elephant trumpeting sound effect. Great for a zoo, circus, or African savannah scene. This is Tarzans friend.", "author": "Mike Koenig", "href": "1140-Elephant.html", "caption": "An elephant is trumpeting.", "id": "1140", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1140&type=wav"} +{"title": "Automatic Machine Gun 3x", "description": "High caliber machine gun automatic fire 3 times. Great for war or battle sequences. Gun has some bass for extra kick sounds.", "author": "Mike Koenig", "href": "1201-Automatic-Machine-Gun-3x.html", "caption": "High caliber gunfire is heard.", "id": "1201", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1201&type=wav"} +{"title": "Guinea Pig", "description": "Guinea Pig making squeaking noises. Could also be used as hamster or other pet rodent. This is 1 happy guinea pig.", "author": "Daniel Simon", "href": "2144-Guinea-Pig.html", "caption": "A rodent is squeaking happily.", "id": "2144", "duration": 17.568375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2144&type=wav"} +{"title": "Fluorescent Light Humming", "description": "Sound of fluorescent light humming. Great for office ambiance or similar sound effects. Hum is caused by the electric ballasts vibrating.", "author": "Mike Koenig", "href": "1635-Fluorescent-Light-Humming.html", "caption": "A fluorescent light is humming.", "id": "1635", "duration": 10.89615625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1635&type=wav"} +{"title": "Winning Triumphal Fanfare", "description": "A brief victorious trumpet fanfare suitable for winning a game. Big thanks to John Stracke for posting this awesome sound!", "author": "John Stracke", "href": "1823-Winning-Triumphal-Fanfare.html", "caption": "A trumpet is playing a victorious fanfare.", "id": "1823", "duration": 5.37546875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1823&type=wav"} +{"title": "UFO Exit", "description": "UFO Exit or flying away", "author": "Mike Koenig", "href": "146-UFO-Exit.html", "caption": "An alien spacecraft is flying away.", "id": "146", "duration": 4.7804375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=146&type=wav"} +{"title": "Perfect Thunder Storm", "description": "The Perfect Thunder Storm sound effect. Great lightning and thunder. Clean crisp loud.. and free.", "author": "Mike Koenig", "href": "916-Perfect-Thunder-Storm.html", "caption": "A thunderstorm is happening.", "id": "916", "duration": 20.41034375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=916&type=wav"} +{"title": "Dying", "description": "Dying sound effect. Someone sound like they have one foot in the grave. Poor soul.", "author": "Mike Koenig", "href": "810-Dying.html", "caption": "A dying sound effect is heard.", "id": "810", "duration": 1.7995625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=810&type=wav"} +{"title": "Ricochet Rapid Fire", "description": "Rapid secession ricochet sound effects. More thanks to Grant Evans.", "author": "Grant Evans", "href": "2051-Ricochet-Rapid-Fire.html", "caption": "Ricochet sounds are heard.", "id": "2051", "duration": 40.410875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2051&type=wav"} +{"title": "Zombie Attack Walk", "description": "Zombie Attack Walking sound. Hes going to want to eat some human flesh soon. Zombie sounds requested by jordangiese.", "author": "NPS.gov", "href": "1030-Zombie-Attack-Walk.html", "caption": "A zombie is walking and attacking.", "id": "1030", "duration": 5.86959375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1030&type=wav"} +{"title": "Water Noise", "description": "Noise made from a water fountain. Great water or trickle sound effect.", "author": "Caroline Ford", "href": "1436-Water-Noise.html", "caption": "A water fountain is making a trickling sound.", "id": "1436", "duration": 17.95628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1436&type=wav"} +{"title": "Squelchy", "description": "Great squishy, or squelchy sound recorded. The sound was requested by Caroline Ford", "author": "Mike Koenig", "href": "514-Squelchy.html", "caption": "A squishy or squelchy sound is heard.", "id": "514", "duration": 1.18421875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=514&type=wav"} +{"title": "Shush", "description": "Shoosh or shush sound effect. someone asking for silence.", "author": "Mike Koenig", "href": "780-Shush.html", "caption": "Someone is asking for silence.", "id": "780", "duration": 1.5209375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=780&type=wav"} +{"title": "Human Heartbeat", "description": "Human heart beating loud and strong. Could also be used to show someone is worried, afraid, or injured.", "author": "Daniel Simion", "href": "2162-Human-Heartbeat.html", "caption": "A heart is beating strongly.", "id": "2162", "duration": 14.98978125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2162&type=wav"} +{"title": "Gun Loud", "description": "A Pistol Shot very loud and from counterstrike and so one", "author": "Soundmaster", "href": "1855-Gun-Loud.html", "caption": "A gun is firing.", "id": "1855", "duration": 2.2405625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1855&type=wav"} +{"title": "Frying Circuits", "description": "The sound of circuits in a machine frying, or just a normal cooking sound effect.", "author": "Mike Koenig", "href": "1054-Frying-Circuits.html", "caption": "Machines are frying.", "id": "1054", "duration": 1.9969375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1054&type=wav"} +{"title": "Laser Machine Gun", "description": "Futuristic laser machine gun sound. What machine guns may sound like in the future. Gun cock and then pulse cannon fired many times.", "author": "Mike Koenig", "href": "1774-Laser-Machine-Gun.html", "caption": "A futuristic gun is firing.", "id": "1774", "duration": 2.16784375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1774&type=wav"} +{"title": "Cutting Tree Limb", "description": "Sound of someone sawing or cutting a medium size tree limb off a tree. This sound like other sounds can also be used for other sound effects like a surgical or bone saw.", "author": "qubodup", "href": "1553-Cutting-Tree-Limb.html", "caption": "Someone is sawing a tree limb.", "id": "1553", "duration": 9.97334375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1553&type=wav"} +{"title": "Jungle", "description": "Nice jungle or tropical rain forest sounds with birds, and frogs.", "author": "Mike Koenig", "href": "1145-Jungle.html", "caption": "Jungle or tropical rainforest sounds with birds and frogs are playing.", "id": "1145", "duration": 5.4335, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1145&type=wav"} +{"title": "German Shepard", "description": "An agitated German Sheppard barking at his home. He is protecting his house like a good guard dog.", "author": "Daniel Simon", "href": "2146-German-Shepard.html", "caption": "A dog is barking.", "id": "2146", "duration": 17.1359375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2146&type=wav"} +{"title": "Many Wolves Howling", "description": "A very large wolf pack howling late at night before a hunt", "author": "fws.gov", "href": "278-Many-Wolves-Howling.html", "caption": "A wolf pack is howling.", "id": "278", "duration": 28.297, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=278&type=wav"} +{"title": "Count Of Three", "description": "Referee counting to three requested by Paul Young. Great sound for a wrestling or other match.", "author": "Mike Koenig", "href": "762-Count-Of-Three.html", "caption": "A referee is counting.", "id": "762", "duration": 3.14628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=762&type=wav"} +{"title": "Demon Girls Mockingbird", "description": "Little Demon Girl singing hush little baby dont say a word. Spooky crap.", "author": "Hello", "href": "2038-Demon-Girls-Mockingbird.html", "caption": "A demon girl is singing.", "id": "2038", "duration": 16.11034375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2038&type=wav"} +{"title": "Small Fireball", "description": "A small size fireball sound effect. Great for a wizard casting a spell, or a catapult launching a flaming ball over a castle wall.", "author": "Mike Koenig", "href": "1359-Small-Fireball.html", "caption": "A small fireball is made.", "id": "1359", "duration": 1.43228125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1359&type=wav"} +{"title": "Reeling In Catch", "description": "Reeling in catch. Great for a fishing game or scene to a movie. Recorded on an open faced reel. Go fishing.", "author": "Mike Koenig", "href": "1093-Reeling-In-Catch.html", "caption": "Someone is reeling in a catch while fishing.", "id": "1093", "duration": 5.12, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1093&type=wav"} +{"title": "Slow Breathing", "description": "Slow Breathing sound effect. Great for sleeping sound effects or meditation.", "author": "Mike Koenig", "href": "766-Slow-Breathing.html", "caption": "Someone is breathing slowly.", "id": "766", "duration": 20.693875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=766&type=wav"} +{"title": "TV Static", "description": "TV Static sound effect requested by Stephen via the request a sound button. This is 4 seconds of tv or radio static that can be looped for an even longer effect.", "author": "Mike Koenig", "href": "1611-TV-Static.html", "caption": "TV or radio static is playing.", "id": "1611", "duration": 4.0078125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1611&type=wav"} +{"title": "Santa Clause Jolly Laugh", "description": "Santa Clause Jolly Laugh. Merry Christmas from St Nick. Great Christmas sound for the kids around the holidays.", "author": "Mike Koenig", "href": "1255-Santa-Clause-Jolly-Laugh.html", "caption": "A person is laughing.", "id": "1255", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1255&type=wav"} +{"title": "Car Drive By", "description": "Single car driving by. Passing car recorded with Zoom H4.", "author": "Mike Koenig", "href": "532-Car-Drive-By.html", "caption": "A car is passing by.", "id": "532", "duration": 10.315875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=532&type=wav"} +{"title": "Text Message Alert 1", "description": "A text message sound or SMS alert to use on your mobile device or tablet to replace your default sound.", "author": "Daniel Simion", "href": "2154-Text-Message-Alert-1.html", "caption": "A text message alert is heard.", "id": "2154", "duration": 2, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2154&type=wav"} +{"title": "Can Opener Electric", "description": "Can Opener Electric sound could be used for many things like a remote control car sound, an electric motor sound, dental drill", "author": "Mike Koenig", "href": "94-Can-Opener-Electric.html", "caption": "An electric can opener is operating.", "id": "94", "duration": 6.2199375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=94&type=wav"} +{"title": "More Thunder", "description": "Recording of thunder and lightning sounds from a recent spring or early summer rain storm.", "author": "Mike Koenig", "href": "1854-More-Thunder.html", "caption": "Thunder and lightning are happening.", "id": "1854", "duration": 12.1684375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1854&type=wav"} +{"title": "Daydreaming", "description": "Tinkle hi pitch chime obsidian needles. Like a magic wand or metal wind chime. Could also represent a daydream or flashback. Thanks to Lisa Redfern for this awesome sound effect.", "author": "Lisa Redfern", "href": "2030-Daydreaming.html", "caption": "Hi pitch chimes are tinkling.", "id": "2030", "duration": 10.80271875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2030&type=wav"} +{"title": "UFO Landing", "description": "Imaginary alien craft descending fast and slowing down...electronically engineered oscillator and lfos included. Ableton device processing. One shot or loop possible.", "author": "Sonidor", "href": "2063-UFO-Landing.html", "caption": "An alien craft is descending.", "id": "2063", "duration": 3.6338125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2063&type=wav"} +{"title": "Buzz Fade In", "description": "Great clean buzz fading in sound generated by tone repetition.", "author": "Mike Koenig", "href": "1174-Buzz-Fade-In.html", "caption": "Clean buzz fading in from tone repetition.", "id": "1174", "duration": 2.06621875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1174&type=wav"} +{"title": "Marbles", "description": "Bag of glass marbels being spilled and rolled accross a table. Hear hundreds of marbles bounce off each other and roll down a gentle slope.", "author": "Daniel Simion", "href": "2199-Marbles.html", "caption": "Glass marbles are spilling and rolling on a table.", "id": "2199", "duration": 5.15, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2199&type=wav"} +{"title": "Purring Cat", "description": "Great cat purring sound effect recorded by Jim Mowatt in mono and mixed into stereo and trimmed by Mike Koenig", "author": "Mike Koenig", "href": "979-Purring-Cat.html", "caption": "A cat is purring.", "id": "979", "duration": 7.2011875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=979&type=wav"} +{"title": "M4A1 Single", "description": "A single shot from the M4A1 tactical assault rifle.", "author": "Kibblesbob", "href": "1804-M4A1-Single.html", "caption": "A single shot from a tactical assault rifle.", "id": "1804", "duration": 1.89678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1804&type=wav"} +{"title": "Squirrel", "description": "A ground squirrel sound recorded in Denali national forest. A public domain nature sound.", "author": "Mike Koenig", "href": "921-Squirrel.html", "caption": "A ground squirrel is making noise.", "id": "921", "duration": 7.65390625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=921&type=wav"} +{"title": "Turkey Gobble", "description": "Turkey gobble gobble gobble sound effect for thanksgiving. Perfect gobbling sound effect for the holidays.", "author": "bod", "href": "1737-Turkey-Gobble.html", "caption": "A turkey is gobbling.", "id": "1737", "duration": 1.3583125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1737&type=wav"} +{"title": "Ambulance", "description": "Ambulance siren passing by sound. I just happened to have my sound recorder within reach. The ambulance was going around 40mph and passed within feet of our vehicle. Top class sound.", "author": "Mike Koenig", "href": "558-Ambulance.html", "caption": "An ambulance siren is passing by.", "id": "558", "duration": 6.74996875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=558&type=wav"} +{"title": "Temple Bell Bigger", "description": "Great sound of a temple bell. This is the largest of 3 recorded. This sound was requested by dj sachin.", "author": "Mike Koenig", "href": "1474-Temple-Bell-Bigger.html", "caption": "A temple bell is ringing.", "id": "1474", "duration": 5.2899375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1474&type=wav"} +{"title": "Humpback Whale", "description": "Another great humpback whale song or sound effect recorded. This one is in the public domain however from the National Park Service!", "author": "Mike Koenig", "href": "744-Humpback-Whale.html", "caption": "A humpback whale is making sounds.", "id": "744", "duration": 27.67365625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=744&type=wav"} +{"title": "Winchester 1873 Single Shots", "description": "Winchester Model 1873 chambered in .44-40 cartridge. Gunfire in singles with ricochet sounds mixed in.", "author": "Grant Evans", "href": "2071-Winchester-1873-Single-Shots.html", "caption": "A gun is fired with ricochet sounds mixed in.", "id": "2071", "duration": 58.567625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2071&type=wav"} +{"title": "Church Bells Ringing", "description": "Large Church Bells Ringing on Sunday great quality sound", "author": "fws.gov", "href": "253-Church-Bells-Ringing.html", "caption": "Church bells are ringing.", "id": "253", "duration": 48.1335625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=253&type=wav"} +{"title": "Party Crowd", "description": "Large crowd at a party or other gathering talking about all sorts of things.", "author": "Daniel Simion", "href": "2163-Party-Crowd.html", "caption": "A large crowd is talking at a party or gathering.", "id": "2163", "duration": 56.38478125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2163&type=wav"} +{"title": "Zombies Eat Brains", "description": "The sound of a zombie wanting to eat your brains. Comon you know your not using them, so share with the zombie. Zombie sounds requested by jordangiese.", "author": "Mike Koenig", "href": "1027-Zombies-Eat-Brains.html", "caption": "A zombie is wanting to eat brains.", "id": "1027", "duration": 4.72884375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1027&type=wav"} +{"title": "Humpback Whale Call", "description": "Public domain Humpback Whale Call for nature sounds and ocean effects.", "author": "Caroline Ford", "href": "985-Humpback-Whale-Call.html", "caption": "A humpback whale is making a sound.", "id": "985", "duration": 7.501, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=985&type=wav"} +{"title": "Blast", "description": "A great explosion or blast sound for a movie or game sound effect. One large blast of great sound quality.", "author": "Mike Koenig", "href": "538-Blast.html", "caption": "A large explosion or blast is heard.", "id": "538", "duration": 2.17, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=538&type=wav"} +{"title": "Scary", "description": "This sound was used in old horror movies. It it really gives you the shivers.", "author": "Titus Calen", "href": "1814-Scary.html", "caption": "A sound used in old horror movies is causing shivers.", "id": "1814", "duration": 7.4356875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1814&type=wav"} +{"title": "Pissed Off Duck", "description": "Sound of a pissed off mallard duck mom protecting her ducklings from a larger adult male.", "author": "Mike Koenig", "href": "1859-Pissed-Off-Duck.html", "caption": "A duck is quacking.", "id": "1859", "duration": 2.92628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1859&type=wav"} +{"title": "Tattoo Gun", "description": "A great tattoo shop tattoo gun sound effect. Getting some ink done. Requested by anonymous user.", "author": "Mike Koenig", "href": "530-Tattoo-Gun.html", "caption": "A tattoo gun is buzzing.", "id": "530", "duration": 9.6955, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=530&type=wav"} +{"title": "Realistic Punch", "description": "Realistic Punch or punching sound effect. Sound by Mark DiAngelo. It took me a while to edit it and get it right. Hope you guys enjoy.", "author": "Mark DiAngelo", "href": "2069-Realistic-Punch.html", "caption": "A realistic punching sound is heard.", "id": "2069", "duration": 1.003875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2069&type=wav"} +{"title": "Industrial Sewing Machine", "description": "Industrial Sewing Machine from factory in the city", "author": "Mike Koenig", "href": "180-Industrial-Sewing-Machine.html", "caption": "An industrial sewing machine is operating in a factory.", "id": "180", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=180&type=wav"} +{"title": "Eat Chips", "description": "Sound of someone eating chips. Mmmm... im hungry for some food.", "author": "Mike Koenig", "href": "912-Eat-Chips.html", "caption": "Someone is eating chips.", "id": "912", "duration": 2.80746875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=912&type=wav"} +{"title": "Bean Fart", "description": "A tasty bean fart sound effect for all your gross needs and what not. Listener discretion is advised if you dont think its funny im sure your kid will.", "author": "Mike Koenig", "href": "1146-Bean-Fart.html", "caption": "There is a farting sound.", "id": "1146", "duration": 6.99575, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1146&type=wav"} +{"title": "Footsteps On Cement", "description": "Footsteps on cement with ambient oncoming cars nearby.", "author": "Tim Fryer", "href": "2057-Footsteps-On-Cement.html", "caption": "Footsteps are heard with nearby cars.", "id": "2057", "duration": 25.1156875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2057&type=wav"} +{"title": "Pouring Hot Tea", "description": "Very, very refreshing and delicious sound effect. Sound of hot water being poured for a cup of tea, coffee, or hot chocolate. Its tea time.", "author": "Cori Samuel", "href": "1244-Pouring-Hot-Tea.html", "caption": "Hot water is being poured.", "id": "1244", "duration": 7.798625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1244&type=wav"} +{"title": "Tolling Bell", "description": "Tolling bell rings or tolls 4 times. Can easily be looped. Large bell very ominous..", "author": "Daniel Simion", "href": "2206-Tolling-Bell.html", "caption": "A large bell is ringing.", "id": "2206", "duration": 20.12096875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2206&type=wav"} +{"title": "Automatic Machine Gun", "description": "High caliber machine gun automatic fire. Great for war or battle sequences. Gun has some bass for extra kick sounds.", "author": "Mike Koenig", "href": "1162-Automatic-Machine-Gun.html", "caption": "A machine gun is firing with strong bass.", "id": "1162", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1162&type=wav"} +{"title": "Double Barrel Shotgun Firing", "description": "Double barrel shotgun cocking both barrels and firing in succession. Requested by joeballs1025.", "author": "Mike Koenig", "href": "452-Double-Barrel-Shotgun-Firing.html", "caption": "A shotgun is firing.", "id": "452", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=452&type=wav"} +{"title": "Rainforest", "description": "Jungle rainforest sounds with frogs and other small animals. Great background or nature ambience.", "author": "Mike Koenig", "href": "435-Rainforest.html", "caption": "Ambience of a rainforest with animals.", "id": "435", "duration": 11.484375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=435&type=wav"} +{"title": "Turkey Gobble", "description": "Turkey gobbling sounds effect. this would be great a thanksgiving sound effect, and best of all its public domain.", "author": "bod", "href": "1663-Turkey-Gobble.html", "caption": "A turkey is gobbling.", "id": "1663", "duration": 1.16428125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1663&type=wav"} +{"title": "Bunker Buster Missile", "description": "The synthesized sound of a bunker buster missle incoming and blowing up the compound that you are in with debris like stones and bricks caving in around you. Enjoy this sound took about an hour to get right.", "author": "Mike Koenig", "href": "1847-Bunker-Buster-Missile.html", "caption": "A missile is exploding, causing debris to cave in.", "id": "1847", "duration": 15.97853125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1847&type=wav"} +{"title": "Large Metal Pan 2", "description": "A great metal pan hit sound 2 requested by Steve metal knock or hit can be used for many things.", "author": "BlastwaveFx.com", "href": "593-Large-Metal-Pan-2.html", "caption": "A pan is hit.", "id": "593", "duration": 1.43965625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=593&type=wav"} +{"title": "Dying Soul", "description": "A great wicked sound for death, souls, ghost, spooks, or just any scene with death or distruction.", "author": "Mike Koenig", "href": "370-Dying-Soul.html", "caption": "A sound for death or destruction is playing.", "id": "370", "duration": 4.05, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=370&type=wav"} +{"title": "Splitting Wood", "description": "Sound of someone splitting wood or chopping wood with an axe. requested by mel francis", "author": "Mike Koenig", "href": "1479-Splitting-Wood.html", "caption": "Someone is splitting or chopping wood with an axe.", "id": "1479", "duration": 7.52640625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1479&type=wav"} +{"title": "Little Girl Talking", "description": "My little girl telling me she wants to brush her teeth.", "author": "Mike Koenig", "href": "1729-Little-Girl-Talking.html", "caption": "A girl is talking.", "id": "1729", "duration": 3.61978125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1729&type=wav"} +{"title": "Kettle Whistle", "description": "This is the sound of a steam kettle or tea pot whistling for a few seconds.", "author": "Caroline Ford", "href": "1437-Kettle-Whistle.html", "caption": "A steam kettle or tea pot is whistling.", "id": "1437", "duration": 17.07828125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1437&type=wav"} +{"title": "Distant Thunder And Light Rain", "description": "The sound of a lightning bolt or thunder in the distance with light rain. Recorded during a summer rainstorm Aug 2009.", "author": "Caroline Ford", "href": "886-Distant-Thunder-And-Light-Rain.html", "caption": "Thunder and light rain in the distance.", "id": "886", "duration": 12.8624375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=886&type=wav"} +{"title": "Distant Thunder", "description": "The sound of a lightning bolt or thunder in the distance. Recorded during a summer rainstorm Aug 2009.", "author": "Mike Koenig", "href": "907-Distant-Thunder.html", "caption": "A thunder is heard in the distance.", "id": "907", "duration": 17.76328125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=907&type=wav"} +{"title": "Cracking Peanut Shells", "description": "Cracking Peanuts Shell Sounds, peanut shells, cracking, crack, shells,", "author": "Mike Koenig", "href": "135-Cracking-Peanut-Shells.html", "caption": "Peanut shells are cracking.", "id": "135", "duration": 1.685625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=135&type=wav"} +{"title": "Crisp Ocean Waves", "description": "Nice crisp and clean ocean wave sound effect normalized and eqd for a great 1 minute sound clip.", "author": "Mike Koenig", "href": "1936-Crisp-Ocean-Waves.html", "caption": "Ocean waves are crashing.", "id": "1936", "duration": 68.37471875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1936&type=wav"} +{"title": "MP5", "description": "MP5 small arms machine gun firing burst rounds. This sound was requested by Zayde.", "author": "ruin", "href": "1447-MP5.html", "caption": "A small arms machine gun is firing burst rounds.", "id": "1447", "duration": 1.67690625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1447&type=wav"} +{"title": "Water Churning", "description": "Water Wav. format HD quality Mark Diangelo. Could be used for a fish breaking surface, a person swimming, and other things.", "author": "Mark DiAngelo", "href": "1790-Water-Churning.html", "caption": "Water sound effect, suitable for various applications.", "id": "1790", "duration": 9.17234375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1790&type=wav"} +{"title": "Warbling Vireo", "description": "The Warbling Vireo or Vireo Gilvis is a small cute bird that is a tanish brown on top with a slightly lighter underbelly. It is Native to more parts of the Americas northern and central americals Their song is a cheerful warble similar to that of the P", "author": "Mike Koenig", "href": "1846-Warbling-Vireo.html", "caption": "A bird is warbling cheerfully.", "id": "1846", "duration": 3.55296875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1846&type=wav"} +{"title": "Purring", "description": "My cat purring again. Great purring cat sound effect!", "author": "Mike Koenig", "href": "1002-Purring.html", "caption": "A cat is purring.", "id": "1002", "duration": 4.1825, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1002&type=wav"} +{"title": "Engine Inside Car", "description": "Engine Rev Inside Car. Nice engine revving motor sound effect.", "author": "Mike Koenig", "href": "785-Engine-Inside-Car.html", "caption": "An engine is revving.", "id": "785", "duration": 5.5561875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=785&type=wav"} +{"title": "Ice Cubes In Cup", "description": "Sounds of someone putting ice cubes in a cup was a request HuiShurn Yong. These are public domains sounds so enjoy.", "author": "chocoholic", "href": "1545-Ice-Cubes-In-Cup.html", "caption": "Ice cubes are being put in a cup.", "id": "1545", "duration": 2.7811875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1545&type=wav"} +{"title": "Text Message Alert 3", "description": "A text message sound or SMS alert to use on your mobile device or tablet to replace your default sound.", "author": "Daniel Simion", "href": "2156-Text-Message-Alert-3.html", "caption": "A text message alert is heard.", "id": "2156", "duration": 2, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2156&type=wav"} +{"title": "Zombie Kill You", "description": "A Zombie Says Kill You! Zombie sounds requested by jordangiese.", "author": "Mike Koenig", "href": "1041-Zombie-Kill-You.html", "caption": "A zombie is threatening.", "id": "1041", "duration": 3.89078125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1041&type=wav"} +{"title": "Chicken", "description": "The sound of chickens on a farm making chicken noises or chicken sounds. Old McDonald had a farm. E I E I ooooo!", "author": "Mike Koenig", "href": "871-Chicken.html", "caption": "Chickens are making noises.", "id": "871", "duration": 5.266, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=871&type=wav"} +{"title": "Obama State Of The Union 2010", "description": "An exert of President Barack Obamas State of the Union speech. January 28th, 2010. Very moving.", "author": "Barack Obama", "href": "1360-Obama-State-Of-The-Union-2010.html", "caption": "Someone is giving a speech.", "id": "1360", "duration": 115.8235625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1360&type=wav"} +{"title": "Camera Shutter Click", "description": "Camera Shutter Click or shutter clicking sound.", "author": "BlastwaveFx.com", "href": "563-Camera-Shutter-Click.html", "caption": "A camera shutter is clicking.", "id": "563", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=563&type=wav"} +{"title": "Fast Sawing", "description": "Person using a small saw and sawing something fast. Rapid saw or cutting sound effect.", "author": "qubodup", "href": "1783-Fast-Sawing.html", "caption": "Rapid sawing sound effect.", "id": "1783", "duration": 7.79671875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1783&type=wav"} +{"title": "Intro Wind", "description": "Lol i literally just breathed into a mic. do whatever the heck you want with it. Thanks again to Mark for another sound :)", "author": "Mark DiAngelo", "href": "1912-Intro-Wind.html", "caption": "Someone breathes into a mic.", "id": "1912", "duration": 12.8174375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1912&type=wav"} +{"title": "Power Down", "description": "Power down sound effect is great for a power outage situational sound effect. Sound of a computer, control room, or factory being powered down. Sound requested by Shawn. Thanks Shawn!", "author": "Mike Koenig", "href": "1712-Power-Down.html", "caption": "A device is powering down.", "id": "1712", "duration": 10.29334375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1712&type=wav"} +{"title": "What You Eatin", "description": "My son asking what you eatin. Any time im chewing on something, even a mint, he wants to know what im eating, and then he wants it. Its just a funny sound clip.", "author": "Mike Koenig", "href": "1309-What-You-Eatin.html", "caption": "Someone's child is asking what another person is eating.", "id": "1309", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1309&type=wav"} +{"title": "Metal Debris Falling", "description": "The sound of metal debris falling after an impact or similar. Could be used after car or bomb explosion to emphasize the devastation.", "author": "Mike Koenig", "href": "1099-Metal-Debris-Falling.html", "caption": "Metal debris is falling after an impact.", "id": "1099", "duration": 2.55421875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1099&type=wav"} +{"title": "Frying Pan Impact", "description": "The sound of a frying pan impact or skillet hitting someone in the head, great for cartoon or movie scene. The sound was requested by Barry Holcomb. Thanks Barry this 2nd sound was pitched down and made even longer in case you didnt like the first one.", "author": "Mike Koenig", "href": "1005-Frying-Pan-Impact.html", "caption": "A skillet hits someone in the head, great for cartoon or movie scene.", "id": "1005", "duration": 1.95765625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1005&type=wav"} +{"title": "Temple Bell Huge", "description": "Great sound of a huge temple bell. This is the largest of 3 recorded. This sound was requested by dj sachin.", "author": "Mike Koenig", "href": "1506-Temple-Bell-Huge.html", "caption": "A temple bell is ringing.", "id": "1506", "duration": 5.32175, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1506&type=wav"} +{"title": "Killing A Fly With Flyswatter", "description": "Me killing an annoying fly with a flyswatter", "author": "fws.gov", "href": "312-Killing-A-Fly-With-Flyswatter.html", "caption": "A fly is being killed.", "id": "312", "duration": 1.85509375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=312&type=wav"} +{"title": "Crumbling", "description": "Sound of a small pile of something crumbling or disintegrating into nothing Sound was a request by Rykrdo Reed.", "author": "Mike Koenig", "href": "1886-Crumbling.html", "caption": "Sound of something crumbling or disintegrating.", "id": "1886", "duration": 1.65925, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1886&type=wav"} +{"title": "Eject Clip And Re-Load", "description": "Eject Clip and Re-Load Gun Sound great for military, battle, or war games and movie scenes.", "author": "Mike Koenig", "href": "414-Eject-Clip-And-Re-Load.html", "caption": "A gun is being reloaded.", "id": "414", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=414&type=wav"} +{"title": "Snow Mobile", "description": "The sound of a Snow Mobile driving in the snow. Great for wintertime or snow themed scenes or games. Recorded at a national park.", "author": "Mike Koenig", "href": "1023-Snow-Mobile.html", "caption": "A snowmobile is driving in the snow.", "id": "1023", "duration": 5.24234375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1023&type=wav"} +{"title": "Common Poorwill", "description": "Sound recording of a Common Poorwill native to cnaada. The Common Poorwill, Phalaenoptilus nuttallii, is a nocturnal bird of the family Caprimulgidae, the nightjars.", "author": "Mike Koenig", "href": "973-Common-Poorwill.html", "caption": "A Common Poorwill bird is chirping.", "id": "973", "duration": 6.5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=973&type=wav"} +{"title": "Large Metal Rusty Door", "description": "Sound of a large metal rusty door bein opened. Great for a haunted house or halloween sound effect. Really rusty hinges.", "author": "Stephan", "href": "1352-Large-Metal-Rusty-Door.html", "caption": "A door is being opened.", "id": "1352", "duration": 3.36396875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1352&type=wav"} +{"title": "Dark Laugh", "description": "Audio recording of me vocal has be pitch shifted. Spooky sound.", "author": "HopeinAwe", "href": "2001-Dark-Laugh.html", "caption": "Someone's voice is pitch-shifted.", "id": "2001", "duration": 3.16953125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2001&type=wav"} +{"title": "Opening Casket", "description": "Sound of a casket lid being opened at a funeral. very morbid and deathlike. any sound a casket makes is spooky and great for halloween or a horror movie. this of course could also be used for the sound of a crate or treasure chest opening.", "author": "Mike Koenig", "href": "1354-Opening-Casket.html", "caption": "A lid is being opened.", "id": "1354", "duration": 2.30928125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1354&type=wav"} +{"title": "Flesh And Bone Tearing ", "description": "The sound of flesh and bone tearing. We dug up a freshly buried body for this one. (not really dont go an call the cops) ripped the body into pieces.", "author": "Caroline Ford", "href": "943-Flesh-And-Bone-Tearing-.html", "caption": "Flesh and bone are tearing apart.", "id": "943", "duration": 4.53021875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=943&type=wav"} +{"title": "A-Z Vocalized", "description": "We hired a male vocal actor to say the alphabet letters a to z this the best quality audio you can get. Use this in your apps or whatever. Just give us credit and tell your friends.", "author": "Mike Koenig", "href": "2009-A-Z-Vocalized.html", "caption": "Someone is saying the alphabet.", "id": "2009", "duration": 35.01253125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2009&type=wav"} +{"title": "Dump Truck", "description": "Large dump truck on a construction site moving its load around and revving its engine and what not.", "author": "Mike Koenig", "href": "1909-Dump-Truck.html", "caption": "A dump truck revs its engine on a construction site.", "id": "1909", "duration": 9.22125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1909&type=wav"} +{"title": "Old Door Creaking", "description": "Sound of an old door creaking open. you can hear the stress and rust on the hitch as it swings open. Great for a haunted house or halloween sound effect.", "author": "Stephan", "href": "1362-Old-Door-Creaking.html", "caption": "A door is creaking open.", "id": "1362", "duration": 2.30928125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1362&type=wav"} +{"title": "Rain Ending", "description": "Semi heavy rain ending or rain clearing up sound effect. Great for for scene changes. Sound requested by tami.", "author": "nps.gov", "href": "910-Rain-Ending.html", "caption": "Semi-heavy rain is ending or clearing up.", "id": "910", "duration": 6.16834375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=910&type=wav"} +{"title": "Astronaut Breathing", "description": "Astronaut breathing in spacesuit on spacewalk.", "author": "Mike Koenig", "href": "143-Astronaut-Breathing.html", "caption": "An astronaut is breathing in a spacesuit on a spacewalk.", "id": "143", "duration": 19.75740625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=143&type=wav"} +{"title": "Plectron Tones", "description": "Sequence of fire alarm paging tones. great for alarm sound effects.", "author": "Brad", "href": "1946-Plectron-Tones.html", "caption": "Fire alarm paging tones are playing.", "id": "1946", "duration": 10.10940625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1946&type=wav"} +{"title": "Computer Error", "description": "Computer error sound effect for Vista or XP", "author": "Mike Koenig", "href": "172-Computer-Error.html", "caption": "A computer is making an error sound.", "id": "172", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=172&type=wav"} +{"title": "Beach Soundscape 3", "description": "A great Beach Soundscape recorded live at the outer banks of North Carolina. Waves crash, and you can even hear kids playing at certain parts.", "author": "Mike Koenig", "href": "551-Beach-Soundscape-3.html", "caption": "Waves crash and children play at a beach.", "id": "551", "duration": 42.80965625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=551&type=wav"} +{"title": "Count Off", "description": "Count off to 4 with drumsticks clicking. This sound usually precedes the beginning of a song.", "author": "Blake", "href": "1971-Count-Off.html", "caption": "Drumsticks are clicking.", "id": "1971", "duration": 1.67184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1971&type=wav"} +{"title": "Air Horn", "description": "Air Horn very loud and clear. Great annoying and loud sound effect.", "author": "Mike Koenig", "href": "1542-Air-Horn.html", "caption": "An air horn is blaring.", "id": "1542", "duration": 2.769, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1542&type=wav"} +{"title": "Cough", "description": "Coughing sound effect. Someone seems a little under the weather. Great for a hospital or doctor related project.", "author": "Mike Koenig", "href": "855-Cough.html", "caption": "Someone is coughing.", "id": "855", "duration": 1.526375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=855&type=wav"} +{"title": "Horror Ambiance", "description": "Great horror movie or game sound effects ambiance. Nice dark sounds echo in and out from zombies or monsters.", "author": "Mike Koenig", "href": "1709-Horror-Ambiance.html", "caption": "Dark sounds echo from zombies or monsters.", "id": "1709", "duration": 19.88353125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1709&type=wav"} +{"title": "Zombie Gibberish", "description": "Zombie Gibberish talking sounds. Great for a game. Zombie sounds requested by jordangiese.", "author": "Mike Koenig", "href": "1031-Zombie-Gibberish.html", "caption": "A zombie is talking gibberish.", "id": "1031", "duration": 2.64421875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1031&type=wav"} +{"title": "Child Scream", "description": "Child Screaming sound effect. The sound of a kid screaming. It is actually my daughter. She sometimes does audio for me.", "author": "Mike Koenig", "href": "1102-Child-Scream.html", "caption": "Someone is screaming.", "id": "1102", "duration": 1.4995, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1102&type=wav"} +{"title": "50 Cal Machine Gun", "description": "50 Cal Machine Gun. Gunfire during a gunfight in Iraq, or Afghanistan. Great battle sound effects.", "author": "JKirsch", "href": "1386-50-Cal-Machine-Gun.html", "caption": "A machine gun is firing during a gunfight.", "id": "1386", "duration": 2.21753125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1386&type=wav"} +{"title": "Spinning", "description": "A great spinning sound made from spinning a small tub of playdough around in circles on our kitchen table.", "author": "BlastwaveFx.com", "href": "586-Spinning.html", "caption": "Playdough is spinning.", "id": "586", "duration": 2.4159375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=586&type=wav"} +{"title": "Gag", "description": "A person making a gag or choke sound effect. Sick or dying sound effect.", "author": "Mike Koenig", "href": "774-Gag.html", "caption": "Someone is gagging or choking.", "id": "774", "duration": 1.172625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=774&type=wav"} +{"title": "Text Message Alert 4", "description": "A text message sound or SMS alert to use on your mobile device or tablet to replace your default sound.", "author": "Daniel Simion", "href": "2157-Text-Message-Alert-4.html", "caption": "A text message alert is heard.", "id": "2157", "duration": 2.62503125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2157&type=wav"} +{"title": "Super Growl", "description": "The ultimate animal growl evil growling sound effect. Pushed the bass up on this to make it even scarier! Great for Halloween or horror movies!", "author": "Mike Koenig", "href": "815-Super-Growl.html", "caption": "An animal is growling.", "id": "815", "duration": 10.28646875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=815&type=wav"} +{"title": "Old Fashion Door Bell", "description": "Old Fashion Door Bell or door buzzer ringing a few times.", "author": "Daniel Simion", "href": "2160-Old-Fashion-Door-Bell.html", "caption": "A doorbell is ringing.", "id": "2160", "duration": 10.672, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2160&type=wav"} +{"title": "Elk Bellowing In Forest", "description": "Elk Bellows from bellowing elk in the forest recorded live from fws.gov", "author": "Mike Koenig", "href": "245-Elk-Bellowing-In-Forest.html", "caption": "Elk are bellowing in the forest.", "id": "245", "duration": 6.337, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=245&type=wav"} +{"title": "Trash Bag 2", "description": "Large trash bag also called a garbage bag around here. Bag is being taken out of box and adjusted moved around a bit.", "author": "Mike Koenig", "href": "2119-Trash-Bag-2.html", "caption": "A bag is being adjusted.", "id": "2119", "duration": 26.54621875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2119&type=wav"} +{"title": "Screaming Hawk", "description": "Perfect screaming hawk loud sound effect. Screaming hawk deer whistle", "author": "PsychoBird", "href": "1517-Screaming-Hawk.html", "caption": "A hawk is screaming.", "id": "1517", "duration": 3.390125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1517&type=wav"} +{"title": "Water Down Gutter 2", "description": "Water running down gutter drain 2. Cool gargling swishing water sound from the front of my house.", "author": "Mike Koenig", "href": "433-Water-Down-Gutter-2.html", "caption": "Water is running down a gutter.", "id": "433", "duration": 15, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=433&type=wav"} +{"title": "Abcdefg", "description": "Son saying his abcs to G and then stopping. He can say them all but he stopped.", "author": "Mike Koenig", "href": "1895-Abcdefg.html", "caption": "Son saying his ABCs before stopping.", "id": "1895", "duration": 2.81621875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1895&type=wav"} +{"title": "Cat Purring", "description": "The sound of a cat Cat Purring great feline happy cat effect", "author": "Stephan", "href": "707-Cat-Purring.html", "caption": "A cat is purring.", "id": "707", "duration": 11.089125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=707&type=wav"} +{"title": "Straw Slurp Normal", "description": "The sound of someone slurping something through a straw. Good suction or drinking beverage sound.", "author": "Mike Koenig", "href": "856-Straw-Slurp-Normal.html", "caption": "Someone is slurping through a straw.", "id": "856", "duration": 3.66878125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=856&type=wav"} +{"title": "Sounds Of War V 10", "description": "A couple of clips i put together to simulate a war-like exchange of fire. this is an epic battle sound effect. sounds like you are right in the middle. thanks Odd Fox!", "author": "ODD-FOX", "href": "1991-Sounds-Of-War-V-10.html", "caption": "There is a war-like exchange of fire.", "id": "1991", "duration": 19.38521875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1991&type=wav"} +{"title": "Tension Wood Stress", "description": "Sound of wood being stressed and popping. Could be a bow and arrow, could be a ships mast, could be a wood floor. Whatever you care to use it for.", "author": "Mike Koenig", "href": "2109-Tension-Wood-Stress.html", "caption": "Wood is being stressed and popping.", "id": "2109", "duration": 2.11990625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2109&type=wav"} +{"title": "Gear Shift Into Drive", "description": "Sound of a vehicles gear shifting into drive. Auto or car sound.", "author": "Mike Koenig", "href": "932-Gear-Shift-Into-Drive.html", "caption": "A vehicle's gear is shifting into drive.", "id": "932", "duration": 1.3505, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=932&type=wav"} +{"title": "Cop Car Siren", "description": "A cop car siren passed me on the way home, so i recorded it. Nice for a cop, or car chase, or just some city sound.", "author": "Mike Koenig", "href": "1058-Cop-Car-Siren.html", "caption": "A siren is blaring.", "id": "1058", "duration": 5.0735625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1058&type=wav"} +{"title": "Classroom Ambiance", "description": "Classroom Ambiance sound effect recorded inside school classroom. Could also be a classroom walla track.", "author": "rcrossley", "href": "1561-Classroom-Ambiance.html", "caption": "Classroom ambiance is recorded.", "id": "1561", "duration": 20.3070625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1561&type=wav"} +{"title": "Train Approach N Pass", "description": "This is an awesome sound clip of a train honking its horn approaching passing and then some metal grinding from its wheels. The preview is shorter than the full version. For full version click on the .ZIP FILE option.", "author": "Mike Koenig", "href": "1693-Train-Approach-N-Pass.html", "caption": "A train is honking its horn and the wheels are grinding.", "id": "1693", "duration": 15, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1693&type=wav"} +{"title": "Baby Crying", "description": "The sound of a baby crying. Its actually my son.. he is hungry, and we are waiting in the drive through for food. Hes not to patient lol", "author": "Mike Koenig", "href": "557-Baby-Crying.html", "caption": "A baby is crying.", "id": "557", "duration": 8.0666875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=557&type=wav"} +{"title": "Uh Oh Baby", "description": "Cute little baby my son 2 years old saying Uh Oh! Its great for tons of reasons. Good sound for any library.", "author": "Mike Koenig", "href": "618-Uh-Oh-Baby.html", "caption": "Someone's son is saying \"uh oh\".", "id": "618", "duration": 1.2384375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=618&type=wav"} +{"title": "Old Car Starting", "description": "Old car engine starting up slowly and running. Very old model t car.", "author": "Daniel Simion", "href": "2214-Old-Car-Starting.html", "caption": "An old car's engine is starting and running.", "id": "2214", "duration": 20.41984375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2214&type=wav"} +{"title": "Dying Robot", "description": "Sound of a robot dying, or shorting out.", "author": "wildcat", "href": "1361-Dying-Robot.html", "caption": "A robot is malfunctioning.", "id": "1361", "duration": 3.66671875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1361&type=wav"} +{"title": "Burp 2x", "description": "Me burping 2x in succession. Soda burp if I recall correctly.", "author": "Mike Koenig", "href": "645-Burp-2x.html", "caption": "Someone is burping.", "id": "645", "duration": 1.40871875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=645&type=wav"} +{"title": "Formula 1 Racing", "description": "Field recording at a Formula 1 race track. At the FIA Formula One World Championship. These are some of the fastest cars in the world.", "author": "Daniel Simion", "href": "2188-Formula-1-Racing.html", "caption": "Cars are racing.", "id": "2188", "duration": 17.6684375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2188&type=wav"} +{"title": "Metroid Door", "description": "The sound the door makes in metroid. Could also be used for a power up or morphing sound effect.", "author": "Brandino480", "href": "1858-Metroid-Door.html", "caption": "A door is opening.", "id": "1858", "duration": 1.06990625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1858&type=wav"} +{"title": "Hiccup", "description": "Hiccuping sound effect. Some drunk hiccup at a bar or just walking the street.", "author": "Mike Koenig", "href": "861-Hiccup.html", "caption": "Someone is hiccuping.", "id": "861", "duration": 1.26721875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=861&type=wav"} +{"title": "Laser Gun", "description": "Laser gun or death ray powering up and firing a blast. Nice sci-fi sound effect.", "author": "Mike Koenig", "href": "1769-Laser-Gun.html", "caption": "A laser gun is powering up and firing.", "id": "1769", "duration": 1.61565625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1769&type=wav"} +{"title": "Pin Dropping", "description": "Sound of a pin dropping a modification of the original pin drop sound effect we posted.", "author": "Brian Rocca", "href": "1992-Pin-Dropping.html", "caption": "A pin is dropping.", "id": "1992", "duration": 1.2915, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1992&type=wav"} +{"title": "Small Electrical Motor", "description": "Small electrical motor or robot arm sound effect. this is a very small elect5ical motor sound. Good for a robot finger or head rotation sound.", "author": "Smoothie", "href": "1427-Small-Electrical-Motor.html", "caption": "An electrical motor or robot arm is making noise.", "id": "1427", "duration": 1.3304375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1427&type=wav"} +{"title": "Suicide Bomber 2", "description": "Another suicide bomber is at it again this time the poor guy sees him coming and tries to stop him. Male vocals credit goes to Ragdoll485.", "author": "Mike Koenig", "href": "1914-Suicide-Bomber-2.html", "caption": "Someone tries to stop a suicide bomber.", "id": "1914", "duration": 9.25, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1914&type=wav"} +{"title": "Super Burp", "description": "Super Burp to the rescue. Super burp is the mother of all burps.", "author": "Glaneur de Sons", "href": "403-Super-Burp.html", "caption": "Someone is burping loudly.", "id": "403", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=403&type=wav"} +{"title": "Bull", "description": "The sound of a mad bull. He seems a bit angry and maybe even pissed.", "author": "Mike Koenig", "href": "755-Bull.html", "caption": "A bull is making angry sounds.", "id": "755", "duration": 2.1899375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=755&type=wav"} +{"title": "Evil Laughs", "description": "4 evil laughs dark and deep with a bit of reberb added for that extra dark and dank dungeon like sound. Alsmost sounds like Darth Vader but these are 100 percent original.", "author": "Mike Koenig", "href": "1704-Evil-Laughs.html", "caption": "Evil laughs are heard.", "id": "1704", "duration": 16.59375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1704&type=wav"} +{"title": "Alien Machine Gun", "description": "For alien or si-fi movies. nice laser or electronic alien-like gun pulses. Good for sci-fi films.", "author": "Matt Cutillo", "href": "1802-Alien-Machine-Gun.html", "caption": "Laser or electronic gun pulses are heard.", "id": "1802", "duration": 2.1561875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1802&type=wav"} +{"title": "Closing Drawer", "description": "The sound of someone closing a drawer of some sort. Great kitchen sound as well.", "author": "Mike Koenig", "href": "934-Closing-Drawer.html", "caption": "Someone is closing a drawer.", "id": "934", "duration": 1.687125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=934&type=wav"} +{"title": "Cutlery Drawer", "description": "Kitchen sound effects. Pots and pans, dishes requested by Steve", "author": "BlastwaveFx.com", "href": "591-Cutlery-Drawer.html", "caption": "Kitchen items are clattering.", "id": "591", "duration": 3.73553125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=591&type=wav"} +{"title": "Gun Loaded Cocked And Shot", "description": "A gun loaded cocked and shot.", "author": "KP", "href": "1613-Gun-Loaded-Cocked-And-Shot.html", "caption": "A gun is being fired.", "id": "1613", "duration": 5.60434375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1613&type=wav"} +{"title": "Breathing Weird", "description": "Breathing Weird a little spacey sounding almost sounds like an alien.", "author": "Mike Koenig", "href": "50-Breathing-Weird.html", "caption": "Someone is breathing weirdly.", "id": "50", "duration": 21.007625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=50&type=wav"} +{"title": "I Love You Daddy", "description": "My son saying i love you daddy. Really cute bit of sound for me to look back on in the future.", "author": "Mike Koenig", "href": "1292-I-Love-You-Daddy.html", "caption": "Someone says \"I love you daddy\".", "id": "1292", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1292&type=wav"} +{"title": "Kitchen Sink", "description": "Kitchen sink sound of water running down a drain and moving around a sink or tap.", "author": "Caroline Ford", "href": "1439-Kitchen-Sink.html", "caption": "Water is running down a kitchen sink's drain and moving around the sink or tap.", "id": "1439", "duration": 12.78115625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1439&type=wav"} +{"title": "Police 357 Magnum Loading", "description": "Police issue 357 Magnum chamber loading with 6 bullets. This gun was my Grandfathers who got it in the 1970s.", "author": "Mike Koenig", "href": "413-Police-357-Magnum-Loading.html", "caption": "A gun is being loaded.", "id": "413", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=413&type=wav"} +{"title": "Woodpecker Tapping Tree", "description": "Woodpecker tapping a large tree in a forest", "author": "Natalie", "href": "280-Woodpecker-Tapping-Tree.html", "caption": "A woodpecker is tapping.", "id": "280", "duration": 27.913, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=280&type=wav"} +{"title": "Surgery", "description": "Great hospital surgery sound effects. Brain, or open heart surgery. Just download and have at it.", "author": "Caroline Ford", "href": "922-Surgery.html", "caption": "Hospital surgery sound effects.", "id": "922", "duration": 8.963375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=922&type=wav"} +{"title": "Baby Music Box", "description": "Baby music box or a musical box being wound or cranked and then released to play a comforting baby lullaby.", "author": "Daniel Simion", "href": "2196-Baby-Music-Box.html", "caption": "A music box is playing.", "id": "2196", "duration": 18.57275, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2196&type=wav"} +{"title": "Elk Bellowing In Forest 2", "description": "Elk Bellows from bellowing elk in the forest recorded live from fws.gov #2", "author": "fws.gov", "href": "246-Elk-Bellowing-In-Forest-2.html", "caption": "Elk are bellowing in the forest.", "id": "246", "duration": 17.977, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=246&type=wav"} +{"title": "Clock Chimes 4x", "description": "Long and clear clock chimes times 4. Could easily be chopped up and used as many times as you needed the chime for.", "author": "Daniel Simion", "href": "2170-Clock-Chimes-4x.html", "caption": "A clock is chiming.", "id": "2170", "duration": 13.27490625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2170&type=wav"} +{"title": "Power Failure", "description": "Power failure sound effect is great for a power outage situational sound effect. Sound requested by Shawn. Thanks Shawn!", "author": "Mike Koenig", "href": "1610-Power-Failure.html", "caption": "A power failure sound effect.", "id": "1610", "duration": 1.75196875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1610&type=wav"} +{"title": "Engine Rev Inside Car", "description": "Engine Rev Inside Car. Nice engine revving motor sound effect.", "author": "Mike Koenig", "href": "804-Engine-Rev-Inside-Car.html", "caption": "An engine is revving.", "id": "804", "duration": 3.1736875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=804&type=wav"} +{"title": "Long Suction", "description": "A very long suction. Great for any number of sound effects. From a vacuum, to a dental office to a drinking straw, or the sound of an air leak", "author": "Mike Koenig", "href": "812-Long-Suction.html", "caption": "A suction is heard.", "id": "812", "duration": 4.35375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=812&type=wav"} +{"title": "Pump Shotgun", "description": "Sound of the Mossburg 500 Pistol grip 20inch (near sawed off) tactical shotgun pumping a round into the chamber. Its that classic pump shotgun sound that says, hey i mean business. Youve all heard this sound before im sure.", "author": "Mike Koenig", "href": "1401-Pump-Shotgun.html", "caption": "A shotgun is being pumped.", "id": "1401", "duration": 1.48609375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1401&type=wav"} +{"title": "Helicopter Hovering", "description": "Helicopter mid size hovering overhead for 20 seconds. Can be looped easily for even longer sound effects.", "author": "Mike Koenig", "href": "1894-Helicopter-Hovering.html", "caption": "A helicopter is hovering overhead.", "id": "1894", "duration": 20, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1894&type=wav"} +{"title": "Martian Death Ray", "description": "Ray gun or alien death ray zapping and killing the humans who are attacking. Great sci fi sound.", "author": "Mike Koenig", "href": "1885-Martian-Death-Ray.html", "caption": "A ray gun or alien death ray is zapping.", "id": "1885", "duration": 1.3991875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1885&type=wav"} +{"title": "P90 Machine Gun Fire", "description": "P90 designed by Belgian firearms manufacturer FN Herstal being fired. P90 gunfire was requested by EVAN.", "author": "ruin", "href": "1449-P90-Machine-Gun-Fire.html", "caption": "A firearm is being fired.", "id": "1449", "duration": 2.17071875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1449&type=wav"} +{"title": "Pooping", "description": "Pooping sound dropping kids off at pool. Splish splash.", "author": "Mike Koenig", "href": "430-Pooping.html", "caption": "Someone is pooping.", "id": "430", "duration": 6.87103125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=430&type=wav"} +{"title": "Thunder HD", "description": "AWWW heres another sound for you guys to toy with. another storm hit and i was there with my mic. Thanks again to Mark for another sound :)", "author": "Mark DiAngelo", "href": "1913-Thunder-HD.html", "caption": "A storm is recorded.", "id": "1913", "duration": 8.8985, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1913&type=wav"} +{"title": "Boxing Punches", "description": "Punching mma fight sounds 1 2 3 combo punch", "author": "Mike Koenig", "href": "177-Boxing-Punches.html", "caption": "Someone is punching in a fight.", "id": "177", "duration": 1.01153125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=177&type=wav"} +{"title": "Slow Motion Warp", "description": "A slow motion sound when an action is being performed", "author": "CouchMango", "href": "2036-Slow-Motion-Warp.html", "caption": "An action is being performed in slow motion.", "id": "2036", "duration": 3.445, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2036&type=wav"} +{"title": "Mystic Chanting 1", "description": "Some kind of mystic chanting", "author": "Marianne Gagnon", "href": "1671-Mystic-Chanting-1.html", "caption": "There is mystic chanting.", "id": "1671", "duration": 1.55575, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1671&type=wav"} +{"title": "Kid Laugh", "description": "Kid laugh short only a few seconds. Recorded by tickling my son.", "author": "Mike Koenig", "href": "2026-Kid-Laugh.html", "caption": "A kid is laughing.", "id": "2026", "duration": 2.20775, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2026&type=wav"} +{"title": "Typewriter And Bell", "description": "Great typing or typewriter and bell ding sounds for a news or office scene in a movie, game, or powerpoint presentation.", "author": "Mike Koenig", "href": "853-Typewriter-And-Bell.html", "caption": "Typing and bell ding sounds are heard.", "id": "853", "duration": 12.595625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=853&type=wav"} +{"title": "Drawing Bow Back", "description": "Sound of a bow and arrow being drawn back the tension sound of the bow and string.", "author": "Mike Koenig", "href": "2107-Drawing-Bow-Back.html", "caption": "A bow and arrow is being drawn back.", "id": "2107", "duration": 2.8235, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2107&type=wav"} +{"title": "Bubbling Cauldron", "description": "Cauldron Bubbling sound made by recording bubbling water and rice mixture great for Halloween or witch movie", "author": "Mike Koenig", "href": "51-Bubbling-Cauldron.html", "caption": "A cauldron is bubbling.", "id": "51", "duration": 8.99284375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=51&type=wav"} +{"title": "Tongue Rolling", "description": "Rolling sound you make with your tongue. Nice Hispanic tongue rolling sound effect.", "author": "Ana C Ibanez", "href": "1993-Tongue-Rolling.html", "caption": "Someone is making a tongue-rolling sound.", "id": "1993", "duration": 26.4500625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1993&type=wav"} +{"title": "Hitting Metal", "description": "Effect banging on metal with depth", "author": "Douglas Vicente", "href": "1750-Hitting-Metal.html", "caption": "A metal object is being banged.", "id": "1750", "duration": 2.845, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1750&type=wav"} +{"title": "Sleigh Bells Ringing", "description": "The sound of sleigh bells ringing. Great Christmas Sound Effect.", "author": "Mike Koenig", "href": "1256-Sleigh-Bells-Ringing.html", "caption": "Bells are ringing.", "id": "1256", "duration": 4.78459375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1256&type=wav"} +{"title": "Fly Buzzing", "description": "House Fly buzzing with other flies around the house. very annoying to say the least.", "author": "Mike Koenig", "href": "396-Fly-Buzzing.html", "caption": "Some house flies are buzzing.", "id": "396", "duration": 4.097625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=396&type=wav"} +{"title": "Devil Dog Crazy", "description": "Some crazy devil dog growling at someone or something. Could be a guard or attack dog.", "author": "Mike Koenig", "href": "1523-Devil-Dog-Crazy.html", "caption": "A dog is growling.", "id": "1523", "duration": 8.5376875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1523&type=wav"} +{"title": "Hello", "description": "Hello wav or mp3 spoken word sound from male.", "author": "Mike Koenig", "href": "678-Hello.html", "caption": "A male voice is saying hello.", "id": "678", "duration": 1.081625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=678&type=wav"} +{"title": "10 Second Applause", "description": "A great 5 second applause or canned laughter and crowd responses. This sound was cut from a public domain speech and converted to stereo, and then mastered for best quality.", "author": "nps.gov", "href": "989-10-Second-Applause.html", "caption": "Applause or canned laughter and crowd responses.", "id": "989", "duration": 15, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=989&type=wav"} +{"title": "Hard Drive Clicking", "description": "Hard drive clicking as it is dying. End of life computer hard drive crashing.", "author": "Robertv", "href": "1951-Hard-Drive-Clicking.html", "caption": "A hard drive is clicking.", "id": "1951", "duration": 76.5006875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1951&type=wav"} +{"title": "Sniff Short", "description": "Sniff or smelling sound effect. Sniffing sound. Breathe sounds as well.", "author": "Mike Koenig", "href": "958-Sniff-Short.html", "caption": "Someone is sniffing.", "id": "958", "duration": 1.34678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=958&type=wav"} +{"title": "Fart Noises", "description": "Some really great fart noises and gross sound clips.", "author": "Mike Koenig", "href": "797-Fart-Noises.html", "caption": "Various fart noises.", "id": "797", "duration": 3.431125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=797&type=wav"} +{"title": "Im Superman", "description": "My son is superman at least that is what he saying he tells me im superman im super strong and i have muscles", "author": "Mike Koenig", "href": "1865-Im-Superman.html", "caption": "Someone is talking about their child pretending to be a superhero.", "id": "1865", "duration": 9.33990625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1865&type=wav"} +{"title": "Creaking Door Spooky", "description": "Best creaking door sound effect. A great squeaking door or scary door opening slowly sound for haunted house or Halloween.", "author": "stephan", "href": "1717-Creaking-Door-Spooky.html", "caption": "A door is creaking.", "id": "1717", "duration": 2.620625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1717&type=wav"} +{"title": "Roll Dice 2", "description": "Rolling Dice 2 on the table during a game", "author": "Mike Koenig", "href": "181-Roll-Dice-2.html", "caption": "Dice are being rolled on a table during a game.", "id": "181", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=181&type=wav"} +{"title": "Cinematic Harsh Light", "description": "Cinematic atmospheric hard light sound effect. Spooky sound - created by Colin Enger. Great for a movie trailer.", "author": "Colin Enger", "href": "2092-Cinematic-Harsh-Light.html", "caption": "A spooky atmospheric sound effect is created.", "id": "2092", "duration": 28.99575, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2092&type=wav"} +{"title": "Crowd At Carnival", "description": "Sound of a crowd or large mass of people at a carnival celebration!", "author": "stephan", "href": "1555-Crowd-At-Carnival.html", "caption": "A crowd is cheering.", "id": "1555", "duration": 14.80559375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1555&type=wav"} +{"title": "Door Bell", "description": "Door Bell ding dong sound from my house", "author": "Mike Koenig", "href": "165-Door-Bell.html", "caption": "A doorbell is ringing.", "id": "165", "duration": 2.9913125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=165&type=wav"} +{"title": "News Intro", "description": "News show intro or newsroom intro music played before broadcast begins.", "author": "Maximilien", "href": "2041-News-Intro.html", "caption": "News intro music is playing.", "id": "2041", "duration": 5.2285, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2041&type=wav"} +{"title": "House On Fire", "description": "Sound of a house or barn on fire. Sound effect perspective is from within the burning building.", "author": "Mike Koenig", "href": "1901-House-On-Fire.html", "caption": "Sound of a building on fire from within.", "id": "1901", "duration": 47.8901875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1901&type=wav"} +{"title": "Tree Frogs And Birds", "description": "Tree frogs, birds, and crickets recorded in a field after a decent rainfall as the sunset", "author": "Mike Koenig", "href": "540-Tree-Frogs-And-Birds.html", "caption": "Tree frogs, birds, and crickets are making noise after rainfall.", "id": "540", "duration": 41.2450625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=540&type=wav"} +{"title": "Mother In Law", "description": "My mother in law talking to my kids saying Nana Can Take Care of It. Shes a good lady even if she is my mother in law :)", "author": "Mike Koenig", "href": "694-Mother-In-Law.html", "caption": "Someone is talking to children.", "id": "694", "duration": 1.97371875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=694&type=wav"} +{"title": "Cuckoo Clock", "description": "An awesome Cuckoo Clock Sound effect for some crazy lunatic out there. Sound taken from a public domain movie, so the sound remains public domain. I reworked it.", "author": "Mike Koenig", "href": "1261-Cuckoo-Clock.html", "caption": "A clock is ticking.", "id": "1261", "duration": 1.2564375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1261&type=wav"} +{"title": "Harley Davidson", "description": "A Harley Davidson motorcycle idling and revving its engine. It then speeds away.", "author": "Daniel Simion", "href": "2211-Harley-Davidson.html", "caption": "A motorcycle is idling and speeding away.", "id": "2211", "duration": 34.00140625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2211&type=wav"} +{"title": "Helicopter Approach", "description": "Helicopter flying from distance and coming towards you the listener.", "author": "Mike Koenig", "href": "2074-Helicopter-Approach.html", "caption": "A helicopter is flying towards the listener.", "id": "2074", "duration": 20, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2074&type=wav"} +{"title": "Shotgun Old School", "description": "An awesome and excellent quality sound of action-pump shot fire of an old school shotgun", "author": "RA The Sun God", "href": "1960-Shotgun-Old-School.html", "caption": "An old-school shotgun is being fired.", "id": "1960", "duration": 1.90340625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1960&type=wav"} +{"title": "Ole Banderillero 3", "description": "Ole! Another banderillero or bullfighter in spain ole sound effect, great for a bullfight or matador.", "author": "Mike Koenig", "href": "668-Ole-Banderillero-3.html", "caption": "A bullfighter or banderillero is saying \"ole.\".", "id": "668", "duration": 1.39321875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=668&type=wav"} +{"title": "Coyote Call", "description": "The sound of a pack of coyotes calling. Great reverb of canyon walls adds extra realism ans sense of space.", "author": "Mike Koenig", "href": "977-Coyote-Call.html", "caption": "Coyotes are calling.", "id": "977", "duration": 19.9974375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=977&type=wav"} +{"title": "Rooster Crowing 2", "description": "Rooster crows at Lynns farm early morning time to wake up", "author": "Shelley", "href": "2040-Rooster-Crowing-2.html", "caption": "A rooster is crowing.", "id": "2040", "duration": 2.0053125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2040&type=wav"} +{"title": "Frog Croaking", "description": "Small group of frogs maybe 3 or 4 croaking in rapid succession. Great little swampy pond sound effect. Requested by Lorrie Watkins.", "author": "snottyboy", "href": "1336-Frog-Croaking.html", "caption": "Frogs are croaking.", "id": "1336", "duration": 5.80503125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1336&type=wav"} +{"title": "Radio Check", "description": "Radio check on apron of airfield. RADIO COMMUNICATION between plane and tower.", "author": "Henk", "href": "1688-Radio-Check.html", "caption": "There is a radio check between a plane and a tower.", "id": "1688", "duration": 12.925, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1688&type=wav"} +{"title": "Zippo Lighter Click", "description": "Zippo lighter flick and light nice clicks", "author": "Mike Koenig", "href": "349-Zippo-Lighter-Click.html", "caption": "A lighter is flicking.", "id": "349", "duration": 1.38846875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=349&type=wav"} +{"title": "Cartoon Birds 2", "description": "Cartoon birds chirping silly. Cartoonish animated birds like you might find in a childs cartoon.", "author": "Daniel Simion", "href": "2207-Cartoon-Birds-2.html", "caption": "Birds are chirping.", "id": "2207", "duration": 6.185125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2207&type=wav"} +{"title": "Alarm Alert Effect", "description": "An alarm or alert sound effect warning clip", "author": "Mike Koenig", "href": "339-Alarm-Alert-Effect.html", "caption": "An alarm is sounding.", "id": "339", "duration": 15.9764375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=339&type=wav"} +{"title": "Crazy Brain", "description": "Some super psycho crazy brain mental institution sounding loop or ambiance", "author": "Mike Koenig", "href": "1713-Crazy-Brain.html", "caption": "An ambiance is heard.", "id": "1713", "duration": 17.4656875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1713&type=wav"} +{"title": "Mystic Chanting 4", "description": "Some kind of mystic chanting", "author": "Marianne Gagnon", "href": "1716-Mystic-Chanting-4.html", "caption": "Chanting is heard.", "id": "1716", "duration": 6.66925, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1716&type=wav"} +{"title": "Butterfly", "description": "Sound of a butterfly flapping its wings quickly. This nature, animal, and insect sound requested by pakshep girdhar. Thanks for the request.", "author": "Mike Koenig", "href": "1322-Butterfly.html", "caption": "A butterfly is flapping its wings.", "id": "1322", "duration": 4.6645625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1322&type=wav"} +{"title": "Rip Arm Off", "description": "The sound of someone having their arm ripped off. Dismemberment and what not. Gross huh.", "author": "Mike Koenig", "href": "953-Rip-Arm-Off.html", "caption": "Someone is having their arm ripped off.", "id": "953", "duration": 1.6795625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=953&type=wav"} +{"title": "Wind", "description": "Awesome wind sound effect, need some breezy effect? This is the one, nice steady medium to heavy wind sound effect.", "author": "Stilgar", "href": "1247-Wind.html", "caption": "Wind is blowing steadily.", "id": "1247", "duration": 7.991, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1247&type=wav"} +{"title": "Fart", "description": "Plane jane fart sound effect. Simple smelly fart.", "author": "Mike Koenig", "href": "790-Fart.html", "caption": "A simple fart sound effect.", "id": "790", "duration": 2.6089375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=790&type=wav"} +{"title": "Kettle Whistle", "description": "Sound of a kettle whistling on a stove. Nice tea pot whistle sound.", "author": "Teto Yasha", "href": "1708-Kettle-Whistle.html", "caption": "A kettle is whistling.", "id": "1708", "duration": 26.72328125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1708&type=wav"} +{"title": "Funny Fart Trail", "description": "A very funny sounding fart that sort of trails off into silence. This one was a blast to make. :)", "author": "Mike Koenig", "href": "494-Funny-Fart-Trail.html", "caption": "A fart is heard.", "id": "494", "duration": 1.570625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=494&type=wav"} +{"title": "Jack In The Box", "description": "A jack in the box playing pop goes the weasel great for a childrens video or cartoon sound effect.", "author": "Mike Koenig", "href": "1872-Jack-In-The-Box.html", "caption": "A jack-in-the-box is playing music.", "id": "1872", "duration": 15.2184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1872&type=wav"} +{"title": "Alien Siren", "description": "A siren with some effects added. Great for an alien world or escape sequence.", "author": "KevanGC", "href": "1753-Alien-Siren.html", "caption": "A siren is sounding with added effects.", "id": "1753", "duration": 8.893, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1753&type=wav"} +{"title": "Frying Chicken", "description": "Sound of chicken frying in a pan. Great sizzle sizzle. Request from Marilyn.", "author": "Mike Koenig", "href": "1482-Frying-Chicken.html", "caption": "Chicken is frying in a pan with a sizzle sound.", "id": "1482", "duration": 6.600625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1482&type=wav"} +{"title": "Air Conditioner", "description": "Air Conditioner ambiance sound. This sound can be heard all over the world on hot days.", "author": "Daniel Simion", "href": "2187-Air-Conditioner.html", "caption": "An air conditioner is humming.", "id": "2187", "duration": 90.092375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2187&type=wav"} +{"title": "Grenade", "description": "Perfect grenade explosion in stereo sound effect. Great for military or war sound effects.", "author": "Mike Koenig", "href": "1151-Grenade.html", "caption": "A grenade has exploded.", "id": "1151", "duration": 1.206, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1151&type=wav"} +{"title": "Monsoon", "description": "The sound of a monsoon or even a hurricane. Great for a massive seasonal storm! Requested by vanchinathan.", "author": "Mike Koenig", "href": "948-Monsoon.html", "caption": "There is a massive seasonal storm.", "id": "948", "duration": 22.17328125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=948&type=wav"} +{"title": "Eat Mommy", "description": "My little daughter asking my wife if she wants to eat. Another cute sound.", "author": "Mike Koenig", "href": "614-Eat-Mommy.html", "caption": "Someone's daughter is asking if her mother wants to eat.", "id": "614", "duration": 1.61665625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=614&type=wav"} +{"title": "Water Drops", "description": "Water Drops hitting more water and setting the mood to dark and dingy. Sounds like you are at the bottom of a well and water is dripping down.", "author": "Daniel Simion", "href": "2186-Water-Drops.html", "caption": "Water is dripping.", "id": "2186", "duration": 62.23946875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2186&type=wav"} +{"title": "Catapult", "description": "Sound a catapult throwing a fireball or siege bomb at a target. Great whoosh and spring sound. Great for a battle or war sound.", "author": "Mike Koenig", "href": "653-Catapult.html", "caption": "A catapult is throwing something.", "id": "653", "duration": 2.293, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=653&type=wav"} +{"title": "Strange Alarm", "description": "Some strange alarm you can use for a security system or something. Pretty clear and unique.", "author": "Mike Koenig", "href": "1306-Strange-Alarm.html", "caption": "An alarm is sounding.", "id": "1306", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1306&type=wav"} +{"title": "Heavy Sigh", "description": "Me making a sighing sound, im obviously not impressed with what is going on at the moment.", "author": "Mike Koenig", "href": "321-Heavy-Sigh.html", "caption": "Someone is sighing.", "id": "321", "duration": 1.31053125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=321&type=wav"} +{"title": "Large Metal Pan 2", "description": "A great metal pan hit sound 2 requested by Steve metal knock or hit can be used for many things.", "author": "Mike Koenig", "href": "594-Large-Metal-Pan-2.html", "caption": "A pan is hit.", "id": "594", "duration": 1.43965625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=594&type=wav"} +{"title": "Thunder Storm 2", "description": "Thunder Storm in summer with rain", "author": "Mike Koenig", "href": "83-Thunder-Storm-2.html", "caption": "A thunderstorm is happening with rain.", "id": "83", "duration": 15.81571875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=83&type=wav"} +{"title": "Wetlands", "description": "Field recording of the wetlands or swamps. A wetland is an area of land whose soil is saturated with moisture either permanently or seasonally. Recorded by Tony Phillips.", "author": "Tony Phillips", "href": "1219-Wetlands.html", "caption": "Wetlands or swamps are being recorded.", "id": "1219", "duration": 12.6651875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1219&type=wav"} +{"title": "Cat Meow", "description": "A nice little cat meow sound effect. Gruff cat sound.", "author": "Mike Koenig", "href": "674-Cat-Meow.html", "caption": "A cat is meowing.", "id": "674", "duration": 1.25175, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=674&type=wav"} +{"title": "Throw Knife", "description": "A knife being thrown and hitting a target. Great for a carnival or knife fight scene.", "author": "Anonymous", "href": "1607-Throw-Knife.html", "caption": "A knife hits a target.", "id": "1607", "duration": 2.0898125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1607&type=wav"} +{"title": "Sonic Boom", "description": "Sonic Boom Sound Effect of an fighter jet breaking this sound barrier. this Actually a real sonic boom, not a fake. Thanks to sandeep singh for the request.", "author": "Grenagen", "href": "1339-Sonic-Boom.html", "caption": "A fighter jet is breaking the sound barrier.", "id": "1339", "duration": 3.12246875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1339&type=wav"} +{"title": "Electric Sander", "description": "Electric sander sound effect. My father uses a small hand held electric sander to buff some wood. Great vibrating wood shop sound effects.", "author": "Mike Koenig", "href": "1103-Electric-Sander.html", "caption": "An electric sander is buffing wood.", "id": "1103", "duration": 11.3661875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1103&type=wav"} +{"title": "Angry", "description": "Very angry sound. Sounds like that big giant guy from the movie Troy. Great anger and strife sound.", "author": "nps.gov", "href": "982-Angry.html", "caption": "A sound of anger and strife.", "id": "982", "duration": 2.85653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=982&type=wav"} +{"title": "Silly Farts", "description": "Silly farting sound. Short and very low brow sound effect, but it is funny nonetheless. Thanks to Joe.", "author": "Joe", "href": "2088-Silly-Farts.html", "caption": "A silly farting sound is made.", "id": "2088", "duration": 4.05296875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2088&type=wav"} +{"title": "Loud Bang", "description": "Its a loud bang. Be sure to turn the volume up all the way to scare people P", "author": "Osama Bin Laden", "href": "1789-Loud-Bang.html", "caption": "A loud bang sound effect.", "id": "1789", "duration": 2.2084375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1789&type=wav"} +{"title": "Rigid Fart", "description": "A very rigid uptight farting sound made by... well.. someone farting.", "author": "Mike Koenig", "href": "680-Rigid-Fart.html", "caption": "Someone is farting.", "id": "680", "duration": 1.529625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=680&type=wav"} +{"title": "Traffic Jam 1", "description": "A traffic jam with horns honking and cars driving. This is part one of 4, the sound had to be chopped up smaller in order for the page to load and render quickly.", "author": "Yo Mama", "href": "1609-Traffic-Jam-1.html", "caption": "Cars are honking in a traffic jam.", "id": "1609", "duration": 24.525375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1609&type=wav"} +{"title": "Lion", "description": "Lion or lion sounds requested by Ivelisse, thanks for the request. Took a cat meow reversed it slowed it down tweaked it a bit, and now hopefully it sounds like a lion roaring.", "author": "Mike Koenig", "href": "1416-Lion.html", "caption": "A lion is roaring.", "id": "1416", "duration": 2.52084375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1416&type=wav"} +{"title": "Electric Saw", "description": "Electrical saw for cutting wood and other material. This sound is about as good ad it gets for saw sounds.", "author": "Mike Koenig", "href": "1092-Electric-Saw.html", "caption": "A saw is cutting through wood and other materials.", "id": "1092", "duration": 13.18646875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1092&type=wav"} +{"title": "Blood Splatters", "description": "A great blood splattering on wall sound effect for gory movie scene or video game! Great for halloween too!", "author": "Mike Koenig", "href": "824-Blood-Splatters.html", "caption": "Blood is splattering on a wall.", "id": "824", "duration": 1.217375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=824&type=wav"} +{"title": "Barreta M9", "description": "Beretta M9 with shell ejection. Great gunshot sound effect. Thanks to Dion for sharing his sound effects!", "author": "Dion Stapper", "href": "1906-Barreta-M9.html", "caption": "A gun fires with shell ejection.", "id": "1906", "duration": 1.33421875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1906&type=wav"} +{"title": "Wasp", "description": "Wasp sound great for an insect buzzing or even a bee, mosquito, hornet, or gnat.", "author": "nps.gov", "href": "980-Wasp.html", "caption": "An insect is buzzing.", "id": "980", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=980&type=wav"} +{"title": "Tape Measure", "description": "Sound of a tape measure great for a lab, construction, masonry, or carpentry.", "author": "Mike Koenig", "href": "1324-Tape-Measure.html", "caption": "A tape measure is retracting.", "id": "1324", "duration": 6.06625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1324&type=wav"} +{"title": "Suicide Bomber", "description": "A suicide bomber blows himself up on the streets of Iraq in protest of the American Occupation.", "author": "snottyboy", "href": "1332-Suicide-Bomber.html", "caption": "A bombing is occurring.", "id": "1332", "duration": 5.4799375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1332&type=wav"} +{"title": "Play Ball Umpire", "description": "Umpire saying play ball a great baseball sports sound requested by Laura Hannan. Thanks Laura.", "author": "Mike Koenig", "href": "502-Play-Ball-Umpire.html", "caption": "An umpire is saying \"Play ball.\".", "id": "502", "duration": 1.32440625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=502&type=wav"} +{"title": "Pager Beeps", "description": "Great pager beeping sound. Lmmn61i requested Regular beeping of a pager or a beeper Regular beeping of an electronic alarm clock", "author": "Mike Koenig", "href": "529-Pager-Beeps.html", "caption": "A pager is beeping.", "id": "529", "duration": 4.2791875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=529&type=wav"} +{"title": "Phone Ringing 8x", "description": "A telephone ringing 8 times from the perspective of the caller or person who just dialed the number", "author": "Mike Koenig", "href": "1869-Phone-Ringing-8x.html", "caption": "A phone is ringing.", "id": "1869", "duration": 37.12275, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1869&type=wav"} +{"title": "Of Suspense", "description": "You know that sound right before something happens? This is that sound. Very suspenseful", "author": "Stephan Moebius", "href": "371-Of-Suspense.html", "caption": "A suspenseful sound is playing.", "id": "371", "duration": 1.23065625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=371&type=wav"} +{"title": "Large Metal Clippers 3x", "description": "The sound of large metal clippers or shears snipping 3x. Great for a quick cutting sound.", "author": "Mike Koenig", "href": "1066-Large-Metal-Clippers-3x.html", "caption": "Some metal clippers or shears are snipping quickly.", "id": "1066", "duration": 3.264625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1066&type=wav"} +{"title": "Fast Drawing", "description": "Person sketching, drawing a picture, or just writing a letter really fast scribbles with pencil.", "author": "Daniel Simion", "href": "2172-Fast-Drawing.html", "caption": "Someone is scribbling with a pencil.", "id": "2172", "duration": 100.0919375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2172&type=wav"} +{"title": "Snow Rock Avalanche", "description": "What does and avalanche sound like? Snow and rock sliding down mountain.", "author": "Daniel Simon", "href": "2137-Snow-Rock-Avalanche.html", "caption": "An avalanche is happening.", "id": "2137", "duration": 76.6, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2137&type=wav"} +{"title": "5 Sec Crowd Cheer", "description": "Crowd cheering loud n clear for 5 seconds or a little more.", "author": "Mike Koenig", "href": "1700-5-Sec-Crowd-Cheer.html", "caption": "A crowd is cheering.", "id": "1700", "duration": 5.3706875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1700&type=wav"} +{"title": "T Rex Roar", "description": "Super cool t rex roar or roaring sound effect requested by malik. Thanks for the request.", "author": "levitb", "href": "1552-T-Rex-Roar.html", "caption": "A T. rex is roaring.", "id": "1552", "duration": 3.5896875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1552&type=wav"} +{"title": "Transfer Truck Driving Off", "description": "A great sound from a transfer truck driving off. I happened to pull up to a truck at a stoplight. Great sound.", "author": "Mike Koenig", "href": "686-Transfer-Truck-Driving-Off.html", "caption": "A transfer truck is driving off.", "id": "686", "duration": 15.96234375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=686&type=wav"} +{"title": "Magical", "description": "Magical wand sound effect. Sound of magic in the making. Wave of a wand, rabbit out of a hat, disappearing, teleporting.", "author": "Mike Koenig", "href": "1088-Magical.html", "caption": "A magical wand is making a sound, indicating magic in the making.", "id": "1088", "duration": 2.92371875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1088&type=wav"} +{"title": "Single Cow", "description": "Single deep moo from sound effect from a large cow or bull from a farm down in Arizona. Could be used for a bull or bullrider sound effect.", "author": "BuffBill84", "href": "1572-Single-Cow.html", "caption": "A cow is mooing.", "id": "1572", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1572&type=wav"} +{"title": "Sonic Boom Massive", "description": "Massive Sonic Boom sound effect made by an F-18 breaking the sound barrier at an air show while passing directly overhead.", "author": "AirMan", "href": "1648-Sonic-Boom-Massive.html", "caption": "A plane is breaking the sound barrier.", "id": "1648", "duration": 7.34971875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1648&type=wav"} +{"title": "Flapping Wings 3", "description": "Flapping Wings 3 or fluttering sound effect. Fairy, bird or dragon wings. Requested by Tracey", "author": "Mike Koenig", "href": "628-Flapping-Wings-3.html", "caption": "Flapping sound of wings.", "id": "628", "duration": 5.45809375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=628&type=wav"} +{"title": "Chopping Wood 2", "description": "A tin can click with bass boost. Thanks to Sound Explorer for another great sound.", "author": "Sound Explorer", "href": "1985-Chopping-Wood-2.html", "caption": "A tin can is being clicked with bass boost.", "id": "1985", "duration": 6.22296875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1985&type=wav"} +{"title": "Boomerang Toss", "description": "The sound of some Australian hurling a boomerang in the outback and it returning to him.", "author": "Mike Koenig", "href": "746-Boomerang-Toss.html", "caption": "Someone is throwing and catching a boomerang.", "id": "746", "duration": 4.5515, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=746&type=wav"} +{"title": "Gun Battle Sound", "description": "Guns bullet flybysricochets distant artillery explosions", "author": "ReamProductions", "href": "2078-Gun-Battle-Sound.html", "caption": "Guns are fired, and explosions are heard.", "id": "2078", "duration": 20.20678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2078&type=wav"} +{"title": "Gagging", "description": "The sound of someone gagging, or chocking. Great choke sound effect.", "author": "Mike Koenig", "href": "844-Gagging.html", "caption": "Someone is gagging or choking.", "id": "844", "duration": 3.02396875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=844&type=wav"} +{"title": "M107 50 Cal Sniper Rifle 3x", "description": "M107 50 Cal Sniper Rifle 3x in open desert region. lots of reverb from canyons in distance", "author": "AmMoe", "href": "1653-M107-50-Cal-Sniper-Rifle-3x.html", "caption": "A gun is firing.", "id": "1653", "duration": 7.12875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1653&type=wav"} +{"title": "Cow And Bell", "description": "Sound of a cow and a bell on a farm somewhere in sweden. Milk cow or dairy cow farm sound.", "author": "Mike Koenig", "href": "1143-Cow-And-Bell.html", "caption": "A cow and a bell are making sounds on a farm.", "id": "1143", "duration": 2.29878125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1143&type=wav"} +{"title": "Explosion Ultra Bass", "description": "An explosion with a little bass to give more juice to your visual experience. Awesome sound, around 14 seconds long.", "author": "Mark DiAngelo", "href": "1807-Explosion-Ultra-Bass.html", "caption": "An explosion sound effect with added bass.", "id": "1807", "duration": 14.7330625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1807&type=wav"} +{"title": "Sea Waves", "description": "Sound of sea waves from the beaches edge. Recorded at the outer banks of North Carolina near Corolla. This was an anonymous request.", "author": "Mike Koenig", "href": "885-Sea-Waves.html", "caption": "Sound of sea waves from the beach.", "id": "885", "duration": 30.59090625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=885&type=wav"} +{"title": "Slam Fork Down", "description": "Sound of someone slamming down fork spoon cutlery", "author": "nps", "href": "876-Slam-Fork-Down.html", "caption": "Someone is slamming cutlery.", "id": "876", "duration": 2.09684375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=876&type=wav"} +{"title": "Nature Ambiance", "description": "Cool Nature Ambiance sound effect. Great for outdoor scenes in movies and video games. Enjoy this sound is in the public domain.", "author": "nille", "href": "1263-Nature-Ambiance.html", "caption": "Nature is serene.", "id": "1263", "duration": 36.07396875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1263&type=wav"} +{"title": "Redneck Rolls Dice", "description": "Redneck old man rolls dice and says Snake Eyes", "author": "Mike Koenig", "href": "189-Redneck-Rolls-Dice.html", "caption": "Someone is rolling dice and saying \"Snake Eyes.\".", "id": "189", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=189&type=wav"} +{"title": "Zombie In Pain", "description": "Zombie in Pain sound. For zombie death, or impact. Great for a game. Zombie sounds requested by jordangiese.", "author": "Mike Koenig", "href": "1033-Zombie-In-Pain.html", "caption": "A zombie is in pain.", "id": "1033", "duration": 1.738625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1033&type=wav"} +{"title": "Crazy Bizarre Guitar", "description": "Crazy and Bizarre Guitar effects played and reworked.", "author": "Daniel Simon", "href": "2153-Crazy-Bizarre-Guitar.html", "caption": "Guitar effects are playing.", "id": "2153", "duration": 8.4101875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2153&type=wav"} +{"title": "Transfer Truck Drive By", "description": "Truck drives by and loudly rattles after it hits speed bump . Nice sound for a road movie scene.", "author": "Jason Baker", "href": "2097-Transfer-Truck-Drive-By.html", "caption": "A truck rattles loudly after hitting a speed bump.", "id": "2097", "duration": 13.09996875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2097&type=wav"} +{"title": "Zen Buddhist Temple Bell", "description": "Another nice zen buddhist temple bell from the mountains. Very good sound.", "author": "Mike Koenig", "href": "1491-Zen-Buddhist-Temple-Bell.html", "caption": "A temple bell is ringing.", "id": "1491", "duration": 5.81190625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1491&type=wav"} +{"title": "Single Water Droplet", "description": "Single Water Drop. Sounds like its recorded with slow motion camera.", "author": "Mike Koenig", "href": "384-Single-Water-Droplet.html", "caption": "A water drop is falling in slow motion.", "id": "384", "duration": 2.677, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=384&type=wav"} +{"title": "Finger Snapping", "description": "The sound of a person snapping their finger 3 times.", "author": "Maddie Fix", "href": "1978-Finger-Snapping.html", "caption": "Someone is snapping their fingers.", "id": "1978", "duration": 3.01821875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1978&type=wav"} +{"title": "Wheres My Mummy", "description": "Little Ghost Girl asking wheres my mummy...Good for horror movies or horror things", "author": "KillahChipmunl", "href": "1715-Wheres-My-Mummy.html", "caption": "A ghost girl is asking for her mummy.", "id": "1715", "duration": 2.59084375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1715&type=wav"} +{"title": "Robot Arm Moving", "description": "Small fast robot movements. Robot arm and leg movement sound effects.", "author": "Mike Koenig", "href": "1369-Robot-Arm-Moving.html", "caption": "Small robot parts are moving.", "id": "1369", "duration": 1.9049375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1369&type=wav"} +{"title": "Alien Brain Scanner", "description": "Alien brain scanner machine future machine", "author": "ezwa", "href": "171-Alien-Brain-Scanner.html", "caption": "A machine is scanning a brain.", "id": "171", "duration": 13.196625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=171&type=wav"} +{"title": "Chain Fence Jump", "description": "Me jumping over a chain fence in our yard. Great for escape or chase scenes", "author": "fws.gov", "href": "316-Chain-Fence-Jump.html", "caption": "Someone is jumping over a fence.", "id": "316", "duration": 2.4141875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=316&type=wav"} +{"title": "Time Bomb Short", "description": "Awesome short time bomb tick tick tick boom explosion sound effect. Great for suspenseful bomb detonations. Best free time bomb sound effect yet.", "author": "Mike Koenig", "href": "1222-Time-Bomb-Short.html", "caption": "A time bomb is ticking and then explodes.", "id": "1222", "duration": 2.7256875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1222&type=wav"} +{"title": "Metal Gong 1", "description": "Sound of a metal gong being struck.", "author": "Dianakc", "href": "2062-Metal-Gong-1.html", "caption": "A gong is being struck.", "id": "2062", "duration": 6.25740625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2062&type=wav"} +{"title": "Tick Tock", "description": "Tick tock sound effect from a clock or large watch. Great for suspenseful scenes, or even a time bomb. Sound requested by Furvillishus.", "author": "Mike Koenig", "href": "1258-Tick-Tock.html", "caption": "A clock is ticking.", "id": "1258", "duration": 5.4011875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1258&type=wav"} +{"title": "Door Close", "description": "Sound of a door closing. Close door 3 sound can be used any time you need a generic close sound effect.", "author": "Caroline Ford", "href": "900-Door-Close.html", "caption": "A door is closing.", "id": "900", "duration": 1.6805625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=900&type=wav"} +{"title": "Water Down Drain", "description": "Water from sink draining into pipes, from my kitchen at home.", "author": "Jc Guan", "href": "372-Water-Down-Drain.html", "caption": "Water is draining from a sink into pipes.", "id": "372", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=372&type=wav"} +{"title": "Weather Alert", "description": "National Weather Alert plays this sound before giving an announcement. I generated a similar tone.", "author": "Caroline Ford", "href": "1020-Weather-Alert.html", "caption": "A national weather alert is playing a sound.", "id": "1020", "duration": 12.5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1020&type=wav"} +{"title": "Running Water", "description": "Sound of running water down pipes, tubes, rocks, or out of a pump. Sound like someone is filling a bathtub full of water.", "author": "Mike Koenig", "href": "1166-Running-Water.html", "caption": "Water is running down pipes, tubes, rocks or out of a pump, someone may be filling a bathtub.", "id": "1166", "duration": 7.8760625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1166&type=wav"} +{"title": "Kid Talking About Spongebob", "description": "My little girl wanting to watch Spongebob on the tv or tele really a cute sound clip.", "author": "fws.gov", "href": "317-Kid-Talking-About-Spongebob.html", "caption": "A child is requesting to watch TV.", "id": "317", "duration": 8.73871875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=317&type=wav"} +{"title": "Plastic Wrinkling", "description": "Sound of plastic as it wrinkels and crinkles against itself. Very crisp and clear sound, by request.", "author": "Mike Koenig", "href": "2110-Plastic-Wrinkling.html", "caption": "Plastic is crinkling against itself.", "id": "2110", "duration": 21.472125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2110&type=wav"} +{"title": "Photocopy Machine", "description": "Photocopy machine also called a copier warming up and then making copies of a report. Great for office work ambience.", "author": "Daniel Simion", "href": "2169-Photocopy-Machine.html", "caption": "A copier is warming up and making copies.", "id": "2169", "duration": 10.0768125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2169&type=wav"} +{"title": "Obama Speech Liar", "description": "Obama gets called a liar by Republican Joe Wilson at a speech about the nationalization of health care. This is technically public domain since its a presidential speech.", "author": "Mike Koenig", "href": "986-Obama-Speech-Liar.html", "caption": "Someone calls a person a liar in a speech.", "id": "986", "duration": 10.6811875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=986&type=wav"} +{"title": "Stampede Large", "description": "Large stampede sound from herd of buffalo cattle or wildebeest traveling over the plains. Thousands of animals. Stampede sound requested by steve.", "author": "Mike Koenig", "href": "1655-Stampede-Large.html", "caption": "Animals are stampeding.", "id": "1655", "duration": 19.2, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1655&type=wav"} +{"title": "Computer Error Alert", "description": "Clean computer error beep sound effect. Great to replace windows operating system default sound files.", "author": "Mike Koenig", "href": "1540-Computer-Error-Alert.html", "caption": "A computer is beeping.", "id": "1540", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1540&type=wav"} +{"title": "Trumpet Fart", "description": "A great fart sound that almost sounds like a trumpet. This one deserves 2 thumbs up for originality. :)", "author": "Mike Koenig", "href": "683-Trumpet-Fart.html", "caption": "A fart sounds like a trumpet.", "id": "683", "duration": 1.00209375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=683&type=wav"} +{"title": "Zombie Back From Dead", "description": "Sound of a zombie coming back from the dead. This and other similar zombie sounds requested by jordangiese.", "author": "Caroline Ford", "href": "1024-Zombie-Back-From-Dead.html", "caption": "A zombie is coming back from the dead.", "id": "1024", "duration": 3.79034375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1024&type=wav"} +{"title": "Music Box", "description": "A music box playing a delightful tune. Quick tune could be used for a notification sound on pc or cell phone, or whatever else you can dream up.", "author": "Big Daddy", "href": "1619-Music-Box.html", "caption": "A music box is playing a tune.", "id": "1619", "duration": 2.13625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1619&type=wav"} +{"title": "Hearbeat 2", "description": "Another great hearbeat sound that can be used for movies or games or whatever else u may want to use it for. This hearbeat is pitched a bit higher so you can hear it on standard pc speakers.", "author": "Mike Koenig", "href": "1707-Hearbeat-2.html", "caption": "A heartbeat is heard.", "id": "1707", "duration": 29.9353125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1707&type=wav"} +{"title": "Frying Food", "description": "Sound of grease or hot oil in a pan in a kitchen popping and bubbling lightly.", "author": "J Bravo", "href": "2031-Frying-Food.html", "caption": "Grease is popping and bubbling in a pan.", "id": "2031", "duration": 18.56, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2031&type=wav"} +{"title": "Fireworks And Crowd", "description": "Fireworks in distance and some spanish dude yelling bravo! A few feet away from me. Great celebration and crowd sounds.", "author": "Mike Koenig", "href": "712-Fireworks-And-Crowd.html", "caption": "Fireworks are going off, and someone is yelling \"bravo.\".", "id": "712", "duration": 6.8191875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=712&type=wav"} +{"title": "Whistle At Girl", "description": "Standard whistling at a girl sound.", "author": "Mike Koenig", "href": "463-Whistle-At-Girl.html", "caption": "Someone is whistling.", "id": "463", "duration": 1.7415, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=463&type=wav"} +{"title": "Large Angry Dog", "description": "A very large angry dog growling and snarling. Pretty evil.", "author": "Mike Koenig", "href": "1489-Large-Angry-Dog.html", "caption": "A large dog is growling.", "id": "1489", "duration": 1.5405, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1489&type=wav"} +{"title": "Incoming Suspense", "description": "When something is coming. Great suspense sound fx.", "author": "Maximilien", "href": "2046-Incoming-Suspense.html", "caption": "A suspenseful sound effect is heard.", "id": "2046", "duration": 2.835375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2046&type=wav"} +{"title": "Ready To Burst", "description": "Sound of a balloon about to burst. Squeaking of a balloon right before it pops. Great plastic stretching sound effect.", "author": "Mike Koenig", "href": "1109-Ready-To-Burst.html", "caption": "A balloon is about to burst.", "id": "1109", "duration": 5.19196875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1109&type=wav"} +{"title": "Muted Metal Pot Hit", "description": "Muted Metal Pot Hit requested by Steve metal knock or hit can be used for many things.", "author": "Mike Koenig", "href": "600-Muted-Metal-Pot-Hit.html", "caption": "A pot is hit.", "id": "600", "duration": 1.35703125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=600&type=wav"} +{"title": "Car Cornering Fast", "description": "The sound of a car cornering very fast. A few skid and break sounds can be heard.", "author": "Mike Koenig", "href": "1044-Car-Cornering-Fast.html", "caption": "A car is cornering fast.", "id": "1044", "duration": 5.5379375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1044&type=wav"} +{"title": "Text Message Alert 5", "description": "A text message sound or SMS alert to use on your mobile device or tablet to replace your default sound.", "author": "Daniel Simion", "href": "2158-Text-Message-Alert-5.html", "caption": "A text message alert is heard.", "id": "2158", "duration": 2, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2158&type=wav"} +{"title": "Flute Tone ", "description": "Its a soothing flute tone flute lovers will love it", "author": "Kushal Parikh", "href": "1739-Flute-Tone-.html", "caption": "A flute is playing.", "id": "1739", "duration": 25.33878125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1739&type=wav"} +{"title": "Police", "description": "This is a sound of Police siren and it last for around 50 seconds. This is a European cop or policia. Great for emergency or cop scenes for movies based in the EuroZone.", "author": "TheCristi95", "href": "1819-Police.html", "caption": "A siren is sounding.", "id": "1819", "duration": 49.49396875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1819&type=wav"} +{"title": "Hello Son", "description": "My son saying hello while on vacation. Cute little kid talking.", "author": "Mike Koenig", "href": "1892-Hello-Son.html", "caption": "Child saying \"hello\" on vacation.", "id": "1892", "duration": 1.8781875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1892&type=wav"} +{"title": "Railroad Crossing Bell", "description": "Safetran crossing bell for a railroad crossing. Sound of bell on for railway system.", "author": "Brylon Terry", "href": "2070-Railroad-Crossing-Bell.html", "caption": "A bell rings.", "id": "2070", "duration": 45.10946875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2070&type=wav"} +{"title": "Time Warp", "description": "This time warp sound was requested by Paul Kim. We modified an already existing time sound.", "author": "Mike Koenig", "href": "978-Time-Warp.html", "caption": "A time warp sound is playing.", "id": "978", "duration": 6.07715625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=978&type=wav"} +{"title": "Woman Blowing Nose", "description": "The sound of a woman blowing her nose. She sounds sickly.", "author": "Mike Koenig", "href": "834-Woman-Blowing-Nose.html", "caption": "A woman is blowing her nose.", "id": "834", "duration": 1.76471875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=834&type=wav"} +{"title": "Fart Squeeze Knees", "description": "Lay on your back and squeeze your knees while farting to get this fart sound.", "author": "Mike Koenig", "href": "2151-Fart-Squeeze-Knees.html", "caption": "A fart sound is made.", "id": "2151", "duration": 2.38509375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2151&type=wav"} +{"title": "Sunny Day", "description": "Very warm happy sunny day ambiance sound effect. great sound effect for a happy day", "author": "stephan", "href": "1661-Sunny-Day.html", "caption": "The ambiance of a warm sunny day is heard.", "id": "1661", "duration": 20.57496875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1661&type=wav"} +{"title": "Horn Honk", "description": "Me honking my horn as im pulling out of our driveway. Great high resolution horn honking sound effect.", "author": "Mike Koenig", "href": "583-Horn-Honk.html", "caption": "A horn is honking.", "id": "583", "duration": 1.1261875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=583&type=wav"} +{"title": "Female Scream Horror", "description": "Scream sound effect. Woman screaming at the top of her lungs in fear or horror. Great for Halloween or a spooky movie.", "author": "NeoPhyTe", "href": "1627-Female-Scream-Horror.html", "caption": "Someone is screaming in fear.", "id": "1627", "duration": 2.63121875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1627&type=wav"} +{"title": "Assembling A Gun", "description": "Sound of a person assembling a gun. sper sa va placa si distractie placuta dat download", "author": "Army", "href": "1792-Assembling-A-Gun.html", "caption": "Sound of someone assembling a gun.", "id": "1792", "duration": 14.39746875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1792&type=wav"} +{"title": "Pterodactyl Screech", "description": "Sound of a pterodactyl or large prehistoric bird or monster screeching as it flies overhead.", "author": "Mike Koenig", "href": "1860-Pterodactyl-Screech.html", "caption": "A large bird is screeching.", "id": "1860", "duration": 6.40203125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1860&type=wav"} +{"title": "Black Crows Cawing", "description": "Sound of 3 black crows cawing out in the middle of a field on a farm.", "author": "PsychoBird", "href": "1486-Black-Crows-Cawing.html", "caption": "Some crows are cawing.", "id": "1486", "duration": 1.7995625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1486&type=wav"} +{"title": "Raven", "description": "Public domain bird sound of a Raven from NPS. Great audio for halloween or something spooky.", "author": "Mike Koenig", "href": "935-Raven.html", "caption": "A raven is cawing.", "id": "935", "duration": 5.701125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=935&type=wav"} +{"title": "Strange Days", "description": "Strange and eerie crawling pad with glitches great for a horror flick or halloween themed media.", "author": "Mike Koenig", "href": "1741-Strange-Days.html", "caption": "A pad is crawling.", "id": "1741", "duration": 6.34859375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1741&type=wav"} +{"title": "Sqeaking Door", "description": "This is a wooden heavy cupboard door or front door squeaking noise. Good for Halloween or horror movie sound effect. Thanks Sarasprella for sharing your sounds!", "author": "Sarasprella", "href": "1870-Sqeaking-Door.html", "caption": "A door is creaking.", "id": "1870", "duration": 7.8663125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1870&type=wav"} +{"title": "Soldiers Marching", "description": "Sound of soldiers marching in formation. Great sound effect for war or a battle sequence.", "author": "Mike Koenig", "href": "1329-Soldiers-Marching.html", "caption": "Soldiers are marching.", "id": "1329", "duration": 11.00628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1329&type=wav"} +{"title": "Car Accelerating", "description": "Car Accelerating sound effect was requested by David. This is good for a racing audio clip.", "author": "SpeedJunkie", "href": "1456-Car-Accelerating.html", "caption": "A car is accelerating.", "id": "1456", "duration": 11.3153125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1456&type=wav"} +{"title": "Sickness", "description": "Another sick human patient blowing his nose. Great hostpical or doctor sounds", "author": "Mike Koenig", "href": "894-Sickness.html", "caption": "Someone is blowing their nose.", "id": "894", "duration": 2.3975625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=894&type=wav"} +{"title": "Yes", "description": "Male saying yes. Confirmation sound effect.", "author": "BlastwaveFx.com", "href": "703-Yes.html", "caption": "Someone is saying \"yes.\".", "id": "703", "duration": 1.18125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=703&type=wav"} +{"title": "Wings Flapping", "description": "Wings flapping or fluttering sound effect. Fairy, bird or dragon wings. Requested by Tracey", "author": "Mike Koenig", "href": "626-Wings-Flapping.html", "caption": "Flapping sound of wings.", "id": "626", "duration": 2.8613125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=626&type=wav"} +{"title": "Bubbling", "description": "Really cool bubbles or bubbling sound effect. Great for nature, fish tank, underwater, or scuba diving sounds. This sound was originally from the public domain but i tweaked it lengthened it, and converted it into stereo sound.", "author": "Mike Koenig", "href": "1148-Bubbling.html", "caption": "Bubbles are making a sound in nature, fish tank, underwater or scuba diving.", "id": "1148", "duration": 2.5495, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1148&type=wav"} +{"title": "Analog Watch Alarm", "description": "Analaog watch alarm also called a digital watch alarm sounding off. Time is up and whatever the alarm was set for now is the time to do it. Taken from a common wrist watch.", "author": "Daniel Simion", "href": "2197-Analog-Watch-Alarm.html", "caption": "An alarm is sounding off.", "id": "2197", "duration": 12.1300625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2197&type=wav"} +{"title": "38 Caliber Gun Shot 5x", "description": "Sounds of a 38 caliber pistol being shot 55 times in succession.", "author": "Mike Koenig", "href": "375-38-Caliber-Gun-Shot-5x.html", "caption": "A pistol is being shot multiple times.", "id": "375", "duration": 2.98778125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=375&type=wav"} +{"title": "Peacock Call", "description": "Awesome Peacock Sound call sound effect. Great 4 or 5 second stereo peacock sound. Sound requested by sue. Thanks sue.", "author": "junglebunny", "href": "1301-Peacock-Call.html", "caption": "A peacock is making a call sound.", "id": "1301", "duration": 6.33696875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1301&type=wav"} +{"title": "Giant Angry", "description": "Giant sounds angry! Sounds like that big giant guy from the movie Troy. Great anger and strife sound.", "author": "Mike Koenig", "href": "794-Giant-Angry.html", "caption": "A giant is angry.", "id": "794", "duration": 2.8388125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=794&type=wav"} +{"title": "Barrett M107 Sniper Rifle", "description": "Barrett m107 sniper rifle being fired in open desert region. lots of reverb from canyons in distance", "author": "AmMoe", "href": "1652-Barrett-M107-Sniper-Rifle.html", "caption": "A gun is firing.", "id": "1652", "duration": 2.66971875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1652&type=wav"} +{"title": "Chopping Wood", "description": "Sound of someone chopping wood or chopping wood with an axe. requested by mel francis", "author": "Mike Koenig", "href": "1507-Chopping-Wood.html", "caption": "Someone is chopping wood.", "id": "1507", "duration": 4.157875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1507&type=wav"} +{"title": "Clear Throat", "description": "Sound of someone clearing their throat. The sound could be either male of female.", "author": "Mike Koenig", "href": "665-Clear-Throat.html", "caption": "Someone is clearing their throat.", "id": "665", "duration": 1.56296875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=665&type=wav"} +{"title": "Space Ship Door Opening", "description": "Sound of a spaceship or space craft door opening. Nice vibrating sound phased and pulsed. Very alien. Sound requested by brooke for her class. Thanks for the request.", "author": "Mike Koenig", "href": "1284-Space-Ship-Door-Opening.html", "caption": "A spaceship door is opening.", "id": "1284", "duration": 11.5806875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1284&type=wav"} +{"title": "Chainsaw", "description": "Sound of a chainsaw cutting wood in a nearby lot. sound is public domain.", "author": "ezwa", "href": "1392-Chainsaw.html", "caption": "A chainsaw is cutting wood.", "id": "1392", "duration": 15.792, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1392&type=wav"} +{"title": "Grasshopper", "description": "Sound of a very large Grasshopper flying by a recording device. Great for insect sound effects. This sound was recorded at Yosemite National Park in CA.", "author": "Caroline Ford", "href": "927-Grasshopper.html", "caption": "A grasshopper is flying.", "id": "927", "duration": 2.8776875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=927&type=wav"} +{"title": "Spaceship Takeoff", "description": "Sound of a space ship turning on and then flying away into the night. Modified sound from Richard.", "author": "Richard", "href": "1957-Spaceship-Takeoff.html", "caption": "A space ship is turning on and flying away.", "id": "1957", "duration": 8.979625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1957&type=wav"} +{"title": "Boat", "description": "Some nice generic boat ambiance. Great sounds for a dock,boat, ferry, or similar background sounds.", "author": "Mike Koenig", "href": "890-Boat.html", "caption": "Sounds of boats in water.", "id": "890", "duration": 3.8, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=890&type=wav"} +{"title": "Puppy Barking", "description": "A young little puppy dog yipping and crying and barking. Sad little dog.", "author": "Daniel Simon", "href": "2136-Puppy-Barking.html", "caption": "A puppy is yipping, crying, and barking.", "id": "2136", "duration": 4.90821875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2136&type=wav"} +{"title": "Lion Roar", "description": "Perfect lion roar sound effect. Download it here and use it for any lion roaring sound effect you need. Roar!", "author": "Mike Koenig", "href": "1282-Lion-Roar.html", "caption": "A lion is roaring.", "id": "1282", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1282&type=wav"} +{"title": "Car Stereo", "description": "Car Stereo from Outside of Car", "author": "Mike Koenig", "href": "52-Car-Stereo.html", "caption": "A car stereo is playing.", "id": "52", "duration": 9.03409375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=52&type=wav"} +{"title": "Bye Bye ", "description": "My daughter saying Bye Bye. Cute for a little girls voice saying goodbye.", "author": "Mike Koenig", "href": "664-Bye-Bye-.html", "caption": "Someone is saying goodbye.", "id": "664", "duration": 1.02165625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=664&type=wav"} +{"title": "Shake Dice", "description": "Shaking Dice during game of craps", "author": "Mike Koenig", "href": "183-Shake-Dice.html", "caption": "Dice are being shaken during a game of craps.", "id": "183", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=183&type=wav"} +{"title": "Tyrannosaurus Rex", "description": "Great Tyrannosaurus Rex or T-Rex sound effect. Great for a dinosaur roar or monster sound effect.", "author": "Mike Koenig", "href": "1319-Tyrannosaurus-Rex.html", "caption": "A T-Rex is roaring.", "id": "1319", "duration": 2.614125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1319&type=wav"} +{"title": "Slot Machine", "description": "Slot machine being played at a Casino or other gambling facility.", "author": "Daniel Simion", "href": "2183-Slot-Machine.html", "caption": "A slot machine is playing.", "id": "2183", "duration": 7.695625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2183&type=wav"} +{"title": "Dog Growl Then Bark", "description": "Sound of a dog or large cat growling and then barking.", "author": "Mike Koenig", "href": "1476-Dog-Growl-Then-Bark.html", "caption": "A dog or large cat is growling and barking.", "id": "1476", "duration": 1.4750625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1476&type=wav"} +{"title": "Loading Shotgun", "description": "Sounds made while loading a Sawed off Pump Shotgun with 7 rounds of 12 gauge buckshot. You can hear the plunk as the shotgun shells enter the tube. Great Loading Shotgun sound effect.", "author": "Mike Koenig", "href": "1403-Loading-Shotgun.html", "caption": "A shotgun is being loaded with rounds.", "id": "1403", "duration": 17.876375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1403&type=wav"} +{"title": "Killer Movie Scene", "description": "Killer movie scene sound effects, great for a bloody shower scene", "author": "Mike Koenig", "href": "178-Killer-Movie-Scene.html", "caption": "Sound effects for a movie scene, great for a bloody shower scene.", "id": "178", "duration": 29.4273125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=178&type=wav"} +{"title": "Grenade Explosion", "description": "Awesome grenade explosion sound effect. Great big boom sound. Great for war or similar.", "author": "Mike Koenig", "href": "1467-Grenade-Explosion.html", "caption": "An explosion sound effect.", "id": "1467", "duration": 2.53753125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1467&type=wav"} +{"title": "Mystic Chanting 2", "description": "Some kind of mystic chanting", "author": "Marianne Gagnon", "href": "1680-Mystic-Chanting-2.html", "caption": "There is mystic chanting.", "id": "1680", "duration": 1.4976875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1680&type=wav"} +{"title": "Hiking A Trail", "description": "Sound of a person hiking a trail in the woods or at a state or national park or reserve.", "author": "aldo", "href": "1546-Hiking-A-Trail.html", "caption": "Someone is hiking.", "id": "1546", "duration": 20.92615625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1546&type=wav"} +{"title": "Oh", "description": "Human spoken word oh sound or emotion.", "author": "Mike Koenig", "href": "795-Oh.html", "caption": "Someone says \"oh\".", "id": "795", "duration": 2.16, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=795&type=wav"} +{"title": "Growling Snarling Dogs", "description": "Two dogs working themselves up for a confrontation. Very long low growls that eventually turn into a bark. Thanks to Lisa Redfern for some great sound effects.", "author": "Lisa Redfern", "href": "2034-Growling-Snarling-Dogs.html", "caption": "Dogs are growling and barking.", "id": "2034", "duration": 33.42475, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2034&type=wav"} +{"title": "Industrial Alarm", "description": "Alarm testing sound at local industrial park", "author": "fws.gov", "href": "287-Industrial-Alarm.html", "caption": "An alarm is being tested.", "id": "287", "duration": 2.229625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=287&type=wav"} +{"title": "Ship Brass Bell", "description": "Ships brass bell 8 rings or 4 depending on how you count with slight resonance as the sound rolls accross the water and through the fog.", "author": "Mike Koenig", "href": "1745-Ship-Brass-Bell.html", "caption": "A bell is ringing.", "id": "1745", "duration": 11.5915, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1745&type=wav"} +{"title": "Dog Whistle", "description": "Dog whistle sound mixed with a slightly lower frequency sound so that humans can hear it as well. Requested by ray leary. Thanks ray.", "author": "Mike Koenig", "href": "879-Dog-Whistle.html", "caption": "A dog whistle mixed with a lower frequency sound.", "id": "879", "duration": 3.221375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=879&type=wav"} +{"title": "Hock Loogie", "description": "Person hocking a loogie. This is the sound a person makes to gather phlegm and mucus before spitting", "author": "BlastwaveFx.com", "href": "649-Hock-Loogie.html", "caption": "Someone is hocking a loogie.", "id": "649", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=649&type=wav"} +{"title": "Ima Firin My Laser", "description": "A sound you use in parodies. This guy is firing his laser.", "author": "Mastercard", "href": "1799-Ima-Firin-My-Laser.html", "caption": "A sound effect of someone firing a laser, suitable for parodies.", "id": "1799", "duration": 2.50778125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1799&type=wav"} +{"title": "Long Fart", "description": "A long fart sound. This fart just wont give up will it. One word for this guy... gas tablets.", "author": "Mike Koenig", "href": "622-Long-Fart.html", "caption": "A long fart sound.", "id": "622", "duration": 3.1805, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=622&type=wav"} +{"title": "Crowd Boo And Heckles", "description": "Thousands of people screaming with some people booing, and heckling the players.", "author": "Mike Koenig", "href": "654-Crowd-Boo-And-Heckles.html", "caption": "People are screaming.", "id": "654", "duration": 9.1875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=654&type=wav"} +{"title": "Mandatory Evacuation", "description": "Loud warning or alarm sound effect plays throughout a building or warehouse. Great for an evacuation scene. Thanks goes to Brandon for this sound.", "author": "Brandon", "href": "1911-Mandatory-Evacuation.html", "caption": "An alarm plays in a building.", "id": "1911", "duration": 39.11634375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1911&type=wav"} +{"title": "Car Spinning Out", "description": "1 more great Car Spinning Out of control sound effect. Recorded this in an abandoned parking lot late at night.", "author": "Mike Koenig", "href": "1057-Car-Spinning-Out.html", "caption": "A car is skidding.", "id": "1057", "duration": 3.62234375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1057&type=wav"} +{"title": "Steam Train Whistle", "description": "A large steam train blowing his horn a few times as it chugs along.", "author": "Daniel Simion", "href": "2177-Steam-Train-Whistle.html", "caption": "A train is blowing its horn.", "id": "2177", "duration": 6.2779375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2177&type=wav"} +{"title": "Water Fountain Noise", "description": "Noise made from a water fountain. Great water or trickle sound effect.", "author": "Caroline Ford", "href": "1435-Water-Fountain-Noise.html", "caption": "A water fountain is making a trickling sound.", "id": "1435", "duration": 21.90078125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1435&type=wav"} +{"title": "Camp Fire Burning", "description": "Camp Fire Burning", "author": "Mike Koenig", "href": "93-Camp-Fire-Burning.html", "caption": "A campfire is burning.", "id": "93", "duration": 13.3743125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=93&type=wav"} +{"title": "Heart Rate Monitor Flatline", "description": "Sound of a heart rate monitor flatline, or death. Sound requested by chris.", "author": "nps.gov", "href": "882-Heart-Rate-Monitor-Flatline.html", "caption": "A heart monitor is flatlining.", "id": "882", "duration": 13.7079375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=882&type=wav"} +{"title": "Temple Bell", "description": "Great sound of a temple bell. This is the smallest of 3 recorded. This sound was requested by dj sachin.", "author": "Mike Koenig", "href": "1531-Temple-Bell.html", "caption": "A temple bell is ringing.", "id": "1531", "duration": 5.18696875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1531&type=wav"} +{"title": "People Screaming", "description": "Sound of people screaming. Great fear, horror, or surprise screaming sound effect. 3 or 4 people screaming include 1 kid, 1 adult male, 1 adult female.", "author": "Mike Koenig", "href": "1082-People-Screaming.html", "caption": "People are screaming in fear or surprise, including a kid, an adult male, and an adult female.", "id": "1082", "duration": 3.3681875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1082&type=wav"} +{"title": "Drive By Farting", "description": "A rancid drive by farting sound. Just another fart sound effect.", "author": "Mike Koenig", "href": "805-Drive-By-Farting.html", "caption": "A drive-by fart sound effect.", "id": "805", "duration": 1.37115625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=805&type=wav"} +{"title": "Wind", "description": "Wind for use in films short films or anything you can think of. A really nice wind blowing, sand or snow storm sound effect. The full version is nearly 2 minutes long and just available in wav format. The MP3 version is a smaller truncated sound clip so that the preview will be loaded faster.", "author": "Mark DiAngelo", "href": "1810-Wind.html", "caption": "Wind is blowing in a desert, snowstorm or sandstorm.", "id": "1810", "duration": 122.96628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1810&type=wav"} +{"title": "Pouring A Glass Full", "description": "Pouring a glass full of liquid this sound makes me thirsty", "author": "Mike Koenig", "href": "218-Pouring-A-Glass-Full.html", "caption": "Liquid is being poured into a glass.", "id": "218", "duration": 12.09759375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=218&type=wav"} +{"title": "M1 Garand Gunfire", "description": "M1 Garand gunfire on battlefield. M1 Garrand is a 30 caliber rifle, and often called Greatest Battle Implement Ever Devised. It was the first semi-automatic rifle used by the military. Sound effect requested by William Andrews. Thanks William.", "author": "battlestar10", "href": "1666-M1-Garand-Gunfire.html", "caption": "A rifle is firing.", "id": "1666", "duration": 2.70628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1666&type=wav"} +{"title": "Background Noise", "description": "Some useless background noise or static. White or black noise. Just stupid noise.", "author": "Mike Koenig", "href": "531-Background-Noise.html", "caption": "There is useless background noise or static.", "id": "531", "duration": 12.3206875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=531&type=wav"} +{"title": "Cow Mooing", "description": "The cow goes moo sound", "author": "Mike Koenig", "href": "215-Cow-Mooing.html", "caption": "A cow is mooing.", "id": "215", "duration": 1.81909375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=215&type=wav"} +{"title": "Jack In The Box Fast", "description": "A jack in the box playing pop goes the weasel and playing ti pretty fast", "author": "Mike Koenig", "href": "1866-Jack-In-The-Box-Fast.html", "caption": "A jack-in-the-box is playing music quickly.", "id": "1866", "duration": 8.91084375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1866&type=wav"} +{"title": "Cutlery Clank", "description": "Multiple cutlery clank sound effects from kitchen.", "author": "NPS", "href": "967-Cutlery-Clank.html", "caption": "Cutlery is clanking in a kitchen.", "id": "967", "duration": 5.34790625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=967&type=wav"} +{"title": "Growling Lion", "description": "Growling lion sounds requested by Ivelisse, thanks for the request. Bit taken from public domain movie and cleaned up a bit.", "author": "Mike Koenig", "href": "1415-Growling-Lion.html", "caption": "A lion is growling.", "id": "1415", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1415&type=wav"} +{"title": "Door Unlock", "description": "Sound of electric locks being unlocked. Nice electric click sound for an auto or similar.", "author": "Mike Koenig", "href": "830-Door-Unlock.html", "caption": "Electric locks are being unlocked.", "id": "830", "duration": 1.24228125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=830&type=wav"} +{"title": "Scary Ambiance", "description": "Nice scary sound or horror ambiance sound effect for Halloween or some spooky movie. Super scary and twisted.", "author": "Mike Koenig", "href": "1756-Scary-Ambiance.html", "caption": "A scary sound is heard.", "id": "1756", "duration": 16.13325, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1756&type=wav"} +{"title": "Ray Gun", "description": "Super cool stereo ray gun or laser gun blsater sound effect. This would be great for sci fi or other video games and movies.", "author": "Mike Koenig", "href": "1770-Ray-Gun.html", "caption": "A stereo ray gun is firing.", "id": "1770", "duration": 2.17109375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1770&type=wav"} +{"title": "Slug Crawling", "description": "Sound of a garden slug crawling. Great for any number of sticky icky creatures that are slimey. This is a fun sound too.", "author": "Mike Koenig", "href": "1083-Slug-Crawling.html", "caption": "A garden slug is crawling, producing a slimy sound.", "id": "1083", "duration": 1.38109375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1083&type=wav"} +{"title": "Karate Punch Suspense", "description": "Nice suspenseful ambiance and then punch, like a ninja sneaking up on someone. Could also be used for boxing and kung fu. Karate Whir requested by Brian", "author": "Mike Koenig", "href": "1727-Karate-Punch-Suspense.html", "caption": "Something is whirring and punching.", "id": "1727", "duration": 3.4604375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1727&type=wav"} +{"title": "Oh Understanding", "description": "Oh Understanding sound effect. Someone understand what is going on now.", "author": "Mike Koenig", "href": "814-Oh-Understanding.html", "caption": "Someone is making a sound of understanding.", "id": "814", "duration": 1.64159375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=814&type=wav"} +{"title": "50 Cal CasingX3", "description": "A .50 Caliber bullet casing hitting the ground. This file has 3 shell casings hitting the ground one by one. Use them however you like.", "author": "Ghost Rider", "href": "1927-50-Cal-CasingX3.html", "caption": "A bullet casing hits the ground.", "id": "1927", "duration": 6.445, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1927&type=wav"} +{"title": "Roaring Lion", "description": "The king of the jungle a lion roaring sound effect.", "author": "Mike Koenig", "href": "1272-Roaring-Lion.html", "caption": "A lion is roaring.", "id": "1272", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1272&type=wav"} +{"title": "Light Bulb Breaking", "description": "Light bulb breaking sound attained by breaking small champagne glass on cement floor", "author": "Mike Koenig", "href": "105-Light-Bulb-Breaking.html", "caption": "A small champagne glass is breaking on a cement floor.", "id": "105", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=105&type=wav"} +{"title": "Cracking Chest Open", "description": "Sound of a doctor or a madman (both one and the same really) cracking a persons chest cavity open. Great for a movie or haunted house", "author": "Caroline Ford", "href": "970-Cracking-Chest-Open.html", "caption": "Someone is cracking a chest cavity.", "id": "970", "duration": 3.680375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=970&type=wav"} +{"title": "Tearing Flesh And Bone", "description": "Tearing flesh and bone sound great for flesh ripping and dismemberment. Made by stretching rubber therapy band", "author": "Mike Koenig", "href": "368-Tearing-Flesh-And-Bone.html", "caption": "Flesh is tearing and bones are breaking.", "id": "368", "duration": 2.7991875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=368&type=wav"} +{"title": "Time Bomb", "description": "Awesome time bomb tick tick tick boom explosion sound effect. Great for suspenseful bomb detonations. Best free time bomb sound effect yet.", "author": "Mike Koenig", "href": "1203-Time-Bomb.html", "caption": "A time bomb is ticking and then explodes.", "id": "1203", "duration": 6.58790625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1203&type=wav"} +{"title": "Zombie Talking", "description": "The sound of a zombie talking. Saying get over here. This zombie wants some brains. Zombie sounds requested by jordangiese.", "author": "Caroline Ford", "href": "1026-Zombie-Talking.html", "caption": "A zombie is saying \"get over here\" and wants brains.", "id": "1026", "duration": 2.48471875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1026&type=wav"} +{"title": "Chicken Frying", "description": "Chicken Frying in a pan sound effect. Great sizzle sizzle. Request from Marilyn.", "author": "Mike Koenig", "href": "1480-Chicken-Frying.html", "caption": "Chicken is frying in a pan with a sizzle sound.", "id": "1480", "duration": 6.65396875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1480&type=wav"} +{"title": "Your Mom", "description": "A funny robot saying Your Mom. This is me with some effects added. The ultimate come back line.", "author": "Kevan", "href": "1755-Your-Mom.html", "caption": "A robot is saying \"Your Mom.\".", "id": "1755", "duration": 1.11, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1755&type=wav"} +{"title": "Peeling Face Off", "description": "Peeling someones face off. Ever wanted to know what it sound like to rip some guys face off? No... ok me neither.. but if you did this is what it would sound like. Great for Halloween!", "author": "Mike Koenig", "href": "936-Peeling-Face-Off.html", "caption": "Someone's face is being peeled off.", "id": "936", "duration": 3.5186875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=936&type=wav"} +{"title": "Lion Growling", "description": "Lion Growling and snarling sound effect. Great precursor to a lion roaring or similar. Could also be a monster sound.", "author": "Mike Koenig", "href": "1483-Lion-Growling.html", "caption": "A lion is growling and snarling.", "id": "1483", "duration": 3.25046875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1483&type=wav"} +{"title": "Whine", "description": "Whining and sniveling pour excuse for a human. Great whine sound effect.", "author": "Mike Koenig", "href": "764-Whine.html", "caption": "Someone is whining.", "id": "764", "duration": 3.483, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=764&type=wav"} +{"title": "Wake Up Call", "description": "Pleasant woman saying good morning this is your wake up call. This was requested by Scott.", "author": "Mike Koenig", "href": "938-Wake-Up-Call.html", "caption": "Someone is saying good morning as a wake-up call.", "id": "938", "duration": 2.582375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=938&type=wav"} +{"title": "Truck Idle And Pull Off", "description": "Sound of a diesel truck approaching, idling for a few seconds and then pulling off again. Great city traffic sound.", "author": "Mike Koenig", "href": "1116-Truck-Idle-And-Pull-Off.html", "caption": "A diesel truck is idling and driving away.", "id": "1116", "duration": 17.19403125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1116&type=wav"} +{"title": "Mallard Duck 2", "description": "Another mallard duck calling out on a pond. Mallard duck field recordings by Tony Phillips.", "author": "Tony Phillips", "href": "1197-Mallard-Duck-2.html", "caption": "A mallard duck is calling out on a pond.", "id": "1197", "duration": 4.09140625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1197&type=wav"} +{"title": "Computer Magic", "description": "A magical bell playing a delightful tune could be used to replace computer event sounds.", "author": "Microsift", "href": "1630-Computer-Magic.html", "caption": "A magical bell is playing a tune.", "id": "1630", "duration": 5.0669375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1630&type=wav"} +{"title": "Time Travel Clip", "description": "Time travel sound effect clip is great for sci-fi and alien sounds.", "author": "Mike Koenig", "href": "109-Time-Travel-Clip.html", "caption": "A sound effect clip is creating a time travel effect.", "id": "109", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=109&type=wav"} +{"title": "Dirty Record Skipping", "description": "A Dirty Old Record Skipping on the turntable.", "author": "Mike Koenig", "href": "401-Dirty-Record-Skipping.html", "caption": "A record is skipping.", "id": "401", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=401&type=wav"} +{"title": "Puke Vomit Ralph", "description": "Someone throwing up or vomiting in the toilet", "author": "Stephan", "href": "173-Puke-Vomit-Ralph.html", "caption": "Someone is vomiting in a toilet.", "id": "173", "duration": 9.71665625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=173&type=wav"} +{"title": "Kitten Meow", "description": "Sound of a tiny kitten meowing. This kitten meow can be used for any scene involving a cat or kitten. Maybe even a baby lion cub.", "author": "Mike Koenig", "href": "1286-Kitten-Meow.html", "caption": "A kitten is meowing.", "id": "1286", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1286&type=wav"} +{"title": "Striking Match", "description": "Sound of a match lighting. Great for fire starting, striking match, or smoking sound effects. Lighting match sound effect requested by Triszzy.", "author": "Mike Koenig", "href": "984-Striking-Match.html", "caption": "A match is lighting, great for fire starting or smoking sound effects.", "id": "984", "duration": 1.403625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=984&type=wav"} +{"title": "Electric Windows Roll Down", "description": "Electric windows on a honda van rolling down. Sound recorded from inside the van for best audio.", "author": "Mike Koenig", "href": "816-Electric-Windows-Roll-Down.html", "caption": "Electric windows on a van are rolling down.", "id": "816", "duration": 3.73703125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=816&type=wav"} +{"title": "M16 Short Burst", "description": "Short burst of fire from an m16 assault. Great for a war or combat scene. Sound can be described as M16 rifle fire.", "author": "snottyboi", "href": "1374-M16-Short-Burst.html", "caption": "A gun is firing.", "id": "1374", "duration": 1.29596875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1374&type=wav"} +{"title": "Train Honk Horn 2x", "description": "Sound of a train honking its horn 2 times in distance followed by the echoes or reverb of the honk or horn.", "author": "Mike Koenig", "href": "1695-Train-Honk-Horn-2x.html", "caption": "A train honks twice in the distance.", "id": "1695", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1695&type=wav"} +{"title": "Blackbird Bird Call", "description": "Red winged Blackbird bird call from edge of meadow", "author": "fws.gov", "href": "252-Blackbird-Bird-Call.html", "caption": "A blackbird is making a call at the edge of a meadow.", "id": "252", "duration": 8.137, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=252&type=wav"} +{"title": "Blue Heron Fishing", "description": "Sound of a Blue Heron fishing in nearby waters", "author": "Mike Koenig", "href": "243-Blue-Heron-Fishing.html", "caption": "A blue heron is fishing in nearby waters.", "id": "243", "duration": 23.185, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=243&type=wav"} +{"title": "Please Open The Door", "description": "A woman or female talking asking someone to open the door. Requested by somnath", "author": "Mike Koenig", "href": "637-Please-Open-The-Door.html", "caption": "Someone is asking to open a door.", "id": "637", "duration": 1.82278125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=637&type=wav"} +{"title": "Change Battery", "description": "Sound recorded changing batteries in a remote control. Batter change or battery swap sound requested.", "author": "Mike Koenig", "href": "2105-Change-Battery.html", "caption": "Batteries are being changed in a remote control.", "id": "2105", "duration": 5.78246875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2105&type=wav"} +{"title": "Metal Rattling", "description": "Metal rattling as if in a moving vehicle on a bumpy or dirt road.", "author": "Gerhard Straub", "href": "2037-Metal-Rattling.html", "caption": "Metal is rattling in a vehicle on a bumpy road.", "id": "2037", "duration": 10.68246875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2037&type=wav"} +{"title": "Walking", "description": "Perfect walking sound effect. Sound of several people walking buy on a hard surface with hard shoes. You can hear the sound reverberating off the walls and solid flooring.", "author": "Stephan Moebius", "href": "1245-Walking.html", "caption": "Several people are walking on hard surface.", "id": "1245", "duration": 8.06059375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1245&type=wav"} +{"title": "Chipmunks Sound", "description": "High pitched vocals that sound like Chipmunks chattering and talking in funny voice. Mickey pitched vocals.", "author": "Uday", "href": "1931-Chipmunks-Sound.html", "caption": "Chipmunks are chattering and talking.", "id": "1931", "duration": 19.7364375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1931&type=wav"} +{"title": "Cartoon Walking", "description": "A funny cartoon walking sound. Next time you watch spongebob this is the sound that Squidward Tentacles makes when he walks.", "author": "Mike Koenig", "href": "789-Cartoon-Walking.html", "caption": "A cartoon walking sound effect is heard.", "id": "789", "duration": 1.21878125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=789&type=wav"} +{"title": "Light Rain And Crickets", "description": "Sound of light rain and crickets at sunset. Very calming serene nature sound. Great for relaxing.", "author": "Mike Koenig", "href": "1192-Light-Rain-And-Crickets.html", "caption": "Light rain and crickets at sunset.", "id": "1192", "duration": 14.48690625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1192&type=wav"} +{"title": "Wet Fart", "description": "This is a nasty wet fart sound effect.", "author": "Mike Koenig", "href": "808-Wet-Fart.html", "caption": "A wet fart sound effect is heard.", "id": "808", "duration": 1.05653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=808&type=wav"} +{"title": "King Farthur", "description": "Short but sweet fart sound kindly entitled King Farthur.", "author": "Stephan", "href": "493-King-Farthur.html", "caption": "A fart is heard.", "id": "493", "duration": 1.33678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=493&type=wav"} +{"title": "Power-Up", "description": "A powering up noise sort of like a spaceship.", "author": "KP", "href": "1639-Power-Up.html", "caption": "Something is powering up.", "id": "1639", "duration": 1.77634375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1639&type=wav"} +{"title": "Noise", "description": "A nice humming noise sound effect.", "author": "Mike Koenig", "href": "889-Noise.html", "caption": "A humming noise.", "id": "889", "duration": 2.96871875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=889&type=wav"} +{"title": "Cartoon Voice Baritone", "description": "A great cartoonish voice talking baritone. Sound like that Charlie Brown teacher but but a male instead.", "author": "Mike Koenig", "href": "689-Cartoon-Voice-Baritone.html", "caption": "A male voice is talking.", "id": "689", "duration": 2.0876875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=689&type=wav"} +{"title": "Singing Happy Birthday", "description": "My family singing happy birthday to my father in law who turned 75 years young.", "author": "Mike Koenig", "href": "498-Singing-Happy-Birthday.html", "caption": "A family is singing happy birthday.", "id": "498", "duration": 19.9135625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=498&type=wav"} +{"title": "Kid Laughing Short", "description": "Another funny sound of a kid giggling or laughing sound. This time its a kid laughing short Very cute great for a commercial or similar.", "author": "Mike Koenig", "href": "1119-Kid-Laughing-Short.html", "caption": "A kid is giggling or laughing.", "id": "1119", "duration": 1.72465625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1119&type=wav"} +{"title": "Spotted Owl Call", "description": "Sound of the rare Spotted Owl recorded at Yosemite National Park. This sound is public domain.", "author": "Mike Koenig", "href": "1010-Spotted-Owl-Call.html", "caption": "A spotted owl is making a sound.", "id": "1010", "duration": 5.262625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1010&type=wav"} +{"title": "Phone Dialing With Dialtone", "description": "I used audacity with an internal mic to record this. Its good quality though. i just dialed some numbers on my house phone with the dialtone at the beginning. Its very clear there might be some background noise though.", "author": "KevanGC", "href": "1560-Phone-Dialing-With-Dialtone.html", "caption": "Someone is dialing a phone number.", "id": "1560", "duration": 6.7015, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1560&type=wav"} +{"title": "Telephone Ring", "description": "Telephone ringing sound effect. Simple phone sound effect.", "author": "transitking", "href": "1411-Telephone-Ring.html", "caption": "A telephone is ringing.", "id": "1411", "duration": 57.7835, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1411&type=wav"} +{"title": "Deep Male Burp", "description": "Yeah its me doing a deep male burp its gross but some one has to do it.", "author": "Stephan", "href": "163-Deep-Male-Burp.html", "caption": "Someone is burping.", "id": "163", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=163&type=wav"} +{"title": "Drawer Slide Close", "description": "Desk, or dresser drawer closing sound effect. Recorded at home in my bedroom. Great for sliding close sound.", "author": "BlastwaveFx.com", "href": "590-Drawer-Slide-Close.html", "caption": "A drawer is closing.", "id": "590", "duration": 1.14940625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=590&type=wav"} +{"title": "Rogue Wave 3", "description": "Sound of a large rogue wave, tidal wave, or rogue wave sound effect 3 requested by Lincoln", "author": "Mike Koenig", "href": "609-Rogue-Wave-3.html", "caption": "Sound of a large wave.", "id": "609", "duration": 23.48184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=609&type=wav"} +{"title": "Suction", "description": "Could be a Suction cup or just some random suction sound effect.", "author": "Mike Koenig", "href": "845-Suction.html", "caption": "A suction cup or suction sound is heard.", "id": "845", "duration": 1.5660625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=845&type=wav"} +{"title": "Public Transit Bus", "description": "Nice public transit bus walla track. The people are speaking but you cant make out the words. Great for city background or transportation sound effects.", "author": "qubodup", "href": "1698-Public-Transit-Bus.html", "caption": "People are talking in the background.", "id": "1698", "duration": 18.3184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1698&type=wav"} +{"title": "Gum Bubble Pop", "description": "All voicing for this common bubble gum trick. Big thanks to Sound Explorer for another great sound.", "author": "Sound Explorer", "href": "1982-Gum-Bubble-Pop.html", "caption": "Someone is voicing a bubble gum trick.", "id": "1982", "duration": 1.32803125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1982&type=wav"} +{"title": "Missile Impact", "description": "This is a missile sound effect. A missile flying in from the left and hitting an object. Great for battles.", "author": "Osama bin Laden", "href": "1592-Missile-Impact.html", "caption": "A missile is flying and hitting an object.", "id": "1592", "duration": 7.7845, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1592&type=wav"} +{"title": "Suspense", "description": "Awesome suspense sound effect for any movie or scene.", "author": "Mike Koenig", "href": "902-Suspense.html", "caption": "A suspense sound effect is heard.", "id": "902", "duration": 3.44190625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=902&type=wav"} +{"title": "Mortar Blast", "description": "Sound of mortar blast hitting 2x in stereo. One on left and the other on the right further away. Great for battle or war scenes.", "author": "Mike Koenig", "href": "537-Mortar-Blast.html", "caption": "Mortar blasts hit in stereo.", "id": "537", "duration": 4.470625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=537&type=wav"} +{"title": "Galloping Horse", "description": "Awesome galloping horse sound effect great for cowboy or western scene. Could also be a medieval steed carrying a night into battle.", "author": "Mike Koenig", "href": "1302-Galloping-Horse.html", "caption": "A horse is galloping.", "id": "1302", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1302&type=wav"} +{"title": "Mallard Duck Quacking", "description": "More mallard duck quacking and talking of our fine feathered friends of the water.", "author": "Mike Koenig", "href": "1862-Mallard-Duck-Quacking.html", "caption": "Ducks are quacking.", "id": "1862", "duration": 2.61053125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1862&type=wav"} +{"title": "Slow Paper Rip", "description": "Construction paper being reipped slowloy for a longer sound effect.", "author": "Mike Koenig", "href": "1925-Slow-Paper-Rip.html", "caption": "Construction paper is being ripped.", "id": "1925", "duration": 5.2964375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1925&type=wav"} +{"title": "6 Cat Meows", "description": "Cat male or female meowing 6 times in a row take your pick of cat meows and cut that one out for games or movies.", "author": "Mr Smith", "href": "1685-6-Cat-Meows.html", "caption": "A cat is meowing.", "id": "1685", "duration": 7.982625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1685&type=wav"} +{"title": "Uh Oh Fart", "description": "This fart was a mistake. Sounds like the fart is saying uh oh. Still gross... just a little bit funnier than normal farts.", "author": "Mike Koenig", "href": "651-Uh-Oh-Fart.html", "caption": "Someone is farting.", "id": "651", "duration": 1.3941875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=651&type=wav"} +{"title": "Depth Charge 2", "description": "Depth Charge sound effect. This sound is great for a subsurface explosion in water. Like a depth charge or torpedo impact sound.", "author": "Mike Koenig", "href": "1604-Depth-Charge-2.html", "caption": "A depth charge or torpedo explosion sound.", "id": "1604", "duration": 1.1226875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1604&type=wav"} +{"title": "Clean Paper Rip", "description": "Nice clean and sharp paper ripping or paper tearing sound effect.", "author": "Mike Koenig", "href": "1930-Clean-Paper-Rip.html", "caption": "Paper is being torn.", "id": "1930", "duration": 1.1853125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1930&type=wav"} +{"title": "Kid Giggle 3x", "description": "Another funny sound of a kid giggling or laughing sound. This time there are 3 so if you want you can edit the one you want. Very cute great for a commercial or similar.", "author": "Mike Koenig", "href": "1117-Kid-Giggle-3x.html", "caption": "Kids are giggling or laughing.", "id": "1117", "duration": 5.21315625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1117&type=wav"} +{"title": "Alarm Clock", "description": "Alarm clock beeping sound effect was requested by Lmmn61i. 22 alarm beeps in all.", "author": "Mike Koenig", "href": "535-Alarm-Clock.html", "caption": "An alarm clock is beeping.", "id": "535", "duration": 10.88328125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=535&type=wav"} +{"title": "Toddler Laugh", "description": "Sound of a toddler, it is actually my son who is two laughing hysterically. Its really funny.", "author": "Mike Koenig", "href": "1303-Toddler-Laugh.html", "caption": "Someone's toddler is laughing hysterically.", "id": "1303", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1303&type=wav"} +{"title": "Crackle", "description": "A nice crackle or crackling sound effect.", "author": "Mike Koenig", "href": "942-Crackle.html", "caption": "There is a crackling sound.", "id": "942", "duration": 5.678625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=942&type=wav"} +{"title": "Fire Trucks Sirens 2", "description": "Another great fire truck siren sound effect. Very loud siren sound effect. Fire truck leaving fire station for an emergency.", "author": "FiremanSam", "href": "1494-Fire-Trucks-Sirens-2.html", "caption": "A fire truck siren is sounding.", "id": "1494", "duration": 13.9784375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1494&type=wav"} +{"title": "Happy Laughter", "description": "Laughter sound. Recorded in Russia", "author": "T Glasses", "href": "1565-Happy-Laughter.html", "caption": "Someone is laughing.", "id": "1565", "duration": 9.1965, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1565&type=wav"} +{"title": "Laugh To Self", "description": "The sound i make when i laugh to myself. Great laugh sound effect.", "author": "Mike Koenig", "href": "839-Laugh-To-Self.html", "caption": "Someone is laughing to themself.", "id": "839", "duration": 1.3879375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=839&type=wav"} +{"title": "Walking On Gravel", "description": "The sound of someone walking on gravel, or a small loose rock bed. Could be used for hiking or similar.", "author": "Caroline Ford", "href": "1432-Walking-On-Gravel.html", "caption": "Someone is walking on gravel or a small loose rock bed.", "id": "1432", "duration": 11.92125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1432&type=wav"} +{"title": "Warning Siren", "description": "Great air raid or warning siren simulation sound effect. Sound just like an air raid siren or warning siren.", "author": "snottyboy", "href": "1355-Warning-Siren.html", "caption": "An alarm is sounding.", "id": "1355", "duration": 7.5405625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1355&type=wav"} +{"title": "Church Ambiance", "description": "Church ambiance sound effects that include people whispering, a priest walking in hard sole shoes, and the church sounds.", "author": "stephan", "href": "1646-Church-Ambiance.html", "caption": "People are whispering in a church.", "id": "1646", "duration": 12.16965625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1646&type=wav"} +{"title": "Climbing Mt Everest", "description": "Climbing Mount Everest or walking in the snow crunching sound.", "author": "Mike Koenig", "href": "685-Climbing-Mt-Everest.html", "caption": "Snow is crunching underfoot.", "id": "685", "duration": 8.4636875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=685&type=wav"} +{"title": "Muscle Car", "description": "American Muscle Car revving engine up loud and strong. Very fast and heavy american engine. Engine revving loud", "author": "Daniel Simion", "href": "2209-Muscle-Car.html", "caption": "An engine is revving.", "id": "2209", "duration": 12.63215625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2209&type=wav"} +{"title": "House Fire Alarm", "description": "House Fire alarm sound effect. New fire alarm or smoke alarm beeping sound effect. Sound of a fire alarm from a house. Run, there is a fire!", "author": "Mike Koenig", "href": "1656-House-Fire-Alarm.html", "caption": "A fire alarm is beeping.", "id": "1656", "duration": 11.1539375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1656&type=wav"} +{"title": "Funny Voices", "description": "Silly and funny voices processed using Sound Forge and a pro mic setup. Very goofy vocal effects.", "author": "Daniel Simon", "href": "2152-Funny-Voices.html", "caption": "Silly vocal effects are heard.", "id": "2152", "duration": 15.45446875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2152&type=wav"} +{"title": "Shotgun Blast", "description": "Awesome single shotgun blast sound effect that is crisp and clear. You can feel the bass from this blast could also be an explosion", "author": "Jim Rogers", "href": "1919-Shotgun-Blast.html", "caption": "A shotgun blasts with a lot of bass.", "id": "1919", "duration": 1.95934375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1919&type=wav"} +{"title": "String Cheese Fart", "description": "A nice little fart wind breaking sound clip sound like string cheese.", "author": "Mike Koenig", "href": "792-String-Cheese-Fart.html", "caption": "A fart wind breaking sound clip.", "id": "792", "duration": 2.6089375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=792&type=wav"} +{"title": "Female Sigh", "description": "Female Sighing sound simple woman sound", "author": "HC", "href": "132-Female-Sigh.html", "caption": "A woman is sighing.", "id": "132", "duration": 2.7225625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=132&type=wav"} +{"title": "Old Movie Projector", "description": "Old movie projector sound effect. The sound of a an old projector like those used in the 70s and before.", "author": "Daniel Simon", "href": "2128-Old-Movie-Projector.html", "caption": "An old movie projector is making sounds.", "id": "2128", "duration": 50.93271875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2128&type=wav"} +{"title": "Metal Metronome", "description": "Sound of a metronome clicking and keeping time. This is a metal ping sounding metronome sound and is pretty standard. If you want to change the speed or pitch of this please be sure to visit the sound editing link on the bottom right of the page after downloading. This sound was requested by Sam.", "author": "Caroline Ford", "href": "915-Metal-Metronome.html", "caption": "A metronome is clicking.", "id": "915", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=915&type=wav"} +{"title": "Shorebirds Talking On Beach", "description": "A handful of shorebirds eat bread from tourist and chatter at the beach", "author": "fws.gov", "href": "272-Shorebirds-Talking-On-Beach.html", "caption": "Shorebirds are eating and chatting at the beach.", "id": "272", "duration": 12.47921875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=272&type=wav"} +{"title": "Wind Blowing", "description": "A storm was moving out and the wind was intense, so we recorded it. When weather changes temperature zones cause wind, in this case some really crazy blowing.", "author": "Mike Koenig", "href": "2125-Wind-Blowing.html", "caption": "Wind is blowing intensely after a storm.", "id": "2125", "duration": 141.77053125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2125&type=wav"} +{"title": "CD Skipping", "description": "That annoying sound that a cd makes when it skips. Great for skips, glitches, glitching, errors, and similar mishaps.", "author": "Mike Koenig", "href": "1195-CD-Skipping.html", "caption": "Sound of a CD skipping.", "id": "1195", "duration": 1.95265625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1195&type=wav"} +{"title": "Banging Radiator", "description": "The sound of someone banging or clanking a metal radiator. Several metal pings.", "author": "NPS", "href": "917-Banging-Radiator.html", "caption": "Someone is clanking a metal radiator.", "id": "917", "duration": 5.9628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=917&type=wav"} +{"title": "Sad", "description": "Some sad human is crying and very unhappy about something.", "author": "Mike Koenig", "href": "809-Sad.html", "caption": "Someone is crying.", "id": "809", "duration": 4.06165625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=809&type=wav"} +{"title": "Croaking 2x", "description": "Small little pond frog croaking 2x. Great little pond or swamp sound effect. Requested by Lorrie Watkins.", "author": "snottyboy", "href": "1340-Croaking-2x.html", "caption": "A frog is croaking.", "id": "1340", "duration": 1.32265625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1340&type=wav"} +{"title": "40 Cal Gun Shot X3", "description": "40 cal gun shot 3x. Great for a battle or war sequence. This gun shot sound was requested by Tabbitha, thanks Tabitha.", "author": "Mike Koenig", "href": "1229-40-Cal-Gun-Shot-X3.html", "caption": "A gun is firing.", "id": "1229", "duration": 1.72596875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1229&type=wav"} +{"title": "Kid Says Hey 4x", "description": "My son doing some vocal work for our site. He is 4 years old and is saying hey 4 times.", "author": "Mike Koenig", "href": "2013-Kid-Says-Hey-4x.html", "caption": "Someone is saying \"hey\".", "id": "2013", "duration": 6.8790625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2013&type=wav"} +{"title": "Anger", "description": "Male vocalizing anger and rage. Hired a vocal actor just for these audio bits. Use however you want just give us credit and tell your friends.", "author": "Mike Koenig", "href": "2027-Anger.html", "caption": "Someone is vocalizing anger.", "id": "2027", "duration": 20.84059375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2027&type=wav"} +{"title": "Drilling", "description": "Sound of drilling. Could be driling for oil, drilling at work, mining, or even used for some spooky or halloween sound effect.", "author": "Mike Koenig", "href": "1108-Drilling.html", "caption": "Drilling sound effect.", "id": "1108", "duration": 4.64878125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1108&type=wav"} +{"title": "Propeller", "description": "The sound of a propeller blade spinning or whirling.", "author": "Mike Koenig", "href": "1036-Propeller.html", "caption": "A propeller blade is spinning.", "id": "1036", "duration": 8.22859375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1036&type=wav"} +{"title": "Little Demon Girl Song", "description": "Scary Demon Girl Sings Song...Good For Horror Theme Songs", "author": "KillahChipmunk", "href": "1738-Little-Demon-Girl-Song.html", "caption": "A girl is singing.", "id": "1738", "duration": 20.09653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1738&type=wav"} +{"title": "Angry Pirate", "description": "Sound of a pirate thats angry. Great for a pirate or attacking scene or game.", "author": "Mike Koenig", "href": "858-Angry-Pirate.html", "caption": "A pirate is angry.", "id": "858", "duration": 2.43753125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=858&type=wav"} +{"title": "Dixie Horn", "description": "The classic Dixie Horn being played from a bus, car, or truck. Also known as the Dukes of Hazzard Horn. Its actually 5 different trumpets rigged to play in a pattern.", "author": "Daniel Simion", "href": "2179-Dixie-Horn.html", "caption": "Trumpets are playing in a pattern.", "id": "2179", "duration": 2.615125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2179&type=wav"} +{"title": "Small Airplane Long Flyby", "description": "Small Airplane or Aeroplane sound effect. This is one of two sounds in this set. This is the longer version about a full minute of a plane passing by.", "author": "Mike Koenig", "href": "1600-Small-Airplane-Long-Flyby.html", "caption": "An airplane is flying.", "id": "1600", "duration": 51.70440625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1600&type=wav"} +{"title": "Hawk Call 2x", "description": "Nice clean hawk call or hawk sound effect for bird lovers. Call 2x.", "author": "PsychoBird", "href": "1481-Hawk-Call-2x.html", "caption": "A hawk is calling twice.", "id": "1481", "duration": 3.31909375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1481&type=wav"} +{"title": "Phone Off Hook", "description": "Phone off hook, or phone dead sound. Great for murder scene, or spooky movie scene, or anything similar where things have run amuck.", "author": "Mike Koenig", "href": "1091-Phone-Off-Hook.html", "caption": "A phone is off the hook or dead, producing a beep sound.", "id": "1091", "duration": 12.79421875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1091&type=wav"} +{"title": "Nose Blowing", "description": "Another blowing nose sound effect of someone sick.", "author": "Mike Koenig", "href": "754-Nose-Blowing.html", "caption": "Someone is blowing their nose.", "id": "754", "duration": 1.3776875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=754&type=wav"} +{"title": "Motorcycle Pass By", "description": "A Motorcycle Pass By sound effect from SoundBible.com", "author": "BlastwaveFx.com", "href": "588-Motorcycle-Pass-By.html", "caption": "A motorcycle is passing by.", "id": "588", "duration": 4.765375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=588&type=wav"} +{"title": "Rope Swinging", "description": "A rope swing or tightening sound. You can hear the fibrous strands stretching.", "author": "Mike Koenig", "href": "391-Rope-Swinging.html", "caption": "A rope is swinging or tightening.", "id": "391", "duration": 2.5283125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=391&type=wav"} +{"title": "Hailstorm", "description": "Hailstorm sound effect was requested by sheryl cruz. Nice icey hail coming down in a storm and landing on roof.", "author": "Mike Koenig", "href": "1718-Hailstorm.html", "caption": "Hail is falling on a roof.", "id": "1718", "duration": 16.774625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1718&type=wav"} +{"title": "Beer Can Opening", "description": "Opening a can of beer sound pop", "author": "Mike Koenig", "href": "216-Beer-Can-Opening.html", "caption": "A can of beer is being opened with a pop.", "id": "216", "duration": 2.10540625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=216&type=wav"} +{"title": "Tearing Into Flesh", "description": "The sound of a monster or maniac tearing into flesh. Great for Halloween, haunted houses, or spooky movies!", "author": "nps.gov", "href": "928-Tearing-Into-Flesh.html", "caption": "Someone is tearing flesh.", "id": "928", "duration": 3.4010625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=928&type=wav"} +{"title": "Grocery Scanning", "description": "The sound of checkout scanner beeping many times as someone checks out after shopping. Grocery scanning sound requested by blissa!", "author": "Mike Koenig", "href": "820-Grocery-Scanning.html", "caption": "A checkout scanner is beeping many times.", "id": "820", "duration": 4.2751875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=820&type=wav"} +{"title": "Phone Ringing", "description": "Sound of a phone ringing, or telephone ringing off the hook sound.", "author": "acclivity", "href": "1518-Phone-Ringing.html", "caption": "A phone is ringing.", "id": "1518", "duration": 18.06475, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1518&type=wav"} +{"title": "Cat Scream", "description": "Sound of an angry or afraid cat screaming. Great for Halloween.", "author": "Ca9", "href": "1509-Cat-Scream.html", "caption": "A cat is screaming.", "id": "1509", "duration": 2.016, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1509&type=wav"} +{"title": "Hi Can I Take Your Order", "description": "Hi Can I Take Your Order from a fast food restaurant speaker in drive thru line. There are many many uses for this sound.", "author": "Mike Koenig", "href": "623-Hi-Can-I-Take-Your-Order.html", "caption": "A fast food restaurant speaker is taking an order.", "id": "623", "duration": 1.05653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=623&type=wav"} +{"title": "Sweeping Broom Shorter", "description": "Sound of an oldschool straw broom sweeping up some trash.", "author": "Mike Koenig", "href": "2112-Sweeping-Broom-Shorter.html", "caption": "A straw broom is sweeping up trash.", "id": "2112", "duration": 7.7538125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2112&type=wav"} +{"title": "Splash Rock In Lake", "description": "Sound of a rock or log being tossed into a lake or pond or river and making a splashing sound.", "author": "Ploor", "href": "2100-Splash-Rock-In-Lake.html", "caption": "A rock or log is being thrown into a body of water.", "id": "2100", "duration": 2.48746875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2100&type=wav"} +{"title": "Sewing Machine 3", "description": "Sound of an electric sewing machine running and sewing clothes or some other material together", "author": "Teto Yasha", "href": "1616-Sewing-Machine-3.html", "caption": "An electric sewing machine is running.", "id": "1616", "duration": 4.0079375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1616&type=wav"} +{"title": "Dial Up Modem", "description": "Dial Up Connection from PC Modem", "author": "Mike Koenig", "href": "136-Dial-Up-Modem.html", "caption": "A PC modem is connecting.", "id": "136", "duration": 39.2359375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=136&type=wav"} +{"title": "Tyrannosaurus Rex Roar", "description": "Sound of a tyrannosaurus rex roar or roaring. Great for a monster or other sound as well.", "author": "mike koenig", "href": "1748-Tyrannosaurus-Rex-Roar.html", "caption": "A tyrannosaurus rex is roaring.", "id": "1748", "duration": 2.7105, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1748&type=wav"} +{"title": "Close Door", "description": "Sound of a door closing. Close door sound can be used any time you need a generic close sound effect.", "author": "Mike Koenig", "href": "875-Close-Door.html", "caption": "A door is closing.", "id": "875", "duration": 1.65846875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=875&type=wav"} +{"title": "Alien AlarmDrum", "description": "A strange sound generated in Audacity. A weird drum beating 16 times this is loopable and sounds like an alien. Pretty cool sound.", "author": "KevanGC", "href": "1633-Alien-AlarmDrum.html", "caption": "A weird drum sound is generated.", "id": "1633", "duration": 12.69209375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1633&type=wav"} +{"title": "Fan Startup", "description": "Fan starting up sound. Start of a small or medium sized fan above the stove in kitchen.", "author": "Mike Koenig", "href": "507-Fan-Startup.html", "caption": "A fan is starting up.", "id": "507", "duration": 12.39403125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=507&type=wav"} +{"title": "FogHorn Barge", "description": "A large barge blasts his Fog Horn to warn others of his arrival.", "author": "Daniel Simon", "href": "2142-FogHorn-Barge.html", "caption": "A barge is blasting its foghorn.", "id": "2142", "duration": 4.9589375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2142&type=wav"} +{"title": "Car Loosing Control", "description": "A car spining out of control or loosing control sound. Great for an auto scene or car game.", "author": "NPS.gov", "href": "1046-Car-Loosing-Control.html", "caption": "A car is losing control.", "id": "1046", "duration": 6.46678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1046&type=wav"} +{"title": "Balloon Blowing Up", "description": "Sound of a balloon blowing up, 1.9 second sound effect.", "author": "NFour", "href": "1417-Balloon-Blowing-Up.html", "caption": "A balloon is being blown up.", "id": "1417", "duration": 1.81409375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1417&type=wav"} +{"title": "Medium Pack Of Wolves Howling", "description": "A medium size pack of wolves about 6 or 7 howling and moaning at the moon at dusk. You can also hear the crickets and a few birds", "author": "fws.gov", "href": "277-Medium-Pack-Of-Wolves-Howling.html", "caption": "A pack of wolves is howling.", "id": "277", "duration": 20.281, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=277&type=wav"} +{"title": "Baby Talk", "description": "Very cute baby babbling or baby talk sound clip. Baby says 3 sounds.", "author": "stephan", "href": "1784-Baby-Talk.html", "caption": "Baby babbling or baby talk sound clip.", "id": "1784", "duration": 4.4148125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1784&type=wav"} +{"title": "Electric Typewriter", "description": "Person typing away at an electric typewriter. Clicks can be heard while a person types.", "author": "Daniel Simion", "href": "2168-Electric-Typewriter.html", "caption": "Someone is typing on an electric typewriter.", "id": "2168", "duration": 44.40340625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2168&type=wav"} +{"title": "Rattlesnake Rattle", "description": "Rattlesnake rattle sound effect from fws.gov", "author": "MIke Koenig", "href": "237-Rattlesnake-Rattle.html", "caption": "A rattlesnake is making a rattling sound.", "id": "237", "duration": 15.145, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=237&type=wav"} +{"title": "Zombie On The Loose", "description": "Sound of a Zombie on the Loose! Zombie sounds requested by jordangiese.", "author": "NPS.gov", "href": "1043-Zombie-On-The-Loose.html", "caption": "A zombie is moaning.", "id": "1043", "duration": 5.48546875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1043&type=wav"} +{"title": "Civil War Drummer ", "description": "Soldier marching drums. User Richy requested a Soldiers Slow March snare drum sound.", "author": "DrumM8", "href": "1512-Civil-War-Drummer-.html", "caption": "Soldiers are marching with drums.", "id": "1512", "duration": 16.90415625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1512&type=wav"} +{"title": "Hello", "description": "The sound of a male saying the word hello. Great spoken word human sound.", "author": "Mike Koenig", "href": "769-Hello.html", "caption": "A male is saying \"hello\".", "id": "769", "duration": 1.31040625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=769&type=wav"} +{"title": "Fuse Burning", "description": "Sound of a fuse burning on a stick of dynamite", "author": "Mike Koenig", "href": "126-Fuse-Burning.html", "caption": "A fuse is burning on a stick of dynamite.", "id": "126", "duration": 1.41525, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=126&type=wav"} +{"title": "Page Turn", "description": "Created by Mark DiAngelo. lol I turned a page", "author": "Mark DiAngelo", "href": "2066-Page-Turn.html", "caption": "Someone is turning a page.", "id": "2066", "duration": 1.0080625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2066&type=wav"} +{"title": "Fart Strain", "description": "Someone straining to fart. This fart sounds like it took a little more effort than those other farts. Hard work really does pay off.", "author": "Mike Koenig", "href": "648-Fart-Strain.html", "caption": "Someone is straining to fart.", "id": "648", "duration": 1.0515, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=648&type=wav"} +{"title": "Breaking Sound Barrier", "description": "Sonic Boom sound effect made by an F-14 breaking the sound barrier at an air show while passing directly overhead.", "author": "AirMan", "href": "1644-Breaking-Sound-Barrier.html", "caption": "A plane is breaking the sound barrier.", "id": "1644", "duration": 4.18934375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1644&type=wav"} +{"title": "Magic Wand Noise", "description": "Magic noise was requested by Ikki Yeong and can be used for a magician changing form or waving his magic wand. Thanks for the request Ikki.", "author": "Mike Koenig", "href": "474-Magic-Wand-Noise.html", "caption": "Magic noise is heard.", "id": "474", "duration": 5.41646875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=474&type=wav"} +{"title": "A Tone", "description": "A single note to replace your default windows beep. Nice calm and enchanting.", "author": "His Self", "href": "1815-A-Tone.html", "caption": "A single note is playing to replace a default windows beep.", "id": "1815", "duration": 1.7143125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1815&type=wav"} +{"title": "Taking A Bite", "description": "Taking a bite of something. great bite sound effect. Nice crisp and clear crunch. Could also be used for a bone break i imagine.", "author": "Mike Koenig", "href": "1304-Taking-A-Bite.html", "caption": "Someone is taking a bite of something with a crisp crunch.", "id": "1304", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1304&type=wav"} +{"title": "Frogs", "description": "A chorus of many frogs singing together. Sounds like you are in a swamp or wet ditch after a rainstorm, or at sunset. Thanks to Lisa Redfern for the nice aquatic sounds.", "author": "Lisa Redfern", "href": "2033-Frogs.html", "caption": "Frogs are singing in a swamp or wet ditch.", "id": "2033", "duration": 10.90159375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2033&type=wav"} +{"title": "Thunder Strike 2", "description": "2 of 3 thunder or lightning strikes that were recorded very clean and crisp during a very strong summer storm.", "author": "Mike Koenig", "href": "2016-Thunder-Strike-2.html", "caption": "Thunder strikes are happening during a storm.", "id": "2016", "duration": 25.1704375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2016&type=wav"} +{"title": "Thunder Storm", "description": "Thunder Storm recorded in backyard", "author": "Mike Koenig", "href": "82-Thunder-Storm.html", "caption": "A thunderstorm is happening.", "id": "82", "duration": 15.81571875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=82&type=wav"} +{"title": "Street", "description": "Street sounds. Field recording of a urban or city street or road. Great urban soundscape. Cars and trucks driving by. Breaks squeaking, horns honking engines revving.", "author": "Daniel Simion", "href": "2175-Street.html", "caption": "Cars and trucks are driving by on a city street.", "id": "2175", "duration": 49.71446875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2175&type=wav"} +{"title": "Dial Tone American", "description": "Dial tone recorded from an American telephone land line. This is the tone you hear when you pick up a landline in the United States. A combination of the frequencies 350 Hz and 440 Hz.", "author": "Daniel Simion", "href": "2181-Dial-Tone-American.html", "caption": "A dial tone is heard on a landline phone.", "id": "2181", "duration": 4.0079375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2181&type=wav"} +{"title": "Movie Freaky Scene", "description": "A great freaky movie sound effect or drone made with alot of reverb and some creativity.", "author": "Mike Koenig", "href": "188-Movie-Freaky-Scene.html", "caption": "A freaky movie sound effect or drone with reverb.", "id": "188", "duration": 25, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=188&type=wav"} +{"title": "Sniff Long", "description": "Sniff or smelling sound effect. Sniffing sound. Breathe sounds as well.", "author": "Caroline Ford", "href": "956-Sniff-Long.html", "caption": "Someone is sniffing.", "id": "956", "duration": 5.67353125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=956&type=wav"} +{"title": "Restaurant Walla Track", "description": "Restaurant walla track from a restaurant in nc", "author": "Mike Koenig", "href": "508-Restaurant-Walla-Track.html", "caption": "People are speaking in a restaurant.", "id": "508", "duration": 13.0928125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=508&type=wav"} +{"title": "Truck Drive By", "description": "The sound of a large truck driving by or passing by us.", "author": "Mike Koenig", "href": "601-Truck-Drive-By.html", "caption": "A truck is passing by.", "id": "601", "duration": 5.566875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=601&type=wav"} +{"title": "Chain Dropped", "description": "The sound of a heavy chain being dropped on a wood or wooden surface. Great wood and metal noise.", "author": "Mike Koenig", "href": "559-Chain-Dropped.html", "caption": "A chain is dropped on a surface.", "id": "559", "duration": 4.4496875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=559&type=wav"} +{"title": "Frogs In The Rainforest", "description": "Rainforest or Wetland Frogs chirping and talking to each other", "author": "fws.gov", "href": "251-Frogs-In-The-Rainforest.html", "caption": "Frogs are chirping and communicating in a rainforest or wetland.", "id": "251", "duration": 23.425, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=251&type=wav"} +{"title": "Hummingbird", "description": "Sound of a small hummingbird recorded by the NPS. Public domain sound so have fun with it.", "author": "Mike Koenig", "href": "940-Hummingbird.html", "caption": "A hummingbird is humming.", "id": "940", "duration": 3.64165625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=940&type=wav"} +{"title": "Mystic Chanting 3", "description": "Some kind of mystic chanting", "author": "Marianne Gagnon", "href": "1732-Mystic-Chanting-3.html", "caption": "Chanting is heard.", "id": "1732", "duration": 1.61959375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1732&type=wav"} +{"title": "Helicopter", "description": "Sound of a helicopter flying and passing overhead on a battlefield", "author": "navaneetha kris", "href": "1740-Helicopter.html", "caption": "A helicopter is flying.", "id": "1740", "duration": 11.3893125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1740&type=wav"} +{"title": "Dove", "description": "Morning dove also spelled mourning dove... song sound effect. Nice brid call sound effect for the nature lovers out there.", "author": "Mike Koenig", "href": "1850-Dove.html", "caption": "A dove is cooing.", "id": "1850", "duration": 4.10740625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1850&type=wav"} +{"title": "Water", "description": "Running water sound. Sound of tap water or a small stream or babbling brook. Thanks to Lisa Redfern for another high quality sound effect.", "author": "Lisa Redfern", "href": "2032-Water.html", "caption": "Running water is heard from a tap or stream.", "id": "2032", "duration": 13.46721875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2032&type=wav"} +{"title": "Whales Spouting Out Water", "description": "Whales spouting or blowing water out their blowholes far out at sea", "author": "fws.gov", "href": "276-Whales-Spouting-Out-Water.html", "caption": "Whales are spouting.", "id": "276", "duration": 32.36578125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=276&type=wav"} +{"title": "Tasmanian Devil", "description": "Tasmanian Devil growling screaming hissing. Warning sounds from a Tasmanian Devil in Zoo.", "author": "Daniel Simion", "href": "2208-Tasmanian-Devil.html", "caption": "A Tasmanian Devil is growling and screaming.", "id": "2208", "duration": 6.50009375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2208&type=wav"} +{"title": "Slowed Breathing", "description": "Slow breathing almost close to mic. Could potentially be used in one of those scenes in a movie when someone is in shock or cant hear because of a bomb blast or crash or something.", "author": "Kibblesbob", "href": "1813-Slowed-Breathing.html", "caption": "Someone is breathing slowly close to a microphone.", "id": "1813", "duration": 11.59225, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1813&type=wav"} +{"title": "Teacher Charlie Brown Talking", "description": "Funny sound effect like the teacher in charlie brown. An audible yet gibberish cartoon speech sound.", "author": "Mike Koenig", "href": "1298-Teacher-Charlie-Brown-Talking.html", "caption": "A cartoon speech sound is being made.", "id": "1298", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1298&type=wav"} +{"title": "Heart Beat", "description": "Manipulated sound of a sheet of paper. Really Deep sound.", "author": "Zarabadeu", "href": "1673-Heart-Beat.html", "caption": "A deep sound of a sheet of paper being manipulated.", "id": "1673", "duration": 6.30525, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1673&type=wav"} +{"title": "Cat Meow 2", "description": "A cat mewoing very clearly 2 times in a row.", "author": "Cat Stevens", "href": "1954-Cat-Meow-2.html", "caption": "A cat is meowing twice.", "id": "1954", "duration": 5.06778125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1954&type=wav"} +{"title": "Rain", "description": "Raining sound effect without lightning, sounds of water coming down from sky.", "author": "Pwlae", "href": "1999-Rain.html", "caption": "Rain is falling.", "id": "1999", "duration": 70.4958125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1999&type=wav"} +{"title": "Pump", "description": "Pump or pumping action sound effect. could be used for a bike pump, or other inflating sound effect.", "author": "ezwa", "href": "1390-Pump.html", "caption": "Something is being pumped.", "id": "1390", "duration": 7.95746875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1390&type=wav"} +{"title": "Drum Roll", "description": "Drum Roll sound effect from a drummer. Drum roll please!", "author": "Mike Koenig", "href": "716-Drum-Roll.html", "caption": "A drummer is doing a drum roll.", "id": "716", "duration": 1.7308125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=716&type=wav"} +{"title": "Gavel Bangs 4x", "description": "Gavel banging sound effect, or a judges gavel banging in courtroom was requested by both Willy Akers and Pavithra. Thanks for the sound effect requests.", "author": "minuteman", "href": "1678-Gavel-Bangs-4x.html", "caption": "A gavel is banging.", "id": "1678", "duration": 1.4625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1678&type=wav"} +{"title": "Airplane Fly Over", "description": "Air Plane Sound Effect from a small passenger plane flying over head. My house is located a few mile from an amateur air port for small general aviation personal aircraft. Just a few small hangers is all that is there but they fly by often .", "author": "Mike Koenig", "href": "1587-Airplane-Fly-Over.html", "caption": "An airplane is flying overhead.", "id": "1587", "duration": 46.25675, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1587&type=wav"} +{"title": "IM Reply Computer", "description": "Could be used as an alert, or ip reply sound for computer or similar", "author": "Mike Koenig", "href": "187-IM-Reply-Computer.html", "caption": "An alert or computer reply sound.", "id": "187", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=187&type=wav"} +{"title": "Tape Deck", "description": "Super retro tape deck sound effect from a cassette player in a car. It has the click and reel sound effect, like you just popped a tape in and its starting.", "author": "stephan", "href": "1549-Tape-Deck.html", "caption": "A tape deck is playing.", "id": "1549", "duration": 7.915125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1549&type=wav"} +{"title": "Sonar Ping", "description": "4 Long sonar pings in stereo. Great uboat, or wwii submarine sound effect. Sound effect recorded from pd wwii film, then mastered and put into stereo. Thanks to Mark Pancino for the request.", "author": "Mike Koenig", "href": "1184-Sonar-Ping.html", "caption": "Some sonar pings are heard in stereo.", "id": "1184", "duration": 24.92609375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1184&type=wav"} +{"title": "Bouncing Golf Ball", "description": "Sound of a golf ball bouncing and then coming to a stop.", "author": "Mike Koenig", "href": "1071-Bouncing-Golf-Ball.html", "caption": "A golf ball is bouncing and coming to a stop.", "id": "1071", "duration": 4.48434375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1071&type=wav"} +{"title": "Little Girl Sigh", "description": "Little girl sighing sound effect,or sigh of a little girl. This sound was requested by July.", "author": "BlastwaveFx.com", "href": "629-Little-Girl-Sigh.html", "caption": "A little girl is sighing.", "id": "629", "duration": 1.5413125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=629&type=wav"} +{"title": "Gorilla", "description": "Very cool gorilla sound. Great for a zoo, or primate and monkey scene. The sound is public domain so thats a bonus.", "author": "Mike Koenig", "href": "1149-Gorilla.html", "caption": "A gorilla is making a sound.", "id": "1149", "duration": 2.42125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1149&type=wav"} +{"title": "Firecrackers Going Off", "description": "Great Firecrackers going off or fireworks sound effect requested by Mike", "author": "Mike Koenig", "href": "691-Firecrackers-Going-Off.html", "caption": "Firecrackers or fireworks are exploding.", "id": "691", "duration": 6.41390625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=691&type=wav"} +{"title": "Large SUV Pass By", "description": "A very large SUV Passing by our vehicle at a gas station.", "author": "Mike Koenig", "href": "611-Large-SUV-Pass-By.html", "caption": "A large SUV is passing by.", "id": "611", "duration": 5.64728125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=611&type=wav"} +{"title": "Strange Noise", "description": "Some wicked crazy strange pulsing panning alien like noise. Looking for a strange noise? Here it is.", "author": "Mike Koenig", "href": "1016-Strange-Noise.html", "caption": "A strange pulsing alien noise is happening.", "id": "1016", "duration": 16.1041875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1016&type=wav"} +{"title": "Swords Clashing", "description": "Medieval swords clashing with each other. Great roman or gladiator war or fighting sounds.", "author": "Mike Koenig", "href": "857-Swords-Clashing.html", "caption": "Medieval swords are clashing.", "id": "857", "duration": 2.39928125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=857&type=wav"} +{"title": "Breathing", "description": "Some great breathe sound effects by human. Could be warped to make some alien sounds.", "author": "Mike Koenig", "href": "777-Breathing.html", "caption": "Someone is breathing.", "id": "777", "duration": 18.83140625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=777&type=wav"} +{"title": "Groan And Grunt", "description": "Old person grunting or in pain. Groan sounds used for pain or suffering or just to emphasize movement.", "author": "Mike Koenig", "href": "854-Groan-And-Grunt.html", "caption": "An old person is grunting.", "id": "854", "duration": 3.77275, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=854&type=wav"} +{"title": "Frog Croaking", "description": "Clear sound of a bullfrog croaking. Bull frog call requested by Lorrie Watkins. Great nature or swamp sound effect.", "author": "snottyboy", "href": "1333-Frog-Croaking.html", "caption": "A bullfrog is croaking.", "id": "1333", "duration": 7.93496875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1333&type=wav"} +{"title": "TomCat", "description": "Tomcat meowing or kitty cat meowing. Great feline sound for movies or games.", "author": "Mr Smith", "href": "1687-TomCat.html", "caption": "A cat is meowing.", "id": "1687", "duration": 1.979, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1687&type=wav"} +{"title": "Strong Punch", "description": "Nice strong punch or punching sound effect. Nice for kung fu boxing or other fight scene or game.", "author": "Mike Koenig", "href": "1773-Strong-Punch.html", "caption": "A punch is being thrown.", "id": "1773", "duration": 1.00125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1773&type=wav"} +{"title": "Sliding Door", "description": "Nice clean and clear sliding door sound effect. This sounds in the public domain so there are no limitations on its use.", "author": "ezwa", "href": "1353-Sliding-Door.html", "caption": "A sliding door is opening or closing.", "id": "1353", "duration": 3.71521875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1353&type=wav"} +{"title": "Industrial Sounds", "description": "This sound is of an industrial was machine at the beach. OBX. It sounds like a repetative manufacturing machine or similar and so could be used for most any machine sounds.", "author": "Mike Koenig", "href": "610-Industrial-Sounds.html", "caption": "Industrial washing machine sound.", "id": "610", "duration": 13.88746875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=610&type=wav"} +{"title": "Stretching Growing", "description": "Sound of something stretching or growing. Nice growing sound effect. Great for power up, level up, and similar.", "author": "Mike Koenig", "href": "1115-Stretching-Growing.html", "caption": "Something is growing or stretching.", "id": "1115", "duration": 2.3938125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1115&type=wav"} +{"title": "Shotgun 12ga Fire", "description": "An awesome and excellent quality sound of action-pump shot fire of an spas 12 combat shotgun.", "author": "RA The Sun God", "href": "1958-Shotgun-12ga-Fire.html", "caption": "A combat shotgun is being fired.", "id": "1958", "duration": 1.9586875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1958&type=wav"} +{"title": "Submarine Diving", "description": "A NAVY submarine setting dive alarm and plunging to a thousand feet. Great for military video or game.", "author": "Daniel Simion", "href": "2176-Submarine-Diving.html", "caption": "A submarine is setting a dive alarm and descending.", "id": "2176", "duration": 9.37903125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2176&type=wav"} +{"title": "Small Dog Barking", "description": "A small dog barking. Maybe a maltese or havanese, or some other small breed of dog. We love to troll our dog with this sound. Turn if up and watch your dog go crazy.", "author": "Daniel Simion", "href": "2174-Small-Dog-Barking.html", "caption": "A small dog is barking.", "id": "2174", "duration": 23.79825, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2174&type=wav"} +{"title": "Ice Skating", "description": "Sound of someone Ice skating on ice at a skating rink. Person is tearing up some ice with their metal skate blades. Could be used for ice hockey or simply chopped up and used as a scraping sound.", "author": "Daniel Simion", "href": "2198-Ice-Skating.html", "caption": "Someone is ice skating on a rink.", "id": "2198", "duration": 34.6348125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2198&type=wav"} +{"title": "Water Down Gutter 3", "description": "Water running down gutter drain 3. Cool gargling swishing water sound from the front of my house.", "author": "Mike Koenig", "href": "434-Water-Down-Gutter-3.html", "caption": "Water is running down a gutter.", "id": "434", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=434&type=wav"} +{"title": "Plate Shatter Break", "description": "Plate Shatter Break it almost bounces then breaks.", "author": "Mike Koenig", "href": "108-Plate-Shatter-Break.html", "caption": "A plate is shattering on the floor.", "id": "108", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=108&type=wav"} +{"title": "Hammering", "description": "Sound of a worker or carpenter hammering a nail into a plank of wood. The thump of the hammer can be heard reverberating through the 2x4.", "author": "J Blow", "href": "2028-Hammering.html", "caption": "A worker is hammering a nail into wood.", "id": "2028", "duration": 6.9865625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2028&type=wav"} +{"title": "Pat On The Back", "description": "Someone giving someone else a pat on the back. Good job or other such rewarding things.", "author": "Mike Koenig", "href": "823-Pat-On-The-Back.html", "caption": "Someone is giving a pat on the back.", "id": "823", "duration": 1.05653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=823&type=wav"} +{"title": "Audience Applause", "description": "The audience applauding the show. Great large crowd applause. Thanks to Mattiew11", "author": "Matthiew11", "href": "2087-Audience-Applause.html", "caption": "The audience is applauding.", "id": "2087", "duration": 6.58275, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2087&type=wav"} +{"title": "Baby Rattle", "description": "Baby rattle sound was requested by Jocelyn. Can be used for a toy or baby rattle maybe even a rattle snake Enjoy.", "author": "Mike Koenig", "href": "1714-Baby-Rattle.html", "caption": "A rattle is rattling.", "id": "1714", "duration": 3.5143125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1714&type=wav"} +{"title": "Sonar", "description": "Long sonar ping in stereo. Great uboat, or wwii submarine sound effect. Sound effect recorded from pd wwii film, then mastered and put into stereo. Thanks to Mark Pancino for the request.", "author": "Mike Koenig", "href": "1183-Sonar.html", "caption": "Long sonar ping in stereo.", "id": "1183", "duration": 6.23153125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1183&type=wav"} +{"title": "Jingle Sound Of Keys", "description": "My car and house keys jingling on my key chain", "author": "Mike Koenig", "href": "176-Jingle-Sound-Of-Keys.html", "caption": "Keys are jingling on a chain.", "id": "176", "duration": 5.86303125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=176&type=wav"} +{"title": "Drop Sword", "description": "The sound of a sword or axe being dropped. Great large metal object ping.", "author": "Mike Koenig", "href": "906-Drop-Sword.html", "caption": "A sword or axe is dropped.", "id": "906", "duration": 1.1135625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=906&type=wav"} +{"title": "UFO Landing", "description": "UFO Landing alien spacecraft lands", "author": "Mike Koenig", "href": "147-UFO-Landing.html", "caption": "An alien spacecraft is landing.", "id": "147", "duration": 4.7804375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=147&type=wav"} +{"title": "Rain", "description": "Great rain or raining sound effect. Medium size rainstorm sound effect, with small rumbling thunder in distance.", "author": "Mike Koenig", "href": "1158-Rain.html", "caption": "It is raining with distant thunder.", "id": "1158", "duration": 15.82015625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1158&type=wav"} +{"title": "Night Rain In Russian City", "description": "The night rain in the Nizhny Novgorod city Russia. Recorded on Zoom H1.", "author": "Alexander Tram", "href": "2059-Night-Rain-In-Russian-City.html", "caption": "Rain is falling.", "id": "2059", "duration": 62.612625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2059&type=wav"} +{"title": "Ringing Phone", "description": "A telephone ringing just 1 time from the perspective of the caller or person who just dialed the numbe", "author": "Mike Koenig", "href": "1868-Ringing-Phone.html", "caption": "A phone is ringing once.", "id": "1868", "duration": 4.64159375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1868&type=wav"} +{"title": "Evil Laugh", "description": "The sound of an Evil Laugh from some evil dude. Scary great for Halloween or some scary movie.", "author": "Mike Koenig", "href": "837-Evil-Laugh.html", "caption": "An evil person is laughing.", "id": "837", "duration": 1.75059375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=837&type=wav"} +{"title": "Squishing", "description": "Great squishy, or squelchy sound recorded. The sound was requested by Caroline Ford", "author": "Mike Koenig", "href": "513-Squishing.html", "caption": "A squishy or squelchy sound is heard.", "id": "513", "duration": 1.47590625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=513&type=wav"} +{"title": "No Dear", "description": "My wife saying no dear thats wrong. Something i hear often to tell you the truth. This vocal was requested by sanja.", "author": "NPS", "href": "937-No-Dear.html", "caption": "Someone's wife is correcting them.", "id": "937", "duration": 1.53253125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=937&type=wav"} +{"title": "Stab And Tear Flesh", "description": "The sound of someone stabbing and then tearing flesh from the bone. Great for Halloween or haunted house.", "author": "Mike Koenig", "href": "924-Stab-And-Tear-Flesh.html", "caption": "Someone is stabbing and tearing flesh.", "id": "924", "duration": 3.52, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=924&type=wav"} +{"title": "Shampoo Hair", "description": "Sound of someone shampooing their hair or washing a animal or similar sound effect. Great washing or bathing sound effect. Original sound by natalie, I cleaned up the audio and removed background noise, bumps, clicks, and needless blank sound.", "author": "mike koenig", "href": "1558-Shampoo-Hair.html", "caption": "Someone is washing something.", "id": "1558", "duration": 6.27165625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1558&type=wav"} +{"title": "Whistle Get Attention", "description": "Whistle sound to get attention. Need a whistle sound effect get one free here.", "author": "Mike Koenig", "href": "770-Whistle-Get-Attention.html", "caption": "Someone is whistling to get attention.", "id": "770", "duration": 1.3535625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=770&type=wav"} +{"title": "Hawk Screeching", "description": "Sound of a hawk screeching with no effects processing added. Next screeching sound is of a hawk or eagle but it is made to sound like it is in a valley or high attop a cliff.", "author": "Mike Koenig", "href": "1844-Hawk-Screeching.html", "caption": "A hawk is screeching in a valley or high up a cliff.", "id": "1844", "duration": 1.726125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1844&type=wav"} +{"title": "Airplane Takeoff", "description": "Airplane on a runway speeding up and taking off. Sound recorded from inside the cockpit.", "author": "Daniel Simion", "href": "2195-Airplane-Takeoff.html", "caption": "An airplane is taking off.", "id": "2195", "duration": 45.8550625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2195&type=wav"} +{"title": "Old Record Player", "description": "Sound of a very old record player, not just your standard record player from the 70s and 80s.", "author": "Daniel Simon", "href": "2131-Old-Record-Player.html", "caption": "An old record player is making sounds.", "id": "2131", "duration": 60.6436875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2131&type=wav"} +{"title": "Machine Gun Burst 50 Cal", "description": "50 caliber machine gun burst. 3 burst of from an automatic 50 cal machine gunner. Great for a battle or war sequence.", "author": "Mike Koenig", "href": "1228-Machine-Gun-Burst-50-Cal.html", "caption": "An automatic gun is firing.", "id": "1228", "duration": 1.96065625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1228&type=wav"} +{"title": "Police Scanner Chatter", "description": "Male police officer speaks about a handgun and retaliation to witness information.", "author": "PoliceScan", "href": "1640-Police-Scanner-Chatter.html", "caption": "Someone talks about a handgun and retaliation.", "id": "1640", "duration": 11.38940625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1640&type=wav"} +{"title": "Sci Fi Robot", "description": "Sci fi robot or science fiction robot moving. Great for a robot walking or moving his arm or even rotating appendages.", "author": "National Park Servic", "href": "756-Sci-Fi-Robot.html", "caption": "A sci-fi robot is moving.", "id": "756", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=756&type=wav"} +{"title": "Car Door Close", "description": "The sound of a our car door closing. Very crisp and clear sound. Nice automotive sound effect, could be used for any shutting or closing sound.", "author": "Mike Koenig", "href": "846-Car-Door-Close.html", "caption": "A car door is closing.", "id": "846", "duration": 1.273625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=846&type=wav"} +{"title": "Best Cardinal Bird", "description": "The sound of a cardinal bird call. This is a nice clean sound effect. Enjoy.", "author": "PsychoBird", "href": "1515-Best-Cardinal-Bird.html", "caption": "A cardinal is calling.", "id": "1515", "duration": 3.1328125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1515&type=wav"} +{"title": "Screw In", "description": "Sound of a heavy metal cap being screwed into or onto something.", "author": "Mike Koenig", "href": "2111-Screw-In.html", "caption": "A metal cap is being screwed onto something.", "id": "2111", "duration": 4.31946875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2111&type=wav"} +{"title": "Click Button 2", "description": "Yet another good button click or pushing sound effect.", "author": "Mike Koenig", "href": "185-Click-Button-2.html", "caption": "A button is being clicked or pushed.", "id": "185", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=185&type=wav"} +{"title": "Small Chain", "description": "The sound of a small chain or charm bracelet. Nice little clinkety clank sound effects.", "author": "Mike Koenig", "href": "1106-Small-Chain.html", "caption": "A small chain or charm bracelet is clinking.", "id": "1106", "duration": 2.65384375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1106&type=wav"} +{"title": "Cat Collar Jingle", "description": "Cat Collar Jingle of bell as cat walks", "author": "Mike Koenig", "href": "118-Cat-Collar-Jingle.html", "caption": "A cat collar is jingling as a cat walks.", "id": "118", "duration": 1.44221875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=118&type=wav"} +{"title": "Missle Launch", "description": "A missile is fired and travels a distance before fading out. Nice for a war or launch sequence.", "author": "Kibblesbob", "href": "1794-Missle-Launch.html", "caption": "Missile launch sound effect, suitable for war or launch sequences.", "id": "1794", "duration": 4.37659375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1794&type=wav"} +{"title": "Bleat", "description": "A billy goat bleat sound effect. This is a long bleat and great for farm, goat, or mountain sounds.", "author": "Mike Koenig", "href": "821-Bleat.html", "caption": "A billy goat is bleating.", "id": "821", "duration": 1.6404375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=821&type=wav"} +{"title": "Plastic Bottle Crush", "description": "The crushing of a plastic bottle. Thanks again to Simon Craggs!", "author": "Simon Craggs", "href": "1972-Plastic-Bottle-Crush.html", "caption": "A plastic bottle is being crushed.", "id": "1972", "duration": 1.188, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1972&type=wav"} +{"title": "Copier Machine", "description": "A synthesized copier machine sound made by piecing together electrical impact sounds", "author": "Mike Koenig", "href": "348-Copier-Machine.html", "caption": "A copier machine is synthesizing.", "id": "348", "duration": 11.2226875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=348&type=wav"} +{"title": "Alien Death Ray", "description": "Sound of an alien death ray or weapon being fired or engaged. Great for sci fi games and stuff.", "author": "Mike Koenig", "href": "1274-Alien-Death-Ray.html", "caption": "A weapon is firing.", "id": "1274", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1274&type=wav"} +{"title": "Hammering", "description": "Rhythmic hammering on a nail with a hammer. Thanks to Lisa Redfern for the donation.", "author": "Lisa Redfern", "href": "2082-Hammering.html", "caption": "A hammer is hitting a nail rhythmically.", "id": "2082", "duration": 6.5085, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2082&type=wav"} +{"title": "Atomic Bomb", "description": "Another breath test with enhanced bass support. Sounds like an atomic bomb to me. Big thanks to Sound Explorer for another great sound.", "author": "Sound Explorer", "href": "1983-Atomic-Bomb.html", "caption": "A breath test creates an atomic bomb-like sound.", "id": "1983", "duration": 11.27365625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1983&type=wav"} +{"title": "Termites and Ants", "description": "Sound of termites and ants crawling around and chewing on things. Could be used for any small bug sound really like a beetlw or spider.", "author": "Mike Koenig", "href": "2113-Termites-and-Ants.html", "caption": "Termites and ants are chewing on things.", "id": "2113", "duration": 7.61309375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2113&type=wav"} +{"title": "Swimming Pool Ambiance", "description": "Swimming Pool Summer Ambiance recorded at indoor aquatic center. Sound recorded by Stephan and is in the public domain.", "author": "Stephan Moebius", "href": "1267-Swimming-Pool-Ambiance.html", "caption": "Water is splashing.", "id": "1267", "duration": 20.9753125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1267&type=wav"} +{"title": "Pop Clip In", "description": "Glock 17 9mm inserting a clip or magazine. High resolution recording of an actual Glock 17 9mm. Very clear gun sound.", "author": "Mike Koenig", "href": "1404-Pop-Clip-In.html", "caption": "A firearm is inserting a clip or magazine.", "id": "1404", "duration": 1.06646875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1404&type=wav"} +{"title": "Kid Giggle 2", "description": "Another funny sound of a kid giggling or laughing sound. Very cute great for a commercial or similar.", "author": "Mike Koenig", "href": "1123-Kid-Giggle-2.html", "caption": "A kid is giggling.", "id": "1123", "duration": 1.63703125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1123&type=wav"} +{"title": "Please Open The Door Loud", "description": "A woman or female talking asking someone to open the door. This one is more demanding than the last. Requested by somnath", "author": "Mike Koenig", "href": "638-Please-Open-The-Door-Loud.html", "caption": "Someone is asking to open a door.", "id": "638", "duration": 1.57896875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=638&type=wav"} +{"title": "Elves Laughing High Pitch", "description": "Elves laughing in a high pitch laugh", "author": "Mike Koenig", "href": "170-Elves-Laughing-High-Pitch.html", "caption": "Elves are laughing in a high pitch.", "id": "170", "duration": 12.031875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=170&type=wav"} +{"title": "Frying Pan Hit", "description": "The sound of a frying pan or skillet hitting someone in the head, great for cartoon or movie scene. The sound was requested by Barry Holcomb. Thanks Barry.", "author": "Mike Koenig", "href": "1004-Frying-Pan-Hit.html", "caption": "A skillet hits someone in the head, great for cartoon or movie scene.", "id": "1004", "duration": 1.7995625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1004&type=wav"} +{"title": "Glass Cookie Jar", "description": "Me adjusting the lid on our glass cookie jar in our kitchen", "author": "fws.gov", "href": "314-Glass-Cookie-Jar.html", "caption": "A lid is being adjusted.", "id": "314", "duration": 1.89915625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=314&type=wav"} +{"title": "Whistling At Girl", "description": "Whistling at a pretty girl. Guy whistles at an attractive lady.", "author": "Daniel Simion", "href": "2203-Whistling-At-Girl.html", "caption": "Someone is whistling.", "id": "2203", "duration": 5.53421875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2203&type=wav"} +{"title": "Ocean Waves", "description": "Here at the outer banks and recorded some ocean waves again. Have a bunch more that ill upload.", "author": "Mike Koenig", "href": "1935-Ocean-Waves.html", "caption": "Ocean waves are recorded.", "id": "1935", "duration": 47.09009375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1935&type=wav"} +{"title": "Eerie Horror Scene", "description": "A very dark and eerie horror scene sound that starts off with a orchestral stab. Cool for haunted house or a scary movie or game.", "author": "BlastwaveFx.com", "href": "577-Eerie-Horror-Scene.html", "caption": "An orchestra stabs before a scary sound.", "id": "577", "duration": 11.48084375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=577&type=wav"} +{"title": "Yoda", "description": "Yoda knows the Force is in you...Vocals highly processed. Nice for sci fi spoof.", "author": "KevanGC", "href": "1772-Yoda.html", "caption": "Someone is speaking in a highly processed vocal.", "id": "1772", "duration": 7.65390625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1772&type=wav"} +{"title": "Slow HeartBeat", "description": "Slow Heart Beat sound effect was requested by Michael for a 3D game he was working on. This sound effect is arund 10 seconds of a beating heart slowed down pretty far.", "author": "Mike Koenig", "href": "1612-Slow-HeartBeat.html", "caption": "A heartbeat is slowed down.", "id": "1612", "duration": 9.95696875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1612&type=wav"} +{"title": "Short Dial Tone", "description": "Short and quick dial tone from phone. We already have one dial tone sound on here this one is just shorter and possibly more suitable for a phone sound effect. Requested by Philip", "author": "Mike Koenig", "href": "1118-Short-Dial-Tone.html", "caption": "A phone is dialing.", "id": "1118", "duration": 1.46034375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1118&type=wav"} +{"title": "Goodbye", "description": "Goodbye wav or mp3 spoken word sound from male.", "author": "Mike Koenig", "href": "681-Goodbye.html", "caption": "A male voice is saying goodbye.", "id": "681", "duration": 1.79321875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=681&type=wav"} +{"title": "Snoring", "description": "Gentle sleeping snore sound. Sound of someone sleeping and snoring a nice simple snore.", "author": "Popup Pixels", "href": "1634-Snoring.html", "caption": "Someone is snoring.", "id": "1634", "duration": 5.6061875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1634&type=wav"} +{"title": "Hard Shoes", "description": "Hard sole shoes walking a hallway of a school or office complex.", "author": "Daniel Simion", "href": "2202-Hard-Shoes.html", "caption": "Someone is walking in hard sole shoes.", "id": "2202", "duration": 9.03978125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2202&type=wav"} +{"title": "UFO Takeoff", "description": "Imaginary alien craft taking off slow then speeding away...electronically engineered oscillator and lfos included. ableton device processing. one shot or loop possible.", "author": "Sonidor", "href": "2064-UFO-Takeoff.html", "caption": "An alien craft is taking off.", "id": "2064", "duration": 3.6338125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2064&type=wav"} +{"title": "Zombie Brain Eater", "description": "Just in case youve not had enough zombie brain eating sound effects here are some more! MMMMMmmmm Brains!!", "author": "Mike Koenig", "href": "1051-Zombie-Brain-Eater.html", "caption": "Zombies are eating brains.", "id": "1051", "duration": 6.7221875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1051&type=wav"} +{"title": "Wind Blowing", "description": "Wind blowing or howling slightly. A great nature sound requested by manoj sharma.", "author": "BlastwaveFx.com", "href": "634-Wind-Blowing.html", "caption": "Wind is blowing.", "id": "634", "duration": 12.70596875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=634&type=wav"} +{"title": "Howler Monkeys", "description": "A troop of howler monkeys screaming and making howling noises near sundown.", "author": "Daniel Simon", "href": "2129-Howler-Monkeys.html", "caption": "Monkeys are screaming and howling.", "id": "2129", "duration": 73.6554375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2129&type=wav"} +{"title": "Door Buzzer", "description": "Housing complex door buzzer like you would here in a large housing complex at the front door. Great sound for city and urban housing.", "author": "Mike Koenig", "href": "1206-Door-Buzzer.html", "caption": "A buzzer is sounding at a housing complex door.", "id": "1206", "duration": 1.97534375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1206&type=wav"} +{"title": "Strange Beeping", "description": "A very strange beeping or electrical sound with pulses and variations.", "author": "Mike Koenig", "href": "555-Strange-Beeping.html", "caption": "A strange beeping or electrical sound is heard.", "id": "555", "duration": 2.1635, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=555&type=wav"} +{"title": "Uzi Shooting", "description": "Automatic machine gun uzi shooting sound effect. Great for a war or combat scene. Sound can be described as light machine gun fire.", "author": "snottyboi", "href": "1371-Uzi-Shooting.html", "caption": "A gun is firing.", "id": "1371", "duration": 2.0491875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1371&type=wav"} +{"title": "Bomb Exploding", "description": "Bomb exploding sound made using a simple breath test with enhanced sound. Thanks to Sound Explorer for another great sound.", "author": "Sound Explorer", "href": "1986-Bomb-Exploding.html", "caption": "A bomb is exploding.", "id": "1986", "duration": 5.55315625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1986&type=wav"} +{"title": "Metal Drop", "description": "A piece of metal or other object being dropped.", "author": "KevanGC", "href": "1615-Metal-Drop.html", "caption": "Something is being dropped.", "id": "1615", "duration": 1.86884375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1615&type=wav"} +{"title": "Footsteps", "description": "The sound of footsteps on wooden floor or pavement. Great for an eerie or suspenseful scene. Requested by Monika", "author": "Caroline Ford", "href": "911-Footsteps.html", "caption": "Footsteps are heard on wooden floor or pavement.", "id": "911", "duration": 6.537375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=911&type=wav"} +{"title": "Urban Traffic", "description": "Some medium traffic driving by. A few cars, suvs, and even some large dump trucks. Pretty good quality audio. Recorded in Manteo NC", "author": "Mike Koenig", "href": "641-Urban-Traffic.html", "caption": "Traffic is passing by.", "id": "641", "duration": 43.01596875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=641&type=wav"} +{"title": "Crying", "description": "Sound of someone crying. This person is morning or sad about something. Poor poor person.", "author": "Mike Koenig", "href": "818-Crying.html", "caption": "Someone is crying.", "id": "818", "duration": 6.9179375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=818&type=wav"} +{"title": "Rustle", "description": "Sound of close or similar rustling.", "author": "Mike Koenig", "href": "895-Rustle.html", "caption": "Rustling is heard.", "id": "895", "duration": 2.66021875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=895&type=wav"} +{"title": "Metronome", "description": "Sound of a metronome clicking and keeping time. This is a wood block metranome sound and is pretty standard. If you want to change the speed or pitch of this please be sure to visit the sound editing link on the bottom right of the page after downloading. This sound was requested by Sam.", "author": "nps.gov", "href": "914-Metronome.html", "caption": "A metronome is clicking.", "id": "914", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=914&type=wav"} +{"title": "Steam Train", "description": "Steam Train or locomotive recorded from doorway of the train as it chugs along.", "author": "Daniel Simion", "href": "2164-Steam-Train.html", "caption": "A train is chugging along.", "id": "2164", "duration": 47.82775, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2164&type=wav"} +{"title": "Scary Chainsaw", "description": "Gas powered chainsaw, cutting down tree in neighborhood. chainsaw next door.", "author": "ezwa", "href": "1539-Scary-Chainsaw.html", "caption": "A chainsaw is cutting a tree.", "id": "1539", "duration": 4.76221875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1539&type=wav"} +{"title": "Door Squeak", "description": "The sound of a door squeak and close. Great for either a squeaking door or closing door.", "author": "Mike Koenig", "href": "873-Door-Squeak.html", "caption": "A door is squeaking and closing.", "id": "873", "duration": 5.67184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=873&type=wav"} +{"title": "Cow Moo", "description": "Sound of a large cow mooing in a pasture.", "author": "Mike Koenig", "href": "1778-Cow-Moo.html", "caption": "A cow is mooing.", "id": "1778", "duration": 3.6381875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1778&type=wav"} +{"title": "Evil Droid", "description": "An evil monster or droid talking about destroying you.", "author": "KevanGC", "href": "1751-Evil-Droid.html", "caption": "A monster or droid is talking about destroying someone.", "id": "1751", "duration": 5.3738125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1751&type=wav"} +{"title": "Tiger Growling", "description": "Tiger Growling and snarling sound effect. Great precursor to a tiger roaring or similar. Could also be a monster sound.", "author": "Mike Koenig", "href": "1485-Tiger-Growling.html", "caption": "A tiger is growling and snarling.", "id": "1485", "duration": 1.4728125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1485&type=wav"} +{"title": "Crackling Fireplace", "description": "Crackling fireplace popping and snapping as wood is burned. Could also be used as a campfire sound. 10MB l minute long.", "author": "Daniel Simion", "href": "2178-Crackling-Fireplace.html", "caption": "Wood is crackling and popping in a fire.", "id": "2178", "duration": 64.83159375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2178&type=wav"} +{"title": "Dog Growling", "description": "A large dog growls a few times. The dog sounds pissed if you ask me.", "author": "Mike Koenig", "href": "523-Dog-Growling.html", "caption": "A dog is growling.", "id": "523", "duration": 3.69725, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=523&type=wav"} +{"title": "Airplane Landing Airport", "description": "Large commercial airplane landing at an airport runway.", "author": "Daniel Simion", "href": "2219-Airplane-Landing-Airport.html", "caption": "An airplane is landing.", "id": "2219", "duration": 14.1424375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2219&type=wav"} +{"title": "Ta Da", "description": "A ta da sound effect was requested Ruth Leacock. The sound you hear when you do something good or win something. Hey mom look at me Ta Da! Like that.", "author": "Mike Koenig", "href": "1003-Ta-Da.html", "caption": "A ta da sound effect for good news or winning.", "id": "1003", "duration": 1.651, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1003&type=wav"} +{"title": "Random Son Talk", "description": "My son talking about a bunch of random stuff. He goes from telling me he pooped, telling me he farted, and mid sentence starts asking me what im eating. Hes as scatterbrained as i am for sure. Really cute.", "author": "Mike Koenig", "href": "1278-Random-Son-Talk.html", "caption": "Someone is talking about random stuff.", "id": "1278", "duration": 25, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1278&type=wav"} +{"title": "Large Fireball", "description": "A very large fireball sound effect. Great for a wizard casting a spell, or a catapult launching a flaming ball over a castle wall.", "author": "Mike Koenig", "href": "1348-Large-Fireball.html", "caption": "A fireball is launching.", "id": "1348", "duration": 1.49978125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1348&type=wav"} +{"title": "Whistling", "description": "Someone Whistling out loud. Maybe they are whistling while they work. Need a whistle sound effect get one free here.", "author": "Mike Koenig", "href": "778-Whistling.html", "caption": "Someone is whistling.", "id": "778", "duration": 3.31196875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=778&type=wav"} +{"title": "Pterodactyl Scream", "description": "Sound of a pterodactyl scream screech. Great dinosaur or raptor sound effect for a scary movie or similar.", "author": "Mike Koenig", "href": "1497-Pterodactyl-Scream.html", "caption": "A pterodactyl is screeching.", "id": "1497", "duration": 2.660875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1497&type=wav"} +{"title": "Spraying Deodorant", "description": "Spraying deodorant sound under arm in bathroom", "author": "Mike Koenig", "href": "144-Spraying-Deodorant.html", "caption": "Someone is spraying deodorant under their arm in a bathroom.", "id": "144", "duration": 1.50853125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=144&type=wav"} +{"title": "Pump Shotgun 2x", "description": "Sound of the Mossburg 500 Pistol grip 20inch (near sawed off) tactical shotgun pumping a round into the chamber ejecting the round and then putting another round in. Its that classic pump shotgun sound that says, hey i mean business. Youve all heard this sound before im sure.", "author": "Mike Koenig", "href": "1406-Pump-Shotgun-2x.html", "caption": "A shotgun is being pumped and loaded.", "id": "1406", "duration": 3.121375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1406&type=wav"} +{"title": "Death", "description": "Scary scream. It sounds like someone get killed. Recorded in russia on pocket pc. Duration 2 seconds", "author": "Roman K", "href": "1570-Death.html", "caption": "Someone is screaming.", "id": "1570", "duration": 2.113375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1570&type=wav"} +{"title": "Dragon Roaring", "description": "Dragon roaring a roar great for a dnd or medieval game or movie scene", "author": "Mike Koenig", "href": "543-Dragon-Roaring.html", "caption": "A dragon is roaring.", "id": "543", "duration": 6.00446875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=543&type=wav"} +{"title": "Splat And Squirt", "description": "Sound of small engine plane shutting down. Its a whining motor or engine sound that slowly stops. Great for an airport, or similar sound effect.", "author": "Mike Koenig", "href": "1089-Splat-And-Squirt.html", "caption": "A small engine plane is shutting down with a whining motor sound.", "id": "1089", "duration": 17.13128125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1089&type=wav"} +{"title": "Male Cough", "description": "Short clean cough sound from a male but could be used as a female if picthed up or if the female was butch", "author": "Mike Koenig", "href": "1864-Male-Cough.html", "caption": "Someone is coughing.", "id": "1864", "duration": 1.56390625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1864&type=wav"} +{"title": "Dogs Howling", "description": "A couple of howling dogs howling and yapping at the moon. These dogs are yappy.", "author": "Daniel Simon", "href": "2149-Dogs-Howling.html", "caption": "Dogs are howling and yapping.", "id": "2149", "duration": 19.606125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2149&type=wav"} +{"title": "City Traffic And Construction", "description": "City traffic and construction sounds from busy intersection in kill Devil Hills North Carolina", "author": "Mike Koenig", "href": "491-City-Traffic-And-Construction.html", "caption": "City traffic and construction sounds are heard.", "id": "491", "duration": 26.42915625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=491&type=wav"} +{"title": "Shooting Star", "description": "Sound of a shooting star or bright idea. A twinkle or a sunbeam. Just some soft chimes with effects added.", "author": "Mike Koenig", "href": "1744-Shooting-Star.html", "caption": "Soft chimes are sounding.", "id": "1744", "duration": 1.14184375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1744&type=wav"} +{"title": "Garbage Bag", "description": "Garbage bag, also called trash bag being taken out and adjusted. Nice clean and crisp plastic ruffling noises can be heard.", "author": "Mike Koenig", "href": "2118-Garbage-Bag.html", "caption": "A bag is being adjusted.", "id": "2118", "duration": 16.425375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2118&type=wav"} +{"title": "Walking Away", "description": "The sound of footsteps leaving or going. Sound of someone walking towards away. Requesteed by Monika", "author": "Mike Koenig", "href": "874-Walking-Away.html", "caption": "Someone is walking away or towards.", "id": "874", "duration": 10.1466875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=874&type=wav"} +{"title": "Cicada", "description": "This is the rare sound of a 7 or 17 year cicada, one of the rarest of the 250 known cicada species. These bugs which i have very fond memories of as a child, can and do stay hidden underground for up to 17 years and then come out again, mate and then bury themselves for another 17 years. Awesome little insects!", "author": "Mike Koenig", "href": "920-Cicada.html", "caption": "A cicada is making noise.", "id": "920", "duration": 28.46190625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=920&type=wav"} +{"title": "Common Fart", "description": "A common everyday fart that you might do when no one else is around.", "author": "Mike Koenig", "href": "2150-Common-Fart.html", "caption": "A fart sound is made.", "id": "2150", "duration": 1.781, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2150&type=wav"} +{"title": "Monster Snarling", "description": "Very scary snarling sound from a monster. Great for nature or horror scenes. Very evil.", "author": "Mike Koenig", "href": "565-Monster-Snarling.html", "caption": "A monster is snarling.", "id": "565", "duration": 3.81909375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=565&type=wav"} +{"title": "Heartbeat", "description": "Awesome heartbeat sound effect. Great for a hosptial or human sound effect.", "author": "Mike Koenig", "href": "1001-Heartbeat.html", "caption": "A heartbeat sound effect, great for hospital or human sound.", "id": "1001", "duration": 30.10959375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1001&type=wav"} +{"title": "Button Click On", "description": "Click button turn on sound", "author": "Mike Koenig", "href": "184-Button-Click-On.html", "caption": "A button is being clicked to turn on something.", "id": "184", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=184&type=wav"} +{"title": "Fishtank Bubbles 2", "description": "Fishtank bubbles bubbling in fishtank. The sound bubbles make when surfacing.", "author": "amanda", "href": "1571-Fishtank-Bubbles-2.html", "caption": "Bubbles are bubbling.", "id": "1571", "duration": 23.56246875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1571&type=wav"} +{"title": "Fire Truck Siren", "description": "A fire truck siren sound effect with bells and horns. Fire truck leaving fire station for an emergency.", "author": "FiremanSam", "href": "1511-Fire-Truck-Siren.html", "caption": "A fire truck siren is sounding.", "id": "1511", "duration": 14.791125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1511&type=wav"} +{"title": "Fire Pager", "description": "This is the tone of my fire department pager when we get a fire call", "author": "jason", "href": "1766-Fire-Pager.html", "caption": "A pager is sounding for a fire call.", "id": "1766", "duration": 2.56534375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1766&type=wav"} +{"title": "Rooster Crowing", "description": "A rooster crowing early and gives a wakeup call at a small farm in the foothills of North Carolina. Great alarm or animal sound. Cock a doodle do!", "author": "Mike Koenig", "href": "1134-Rooster-Crowing.html", "caption": "A rooster is crowing.", "id": "1134", "duration": 2.4785625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1134&type=wav"} +{"title": "Underwater Pool", "description": "Sound effect from someone submerged in a pool pond lake ocean or any other body of water for that matter.", "author": "Mike Koenig", "href": "1660-Underwater-Pool.html", "caption": "Someone is submerged in water.", "id": "1660", "duration": 11.08978125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1660&type=wav"} +{"title": "Labrador Barking Dog", "description": "Large dog, breed labrador retriever, barking for 20 seconds. Large and deep barking troll your dog today!.", "author": "Daniel Simion", "href": "2215-Labrador-Barking-Dog.html", "caption": "A dog is barking.", "id": "2215", "duration": 21.4625625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2215&type=wav"} +{"title": "Normal Shotgun", "description": "Normal shotgun sound effect. Sound of a shotgun being fired 8x (high capacity) in rapid succession. This is not a real recording, but sounds good anyway.", "author": "Soundeffects", "href": "2020-Normal-Shotgun.html", "caption": "A shotgun is firing repeatedly.", "id": "2020", "duration": 4.50721875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2020&type=wav"} +{"title": "Clarks Nutcracker Bird", "description": "Field recording of a clarks nutcracker bird. The Clarks Nutcracker Nucifraga columbiana, is a large passerine bird, in the family Corvidae.", "author": "Caroline Ford", "href": "887-Clarks-Nutcracker-Bird.html", "caption": "Recording of a bird.", "id": "887", "duration": 2.8364375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=887&type=wav"} +{"title": "Aww Sympathy", "description": "The sound of a human feeling sympathetic to another human or animal.", "author": "Mike Koenig", "href": "966-Aww-Sympathy.html", "caption": "Someone is showing sympathy.", "id": "966", "duration": 1.2655, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=966&type=wav"} +{"title": "Metal Gong", "description": "Metal Gong sound from a big metal gong at a shop we stopped at", "author": "Mike Koenig", "href": "128-Metal-Gong.html", "caption": "A big metal gong is making a sound.", "id": "128", "duration": 6.45628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=128&type=wav"} +{"title": "Thunderstorm Thin", "description": "Its a storm with two thunderbolts striking. The low or bass end is very thin so this sound should only be used on something that would be played back on pc or laptop speakers. Thanks to Tim for the sound!", "author": "Tim", "href": "1857-Thunderstorm-Thin.html", "caption": "Thunder is rumbling.", "id": "1857", "duration": 90.4359375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1857&type=wav"} +{"title": "Tornado Siren", "description": "A tornado alert in stereo or air raid siren going off in a town out west, great for war or storms, or similar situations. Even good for a spooky movie.", "author": "Mike Koenig", "href": "1061-Tornado-Siren.html", "caption": "A tornado alert or air raid siren is going off in a town out west, possibly for war or storm situations.", "id": "1061", "duration": 36.91503125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1061&type=wav"} +{"title": "Earthquake Tremors", "description": "Sounds from earthquake tremors shaking dishes and other such things in cabinet", "author": "Mike Koenig", "href": "179-Earthquake-Tremors.html", "caption": "Dishes and other objects are shaking during an earthquake tremor.", "id": "179", "duration": 25, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=179&type=wav"} +{"title": "Halogen Light", "description": "The hum or buzz of a halogen light in a garage. Its turned up loud so you can hear it.", "author": "Mike Koenig", "href": "1085-Halogen-Light.html", "caption": "A halogen light is humming or buzzing loudly in a garage.", "id": "1085", "duration": 4.736875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1085&type=wav"} +{"title": "Please Turn On The Air", "description": "Please turn on the air a sound requested by Rhey to be used for his office.", "author": "Mike Koenig", "href": "657-Please-Turn-On-The-Air.html", "caption": "Air is turning on.", "id": "657", "duration": 3.70025, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=657&type=wav"} +{"title": "Rooster", "description": "Another rooster sound effect for a farm or similar. Sound effect requested by yoli.", "author": "Mike Koenig", "href": "1510-Rooster.html", "caption": "A rooster is crowing.", "id": "1510", "duration": 2.5435, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1510&type=wav"} +{"title": "Horned Owl", "description": "Horned owl or greater horned owl from a field recording at the edge of the woods connected to a pasture.", "author": "Mike Koenig", "href": "1851-Horned-Owl.html", "caption": "An owl is hooting.", "id": "1851", "duration": 2.78471875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1851&type=wav"} +{"title": "Newspaper Ticker", "description": "Sound of a newspaper ticker. Used when a spinning newspaper is shown. Was requested by Alissa Sallee. Thanks Alissa", "author": "Mike Koenig", "href": "1347-Newspaper-Ticker.html", "caption": "A ticker is ticking.", "id": "1347", "duration": 15.55025, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1347&type=wav"} +{"title": "9mm Gunshot", "description": "New recording tools means better recordings. This is a new 9mm gunshot sound effect recorded up close and personal.", "author": "Mike Koenig", "href": "2120-9mm-Gunshot.html", "caption": "A gunshot is being fired.", "id": "2120", "duration": 1.736625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2120&type=wav"} +{"title": "Maniacal Witches Laugh", "description": "A very maniacal Witch Laugh great for a halloween soundtrack, for scary movie, or scifi and fantasy fanatics.", "author": "Mike Koenig", "href": "1129-Maniacal-Witches-Laugh.html", "caption": "Someone is laughing maniacally.", "id": "1129", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1129&type=wav"} +{"title": "Sharpen Knife", "description": "A knife or other tool being sharpened by manually grinding the item against a sharpening stone.", "author": "J Bravo", "href": "2025-Sharpen-Knife.html", "caption": "A tool is being sharpened on a stone.", "id": "2025", "duration": 5.773, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2025&type=wav"} +{"title": "Monster Growl", "description": "Some large ficticious monster growling and sounding really evil. Great for a dungeon, or scary scene or game. Scare the kids at Halloween!", "author": "Mike Koenig", "href": "768-Monster-Growl.html", "caption": "A fictitious monster is growling.", "id": "768", "duration": 3.9781875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=768&type=wav"} +{"title": "Fire Truck Horn", "description": "Fire truck blowing its air horn to alert traffic of its arival.", "author": "Daniel Simion", "href": "2192-Fire-Truck-Horn.html", "caption": "A fire truck is using its horn.", "id": "2192", "duration": 8.45175, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2192&type=wav"} +{"title": "Annoying Alarm Clock", "description": "Basic loud alarm clock sound. Perfect for early morning.", "author": "UncleKornicob", "href": "1787-Annoying-Alarm-Clock.html", "caption": "Loud alarm clock sound effect.", "id": "1787", "duration": 9.8104375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1787&type=wav"} +{"title": "Branch Wood Stress Cracking", "description": "Branch tree or wood plank stress and then snap break sound. Great for a wood stress and breaking sound.", "author": "Mike Koenig", "href": "518-Branch-Wood-Stress-Cracking.html", "caption": "A branch or wood plank is stressing and snapping.", "id": "518", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=518&type=wav"} +{"title": "Cutlery", "description": "The sound of cutlery clanking or whatever sound it is making.", "author": "Mike Koenig", "href": "959-Cutlery.html", "caption": "Cutlery is clanking.", "id": "959", "duration": 2.1545625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=959&type=wav"} +{"title": "Bird Song", "description": "A bird singing a song in the forest", "author": "Mike Koenig", "href": "340-Bird-Song.html", "caption": "A bird is singing.", "id": "340", "duration": 62.56328125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=340&type=wav"} +{"title": "Flushing The Toilet", "description": "Sound of person flushing the toilet. Toilet flush sound effect is public domain so use it however you want. Great bathroom, restroom, or cleaning sounds.", "author": "Grzegorz Adam Hankie", "href": "1246-Flushing-The-Toilet.html", "caption": "Someone is flushing a toilet.", "id": "1246", "duration": 23.60753125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1246&type=wav"} +{"title": "Alligator Crocodile Growl", "description": "Alligator Crocodile or Dragon Low Growl. Very bass vibrato and a bit scary. Great animal nature sound.", "author": "BlastwaveFx.com", "href": "560-Alligator-Crocodile-Growl.html", "caption": "An animal is growling.", "id": "560", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=560&type=wav"} +{"title": "Rain And Thunder Strikes", "description": "Cool sound of rain and thunder strikes. 2 thunder bolts with light rain as a background.", "author": "nps.gov", "href": "901-Rain-And-Thunder-Strikes.html", "caption": "Rain and thunder strikes are heard.", "id": "901", "duration": 30.27884375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=901&type=wav"} +{"title": "Fireworks Finale", "description": "Fireworks 4th of july sound effects requested by Mike. The sounds are in the public domain.", "author": "Mike Koenig", "href": "693-Fireworks-Finale.html", "caption": "Fireworks are exploding.", "id": "693", "duration": 18.5725, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=693&type=wav"} +{"title": "Front Desk Bell", "description": "Front desk bel that you ring to get service. Also known as a service bell or call bell.", "author": "Daniel Simion", "href": "2190-Front-Desk-Bell.html", "caption": "A bell is ringing for service.", "id": "2190", "duration": 4.32025, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2190&type=wav"} +{"title": "Dinosaur", "description": "Great dinosaur sounds effects. 3 dinosaurs roar and eat food over a few seconds.", "author": "mike koenig", "href": "1711-Dinosaur.html", "caption": "Dinosaurs are roaring and eating.", "id": "1711", "duration": 25.6174375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1711&type=wav"} +{"title": "I Love You Baby Talk", "description": "My daughter saying i love you. Cute baby talk voice for something good im sure.", "author": "Mike Koenig", "href": "807-I-Love-You-Baby-Talk.html", "caption": "A baby says \"I love you\".", "id": "807", "duration": 1.33590625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=807&type=wav"} +{"title": "Turkey Call 2", "description": "Another very clean and mastered turkey hen calling. Can be used to call male Tom or Gobbler. Great for hunters.", "author": "JimBob", "href": "1896-Turkey-Call-2.html", "caption": "A turkey hen is calling.", "id": "1896", "duration": 2.67496875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1896&type=wav"} +{"title": "Crushing Can On Head", "description": "Crushing beer can on my head sound, well not really but it sounds like it.", "author": "Mike Koenig", "href": "124-Crushing-Can-On-Head.html", "caption": "Someone is crushing a beer can on their head.", "id": "124", "duration": 5.33878125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=124&type=wav"} +{"title": "Stretching Growing", "description": "Sound of something stretching or growing. Nice growing sound effect. Great for power up, level up, and similar.", "author": "Mike Koenig", "href": "1110-Stretching-Growing.html", "caption": "Something is growing or stretching.", "id": "1110", "duration": 2.3938125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1110&type=wav"} +{"title": "Rigid Dark Pulse", "description": "Rigid dark and vibrating dark pulsing sound with a bit of flange to help it move or breathe.", "author": "lol", "href": "1754-Rigid-Dark-Pulse.html", "caption": "A pulsing sound with flange effect is heard.", "id": "1754", "duration": 5.98240625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1754&type=wav"} +{"title": "Laser Cannon", "description": "Power Up and fire Laser Cannon for sci fi game of video. Nice blaser or laser cannon.", "author": "Mike Koenig", "href": "1771-Laser-Cannon.html", "caption": "A laser cannon is powering up and firing.", "id": "1771", "duration": 1.95384375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1771&type=wav"} +{"title": "Piano Breaking", "description": "The sound effect is often heard on pianos that have been broken by falling. Sounds like everything is falling apart and going wrong.", "author": "Brandondorf", "href": "2086-Piano-Breaking.html", "caption": "A broken piano makes a sound of falling apart.", "id": "2086", "duration": 4.18359375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2086&type=wav"} +{"title": "Bats Vocalizing", "description": "Bats making sound while vocalizing from nearby cave", "author": "MIke Koenig", "href": "238-Bats-Vocalizing.html", "caption": "Bats are vocalizing from a nearby cave.", "id": "238", "duration": 12.337, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=238&type=wav"} +{"title": "Electric Toothbrush", "description": "Me and my little girl brushing her teeth with her new princess electric toothbrush.", "author": "Mike Koenig", "href": "1731-Electric-Toothbrush.html", "caption": "Someone is brushing teeth.", "id": "1731", "duration": 12.67903125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1731&type=wav"} +{"title": "Ole Matador 2", "description": "Bullfighter in spain ole sound effect, great for a bullfight or matador.", "author": "Mike Koenig", "href": "698-Ole-Matador-2.html", "caption": "Someone is cheering at a bullfight.", "id": "698", "duration": 1.6138125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=698&type=wav"} +{"title": "Radio Interruption", "description": "Radio Interruption sound effect where a live broadcast is intterupted by the government or other org in order to broadcast an important weather alert, or child abduction.", "author": "Mike Koenig", "href": "1063-Radio-Interruption.html", "caption": "A radio interruption sound effect is playing, possibly broadcasting an important alert or announcement.", "id": "1063", "duration": 6.46909375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1063&type=wav"} +{"title": "Crystal Glass", "description": "Made sound by rubbing wet finger across the edge of a crystal champagne glass", "author": "Mike Koenig", "href": "125-Crystal-Glass.html", "caption": "Someone is making a sound by rubbing a wet finger on the edge of a crystal glass.", "id": "125", "duration": 7.442, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=125&type=wav"} +{"title": "M1 Garand Gun", "description": "M1 Garand Double Shot gunfire sound effect. M1 Garrand is a 30 caliber rifle, and often called Greatest Battle Implement Ever Devised. It was the first semi-automatic rifle used by the military. Sound effect requested by William Andrews. Thanks William.", "author": "battlestar10", "href": "1638-M1-Garand-Gun.html", "caption": "A rifle is firing.", "id": "1638", "duration": 2.17615625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1638&type=wav"} +{"title": "Biting Apple", "description": "Me taking a bite of a golden delicious apple from the apple tree. Great crunchy biting sound.", "author": "Mike Koenig", "href": "407-Biting-Apple.html", "caption": "Someone is biting an apple.", "id": "407", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=407&type=wav"} +{"title": "Window Shattering", "description": "Shattering window pane. Glass breaking noise", "author": "Mike Koenig", "href": "392-Window-Shattering.html", "caption": "Glass is shattering.", "id": "392", "duration": 4.26084375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=392&type=wav"} +{"title": "Tractor Digging", "description": "Sound of a tractor or backhoe digging and scraping the ground.", "author": "Daniel Simon", "href": "2134-Tractor-Digging.html", "caption": "A tractor or backhoe is digging and scraping the ground.", "id": "2134", "duration": 111.720375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2134&type=wav"} +{"title": "Bottle Rocket", "description": "Large bottle rocket sounds like a jet or missile taking off. Fast ffssssttt sound. This recording actually burned the wind shield on the zoom h4", "author": "Mike Koenig", "href": "709-Bottle-Rocket.html", "caption": "A bottle rocket is launched, making a fast sound.", "id": "709", "duration": 2.27903125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=709&type=wav"} +{"title": "Paparazzi Cameras", "description": "Paparazzi cameras the sound of many cameras going off at once Requested by fiona.", "author": "Mike Koenig", "href": "589-Paparazzi-Cameras.html", "caption": "Cameras are flashing.", "id": "589", "duration": 11.65628125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=589&type=wav"} +{"title": "Coughing", "description": "Coughing twice, i must be coming down with something", "author": "Mike Koenig", "href": "400-Coughing.html", "caption": "Someone is coughing.", "id": "400", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=400&type=wav"} +{"title": "Train Honk Horn Clear", "description": "Train honking its horn one time very short and clear. Great train or locomotive sound effect.", "author": "Mike Koenig", "href": "1696-Train-Honk-Horn-Clear.html", "caption": "A train is honking its horn.", "id": "1696", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1696&type=wav"} +{"title": "Emergency Flashers", "description": "Emergency flashers on a car blinking on and off. could also be used as a turn signal or other blinking sound.", "author": "Mike Koenig", "href": "822-Emergency-Flashers.html", "caption": "Emergency flashers on a car are blinking on and off.", "id": "822", "duration": 7.42775, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=822&type=wav"} +{"title": "Hot Sizzling", "description": "Sizzling hot sound effect. Great sizzle of something burning in heat. Ssssssss. Recroded a hot frying pan and dropped a drop of water in it. The sound of your brain on drugs. Any questions? (If you did not get this reference there used to be a commercial on in the mid 90s that said that)", "author": "Mike Koenig", "href": "1090-Hot-Sizzling.html", "caption": "Something is sizzling and burning in a hot frying pan.", "id": "1090", "duration": 2.851875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1090&type=wav"} +{"title": "Click On", "description": "Cool computer button click sound. Great for an operating system or web page. Great on or off toggle sound.", "author": "Mike Koenig", "href": "1280-Click-On.html", "caption": "A computer button is clicking.", "id": "1280", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1280&type=wav"} +{"title": "Tree Fall Small", "description": "Small tree falling in woods and leaves and branches moving about", "author": "Daniel Simion", "href": "2039-Tree-Fall-Small.html", "caption": "A tree is falling with moving leaves and branches.", "id": "2039", "duration": 6.43, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2039&type=wav"} +{"title": "Baby Talk 30 Sec", "description": "Very cute baby babbling or baby talk sound clip lasts about 30 seconds and the baby says all sorts of cute things.", "author": "stephan", "href": "1576-Baby-Talk-30-Sec.html", "caption": "A baby is babbling.", "id": "1576", "duration": 27.7660625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1576&type=wav"} +{"title": "Countdown", "description": "A countdown from 5. 5 4 3 2 1 Go.", "author": "Me", "href": "2049-Countdown.html", "caption": "A countdown is happening.", "id": "2049", "duration": 7.36009375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2049&type=wav"} +{"title": "Terns Talking At Beach", "description": "Terns a member of the gull family at the beach", "author": "fws.gov", "href": "274-Terns-Talking-At-Beach.html", "caption": "Terns are making sounds.", "id": "274", "duration": 25.873, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=274&type=wav"} +{"title": "Small Crowd Applause", "description": "A small crowd in a theater applauding for a few seconds.", "author": "Yannick Lemieux", "href": "1964-Small-Crowd-Applause.html", "caption": "A crowd is applauding.", "id": "1964", "duration": 7.540875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1964&type=wav"} +{"title": "Fax Machine", "description": "The sound of someone dialing a number on a fax machine and the delay before the actual message sends. It is neither a confirmed nor bad send.", "author": "Mike Koenig", "href": "851-Fax-Machine.html", "caption": "Someone is dialing on a fax machine.", "id": "851", "duration": 12.62596875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=851&type=wav"} +{"title": "Church Bell Chime", "description": "Church bells ring for about 1 minute. Great for wedding, or funeral, or church type video.", "author": "Daniel Simion", "href": "2171-Church-Bell-Chime.html", "caption": "Church bells are ringing.", "id": "2171", "duration": 65.188125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2171&type=wav"} +{"title": "Toke And Exhale", "description": "Toke and exhale sound for those of you who need a smoking effect.", "author": "Jaime Os Rivera", "href": "2077-Toke-And-Exhale.html", "caption": "A smoking effect is created.", "id": "2077", "duration": 2.52915625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2077&type=wav"} +{"title": "Gunfire In Crowd", "description": "A gun firing in a crowd of people. Scary.", "author": "KevanGC", "href": "1608-Gunfire-In-Crowd.html", "caption": "A gun is fired in a crowd.", "id": "1608", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1608&type=wav"} +{"title": "Scream Of Joy", "description": "Woohoo sound of a Female Scream for Joy. Could be used for a sports sound or similar.", "author": "BlastwaveFx.com", "href": "666-Scream-Of-Joy.html", "caption": "A woman is screaming for joy.", "id": "666", "duration": 1.54275, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=666&type=wav"} +{"title": "Bye Bye Son", "description": "My son saying bye bye while on a vacation in the mtns of NC", "author": "Mike Koenig", "href": "1879-Bye-Bye-Son.html", "caption": "Someone is saying \"bye bye\".", "id": "1879", "duration": 1.0681875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1879&type=wav"} +{"title": "Cat Meowing 2", "description": "Large tom cat meowing one long time with some vibrations in it.", "author": "Mr Smith", "href": "1684-Cat-Meowing-2.html", "caption": "A large cat is meowing with vibrations.", "id": "1684", "duration": 1.61053125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1684&type=wav"} +{"title": "747 Jet Crash", "description": "Sound of a 747 jet crashing. Great for airplane scenes with a jet crashing.", "author": "keyWasFull", "href": "1651-747-Jet-Crash.html", "caption": "A jet is crashing.", "id": "1651", "duration": 13.7360625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1651&type=wav"} +{"title": "Waterphone", "description": "The waterphone is responsible for most of those spooky sounds you hear during a suspenseful horror movie scene. Classic horror or Halloween audio at its best. Also called ocean harp, or AquaSonic waterphone.", "author": "Daniel Simion", "href": "2173-Waterphone.html", "caption": "An instrument called a waterphone is making spooky sounds.", "id": "2173", "duration": 76.428375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2173&type=wav"} +{"title": "Grenade Launcher 2", "description": "Another quality grenade launcher sfx. Grenade launches explosion and reload.", "author": "Daniel Simon", "href": "2140-Grenade-Launcher-2.html", "caption": "A grenade launcher is firing and exploding.", "id": "2140", "duration": 3.17321875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2140&type=wav"} +{"title": "Fire Burning", "description": "Fire burning and crackling and burning some more for a total of about 16 seconds. Great sound effect for a fire.", "author": "JaBa", "href": "1902-Fire-Burning.html", "caption": "Fire crackles and burns.", "id": "1902", "duration": 16.15721875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1902&type=wav"} +{"title": "I Want Brains", "description": "Zombies have an unquenchable thirst for brains. Comon you know your not using them, so share with the zombie. Zombie sounds requested by jordangiese.", "author": "Mike Koenig", "href": "1028-I-Want-Brains.html", "caption": "Zombies have a thirst for brains.", "id": "1028", "duration": 3.6411875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1028&type=wav"} +{"title": "Chicks Feeding", "description": "2 chicks not human girls but bird babies feeding", "author": "Mike Koenig", "href": "244-Chicks-Feeding.html", "caption": "Bird chicks are feeding.", "id": "244", "duration": 13.177, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=244&type=wav"} +{"title": "Dig In A Cat Litter Box", "description": "Me pretending to dig in a cat litter box. A great digging or tunneling sound", "author": "fws.gov", "href": "313-Dig-In-A-Cat-Litter-Box.html", "caption": "Someone is pretending to dig in a litter box.", "id": "313", "duration": 3.41334375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=313&type=wav"} +{"title": "Turkey Call", "description": "Very clean and mastered turkey hen calling. Can be used to call male Tom or Gobbler. Great for hunters.", "author": "JimBob", "href": "1889-Turkey-Call.html", "caption": "Clean turkey hen calling for hunters.", "id": "1889", "duration": 5.833125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1889&type=wav"} +{"title": "Machine Sound", "description": "Metallic sound that could be made by a large machine. Very dark and ambient with lots of reverb.", "author": "Marianne Gagnon", "href": "1668-Machine-Sound.html", "caption": "A metallic sound is heard.", "id": "1668", "duration": 3.32046875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1668&type=wav"} +{"title": "416 Barrett Sniper Rifle", "description": "Sound of a .416 Barrett Sniper Rifle being fired 1 time with a bit of reverb added so the gunshot was not truncated. Sounds requested by Trevor Browning.", "author": "Mike Koenig", "href": "1878-416-Barrett-Sniper-Rifle.html", "caption": "A gun is firing.", "id": "1878", "duration": 1.819375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1878&type=wav"} +{"title": "Baby Heartbeat", "description": "A babies hearbeat heard from outside the mother. As heard by a doctor.", "author": "Daniel Simion", "href": "2161-Baby-Heartbeat.html", "caption": "A baby's heartbeat is heard.", "id": "2161", "duration": 8.98721875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2161&type=wav"} +{"title": "Asian Air Raid Siren", "description": "Asian air raid siren in distance", "author": "Mike Koenig", "href": "133-Asian-Air-Raid-Siren.html", "caption": "An air raid siren is sounding in the distance.", "id": "133", "duration": 35.767375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=133&type=wav"} +{"title": "Water Down Gutter 1", "description": "Water running down gutter drain 1. Cool gargling swishing water sound from the front of my house.", "author": "Mike Koenig", "href": "432-Water-Down-Gutter-1.html", "caption": "Water is running down a gutter.", "id": "432", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=432&type=wav"} +{"title": "380 Gunshot", "description": "Newly recorded 380 gunshot being fired from a ruger lcp. Great gunshot sound effect", "author": "Mike Koenig", "href": "2121-380-Gunshot.html", "caption": "A gunshot is being fired.", "id": "2121", "duration": 2.34378125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2121&type=wav"} +{"title": "Bomb Drop", "description": "A nice high-quality sound effect. theres a whistle on the left and then a blast on the right.", "author": " ", "href": "1582-Bomb-Drop.html", "caption": "A whistle and a blast are heard.", "id": "1582", "duration": 17.01984375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1582&type=wav"} +{"title": "Train Sound Indian Railways", "description": "Running train sound of Indian railways. Train horn and then clickety clack sound of train riding over rails.", "author": "Satish Madiwale", "href": "1812-Train-Sound-Indian-Railways.html", "caption": "A train horn is sounding and the train is moving over rails.", "id": "1812", "duration": 26.21496875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1812&type=wav"} +{"title": "Dog Licking", "description": "Dog licking himself down there. yeah gross", "author": "Mike Koenig", "href": "137-Dog-Licking.html", "caption": "A dog is licking itself.", "id": "137", "duration": 5.2900625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=137&type=wav"} +{"title": "Dark Cavern Soundscape", "description": "Dark Cavern dripping and glitches soundscape", "author": "PD Ezwa", "href": "161-Dark-Cavern-Soundscape.html", "caption": "Water is dripping in a dark cavern.", "id": "161", "duration": 6.00090625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=161&type=wav"} +{"title": "Moaning Moan", "description": "Moan or moaning sound effect from a human. Great for a stressed out person.", "author": "Mike Koenig", "href": "848-Moaning-Moan.html", "caption": "Someone is moaning.", "id": "848", "duration": 1.358375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=848&type=wav"} +{"title": "Ducks Landing In Water", "description": "Ducks landing in the water at lake", "author": "MIke Koenig", "href": "234-Ducks-Landing-In-Water.html", "caption": "Ducks are landing in the water at a lake.", "id": "234", "duration": 9.7765, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=234&type=wav"} +{"title": "Cordless Drill 2", "description": "Cordless drill screwing in a screw sound effect. not drilling but screwing sound", "author": "Mike Koenig", "href": "1722-Cordless-Drill-2.html", "caption": "A screw is being screwed.", "id": "1722", "duration": 1.2210625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1722&type=wav"} +{"title": "Demon Zombie Ambiance", "description": "Awesome Demon and Zombie Ambiance sound effects. zombie sounds requested by jordangiese.", "author": "Caroline Ford", "href": "1025-Demon-Zombie-Ambiance.html", "caption": "Demon and zombie ambiance.", "id": "1025", "duration": 9.01034375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1025&type=wav"} +{"title": "Siren Noise", "description": "I made this loopable siren noise and added some extra effects.", "author": "KevanGC", "href": "1577-Siren-Noise.html", "caption": "A siren is blaring with added effects.", "id": "1577", "duration": 8, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1577&type=wav"} +{"title": "Helicopter Leaving", "description": "A helicopter leaving shortly after lift off. Helicopter flies away sound effect.", "author": "Mike Koenig", "href": "1897-Helicopter-Leaving.html", "caption": "Helicopter flying away after lift off.", "id": "1897", "duration": 20, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1897&type=wav"} +{"title": "Glock 18 Full Auto", "description": "This is the awesome sound of a fully automatic glock 9mm. Great for some intense gunfire for a gun fight.", "author": "JKirsch", "href": "1384-Glock-18-Full-Auto.html", "caption": "A fully automatic gun is firing.", "id": "1384", "duration": 2.11303125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1384&type=wav"} +{"title": "Police Whistle", "description": "Traffic cop blowing his police whistle. Or a police officer chasing down bad guy.", "author": "Daniel Simion", "href": "2184-Police-Whistle.html", "caption": "A cop is blowing a whistle.", "id": "2184", "duration": 4.98040625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2184&type=wav"} +{"title": "Dogs Barking", "description": "Dogs barking in a very annoying fashion. About 4 or 5 dogs in total.", "author": "Ca9", "href": "1499-Dogs-Barking.html", "caption": "Dogs are barking.", "id": "1499", "duration": 7.74109375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1499&type=wav"} +{"title": "Puking Or Fighting", "description": "I cant tell if its someone fighting in a Kung Fu battle or puking in a toilet.", "author": "Puke Man", "href": "1665-Puking-Or-Fighting.html", "caption": "Someone is fighting or puking.", "id": "1665", "duration": 3.4503125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1665&type=wav"} +{"title": "Earthquake", "description": "Bass heavy earthquake sound effects from nature. Sound of an earthquake outside. Low rumbling and such.", "author": "Mike Koenig", "href": "1131-Earthquake.html", "caption": "There is an earthquake sound.", "id": "1131", "duration": 9.26125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1131&type=wav"} +{"title": "Motor Bike Fart", "description": "Just like the title says this fart sounds like a motor bike. This guy is just putting along. You can almost taste this one. Hehehe", "author": "Mike Koenig", "href": "643-Motor-Bike-Fart.html", "caption": "Someone is farting like a motorbike.", "id": "643", "duration": 8.4003125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=643&type=wav"} +{"title": "Thunder 02", "description": "I made this sound completely. I left my mic on for god knows how long and edited a short little lightning strike. Enjoy. Big thanks to Mark from SoundBible.com for another great sound effect.", "author": "Mark DiAngelo", "href": "1905-Thunder-02.html", "caption": "Lightning strike sound effect edited from a recording.", "id": "1905", "duration": 4.9869375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1905&type=wav"} +{"title": "Morse Code", "description": "Great public domain morse code sound effect for your downloading pleasure! Plus this sound is public domain. I turned this into stereo and optimized it.", "author": "Mike Koenig", "href": "1170-Morse-Code.html", "caption": "A morse code sound is playing.", "id": "1170", "duration": 11.23265625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1170&type=wav"} +{"title": "Thunder Strike 1", "description": "1 of 3 thunder or lightning strikes that were recorded very clean and crisp during a very strong summer storm.", "author": "Mike Koenig", "href": "2015-Thunder-Strike-1.html", "caption": "A thunder strike is happening during a storm.", "id": "2015", "duration": 21.362375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2015&type=wav"} +{"title": "Dentist Drill", "description": "Dentist Drill sound effect. This horrid sound has been used in many a horror movie, or just a dentist scene.", "author": "Mike Koenig", "href": "1068-Dentist-Drill.html", "caption": "A dentist drill is making a horrid sound.", "id": "1068", "duration": 1.7884375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1068&type=wav"} +{"title": "Flapping Wings", "description": "Flapping Wings 2 or fluttering sound effect. Fairy, bird or dragon wings. Requested by Tracey", "author": "Mike Koenig", "href": "627-Flapping-Wings.html", "caption": "Flapping sound of wings.", "id": "627", "duration": 5.71209375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=627&type=wav"} +{"title": "Times Up 2", "description": "Cute time up kids voice 2 also requested by Amy. Good for some cute kids game or activity.", "author": "Mike Koenig", "href": "787-Times-Up-2.html", "caption": "Children are talking.", "id": "787", "duration": 1.33590625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=787&type=wav"} +{"title": "Large Industrial Robot", "description": "Sound of a large industrial robot moving. Sounds like a robot from a manufacturing facility.", "author": "Mike Koenig", "href": "1366-Large-Industrial-Robot.html", "caption": "A robot is moving.", "id": "1366", "duration": 3.63090625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1366&type=wav"} +{"title": "Kettle", "description": "Sound of a kettle percolating. Nice kitchen or cafe sound effects.", "author": "Mike Koenig", "href": "872-Kettle.html", "caption": "A kettle is percolating.", "id": "872", "duration": 5.05034375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=872&type=wav"} +{"title": "600 Nitro Express", "description": "Gunshot from worlds most powerful handgun that is really a hand cannon. The Nitro 600 Express is frekin huge. Look it up online. Its a custom build and not a production model but on hell of a gun.", "author": "gunna76", "href": "1593-600-Nitro-Express.html", "caption": "A gun is firing.", "id": "1593", "duration": 1.20165625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1593&type=wav"} +{"title": "Nitrous Oxide", "description": "Nitrous oxide sound effect requested by cristi. Could be Nitrus Oxide from a car or similar.", "author": "Mike Koenig", "href": "1530-Nitrous-Oxide.html", "caption": "Nitrous oxide is being released.", "id": "1530", "duration": 2.94, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1530&type=wav"} +{"title": "Motorcycle Gang", "description": "Motorcycle gang driving by a parking lot.", "author": "Mike Koenig", "href": "515-Motorcycle-Gang.html", "caption": "A motorcycle gang is driving by.", "id": "515", "duration": 21.96465625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=515&type=wav"} +{"title": "Robot Leg Moving", "description": "Robot arm and leg movement sound effects. Small fast robot movements. Robot walking or grabbing something.", "author": "Mike Koenig", "href": "1364-Robot-Leg-Moving.html", "caption": "Small robot parts are moving.", "id": "1364", "duration": 1.9049375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1364&type=wav"} +{"title": "Umpire Saying Youre Out", "description": "Umpire Saying Youre Out a great baseball sports sound requested by Laura Hannan. Thanks Laura.", "author": "Mike Koenig", "href": "506-Umpire-Saying-Youre-Out.html", "caption": "An umpire is saying \"You're out.\".", "id": "506", "duration": 1.588625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=506&type=wav"} +{"title": "Blood Squirts", "description": "Blood squirting sound effect. Another great gory sound effect.", "author": "Mike Koenig", "href": "949-Blood-Squirts.html", "caption": "Blood is squirting.", "id": "949", "duration": 6.3195625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=949&type=wav"} +{"title": "Knife Scrape Horror", "description": "Great horror sound of a knife scraping with some effects added to it. Scary", "author": "Mike Koenig", "href": "405-Knife-Scrape-Horror.html", "caption": "A knife is scraping with added effects.", "id": "405", "duration": 15, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=405&type=wav"} +{"title": "Dog Toy Squeaks", "description": "Dog Toy Squeaks from my dogs bone", "author": "Mike Koenig", "href": "186-Dog-Toy-Squeaks.html", "caption": "A dog toy is squeaking.", "id": "186", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=186&type=wav"} +{"title": "Cartoon Computer", "description": "Cartoon or silly computer or computing sound. Blippy bloopy glitchy all mixed together.", "author": "Daniel Simon", "href": "2135-Cartoon-Computer.html", "caption": "A computer is making cartoon or silly sounds.", "id": "2135", "duration": 15.14240625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2135&type=wav"} +{"title": "Scary And Eerie", "description": "Robotic like sound created in Adobe Soundbooth. Very scary great for halloween or horror flick. The MP3 version is the smaller so it can load on the page for preview. The WAV version is the full version and is 1 minute of quality audio.", "author": "Mark DiAngelo", "href": "1801-Scary-And-Eerie.html", "caption": "A robotic sound is heard.", "id": "1801", "duration": 55.87990625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1801&type=wav"} +{"title": "Cough 3x", "description": "3 short coughing sounds from a male but could be used as a female if picthed up or if the female was butch", "author": "Mike Koenig", "href": "1863-Cough-3x.html", "caption": "Someone is coughing.", "id": "1863", "duration": 1.81446875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1863&type=wav"} +{"title": "Gun Fire", "description": "A single gunshot sound effect with a bit of the gun sound reverberating through the surroundings.", "author": "GoodSoundForYou", "href": "1998-Gun-Fire.html", "caption": "A gun is firing.", "id": "1998", "duration": 3.7141875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1998&type=wav"} +{"title": "Creepy Laugh", "description": "An Evil laugh created by mixing different pitches together and adding a echo. Thanks to Adam Webb.", "author": "Adam Webb", "href": "2052-Creepy-Laugh.html", "caption": "Someone is evilly laughing.", "id": "2052", "duration": 8.96290625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2052&type=wav"} +{"title": "Totally Valley Girl", "description": "Some rich valley girl saying totally. A very valley girl thing to say. I feel sorry for whoever she marries.", "author": "Mike Koenig", "href": "676-Totally-Valley-Girl.html", "caption": "Someone is saying \"totally.\".", "id": "676", "duration": 1.07975, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=676&type=wav"} +{"title": "Peacock", "description": "Sound of a peacock recorded by Caroline Ford. Great wild, nature, or zoo sound effect.", "author": "Caroline Ford", "href": "1430-Peacock.html", "caption": "A peacock is making noise.", "id": "1430", "duration": 2.768625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1430&type=wav"} +{"title": "Dog Panting Fast", "description": "A dog panting and breathing very fast and hard. Dog having a hard time breathing. (Canis lupus familiaris) .", "author": "Daniel Simon", "href": "2147-Dog-Panting-Fast.html", "caption": "A dog is breathing heavily.", "id": "2147", "duration": 14.3935, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2147&type=wav"} +{"title": "Strange Mechanical Sound", "description": "Strange mechanical sound could suit a weird machine", "author": "Marianne Gagnon", "href": "1675-Strange-Mechanical-Sound.html", "caption": "A strange mechanical sound is heard.", "id": "1675", "duration": 1.6138125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1675&type=wav"} +{"title": "Dishwasher", "description": "Dishwasher sound effect from a kitchen or restaurant dishwasher.", "author": "stephan", "href": "1667-Dishwasher.html", "caption": "A dishwasher is running.", "id": "1667", "duration": 12.66940625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1667&type=wav"} +{"title": "Appear", "description": "A nice clean computer noise kind of like somethings appearing.", "author": "KP", "href": "1686-Appear.html", "caption": "A computer noise is heard.", "id": "1686", "duration": 6.79396875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1686&type=wav"} +{"title": "That Mine", "description": "My son saying that mine. Really cute bit of sound for me to look back on in the future.", "author": "Mike Koenig", "href": "1307-That-Mine.html", "caption": "Someone's child is saying \"that's mine.\".", "id": "1307", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1307&type=wav"} +{"title": "Screaming Hawk 2", "description": "Perfect screaming hawk loud sound effect 2. Great nature sound effect.", "author": "PsychoBird", "href": "1505-Screaming-Hawk-2.html", "caption": "A hawk is screaming.", "id": "1505", "duration": 4.035875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1505&type=wav"} +{"title": "Buzz", "description": "Great clean buzz sound generated by tone repetition.", "author": "Mike Koenig", "href": "1204-Buzz.html", "caption": "A clean buzz sound is being generated.", "id": "1204", "duration": 2.06621875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1204&type=wav"} +{"title": "Breathing Vent", "description": "Breathing Vent from Hospital", "author": "Mike Koenig", "href": "49-Breathing-Vent.html", "caption": "A breathing vent is operating.", "id": "49", "duration": 6.73671875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=49&type=wav"} +{"title": "Phone Vibrating", "description": "Phone Vibrating sound effect. Origainally meant to be a red alert but sounded so good I had to keep it", "author": "Sound Explorer", "href": "1994-Phone-Vibrating.html", "caption": "A phone is vibrating.", "id": "1994", "duration": 7.8548125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1994&type=wav"} +{"title": "Whimper", "description": "Whimpering and sniveling pour excuse for a human. Great sound effect.", "author": "Mike Koenig", "href": "800-Whimper.html", "caption": "Someone is whimpering and sniveling.", "id": "800", "duration": 4.26234375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=800&type=wav"} +{"title": "What You Eatin Daddy", "description": "My son asking what you eatin 2x. Any time im chewing on something, even a mint, he wants to know what im eating, and then he wants it. Its just a funny sound clip.", "author": "Mike Koenig", "href": "1313-What-You-Eatin-Daddy.html", "caption": "Someone is asking what another person is eating.", "id": "1313", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1313&type=wav"} +{"title": "Spooky Water Drops", "description": "Frekin spooky water drops in some abandoned cathedral scary as hell", "author": "Mike Koenig", "href": "380-Spooky-Water-Drops.html", "caption": "Water is dripping in an abandoned cathedral.", "id": "380", "duration": 6, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=380&type=wav"} +{"title": "Traffic Jam 3", "description": "A traffic jam with horns honking and cars driving. This is part 3 of 4, the sound had to be chopped up smaller in order for the page to load and render quickly.", "author": "Yo Mama", "href": "1629-Traffic-Jam-3.html", "caption": "Cars are honking in a traffic jam.", "id": "1629", "duration": 15.77171875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1629&type=wav"} +{"title": "Sharpening Knife", "description": "Knife sharpener from our kitchen sharpening a knife slowly. Nice metal scraping sounds", "author": "Mike Koenig", "href": "406-Sharpening-Knife.html", "caption": "A knife is being sharpened.", "id": "406", "duration": 30, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=406&type=wav"} +{"title": "Bubbles", "description": "Really cool bubbles or bubbling sound effect. Great for nature, fish tank, underwater, or scuba diving sounds. This sound was originally from the public domain but i tweaked it lengthened it, and converted it into stereo sound.", "author": "Mike Koenig", "href": "1137-Bubbles.html", "caption": "Bubbles are bubbling.", "id": "1137", "duration": 3.946, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1137&type=wav"} +{"title": "Real Heart Beat", "description": "Very real and deep sounding heartbeat sound. Took a beating heart sound and made pitched it down to make it sound more movie like", "author": "Mike Koenig", "href": "379-Real-Heart-Beat.html", "caption": "A deep heartbeat sound is playing.", "id": "379", "duration": 12.14309375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=379&type=wav"} +{"title": "UMP45 Heckler Koch", "description": "Sound of an ump45 made by Heckler Koch being fired several times with 3 round burst and a finale. Sound requested by Tom", "author": "Gunner", "href": "1877-UMP45-Heckler-Koch.html", "caption": "A gun is firing.", "id": "1877", "duration": 4.945625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1877&type=wav"} +{"title": "Cargo Plane Cabin Ambiance", "description": "Great cargo plane cabin ambiance sound effect. You can hear the planes engine drone in the background. Great for any aviation bit.", "author": "Mike Koenig", "href": "1305-Cargo-Plane-Cabin-Ambiance.html", "caption": "A cargo plane's engine is droning in the background.", "id": "1305", "duration": 12.346, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1305&type=wav"} +{"title": "Crickets At Night", "description": "A nice little recording of crickets at night recorded in my backyard with my handy dandy Zoom H4", "author": "Mike Koenig", "href": "365-Crickets-At-Night.html", "caption": "Crickets are chirping.", "id": "365", "duration": 15.6083125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=365&type=wav"} +{"title": "Goofy Laugh", "description": "A spontaneous goofy laugh in response to my sons question about what im eating.", "author": "Mike Koenig", "href": "1279-Goofy-Laugh.html", "caption": "Someone is spontaneously laughing.", "id": "1279", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1279&type=wav"} +{"title": "Crow Call 2", "description": "This is the sound of a crow calling just 1x very short. Can be opened with a sound editor and doubled.", "author": "JimBob", "href": "1929-Crow-Call-2.html", "caption": "A crow is calling.", "id": "1929", "duration": 6.027625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1929&type=wav"} +{"title": "Wind", "description": "Wind blowing 2 or howling slightly. A great nature sound requested by manoj sharma.", "author": "Mike Koenig", "href": "635-Wind.html", "caption": "Wind is blowing.", "id": "635", "duration": 19.24734375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=635&type=wav"} +{"title": "Computer Sci Fi", "description": "Computer processing data a good Sci Fi sound effect. Sound like a large cartoonish or sci fi machine.", "author": "BlastwaveFx.com", "href": "561-Computer-Sci-Fi.html", "caption": "A computer is processing data.", "id": "561", "duration": 3.82634375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=561&type=wav"} +{"title": "Robot Machine", "description": "Industrial robot moves material and then pounds the heck out of it. Great for am industrial or manufacturing setting.", "author": "Mike Koenig", "href": "1193-Robot-Machine.html", "caption": "Industrial robot moving and pounding material.", "id": "1193", "duration": 8.14146875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1193&type=wav"} +{"title": "Atchisson Assault Shotgun", "description": "AA 12 also known as Atchisson Assault Shotgun sound effect. 8 shotgun shells fired in fairly rapid succession.", "author": "Soundeffects", "href": "2021-Atchisson-Assault-Shotgun.html", "caption": "A shotgun is firing.", "id": "2021", "duration": 7.40678125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2021&type=wav"} +{"title": "Crowd Applause", "description": "Modification of original public domain Auditorium Appluse sound clip to create a great large crowd applause sound effect.", "author": "Thore", "href": "1995-Crowd-Applause.html", "caption": "A large crowd is applauding.", "id": "1995", "duration": 10.89134375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1995&type=wav"} +{"title": "Whistling Person", "description": "Someone Whistling out loud. Maybe they are whistling while they work. Need a whistle sound effect get one free here.", "author": "Mike Koenig", "href": "793-Whistling-Person.html", "caption": "Someone is whistling.", "id": "793", "duration": 5.38553125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=793&type=wav"} +{"title": "Real Messy Fart", "description": "This fart is so messy the person farting needed to change his underwear. Yeah gross.", "author": "Mike Koenig", "href": "399-Real-Messy-Fart.html", "caption": "Someone farted messily.", "id": "399", "duration": 10, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=399&type=wav"} +{"title": "IMac Startup Chime", "description": "This is the startup chime from an iMac. It has been highly modified in order to include the work within the Public Domain.", "author": "Carlo", "href": "1821-IMac-Startup-Chime.html", "caption": "An iMac is starting up with a modified chime.", "id": "1821", "duration": 2.1881875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1821&type=wav"} +{"title": "Neighborhood Dogs Barking", "description": "A bunch of the neighborhood dogs barking loud and annoyingly. Great dog sound effects.", "author": "Ca9", "href": "1514-Neighborhood-Dogs-Barking.html", "caption": "Neighborhood dogs are barking.", "id": "1514", "duration": 6.35953125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1514&type=wav"} +{"title": "DTMF Tones", "description": "Some DTMF tones generated in audacity. It sounds like a phone dialing. Great phone, modem, or fax sound effects", "author": "KevanGC", "href": "1573-DTMF-Tones.html", "caption": "DTMF tones are sounding.", "id": "1573", "duration": 4.0000625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1573&type=wav"} +{"title": "Bear Growl And Roar 2", "description": "Bear growling and roaring to protect its cubs #2", "author": "Mike Koenig", "href": "242-Bear-Growl-And-Roar-2.html", "caption": "A bear is growling and roaring to protect its cubs.", "id": "242", "duration": 20.785, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=242&type=wav"} +{"title": "Farm", "description": "Sound of an actual farm with animals mostly sheep, goats, and other such animals. Old mcdonald had one of these.", "author": "stephan", "href": "1662-Farm.html", "caption": "There is the sound of a farm with various animals.", "id": "1662", "duration": 16.6615625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1662&type=wav"} +{"title": "Shell Falling", "description": "Sound of a brass casing or or shell falling to the ground and bouncing slightly.", "author": "Marcel", "href": "2072-Shell-Falling.html", "caption": "A brass casing falls to the ground and bounces.", "id": "2072", "duration": 1.49778125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2072&type=wav"} +{"title": "Dinosaur Roar", "description": "Sound of a large meat eating dinosaur roaring very loud and clear. About a second long.", "author": "Mike Koenig", "href": "1165-Dinosaur-Roar.html", "caption": "A large meat-eating dinosaur is roaring.", "id": "1165", "duration": 1.73134375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1165&type=wav"} +{"title": "Japanese Temple Bell Small", "description": "Japanese Temple Bell Small great for Japanese, Korean, Chinese, or other Asian sound effects.. even for Kung Fu", "author": "Mike Koenig", "href": "1496-Japanese-Temple-Bell-Small.html", "caption": "A temple bell is ringing.", "id": "1496", "duration": 3.89321875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1496&type=wav"} +{"title": "Elephant Trumpeting", "description": "Great Elephant trumpeting or blasting sound effect. Great for a zoo, circus, or African savannah scene. This is Tarzans friend.", "author": "Mike Koenig", "href": "1136-Elephant-Trumpeting.html", "caption": "An elephant is trumpeting.", "id": "1136", "duration": 1.57615625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1136&type=wav"} +{"title": "Chainsaw", "description": "Some guy in my neighborhood was chopping up some trees from a recent storm so i figured i would record it.", "author": "Mike Koenig", "href": "625-Chainsaw.html", "caption": "Someone is chopping trees.", "id": "625", "duration": 11.73653125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=625&type=wav"} +{"title": "Heavy Rain Wind", "description": "Super heavy rainstorm and wind pouring down.", "author": "Daniel Simion", "href": "2217-Heavy-Rain-Wind.html", "caption": "It is raining heavily and windy.", "id": "2217", "duration": 86.42671875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2217&type=wav"} +{"title": "Gun Silencer", "description": "The sound of a gun silencer being fired at someone. Great for a special ops or james bond type scenario.", "author": "Mike Koenig", "href": "930-Gun-Silencer.html", "caption": "A gun is firing with a silencer.", "id": "930", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=930&type=wav"} +{"title": "Rockslide Small", "description": "Small rock-slide effect made by crumpling paper. Thanks to Sound Explorer for another great sound.", "author": "Sound Explorer", "href": "1987-Rockslide-Small.html", "caption": "Paper is being crumpled to create a rock-slide sound.", "id": "1987", "duration": 2.82125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1987&type=wav"} +{"title": "Cartoon Phone Ring", "description": "Old school phone ringing used in cartoons and animations regularly.", "author": "Daniel Simion", "href": "2189-Cartoon-Phone-Ring.html", "caption": "A phone is ringing.", "id": "2189", "duration": 5.963875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2189&type=wav"} +{"title": "50 Caliber Machine Gun", "description": "50 caliber machine gun fires 8 rounds a shooting range. Great for a battle scene", "author": "Aldor", "href": "373-50-Caliber-Machine-Gun.html", "caption": "A machine gun is firing at a shooting range.", "id": "373", "duration": 1.187125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=373&type=wav"} +{"title": "Red Stag Roar", "description": "Red Stag bellowing in mating status. Great for use in a hunting app. Could be used to get other stags attention.", "author": "Juan Carlos", "href": "2073-Red-Stag-Roar.html", "caption": "An animal is bellowing.", "id": "2073", "duration": 11.038125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2073&type=wav"} +{"title": "River Noise", "description": "Noise of a river or brook. Great water sound effect recorded by Caroline Ford", "author": "Caroline Ford", "href": "1429-River-Noise.html", "caption": "A river or brook is making noise.", "id": "1429", "duration": 27.63759375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1429&type=wav"} +{"title": "Free Walla Track", "description": "Short and Free Walla Track filled with people and kids speaking", "author": "Mike Koenig", "href": "517-Free-Walla-Track.html", "caption": "People and kids are speaking.", "id": "517", "duration": 13.87340625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=517&type=wav"} +{"title": "Electric Windows Roll Up", "description": "Electric windows on a honda van rolling up. Sound recorded from inside the van for best audio.", "author": "Mike Koenig", "href": "806-Electric-Windows-Roll-Up.html", "caption": "Electric windows are rolling up.", "id": "806", "duration": 3.32046875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=806&type=wav"} +{"title": "Candy Bar Wrapper", "description": "Candy Bar wrapper plastic sound of crinkling in hand", "author": "Stephan", "href": "95-Candy-Bar-Wrapper.html", "caption": "A candy bar wrapper is crinkling.", "id": "95", "duration": 9.72075, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=95&type=wav"} +{"title": "Pouring Bowl Cereal", "description": "Pouring bowl cereal for breakfast sound", "author": "Mike Koenig", "href": "342-Pouring-Bowl-Cereal.html", "caption": "Cereal is being poured.", "id": "342", "duration": 5.11615625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=342&type=wav"} +{"title": "Submarine Creaking", "description": "Sounds from inside a submarine. Sound of a submarine or metal hull ship below deck creaking and stressing in the water.", "author": "stephan", "href": "1625-Submarine-Creaking.html", "caption": "A ship is creaking in the water.", "id": "1625", "duration": 9.49175, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1625&type=wav"} +{"title": "Rooster Crow", "description": "Awesome sound of a rooster crowing early in the morning. Great farming or alarm clock sound effects.", "author": "Mike Koenig", "href": "1218-Rooster-Crow.html", "caption": "A rooster is crowing.", "id": "1218", "duration": 1.87896875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1218&type=wav"} +{"title": "Typewriter", "description": "Great typing or typewritter sounds for a news or office scene in a movie, game, or powerpoint presentation.", "author": "Mike Koenig", "href": "827-Typewriter.html", "caption": "There are typing or typewriter sounds.", "id": "827", "duration": 7.47865625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=827&type=wav"} +{"title": "Dog Chain", "description": "Dog chain rattle sound effect. Its great for chain mail, chains, or just clanking metal sound.", "author": "Mike Koenig", "href": "1078-Dog-Chain.html", "caption": "A dog chain is rattling, creating a clanking metal sound.", "id": "1078", "duration": 5.3625625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1078&type=wav"} +{"title": "Merlin", "description": "Call of a merlin in flight. A merlin is a large hawk that is also known as a pigeon hawk.", "author": "Mark Mattingly", "href": "1965-Merlin.html", "caption": "A large hawk is calling in flight.", "id": "1965", "duration": 2.71884375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1965&type=wav"} +{"title": "Thousands Of Wood Storks", "description": "Thousands of wood stork and their chicks during mating season roosting and talking.", "author": "fws.gov", "href": "279-Thousands-Of-Wood-Storks.html", "caption": "Wood storks and their chicks are roosting.", "id": "279", "duration": 30.457, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=279&type=wav"} +{"title": "Fireworks", "description": "Fireworks 4th of july sound effects requested by Mike. The sounds are in the public domain.", "author": "Mike Koenig", "href": "692-Fireworks.html", "caption": "Fireworks are exploding.", "id": "692", "duration": 6.41390625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=692&type=wav"} +{"title": "River", "description": "Great sound of a river flowing. Nice stream, brook, or creek running next to a meadow.", "author": "Mike Koenig", "href": "1144-River.html", "caption": "A river is flowing beside a meadow.", "id": "1144", "duration": 6.98240625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1144&type=wav"} +{"title": "Playing Pool", "description": "Someone playing pool hitting ball with cue and sinking one in the pocket.", "author": "Pool Shot", "href": "2035-Playing-Pool.html", "caption": "Someone is playing pool and sinking a ball.", "id": "2035", "duration": 1.16353125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2035&type=wav"} +{"title": "Electric Razor", "description": "I recorded a sound which sounds a lot like an electric razor. I added bass to give it some juice. Thanks to Mark DiAngelo for this one.", "author": "Mark DiAngelo", "href": "1973-Electric-Razor.html", "caption": "An electric razor is buzzing.", "id": "1973", "duration": 20.5226875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1973&type=wav"} +{"title": "Smoke Alarm", "description": "I recorded a smoke alarm at the house we have serveral this is just from a generic smoke alarm used in a house. Could be used for fire settings as well. Sound wass requested by Kaye Barrett. Thanks Kaye", "author": "Mike Koenig", "href": "1249-Smoke-Alarm.html", "caption": "A smoke alarm is beeping.", "id": "1249", "duration": 5.80984375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1249&type=wav"} +{"title": "Annoying Alien Buzzer", "description": "Its a very annoying high-pitched wobbly siren noise. It might give you a splitting headache if you listed to it to long. lol.", "author": "Kevan", "href": "1811-Annoying-Alien-Buzzer.html", "caption": "An annoying high-pitched wobbly siren is making a noise.", "id": "1811", "duration": 35.78775, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1811&type=wav"} +{"title": "Double Barrel Shotgun Cocking", "description": "The sound of a double barrel shotgun cocking both barrels. Requested by joeballs1025.", "author": "Mike Koenig", "href": "451-Double-Barrel-Shotgun-Cocking.html", "caption": "A shotgun is cocking.", "id": "451", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=451&type=wav"} +{"title": "Zen Temple Bell", "description": "Nice zen buddhist temple bell from the mountains. Very good sound.", "author": "Mike Koenig", "href": "1477-Zen-Temple-Bell.html", "caption": "A temple bell is ringing.", "id": "1477", "duration": 5.81190625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1477&type=wav"} +{"title": "Woah Male", "description": "A normal guy surprised by some random thing. Thanks to Sound Explorer for another great sound.", "author": "Sound Explorer", "href": "1984-Woah-Male.html", "caption": "Someone is surprised.", "id": "1984", "duration": 3.081, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1984&type=wav"} +{"title": "Medium Rainstorm", "description": "An average or medium size rainstorm or lightning storm. Very calming and relaxing really.", "author": "Mike Koenig", "href": "1829-Medium-Rainstorm.html", "caption": "Rain or lightning is calming and relaxing.", "id": "1829", "duration": 37.47703125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1829&type=wav"} +{"title": "Barred Owl Call", "description": "Great outdoor owl call. This barred owl call is a decent field recording of the barred or hoot owl. Names include eight hooter, rain owl, wood owl, and striped owl, but is probably known best as the hoot owl.", "author": "snottyboy", "href": "1342-Barred-Owl-Call.html", "caption": "An owl is hooting.", "id": "1342", "duration": 8.41265625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1342&type=wav"} +{"title": "Sad Trombone", "description": "This is the Sad Trombone sound effect great for telling someone they screwed up or have just messed something up big. Bookmark and play for your pals..in good humor of course.", "author": "Joe Lamb", "href": "1830-Sad-Trombone.html", "caption": "A \"Sad Trombone\" sound effect is played.", "id": "1830", "duration": 4.15096875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1830&type=wav"} +{"title": "Kids Laughing", "description": "2 Kids Laughing a quick but cute sound effect for those needing a canned laughter sound.", "author": "Mike Koenig", "href": "587-Kids-Laughing.html", "caption": "Kids are laughing.", "id": "587", "duration": 2.93665625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=587&type=wav"} +{"title": "Electric Table Saw", "description": "Construction or woodworking sound of an electric table saw cutting a piece of plywood.", "author": "ezwa", "href": "1583-Electric-Table-Saw.html", "caption": "An electric table saw is cutting through plywood.", "id": "1583", "duration": 7.5645, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1583&type=wav"} +{"title": "Demons Screaming In Hell", "description": "Demons Screaming in Hell sound chorus", "author": "Mike Koenig", "href": "162-Demons-Screaming-In-Hell.html", "caption": "Demons are screaming in hell.", "id": "162", "duration": 16, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=162&type=wav"} +{"title": "Crickets", "description": "Trying to record other things but the crickets wont stop chirping so i tweaked the file and now we have some cricket sounds.", "author": "Mike Koenig", "href": "1064-Crickets.html", "caption": "Crickets are chirping in the background, possibly outside.", "id": "1064", "duration": 7.1429375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1064&type=wav"} +{"title": "Backing Up", "description": "Sound of a Coca Cola truck backing up with warning beep and diesel engine running. Also has air break at end of sound", "author": "Mike Koenig", "href": "675-Backing-Up.html", "caption": "A truck is backing up with a warning beep and diesel engine running.", "id": "675", "duration": 31.71096875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=675&type=wav"} +{"title": "Dry Cough", "description": "Dry cough sound effect. This one is probably a males cough. I was sick. Great for sickness, plague, pneumonia, or any other similar sound effect need.", "author": "Mike Koenig", "href": "1275-Dry-Cough.html", "caption": "A male is coughing.", "id": "1275", "duration": 5, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1275&type=wav"} +{"title": "Musket Fire", "description": "The sound of Musket Fire at a civil war reenactment. Great for civil war, or wars in that time period.", "author": "Caroline Ford", "href": "913-Musket-Fire.html", "caption": "Guns are firing.", "id": "913", "duration": 5.72084375, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=913&type=wav"} +{"title": "Huge Crowd", "description": "Very large crowd at a stadium with thousands of people screaming.", "author": "Mike Koenig", "href": "644-Huge-Crowd.html", "caption": "A crowd is screaming.", "id": "644", "duration": 6.86225, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=644&type=wav"} +{"title": "Making Espresso", "description": "An espresso machine foaming and bubbling as it makes espresso. Makes me want to go to the local coffee house.", "author": "Mike Koenig", "href": "548-Making-Espresso.html", "caption": "An espresso machine is foaming and bubbling.", "id": "548", "duration": 4.4970625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=548&type=wav"} +{"title": "Peacock Noise", "description": "This peacock noise recorded by Caroline Ford. Great wild, nature, or zoo sound effect.", "author": "Caroline Ford", "href": "1433-Peacock-Noise.html", "caption": "A peacock is making noise.", "id": "1433", "duration": 2.567, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=1433&type=wav"} +{"title": "Wolf Howling Yipping", "description": "Several wolf or coyote howling and yipping sound effects. Was a request for cartoon wolf sound..", "author": "Daniel Simon", "href": "2132-Wolf-Howling-Yipping.html", "caption": "Wolves or coyotes are howling and yipping.", "id": "2132", "duration": 8.99221875, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=2132&type=wav"} +{"title": "Bear And Ber Cubs", "description": "The sound of a mother bear with its cubs. Great nature and natural mammal sounds for camping, or outdoor sounds.", "author": "Mike Koenig", "href": "868-Bear-And-Ber-Cubs.html", "caption": "A mother bear is with its cubs.", "id": "868", "duration": 6.21715625, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=868&type=wav"} +{"title": "Bald Eagle", "description": "Bald eagle sound originally from the public domain but I reworked it and improved upon the audio quality. Slight hiss in background.", "author": "Mike Koenig", "href": "975-Bald-Eagle.html", "caption": "A bald eagle is making noise.", "id": "975", "duration": 3.7243125, "audio": "wav_path", "download_link": "http://soundbible.com/grab.php?id=975&type=wav"} diff --git a/tests/scps/tango-master/data/val_audioset_sl.json b/tests/scps/tango-master/data/val_audioset_sl.json new file mode 100644 index 0000000000000000000000000000000000000000..659816dc62e9ac7e3c64aac792d714d836be85e8 --- /dev/null +++ b/tests/scps/tango-master/data/val_audioset_sl.json @@ -0,0 +1,1000 @@ +{"id": "YVLjcIlZvkY0.wav", "caption": "Music, wild animal sounds, breathing, footsteps, and groaning are heard.", "audio": "wav_path", "duration": 10.0} +{"id": "Y8P9b72wW8OQ.wav", "caption": "Male speech accompanies breathing and mechanical noises.", "audio": "wav_path", "duration": 10.0} +{"id": "YcjxnDtyw9pE.wav", "caption": "The sound of waves crashing against a shoreline can be heard.", "audio": "wav_path", "duration": 10.0} +{"id": "Y_h5Xejh8LIs.wav", "caption": "Music, roaring, man speaking, applause, and whistling sounds mix.", "audio": "wav_path", "duration": 10.0} +{"id": "YEUwi4Yp3YB8.wav", "caption": "Cows moo and birds chirp amidst background noise and mechanisms.", "audio": "wav_path", "duration": 10.0} +{"id": "YzO4tdW9E8Ck.wav", "caption": "Music, speech babble, and screaming create a noisy environment.", "audio": "wav_path", "duration": 10.0} +{"id": "YGXl21oGvH3U.wav", "caption": "People run while speaking and machines hum.", "audio": "wav_path", "duration": 9.69678125} +{"id": "Yko2xNHYShaQ.wav", "caption": "People are speaking and wind noise is heard, a car is heard accelerating.", "audio": "wav_path", "duration": 10.0} +{"id": "YN5lrF4u0qEk.wav", "caption": "People are laughing, breathing, and speaking amidst wind and an electric shaver.", "audio": "wav_path", "duration": 9.99996875} +{"id": "Y4OeqwuG9k18.wav", "caption": "Video game sounds and sound effects play in rapid succession.", "audio": "wav_path", "duration": 10.0} +{"id": "YwZL9xO70HJU.wav", "caption": "A man is speaking, it's raining, and laughter can be heard.", "audio": "wav_path", "duration": 10.0} +{"id": "YEjilXXbICJE.wav", "caption": "Female singing and the sound of ducks are heard amidst music.", "audio": "wav_path", "duration": 9.67975} +{"id": "Y3lo-VZ-qZl0.wav", "caption": "A steam whistle is blowing repeatedly.", "audio": "wav_path", "duration": 10.00090625} +{"id": "YdRhSRn7H9dk.wav", "caption": "A sewing machine ticks and hums while background noise is heard.", "audio": "wav_path", "duration": 10.0} +{"id": "YYGAZXnNcCPY.wav", "caption": "Women are speaking, having a conversation, and hearing subway sounds and speech synthesizers.", "audio": "wav_path", "duration": 10.0} +{"id": "Y3ZqS1eG_BRI.wav", "caption": "A group of male and female singers perform music.", "audio": "wav_path", "duration": 10.0} +{"id": "YAVmJF1uaRuE.wav", "caption": "Men are singing and music is playing.", "audio": "wav_path", "duration": 10.0} +{"id": "Y8uNHIoPPy9Y.wav", "caption": "A man is speaking, crows are cawing, and a man is singing.", "audio": "wav_path", "duration": 10.0} +{"id": "Y8SKdI7v1lrY.wav", "caption": "Music and mechanisms sound as people breathe, speak, and make sounds.", "audio": "wav_path", "duration": 10.0004375} +{"id": "Y83e-DCkTg7Y.wav", "caption": "A child and adult cry and speak, with background noise and squeaks.", "audio": "wav_path", "duration": 10.0} +{"id": "YC9ydhEcGMC0.wav", "caption": "Bells are ringing in a change ringing pattern.", "audio": "wav_path", "duration": 10.0} +{"id": "YemP2Sg9QEg4.wav", "caption": "Music is playing.", "audio": "wav_path", "duration": 10.0} +{"id": "YasuybGFBPa0.wav", "caption": "Footsteps and bird sounds are heard with sound effects in the background.", "audio": "wav_path", "duration": 10.0} +{"id": "YGwI0V20eyw4.wav", "caption": "A man speaks, mechanisms tick, and breathing and human voices are audible.", "audio": 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video game sounds, and explosions are heard while people are speaking.", "audio": "wav_path", "duration": 10.0} +{"id": "Y5-acFNBnyLQ.wav", "caption": "A chainsaw is being used with background noise.", "audio": "wav_path", "duration": 9.9135} +{"id": "YmZIBXZlICgw.wav", "caption": "A light engine is running with a ticking sound.", "audio": "wav_path", "duration": 10.0} +{"id": "YWdlMyO_CR4c.wav", "caption": "People walk, make sound effects, play video games, and hear whip sounds.", "audio": "wav_path", "duration": 9.19521875} +{"id": "Yv8NtH43iHXM.wav", "caption": "Breathing and a man speaking are heard with mechanisms ticking.", "audio": "wav_path", "duration": 10.0} +{"id": "Ymn2-63qW_wo.wav", "caption": "Birds sing and people walk, slam doors, and converse with music playing.", "audio": "wav_path", "duration": 10.0} +{"id": "YBYQ9dV5WxeM.wav", "caption": "Sound effects and human sounds can be heard with music and video game sounds.", "audio": "wav_path", "duration": 10.0} +{"id": "Y4hxX-BPWQGY.wav", "caption": "Snoring and ticking sounds are heard with insect sounds.", "audio": "wav_path", "duration": 10.0} +{"id": "YC6rohe-t1iU.wav", "caption": "Male speech and waves crashing are heard with a child speaking.", "audio": "wav_path", "duration": 10.0} +{"id": "Y7nbga07GxDg.wav", "caption": "A child is speaking and breathing while mechanisms sounds are heard.", "audio": "wav_path", "duration": 10.0} +{"id": "YJtiAq_LErAY.wav", "caption": "A woman speaks intermittently amid brief tones and cash register sounds.", "audio": "wav_path", "duration": 9.4135} +{"id": "YkzTK14YsWPg.wav", "caption": "Crinkling sounds and bird songs are heard in a windy environment.", "audio": "wav_path", "duration": 9.8535} +{"id": "YPBzeQWDqQA8.wav", "caption": "Rustling, wind, and explosions are heard.", "audio": "wav_path", "duration": 10.0} +{"id": "Yfdn3uM_meRw.wav", "caption": "Music, singing, and speaking are heard with applause.", "audio": "wav_path", "duration": 10.0} +{"id": "YKu89jtybecM.wav", "caption": "Plops and meowing are heard with music.", "audio": "wav_path", "duration": 10.0} +{"id": "Y1a_nvi4sW64.wav", "caption": "Female singers perform music.", "audio": "wav_path", "duration": 10.000875} +{"id": "Y2tgnMkCEi7g.wav", "caption": "An engine runs, wind blows, and footsteps can be heard.", "audio": "wav_path", "duration": 8.8735} +{"id": "YPQBIe980K6E.wav", "caption": "Bells ring in a change ringing pattern.", "audio": "wav_path", "duration": 10.0} +{"id": "Y6LSdXZSYT4I.wav", "caption": "Music, choir, and a male singing are heard.", "audio": "wav_path", "duration": 10.0} +{"id": "YNafDNhiFsTc.wav", "caption": "A truck uses air brakes and reversing beeps while a man speaks.", "audio": "wav_path", "duration": 10.0} +{"id": "YhlIW4TGiMCA.wav", "caption": "Background music is heard.", "audio": "wav_path", "duration": 10.0} +{"id": "YDyuKhlB2NHs.wav", "caption": "Mechanisms and shuffling sounds.", "audio": "wav_path", "duration": 10.0} +{"id": "YSp1YBy4h9OY.wav", "caption": "A bell rings and fades in and out over background speech noise.", "audio": "wav_path", "duration": 10.0} +{"id": "YxwRBn5TCpow.wav", "caption": "A child is speaking with coughing and laughter in the background.", "audio": "wav_path", "duration": 10.0} +{"id": "Y7blprMMvWLA.wav", "caption": "Music, video game sounds, and men speaking with sound effects are heard in the recording.", "audio": "wav_path", "duration": 9.99909375} +{"id": "Ygs3cRbXITZ0.wav", "caption": "Music plays while women and a man speak and wind noise persists.", "audio": "wav_path", "duration": 10.0} +{"id": "Y1wRDPK3E3q4.wav", "caption": "Laughter, shouting, sound effects, and breathing can be heard over background noise.", "audio": "wav_path", "duration": 9.3135} +{"id": "Ygo0gXq4NHIQ.wav", "caption": "Chants and mechanisms are heard with tapping sounds.", "audio": "wav_path", "duration": 10.0} +{"id": "YSyG7KciDpy0.wav", "caption": "A car is driving by with an accelerating engine and ticking sounds.", "audio": "wav_path", "duration": 9.63165625} +{"id": "Y5gJ_PWgJWIw.wav", "caption": "Screaming and gunfire sounds mix with music, screams, groans, and gunfire.", "audio": "wav_path", "duration": 10.0} +{"id": "Y5rSgETYVSos.wav", "caption": "Wind is blowing and a man is speaking while rodents make patter sounds and mechanisms are heard.", "audio": "wav_path", "duration": 10.0} +{"id": "YwPSIlb578ss.wav", "caption": "Children are speaking and splashing in water with ticking sounds in the background.", "audio": "wav_path", "duration": 9.9994375} +{"id": "YfHYYmUsEE-4.wav", "caption": "Children are speaking and making plopping sounds.", "audio": "wav_path", "duration": 10.0} +{"id": "YTlLj5bR7nD8.wav", "caption": "Steam hisses as a train moves with ticking and babbling sounds.", "audio": "wav_path", "duration": 10.0} diff --git a/tests/scps/tango-master/data/valid_audiocaps.json b/tests/scps/tango-master/data/valid_audiocaps.json new file mode 100644 index 0000000000000000000000000000000000000000..fe37457dc53b0964f6edc1201c5fbf8922087b6d --- /dev/null +++ b/tests/scps/tango-master/data/valid_audiocaps.json @@ -0,0 +1,2240 @@ +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/vfY_TJq7n_U_130.wav", "captions": "Rustling occurs, ducks quack and water splashes, followed by an adult female and adult male speaking and duck calls being blown"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/tdWhHV3X25Q_60.wav", "captions": "An audience gives applause as a man yells and a group sings"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/tw76HGONaKg_570.wav", "captions": "A man speaks over intermittent keyboard taps"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/y2bVZ7rz-5M_280.wav", "captions": "Motor noise is followed by a horn honking and a siren wailing"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/uYT5gxnyMWM_50.wav", "captions": "A young female speaks, followed 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"location": "/data/deep/audioset/data/zoKp_laniT8_10.wav", "captions": "A boat passes by on the water and a man speaks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/t97k0cejSQE_250.wav", "captions": "Birds chirp in the distance followed by bees buzzing loudly"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/xeOp_6mV1DY_60.wav", "captions": "Ducks quack loudly and repeatedly while men speak and a dog barks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/wIvYjuR3nrg_9.wav", "captions": "Birds tweet and pigeons vocalize as they walk around"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/xzKKf9bKNUo_10.wav", "captions": "A person is snoring while sleeping"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/sZvwOuuPGP0_50.wav", "captions": "A diesel truck engine runs steadily"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/y1saVTXsKwc_80.wav", "captions": "A dog growls lowly with a man speaking in the middle"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/sZuuj08Gr_I_150.wav", "captions": "Some rustling and a woman speaks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/wsHBIgzs9Fs_50.wav", "captions": "Some motorcycle moves then a horn is triggered and motorcycles are accelerates and a man shouts"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/xERFUeZONz8_0.wav", "captions": "A siren wails, and then interrupted, and wails again"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/yVVP8XvWJTo_260.wav", "captions": "A female voice briefly yells as several children start talking and yelling all around"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/s4tUs779vBA_160.wav", "captions": "A motor runs choppily, followed by an animal croaking, and a person exclaiming"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/yZmhM1HcsyE_4.wav", "captions": "Waves crashing as wind blows 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background"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/zdYdyF9-m8U_7.wav", "captions": "Ocean waves crashing as water trickles and splashes while wind blows into a microphone alongside seagulls squawking in the background"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/xYoIXskAdKg_20.wav", "captions": "Vehicle engine revving"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/zVacuqSb4LI_30.wav", "captions": "A train horn whistles as it passes by"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/sG7TyPnFDR0_180.wav", "captions": "A man speaks followed by a two beeps and another man speaking"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/wqZ135_Ssz0_60.wav", "captions": "A man and woman speak outside as the wind blows"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/xSN_cBFt-PI_30.wav", "captions": "A clock chimes, ticks, then chimes again"} +{"dataset": "audiocaps", "location": 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"/data/deep/audioset/data/z4uELRI6p08_40.wav", "captions": "Laughing followed by a short groan then more laughing"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/y8WEcpOlT3I_40.wav", "captions": "A man speaks while wind blows"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/w9ejUrlz1GM_460.wav", "captions": "Someone crumples plastic and speaks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/wmTdukran8Y_410.wav", "captions": "A grown man speaks and a machine cranks and runs"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/x_l2PIWyXaM_160.wav", "captions": "A man and a woman talk as birds chirp in the background."} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/yRcOezOVG_s_10.wav", "captions": "A motor runs as a man speaks and a door slams"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/tqR406bGi_E_40.wav", "captions": "A toilet flushes and water drains"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/uK5doE8g_nY_80.wav", "captions": "A motor sputters and runs choppily"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/vms5XGTDVQc_220.wav", "captions": "Continuous crumpling and crinkling"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/ztQ79sWWC34_60.wav", "captions": "A child is speaking, shuffling and faint scraping occur, and a glass dish thumps"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/xmdGaCbvhFc_140.wav", "captions": "A man speaks as a water faucet runs"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/uiS58TNyUiw_430.wav", "captions": "A grown man talks calmly while a creature produces low grunts"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/un9VQ_lzgZM_5.wav", "captions": "A woman speaks and another laughs as wind blows and a foghorn sounds"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/vz8868znkVQ_60.wav", "captions": "A goat bleats and children laugh and speak"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/spYNpeN7rPY_1.wav", "captions": "A man speaks then a clock ticktocks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/t5ZbXbniOWk_30.wav", "captions": "A propeller spins and ticks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/w2htir_si7g_100.wav", "captions": "Loud musical whistling"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/sGgBtiZY0U8_30.wav", "captions": "Girls scream and a man speaks as wind blows and a boat motor runs"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/uiItxDsDMFI_30.wav", "captions": "A saw cuts roughly through something"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/yaln9y8I7ms_230.wav", "captions": "Clicking followed by a flushing toilet and a child speaking briefly"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/uJV8NDaHqqk_100.wav", "captions": "Birds chirp softly as insects buzz"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/vcTWN0HCyoY_210.wav", "captions": "Rain falls onto a surface and thunder roars"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/xfaoyyzw2WU_180.wav", "captions": "An airplane engine works nearby while a man talks"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/w9lpbUn0hPc_30.wav", "captions": "A man speaking followed by a man in the distance then a short burst of air spraying with wind blowing"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/sfAvvZwdLCY_20.wav", "captions": "A toilet flushes and water drains"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/rwb6PSAee5Y_60.wav", "captions": "A toilet flushes and water drains"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/tqR406bGi_E_40.wav", "captions": "A toilet flushes and water drains"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/s-T9OVOiMLo_330.wav", "captions": "Insects buzz around and men talk"} +{"dataset": "audiocaps", "location": "/data/deep/audioset/data/yiUDYRSJpJI_30.wav", "captions": "Rapid fire loud booming gunshots"} diff --git a/tests/vgg_test.scp b/tests/vgg_test.scp new file mode 100644 index 0000000000000000000000000000000000000000..2cc4276f1645bfae734f78c089886437e7b76164 --- /dev/null +++ b/tests/vgg_test.scp @@ -0,0 +1,14592 @@ +tests/VGGSound/video/1u1orBeV4xI_000428.mp4 ripping paper +tests/VGGSound/video/1uCzQCdCC1U_000170.mp4 race car, auto racing +tests/VGGSound/video/1uIfP9ipzxY_000058.mp4 playing table tennis +tests/VGGSound/video/1uLkSMHxvZY_000440.mp4 playing zither +tests/VGGSound/video/7E0I8_VuI7w_000006.mp4 people slurping +tests/VGGSound/video/7EAkRbG8qKk_000140.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/7EDm66CQuHA_000337.mp4 planing timber +tests/VGGSound/video/1uhuVsFGe6E_000050.mp4 child speech, kid speaking +tests/VGGSound/video/7EgbS-lbHWY_000005.mp4 chicken clucking +tests/VGGSound/video/1vByeH2oiHU_000260.mp4 firing cannon +tests/VGGSound/video/7FBIBPKPzAA_000035.mp4 air conditioning noise +tests/VGGSound/video/1veIcvGPRYw_000003.mp4 dog bow-wow +tests/VGGSound/video/1vl0QEz3844_000000.mp4 sheep bleating +tests/VGGSound/video/7FHHtRuAz0s_000020.mp4 people clapping +tests/VGGSound/video/1vrJPFfLMvA_000233.mp4 playing glockenspiel +tests/VGGSound/video/1vrR6Im_RDo_000030.mp4 female singing +tests/VGGSound/video/1vy-ZxTMQf4_000377.mp4 people marching +tests/VGGSound/video/1w_iLXQb-9Q_000007.mp4 children shouting +tests/VGGSound/video/7G0CFAGswrw_000240.mp4 playing marimba, xylophone +tests/VGGSound/video/1wdCX1HmRyk_000140.mp4 cricket chirping +tests/VGGSound/video/7G8ZGuGNrw8_000030.mp4 male singing +tests/VGGSound/video/j-wEtmNLMgM_000062.mp4 cricket chirping +tests/VGGSound/video/mGKX6kwKvSE_000340.mp4 eating with cutlery +tests/VGGSound/video/j0CcOZJLBDg_000020.mp4 ambulance siren 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howling +tests/VGGSound/video/-JzMCtGCh4o_000000.mp4 frog croaking +tests/VGGSound/video/-K-ccLMFE5M_000245.mp4 people marching +tests/VGGSound/video/-K-ccLMFE5M_000259.mp4 people marching +tests/VGGSound/video/-K1BRF6qng8_000030.mp4 female singing +tests/VGGSound/video/-KA76yUSK44_000240.mp4 playing cello +tests/VGGSound/video/-KBH8YmHR-0_000050.mp4 snake rattling +tests/VGGSound/video/-KCYC-n5Uag_000022.mp4 wind chime +tests/VGGSound/video/-KTabIWnPSg_000021.mp4 rapping +tests/VGGSound/video/-KqXcm-I2zY_000087.mp4 playing tennis +tests/VGGSound/video/-KqXcm-I2zY_000162.mp4 playing tennis +tests/VGGSound/video/-Lmibx_Iu_E_000173.mp4 tractor digging +tests/VGGSound/video/-Lv13WPa4xk_000170.mp4 airplane flyby +tests/VGGSound/video/-LxtesAXWIU_000032.mp4 sea waves +tests/VGGSound/video/-LxtesAXWIU_000042.mp4 sea waves +tests/VGGSound/video/-M6K3QoHh40_000030.mp4 people shuffling +tests/VGGSound/video/-M7ZNV6gLo0_000310.mp4 bird squawking +tests/VGGSound/video/-MIwX2AaUas_000158.mp4 chopping food +tests/VGGSound/video/-N00SskHxS4_000529.mp4 playing bugle +tests/VGGSound/video/-NCa3eFLULw_000221.mp4 dinosaurs bellowing +tests/VGGSound/video/-NQl3o-CGwY_000098.mp4 elk bugling +tests/VGGSound/video/-NRx0SBMjo0_000024.mp4 pumping water +tests/VGGSound/video/-NwBdmVSg1w_000000.mp4 cat hissing +tests/VGGSound/video/-O4W3NA5-uA_000150.mp4 playing tennis +tests/VGGSound/video/-OAyRsvFGgc_000030.mp4 tapping guitar +tests/VGGSound/video/-OEJFMpQ-ko_000159.mp4 playing darts +tests/VGGSound/video/-OJzsMV1G1A_000061.mp4 chopping wood +tests/VGGSound/video/-OVb-UG8yJw_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/-SWaCArvQug_000021.mp4 opening or closing drawers +tests/VGGSound/video/-Sd-j0rKeKw_000030.mp4 dog whimpering +tests/VGGSound/video/-T2MO0xBNwM_000026.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/-T8L4SVm3u0_000001.mp4 footsteps on snow +tests/VGGSound/video/-OxoxrlzLXA_000045.mp4 roller coaster running 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cornet +tests/VGGSound/video/-Y8sJDoL1YA_000015.mp4 playing gong +tests/VGGSound/video/-YfaQljuwwA_000030.mp4 horse clip-clop +tests/VGGSound/video/-YwPSwhe2jo_000030.mp4 people shuffling +tests/VGGSound/video/-Z1ZSWDouUU_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/-ZFNLu4HclQ_000000.mp4 sharpen knife +tests/VGGSound/video/-ZJqu_4zLMc_000030.mp4 cat meowing +tests/VGGSound/video/-ZSgg6jFUd8_000688.mp4 people eating crisps +tests/VGGSound/video/-Zl_ZkDmZHE_000000.mp4 playing castanets +tests/VGGSound/video/-_QPd-VskKY_000030.mp4 mouse squeaking +tests/VGGSound/video/-_f_ClsDxyc_000080.mp4 playing clarinet +tests/VGGSound/video/-_umX4zgLVY_000028.mp4 lions growling +tests/VGGSound/video/-_yRmyG71Z0_000036.mp4 woodpecker pecking tree +tests/VGGSound/video/-aK9JKAGme0_000041.mp4 cheetah chirrup +tests/VGGSound/video/-aK9JKAGme0_000051.mp4 cheetah chirrup +tests/VGGSound/video/-aOxR6ILsw8_000000.mp4 car engine starting +tests/VGGSound/video/-aUJLRXkj-Y_000118.mp4 children shouting +tests/VGGSound/video/-aXWYfAdovc_000230.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/-b42018ceoE_000078.mp4 striking pool +tests/VGGSound/video/-bJPDtT31p0_000100.mp4 playing drum kit +tests/VGGSound/video/-c6baaENcjA_000204.mp4 sea lion barking +tests/VGGSound/video/-cA9HsnV1ao_000030.mp4 hair dryer drying +tests/VGGSound/video/-cm0voL_GRM_000322.mp4 cell phone buzzing +tests/VGGSound/video/-crF-0Z7l3o_000447.mp4 playing bassoon +tests/VGGSound/video/-ct58kOlLfs_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/-d1KR2BSfHM_000065.mp4 squishing water +tests/VGGSound/video/-dRucPKqTFc_000007.mp4 people slapping +tests/VGGSound/video/-e4wXAy1iVo_000000.mp4 playing ukulele +tests/VGGSound/video/-f1DNyngKVY_000030.mp4 playing sitar +tests/VGGSound/video/-fAGzY9rnaA_000030.mp4 female speech, woman speaking +tests/VGGSound/video/-fAVezaAX18_000126.mp4 playing drum kit +tests/VGGSound/video/-fJsZm3YRc0_000030.mp4 reversing beeps 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barking +tests/VGGSound/video/-hYRFCQdbLg_000030.mp4 playing steelpan +tests/VGGSound/video/-hb5BJ9xxBQ_000062.mp4 striking bowling +tests/VGGSound/video/-hedbpc8T0E_000030.mp4 people babbling +tests/VGGSound/video/-hfAbHHlj44_000030.mp4 people crowd +tests/VGGSound/video/-hn5Sfg7kX0_000000.mp4 mouse pattering +tests/VGGSound/video/-hss7xpzIVc_000030.mp4 male singing +tests/VGGSound/video/-iF4a6f5PJ8_000000.mp4 pheasant crowing +tests/VGGSound/video/-iF4a6f5PJ8_000060.mp4 pheasant crowing +tests/VGGSound/video/-inB65exXFU_000030.mp4 firing cannon +tests/VGGSound/video/-jA7nRwQp_E_000030.mp4 orchestra +tests/VGGSound/video/-jFSYIHh6zc_000030.mp4 dog whimpering +tests/VGGSound/video/-jVXNEvUJss_000259.mp4 playing table tennis +tests/VGGSound/video/-jZENGDFArw_000080.mp4 child speech, kid speaking +tests/VGGSound/video/-jaY3LS3Dv0_000030.mp4 child speech, kid speaking +tests/VGGSound/video/-k-hxP5eWko_000030.mp4 lawn mowing +tests/VGGSound/video/-kPDH9n0PG4_000310.mp4 railroad car, train wagon +tests/VGGSound/video/-kWlE2dkoxc_000170.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/-kZVoaYYU6o_000000.mp4 driving buses +tests/VGGSound/video/-kephM41AwA_000333.mp4 electric grinder grinding +tests/VGGSound/video/-l-E3kyNcag_000150.mp4 playing french horn +tests/VGGSound/video/-lJctvybAJ8_000030.mp4 playing vibraphone +tests/VGGSound/video/-lPXTBXa0tE_000030.mp4 tapping guitar +tests/VGGSound/video/-mKtgDnG0oM_000030.mp4 female singing +tests/VGGSound/video/-mN5Uo1_TRI_000100.mp4 striking pool +tests/VGGSound/video/-miI_C3At4Y_000104.mp4 playing badminton +tests/VGGSound/video/-nDPmlHReow_000060.mp4 people crowd +tests/VGGSound/video/-nJbGyPg6BY_000060.mp4 people clapping +tests/VGGSound/video/-nQ9a0P1TlY_000023.mp4 child singing +tests/VGGSound/video/-na-0NBG5Ow_000001.mp4 frog croaking +tests/VGGSound/video/-nj0HaLz2N4_000023.mp4 playing hockey +tests/VGGSound/video/-njdG2dcQx0_000220.mp4 chimpanzee pant-hooting +tests/VGGSound/video/-nlkWWphiaM_000030.mp4 playing acoustic guitar +tests/VGGSound/video/-oGJwGEsIiA_000090.mp4 splashing water +tests/VGGSound/video/-oOARU0JwWE_000153.mp4 people humming +tests/VGGSound/video/-oSzD8P2BtU_000030.mp4 reversing beeps +tests/VGGSound/video/-ocADGlyaHc_000030.mp4 helicopter +tests/VGGSound/video/-p-pVVp0Ibo_000020.mp4 baby babbling +tests/VGGSound/video/-pBFsYisTCM_000010.mp4 playing vibraphone +tests/VGGSound/video/-qtYcqvW_oc_000330.mp4 orchestra +tests/VGGSound/video/-qxw8nbLj_0_000000.mp4 waterfall burbling +tests/VGGSound/video/-r-k-BvQbRM_000038.mp4 black capped chickadee calling +tests/VGGSound/video/-r2-9oyIzkQ_000030.mp4 male singing +tests/VGGSound/video/-r3nM90RCNs_000161.mp4 sharpen knife +tests/VGGSound/video/-r4vbRkcndc_000128.mp4 sea waves +tests/VGGSound/video/-rTTPoBJNI4_000123.mp4 playing tambourine +tests/VGGSound/video/-rb6uia1wSo_000190.mp4 playing clarinet +tests/VGGSound/video/-rcoSOKo-qM_000566.mp4 electric grinder grinding +tests/VGGSound/video/-rqhMzJRYoc_000030.mp4 people hiccup +tests/VGGSound/video/-s5ZidRvnjQ_000250.mp4 singing bowl +tests/VGGSound/video/-sbrgNGuWXE_000270.mp4 playing flute +tests/VGGSound/video/-spqqACI6UQ_000070.mp4 skateboarding +tests/VGGSound/video/-t-htrAtNvM_000030.mp4 reversing beeps +tests/VGGSound/video/-tm7JvKYFcE_000042.mp4 bowling impact +tests/VGGSound/video/-tptsFSnu60_000235.mp4 hair dryer drying +tests/VGGSound/video/-u-40BIU1HE_000003.mp4 cat hissing +tests/VGGSound/video/-u-40BIU1HE_000014.mp4 cat hissing +tests/VGGSound/video/-uD3ZbhFTnk_000077.mp4 baltimore oriole calling +tests/VGGSound/video/-uGHAvfqs2I_000030.mp4 cat meowing +tests/VGGSound/video/-uaTK8sa5Ms_000010.mp4 playing banjo +tests/VGGSound/video/-ugSeFtSqhU_000134.mp4 playing shofar +tests/VGGSound/video/-vAtBe4LMCQ_000063.mp4 people eating crisps +tests/VGGSound/video/-vBj0PZ1RF0_000009.mp4 people clapping +tests/VGGSound/video/-vNGqcDA6oE_000020.mp4 scuba diving +tests/VGGSound/video/-vZ-_4oFCzs_000017.mp4 cat meowing +tests/VGGSound/video/-vg8ttgP32I_000018.mp4 car passing by +tests/VGGSound/video/-w8maIWtnUk_000030.mp4 playing electric guitar +tests/VGGSound/video/-wP6ycrwb9U_000026.mp4 ice cream truck, ice cream van +tests/VGGSound/video/-wQ8El8J_dE_000030.mp4 sliding door +tests/VGGSound/video/-wi8kPVJLcw_000205.mp4 air conditioning noise +tests/VGGSound/video/-wnDAPcoPsk_000030.mp4 playing hammond organ +tests/VGGSound/video/-wwPo59cjuo_000334.mp4 people eating apple +tests/VGGSound/video/-xCaTrKy1CI_000000.mp4 playing marimba, xylophone +tests/VGGSound/video/-xQbyezhw_k_000040.mp4 hair dryer drying +tests/VGGSound/video/-xTVeti9VkQ_000018.mp4 magpie calling +tests/VGGSound/video/-xfgovG6-KU_000030.mp4 sliding door +tests/VGGSound/video/-yI3BN2OrO4_000352.mp4 mouse clicking +tests/VGGSound/video/-yicwYUKKuo_000304.mp4 airplane flyby +tests/VGGSound/video/-yrglmBmErg_000225.mp4 opening or closing car doors +tests/VGGSound/video/-z3AAq0FK-0_000001.mp4 snake rattling 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ice cream truck, ice cream van +tests/VGGSound/video/02Ak1eIyj3M_000030.mp4 ambulance siren +tests/VGGSound/video/02UvvE1oA1I_000030.mp4 goat bleating +tests/VGGSound/video/030h_KwNm-g_000003.mp4 sheep bleating +tests/VGGSound/video/03Q2SbeP_cw_000030.mp4 ambulance siren +tests/VGGSound/video/03zeVlBWhdY_000030.mp4 dog whimpering +tests/VGGSound/video/0439dMJj-FY_000030.mp4 thunder +tests/VGGSound/video/0474eRAlFLY_000030.mp4 playing bagpipes +tests/VGGSound/video/04L5PnWm3SQ_000053.mp4 sea lion barking +tests/VGGSound/video/04QV0Xi5YTk_000030.mp4 playing zither +tests/VGGSound/video/04zBqiZ6M4w_000179.mp4 playing castanets +tests/VGGSound/video/052VMqTM4Xs_000000.mp4 donkey, ass braying +tests/VGGSound/video/054iiUoKoyo_000010.mp4 playing synthesizer +tests/VGGSound/video/05GsUEyThd8_000013.mp4 parrot talking +tests/VGGSound/video/05je2oOzmV0_000071.mp4 smoke detector beeping +tests/VGGSound/video/05uiW8xh5QU_000001.mp4 playing hockey +tests/VGGSound/video/064Ilsz8Fzg_000051.mp4 car engine starting +tests/VGGSound/video/067izxXJJu4_000020.mp4 running electric fan +tests/VGGSound/video/06pzMwo6VHA_000120.mp4 playing marimba, xylophone +tests/VGGSound/video/06si40RVDco_000030.mp4 driving motorcycle +tests/VGGSound/video/076qdKSC8nU_000030.mp4 tapping guitar +tests/VGGSound/video/077aWlQn6XI_000030.mp4 reversing beeps +tests/VGGSound/video/07FxCXxknY4_000030.mp4 playing bass guitar +tests/VGGSound/video/07I7v5ISD7Y_000350.mp4 hair dryer drying +tests/VGGSound/video/07bi-w2VKeg_000035.mp4 footsteps on snow +tests/VGGSound/video/08Cm_RuvHmk_000000.mp4 playing zither +tests/VGGSound/video/08mf5GxT820_000030.mp4 people shuffling +tests/VGGSound/video/09LqFbgwszg_000155.mp4 heart sounds, heartbeat +tests/VGGSound/video/09NfjFeq2cs_000078.mp4 francolin calling +tests/VGGSound/video/09kqMqn5rWs_000260.mp4 child speech, kid speaking +tests/VGGSound/video/09pZj6CEvRw_000250.mp4 church bell ringing +tests/VGGSound/video/0B7fwvTtvLM_000000.mp4 basketball bounce 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(siren) +tests/VGGSound/video/0N3-lCzOQPI_000000.mp4 frog croaking +tests/VGGSound/video/0N6S5OoG7Vg_000150.mp4 wind noise +tests/VGGSound/video/0N9EN0BEjP0_000430.mp4 driving buses +tests/VGGSound/video/0NIE-eDk92M_000029.mp4 playing congas +tests/VGGSound/video/0NLXz4JgvcQ_000096.mp4 people eating crisps +tests/VGGSound/video/0NQXsEwBqAk_000136.mp4 tractor digging +tests/VGGSound/video/0NZLG7HMiLg_000590.mp4 wind noise +tests/VGGSound/video/0NZQRllfNhE_000140.mp4 mynah bird singing +tests/VGGSound/video/0O-gZoirpRA_000030.mp4 reversing beeps +tests/VGGSound/video/0O463Ft4mVY_000080.mp4 skiing +tests/VGGSound/video/0O4_CpR6azM_000091.mp4 volcano explosion +tests/VGGSound/video/0O5xrYEZlSM_000456.mp4 heart sounds, heartbeat +tests/VGGSound/video/0OFlTh2_Obo_000030.mp4 dog bow-wow +tests/VGGSound/video/0OH28bnOdEE_000058.mp4 people gargling +tests/VGGSound/video/0OLYyjqNdn4_000352.mp4 train whistling +tests/VGGSound/video/0OY8XXZ98rw_000030.mp4 male singing 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+tests/VGGSound/video/0YI_WYJVv2M_000030.mp4 goat bleating +tests/VGGSound/video/0YIyGEM0yG0_000550.mp4 train wheels squealing +tests/VGGSound/video/0YTieIiZNN4_000010.mp4 machine gun shooting +tests/VGGSound/video/0a264PE9qEY_000024.mp4 playing cornet +tests/VGGSound/video/0a4UPHowiOM_000011.mp4 people gargling +tests/VGGSound/video/0aJZPu-3anY_000022.mp4 plastic bottle crushing +tests/VGGSound/video/0aaLWD7TUSU_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/0apGJGFHQO4_000067.mp4 playing violin, fiddle +tests/VGGSound/video/0bBJkY4_zs8_000033.mp4 elk bugling +tests/VGGSound/video/0bJgHzGSqK0_000002.mp4 sloshing water +tests/VGGSound/video/0bKpv6YBl7g_000050.mp4 opening or closing drawers +tests/VGGSound/video/0bobzCB2ObQ_000076.mp4 tractor digging +tests/VGGSound/video/0c78GAZ0jLY_000005.mp4 child singing +tests/VGGSound/video/0cNYPgD6cEA_000030.mp4 male singing +tests/VGGSound/video/0d6YdyxkXzQ_000815.mp4 ripping paper +tests/VGGSound/video/0dC1f6bdyr4_000142.mp4 yodelling +tests/VGGSound/video/0dC6Ay0oqWk_000030.mp4 playing zither +tests/VGGSound/video/0dUL0EweBEY_000387.mp4 plastic bottle crushing +tests/VGGSound/video/0dUL0EweBEY_000423.mp4 plastic bottle crushing +tests/VGGSound/video/0dd6AlyOnfc_000030.mp4 pumping water +tests/VGGSound/video/0eA2QcSRgh0_000053.mp4 dog baying +tests/VGGSound/video/0eA2QcSRgh0_000063.mp4 dog baying +tests/VGGSound/video/0eDN0YmnJRY_000002.mp4 cheetah chirrup +tests/VGGSound/video/0eTrzI5-ong_000030.mp4 playing zither +tests/VGGSound/video/0eZHWqzsRqU_000005.mp4 elk bugling +tests/VGGSound/video/0f0Rq7e5yX8_000160.mp4 sloshing water +tests/VGGSound/video/0f2Q2J0AwQQ_000377.mp4 scuba diving +tests/VGGSound/video/0fDDlf0Mrp8_000782.mp4 swimming +tests/VGGSound/video/0foC-4n-eH0_000000.mp4 sliding door +tests/VGGSound/video/0fqtA_ZBn_8_000030.mp4 playing sitar +tests/VGGSound/video/0fsFWLev-q4_000257.mp4 running electric fan +tests/VGGSound/video/0g-KosNgMYA_000070.mp4 railroad car, train wagon +tests/VGGSound/video/0g4SlqjORM4_000080.mp4 playing french horn +tests/VGGSound/video/0g_-KI5NZ-E_000030.mp4 people whistling +tests/VGGSound/video/0glBUluF4Yk_000175.mp4 fox barking +tests/VGGSound/video/0hOD_iIeePk_000030.mp4 car engine starting +tests/VGGSound/video/0hWIKYNSEPE_000080.mp4 playing bagpipes +tests/VGGSound/video/0hdkmTWLnw8_000042.mp4 playing darts +tests/VGGSound/video/0he6VV5Y9Bg_000030.mp4 cricket chirping +tests/VGGSound/video/0hfU27A6tus_000070.mp4 playing banjo +tests/VGGSound/video/0hjqlmdPT6g_000050.mp4 car engine starting +tests/VGGSound/video/0iX0QmnbrK4_000085.mp4 playing trombone +tests/VGGSound/video/0iiwZ2_9Vi8_000090.mp4 people coughing +tests/VGGSound/video/0izHOfrwPn4_000180.mp4 duck quacking +tests/VGGSound/video/0jiu0RNizU8_000160.mp4 playing violin, fiddle +tests/VGGSound/video/0ju5RWqEwGQ_000033.mp4 playing darts +tests/VGGSound/video/0ju5RWqEwGQ_000108.mp4 playing darts +tests/VGGSound/video/0jy-sVREk4o_000030.mp4 horse clip-clop +tests/VGGSound/video/0kK-PnupAow_000086.mp4 opening or closing car doors +tests/VGGSound/video/0kQkVbOikzQ_000004.mp4 airplane flyby +tests/VGGSound/video/0kqQNBR09Rc_000090.mp4 skidding +tests/VGGSound/video/0lPcHRhXlWk_000030.mp4 driving buses +tests/VGGSound/video/0loP4WNnL2k_000000.mp4 subway, metro, underground +tests/VGGSound/video/0m9-5BkL4Mc_000030.mp4 child singing +tests/VGGSound/video/0mNvPaqfwUI_000220.mp4 railroad car, train wagon +tests/VGGSound/video/0mZQ6Q-viPw_000010.mp4 people coughing +tests/VGGSound/video/0mkj5A9qg9A_000086.mp4 shot football +tests/VGGSound/video/0n-Z2AQCRnU_000385.mp4 people eating noodle +tests/VGGSound/video/0n56ajMNoMA_000118.mp4 driving snowmobile +tests/VGGSound/video/0nYltlo90Zc_000147.mp4 playing congas +tests/VGGSound/video/0nYltlo90Zc_000161.mp4 playing congas +tests/VGGSound/video/0nib7bMm8BA_000015.mp4 canary calling +tests/VGGSound/video/0nvBTp-q7tU_000112.mp4 driving snowmobile +tests/VGGSound/video/0oTdsarJHA4_000220.mp4 playing trombone +tests/VGGSound/video/0olhNr566Z0_000018.mp4 playing trumpet +tests/VGGSound/video/0onKcFY1Tu0_000002.mp4 frog croaking +tests/VGGSound/video/0pHTgC1Frnw_000350.mp4 playing marimba, xylophone +tests/VGGSound/video/0pYpyy1VXdM_000080.mp4 bird squawking +tests/VGGSound/video/0q1zNZNjzaA_000001.mp4 whale calling +tests/VGGSound/video/0q5kQGcOn2I_000083.mp4 francolin calling +tests/VGGSound/video/0q6GOUn_dhU_000066.mp4 playing castanets +tests/VGGSound/video/0q9FUj_2qMc_000539.mp4 hedge trimmer running +tests/VGGSound/video/0qDs_aC0LwI_000005.mp4 mouse squeaking +tests/VGGSound/video/0qSK2GuljEc_000580.mp4 playing gong +tests/VGGSound/video/0rDaP06do8c_000092.mp4 striking bowling +tests/VGGSound/video/0rKz4unZteU_000063.mp4 hail +tests/VGGSound/video/0ryt1DPirB0_000020.mp4 playing gong +tests/VGGSound/video/0s62qg0kfJE_000013.mp4 warbler chirping +tests/VGGSound/video/0sT6vnChbrc_000000.mp4 cat growling +tests/VGGSound/video/0slFEpnTKkY_000115.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/0slyl34xWug_000010.mp4 splashing water +tests/VGGSound/video/0ssOpzqkojU_000030.mp4 playing harpsichord +tests/VGGSound/video/0t1jQa_Lj_E_000130.mp4 arc welding +tests/VGGSound/video/0teMcpgy9Jo_000058.mp4 pheasant crowing +tests/VGGSound/video/0ti14lvd2Aw_000000.mp4 pheasant crowing +tests/VGGSound/video/0u5dddSWuj8_000030.mp4 playing bagpipes +tests/VGGSound/video/0uMEyyhzaqU_000034.mp4 cutting hair with electric trimmers +tests/VGGSound/video/0ua6AnyVwbk_000036.mp4 disc scratching +tests/VGGSound/video/0unbxXUE_c0_000114.mp4 bowling impact +tests/VGGSound/video/0ut4if4B6zM_000056.mp4 plastic bottle crushing +tests/VGGSound/video/0vFPs6XsU_Q_000030.mp4 male singing +tests/VGGSound/video/0vXqf9ix8LE_000030.mp4 cricket chirping +tests/VGGSound/video/0vg9qxNKXOw_000030.mp4 skateboarding +tests/VGGSound/video/0w7pCxwXzVc_000120.mp4 wind noise +tests/VGGSound/video/0w9PLY1owzk_000108.mp4 airplane +tests/VGGSound/video/0wdNFZhpdQw_000368.mp4 people eating crisps +tests/VGGSound/video/0welW-8hB1c_000071.mp4 black capped chickadee calling +tests/VGGSound/video/0wzsE67O5tE_000230.mp4 playing ukulele +tests/VGGSound/video/0x9TnOQ5Nhw_000020.mp4 pigeon, dove cooing +tests/VGGSound/video/0xDlT_u31fg_000030.mp4 fire truck siren +tests/VGGSound/video/0xPWkrfjMu0_000178.mp4 lip smacking +tests/VGGSound/video/0yxJzCQW5zI_000030.mp4 people whispering +tests/VGGSound/video/1-J5ByJcrc4_000066.mp4 snake rattling +tests/VGGSound/video/1-feQHDL-Qo_000030.mp4 waterfall burbling +tests/VGGSound/video/10RyykoW3Mw_000030.mp4 female singing +tests/VGGSound/video/10Y5oGN2J30_000142.mp4 skiing +tests/VGGSound/video/10YXuv9Go0E_000140.mp4 skateboarding +tests/VGGSound/video/10aBef0Ghkc_000040.mp4 playing piano +tests/VGGSound/video/10aF24rMeu0_000030.mp4 reversing beeps +tests/VGGSound/video/10hGfv89L3g_000030.mp4 car passing by +tests/VGGSound/video/10rH37YYvKU_000030.mp4 thunder +tests/VGGSound/video/115l3adqQ1M_000417.mp4 driving motorcycle +tests/VGGSound/video/11KWMKfalJo_000040.mp4 people running +tests/VGGSound/video/11ruZHgyTKM_000030.mp4 chicken crowing +tests/VGGSound/video/126AbihZt28_000009.mp4 horse clip-clop +tests/VGGSound/video/12C-RCb6UFw_000430.mp4 subway, metro, underground +tests/VGGSound/video/12Sd9Aap5ww_000251.mp4 running electric fan +tests/VGGSound/video/12T-9dLEbY8_000020.mp4 bird squawking +tests/VGGSound/video/12eRdXA6Iig_000077.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/130v5XJl8G0_000070.mp4 people coughing +tests/VGGSound/video/13ITCsFeMJU_000017.mp4 cutting hair with electric trimmers +tests/VGGSound/video/13Ij0Y-m7N0_000121.mp4 running electric fan +tests/VGGSound/video/13W_9xdaOZE_000068.mp4 tap dancing +tests/VGGSound/video/13k0xa_vTFI_000022.mp4 blowtorch igniting +tests/VGGSound/video/145N68nh4m0_000130.mp4 police car (siren) +tests/VGGSound/video/14XML4NbS38_000005.mp4 chicken crowing +tests/VGGSound/video/14jcqHjMXcI_000000.mp4 horse clip-clop +tests/VGGSound/video/14lBeX_dOHU_000234.mp4 canary calling +tests/VGGSound/video/14tRPoQA4q0_000004.mp4 baby laughter +tests/VGGSound/video/156q2w_ca1U_000030.mp4 female singing +tests/VGGSound/video/15703UC_0b0_000138.mp4 airplane flyby +tests/VGGSound/video/15Mw2jyyHk0_000030.mp4 playing bass guitar +tests/VGGSound/video/15aMq3FEyjQ_000026.mp4 sea lion barking +tests/VGGSound/video/15hFilKnrlM_000200.mp4 people whistling +tests/VGGSound/video/15pi8h_bHQE_000173.mp4 cow lowing +tests/VGGSound/video/169a2JSphHA_000269.mp4 playing double bass +tests/VGGSound/video/16CvcIXIjzQ_000332.mp4 chinchilla barking +tests/VGGSound/video/16TsDMjHzYU_000030.mp4 female singing +tests/VGGSound/video/17CpJxlwzNg_000030.mp4 stream burbling +tests/VGGSound/video/17Fh7LMMzhc_000070.mp4 playing ukulele +tests/VGGSound/video/17K-oEuH1p0_000020.mp4 playing bugle +tests/VGGSound/video/17L2VkXtcQ0_000030.mp4 chicken crowing +tests/VGGSound/video/17Ne52PWgsI_000093.mp4 electric grinder grinding +tests/VGGSound/video/17QNWSDwhm0_000000.mp4 firing muskets +tests/VGGSound/video/17WW_p1N7BQ_000030.mp4 cat meowing +tests/VGGSound/video/17cwMjZ3MZs_000113.mp4 air conditioning noise +tests/VGGSound/video/17yDXvJTdeo_000603.mp4 people slurping +tests/VGGSound/video/18212B4yfLg_000080.mp4 lighting firecrackers +tests/VGGSound/video/188AGDc9CSY_000070.mp4 running electric fan +tests/VGGSound/video/18HRNQyo9mg_000025.mp4 cat meowing +tests/VGGSound/video/18PLoJDIvIQ_000110.mp4 bird squawking +tests/VGGSound/video/19_c58yNYVw_000010.mp4 thunder +tests/VGGSound/video/19knOj43yZE_000330.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/19r6_MQei4M_000119.mp4 dinosaurs bellowing +tests/VGGSound/video/1ACn3u5UnBw_000030.mp4 male singing +tests/VGGSound/video/1B-RuZgSqf8_000030.mp4 raining +tests/VGGSound/video/1B0VJf7jRDg_000313.mp4 people slurping +tests/VGGSound/video/1BYZiONhW3c_000030.mp4 singing choir +tests/VGGSound/video/1BivKH8w7Fo_000037.mp4 people cheering 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+tests/VGGSound/video/1ETrMAVZdY8_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/1EWkwWXwI1g_000210.mp4 lighting firecrackers +tests/VGGSound/video/1EiNSiO0UvU_000000.mp4 people sneezing +tests/VGGSound/video/1ErGsKIlhAI_000051.mp4 people humming +tests/VGGSound/video/1EuGaYmvlXM_000170.mp4 goose honking +tests/VGGSound/video/1F-jIu9oy6A_000060.mp4 splashing water +tests/VGGSound/video/1F23RciUwDE_000030.mp4 car engine starting +tests/VGGSound/video/1F3_bvIT0ig_000000.mp4 car passing by +tests/VGGSound/video/1F9zCsJyw6k_000230.mp4 police car (siren) +tests/VGGSound/video/1FJvkhl--e0_000825.mp4 lathe spinning +tests/VGGSound/video/1FU5odlgLmo_000030.mp4 playing mandolin +tests/VGGSound/video/1FWUnWVX5Xk_000159.mp4 baltimore oriole calling +tests/VGGSound/video/1FnA3w94zXI_000030.mp4 tapping guitar +tests/VGGSound/video/1G6wtnmdZhE_000030.mp4 car passing by +tests/VGGSound/video/1GDAnA4hAqQ_000105.mp4 airplane +tests/VGGSound/video/1GI75yXlrTk_000029.mp4 people slapping +tests/VGGSound/video/1GyO48dbGCI_000000.mp4 running electric fan +tests/VGGSound/video/1HUCwslugK8_000283.mp4 playing glockenspiel +tests/VGGSound/video/1HswRpBt6mI_000083.mp4 playing tympani +tests/VGGSound/video/1I5QQBbZP8g_000150.mp4 people crowd +tests/VGGSound/video/1I9s8TxOlaU_000028.mp4 people slurping +tests/VGGSound/video/1Isq_KJHriU_000016.mp4 dog baying +tests/VGGSound/video/1JSbmO1NQzk_000130.mp4 cricket chirping +tests/VGGSound/video/1JY4rwQZn3s_000011.mp4 donkey, ass braying +tests/VGGSound/video/1J_j6c2uQaM_000030.mp4 thunder +tests/VGGSound/video/1JfwuwHV0hc_000212.mp4 volcano explosion +tests/VGGSound/video/1Jo_WQrPc1Q_000140.mp4 striking pool +tests/VGGSound/video/1JsIcP2nXMw_000108.mp4 fox barking +tests/VGGSound/video/1K1hxgzudsM_000047.mp4 sea waves +tests/VGGSound/video/1KLmIS-v60U_000010.mp4 railroad car, train wagon +tests/VGGSound/video/1Kb6GNZClSM_000140.mp4 hail +tests/VGGSound/video/1KiFXylkPpg_000010.mp4 playing electronic organ +tests/VGGSound/video/1KpqiBhyP7Q_000008.mp4 ferret dooking +tests/VGGSound/video/1KpqiBhyP7Q_000066.mp4 ferret dooking +tests/VGGSound/video/1KpvQAM14Ic_000030.mp4 waterfall burbling +tests/VGGSound/video/1LA8BxMlXSY_000080.mp4 ambulance siren +tests/VGGSound/video/1LPIxPA6-O8_000261.mp4 playing erhu +tests/VGGSound/video/1LTxZ2aNytc_000030.mp4 people screaming +tests/VGGSound/video/1MP3sQTk8wo_000000.mp4 dog barking +tests/VGGSound/video/1MTKUN3uFrs_000440.mp4 fireworks banging +tests/VGGSound/video/1MaEJRh2oGY_000034.mp4 cheetah chirrup +tests/VGGSound/video/1MaEJRh2oGY_000089.mp4 cheetah chirrup +tests/VGGSound/video/1MgcrYdYas0_000030.mp4 chainsawing trees +tests/VGGSound/video/1MlgXBFnJl8_000044.mp4 train wheels squealing +tests/VGGSound/video/1Mvw2601xRg_000158.mp4 cuckoo bird calling +tests/VGGSound/video/1NV87x_JYnQ_000368.mp4 strike lighter +tests/VGGSound/video/1NkUBIl2Plw_000030.mp4 raining +tests/VGGSound/video/1Nm7UqNx9zs_000061.mp4 squishing water +tests/VGGSound/video/1Ny5ZlcBlcQ_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/1O-WeYTRS4w_000370.mp4 cattle, bovinae cowbell +tests/VGGSound/video/1OFDyTzUj24_000030.mp4 male speech, man speaking +tests/VGGSound/video/1OFOElP7bqc_000360.mp4 stream burbling +tests/VGGSound/video/1ON1iLkUPp8_000040.mp4 playing vibraphone +tests/VGGSound/video/1On2yNySbZ0_000210.mp4 sailing +tests/VGGSound/video/1OpNI5DjxC0_000030.mp4 playing synthesizer +tests/VGGSound/video/1P5FFxXLSpY_000030.mp4 reversing beeps +tests/VGGSound/video/1P9yEzO1Bic_000025.mp4 playing erhu +tests/VGGSound/video/1PAb2MoavDc_000210.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/1PN-bfs2EhY_000030.mp4 child singing +tests/VGGSound/video/1PPboJuO1Ks_000021.mp4 horse neighing +tests/VGGSound/video/1QBsc_IXg8U_000750.mp4 tornado roaring +tests/VGGSound/video/1QtsF8qkX1Y_000070.mp4 raining +tests/VGGSound/video/1Qvce8w_Vds_000011.mp4 people nose blowing +tests/VGGSound/video/1RAcDEFEszA_000093.mp4 chopping food +tests/VGGSound/video/1RfdLnNRLfA_000149.mp4 cupboard opening or closing +tests/VGGSound/video/1RhYdQnZ_hw_000030.mp4 female singing +tests/VGGSound/video/1RwhRTe-OKk_000030.mp4 playing banjo +tests/VGGSound/video/1S4SJnWsq1s_000442.mp4 playing hockey +tests/VGGSound/video/1SBP-Dy8_II_000119.mp4 tornado roaring +tests/VGGSound/video/1SJFTbu1abo_000042.mp4 canary calling +tests/VGGSound/video/1SPu2hsIhDw_000167.mp4 roller coaster running +tests/VGGSound/video/1TAOyk0Xgss_000370.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/1TJrceFMGrU_000114.mp4 tractor digging +tests/VGGSound/video/1TP8JyI5vHI_000030.mp4 duck quacking +tests/VGGSound/video/1Tg9VvRZN5k_000030.mp4 subway, metro, underground +tests/VGGSound/video/1Thl21awe2g_000020.mp4 car engine knocking +tests/VGGSound/video/1TvSxv6aql8_000430.mp4 splashing water +tests/VGGSound/video/1U38Q2MpYM4_000030.mp4 wind noise +tests/VGGSound/video/1U8Y6VifI-M_000050.mp4 people sneezing +tests/VGGSound/video/1UNk699Uqto_000030.mp4 goose honking +tests/VGGSound/video/1UXkMZNI5o4_000373.mp4 wood thrush calling +tests/VGGSound/video/1Uj_ulATth0_000360.mp4 bird chirping, tweeting +tests/VGGSound/video/1V-_jMSJR6A_000024.mp4 playing trumpet +tests/VGGSound/video/1VHm2PacRWc_000020.mp4 cow lowing +tests/VGGSound/video/1Vt6qYw1BnQ_000002.mp4 playing bongo +tests/VGGSound/video/1W-KLZJwXkc_000010.mp4 people shuffling +tests/VGGSound/video/1W2FOzSXsxs_000030.mp4 child singing +tests/VGGSound/video/1W83RMliwv8_000049.mp4 francolin calling +tests/VGGSound/video/1W9fwoe4O-M_000117.mp4 child singing +tests/VGGSound/video/1WGfcIOLUK8_000030.mp4 dog barking +tests/VGGSound/video/1WI9921OeRc_000570.mp4 people burping +tests/VGGSound/video/1WLMVX_Y2Pk_000018.mp4 elephant trumpeting +tests/VGGSound/video/1WLMVX_Y2Pk_000213.mp4 elephant trumpeting +tests/VGGSound/video/1XO0SqsZhHU_000030.mp4 raining +tests/VGGSound/video/1XZyIaJT8Lw_000106.mp4 snake hissing +tests/VGGSound/video/1Xmw9VUzvLY_000150.mp4 people coughing +tests/VGGSound/video/1XxHC7eMNg8_000011.mp4 forging swords +tests/VGGSound/video/1XxHC7eMNg8_000024.mp4 forging swords +tests/VGGSound/video/1Y2YtG9EX-g_000300.mp4 thunder +tests/VGGSound/video/1YFa9CpH7Kc_000180.mp4 cattle, bovinae cowbell +tests/VGGSound/video/1YWeSXAXwQE_000030.mp4 people burping +tests/VGGSound/video/1YxcifClvo0_000016.mp4 pigeon, dove cooing +tests/VGGSound/video/1Z9lTtd7ReE_000014.mp4 playing lacrosse +tests/VGGSound/video/1ZXe1qg_xeg_000125.mp4 cell phone buzzing +tests/VGGSound/video/1ZgXgyEJSbc_000390.mp4 playing tabla +tests/VGGSound/video/1ZloXG3iHl8_000018.mp4 children shouting +tests/VGGSound/video/1ZwVoNUvaAE_000000.mp4 playing snare drum +tests/VGGSound/video/1_0T2ZIjWnw_000031.mp4 playing violin, fiddle +tests/VGGSound/video/1_JeO9Pg1aQ_000020.mp4 cricket chirping +tests/VGGSound/video/1_Q80fDGLRM_000010.mp4 dog barking +tests/VGGSound/video/1_Yd3NwpP7M_000210.mp4 singing bowl +tests/VGGSound/video/1_iqBlxMkBU_000030.mp4 printer printing +tests/VGGSound/video/1_v-Kro86Io_000010.mp4 playing harpsichord +tests/VGGSound/video/1_xoCNmTn3Y_000012.mp4 coyote howling +tests/VGGSound/video/1_xoCNmTn3Y_000023.mp4 coyote howling +tests/VGGSound/video/1_yyvTRVoZQ_000002.mp4 alligators, crocodiles hissing +tests/VGGSound/video/1_yyvTRVoZQ_000209.mp4 alligators, crocodiles hissing +tests/VGGSound/video/1a-ODBWMUAE_000030.mp4 waterfall burbling +tests/VGGSound/video/1aDnyPubxdY_000118.mp4 baby crying +tests/VGGSound/video/1aexyJH0jU8_000002.mp4 blowtorch igniting +tests/VGGSound/video/1bIH_Qh_clk_000030.mp4 frog croaking +tests/VGGSound/video/1bSLrOlRIB4_000050.mp4 people slapping +tests/VGGSound/video/1bbyaXEVouE_000030.mp4 fire crackling +tests/VGGSound/video/1cneTLKxerM_000167.mp4 snake hissing +tests/VGGSound/video/1cqcTbDxsHM_000130.mp4 playing theremin +tests/VGGSound/video/1cwGW0cBdRs_000030.mp4 playing theremin +tests/VGGSound/video/1cwReJkXLVo_000505.mp4 race car, auto racing +tests/VGGSound/video/1cxvg7qu0G0_000070.mp4 lighting firecrackers +tests/VGGSound/video/1dyFP4MGkIM_000030.mp4 skidding +tests/VGGSound/video/1e0_4dwF9A4_000030.mp4 goose honking +tests/VGGSound/video/1eBzpkIY-TY_000198.mp4 snake hissing +tests/VGGSound/video/1eP5LSjyge0_000220.mp4 hair dryer drying +tests/VGGSound/video/1f-L1M-S6RQ_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/1f-s2gYqyh8_000019.mp4 shot football +tests/VGGSound/video/1fDGejVDAHU_000000.mp4 chainsawing trees +tests/VGGSound/video/1fJoK95DpaM_000002.mp4 police radio chatter +tests/VGGSound/video/7-COxzRtOEU_000030.mp4 toilet flushing +tests/VGGSound/video/1g3n6Zaqid8_000064.mp4 black capped chickadee calling +tests/VGGSound/video/7-G0kK4FIdM_000030.mp4 people whistling +tests/VGGSound/video/1g6sdWOc9k4_000510.mp4 stream burbling +tests/VGGSound/video/7-Ly3ICovLE_000030.mp4 people shuffling +tests/VGGSound/video/7-P4s1CBsZo_000243.mp4 blowtorch igniting +tests/VGGSound/video/7-V8cMwkXTk_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/7-Wm2TyvMs8_000030.mp4 people sniggering +tests/VGGSound/video/7-htobm4qu0_000030.mp4 dog bow-wow +tests/VGGSound/video/1gSwLBNvEWE_000034.mp4 playing oboe +tests/VGGSound/video/7-vFjIl7wCI_000021.mp4 children shouting +tests/VGGSound/video/7-z44NWB-84_000107.mp4 gibbon howling +tests/VGGSound/video/7-z44NWB-84_000170.mp4 gibbon howling +tests/VGGSound/video/1gWu-9hPzFs_000022.mp4 cheetah chirrup +tests/VGGSound/video/70CjsIbLwU0_000030.mp4 car engine starting +tests/VGGSound/video/70CtvdsGQf4_000002.mp4 cat caterwauling +tests/VGGSound/video/1garMoYilAY_000030.mp4 wind rustling leaves +tests/VGGSound/video/70RN67npErE_000008.mp4 air horn +tests/VGGSound/video/70SeDyvtqi8_000205.mp4 eletric blender running +tests/VGGSound/video/70nxwCv5v6Y_000080.mp4 hammering nails +tests/VGGSound/video/1hIg-Lsvc7Q_000030.mp4 driving buses +tests/VGGSound/video/1hJnxzlxnQs_000030.mp4 car passing by +tests/VGGSound/video/1hKSlZZ5T50_000002.mp4 chopping wood +tests/VGGSound/video/71T8pe3yPTQ_000047.mp4 scuba diving +tests/VGGSound/video/1hWAOReJehw_000140.mp4 playing tabla +tests/VGGSound/video/1hba9jmspEQ_000030.mp4 female speech, woman speaking +tests/VGGSound/video/1hknEtsmdOc_000030.mp4 car passing by +tests/VGGSound/video/1hoUEfsTmdE_000030.mp4 female singing +tests/VGGSound/video/1hrYIADPJ_w_000017.mp4 air conditioning noise +tests/VGGSound/video/72-UFjSlpvM_000314.mp4 golf driving +tests/VGGSound/video/1hsOUPwn21E_000083.mp4 cuckoo bird calling +tests/VGGSound/video/1hwkxJOl1PY_000020.mp4 lions roaring +tests/VGGSound/video/72RI4phr0F8_000020.mp4 male speech, man speaking +tests/VGGSound/video/1iP-Y7FDMys_000070.mp4 lathe spinning +tests/VGGSound/video/72b5UupN-Nw_000150.mp4 female speech, woman speaking +tests/VGGSound/video/72baZt5rKAs_000260.mp4 gibbon howling +tests/VGGSound/video/1ib1pd6mHoE_000001.mp4 eletric blender running +tests/VGGSound/video/1j13NdQiw8c_000030.mp4 playing steelpan +tests/VGGSound/video/1jHVyPknyhM_000005.mp4 elephant trumpeting +tests/VGGSound/video/73YTz8RC2Fo_000030.mp4 male singing +tests/VGGSound/video/73cuZZq-J3w_000020.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/73jyWz6o3X4_000130.mp4 people crowd +tests/VGGSound/video/73l89PUGTos_000040.mp4 mouse pattering +tests/VGGSound/video/1jq7zSF_v7s_000140.mp4 opening or closing drawers +tests/VGGSound/video/73yT9UXJLT0_000004.mp4 people booing +tests/VGGSound/video/73yT9UXJLT0_000032.mp4 people booing +tests/VGGSound/video/1k0R3npPdKI_000252.mp4 eletric blender running +tests/VGGSound/video/74Eeq1qer94_000030.mp4 playing harp +tests/VGGSound/video/74RHxEBrxdw_000005.mp4 playing guiro +tests/VGGSound/video/74Z5Pqx2HIk_000024.mp4 bathroom ventilation fan running +tests/VGGSound/video/74j6uEsqh4M_000120.mp4 playing guiro +tests/VGGSound/video/74j6uEsqh4M_000130.mp4 playing guiro +tests/VGGSound/video/74p3DLeDCHE_000030.mp4 playing acoustic guitar 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railroad car, train wagon +tests/VGGSound/video/78J9QqSBsN4_000030.mp4 train wheels squealing +tests/VGGSound/video/78N2SP6JFaI_000000.mp4 playing trombone +tests/VGGSound/video/1o_gJNHZBZs_000110.mp4 footsteps on snow +tests/VGGSound/video/78S8DnvLQDY_000030.mp4 baby babbling +tests/VGGSound/video/1obzCbmFpa8_000410.mp4 people giggling +tests/VGGSound/video/1owKdIYYYeg_000000.mp4 ocean burbling +tests/VGGSound/video/1p3NSKpuJDs_000144.mp4 child singing +tests/VGGSound/video/1p5jl5JeZx8_000117.mp4 people cheering +tests/VGGSound/video/78t2zq75Amg_000010.mp4 child speech, kid speaking +tests/VGGSound/video/1pMMz2vm6JE_000002.mp4 running electric fan +tests/VGGSound/video/1pMMz2vm6JE_000109.mp4 running electric fan +tests/VGGSound/video/7916WqcPKBA_000030.mp4 cat purring +tests/VGGSound/video/1pViEqMXJH0_000030.mp4 printer printing +tests/VGGSound/video/799dPLm5vs4_000002.mp4 pheasant crowing +tests/VGGSound/video/1q8kkQhS97g_000140.mp4 playing cymbal 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harp +tests/VGGSound/video/7Bsfl6Y7ZK4_000107.mp4 cupboard opening or closing +tests/VGGSound/video/7C-OTkTHHBY_000000.mp4 playing french horn +tests/VGGSound/video/1sukRxLM77w_000021.mp4 hedge trimmer running +tests/VGGSound/video/7CBrxJI9Pxs_000163.mp4 car engine idling +tests/VGGSound/video/7CG_9qUdU8M_000030.mp4 cattle mooing +tests/VGGSound/video/1tC7bTilFWk_000030.mp4 cat caterwauling +tests/VGGSound/video/7CRVoUCXg_A_000030.mp4 cat caterwauling +tests/VGGSound/video/7CTzN_wSb6g_000030.mp4 raining +tests/VGGSound/video/7C_jcD_FOQI_000030.mp4 goat bleating +tests/VGGSound/video/7CbQWONEGLk_000270.mp4 cutting hair with electric trimmers +tests/VGGSound/video/7Cey4yVxuSk_000312.mp4 playing badminton +tests/VGGSound/video/1tiz4gWXVGI_000608.mp4 turkey gobbling +tests/VGGSound/video/1tjJmArxVBM_000030.mp4 wind rustling leaves +tests/VGGSound/video/1tn0MJTOprg_000003.mp4 firing muskets +tests/VGGSound/video/1tobDIRRV0A_000030.mp4 crow cawing +tests/VGGSound/video/7D6AVpPGHzg_000510.mp4 mosquito buzzing +tests/VGGSound/video/1tz4xNRRR4M_000010.mp4 playing vibraphone +tests/VGGSound/video/7GCUGTrsFOE_000030.mp4 pig oinking +tests/VGGSound/video/1woaZGPrY9g_000002.mp4 car passing by +tests/VGGSound/video/7GJ9EGKOxSI_000200.mp4 alarm clock ringing +tests/VGGSound/video/1wqJ9KDfcME_000060.mp4 playing cymbal +tests/VGGSound/video/7GZdzd_wcBg_000230.mp4 fireworks banging +tests/VGGSound/video/7GjdyxNBxZQ_000220.mp4 people crowd +tests/VGGSound/video/7Gua0-UrKIw_000030.mp4 reversing beeps +tests/VGGSound/video/7H3_936cWTg_000007.mp4 air horn +tests/VGGSound/video/1xRNQCP4MbE_000030.mp4 female singing +tests/VGGSound/video/7H7l7lfs6JQ_000000.mp4 cuckoo bird calling +tests/VGGSound/video/1xS-iGBR2b8_000014.mp4 donkey, ass braying +tests/VGGSound/video/7HF6OiDKaQA_000232.mp4 chipmunk chirping +tests/VGGSound/video/1xYpHbg0fEE_000030.mp4 female singing +tests/VGGSound/video/1xZESfMpi9Q_000156.mp4 playing badminton +tests/VGGSound/video/1xhSBniwGbM_000030.mp4 male singing 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door +tests/VGGSound/video/7OPMIXXz1DM_000000.mp4 scuba diving +tests/VGGSound/video/22OjhEqCWj8_000042.mp4 playing tambourine +tests/VGGSound/video/7OhXiEHalAk_000047.mp4 elephant trumpeting +tests/VGGSound/video/7OhXiEHalAk_000063.mp4 elephant trumpeting +tests/VGGSound/video/7OpYEh7weVM_000000.mp4 lions roaring +tests/VGGSound/video/7OqOXtp8_tk_000030.mp4 child singing +tests/VGGSound/video/7OqsePnrOSo_000061.mp4 magpie calling +tests/VGGSound/video/7OuOH15wRhU_000010.mp4 magpie calling +tests/VGGSound/video/22gk62Sijnc_000300.mp4 people farting +tests/VGGSound/video/7OyCsvavJNA_000040.mp4 cap gun shooting +tests/VGGSound/video/7P7sCHtDLU8_000030.mp4 subway, metro, underground +tests/VGGSound/video/7PEL4NrU1Jk_000023.mp4 cattle mooing +tests/VGGSound/video/7PK3nvCihMk_000011.mp4 bull bellowing +tests/VGGSound/video/23FY9sjfgM8_000117.mp4 ice cracking +tests/VGGSound/video/23HYypV2gcM_000590.mp4 child speech, kid speaking +tests/VGGSound/video/23J1LFGj910_000064.mp4 planing timber 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woodpecker pecking tree +tests/VGGSound/video/2N2msWTHybg_000340.mp4 child speech, kid speaking +tests/VGGSound/video/2NESqWU89V0_000338.mp4 playing violin, fiddle +tests/VGGSound/video/2NKHzLvsfXk_000113.mp4 bowling impact +tests/VGGSound/video/7kxpD5UzNpU_000022.mp4 striking pool +tests/VGGSound/video/7kxpD5UzNpU_000170.mp4 striking pool +tests/VGGSound/video/7l_TPfOhh5c_000570.mp4 chicken crowing +tests/VGGSound/video/2OOZIIosPX4_000071.mp4 train wheels squealing +tests/VGGSound/video/7mPAAZP8SIk_000429.mp4 people eating noodle +tests/VGGSound/video/7mQCtRG83wo_000010.mp4 playing timpani +tests/VGGSound/video/7mXmO2XpH_A_000105.mp4 strike lighter +tests/VGGSound/video/2Oe5kao1ycY_000310.mp4 subway, metro, underground +tests/VGGSound/video/7mr9UVVsv6I_000030.mp4 singing bowl +tests/VGGSound/video/7mtYFBOmeNs_000030.mp4 people whispering +tests/VGGSound/video/7n0vuxy-OXg_000026.mp4 playing bugle +tests/VGGSound/video/7nCe_iDT0NA_000000.mp4 horse neighing 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electric guitar +tests/VGGSound/video/7pdrGzdWMzI_000050.mp4 rapping +tests/VGGSound/video/2REf8hLLYMw_000030.mp4 cat meowing +tests/VGGSound/video/7pejUx-WH4g_000397.mp4 arc welding +tests/VGGSound/video/2RHarmH7DEk_000024.mp4 woodpecker pecking tree +tests/VGGSound/video/7qE47XOqcG0_000100.mp4 female speech, woman speaking +tests/VGGSound/video/7qfxCvwyxms_000010.mp4 playing piano +tests/VGGSound/video/2S-YRM0p6cc_000034.mp4 coyote howling +tests/VGGSound/video/7r1ZIR38fFY_000050.mp4 playing french horn +tests/VGGSound/video/7rMhrFb-DsE_000183.mp4 blowtorch igniting +tests/VGGSound/video/2SchRwpsT7s_000048.mp4 people battle cry +tests/VGGSound/video/2SgGaIe_5vw_000000.mp4 underwater bubbling +tests/VGGSound/video/2Ssh4YWMroo_000030.mp4 cat caterwauling +tests/VGGSound/video/7rqy1JhY7TU_000030.mp4 goat bleating +tests/VGGSound/video/7rxfucuwC-Q_000360.mp4 people eating noodle +tests/VGGSound/video/7rzEesL55fM_000340.mp4 playing vibraphone +tests/VGGSound/video/2Szah76TMgo_000002.mp4 people running +tests/VGGSound/video/7s6xFTV74tE_000070.mp4 child speech, kid speaking +tests/VGGSound/video/2T1P9ovsl4A_000030.mp4 playing bass guitar +tests/VGGSound/video/2T8OhRXZDTs_000030.mp4 playing zither +tests/VGGSound/video/2TE2oO9QpT8_000181.mp4 foghorn +tests/VGGSound/video/7sYsxcdTcXY_000056.mp4 playing glockenspiel +tests/VGGSound/video/7sjPS_ru0Kw_000030.mp4 typing on typewriter +tests/VGGSound/video/2TW5ZDk8_A0_000017.mp4 foghorn +tests/VGGSound/video/7spslajA0hc_000099.mp4 strike lighter +tests/VGGSound/video/7t2HZLZ1PQs_000028.mp4 people clapping +tests/VGGSound/video/2TjVbDWZvcE_000007.mp4 owl hooting +tests/VGGSound/video/7tE6gxSwrH4_000030.mp4 singing choir +tests/VGGSound/video/2TprtMP1RDo_000030.mp4 people whispering +tests/VGGSound/video/7tMPoaU2oL4_000000.mp4 people cheering +tests/VGGSound/video/2Tx5L5RBXxw_000200.mp4 stream burbling +tests/VGGSound/video/2U-4QHS0QBc_000040.mp4 playing tabla +tests/VGGSound/video/2U5f3uTl7qg_000167.mp4 playing tambourine 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whispering +tests/VGGSound/video/2XFrBXTnNY8_000080.mp4 dog barking +tests/VGGSound/video/7yi2rZVC41E_000003.mp4 cupboard opening or closing +tests/VGGSound/video/7yjEC7Cr6i8_000030.mp4 playing harp +tests/VGGSound/video/7yk8XI5q7go_000030.mp4 orchestra +tests/VGGSound/video/2XK3vXa-wgw_000030.mp4 horse clip-clop +tests/VGGSound/video/2XOTejBfF2g_000404.mp4 chopping wood +tests/VGGSound/video/2XOTejBfF2g_000514.mp4 chopping wood +tests/VGGSound/video/2XQzahrQ_tE_000025.mp4 sea waves +tests/VGGSound/video/2XQzahrQ_tE_000075.mp4 sea waves +tests/VGGSound/video/2XR54m3kvn8_000370.mp4 mouse pattering +tests/VGGSound/video/7zS81_mUsK0_000080.mp4 lawn mowing +tests/VGGSound/video/8-54FDyd8dk_000382.mp4 car engine idling +tests/VGGSound/video/2YJpjSldLtg_000495.mp4 driving snowmobile +tests/VGGSound/video/8-DsEUYJMJo_000442.mp4 cuckoo bird calling +tests/VGGSound/video/2YW7WBtqzzQ_000000.mp4 people burping +tests/VGGSound/video/2YXcqoFlYFY_000160.mp4 fireworks banging 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screaming +tests/VGGSound/video/8Aq06SXi6G8_000010.mp4 coyote howling +tests/VGGSound/video/2gvw16YDwMA_000043.mp4 cat caterwauling +tests/VGGSound/video/2gvw16YDwMA_000153.mp4 cat caterwauling +tests/VGGSound/video/2gyMDnt8e6k_000411.mp4 playing tennis +tests/VGGSound/video/8B3FjLzkdPA_000020.mp4 playing clarinet +tests/VGGSound/video/2hCMb1rgLK4_000102.mp4 penguins braying +tests/VGGSound/video/8BQgOfXaBa4_000125.mp4 snake rattling +tests/VGGSound/video/2hNEs5VCQR8_000106.mp4 playing trumpet +tests/VGGSound/video/8BWEY-CvafE_000067.mp4 air conditioning noise +tests/VGGSound/video/8BWcP2uUzpo_000107.mp4 people humming +tests/VGGSound/video/8C4-ZFYWkcc_000102.mp4 wood thrush calling +tests/VGGSound/video/2i1Gs32odx4_000410.mp4 playing tabla +tests/VGGSound/video/2i4UNf8tjvU_000030.mp4 wind rustling leaves +tests/VGGSound/video/2iAO9PKZDGk_000000.mp4 church bell ringing +tests/VGGSound/video/8CqqK9CzuXM_000090.mp4 skidding +tests/VGGSound/video/8CrTpWNBiTo_000120.mp4 dog barking 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vibraphone +tests/VGGSound/video/8Nu6Tfgw-Dg_000368.mp4 footsteps on snow +tests/VGGSound/video/8Nu6Tfgw-Dg_000647.mp4 footsteps on snow +tests/VGGSound/video/8O-hCtPfef8_000044.mp4 playing bass drum +tests/VGGSound/video/2uHcWdkV4W4_000120.mp4 subway, metro, underground +tests/VGGSound/video/8OKAwDv20R8_000006.mp4 male singing +tests/VGGSound/video/2uRe-e8RVEM_000190.mp4 dog bow-wow +tests/VGGSound/video/8ONN7XhqNGY_000230.mp4 playing guiro +tests/VGGSound/video/2uYTNgvxVwk_000257.mp4 people humming +tests/VGGSound/video/2uZt59va3Ss_000050.mp4 subway, metro, underground +tests/VGGSound/video/2uagA3ujRtM_000000.mp4 cat purring +tests/VGGSound/video/8OXOwCahOOU_000089.mp4 playing ukulele +tests/VGGSound/video/8OukwZl_vsg_000030.mp4 car engine starting +tests/VGGSound/video/2v1rSA4FqlM_000100.mp4 pumping water +tests/VGGSound/video/2vFqNsOPq3I_000020.mp4 playing french horn +tests/VGGSound/video/2vSF2Yh6o_k_000020.mp4 mouse pattering +tests/VGGSound/video/2vYkvwD-fkc_000010.mp4 playing harmonica +tests/VGGSound/video/2v_KyNpsyKs_000030.mp4 ambulance siren +tests/VGGSound/video/2vcA_vgImHQ_000020.mp4 lawn mowing +tests/VGGSound/video/8Q3e7Hvo0zo_000490.mp4 people crowd +tests/VGGSound/video/2voy_hxeD54_000089.mp4 playing table tennis +tests/VGGSound/video/2vycuIKwnnA_000000.mp4 baltimore oriole calling +tests/VGGSound/video/2vzUFWykARU_000020.mp4 toilet flushing +tests/VGGSound/video/8QHoSMEiBAg_000025.mp4 driving snowmobile +tests/VGGSound/video/8QIsxTcZio4_000141.mp4 cutting hair with electric trimmers +tests/VGGSound/video/8QaKO2JbGfk_000000.mp4 bird squawking +tests/VGGSound/video/8QfmtF0FGA4_000114.mp4 arc welding +tests/VGGSound/video/2wGvpfAkly0_000030.mp4 child singing +tests/VGGSound/video/8QiTQN5reqs_000218.mp4 parrot talking +tests/VGGSound/video/2wIrHCaxBNU_000370.mp4 mosquito buzzing +tests/VGGSound/video/8QntTInSS1A_000030.mp4 raining +tests/VGGSound/video/2wsp3s4hIKs_000008.mp4 francolin calling +tests/VGGSound/video/2x373CrHD6E_000000.mp4 cupboard opening or closing +tests/VGGSound/video/2xBIHi3oqy4_000030.mp4 female speech, woman speaking +tests/VGGSound/video/2xCwG0Wju4s_000100.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/8RjJvfW0Q3M_000130.mp4 ocean burbling +tests/VGGSound/video/2xQuWif8axE_000030.mp4 playing electric guitar +tests/VGGSound/video/8S-R5p17_IE_000160.mp4 playing saxophone +tests/VGGSound/video/8S7zsWndDfk_000070.mp4 opening or closing drawers +tests/VGGSound/video/2y7aiiaJPf8_000240.mp4 eating with cutlery +tests/VGGSound/video/8ScHkS_cqk4_000090.mp4 stream burbling +tests/VGGSound/video/8Sfjahpupqg_000000.mp4 mouse squeaking +tests/VGGSound/video/8SpDSZY-ge0_000451.mp4 heart sounds, heartbeat +tests/VGGSound/video/2yX9079mMB4_000003.mp4 cat meowing +tests/VGGSound/video/8T6O7iBGj5o_000410.mp4 singing bowl +tests/VGGSound/video/8TCdnr4F6tw_000303.mp4 playing glockenspiel +tests/VGGSound/video/8TNLqJ0dJDA_000297.mp4 skiing +tests/VGGSound/video/2yllw7g5EkU_000030.mp4 people eating 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crying +tests/VGGSound/video/8ws1ligErwo_000000.mp4 cat meowing +tests/VGGSound/video/8wsYT1PRjIg_000074.mp4 police car (siren) +tests/VGGSound/video/3LLKsRSkAbE_000110.mp4 subway, metro, underground +tests/VGGSound/video/3LNnX2Vq0XM_000000.mp4 snake hissing +tests/VGGSound/video/8xU2s6Y-_a0_000030.mp4 playing electronic organ +tests/VGGSound/video/8xoenlVVBZw_000030.mp4 cat meowing +tests/VGGSound/video/3LiCT1BSrgQ_000150.mp4 reversing beeps +tests/VGGSound/video/8xpT2UQhzqE_000084.mp4 playing tennis +tests/VGGSound/video/3Liy9uBgsQM_000060.mp4 people coughing +tests/VGGSound/video/3LtXT2KVI-c_000030.mp4 cat meowing +tests/VGGSound/video/3Lu6lM69r6Q_000196.mp4 firing muskets +tests/VGGSound/video/3LulQoOXNB0_000030.mp4 driving motorcycle +tests/VGGSound/video/3LvZUtupOCs_000030.mp4 dog howling +tests/VGGSound/video/3LxtO_vMokk_000010.mp4 driving motorcycle +tests/VGGSound/video/8yjxwQBqQAI_000070.mp4 coyote howling +tests/VGGSound/video/3MUeg3nD2OU_000120.mp4 playing acoustic guitar 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slot machine +tests/VGGSound/video/3NvKtRbbOYU_000310.mp4 driving snowmobile +tests/VGGSound/video/3NwKXCGLjAk_000030.mp4 people shuffling +tests/VGGSound/video/3O0a3DAcNLM_000029.mp4 wind chime +tests/VGGSound/video/9-R70gSqvrc_000030.mp4 playing banjo +tests/VGGSound/video/3O7CzEL0pXA_000421.mp4 people marching +tests/VGGSound/video/3O7CzEL0pXA_000496.mp4 people marching +tests/VGGSound/video/9-b18y3Nexg_000285.mp4 train horning +tests/VGGSound/video/9-rrXPvMbro_000076.mp4 playing bassoon +tests/VGGSound/video/9-tUObAs28M_000030.mp4 car passing by +tests/VGGSound/video/3OSOrymuA6A_000160.mp4 playing steelpan +tests/VGGSound/video/3OWArQGgmm0_000040.mp4 tapping guitar +tests/VGGSound/video/90-yhRr5p1g_000000.mp4 people clapping +tests/VGGSound/video/3Oa4oE3bQTY_000510.mp4 playing harp +tests/VGGSound/video/3OlQmVVOzbQ_000250.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/3P0TaRKQPbE_000400.mp4 playing clarinet +tests/VGGSound/video/90q-9qr7-Qg_000075.mp4 chipmunk chirping 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francolin calling +tests/VGGSound/video/3VfSV1vJydw_000191.mp4 playing mandolin +tests/VGGSound/video/98T0aXt-aq0_000190.mp4 elephant trumpeting +tests/VGGSound/video/98ZM90poqNE_000164.mp4 people slapping +tests/VGGSound/video/3Vpt-gR-8Lk_000030.mp4 cat purring +tests/VGGSound/video/98xglJB2PQI_000003.mp4 forging swords +tests/VGGSound/video/99-mbUX8mJw_000030.mp4 sliding door +tests/VGGSound/video/99A5reksPts_000520.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/99VNZPt2MIs_000126.mp4 elephant trumpeting +tests/VGGSound/video/99iIggWrfNM_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/3X9dtfeV1mQ_000040.mp4 playing saxophone +tests/VGGSound/video/3XC4QOoRjB4_000240.mp4 playing cymbal +tests/VGGSound/video/3XQz8AOcq7o_000146.mp4 writing on blackboard with chalk +tests/VGGSound/video/9A4wz85FItc_000154.mp4 skiing +tests/VGGSound/video/3XhpZyBrIVk_000018.mp4 woodpecker pecking tree +tests/VGGSound/video/9AUSYLKYKGg_001113.mp4 owl hooting 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rapping +tests/VGGSound/video/9DCH0BCASyk_000302.mp4 donkey, ass braying +tests/VGGSound/video/3_A0AP3Xh9s_000290.mp4 playing cymbal +tests/VGGSound/video/9DSDisMCUsc_000190.mp4 playing darts +tests/VGGSound/video/3_M9ZMo5TiU_000130.mp4 playing theremin +tests/VGGSound/video/3_OLj6XChvM_000030.mp4 car engine starting +tests/VGGSound/video/3_mv3UWGkt0_000011.mp4 playing glockenspiel +tests/VGGSound/video/3aJH8XTyWLA_000024.mp4 barn swallow calling +tests/VGGSound/video/3aJH8XTyWLA_000073.mp4 barn swallow calling +tests/VGGSound/video/9EL_wYpAj6I_000355.mp4 francolin calling +tests/VGGSound/video/3adOb4Wns_k_000124.mp4 civil defense siren +tests/VGGSound/video/9EsgN-WS2qY_000030.mp4 reversing beeps +tests/VGGSound/video/3afdupjoqvQ_000074.mp4 car engine idling +tests/VGGSound/video/9F1Tw0VnG38_000010.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/3b0W6CnqYHc_000031.mp4 people battle cry +tests/VGGSound/video/3bC3I41ROVU_000014.mp4 sea lion barking 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magpie calling +tests/VGGSound/video/3dNiqeUQIq4_000408.mp4 playing table tennis +tests/VGGSound/video/3dgg5f9CyP4_000030.mp4 singing choir +tests/VGGSound/video/9IMO27jHA6o_000200.mp4 people finger snapping +tests/VGGSound/video/9Ijpv6e57a4_000030.mp4 skateboarding +tests/VGGSound/video/3eBoAlHnttY_000030.mp4 singing choir +tests/VGGSound/video/9IuFwl2AtcI_000030.mp4 baby crying +tests/VGGSound/video/3eaA8bsLJBA_000042.mp4 playing cornet +tests/VGGSound/video/9J8sce4390s_000106.mp4 playing washboard +tests/VGGSound/video/9JAatGaveSc_000035.mp4 eagle screaming +tests/VGGSound/video/9JBG-Wi1gUQ_000030.mp4 waterfall burbling +tests/VGGSound/video/9JISgXvxb4Y_000086.mp4 gibbon howling +tests/VGGSound/video/3f5atenstgc_000030.mp4 horse clip-clop +tests/VGGSound/video/9JnCupgoSrc_000181.mp4 playing lacrosse +tests/VGGSound/video/9JwAddAl120_000310.mp4 people finger snapping +tests/VGGSound/video/9K1WO3UNFb0_000269.mp4 bouncing on trampoline +tests/VGGSound/video/3feU6jqOjnU_000003.mp4 zebra braying +tests/VGGSound/video/9KxwnbkRskU_000000.mp4 opening or closing car electric windows +tests/VGGSound/video/3fx2rF3lDUo_000014.mp4 smoke detector beeping +tests/VGGSound/video/9L21uB0nyq0_000024.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/9L2apEHg93I_000028.mp4 people gargling +tests/VGGSound/video/3g3cr1rw3HU_000105.mp4 train whistling +tests/VGGSound/video/9LCxd1wjCQk_000276.mp4 turkey gobbling +tests/VGGSound/video/3gCD4JFbxuo_000090.mp4 baby laughter +tests/VGGSound/video/3gLaidU3lHs_000027.mp4 playing oboe +tests/VGGSound/video/3gR0QBgrzYQ_000020.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/3gjFMkV2ucY_000030.mp4 playing accordion +tests/VGGSound/video/3h-cSxTTU3o_000182.mp4 smoke detector beeping +tests/VGGSound/video/3h1-zP8M-yU_000020.mp4 playing shofar +tests/VGGSound/video/9M3XChzFowA_000038.mp4 air horn +tests/VGGSound/video/3hEgl8N2FBA_000210.mp4 cattle mooing +tests/VGGSound/video/9MT7lQN7fN0_000085.mp4 tractor digging 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+tests/VGGSound/video/9P6-DKN1XLA_000320.mp4 ambulance siren +tests/VGGSound/video/9PEyCM-BrG4_000024.mp4 hedge trimmer running +tests/VGGSound/video/3juGfzF29Sc_000140.mp4 playing vibraphone +tests/VGGSound/video/9PdzaYwgQBE_000030.mp4 pumping water +tests/VGGSound/video/9PmzQI8ZYpg_000030.mp4 using sewing machines +tests/VGGSound/video/3k8zGf8Btfo_000250.mp4 playing drum kit +tests/VGGSound/video/3kDi5Hk-Vmw_000030.mp4 playing accordion +tests/VGGSound/video/9QEm6u4bowQ_000030.mp4 playing electric guitar +tests/VGGSound/video/3kFl_TY3iUg_000000.mp4 cheetah chirrup +tests/VGGSound/video/9QIxNSbVBuc_000058.mp4 fox barking +tests/VGGSound/video/3kSQNjfJnN8_000210.mp4 playing theremin +tests/VGGSound/video/3kaCL9Zu7NY_000230.mp4 playing zither +tests/VGGSound/video/9QjGgc1UkkU_000044.mp4 playing congas +tests/VGGSound/video/9QjGgc1UkkU_000105.mp4 playing congas +tests/VGGSound/video/3kx-UhywUf0_000020.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/9QwaP-cvdeU_000360.mp4 skateboarding +tests/VGGSound/video/9QzT2cdoTzc_000124.mp4 strike lighter +tests/VGGSound/video/9QzTS3fW9Fc_000088.mp4 playing tambourine +tests/VGGSound/video/9R4qwSl7u2A_000480.mp4 turkey gobbling +tests/VGGSound/video/9R6XN9-Z27U_000030.mp4 goat bleating +tests/VGGSound/video/9RB54_fJZyw_000030.mp4 playing bagpipes +tests/VGGSound/video/9RNNZ3e-9IA_000028.mp4 dog barking +tests/VGGSound/video/9RNvMneZR7U_000326.mp4 striking bowling +tests/VGGSound/video/9RNvMneZR7U_000697.mp4 striking bowling +tests/VGGSound/video/9Rbte5hjob8_000100.mp4 playing cornet +tests/VGGSound/video/3lkI_scF2eU_000130.mp4 chainsawing trees +tests/VGGSound/video/9RisgTyd5aA_000138.mp4 people cheering +tests/VGGSound/video/3m6g0rfn2T0_000136.mp4 lathe spinning +tests/VGGSound/video/3mCWARDySc8_000059.mp4 playing violin, fiddle +tests/VGGSound/video/3mDPQ_CPopw_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/3mENYq_Ta3s_000012.mp4 people booing +tests/VGGSound/video/9S69B4UvI-M_000000.mp4 playing cymbal +tests/VGGSound/video/9STauy5DsC8_000030.mp4 rapping +tests/VGGSound/video/9SVbr69L7wM_000060.mp4 waterfall burbling +tests/VGGSound/video/3mkiTkMVemM_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/9SZC5O-gwAI_000263.mp4 whale calling +tests/VGGSound/video/3mtdpXbogzk_000180.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/9Srnaag2tCo_000079.mp4 playing violin, fiddle +tests/VGGSound/video/3nQ-LsDU9_M_000157.mp4 playing snare drum +tests/VGGSound/video/9THW8yB2ElE_000047.mp4 air horn +tests/VGGSound/video/3njuN-F2Ecs_000332.mp4 playing washboard +tests/VGGSound/video/9Ti98L4PRCo_000017.mp4 reversing beeps +tests/VGGSound/video/9TkW1M_ZRr0_000030.mp4 rapping +tests/VGGSound/video/3oF5wexQq_Q_000070.mp4 people hiccup +tests/VGGSound/video/3oGWyWYbFyk_000006.mp4 elk bugling +tests/VGGSound/video/9TzyRdTYDvo_000024.mp4 dog growling +tests/VGGSound/video/3oYSlw6l0XA_000380.mp4 typing on computer keyboard +tests/VGGSound/video/3oaky81Equ8_000016.mp4 electric grinder grinding +tests/VGGSound/video/3oaky81Equ8_000045.mp4 electric grinder grinding +tests/VGGSound/video/3od9aUtrcz4_000040.mp4 playing saxophone +tests/VGGSound/video/3oef68YabD0_000002.mp4 male speech, man speaking +tests/VGGSound/video/3ogvpIfTlhY_000000.mp4 hail +tests/VGGSound/video/3ogvpIfTlhY_000029.mp4 hail +tests/VGGSound/video/3otUlQ4wvLY_000030.mp4 male singing +tests/VGGSound/video/3p3A4QDXw-g_000030.mp4 male singing +tests/VGGSound/video/3pV7d32BfBQ_000050.mp4 lions roaring +tests/VGGSound/video/9VLCK2iTxhY_000240.mp4 pumping water +tests/VGGSound/video/9VMXgZ4ihTM_000138.mp4 footsteps on snow +tests/VGGSound/video/3posAjJWEi4_000400.mp4 splashing water +tests/VGGSound/video/9Vg_aX3jhjU_000020.mp4 civil defense siren +tests/VGGSound/video/9Vj1UPzlrTc_000030.mp4 playing harpsichord +tests/VGGSound/video/3ptxRyVuU0w_000520.mp4 machine gun shooting +tests/VGGSound/video/9W1W43n9-3g_000037.mp4 cutting hair with electric trimmers +tests/VGGSound/video/9W4cZpE6tH8_000037.mp4 forging swords +tests/VGGSound/video/3qEb6Y-D7Mw_000050.mp4 child speech, kid speaking +tests/VGGSound/video/9WClEjrr_RA_000027.mp4 mynah bird singing +tests/VGGSound/video/3qKgKd6B5E0_000147.mp4 cat purring +tests/VGGSound/video/9WWZUjBE5HA_000079.mp4 striking pool +tests/VGGSound/video/9WWZUjBE5HA_000183.mp4 striking pool +tests/VGGSound/video/9WXz_4FvZCw_000069.mp4 canary calling +tests/VGGSound/video/3qO4P2X-oHU_000063.mp4 cheetah chirrup +tests/VGGSound/video/3qPefjNIBok_000030.mp4 goat bleating +tests/VGGSound/video/3qe9RK3sMBs_000000.mp4 basketball bounce +tests/VGGSound/video/3qesirWAGt4_000020.mp4 dog barking +tests/VGGSound/video/9WtDINM2mNc_000237.mp4 car engine idling +tests/VGGSound/video/9WtK0gh4ugE_000030.mp4 ambulance siren +tests/VGGSound/video/3qtnbifHKXU_000064.mp4 playing tuning fork +tests/VGGSound/video/9XHRHFTY0iU_000409.mp4 people cheering +tests/VGGSound/video/9XHRHFTY0iU_000480.mp4 people cheering +tests/VGGSound/video/3rOi5Gd0LLY_000250.mp4 splashing water +tests/VGGSound/video/9XfmOHbHniE_000003.mp4 snake rattling +tests/VGGSound/video/9XfmOHbHniE_000018.mp4 snake rattling +tests/VGGSound/video/9Xiu4xzzurQ_000023.mp4 train wheels squealing +tests/VGGSound/video/3rn-tCQafl8_000030.mp4 dog bow-wow +tests/VGGSound/video/9XuTWG0Svls_000041.mp4 popping popcorn +tests/VGGSound/video/9Y1bZa7Arj8_000000.mp4 bowling impact +tests/VGGSound/video/9Y8NR6nDxjk_000460.mp4 playing timpani +tests/VGGSound/video/3sBIRZReSC0_000044.mp4 police radio chatter +tests/VGGSound/video/3sDUymEIwJw_000029.mp4 eletric blender running +tests/VGGSound/video/9YSvwsbk9Dw_000040.mp4 waterfall burbling +tests/VGGSound/video/3sQrJVyxju0_000065.mp4 playing mandolin +tests/VGGSound/video/3sRO6iwfUxo_000030.mp4 rapping +tests/VGGSound/video/3sYnYraOuIo_000510.mp4 fireworks banging +tests/VGGSound/video/9YeN0TWM6xo_000033.mp4 firing muskets +tests/VGGSound/video/3sflCnetnS0_000030.mp4 car engine knocking +tests/VGGSound/video/3sz7nQTcwcE_000009.mp4 dog growling +tests/VGGSound/video/3t6pqBKV0kY_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/9ZBaKqh-Bmk_000027.mp4 alligators, crocodiles hissing +tests/VGGSound/video/9ZBaKqh-Bmk_000131.mp4 alligators, crocodiles hissing +tests/VGGSound/video/9ZCHzzCh5nk_000030.mp4 playing cello +tests/VGGSound/video/9ZClVJ2V7bA_000022.mp4 telephone bell ringing +tests/VGGSound/video/3tK7PpCo0PQ_000080.mp4 male singing +tests/VGGSound/video/3tSPMzvuQpk_000030.mp4 male singing +tests/VGGSound/video/9ZWmZdgrE78_000080.mp4 playing mandolin +tests/VGGSound/video/9ZYj5toEbGA_000000.mp4 skateboarding +tests/VGGSound/video/3tbFP_JKzXw_000030.mp4 playing sitar +tests/VGGSound/video/3twm2ErD0kM_000154.mp4 playing cornet +tests/VGGSound/video/9_6Sx2Oqq7E_000376.mp4 dinosaurs bellowing +tests/VGGSound/video/9_L9CXHPd9M_000100.mp4 sailing +tests/VGGSound/video/3uHd7_jU2gE_000031.mp4 wind noise +tests/VGGSound/video/9_eXYyA8N18_000530.mp4 child speech, kid speaking +tests/VGGSound/video/3uLeK7Lr6W8_000007.mp4 wind chime +tests/VGGSound/video/3uLmjElob2Q_000004.mp4 cuckoo bird calling +tests/VGGSound/video/9a3zqFrIeGI_000076.mp4 swimming +tests/VGGSound/video/9aK2LBnTT2s_000030.mp4 skidding +tests/VGGSound/video/3uuyQ4O0L68_000030.mp4 playing french horn +tests/VGGSound/video/9aR-uBVtrVA_000010.mp4 lions roaring +tests/VGGSound/video/3uz_ZrGsIaA_000030.mp4 playing electric guitar +tests/VGGSound/video/3v1pMz1N5RU_000030.mp4 singing choir +tests/VGGSound/video/9ao6stS2toU_000003.mp4 cat caterwauling +tests/VGGSound/video/3vDDWN5GKAA_000139.mp4 playing snare drum +tests/VGGSound/video/3vLc6D64xcs_000330.mp4 using sewing machines +tests/VGGSound/video/9b3P0ERIZ-c_000001.mp4 ice cream truck, ice cream van +tests/VGGSound/video/9b3P0ERIZ-c_000053.mp4 ice cream truck, ice cream van +tests/VGGSound/video/3vp3XshIuSI_000017.mp4 playing bassoon +tests/VGGSound/video/3vp3XshIuSI_000189.mp4 playing bassoon +tests/VGGSound/video/3vpG1PgFF34_000030.mp4 playing harpsichord +tests/VGGSound/video/3vpNLYc0YN4_000110.mp4 playing french horn +tests/VGGSound/video/9bQDhTTpkiQ_000176.mp4 playing snare drum +tests/VGGSound/video/3w4nFQrUQ8k_000020.mp4 playing timpani +tests/VGGSound/video/9bcic5mk4xc_000147.mp4 shot football +tests/VGGSound/video/3wWw2WDsHY8_000080.mp4 foghorn +tests/VGGSound/video/9c9dRz8t4bI_000152.mp4 electric grinder grinding +tests/VGGSound/video/9cYVBOJmXIw_000030.mp4 male speech, man speaking +tests/VGGSound/video/3xDZU7GME7E_000170.mp4 lighting firecrackers +tests/VGGSound/video/9crt3kBm2Hc_000012.mp4 female speech, woman speaking +tests/VGGSound/video/3xW9NcPDSCk_000223.mp4 people eating noodle +tests/VGGSound/video/3xh2kScw64U_000030.mp4 reversing beeps +tests/VGGSound/video/9dQZetLWxwg_000075.mp4 dog baying +tests/VGGSound/video/9dU2y2b_LBg_000380.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/3y4xVx5yY_E_000213.mp4 playing hockey +tests/VGGSound/video/3yCaMM8can0_000100.mp4 playing harmonica +tests/VGGSound/video/9dttk1IPs3o_000597.mp4 playing bassoon +tests/VGGSound/video/9e6oA02wk94_000020.mp4 singing bowl +tests/VGGSound/video/3ymgPYkdSIg_000040.mp4 mosquito buzzing +tests/VGGSound/video/3ypSlMWAZeo_000239.mp4 people marching +tests/VGGSound/video/3yt8xEb1VXA_000200.mp4 raining +tests/VGGSound/video/9eUl4gF0ED4_000002.mp4 male speech, man speaking +tests/VGGSound/video/9ezA12O_aOE_000170.mp4 fire truck siren +tests/VGGSound/video/3zIQTDfS4Hk_000030.mp4 playing steelpan +tests/VGGSound/video/3zQPWg-F8Xk_000030.mp4 male singing +tests/VGGSound/video/3zRatdumh0M_000090.mp4 playing trumpet +tests/VGGSound/video/9fMBtDjXvcg_000011.mp4 blowtorch igniting +tests/VGGSound/video/3zcm-TZ5s1Y_000377.mp4 metronome +tests/VGGSound/video/9fS92peHJh0_000002.mp4 people humming +tests/VGGSound/video/9fWNP6yAgrU_000003.mp4 woodpecker pecking tree +tests/VGGSound/video/4--05CAaDsg_000460.mp4 splashing water +tests/VGGSound/video/4-DcTjFR4qw_000100.mp4 car passing by +tests/VGGSound/video/4-SlE4qtKvw_000222.mp4 fox barking +tests/VGGSound/video/4-SlE4qtKvw_000239.mp4 fox barking +tests/VGGSound/video/9gCeNCnWZhE_000030.mp4 wind rustling leaves +tests/VGGSound/video/9gK1Nqqsy6o_000160.mp4 playing harp +tests/VGGSound/video/4-X3c59e3Hk_000053.mp4 airplane flyby +tests/VGGSound/video/9gLVI1d6XtU_000112.mp4 planing timber +tests/VGGSound/video/9ge5GwYO-pU_000016.mp4 rope skipping +tests/VGGSound/video/4-uPbaefZGs_000010.mp4 lathe spinning +tests/VGGSound/video/9gp9FpidesQ_000030.mp4 car engine starting +tests/VGGSound/video/9grtLEqt_RM_000330.mp4 people belly laughing +tests/VGGSound/video/40AD_oH9eCU_000030.mp4 child speech, kid speaking +tests/VGGSound/video/40CVvVDVWVM_000051.mp4 ferret dooking +tests/VGGSound/video/9h3a7fN0f-c_000240.mp4 people coughing +tests/VGGSound/video/40fIOkLK3j4_000060.mp4 people coughing +tests/VGGSound/video/40s88hEcn5I_000170.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/40sAH2ZB0Pg_000030.mp4 playing banjo +tests/VGGSound/video/41-B5Y2iF9A_000023.mp4 pheasant crowing +tests/VGGSound/video/9i3NIA1NLeY_000060.mp4 playing harpsichord +tests/VGGSound/video/9iVLuQ403ww_000039.mp4 slot machine +tests/VGGSound/video/9ipjwnbdxmg_000120.mp4 coyote howling +tests/VGGSound/video/9ivV2chJLa4_000030.mp4 playing french horn +tests/VGGSound/video/9j-M5q5uSr8_000140.mp4 female speech, woman speaking +tests/VGGSound/video/421CRF4HFlA_000140.mp4 playing harpsichord +tests/VGGSound/video/42CPymJ_MXI_000060.mp4 people crowd +tests/VGGSound/video/9jVVZ1Y9Alc_000134.mp4 ferret dooking +tests/VGGSound/video/42QgE4mM55I_000030.mp4 male singing +tests/VGGSound/video/9j_FItO0jt8_000030.mp4 cricket chirping +tests/VGGSound/video/42v1BJvU4OA_000354.mp4 running electric fan +tests/VGGSound/video/42vB40Fkdis_000076.mp4 airplane flyby +tests/VGGSound/video/9jrTswHdg4I_000290.mp4 hair dryer drying +tests/VGGSound/video/43R5uK6JJoA_000030.mp4 wind rustling leaves +tests/VGGSound/video/9kFZhnbKUXo_000030.mp4 people belly laughing +tests/VGGSound/video/9kIBkY7Tj5g_000000.mp4 civil defense siren +tests/VGGSound/video/9koUQIbosEg_000259.mp4 car engine idling +tests/VGGSound/video/446etGsnI_E_000030.mp4 cat meowing +tests/VGGSound/video/9l0ZJENyWq0_000010.mp4 wind rustling leaves +tests/VGGSound/video/448X3t13rlk_000325.mp4 driving snowmobile +tests/VGGSound/video/44Nt8WOHyyU_000040.mp4 playing accordion +tests/VGGSound/video/9lKIoqoJy0M_000030.mp4 baby babbling +tests/VGGSound/video/44Wc6OPLcIU_000000.mp4 coyote howling +tests/VGGSound/video/9lkeWpzWNDM_000080.mp4 pumping water +tests/VGGSound/video/9lrhuW6aatg_000000.mp4 barn swallow calling +tests/VGGSound/video/9m1FFbsR704_000127.mp4 playing guiro +tests/VGGSound/video/9mEfikl6mAM_000029.mp4 chimpanzee pant-hooting +tests/VGGSound/video/44wxFq7DWFg_000612.mp4 playing hockey +tests/VGGSound/video/9mIDP_OT1uM_000030.mp4 door slamming +tests/VGGSound/video/45IkbUGPyzQ_000311.mp4 playing darts +tests/VGGSound/video/45JHcLU57B8_000020.mp4 driving motorcycle +tests/VGGSound/video/9mu6h8pTooE_000030.mp4 horse clip-clop +tests/VGGSound/video/9n5G0qFBsHM_000000.mp4 ocean burbling +tests/VGGSound/video/45h1cMSHzYU_000110.mp4 male speech, man speaking +tests/VGGSound/video/45vBbOhzS6g_000050.mp4 people screaming +tests/VGGSound/video/9nL1XhKm9q8_000030.mp4 pumping water +tests/VGGSound/video/9nNBz3phufo_000040.mp4 eating with cutlery +tests/VGGSound/video/461QChXkDlA_000029.mp4 running electric fan +tests/VGGSound/video/466XkuormNQ_000030.mp4 playing harpsichord +tests/VGGSound/video/9nVNtRGU-rg_000270.mp4 lighting firecrackers +tests/VGGSound/video/9nmXhr76EkI_000230.mp4 playing table tennis +tests/VGGSound/video/9nsLTLNvOSw_000150.mp4 helicopter +tests/VGGSound/video/46T9h0qV75g_000088.mp4 roller coaster running +tests/VGGSound/video/9nxDHhDpJUk_000065.mp4 cuckoo bird calling +tests/VGGSound/video/46gkmd8hhYo_000125.mp4 playing volleyball +tests/VGGSound/video/46t-4NFQ9_w_000002.mp4 cat meowing +tests/VGGSound/video/46zbt7TQHRs_000000.mp4 chicken crowing +tests/VGGSound/video/9oeGmqm6g8E_000080.mp4 railroad car, train wagon +tests/VGGSound/video/9ofZp-R3BlY_000021.mp4 squishing water +tests/VGGSound/video/9omaijBLqrg_000060.mp4 playing guiro +tests/VGGSound/video/476vNb6thyM_000030.mp4 playing acoustic guitar +tests/VGGSound/video/9ooTD5lVkM0_000164.mp4 yodelling +tests/VGGSound/video/9p9Lg1SqJpg_000110.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/47mYYtNAp_4_000000.mp4 elephant trumpeting +tests/VGGSound/video/9pfZ4sXXsE4_000330.mp4 chicken crowing +tests/VGGSound/video/9pgSPM4_wjM_000540.mp4 playing timpani +tests/VGGSound/video/9ppa4lXXspA_000030.mp4 dog barking +tests/VGGSound/video/9q3JJ7Fhvbs_000070.mp4 playing electronic organ +tests/VGGSound/video/9q8N_KgH8SI_000250.mp4 eating with cutlery +tests/VGGSound/video/48HhCnV2U7s_000432.mp4 spraying water +tests/VGGSound/video/48Jgt4igVEI_000021.mp4 sailing +tests/VGGSound/video/9qwtgSVzalo_000223.mp4 chopping food +tests/VGGSound/video/9r7v3hhUtY4_000004.mp4 bathroom ventilation fan running +tests/VGGSound/video/48zE-hRAYEA_000030.mp4 machine gun shooting +tests/VGGSound/video/9rXAmXuAOw8_000000.mp4 crow cawing +tests/VGGSound/video/492jB4DXETM_000240.mp4 bird chirping, tweeting +tests/VGGSound/video/495u-1lHHSc_000002.mp4 sailing +tests/VGGSound/video/495u-1lHHSc_000228.mp4 sailing +tests/VGGSound/video/498ynMnZ6Lo_000030.mp4 door slamming +tests/VGGSound/video/9rw3qz2ouRQ_000290.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/49PCE6AXrGw_000030.mp4 cow lowing +tests/VGGSound/video/9s26XGoKYG0_000250.mp4 playing harpsichord +tests/VGGSound/video/9s8jDGsBij4_000010.mp4 people sniggering +tests/VGGSound/video/49WpWcOnPs4_000200.mp4 church bell ringing +tests/VGGSound/video/9sJU5MALkgg_000068.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/9skENGpT1_8_000000.mp4 ice cream truck, ice cream van +tests/VGGSound/video/9sxNlZsWmS0_000009.mp4 coyote howling +tests/VGGSound/video/9t0s8TUHMiM_000020.mp4 snake hissing +tests/VGGSound/video/9tBOegUHrL0_000080.mp4 playing bass drum +tests/VGGSound/video/9tDqkjQLtNM_000096.mp4 train wheels squealing +tests/VGGSound/video/9tLzTdRhTrI_000180.mp4 playing theremin +tests/VGGSound/video/9u2eYruI2CY_000076.mp4 roller coaster running +tests/VGGSound/video/9u9Zgbbngkg_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/9uOOfuRD6Fc_000070.mp4 railroad car, train wagon +tests/VGGSound/video/9uSTEQy8DKg_000030.mp4 duck quacking +tests/VGGSound/video/9uTzThSwQ80_000580.mp4 railroad car, train wagon +tests/VGGSound/video/9uj350nZ-D4_000000.mp4 zebra braying +tests/VGGSound/video/9uj350nZ-D4_000010.mp4 zebra braying +tests/VGGSound/video/9uwWavcx0E4_000000.mp4 bowling impact +tests/VGGSound/video/9vDOSz1KxrQ_000169.mp4 electric grinder grinding +tests/VGGSound/video/9wMeb3Q-IiQ_000030.mp4 chicken crowing +tests/VGGSound/video/9wUl5xHWcfc_000028.mp4 people nose blowing +tests/VGGSound/video/9wW-losmGws_000030.mp4 playing washboard +tests/VGGSound/video/9wW-losmGws_000097.mp4 playing washboard +tests/VGGSound/video/9wkgTdE7nz8_000030.mp4 male speech, man speaking +tests/VGGSound/video/9xV0nmojVeg_000030.mp4 playing acoustic guitar +tests/VGGSound/video/9xvmNaF73fo_000030.mp4 child speech, kid speaking +tests/VGGSound/video/9y2BI6yaNkA_000114.mp4 smoke detector beeping +tests/VGGSound/video/9ytPHkPCXgA_000050.mp4 playing tambourine +tests/VGGSound/video/9z5fd1F20sw_000024.mp4 people eating crisps +tests/VGGSound/video/9zPrLhdmgpg_000031.mp4 slot machine +tests/VGGSound/video/9zW-E0XdWdw_000160.mp4 female singing +tests/VGGSound/video/9zWMaAO5U3k_000105.mp4 donkey, ass braying +tests/VGGSound/video/9zeZEa45Wd0_000010.mp4 splashing water +tests/VGGSound/video/A-AoGf9gIW8_000521.mp4 people battle cry +tests/VGGSound/video/A-IzSI1ysmc_000030.mp4 ambulance siren +tests/VGGSound/video/A-Mg-FwSkiU_000030.mp4 stream burbling +tests/VGGSound/video/A-OZ4_eEMRo_000150.mp4 machine gun shooting +tests/VGGSound/video/A-QYRlK7cd8_000030.mp4 raining +tests/VGGSound/video/A-YKT8XB0xg_000000.mp4 people farting +tests/VGGSound/video/A-gtqqzNIck_000039.mp4 tornado roaring +tests/VGGSound/video/A-odqVz9Oc4_000001.mp4 dog growling +tests/VGGSound/video/A-xnMFhk62M_000110.mp4 playing marimba, xylophone +tests/VGGSound/video/A0Jgjdcys6U_000084.mp4 skiing +tests/VGGSound/video/A0dHhG6Y8C0_000030.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/A0hl8W3RF5c_000000.mp4 train horning +tests/VGGSound/video/A1E-agNyE2U_000172.mp4 rope skipping +tests/VGGSound/video/A1qKwuz07ss_000030.mp4 playing tabla +tests/VGGSound/video/A1vkiLZfAMs_000030.mp4 playing clarinet +tests/VGGSound/video/A24InXJHgOk_000028.mp4 playing trumpet +tests/VGGSound/video/A2D_eaALRug_000019.mp4 hammering nails +tests/VGGSound/video/A2D_eaALRug_000144.mp4 hammering nails +tests/VGGSound/video/A2PfJsLueeg_000203.mp4 playing tuning fork +tests/VGGSound/video/A3CJkhyupM0_000010.mp4 police car (siren) +tests/VGGSound/video/A3PZs1dPMgY_000110.mp4 dog growling +tests/VGGSound/video/A43JOxLa5MM_000023.mp4 chicken clucking +tests/VGGSound/video/A458iJLZGvg_000080.mp4 child speech, kid speaking +tests/VGGSound/video/A4P0IgZQf90_000136.mp4 people slurping +tests/VGGSound/video/A4a5VD-hmz4_000016.mp4 people marching +tests/VGGSound/video/A4jzYzlzgC4_000009.mp4 cell phone buzzing +tests/VGGSound/video/CxSALNdzjKs_000096.mp4 blowtorch igniting +tests/VGGSound/video/CxSALNdzjKs_000125.mp4 blowtorch igniting +tests/VGGSound/video/A58jDX8MIbs_000020.mp4 stream burbling +tests/VGGSound/video/A58nnmnhfUo_000001.mp4 chicken crowing +tests/VGGSound/video/CyKt86nLh-Y_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/A5RP_P_aFsk_000010.mp4 playing vibraphone +tests/VGGSound/video/CyQ5KpFI5A4_000030.mp4 typing on typewriter +tests/VGGSound/video/A5lX7rsPIDw_000300.mp4 playing acoustic guitar +tests/VGGSound/video/A5pf6D1ZYi4_000030.mp4 horse neighing +tests/VGGSound/video/A68tYY9AA9Q_000030.mp4 helicopter +tests/VGGSound/video/A69_hm6mMrU_000023.mp4 playing volleyball +tests/VGGSound/video/A6PMpITUNMs_000133.mp4 children shouting +tests/VGGSound/video/A6PMpITUNMs_000180.mp4 children shouting +tests/VGGSound/video/A6T7Pu4pL1M_000030.mp4 singing choir +tests/VGGSound/video/A6_-Ji7bq5E_000337.mp4 people slurping +tests/VGGSound/video/A6_Rikjub4o_000032.mp4 people battle cry +tests/VGGSound/video/CzhsbdoRfr0_000330.mp4 playing harpsichord +tests/VGGSound/video/A6p86Kp6tDE_000030.mp4 raining +tests/VGGSound/video/D-7c7OP4dFg_000051.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/D-A7agR6y4w_000110.mp4 playing drum kit +tests/VGGSound/video/A7DQjMwCtI8_000270.mp4 car passing by +tests/VGGSound/video/A7Q9tTUxNO8_000189.mp4 tornado roaring +tests/VGGSound/video/D-TltLbYiDU_000001.mp4 volcano explosion +tests/VGGSound/video/A7SolJSMhEI_000034.mp4 ice cream truck, ice cream van +tests/VGGSound/video/A7jC_5YqD5k_000018.mp4 mouse squeaking +tests/VGGSound/video/A7jMX_jLeQc_000127.mp4 people battle cry +tests/VGGSound/video/D-p9s8y2z_U_000000.mp4 playing acoustic guitar +tests/VGGSound/video/A7o-wmriwc8_000007.mp4 wood thrush calling +tests/VGGSound/video/A7pW5W-4snM_000150.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/D05-MrPXqjw_000030.mp4 fire truck siren +tests/VGGSound/video/A8L0mC1_Geg_000400.mp4 bird wings flapping +tests/VGGSound/video/D0L-M4trkpw_000210.mp4 playing electric guitar +tests/VGGSound/video/D0Vk5yjzXB0_000017.mp4 magpie calling +tests/VGGSound/video/D0c3UEE4RXk_000030.mp4 sloshing water +tests/VGGSound/video/A8gbOIvxvMA_000030.mp4 playing cello +tests/VGGSound/video/A8rklgn3N4A_000028.mp4 cat growling +tests/VGGSound/video/D10TL67RDVE_000257.mp4 scuba diving +tests/VGGSound/video/A91s78YZt-Y_000010.mp4 people farting +tests/VGGSound/video/D1Ck6nksu8s_000030.mp4 playing bagpipes +tests/VGGSound/video/D1Grrka9WdA_000060.mp4 playing timbales +tests/VGGSound/video/D1KdCkSFmnk_000000.mp4 people shuffling +tests/VGGSound/video/D1NDNFZGY7k_000040.mp4 playing cymbal +tests/VGGSound/video/D1NO38P8vqI_000284.mp4 playing bongo +tests/VGGSound/video/A9JSptUG5HU_000020.mp4 black capped chickadee calling +tests/VGGSound/video/A9KMqwqLboE_000030.mp4 reversing beeps +tests/VGGSound/video/A9LkQyImgNI_000030.mp4 playing cello +tests/VGGSound/video/D1VQAb8CfWM_000008.mp4 cat hissing +tests/VGGSound/video/D1VQAb8CfWM_000022.mp4 cat hissing +tests/VGGSound/video/D1eDJb5FMw0_000065.mp4 dog growling +tests/VGGSound/video/D1tajOObltQ_000015.mp4 fire truck siren +tests/VGGSound/video/D1tl1eS7ubI_000000.mp4 female speech, woman speaking +tests/VGGSound/video/D1tzSCqOGV4_000080.mp4 playing double bass +tests/VGGSound/video/A9n6gH2uS5U_000019.mp4 cat growling +tests/VGGSound/video/D2ISzNuhtxE_000009.mp4 cat caterwauling +tests/VGGSound/video/D2IvCQMkGWk_000055.mp4 tractor digging +tests/VGGSound/video/D2KrgDuU3K8_000100.mp4 bird chirping, tweeting +tests/VGGSound/video/AA0Ekw6dlQo_000046.mp4 playing oboe +tests/VGGSound/video/AA0N8XMqx9s_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/AABgGgkXH94_000030.mp4 female speech, woman speaking +tests/VGGSound/video/D30UC-C-lIs_000029.mp4 blowtorch igniting +tests/VGGSound/video/AAHybONa3n4_000150.mp4 dinosaurs bellowing +tests/VGGSound/video/D39kBvBeVJs_000048.mp4 cupboard opening or closing +tests/VGGSound/video/D3BJuOwltoI_000010.mp4 driving motorcycle +tests/VGGSound/video/D3FV0JAngZ4_000210.mp4 playing acoustic guitar +tests/VGGSound/video/AAWe4zRLVVU_000030.mp4 playing timpani +tests/VGGSound/video/D3TlQdOZZB8_000030.mp4 singing choir +tests/VGGSound/video/AA_XVhso6IU_000244.mp4 playing violin, fiddle +tests/VGGSound/video/AAdciXShS1c_000019.mp4 parrot talking +tests/VGGSound/video/D3ZsXH8yrh0_000000.mp4 electric grinder grinding +tests/VGGSound/video/AAyqgdDOUYA_000020.mp4 fire truck siren +tests/VGGSound/video/AB--KnXO_0c_000030.mp4 playing gong +tests/VGGSound/video/ABCUrbSmLuo_000030.mp4 baby crying +tests/VGGSound/video/ABH4iCT5Iik_000030.mp4 singing choir +tests/VGGSound/video/ABL8jtrfZ3E_000167.mp4 playing tuning fork +tests/VGGSound/video/ABNmO9SewG8_000030.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/D4Jb8jIl-2A_000378.mp4 lip smacking +tests/VGGSound/video/D4diwZCLvl0_000043.mp4 playing bongo +tests/VGGSound/video/ABf_0EVfFR0_000040.mp4 mosquito buzzing +tests/VGGSound/video/ABs3qGwvW-U_000020.mp4 basketball bounce +tests/VGGSound/video/D5-jwFJXn1U_000182.mp4 cupboard opening or closing +tests/VGGSound/video/AC4ITIdiccw_000030.mp4 playing clarinet +tests/VGGSound/video/D5Zi0Mfo0Ts_000048.mp4 electric grinder grinding +tests/VGGSound/video/ACIG-myn6uA_000106.mp4 dinosaurs bellowing +tests/VGGSound/video/ACWNRYsyMGk_000030.mp4 people finger snapping +tests/VGGSound/video/ACjLm_tKyu8_000060.mp4 electric grinder grinding +tests/VGGSound/video/D668Jl6zuAk_000190.mp4 child speech, kid speaking +tests/VGGSound/video/AD9ajeVpxxU_000266.mp4 playing bugle +tests/VGGSound/video/D6VGsQPmhLU_000030.mp4 typing on computer keyboard +tests/VGGSound/video/D6shA0yJ8W4_000061.mp4 fly, housefly buzzing +tests/VGGSound/video/D6shA0yJ8W4_000072.mp4 fly, housefly buzzing +tests/VGGSound/video/D6zJCzkFVRQ_000030.mp4 playing cello +tests/VGGSound/video/ADjyDcauxzM_000030.mp4 dog growling +tests/VGGSound/video/D7BhU7lUtiE_000140.mp4 playing zither +tests/VGGSound/video/ADtA2TMXVvo_000042.mp4 playing cornet +tests/VGGSound/video/ADtA2TMXVvo_000092.mp4 playing cornet +tests/VGGSound/video/D7TB8b2t3QE_000530.mp4 people clapping +tests/VGGSound/video/AENNoAeote8_000059.mp4 children shouting +tests/VGGSound/video/D7cJVCMB7u8_000030.mp4 people clapping +tests/VGGSound/video/D7iyQCgox0g_000017.mp4 chipmunk chirping +tests/VGGSound/video/D7sYo1XWj5Y_000036.mp4 playing volleyball +tests/VGGSound/video/D7xcDFonDF8_000678.mp4 telephone bell ringing +tests/VGGSound/video/D7z57SPBpaU_000044.mp4 volcano explosion +tests/VGGSound/video/AEwkS57P4eE_000030.mp4 male singing +tests/VGGSound/video/AEwl00_Vv9s_000052.mp4 gibbon howling +tests/VGGSound/video/D8BQyUNbIps_000116.mp4 running electric fan +tests/VGGSound/video/AF0CtMb81t8_000030.mp4 dog barking +tests/VGGSound/video/D8G6YuWL230_000030.mp4 firing cannon +tests/VGGSound/video/D8LW5sTsIlc_000030.mp4 printer printing +tests/VGGSound/video/AF7OSOdwhG8_000311.mp4 tornado roaring +tests/VGGSound/video/AF7sah5a_DE_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/D8R-u0sG5eg_000009.mp4 people finger snapping +tests/VGGSound/video/AFACjpDiMSQ_000041.mp4 chipmunk chirping +tests/VGGSound/video/AFACjpDiMSQ_000062.mp4 chipmunk chirping +tests/VGGSound/video/AFGcqc-gfiw_000030.mp4 printer printing +tests/VGGSound/video/AFJN5sQt1ec_000030.mp4 singing choir +tests/VGGSound/video/D8l4-MXkCZQ_000019.mp4 people farting +tests/VGGSound/video/D8uaczGW2RE_000011.mp4 sea lion barking +tests/VGGSound/video/D8vA5rdtYd8_000030.mp4 playing accordion +tests/VGGSound/video/AFgdcQqt3PY_000010.mp4 cat growling +tests/VGGSound/video/AFwmMFq_xlc_000390.mp4 reversing beeps +tests/VGGSound/video/AFwtBviVhhM_000030.mp4 playing electric guitar +tests/VGGSound/video/AG2YTG36nYg_000504.mp4 scuba diving +tests/VGGSound/video/D9ag3OB7E4k_000000.mp4 snake hissing +tests/VGGSound/video/AG7Zm7D4JIE_000030.mp4 mouse squeaking +tests/VGGSound/video/AGA3hiGZJCo_000000.mp4 helicopter +tests/VGGSound/video/AGDQXlgdzhA_000285.mp4 sheep bleating +tests/VGGSound/video/D9qpDjafWRM_000030.mp4 playing flute +tests/VGGSound/video/D9yNCDer4YM_000094.mp4 electric grinder grinding +tests/VGGSound/video/DA-XLk-aikM_000776.mp4 bouncing on trampoline +tests/VGGSound/video/AGTyP86x_Sc_000110.mp4 people crowd +tests/VGGSound/video/DA2QCyip6mY_000618.mp4 forging swords +tests/VGGSound/video/AGoxtfIvAmo_000152.mp4 ripping paper +tests/VGGSound/video/AHIV0RMwnN8_000150.mp4 tap dancing +tests/VGGSound/video/AHIV0RMwnN8_000210.mp4 tap dancing +tests/VGGSound/video/DAPGvg8qOAU_000000.mp4 playing mandolin +tests/VGGSound/video/AHIiNsAzgKo_000024.mp4 eagle screaming +tests/VGGSound/video/DAQGE0SNs6g_000108.mp4 dinosaurs bellowing +tests/VGGSound/video/AHPRhJ4u0ss_000027.mp4 duck quacking +tests/VGGSound/video/DAbcAA6XbfE_000117.mp4 playing lacrosse +tests/VGGSound/video/DAbcAA6XbfE_000168.mp4 playing lacrosse +tests/VGGSound/video/AHoWincIkzc_000030.mp4 people clapping +tests/VGGSound/video/AHom7lBbtoY_000030.mp4 train horning +tests/VGGSound/video/AI-nr0guriE_000093.mp4 spraying water +tests/VGGSound/video/DAubFydKLOE_000008.mp4 police radio chatter +tests/VGGSound/video/AI7xMI4BJ8s_000143.mp4 spraying water +tests/VGGSound/video/AIDJFkDURPY_000030.mp4 lawn mowing +tests/VGGSound/video/DB38NRSHw9A_000030.mp4 male speech, man speaking +tests/VGGSound/video/DB3Ao8x9Om8_000039.mp4 people battle cry +tests/VGGSound/video/AIVt3e5EVtc_000070.mp4 people coughing +tests/VGGSound/video/DBW6rwVoIcQ_000056.mp4 heart sounds, heartbeat +tests/VGGSound/video/DBh-oPTYJ7M_000039.mp4 chopping food +tests/VGGSound/video/AIuayXjDos8_000130.mp4 playing ukulele +tests/VGGSound/video/AJ2_gn8V2fo_000030.mp4 basketball bounce +tests/VGGSound/video/DBxaCgkkBrA_000001.mp4 running electric fan +tests/VGGSound/video/DC2q5iyvKFM_000060.mp4 playing cornet +tests/VGGSound/video/AJKmKTU32_c_000030.mp4 using sewing machines +tests/VGGSound/video/AJNOn6GBymE_000030.mp4 printer printing +tests/VGGSound/video/DC4_1CHRcx8_000196.mp4 dinosaurs bellowing +tests/VGGSound/video/AJRD-zU2Akw_000000.mp4 lighting firecrackers +tests/VGGSound/video/AJVSqnsBf70_000080.mp4 eating with cutlery +tests/VGGSound/video/AJY56V2Iul4_000510.mp4 waterfall burbling +tests/VGGSound/video/DCZeMextoMU_000034.mp4 parrot talking +tests/VGGSound/video/AJttSbZwVew_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/DCftdpZ9lIs_000162.mp4 dinosaurs bellowing +tests/VGGSound/video/AJw-x30L46E_000080.mp4 playing acoustic guitar +tests/VGGSound/video/DCpWtyLjKmM_000030.mp4 mouse squeaking +tests/VGGSound/video/AK0kZUDk294_000002.mp4 subway, metro, underground +tests/VGGSound/video/DCrct29xGEY_000030.mp4 lions roaring +tests/VGGSound/video/AK_xkz5nfIM_000089.mp4 lip smacking +tests/VGGSound/video/DDL2vJqSA1o_000032.mp4 civil defense siren +tests/VGGSound/video/AKdT8WAIGmk_000030.mp4 basketball bounce +tests/VGGSound/video/AKjcrEsYykE_000340.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/AKmkhvb9shk_000000.mp4 baltimore oriole calling +tests/VGGSound/video/DDZlMjb-0i4_000150.mp4 helicopter +tests/VGGSound/video/AKxHQn994OI_000140.mp4 skateboarding +tests/VGGSound/video/DDhKU_VH0Js_000228.mp4 canary calling +tests/VGGSound/video/DDlAcAppYtE_000026.mp4 parrot talking +tests/VGGSound/video/AKxm4V3OylU_000030.mp4 lions roaring +tests/VGGSound/video/DDmCxUncIyc_000030.mp4 crow cawing +tests/VGGSound/video/AKzmNMyyMms_000030.mp4 ambulance siren +tests/VGGSound/video/DDoJMpe85o0_000386.mp4 mynah bird singing +tests/VGGSound/video/AL-dutJvx0s_000030.mp4 typing on computer keyboard +tests/VGGSound/video/AL7eCaqpzLk_000569.mp4 swimming +tests/VGGSound/video/DE4E77nF8Mg_000030.mp4 dog whimpering +tests/VGGSound/video/DEGSyVygE98_000110.mp4 car engine starting +tests/VGGSound/video/DEMF3mvYPUM_000350.mp4 people crowd +tests/VGGSound/video/DEXE_V8oBYI_000030.mp4 driving buses +tests/VGGSound/video/ALU-1AILj1c_000220.mp4 playing tabla +tests/VGGSound/video/ALVS3Q_jNaU_000030.mp4 playing electric guitar +tests/VGGSound/video/ALcCb2HJmG8_000070.mp4 rapping +tests/VGGSound/video/ALdjQ9kbwd8_000030.mp4 playing accordion +tests/VGGSound/video/DF0AL3gaNLQ_000030.mp4 raining +tests/VGGSound/video/ALngpCKUzmE_000099.mp4 chimpanzee pant-hooting +tests/VGGSound/video/ALtDtYnWFuo_000030.mp4 playing cello +tests/VGGSound/video/ALxn5-2bVyI_000030.mp4 skateboarding +tests/VGGSound/video/DFJ_Z70bfmo_000026.mp4 foghorn +tests/VGGSound/video/DFTZgruYPL4_000115.mp4 alligators, crocodiles hissing +tests/VGGSound/video/AM3p_hpT-0o_000015.mp4 crow cawing +tests/VGGSound/video/DFf71XYDX3g_000016.mp4 chipmunk chirping +tests/VGGSound/video/AMLJZImQ5Xk_000030.mp4 mouse squeaking +tests/VGGSound/video/AMLvdc8Dbq4_000170.mp4 playing clarinet +tests/VGGSound/video/DG3jA6Fswak_000029.mp4 sailing +tests/VGGSound/video/DGBtx9IyqcU_000410.mp4 playing clarinet +tests/VGGSound/video/AMvZ3ANXNW0_000320.mp4 railroad car, train wagon +tests/VGGSound/video/AMxnCzC33lo_000070.mp4 turkey gobbling +tests/VGGSound/video/DGS6j6k14ak_000105.mp4 popping popcorn +tests/VGGSound/video/AN60q9nSnMk_000030.mp4 people sneezing +tests/VGGSound/video/DGeHJrq-FoI_000012.mp4 people eating crisps +tests/VGGSound/video/ANMQ_fFwRl8_000015.mp4 elephant trumpeting +tests/VGGSound/video/ANPjV_rudog_000030.mp4 skateboarding +tests/VGGSound/video/ANWU9Hiy_5k_000040.mp4 driving motorcycle +tests/VGGSound/video/ANXFvn9bRN4_000049.mp4 ferret dooking +tests/VGGSound/video/DH8Fb1kKsGM_000020.mp4 playing marimba, xylophone +tests/VGGSound/video/ANXFvn9bRN4_000063.mp4 ferret dooking +tests/VGGSound/video/DHDn79ee98Q_000030.mp4 playing theremin +tests/VGGSound/video/DHHhgQTYUw8_000183.mp4 bouncing on trampoline +tests/VGGSound/video/AN_nK_tgQSc_000032.mp4 ice cream truck, ice cream van +tests/VGGSound/video/DHK1lEGyOV4_000030.mp4 duck quacking +tests/VGGSound/video/DHSr8GMQSqw_000028.mp4 playing tennis +tests/VGGSound/video/DHXgiZqSoTg_000270.mp4 playing gong +tests/VGGSound/video/ANxHyEeVnV8_000026.mp4 barn swallow calling +tests/VGGSound/video/AO-plgsoaoQ_000194.mp4 roller coaster running +tests/VGGSound/video/DHoVXJe-MXY_000293.mp4 playing glockenspiel +tests/VGGSound/video/AO4Rp4DQXCw_000358.mp4 alarm clock ringing +tests/VGGSound/video/DHoVXJe-MXY_000729.mp4 playing glockenspiel +tests/VGGSound/video/AOH4vRCpxww_000004.mp4 cupboard opening or closing 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+tests/VGGSound/video/DbErO8V96bg_000000.mp4 playing didgeridoo +tests/VGGSound/video/Ah-IBgwj2lg_000030.mp4 owl hooting +tests/VGGSound/video/AhcY8QVSLtM_000050.mp4 chainsawing trees +tests/VGGSound/video/Ahhba-EM4nI_000000.mp4 people sneezing +tests/VGGSound/video/AhlnqK6ONro_000030.mp4 playing didgeridoo +tests/VGGSound/video/Dbo9tI1f2mo_000083.mp4 beat boxing +tests/VGGSound/video/Ai95CU2jN9Y_000504.mp4 chimpanzee pant-hooting +tests/VGGSound/video/AiHq9qStg00_000042.mp4 people marching +tests/VGGSound/video/AiHq9qStg00_000075.mp4 people marching +tests/VGGSound/video/DcMUa81JfBE_000010.mp4 dog baying +tests/VGGSound/video/DcMUa81JfBE_000032.mp4 dog baying +tests/VGGSound/video/DcNVcRK4F4g_000030.mp4 horse neighing +tests/VGGSound/video/DcU6AzN7imA_000210.mp4 reversing beeps +tests/VGGSound/video/Aiks9EreMFY_000171.mp4 playing cornet +tests/VGGSound/video/DcbzE8AnLcE_000030.mp4 fire truck siren +tests/VGGSound/video/DcdwmEsIqRQ_000097.mp4 cell phone buzzing +tests/VGGSound/video/Aj8BKEbijso_000010.mp4 sliding door +tests/VGGSound/video/DcpPZ9pltNs_000137.mp4 cupboard opening or closing +tests/VGGSound/video/AjKzheBybyg_000021.mp4 plastic bottle crushing +tests/VGGSound/video/AjLuenrAsbE_000030.mp4 playing electric guitar +tests/VGGSound/video/DdFjX2ikXbw_000010.mp4 roller coaster running +tests/VGGSound/video/Aja7pKNUbY4_000030.mp4 railroad car, train wagon +tests/VGGSound/video/AjjQqd0eLzw_000030.mp4 playing theremin +tests/VGGSound/video/Ajl5A3YbR88_000120.mp4 playing timpani +tests/VGGSound/video/AkAdDFHQars_000030.mp4 fire truck siren +tests/VGGSound/video/Ddo9DOeh-PA_000218.mp4 people slurping +tests/VGGSound/video/DdwQJlhORjo_000090.mp4 people eating apple +tests/VGGSound/video/DdxiyqivyTc_000029.mp4 wind chime +tests/VGGSound/video/De311q4Wp6Q_000030.mp4 car engine knocking +tests/VGGSound/video/AkUDv7JexjQ_000520.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/Akmt_1N_tuU_000030.mp4 raining +tests/VGGSound/video/Aky0DF507fw_000170.mp4 playing didgeridoo +tests/VGGSound/video/Al5Ks0PnV0w_000017.mp4 shot football +tests/VGGSound/video/Al5Ks0PnV0w_000049.mp4 shot football +tests/VGGSound/video/DegSrwcSF3k_000030.mp4 horse neighing +tests/VGGSound/video/DeiK0fdPv8Y_000008.mp4 people booing +tests/VGGSound/video/AlPu_yxLT2g_000230.mp4 people coughing +tests/VGGSound/video/DexDu4FDEWM_000031.mp4 driving snowmobile +tests/VGGSound/video/AlZUmhHgF8g_000008.mp4 chipmunk chirping +tests/VGGSound/video/AlZv9bRtnws_000030.mp4 playing bass guitar +tests/VGGSound/video/DfCTXmNRj24_000030.mp4 people clapping +tests/VGGSound/video/DfEOfuu863Q_000016.mp4 running electric fan +tests/VGGSound/video/DfKk-fK_gvQ_000153.mp4 people battle cry +tests/VGGSound/video/Alj6G_oFY4E_000025.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/AlnFwT2U1xM_000163.mp4 parrot talking +tests/VGGSound/video/AlqCbPTpKUg_000019.mp4 ice cracking +tests/VGGSound/video/AlsDSDTiaWI_000030.mp4 skidding +tests/VGGSound/video/AmAThmRphk0_000030.mp4 playing banjo +tests/VGGSound/video/AmC1pCa1GfE_000040.mp4 baby babbling +tests/VGGSound/video/AmDDp-cCo24_000000.mp4 cat caterwauling +tests/VGGSound/video/DfrOLl-Or0Q_000011.mp4 telephone bell ringing +tests/VGGSound/video/Dfs090CuKNM_000030.mp4 people crowd +tests/VGGSound/video/Dg8BLvkzdr0_000030.mp4 playing theremin +tests/VGGSound/video/Amd-OLa3tMI_000030.mp4 subway, metro, underground +tests/VGGSound/video/AmipJSk2B-o_000005.mp4 driving snowmobile +tests/VGGSound/video/AmrR1Y9Uvjw_000150.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/An-4jPvUT14_000060.mp4 skateboarding +tests/VGGSound/video/An32hX6i1gs_000030.mp4 male speech, man speaking +tests/VGGSound/video/AnGYl7BIqC4_000025.mp4 sea lion barking +tests/VGGSound/video/Dgl_sLTIOaA_000030.mp4 hair dryer drying +tests/VGGSound/video/DhBqfQ72Im0_000087.mp4 people gargling +tests/VGGSound/video/DhMLiwShZss_000137.mp4 people battle cry +tests/VGGSound/video/AoIHTerxdas_000000.mp4 lawn mowing +tests/VGGSound/video/DhfdRzT2AP4_000132.mp4 metronome +tests/VGGSound/video/DhiZ6pZ8LEc_000170.mp4 using sewing machines +tests/VGGSound/video/AoUn8I-RtRk_000030.mp4 horse neighing +tests/VGGSound/video/Ap26rqhM6gI_000062.mp4 francolin calling +tests/VGGSound/video/Ap2plDNvTTU_000080.mp4 sloshing water +tests/VGGSound/video/DhygJyCvYeA_000263.mp4 playing oboe +tests/VGGSound/video/Ap9gDgwq1DU_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/DiBKqoKUjOk_000080.mp4 goose honking +tests/VGGSound/video/ApIuCbTZuxc_000150.mp4 playing saxophone +tests/VGGSound/video/DiUgEH6m7fw_000099.mp4 gibbon howling +tests/VGGSound/video/ApNcj8ijJlo_000030.mp4 chainsawing trees +tests/VGGSound/video/ApWdM0PXpbk_000001.mp4 woodpecker pecking tree +tests/VGGSound/video/Ap_IlJVRHtw_000230.mp4 lighting firecrackers +tests/VGGSound/video/ApgCxwAImCE_000030.mp4 playing hammond organ +tests/VGGSound/video/DitJemO43co_000014.mp4 ice cream truck, ice cream van +tests/VGGSound/video/AqjB8DGt85U_000034.mp4 cat caterwauling +tests/VGGSound/video/DjXyE3_g0b4_000156.mp4 playing cornet +tests/VGGSound/video/Ar-qKACbnkg_000200.mp4 machine gun shooting +tests/VGGSound/video/Ar0qgvu2BY8_000080.mp4 people crowd +tests/VGGSound/video/Ar5_nY1UZ80_000030.mp4 singing choir +tests/VGGSound/video/Ar5r0pzgaRU_000030.mp4 cat purring +tests/VGGSound/video/DjqOjkoVu3M_000153.mp4 alarm clock ringing +tests/VGGSound/video/Dj3kmG8E1Ng_000030.mp4 people whispering +tests/VGGSound/video/Dj9gyAoqmQ0_000030.mp4 machine gun shooting +tests/VGGSound/video/Aq3pc1q58Kw_000084.mp4 cat caterwauling +tests/VGGSound/video/Aq58qBpVkv8_000160.mp4 people shuffling +tests/VGGSound/video/DjPrMmqCqlg_000075.mp4 eletric blender running +tests/VGGSound/video/DkAeTKwWXs8_000065.mp4 scuba diving +tests/VGGSound/video/ArYIGhYJJns_000030.mp4 stream burbling +tests/VGGSound/video/AraV2kvytIY_000024.mp4 airplane flyby +tests/VGGSound/video/DkJ6OScQshI_000000.mp4 chicken crowing +tests/VGGSound/video/Arah6WF7OPM_000026.mp4 playing erhu +tests/VGGSound/video/DkWAn4rtLa4_000160.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/ArmIysvGUyk_000020.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/Arp482w8r_s_000030.mp4 people clapping +tests/VGGSound/video/Dkfcal9MGPs_000400.mp4 bird squawking +tests/VGGSound/video/As1qH-6EF4I_000030.mp4 people sneezing +tests/VGGSound/video/DkhdvvtvwTE_000020.mp4 owl hooting +tests/VGGSound/video/As8sg7z5n5E_000065.mp4 electric grinder grinding +tests/VGGSound/video/AsAFnQXl6sc_000604.mp4 mouse clicking +tests/VGGSound/video/DkwFXd5nYLE_000040.mp4 driving buses +tests/VGGSound/video/AsghD21CFr4_000030.mp4 lawn mowing +tests/VGGSound/video/DlAnJVkaHn0_000311.mp4 playing darts +tests/VGGSound/video/DlQK2qeiVRs_000039.mp4 playing darts +tests/VGGSound/video/At3hmrH23NI_000400.mp4 people sobbing +tests/VGGSound/video/DlaEUR5O_iY_000010.mp4 car engine knocking 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bowl +tests/VGGSound/video/DpxmQlaOtDg_000194.mp4 playing shofar +tests/VGGSound/video/Ay7bs8DMMyA_000005.mp4 child speech, kid speaking +tests/VGGSound/video/AyEGPZ3cFfY_000043.mp4 owl hooting +tests/VGGSound/video/AyEctiqVYQc_000030.mp4 printer printing +tests/VGGSound/video/DqEpvRDVDEI_000076.mp4 metronome +tests/VGGSound/video/DqFpx3mE9fQ_000030.mp4 crow cawing +tests/VGGSound/video/DqOGYyFVnKk_000200.mp4 skateboarding +tests/VGGSound/video/DqQT03hOLA4_000240.mp4 waterfall burbling +tests/VGGSound/video/Ayr3X0IMj04_000000.mp4 driving buses +tests/VGGSound/video/Az8NdAwKHzo_000008.mp4 lions growling +tests/VGGSound/video/Az9XH0eajXI_000030.mp4 horse clip-clop +tests/VGGSound/video/AzY_KZTSXJk_000030.mp4 playing harmonica +tests/VGGSound/video/AzcRIvaea7o_000030.mp4 waterfall burbling +tests/VGGSound/video/Dqv8aWzOgmo_000049.mp4 whale calling +tests/VGGSound/video/AzhAMscTxyc_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/Dr0Crzj0f4I_000141.mp4 snake rattling 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horn +tests/VGGSound/video/B8prYj0sbgw_000014.mp4 air horn +tests/VGGSound/video/E-hmA_v9ePI_000022.mp4 mouse squeaking +tests/VGGSound/video/E-nunSOWtMs_000070.mp4 ambulance siren +tests/VGGSound/video/E-pIudhSCSg_000496.mp4 playing oboe +tests/VGGSound/video/B90BOtSOD2Q_000410.mp4 female singing +tests/VGGSound/video/E0AacWfbeRE_000030.mp4 frog croaking +tests/VGGSound/video/B98yOZSj2GE_000012.mp4 car passing by +tests/VGGSound/video/B9Aaspp7sy8_000463.mp4 striking pool +tests/VGGSound/video/B9Aaspp7sy8_000729.mp4 striking pool +tests/VGGSound/video/B9Sd9ubebhY_000030.mp4 ambulance siren +tests/VGGSound/video/E0gBwPTHxqE_000030.mp4 skateboarding +tests/VGGSound/video/B9a-LlMTQ9o_000170.mp4 people booing +tests/VGGSound/video/E0pr-jw5Nrg_000129.mp4 playing djembe +tests/VGGSound/video/E1I6LhzVPVw_000132.mp4 beat boxing +tests/VGGSound/video/B9wRwZkoFvY_000038.mp4 telephone bell ringing +tests/VGGSound/video/E1cKPUWHa8I_000084.mp4 airplane flyby 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burbling +tests/VGGSound/video/E5GF74D6Ylc_000043.mp4 playing tambourine +tests/VGGSound/video/BE0qaVGwpLE_000278.mp4 mouse clicking +tests/VGGSound/video/BE1qG9iQZlg_000190.mp4 eating with cutlery +tests/VGGSound/video/BE8Mv5ww4BM_000171.mp4 playing hammond organ +tests/VGGSound/video/E67DLGqXPMo_000200.mp4 eletric blender running +tests/VGGSound/video/BEGgDbKEXMw_000028.mp4 coyote howling +tests/VGGSound/video/BEHaVb_cz44_000210.mp4 playing harp +tests/VGGSound/video/E6Fb7i2rP-Q_000370.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/BEKeSHBu9qI_000340.mp4 playing saxophone +tests/VGGSound/video/E6NTp_ppAAM_000015.mp4 playing bassoon +tests/VGGSound/video/E6QQRZHrx6s_000030.mp4 dog growling +tests/VGGSound/video/BETuSJGFgs4_000280.mp4 playing harp +tests/VGGSound/video/E6TSYy7ikcs_000129.mp4 playing synthesizer +tests/VGGSound/video/E6_602iIrgY_000561.mp4 forging swords +tests/VGGSound/video/E6tdua70y5E_000316.mp4 people slurping +tests/VGGSound/video/BFEeNJkKx6g_000030.mp4 dog howling +tests/VGGSound/video/E75i9rHDHaE_000000.mp4 strike lighter +tests/VGGSound/video/E7BYs6EMeD8_000051.mp4 underwater bubbling +tests/VGGSound/video/E7CeefZM4I8_000008.mp4 magpie calling +tests/VGGSound/video/BFU4nurvCAw_000030.mp4 horse clip-clop +tests/VGGSound/video/E7JkJyUuujE_000307.mp4 people battle cry +tests/VGGSound/video/BFqHyCoypfM_000016.mp4 people screaming +tests/VGGSound/video/E7lohOf6fKE_000205.mp4 squishing water +tests/VGGSound/video/E7m7feGvswI_000229.mp4 people eating noodle +tests/VGGSound/video/E7m7feGvswI_000620.mp4 people eating noodle +tests/VGGSound/video/E7n4klULtxI_000530.mp4 skidding +tests/VGGSound/video/E7qRkUYu580_000307.mp4 sea waves +tests/VGGSound/video/E7q_QwLYI8U_000210.mp4 playing acoustic guitar +tests/VGGSound/video/BGVT6ozn17E_000026.mp4 sea lion barking +tests/VGGSound/video/E81-l2bwh40_000190.mp4 toilet flushing +tests/VGGSound/video/E86Oa92UDS4_000009.mp4 mouse pattering +tests/VGGSound/video/E8SPrMj1cto_000030.mp4 baby crying +tests/VGGSound/video/BGtTepVOst4_000252.mp4 warbler chirping +tests/VGGSound/video/BHDhHO7J-Oo_000030.mp4 skateboarding +tests/VGGSound/video/BHGB73ilrCc_000030.mp4 dog barking +tests/VGGSound/video/BHPYgbsCEtk_000000.mp4 baby laughter +tests/VGGSound/video/E8tUICNlnu0_000137.mp4 opening or closing car electric windows +tests/VGGSound/video/BHajqlL5wmw_000500.mp4 opening or closing drawers +tests/VGGSound/video/BHf4pvm-gGM_000030.mp4 playing cello +tests/VGGSound/video/E9CrHaJJ8I8_000130.mp4 playing timpani +tests/VGGSound/video/BI4quuGz_zk_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/BI8YQ3ueD24_000030.mp4 tapping guitar +tests/VGGSound/video/BI96CRWSZd4_000223.mp4 ripping paper +tests/VGGSound/video/BI96CRWSZd4_000374.mp4 ripping paper +tests/VGGSound/video/BIFzpJ9D6-w_000063.mp4 people eating crisps +tests/VGGSound/video/E9Xbw70cul8_000037.mp4 eletric blender running +tests/VGGSound/video/E9fvVHNgC7A_000102.mp4 running electric fan +tests/VGGSound/video/BITOpJi3deA_000000.mp4 people farting +tests/VGGSound/video/E9ulxBBGUVc_000350.mp4 thunder +tests/VGGSound/video/BIn8CogzivA_000020.mp4 playing trombone +tests/VGGSound/video/E9zyGJjnp6A_000250.mp4 car engine starting +tests/VGGSound/video/BJ1rHiaa590_000095.mp4 civil defense siren +tests/VGGSound/video/EAHbMk015Rw_000030.mp4 thunder +tests/VGGSound/video/EAJT9Bk_GeQ_000030.mp4 playing french horn +tests/VGGSound/video/BJQPnGKD9X0_000049.mp4 lip smacking +tests/VGGSound/video/BJRg1SmxfLk_000044.mp4 footsteps on snow +tests/VGGSound/video/BJX2fm61IKY_000030.mp4 wind rustling leaves +tests/VGGSound/video/BKE_Z-iGErM_000041.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/BKVcTXsztAU_000030.mp4 opening or closing drawers +tests/VGGSound/video/BK_hqG0d5QE_000030.mp4 car engine knocking +tests/VGGSound/video/EB5rkiiHFw8_000030.mp4 hair dryer drying +tests/VGGSound/video/BKgwRJP-wDI_000010.mp4 wind rustling leaves +tests/VGGSound/video/EBEXWRdUZB8_000024.mp4 playing double bass +tests/VGGSound/video/EBHSSNxR-_0_000004.mp4 using sewing machines +tests/VGGSound/video/EBHtpU1tB3E_000000.mp4 penguins braying +tests/VGGSound/video/BL8zBkt6v3o_000030.mp4 dog bow-wow +tests/VGGSound/video/BLEthZXy35s_000250.mp4 railroad car, train wagon +tests/VGGSound/video/BLXwpGCn2KQ_000030.mp4 orchestra +tests/VGGSound/video/EBnrA85wsc4_000030.mp4 people eating +tests/VGGSound/video/BLlnu2Tyqu0_000030.mp4 cat meowing +tests/VGGSound/video/EC7ZXHrHhvE_000057.mp4 chinchilla barking +tests/VGGSound/video/BMAruFZo5NM_000067.mp4 playing bugle +tests/VGGSound/video/BMAruFZo5NM_000088.mp4 playing bugle +tests/VGGSound/video/ECP7EJka6N8_000590.mp4 playing cello +tests/VGGSound/video/ECVfSkmVy5Y_000001.mp4 elk bugling +tests/VGGSound/video/ECVzhzOC5Q0_000030.mp4 chicken clucking +tests/VGGSound/video/BMS_gXhrrko_000000.mp4 sea lion barking +tests/VGGSound/video/ECjMbkRjVzE_000000.mp4 playing electronic organ +tests/VGGSound/video/BMgYWTTJv3s_000240.mp4 playing clarinet +tests/VGGSound/video/ED8UQJIMgeY_000521.mp4 playing steelpan +tests/VGGSound/video/BN4k3mnJteo_000000.mp4 playing flute +tests/VGGSound/video/BN7SNU4g7hs_000030.mp4 playing synthesizer +tests/VGGSound/video/EDVJNo2EAmA_000030.mp4 orchestra +tests/VGGSound/video/EDVrjC9uVgA_000025.mp4 francolin calling +tests/VGGSound/video/EDfFfJ_RLQk_000078.mp4 hail +tests/VGGSound/video/BNfeHeas6hA_000076.mp4 lions growling +tests/VGGSound/video/BNrmXcZQ-p4_000030.mp4 helicopter +tests/VGGSound/video/BNxn1bNPkZE_000000.mp4 footsteps on snow +tests/VGGSound/video/BNxowL6utbQ_000030.mp4 playing harp +tests/VGGSound/video/EDxDbfLpQEI_000006.mp4 magpie calling +tests/VGGSound/video/BO555bbZkDw_000550.mp4 playing vibraphone +tests/VGGSound/video/BOTMv61wlEs_000030.mp4 stream burbling +tests/VGGSound/video/BOgYLyIbVN8_000031.mp4 dog growling +tests/VGGSound/video/BOvH0ICyVLY_000109.mp4 whale calling +tests/VGGSound/video/BP0iZLks5EY_000034.mp4 lions growling +tests/VGGSound/video/BP7tLbj4fOI_000030.mp4 car engine starting +tests/VGGSound/video/EErujqgq1o0_000030.mp4 pig oinking +tests/VGGSound/video/BPeLfS4NPEI_000060.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/EFSxZd_eGjM_000017.mp4 dog whimpering +tests/VGGSound/video/BQ2om2mrIps_000298.mp4 disc scratching +tests/VGGSound/video/EF_X0Ri1S3U_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/BQ86IY0M860_000030.mp4 sailing +tests/VGGSound/video/EFdgfTqdF3Y_000030.mp4 baby laughter +tests/VGGSound/video/BQPk4cmN__4_000030.mp4 dog barking +tests/VGGSound/video/BQpa8whzwAE_000030.mp4 train horning +tests/VGGSound/video/BQsQzaDrHKY_000155.mp4 alligators, crocodiles hissing +tests/VGGSound/video/EGR7EIz9JQ4_000030.mp4 fire truck siren +tests/VGGSound/video/BQsQzaDrHKY_000210.mp4 alligators, crocodiles hissing +tests/VGGSound/video/EGjwVJLLsfQ_000002.mp4 black capped chickadee calling +tests/VGGSound/video/BR3U7WaCP-4_000005.mp4 people nose blowing 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+tests/VGGSound/video/BYajSeGujsM_000028.mp4 francolin calling +tests/VGGSound/video/EP8QFFUA3xE_000005.mp4 hail +tests/VGGSound/video/BZ9I6UN9skY_000050.mp4 zebra braying +tests/VGGSound/video/BZ9I6UN9skY_000063.mp4 zebra braying +tests/VGGSound/video/EPJp93NxFGM_000070.mp4 swimming +tests/VGGSound/video/BZRZcFA9Dr4_000260.mp4 cattle mooing +tests/VGGSound/video/BZTmMcmbNNg_000000.mp4 slot machine +tests/VGGSound/video/BZU01hhyVKs_000480.mp4 people coughing +tests/VGGSound/video/BZWyX4pYUSk_000396.mp4 heart sounds, heartbeat +tests/VGGSound/video/EPzNwL4OVYI_000263.mp4 playing congas +tests/VGGSound/video/BZnklP9nY_8_000002.mp4 pumping water +tests/VGGSound/video/EQ91XVsmq-I_000030.mp4 female speech, woman speaking +tests/VGGSound/video/B_Kfb4_-6Kw_000009.mp4 playing tuning fork +tests/VGGSound/video/B_Kfb4_-6Kw_000025.mp4 playing tuning fork +tests/VGGSound/video/EQHrQIaQNv8_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/EQJHgbw5LFE_000000.mp4 door slamming 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+tests/VGGSound/video/BbND7nQxop4_000030.mp4 lighting firecrackers +tests/VGGSound/video/BbNHWQrTu2o_000030.mp4 waterfall burbling +tests/VGGSound/video/BbOVvWpZAWo_000360.mp4 door slamming +tests/VGGSound/video/BbVoVbQHoXo_000030.mp4 typing on typewriter +tests/VGGSound/video/BbWdsbZ9TsM_000130.mp4 subway, metro, underground +tests/VGGSound/video/ERxlveTpCnw_000137.mp4 sharpen knife +tests/VGGSound/video/BbedVdUH4LA_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/Bbnt3nKDZiI_000150.mp4 cricket chirping +tests/VGGSound/video/ESKallQizu8_000019.mp4 playing marimba, xylophone +tests/VGGSound/video/BcBi3aKtqJk_000177.mp4 tap dancing +tests/VGGSound/video/EScf6Anv-8E_000030.mp4 dog barking +tests/VGGSound/video/BcDXW4fKExE_000086.mp4 dog baying +tests/VGGSound/video/Bch9D2rDK1w_000071.mp4 swimming +tests/VGGSound/video/ETJOLbXNiwA_000007.mp4 airplane +tests/VGGSound/video/BckOteKD49k_000030.mp4 mouse pattering +tests/VGGSound/video/ETbXNJxQrQU_000030.mp4 train horning +tests/VGGSound/video/Bd-1gr7807g_000016.mp4 volcano explosion +tests/VGGSound/video/EU0Vrwxs7pU_000170.mp4 playing vibraphone +tests/VGGSound/video/EUF5k23kQuc_000034.mp4 parrot talking +tests/VGGSound/video/BdeN2D7f528_000022.mp4 scuba diving +tests/VGGSound/video/EUXUKCqUKyo_000005.mp4 playing shofar +tests/VGGSound/video/Bdz-NtAD2SU_000030.mp4 firing cannon +tests/VGGSound/video/Be61A67ltP4_000080.mp4 sliding door +tests/VGGSound/video/EUy-RsUXJ00_000030.mp4 owl hooting +tests/VGGSound/video/BeFjxrUwAC4_000030.mp4 rapping +tests/VGGSound/video/BeHNQZRpizU_000098.mp4 missile launch +tests/VGGSound/video/EVGQc-w5d2I_000014.mp4 people nose blowing +tests/VGGSound/video/EVSNLohmKFc_000540.mp4 using sewing machines +tests/VGGSound/video/EVX-0lgG7Zo_000120.mp4 playing saxophone +tests/VGGSound/video/BeZqhYLzRg4_000181.mp4 running electric fan +tests/VGGSound/video/EW1Jk7-DIO0_000030.mp4 duck quacking +tests/VGGSound/video/EW2eK_x3Rfc_000020.mp4 playing shofar 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+tests/VGGSound/video/EY18UyQJrCs_000144.mp4 canary calling +tests/VGGSound/video/EY1UjHKhb0o_000083.mp4 hammering nails +tests/VGGSound/video/EY7ZnPaMEyM_000050.mp4 bird wings flapping +tests/VGGSound/video/EYCreC_kg5o_000030.mp4 playing tabla +tests/VGGSound/video/Bgnaur8-fas_000160.mp4 playing bongo +tests/VGGSound/video/EYTz1LPDHsc_000017.mp4 opening or closing car doors +tests/VGGSound/video/EYWZz8l8yKg_000110.mp4 playing drum kit +tests/VGGSound/video/Bh-o_G4wNZU_000010.mp4 people babbling +tests/VGGSound/video/EYcrtHKaZlw_000390.mp4 stream burbling +tests/VGGSound/video/BhI1wTFc6KU_000000.mp4 door slamming +tests/VGGSound/video/BhTuYVycq0s_000030.mp4 using sewing machines +tests/VGGSound/video/EZj9VRgD6WQ_000090.mp4 orchestra +tests/VGGSound/video/Bho0lwcxn1g_000020.mp4 people babbling +tests/VGGSound/video/Bhsh62xI1Yg_000109.mp4 ferret dooking +tests/VGGSound/video/EZwY3i6XFaY_000118.mp4 playing badminton +tests/VGGSound/video/Bhsh62xI1Yg_000128.mp4 ferret dooking +tests/VGGSound/video/Bi9gmCJNqDE_000030.mp4 playing french horn +tests/VGGSound/video/BiEt6Hc62go_000000.mp4 crow cawing +tests/VGGSound/video/E_ZBELcyb3g_000008.mp4 playing tuning fork +tests/VGGSound/video/BiNbPvdPthY_000030.mp4 dog whimpering +tests/VGGSound/video/BiRPlINV5N4_000023.mp4 dog baying +tests/VGGSound/video/Bik1ZmiW7gI_008104.mp4 orchestra +tests/VGGSound/video/BilI7w8Am28_000017.mp4 warbler chirping +tests/VGGSound/video/BioGVnRl7OE_000127.mp4 barn swallow calling +tests/VGGSound/video/EaBRGh2s0rU_000030.mp4 door slamming +tests/VGGSound/video/EaGGJ2YQou4_000147.mp4 hammering nails +tests/VGGSound/video/Bj7jRqDk0vE_000280.mp4 child speech, kid speaking +tests/VGGSound/video/BjHakHE9geo_000011.mp4 mynah bird singing +tests/VGGSound/video/BjJf35bzNdM_000050.mp4 popping popcorn +tests/VGGSound/video/BjR_ixR8TUw_000030.mp4 basketball bounce +tests/VGGSound/video/EaTdesZG5PY_000260.mp4 ambulance siren +tests/VGGSound/video/BjYsesK0GQw_000030.mp4 people babbling 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burping +tests/VGGSound/video/EhhmtF1viOo_000076.mp4 skiing +tests/VGGSound/video/EhlXJGEcuBU_000010.mp4 playing tambourine +tests/VGGSound/video/EhmWEYp0vno_000190.mp4 bird squawking +tests/VGGSound/video/EhvCJi5Zbsw_000088.mp4 playing congas +tests/VGGSound/video/BrjXD7rdihs_000497.mp4 playing bass drum +tests/VGGSound/video/BrtKgAjXv7g_000030.mp4 mouse pattering +tests/VGGSound/video/EiOtCVfF83c_000001.mp4 blowtorch igniting +tests/VGGSound/video/BsYFCAuPjwE_000030.mp4 chainsawing trees +tests/VGGSound/video/Ej8tSqilL54_000086.mp4 canary calling +tests/VGGSound/video/BslzZEEwFa8_000030.mp4 people whistling +tests/VGGSound/video/BsnjK6DypAg_000030.mp4 playing didgeridoo +tests/VGGSound/video/EjRiXLPEkwo_000025.mp4 playing glockenspiel +tests/VGGSound/video/Bt_kR7u6mM4_000000.mp4 people farting +tests/VGGSound/video/EjqjnaA1nVg_000030.mp4 playing trumpet +tests/VGGSound/video/EkNx30baO0I_000111.mp4 striking pool +tests/VGGSound/video/EkP005U571U_000000.mp4 child speech, kid speaking 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kid speaking +tests/VGGSound/video/ByndCEEPsu4_000090.mp4 playing cello +tests/VGGSound/video/Byndzwec79o_000030.mp4 printer printing +tests/VGGSound/video/EoquowIMQWA_000000.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/Bz-9hAyxlVU_000026.mp4 warbler chirping +tests/VGGSound/video/Bz3F3488Ypc_000238.mp4 race car, auto racing +tests/VGGSound/video/BzMo0qCklGg_000150.mp4 playing hammond organ +tests/VGGSound/video/BzOeIRpjUN4_000599.mp4 parrot talking +tests/VGGSound/video/BzQw9qtl32o_000010.mp4 playing theremin +tests/VGGSound/video/BzcOUlROXVo_000110.mp4 playing harmonica +tests/VGGSound/video/BzuyMFBB_3Q_000515.mp4 playing cornet +tests/VGGSound/video/EqFttu-PgP0_000030.mp4 playing clarinet +tests/VGGSound/video/C-H88K5GdQE_000020.mp4 playing trombone +tests/VGGSound/video/C-aMG8XXWyE_000030.mp4 people running +tests/VGGSound/video/EqfXm8FwFe0_000009.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/C-fRZcWsRYM_000010.mp4 playing harp 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dog barking +tests/VGGSound/video/EsLDe5fYDrs_000080.mp4 playing french horn +tests/VGGSound/video/C1ZHFE6tU7o_000030.mp4 sliding door +tests/VGGSound/video/C1pyHakPaIE_000030.mp4 singing choir +tests/VGGSound/video/C1tpllWtBVk_000000.mp4 chimpanzee pant-hooting +tests/VGGSound/video/C1wvmtqaQmc_000210.mp4 frog croaking +tests/VGGSound/video/EsoKL_41uOc_000023.mp4 door slamming +tests/VGGSound/video/C2BFL4F6zOM_000062.mp4 rope skipping +tests/VGGSound/video/C2Qj2zgfKaM_000233.mp4 playing guiro +tests/VGGSound/video/EtD6VOh6c9A_000000.mp4 people finger snapping +tests/VGGSound/video/C2rJ-VJLcdk_000330.mp4 hair dryer drying +tests/VGGSound/video/EtcoN3RhRZg_000127.mp4 playing guiro +tests/VGGSound/video/C31iMozaMEA_000010.mp4 child speech, kid speaking +tests/VGGSound/video/C31lRcmAASo_000182.mp4 squishing water +tests/VGGSound/video/EtoEpxSMfSc_000090.mp4 playing accordion +tests/VGGSound/video/C33WdI64FiY_000030.mp4 rapping +tests/VGGSound/video/C3LXTkKw6sU_000030.mp4 railroad car, train wagon +tests/VGGSound/video/C3OOsm-XLO4_000002.mp4 sheep bleating +tests/VGGSound/video/EuJh6cH3kcE_000030.mp4 horse clip-clop +tests/VGGSound/video/C3o8pEsAu5U_000040.mp4 male singing +tests/VGGSound/video/C3yqIuEs_zQ_000430.mp4 ocean burbling +tests/VGGSound/video/C46X66FU_Dw_000030.mp4 chainsawing trees +tests/VGGSound/video/C4EJRCN7f7Q_000558.mp4 child singing +tests/VGGSound/video/Euu6zlJQSD0_000030.mp4 rapping +tests/VGGSound/video/Ev-JWIcNW7A_000030.mp4 wind noise +tests/VGGSound/video/C4GudvmdUHI_000101.mp4 metronome +tests/VGGSound/video/C4GudvmdUHI_000237.mp4 metronome +tests/VGGSound/video/Ev7EbZbgr80_000013.mp4 cupboard opening or closing +tests/VGGSound/video/EvIZC-vFO60_000141.mp4 playing volleyball +tests/VGGSound/video/C4YMjmJ7tt4_000090.mp4 people screaming +tests/VGGSound/video/C4m1KHjp03M_000030.mp4 playing cello +tests/VGGSound/video/Evh-bm79BgQ_000275.mp4 people eating noodle +tests/VGGSound/video/EvzXps-qqO8_000040.mp4 basketball bounce 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rustling leaves +tests/VGGSound/video/EzXThJXRdbI_000017.mp4 firing cannon +tests/VGGSound/video/EzxFkw7UL-k_000050.mp4 chinchilla barking +tests/VGGSound/video/EzxFkw7UL-k_000073.mp4 chinchilla barking +tests/VGGSound/video/F-Ly8CI7-Pc_000020.mp4 firing cannon +tests/VGGSound/video/C8KVATdHjzA_000030.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/F-bjopMLAo4_000090.mp4 barn swallow calling +tests/VGGSound/video/F-c6oa091zo_000150.mp4 airplane +tests/VGGSound/video/F-mbfDB9bN4_000020.mp4 toilet flushing +tests/VGGSound/video/F-p8xsDSjnw_000030.mp4 lions roaring +tests/VGGSound/video/F-scwW3EM1E_000060.mp4 playing harp +tests/VGGSound/video/C8kucowz2NM_000328.mp4 bouncing on trampoline +tests/VGGSound/video/F-yyHi8weHk_000030.mp4 people running +tests/VGGSound/video/C8q-VueE_ok_000330.mp4 bird wings flapping +tests/VGGSound/video/F09naomjaaM_000024.mp4 mouse squeaking +tests/VGGSound/video/F0AtWOUItaQ_000060.mp4 singing bowl +tests/VGGSound/video/F0CgRLr_pTI_000003.mp4 wind chime +tests/VGGSound/video/C989KLZ_3Tw_000021.mp4 playing tambourine +tests/VGGSound/video/C9LzJZ1PpL0_000000.mp4 civil defense siren +tests/VGGSound/video/F0StNDt5xE8_000330.mp4 playing tabla +tests/VGGSound/video/C9f_yqkzqac_000510.mp4 typing on computer keyboard +tests/VGGSound/video/F0xRrtS-_Wk_000030.mp4 crow cawing +tests/VGGSound/video/F1Ig-hdRhuQ_000075.mp4 hail +tests/VGGSound/video/F1X7egd8Us0_000030.mp4 playing acoustic guitar +tests/VGGSound/video/CA5iF0mpXFE_000030.mp4 playing harmonica +tests/VGGSound/video/F2-PKsD5-Vk_000010.mp4 sea waves +tests/VGGSound/video/F2-PKsD5-Vk_000381.mp4 sea waves +tests/VGGSound/video/CAbXVOWLYps_000030.mp4 dog howling +tests/VGGSound/video/F20SKPMppQU_000030.mp4 goose honking +tests/VGGSound/video/CAfUAq5B2jk_000250.mp4 people crowd +tests/VGGSound/video/F2GlSHPf8PA_000014.mp4 playing table tennis +tests/VGGSound/video/F2JQ0swc7kU_000177.mp4 sharpen knife +tests/VGGSound/video/CB1JIYWrzTs_000033.mp4 cell phone buzzing 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black capped chickadee calling +tests/VGGSound/video/CD5VBM6pClk_000030.mp4 sliding door +tests/VGGSound/video/CD8n7ZPuA1U_000005.mp4 mynah bird singing +tests/VGGSound/video/CDABuTQLNe8_000140.mp4 opening or closing drawers +tests/VGGSound/video/CDIex7WRfFo_000025.mp4 telephone bell ringing +tests/VGGSound/video/F5M_tjEX948_000000.mp4 playing hammond organ +tests/VGGSound/video/F5Pbua5Wp7A_000004.mp4 cat growling +tests/VGGSound/video/CE93IieQkAg_000030.mp4 lawn mowing +tests/VGGSound/video/CEIDpwB1ZFE_000030.mp4 playing synthesizer +tests/VGGSound/video/F5e-SEICJP4_000060.mp4 playing steelpan +tests/VGGSound/video/F5iBhMGDdwE_000070.mp4 cattle, bovinae cowbell +tests/VGGSound/video/CEWnNoK8LVQ_000090.mp4 playing volleyball +tests/VGGSound/video/CEWvYJiAxgg_000069.mp4 bouncing on trampoline +tests/VGGSound/video/CEYDkGy1uAY_000294.mp4 people eating crisps +tests/VGGSound/video/CE_cEThCA1M_000099.mp4 pheasant crowing +tests/VGGSound/video/CE_cEThCA1M_000151.mp4 pheasant crowing 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+tests/VGGSound/video/CIJhL5kL8Sg_000788.mp4 driving snowmobile +tests/VGGSound/video/CIN_pzwxrCE_000069.mp4 ferret dooking +tests/VGGSound/video/FAcA4CyL90s_000127.mp4 tap dancing +tests/VGGSound/video/FAm2fNxtHOw_000000.mp4 lions roaring +tests/VGGSound/video/CIiA39U8UTw_000030.mp4 fire truck siren +tests/VGGSound/video/CIlNi_e9SJ0_000120.mp4 sharpen knife +tests/VGGSound/video/FBIbveps_SQ_000030.mp4 people sobbing +tests/VGGSound/video/CJdr8iZw8rE_000277.mp4 firing muskets +tests/VGGSound/video/FBywOWQykEc_000492.mp4 people humming +tests/VGGSound/video/FC-h534z9uA_000400.mp4 playing bagpipes +tests/VGGSound/video/CJr8XzTyIr4_000158.mp4 playing accordion +tests/VGGSound/video/CK5D-skzB5Y_000170.mp4 dinosaurs bellowing +tests/VGGSound/video/CK7_1E8cNMM_000043.mp4 playing tympani +tests/VGGSound/video/FD1LeLl1xBA_000060.mp4 beat boxing +tests/VGGSound/video/FD2paju93aI_000030.mp4 door slamming +tests/VGGSound/video/CKkbZCb9Y18_000030.mp4 chainsawing trees +tests/VGGSound/video/FDHKDDeamFw_000169.mp4 playing guiro +tests/VGGSound/video/FDHKDDeamFw_000193.mp4 playing guiro +tests/VGGSound/video/CKn1FuB53KU_000030.mp4 sailing +tests/VGGSound/video/CL4aLxsGEiY_000151.mp4 playing shofar +tests/VGGSound/video/CL5vkiMs2c0_000010.mp4 reversing beeps +tests/VGGSound/video/CLkaBeRcGT0_000002.mp4 playing timbales +tests/VGGSound/video/FEGa4e6RAlw_000030.mp4 driving buses +tests/VGGSound/video/FEONPM3mckU_000090.mp4 frog croaking +tests/VGGSound/video/CLtTzEgjeJk_000066.mp4 playing bugle +tests/VGGSound/video/CM1TyRRGGd0_000061.mp4 francolin calling +tests/VGGSound/video/CMCtge02AnU_000260.mp4 playing hammond organ +tests/VGGSound/video/CMKnSInoA7I_000003.mp4 horse clip-clop +tests/VGGSound/video/CMWoAvgD0A0_000009.mp4 people screaming +tests/VGGSound/video/FF0VaBxb27w_000030.mp4 playing ukulele +tests/VGGSound/video/FF2bhR7s3VY_000030.mp4 waterfall burbling +tests/VGGSound/video/FF9A0DTCFfY_000504.mp4 bowling impact +tests/VGGSound/video/FFSWmryaZ60_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/CMzLTmZsUGo_000000.mp4 baby babbling +tests/VGGSound/video/FFUSdzyhgZo_000290.mp4 playing timpani +tests/VGGSound/video/CNWRE8HnSmU_000023.mp4 opening or closing car doors +tests/VGGSound/video/FG9lLFEg__Y_000286.mp4 ice cracking +tests/VGGSound/video/CNcxzB9F-Q8_000100.mp4 skateboarding +tests/VGGSound/video/FGEcmA0EFpI_000000.mp4 whale calling +tests/VGGSound/video/CNoP-Y19lRI_000004.mp4 whale calling +tests/VGGSound/video/CNteFuxbbZs_000030.mp4 mouse squeaking +tests/VGGSound/video/FGPx2E089VU_000019.mp4 frog croaking +tests/VGGSound/video/COHl887nx60_000003.mp4 playing badminton +tests/VGGSound/video/COIZ9xZCRyI_000009.mp4 people nose blowing +tests/VGGSound/video/FGz_-95vo0c_000118.mp4 people nose blowing +tests/VGGSound/video/FH0MZoQHSro_000030.mp4 driving motorcycle +tests/VGGSound/video/FHChU52nch0_000010.mp4 bird squawking +tests/VGGSound/video/COhPkkb8I0c_000096.mp4 cat growling +tests/VGGSound/video/FHaWu2rcP94_000080.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/FHcsjO-lVbw_000060.mp4 people whistling +tests/VGGSound/video/FHgtLE-TzQ4_000030.mp4 singing bowl +tests/VGGSound/video/FHhZzDbLmw0_000016.mp4 snake hissing +tests/VGGSound/video/FHrLulSgRpI_000039.mp4 scuba diving +tests/VGGSound/video/FHuxuM-iRo4_000160.mp4 eating with cutlery +tests/VGGSound/video/CPVPmzfWJhQ_000020.mp4 playing tympani +tests/VGGSound/video/FI6SwkcxekM_000540.mp4 opening or closing drawers +tests/VGGSound/video/CPvs0cy_RR4_000034.mp4 cuckoo bird calling +tests/VGGSound/video/CQ8oRAR8mVo_000014.mp4 warbler chirping +tests/VGGSound/video/FIktp5ggvX4_000010.mp4 dog barking +tests/VGGSound/video/CQGQV-JxPoI_000030.mp4 cat meowing +tests/VGGSound/video/CQNxQ_dD040_000005.mp4 horse clip-clop +tests/VGGSound/video/FJ6cTKn5MUw_000010.mp4 waterfall burbling +tests/VGGSound/video/CQTUoapmD_s_000030.mp4 motorboat, speedboat acceleration 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+tests/VGGSound/video/FMLhPfYb-oY_000030.mp4 lions roaring +tests/VGGSound/video/CTYO9dLDun4_000020.mp4 sliding door +tests/VGGSound/video/FMfTSJGsk5M_000062.mp4 people gargling +tests/VGGSound/video/CTp0IjcFOg8_000576.mp4 air conditioning noise +tests/VGGSound/video/FMfZWfpusVk_000130.mp4 people crowd +tests/VGGSound/video/FMr1WHtXJbc_000030.mp4 tapping guitar +tests/VGGSound/video/CU72qSlceqM_000030.mp4 chicken crowing +tests/VGGSound/video/FN7OcEhMA7I_000132.mp4 playing badminton +tests/VGGSound/video/CUJ1MnvyKOw_000040.mp4 dog growling +tests/VGGSound/video/CUL0UrnVfZI_000030.mp4 singing choir +tests/VGGSound/video/FNFgjJ00J9w_000030.mp4 chicken crowing +tests/VGGSound/video/CUMunjwsO2U_000020.mp4 playing piano +tests/VGGSound/video/CUWfvJiJFLQ_000030.mp4 playing bagpipes +tests/VGGSound/video/CUcsXLZhXfk_000021.mp4 cheetah chirrup +tests/VGGSound/video/CUt0oGFuxL8_000053.mp4 woodpecker pecking tree +tests/VGGSound/video/CV3EAozMSzw_000047.mp4 parrot talking +tests/VGGSound/video/FO0u1akOwOM_000000.mp4 playing badminton +tests/VGGSound/video/FO1ho1R18P8_000140.mp4 playing vibraphone +tests/VGGSound/video/CVLqZyUwqv8_000200.mp4 playing sitar +tests/VGGSound/video/FONKpzlXUoc_000172.mp4 roller coaster running +tests/VGGSound/video/FOseBorBQ_I_000460.mp4 people belly laughing +tests/VGGSound/video/CWA2pRIDHuI_000000.mp4 snake rattling +tests/VGGSound/video/CWHD3CxFWkQ_000043.mp4 people humming +tests/VGGSound/video/CWMLP1OHIW8_000030.mp4 people sneezing +tests/VGGSound/video/CWY1Y5hjfpo_000030.mp4 playing bass guitar +tests/VGGSound/video/CW_UrQzAqzU_000025.mp4 canary calling +tests/VGGSound/video/CWctSkH4jR0_000078.mp4 car engine idling +tests/VGGSound/video/FPmtQAIfLBQ_000030.mp4 ocean burbling +tests/VGGSound/video/CWi_968aD3M_000017.mp4 rope skipping +tests/VGGSound/video/CWxZNhucY8o_000573.mp4 people eating apple +tests/VGGSound/video/CX-gGuT3iEs_000230.mp4 chicken crowing +tests/VGGSound/video/CXISjTeWfTE_000200.mp4 cap gun shooting +tests/VGGSound/video/FQHhMhW4sHw_000040.mp4 beat boxing +tests/VGGSound/video/CXRemJ1ZLC8_000250.mp4 child speech, kid speaking +tests/VGGSound/video/CXfxDP-UyiE_000030.mp4 people whistling +tests/VGGSound/video/CY6xP2-6e3Q_000030.mp4 goat bleating +tests/VGGSound/video/FR9qGkCa78M_000140.mp4 eating with cutlery +tests/VGGSound/video/CYRnb2F9ekQ_000280.mp4 goose honking +tests/VGGSound/video/FRoMl49q5gc_000160.mp4 people crowd +tests/VGGSound/video/FRu6azEgTvU_000285.mp4 writing on blackboard with chalk +tests/VGGSound/video/FRwFfq3Tl1g_000310.mp4 skateboarding +tests/VGGSound/video/FRzHx9ibb9I_000240.mp4 car engine starting +tests/VGGSound/video/CYZTjXQMiV8_000570.mp4 bird wings flapping +tests/VGGSound/video/FS9uRzU3-v0_000057.mp4 disc scratching +tests/VGGSound/video/FSAGhEQ3uFk_000003.mp4 playing trumpet +tests/VGGSound/video/CZ4scHrRlVA_000053.mp4 people eating noodle +tests/VGGSound/video/CZZNrpHh3UM_000000.mp4 people sneezing +tests/VGGSound/video/CZf-yC8pkwk_000106.mp4 people gargling +tests/VGGSound/video/CZf-yC8pkwk_000204.mp4 people gargling +tests/VGGSound/video/FTBa7HXdxqE_000004.mp4 smoke detector beeping +tests/VGGSound/video/CZgx_6XaEkg_000030.mp4 driving motorcycle +tests/VGGSound/video/CZilvdWN8PI_000079.mp4 planing timber +tests/VGGSound/video/CZlQbIE6FXQ_000050.mp4 wind noise +tests/VGGSound/video/CZpzlNUH_Hc_000030.mp4 cricket chirping +tests/VGGSound/video/FTOafffuu5U_000150.mp4 people babbling +tests/VGGSound/video/CZv_yRWyT74_000377.mp4 plastic bottle crushing +tests/VGGSound/video/C_1vUaruCYI_000030.mp4 ocean burbling +tests/VGGSound/video/C_GSeZOpoRo_000030.mp4 using sewing machines +tests/VGGSound/video/ccCzbG5FcZI_000038.mp4 tractor digging +tests/VGGSound/video/fvIV8Wu_-Lo_000129.mp4 pheasant crowing +tests/VGGSound/video/fvOZ_L5EY0k_000030.mp4 playing hammond organ +tests/VGGSound/video/fvQeqBqqcVw_000030.mp4 raining +tests/VGGSound/video/fvWS01GjKIw_000010.mp4 ocean burbling +tests/VGGSound/video/ccmAp6PBdDI_000030.mp4 mosquito buzzing +tests/VGGSound/video/fvhbI-7e89s_000010.mp4 people burping +tests/VGGSound/video/fvxQYHXvikY_000316.mp4 rope skipping +tests/VGGSound/video/fw3aeZ0BieE_000010.mp4 playing djembe +tests/VGGSound/video/cdEytWP8M9U_000057.mp4 air conditioning noise +tests/VGGSound/video/fw5gg4WM-ko_000321.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/cdIvqn14xgI_000030.mp4 playing didgeridoo +tests/VGGSound/video/fw8zeOi0DiA_000137.mp4 parrot talking +tests/VGGSound/video/fwFuuaK8WqE_000332.mp4 playing cornet +tests/VGGSound/video/fwKMB57hL6E_000056.mp4 pheasant crowing +tests/VGGSound/video/fwKMB57hL6E_000097.mp4 pheasant crowing +tests/VGGSound/video/cdbYsoEasio_000070.mp4 people screaming +tests/VGGSound/video/cdhpPQr5xnU_000017.mp4 turkey gobbling +tests/VGGSound/video/fwas0HLGbqM_000030.mp4 raining +tests/VGGSound/video/cImwD_Vy7lI_000030.mp4 firing cannon +tests/VGGSound/video/cIriwVhRPVA_000031.mp4 female singing +tests/VGGSound/video/fbJxpi7W9ds_000130.mp4 playing accordion +tests/VGGSound/video/cJCRYyTgscg_000200.mp4 waterfall burbling +tests/VGGSound/video/fbOcgbgERGg_000192.mp4 cutting hair with electric trimmers +tests/VGGSound/video/cJZsuL9iRVc_000321.mp4 writing on blackboard with chalk +tests/VGGSound/video/fbdz2U-fJsk_000110.mp4 owl hooting +tests/VGGSound/video/fbmriH12IMg_000077.mp4 people humming +tests/VGGSound/video/cK5aT07gOis_000151.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/cK9JgR-LGfU_000011.mp4 alligators, crocodiles hissing +tests/VGGSound/video/cK9JgR-LGfU_000046.mp4 alligators, crocodiles hissing +tests/VGGSound/video/cKBrnjxlKgU_000254.mp4 playing bassoon +tests/VGGSound/video/fc9x20wj8ss_000076.mp4 telephone bell ringing +tests/VGGSound/video/bH_4hTLhZi4_000030.mp4 sliding door +tests/VGGSound/video/Z55jffJcevQ_000040.mp4 mouse pattering +tests/VGGSound/video/bHeeVi0fgv8_000180.mp4 bird squawking +tests/VGGSound/video/bHmbZDvqpyo_000020.mp4 people babbling +tests/VGGSound/video/Z5QU8D9hhQA_000010.mp4 footsteps on snow +tests/VGGSound/video/UjXi6X-moxE_000090.mp4 baby laughter +tests/VGGSound/video/NjFkfmusEbM_000140.mp4 playing saxophone +tests/VGGSound/video/R05dToeNqng_000580.mp4 lawn mowing +tests/VGGSound/video/NjLHnT9ZtPw_000119.mp4 playing table tennis +tests/VGGSound/video/MHfusgSoXiw_000010.mp4 playing timpani +tests/VGGSound/video/P_utET7TCMQ_000020.mp4 people babbling +tests/VGGSound/video/MHphDoMqN4g_000079.mp4 mynah bird singing +tests/VGGSound/video/PaJatNJhmsQ_000000.mp4 church bell ringing +tests/VGGSound/video/MHykFW1zgoA_000121.mp4 lathe spinning +tests/VGGSound/video/PaQGXIh94uc_000150.mp4 playing ukulele +tests/VGGSound/video/M2ItM1UNiyU_000325.mp4 hedge trimmer running +tests/VGGSound/video/ItsHQv62xTs_000114.mp4 strike lighter +tests/VGGSound/video/ItvWPMW7RWE_000150.mp4 goose honking +tests/VGGSound/video/M2WVhHYQvTM_000030.mp4 people sniggering +tests/VGGSound/video/Iu1k5XJoeXk_000000.mp4 dog bow-wow +tests/VGGSound/video/M2Xd3b0-rAI_000190.mp4 printer printing +tests/VGGSound/video/Iuq6qxeDVR0_000190.mp4 francolin calling +tests/VGGSound/video/M34hO-PqzpE_000050.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/IuvZlJaF4Go_000030.mp4 goat bleating +tests/VGGSound/video/IvCd8eU3N7U_000005.mp4 alligators, crocodiles hissing +tests/VGGSound/video/IvPbQdbsQUI_000331.mp4 sharpen knife +tests/VGGSound/video/M3mR0OB6iAs_000061.mp4 warbler chirping +tests/VGGSound/video/IvUXQLAqHz4_000971.mp4 ripping paper +tests/VGGSound/video/M3tAFphkQow_000001.mp4 goat bleating +tests/VGGSound/video/M428cu9VTT8_000026.mp4 snake rattling +tests/VGGSound/video/Iw4CEwT1wI8_000011.mp4 plastic bottle crushing +tests/VGGSound/video/IUItviB2VsQ_000030.mp4 singing choir +tests/VGGSound/video/IU_j5shHQP4_000430.mp4 squishing water +tests/VGGSound/video/IUgHJv3LBns_000089.mp4 people eating crisps +tests/VGGSound/video/IUlF2uk8JA0_000056.mp4 playing hockey +tests/VGGSound/video/LdBuyaHo5Vg_000017.mp4 bull bellowing +tests/VGGSound/video/LdGcKY4CHaE_000038.mp4 playing squash +tests/VGGSound/video/IVJkeUVwUaY_000037.mp4 playing erhu +tests/VGGSound/video/IVJkeUVwUaY_000145.mp4 playing erhu +tests/VGGSound/video/Ld_6bCcNVI4_000290.mp4 hair dryer drying +tests/VGGSound/video/LdeIAOUu15M_000091.mp4 striking bowling +tests/VGGSound/video/LdfJMLzJM3A_000030.mp4 people eating +tests/VGGSound/video/LdljbBlb1Vs_000010.mp4 people sniggering +tests/VGGSound/video/IVZQRMQULlQ_000100.mp4 playing cello +tests/VGGSound/video/LdpRTw1ieMI_000030.mp4 crow cawing +tests/VGGSound/video/Ldy55yHcRxk_000055.mp4 missile launch +tests/VGGSound/video/Le2MGWRa_SE_000030.mp4 cat hissing +tests/VGGSound/video/Le4cUq4dLUI_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/Le4vGJ4U7AM_000000.mp4 people babbling +tests/VGGSound/video/IW0a2qTioAA_000019.mp4 goat bleating +tests/VGGSound/video/Le9QaCTQFQ4_000150.mp4 people farting +tests/VGGSound/video/L9-nSe9P0l8_000364.mp4 people eating noodle +tests/VGGSound/video/L91DeeZZYnU_000042.mp4 people slapping +tests/VGGSound/video/C_pnsyNXphA_000030.mp4 race car, auto racing +tests/VGGSound/video/CaLHi97qsZc_000428.mp4 scuba diving +tests/VGGSound/video/CaYNuuW9rt4_000011.mp4 horse neighing +tests/VGGSound/video/Cah4MJiVUFI_000030.mp4 people crowd +tests/VGGSound/video/FVXdvx8eBp8_000038.mp4 writing on blackboard with chalk +tests/VGGSound/video/Cb2k9JwDkDQ_000030.mp4 goose honking +tests/VGGSound/video/FVk1LVQ5K98_000530.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/FVpLUGcFLTY_000290.mp4 people crowd +tests/VGGSound/video/FWLkyzlJBP8_000170.mp4 church bell ringing +tests/VGGSound/video/FWNcjUpRg04_000030.mp4 playing bagpipes +tests/VGGSound/video/CbomWMJU3ro_000030.mp4 opening or closing drawers +tests/VGGSound/video/FWWM9d899l0_000030.mp4 people sniggering +tests/VGGSound/video/FW_ZKuAD_Vo_000039.mp4 shot football +tests/VGGSound/video/FWm0H1oyVwE_000180.mp4 scuba diving +tests/VGGSound/video/CcR1jeBHtCk_000058.mp4 snake rattling +tests/VGGSound/video/FXGNlx9HJ6I_000010.mp4 people booing +tests/VGGSound/video/FXGNlx9HJ6I_000036.mp4 people booing +tests/VGGSound/video/FXQxobF8FWw_000030.mp4 playing electric guitar +tests/VGGSound/video/Cd4YOq17N6w_000062.mp4 ferret dooking +tests/VGGSound/video/CdCiigzp5Cw_000000.mp4 opening or closing drawers +tests/VGGSound/video/FXlPUGUw9UU_000260.mp4 singing bowl +tests/VGGSound/video/CdSt0vG0uk0_000320.mp4 people crowd +tests/VGGSound/video/Ce1P47VwTAI_000030.mp4 female speech, woman speaking +tests/VGGSound/video/Ce2fbtvF_TI_000039.mp4 playing glockenspiel +tests/VGGSound/video/Ce2fbtvF_TI_000136.mp4 playing glockenspiel +tests/VGGSound/video/CeA8--FUxYg_000300.mp4 playing cymbal +tests/VGGSound/video/FZ6SAZzghk0_000030.mp4 playing didgeridoo +tests/VGGSound/video/Cefeb2q4KSE_000110.mp4 playing gong +tests/VGGSound/video/Cer1un9vciI_000030.mp4 singing choir +tests/VGGSound/video/CewaO3Aug84_000080.mp4 firing muskets +tests/VGGSound/video/FZiKkwC6bIE_000000.mp4 lathe spinning +tests/VGGSound/video/Cf0qCCo8ItA_000219.mp4 car engine idling +tests/VGGSound/video/CfPbKzvW0SQ_000070.mp4 playing trombone +tests/VGGSound/video/CfnFpH_Xe4Y_000013.mp4 ice cream truck, ice cream van +tests/VGGSound/video/Cfs7cp5r38U_000067.mp4 volcano explosion +tests/VGGSound/video/Cg07QFTiJtI_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/Cg8J1IVC3Ic_000013.mp4 mouse pattering +tests/VGGSound/video/FaMZfnJKuqA_000019.mp4 tractor digging +tests/VGGSound/video/CgMmtC41T9k_000030.mp4 wind chime +tests/VGGSound/video/CgMt2IylPic_000494.mp4 canary calling +tests/VGGSound/video/FatuEXsaQ20_000030.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/FauOsBt_IFA_000160.mp4 people crowd +tests/VGGSound/video/FayXchyGICg_000027.mp4 people booing +tests/VGGSound/video/Cgb7x_fbmHk_000014.mp4 scuba diving +tests/VGGSound/video/FbLFOzKYe-w_000123.mp4 cutting hair with electric trimmers +tests/VGGSound/video/CguHOT6Ve3E_000020.mp4 waterfall burbling +tests/VGGSound/video/CgzmlbU6hsk_000030.mp4 playing banjo +tests/VGGSound/video/ChBwdyjZAJI_000030.mp4 chicken crowing +tests/VGGSound/video/FbwgXeLSRTE_000002.mp4 wood thrush calling +tests/VGGSound/video/FcUVtXJMkJs_000030.mp4 people screaming +tests/VGGSound/video/ChX3mPUgLok_000030.mp4 door slamming +tests/VGGSound/video/ChYU7ABCcq0_000089.mp4 sheep bleating +tests/VGGSound/video/FcYTmYV1eVg_001089.mp4 playing hockey +tests/VGGSound/video/Fc_P1r8SSRw_000071.mp4 people sniggering +tests/VGGSound/video/Chc1xUT9KB0_000070.mp4 railroad car, train wagon +tests/VGGSound/video/Chi9u8htrm4_000230.mp4 hair dryer drying +tests/VGGSound/video/Ci3-0HPWSa8_000070.mp4 mouse pattering +tests/VGGSound/video/Fd6btl9L0Ns_000182.mp4 car engine idling +tests/VGGSound/video/CiSmL4nmic0_000150.mp4 ocean burbling +tests/VGGSound/video/Cih7zp6KJac_000060.mp4 people eating noodle +tests/VGGSound/video/Citws4f_LJw_000027.mp4 cat growling +tests/VGGSound/video/CiuMO1EkzU4_000010.mp4 child speech, kid speaking +tests/VGGSound/video/Fe2qg0G74do_000268.mp4 train horning +tests/VGGSound/video/CjO1ZZZI8CE_000030.mp4 female speech, woman speaking +tests/VGGSound/video/FeXZY4eVLlo_000040.mp4 basketball bounce +tests/VGGSound/video/FeXj1i4ur5Q_000030.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/Cju3g4Jobkg_000148.mp4 warbler chirping +tests/VGGSound/video/CjuYza6dsvs_000030.mp4 crow cawing +tests/VGGSound/video/CkR2jl_LI3w_000030.mp4 horse clip-clop +tests/VGGSound/video/CkUHXjbrlN4_000090.mp4 baby babbling +tests/VGGSound/video/CkXT-wEQRfM_000140.mp4 people crowd +tests/VGGSound/video/CkaCgJWCpdM_000030.mp4 horse neighing +tests/VGGSound/video/Ckmc5j2_a9s_000350.mp4 playing clarinet +tests/VGGSound/video/Ckr_j4ajrx0_000007.mp4 playing guiro +tests/VGGSound/video/Ckry8_o74DU_000030.mp4 car engine knocking +tests/VGGSound/video/CkutJYIfghs_000030.mp4 sailing +tests/VGGSound/video/Ckv52MHdAeg_000070.mp4 playing harpsichord +tests/VGGSound/video/FfwAkXR6JMc_000025.mp4 cat hissing +tests/VGGSound/video/Fg18M9ARcQY_000030.mp4 car engine knocking +tests/VGGSound/video/Ckz3mjx9XwY_000000.mp4 footsteps on snow +tests/VGGSound/video/FgJVcuKfP5A_000037.mp4 spraying water +tests/VGGSound/video/ClS4xz2GtBk_000644.mp4 people eating apple +tests/VGGSound/video/ClaW4rHT6t0_000000.mp4 railroad car, train wagon +tests/VGGSound/video/CljO1-A89-g_000030.mp4 people crowd +tests/VGGSound/video/FgiGqzj8Hkk_000030.mp4 ambulance siren +tests/VGGSound/video/ClnfpR5VSgA_000010.mp4 cattle mooing +tests/VGGSound/video/Fgsn0aqrCgU_000028.mp4 spraying water +tests/VGGSound/video/FgzVC4jxtxg_000100.mp4 playing clarinet +tests/VGGSound/video/Cm6yI1OrbzM_000010.mp4 playing french horn +tests/VGGSound/video/Fh53p0Tnnxg_000130.mp4 playing sitar +tests/VGGSound/video/Fh6RuC3pNhw_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/CmAt9DymrbM_000030.mp4 door slamming +tests/VGGSound/video/CmBawC_pvEo_000130.mp4 people cheering +tests/VGGSound/video/CmGHMSQZOVw_000370.mp4 cattle mooing +tests/VGGSound/video/FhOjRWQ8Ylw_000103.mp4 people booing +tests/VGGSound/video/FhaYvI1yrUM_000021.mp4 horse neighing +tests/VGGSound/video/FhaxyhtVfCA_000011.mp4 ambulance siren +tests/VGGSound/video/Cmb7oRnRLio_000034.mp4 whale calling +tests/VGGSound/video/Cmb7oRnRLio_000083.mp4 whale calling +tests/VGGSound/video/Cmhpj4MJ_hQ_000020.mp4 people babbling +tests/VGGSound/video/Cmz0InA1eM4_000030.mp4 singing choir +tests/VGGSound/video/Fic2Go84_k0_000116.mp4 bouncing on trampoline +tests/VGGSound/video/Fihamhv6TJo_000030.mp4 people clapping +tests/VGGSound/video/CnxNaUbF61U_000030.mp4 sloshing water +tests/VGGSound/video/Co7vOJiMeO0_000064.mp4 baby crying +tests/VGGSound/video/CoFbRc1OxFU_000009.mp4 driving buses +tests/VGGSound/video/Fj9Hv1gEJLA_000030.mp4 crow cawing +tests/VGGSound/video/FjCtruuJ09I_000031.mp4 popping popcorn +tests/VGGSound/video/CodqNx1ukOc_000030.mp4 tapping guitar +tests/VGGSound/video/FjRjHKz1kU0_000030.mp4 turkey gobbling +tests/VGGSound/video/FjeBeV_0-aE_000030.mp4 playing zither +tests/VGGSound/video/Coxhwm4cDIQ_000494.mp4 bouncing on trampoline +tests/VGGSound/video/Fk4VP1Qo4so_000018.mp4 train horning +tests/VGGSound/video/CpNfxbqRDUA_000030.mp4 owl hooting +tests/VGGSound/video/FkS5NOnVsL0_000050.mp4 rope skipping +tests/VGGSound/video/Cp_wgmmliuk_000210.mp4 playing cello +tests/VGGSound/video/FkiXyAHTKgY_000137.mp4 ice cracking +tests/VGGSound/video/CpoUHOCPaNw_000020.mp4 playing harp +tests/VGGSound/video/Fl0yc47JSWM_000025.mp4 chicken clucking +tests/VGGSound/video/Fl95Zz5wssE_000080.mp4 arc welding +tests/VGGSound/video/Cpwy_3wUjSc_000330.mp4 child singing +tests/VGGSound/video/FlYi8CPdbBs_000053.mp4 roller coaster running +tests/VGGSound/video/Fl_gvQ9bPvM_000129.mp4 eletric blender running +tests/VGGSound/video/FllDQbpfpPM_000146.mp4 yodelling +tests/VGGSound/video/Flnwq0YuoAU_000100.mp4 bird squawking +tests/VGGSound/video/Flusa6-SaDM_000090.mp4 horse clip-clop +tests/VGGSound/video/CqU0IKskISI_000605.mp4 playing lacrosse +tests/VGGSound/video/Fm5ZiCupuqc_000045.mp4 beat boxing +tests/VGGSound/video/Cqb1zyyTiHw_000000.mp4 bathroom ventilation fan running +tests/VGGSound/video/Cqb1zyyTiHw_000011.mp4 bathroom ventilation fan running +tests/VGGSound/video/CqmuLdNiEjE_000077.mp4 dog growling +tests/VGGSound/video/FmekHi2dLdI_000004.mp4 sheep bleating +tests/VGGSound/video/FmekHi2dLdI_000083.mp4 sheep bleating +tests/VGGSound/video/CrCsfXn48q0_000230.mp4 people eating +tests/VGGSound/video/FmpWIi0pt7o_000094.mp4 playing erhu +tests/VGGSound/video/CrNtUnMS4_Y_000004.mp4 warbler chirping +tests/VGGSound/video/CrOlDmMSVSM_000120.mp4 cattle mooing +tests/VGGSound/video/FnAMBtdpeLM_000023.mp4 playing badminton +tests/VGGSound/video/Cr__MHtll1g_000021.mp4 alligators, crocodiles hissing +tests/VGGSound/video/FnCrdfgwfdM_000622.mp4 playing bassoon +tests/VGGSound/video/CrbZHPkHeV4_000030.mp4 rapping +tests/VGGSound/video/Cs0UHi69c7Y_000030.mp4 playing zither +tests/VGGSound/video/FndCEC7yK2g_000104.mp4 airplane flyby +tests/VGGSound/video/CsBwBct0_5U_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/FneEc150gSY_000120.mp4 pumping water +tests/VGGSound/video/Fnsn0MeW3X4_000580.mp4 playing french horn +tests/VGGSound/video/CsRF3qYnSLI_000030.mp4 dog howling +tests/VGGSound/video/Cs_DJvnYWTs_000010.mp4 dog whimpering +tests/VGGSound/video/CsaSKyluqPU_000032.mp4 hail +tests/VGGSound/video/Csj-8j5NRUk_000090.mp4 scuba diving +tests/VGGSound/video/FoHlrQScWl0_000241.mp4 tap dancing +tests/VGGSound/video/CsqoaGRJhfM_000030.mp4 chicken crowing +tests/VGGSound/video/CsrB8B5aiR0_000014.mp4 zebra braying +tests/VGGSound/video/FoUk5_00P9o_000003.mp4 forging swords +tests/VGGSound/video/CsrB8B5aiR0_000049.mp4 zebra braying +tests/VGGSound/video/Fo_FDiZhzDo_000030.mp4 skidding +tests/VGGSound/video/Ct0DTSW4mvw_000181.mp4 firing muskets +tests/VGGSound/video/Fot4v0DdGyE_000020.mp4 driving snowmobile +tests/VGGSound/video/Ct9ltnuEPvc_000038.mp4 playing washboard +tests/VGGSound/video/FpFwKojx3ls_000086.mp4 squishing water +tests/VGGSound/video/FpLAlaQCI5w_000010.mp4 playing harpsichord +tests/VGGSound/video/FpSHaK68ch8_000000.mp4 goat bleating +tests/VGGSound/video/FpYuJwh_vo8_000070.mp4 chicken crowing +tests/VGGSound/video/CtcmYF7mufk_000030.mp4 rapping +tests/VGGSound/video/FpgEvLIh-jM_000052.mp4 spraying water +tests/VGGSound/video/FpjFjKdm9eI_000040.mp4 skateboarding +tests/VGGSound/video/Ctnf51mWdPI_000024.mp4 hail +tests/VGGSound/video/FpsBLinFYik_000012.mp4 police car (siren) +tests/VGGSound/video/CuS-ok0xG9g_000000.mp4 skidding +tests/VGGSound/video/FqZR5xJFOtI_000120.mp4 frog croaking +tests/VGGSound/video/CudxWnS7ukw_000030.mp4 playing banjo +tests/VGGSound/video/Fr0UnYeFVW0_000010.mp4 pumping water +tests/VGGSound/video/Fr6WH57YHxM_000070.mp4 mouse pattering +tests/VGGSound/video/FrCNRlxXulg_000012.mp4 woodpecker pecking tree +tests/VGGSound/video/FrHCQ5x2pNQ_000020.mp4 waterfall burbling +tests/VGGSound/video/FrJx8vk4GWs_000100.mp4 playing cornet +tests/VGGSound/video/FrLkQovl2Ok_000000.mp4 pheasant crowing +tests/VGGSound/video/Frgvl2G8pas_000350.mp4 opening or closing drawers +tests/VGGSound/video/FrnRa5sseEM_000104.mp4 playing castanets +tests/VGGSound/video/Cvwyf4tOrqc_000030.mp4 door slamming +tests/VGGSound/video/Fs462T7ODUQ_000030.mp4 sliding door +tests/VGGSound/video/FsBC8LIZ7eI_000045.mp4 hammering nails +tests/VGGSound/video/CwHSb1NOi4c_000030.mp4 playing vibraphone +tests/VGGSound/video/FsLaTZmP6Uw_000006.mp4 playing table tennis +tests/VGGSound/video/FsO5303dhUc_000041.mp4 sheep bleating +tests/VGGSound/video/FsO5303dhUc_000072.mp4 sheep bleating +tests/VGGSound/video/FsVcCpJ6Gak_000030.mp4 church bell ringing +tests/VGGSound/video/CwfMxqs0i4U_000030.mp4 playing tabla +tests/VGGSound/video/CwgPdC20hew_000310.mp4 playing zither +tests/VGGSound/video/Fsu8KjtWhPo_000003.mp4 cat caterwauling +tests/VGGSound/video/Fsu8KjtWhPo_000079.mp4 cat caterwauling +tests/VGGSound/video/FsywuRmOMTM_000030.mp4 playing acoustic guitar +tests/VGGSound/video/CwjSkhMXLNg_000152.mp4 metronome +tests/VGGSound/video/FszIzkuAyHo_000028.mp4 penguins braying +tests/VGGSound/video/Cwt7hCUOCDY_000030.mp4 people sneezing +tests/VGGSound/video/Ftap_CMYlfc_000327.mp4 playing oboe +tests/VGGSound/video/Ftk0nQ6FBO4_000010.mp4 bird wings flapping +tests/VGGSound/video/Fu-lnC9KbdI_000052.mp4 playing badminton +tests/VGGSound/video/Fue6UG6i74U_000089.mp4 playing table tennis +tests/VGGSound/video/Fum4pvH1Bf0_000451.mp4 roller coaster running +tests/VGGSound/video/Fum4pvH1Bf0_000476.mp4 roller coaster running +tests/VGGSound/video/Fup02r6oh-8_000030.mp4 cat purring +tests/VGGSound/video/FutkUYNyMUI_000000.mp4 blowtorch igniting +tests/VGGSound/video/FvM-7vvgy8c_000119.mp4 baby laughter +tests/VGGSound/video/Fvk3sWUjGuM_000030.mp4 wind rustling leaves +tests/VGGSound/video/FvmWB20IUaM_000184.mp4 people hiccup +tests/VGGSound/video/FwVYUHKoLtQ_000034.mp4 playing violin, fiddle +tests/VGGSound/video/Fwdl3YZeLRk_000080.mp4 playing cymbal +tests/VGGSound/video/FwjlaF2FSzg_000318.mp4 playing darts +tests/VGGSound/video/FwlNz4gc9s0_000030.mp4 people sniggering +tests/VGGSound/video/FwnRxfcUHIE_000029.mp4 chopping food +tests/VGGSound/video/FxZTKkmtKic_000000.mp4 people farting +tests/VGGSound/video/FxazUcUfh1o_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/FxkZsO4Kd78_000022.mp4 black capped chickadee calling +tests/VGGSound/video/Fxl4CpEjcQU_000008.mp4 fire crackling +tests/VGGSound/video/Fy0aCDmgnxg_000540.mp4 playing vibraphone +tests/VGGSound/video/Fz-dxPOWP58_000038.mp4 baby crying +tests/VGGSound/video/Fz1SAYd7js0_000030.mp4 thunder +tests/VGGSound/video/Fz2VI-6exXU_000030.mp4 mouse squeaking +tests/VGGSound/video/Fz99QvWup20_000030.mp4 raining +tests/VGGSound/video/FzS3nUnoDPQ_000110.mp4 playing timpani +tests/VGGSound/video/FzgCq9oAXGk_000000.mp4 basketball bounce +tests/VGGSound/video/Fzs-OIw-Atw_000000.mp4 chicken crowing +tests/VGGSound/video/J3SVckp6Gvk_000001.mp4 cupboard opening or closing +tests/VGGSound/video/FzzboZDObbs_000041.mp4 car engine starting +tests/VGGSound/video/J3_suqJKrug_000058.mp4 eletric blender running +tests/VGGSound/video/G--718JDmAQ_000000.mp4 people screaming +tests/VGGSound/video/G-7BfzMgZL8_000030.mp4 rapping +tests/VGGSound/video/J3koDvZY6Ag_000030.mp4 playing zither +tests/VGGSound/video/J3lsvPHrS-8_000577.mp4 smoke detector beeping +tests/VGGSound/video/J3yMNpeDo6Q_000030.mp4 cap gun shooting +tests/VGGSound/video/G-Z9WNT5asw_000074.mp4 missile launch +tests/VGGSound/video/J4IWp4vNFnw_000100.mp4 slot machine +tests/VGGSound/video/G-tO6Sqyiu4_000030.mp4 chicken clucking +tests/VGGSound/video/J5E3DDNxZGs_000078.mp4 cuckoo bird calling +tests/VGGSound/video/G0SUSiUozWM_000236.mp4 popping popcorn +tests/VGGSound/video/J5_m9Ee6A6M_000030.mp4 female speech, woman speaking +tests/VGGSound/video/J5a_yyh4KbQ_000112.mp4 tornado roaring +tests/VGGSound/video/G0w4RcrTJGA_000009.mp4 whale calling +tests/VGGSound/video/G1-XHWLgtlA_000000.mp4 playing cymbal +tests/VGGSound/video/J5om8xfMYYw_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/J5q9wLnXFh8_000206.mp4 playing bongo +tests/VGGSound/video/J5wBPfpzJgE_000000.mp4 mouse clicking +tests/VGGSound/video/J65y3xLtzhY_000016.mp4 telephone bell ringing +tests/VGGSound/video/J66wMnYRl7s_000306.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/G1OlHEvPRT8_000030.mp4 wind rustling leaves +tests/VGGSound/video/J6T4OwacRL0_000450.mp4 playing cymbal +tests/VGGSound/video/J6bVy2iKZZM_000138.mp4 swimming +tests/VGGSound/video/J6iYFxXuHrI_000654.mp4 disc scratching +tests/VGGSound/video/J75Aju6BsT8_000010.mp4 bird squawking +tests/VGGSound/video/G2Ko0bwzbVs_001549.mp4 playing lacrosse +tests/VGGSound/video/J7Nyf-zX5Q8_000033.mp4 chinchilla barking +tests/VGGSound/video/J7cctrtfYCw_000200.mp4 playing tabla +tests/VGGSound/video/G2jq2X-00n4_000000.mp4 car engine starting +tests/VGGSound/video/G3GR-m8Q3Zk_000070.mp4 machine gun shooting +tests/VGGSound/video/J8s8gIg1UFw_000103.mp4 civil defense siren +tests/VGGSound/video/G3Ze1ntr30g_000440.mp4 baby laughter +tests/VGGSound/video/G3c7Ye58Y2Q_000025.mp4 driving snowmobile +tests/VGGSound/video/J9CVwkhvBWI_000001.mp4 fox barking +tests/VGGSound/video/J9PJI1UwIQ4_000030.mp4 playing synthesizer +tests/VGGSound/video/J9TaPK4a3cw_000133.mp4 female singing +tests/VGGSound/video/G5-Q3SegMa0_000030.mp4 playing flute +tests/VGGSound/video/JANYxVn0O-M_000030.mp4 stream burbling +tests/VGGSound/video/JAShuewafAc_000051.mp4 spraying water +tests/VGGSound/video/G5LqrMcq1QE_000280.mp4 playing trombone +tests/VGGSound/video/G4YJUKofIHk_000005.mp4 cupboard opening or closing +tests/VGGSound/video/JA4NSoCs-Q0_000408.mp4 alarm clock ringing +tests/VGGSound/video/G4fTKotMoWI_000030.mp4 playing acoustic guitar +tests/VGGSound/video/G4kqAg8lxc4_000218.mp4 foghorn +tests/VGGSound/video/JBCFIEjHh2o_000005.mp4 eletric blender running +tests/VGGSound/video/G5jekk6z4tQ_000045.mp4 opening or closing car doors +tests/VGGSound/video/JBIGPZK6V5g_000040.mp4 people hiccup +tests/VGGSound/video/JBKDFk2o5kI_000018.mp4 air horn +tests/VGGSound/video/JBTEFp-SiAA_000171.mp4 playing tambourine +tests/VGGSound/video/JBbLvj_lHRI_000089.mp4 black capped chickadee calling +tests/VGGSound/video/G6sxdejGOqw_000100.mp4 eating with cutlery +tests/VGGSound/video/JCapiyzc_AA_000030.mp4 playing harmonica +tests/VGGSound/video/G7Fr50rWppo_000040.mp4 train wheels squealing +tests/VGGSound/video/G7IRrV4fNpU_000191.mp4 tractor digging +tests/VGGSound/video/G7JFyw4L_7A_000070.mp4 toilet flushing +tests/VGGSound/video/JDBu-3VCyWc_000110.mp4 playing accordion +tests/VGGSound/video/G7MdRJf7kMo_000031.mp4 strike lighter +tests/VGGSound/video/JDO_04901m0_000062.mp4 playing tympani +tests/VGGSound/video/G7ZE5J9gHMQ_000150.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/JDbNy8sAMOo_000023.mp4 cuckoo bird calling +tests/VGGSound/video/G7qe64jM9zs_000200.mp4 railroad car, train wagon +tests/VGGSound/video/JDrpFuzeeX4_000012.mp4 beat boxing +tests/VGGSound/video/JDtPwO8xuX4_000076.mp4 roller coaster running +tests/VGGSound/video/G7szS53-WZk_000022.mp4 strike lighter +tests/VGGSound/video/G880gxjj9dI_000030.mp4 dog whimpering +tests/VGGSound/video/G8VETC-kEio_000049.mp4 bathroom ventilation fan running +tests/VGGSound/video/G8o4P-aM8UE_000085.mp4 planing timber +tests/VGGSound/video/G8o4P-aM8UE_000196.mp4 planing timber +tests/VGGSound/video/JEWRZmHMQkY_000166.mp4 black capped chickadee calling +tests/VGGSound/video/JEaWbkxzFIk_000000.mp4 basketball bounce +tests/VGGSound/video/JEbcpvPiz5s_000280.mp4 black capped chickadee calling +tests/VGGSound/video/G93_g41lh7U_000032.mp4 dog growling +tests/VGGSound/video/JEgaH1K6Q8w_000024.mp4 cattle mooing +tests/VGGSound/video/JErx-AImWqk_000000.mp4 dog bow-wow +tests/VGGSound/video/G9XfEoNvHkA_000042.mp4 chinchilla barking +tests/VGGSound/video/JF-fcOJbN2k_000015.mp4 bowling impact +tests/VGGSound/video/G9ezMnDioco_000024.mp4 spraying water +tests/VGGSound/video/JFG4YvcJ3bo_000228.mp4 playing bongo +tests/VGGSound/video/JFJuEOZx1K4_000160.mp4 playing bass guitar +tests/VGGSound/video/G9vxeHobkfU_000058.mp4 ice cracking +tests/VGGSound/video/GA5llS6bq5Y_000105.mp4 skiing +tests/VGGSound/video/JFVs86eb014_000052.mp4 coyote howling +tests/VGGSound/video/JFX0wxrS5_o_000069.mp4 sea waves +tests/VGGSound/video/GAKUJVqdq3M_000268.mp4 foghorn +tests/VGGSound/video/JFiBXFFzT5c_000021.mp4 volcano explosion +tests/VGGSound/video/JFuARgBjOSk_000034.mp4 civil defense siren +tests/VGGSound/video/GAi7PmpjSww_000072.mp4 footsteps on snow +tests/VGGSound/video/JG9kAyMn8hM_000187.mp4 spraying water +tests/VGGSound/video/GB4zmWN0KxE_000062.mp4 people giggling +tests/VGGSound/video/JGeotTAFVWw_000444.mp4 sharpen knife +tests/VGGSound/video/GBLKj2d0iC4_000030.mp4 playing theremin +tests/VGGSound/video/JGqBknP7CG8_000062.mp4 volcano explosion +tests/VGGSound/video/GB_lCwieXTc_000420.mp4 ambulance siren +tests/VGGSound/video/JH7pyZNuk0A_000380.mp4 playing flute +tests/VGGSound/video/JHAQKzJ43Qo_000110.mp4 playing cymbal +tests/VGGSound/video/JHFAwMOuqk4_000110.mp4 goose honking +tests/VGGSound/video/GBifExKnaWI_000001.mp4 opening or closing car electric windows +tests/VGGSound/video/GBifExKnaWI_000012.mp4 opening or closing car electric windows +tests/VGGSound/video/JHL7f0njYzY_000293.mp4 playing bongo +tests/VGGSound/video/JHM3zMBQxTQ_000030.mp4 playing harp +tests/VGGSound/video/GC1ajVlK-ek_000050.mp4 railroad car, train wagon +tests/VGGSound/video/GCCJV53zu3w_000090.mp4 playing hammond organ +tests/VGGSound/video/GCDWVj9BjU8_000012.mp4 lions roaring +tests/VGGSound/video/GCO9y8PWSFg_000396.mp4 shot football +tests/VGGSound/video/GCVw4MarbJE_000470.mp4 wind noise +tests/VGGSound/video/JHi0b3OtazQ_000001.mp4 cuckoo bird calling +tests/VGGSound/video/GCo2uCLXvhk_000030.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/GCwUX8jj57o_000156.mp4 dog baying +tests/VGGSound/video/GD1vgJwYR4Q_000030.mp4 male speech, man speaking +tests/VGGSound/video/GD8XWhkFC50_000030.mp4 people sniggering +tests/VGGSound/video/GD8aF9jc1C8_000019.mp4 running electric fan +tests/VGGSound/video/GD8aF9jc1C8_000033.mp4 running electric fan +tests/VGGSound/video/GDDDe4v0IQo_000222.mp4 hammering nails +tests/VGGSound/video/JIG2w-yhwDk_000030.mp4 printer printing +tests/VGGSound/video/JIMJ7ewIoPA_000030.mp4 playing harmonica +tests/VGGSound/video/JIRCCthKAh0_000118.mp4 shot football +tests/VGGSound/video/GDXalnUbHYY_000031.mp4 ferret dooking +tests/VGGSound/video/JIVlpGCaiTs_000030.mp4 playing gong +tests/VGGSound/video/GDpUS5fvvq0_000210.mp4 people crowd +tests/VGGSound/video/JIemsK_0lXc_000364.mp4 playing bass drum +tests/VGGSound/video/JIjMPvlO00I_000148.mp4 wind noise +tests/VGGSound/video/JIjMPvlO00I_000182.mp4 wind noise +tests/VGGSound/video/JIy2No-Xg8A_000370.mp4 playing tabla +tests/VGGSound/video/JJ9WZ407_a8_000419.mp4 foghorn +tests/VGGSound/video/GESrnHr-SjU_000021.mp4 owl hooting +tests/VGGSound/video/JJFbs0sC8Hk_000540.mp4 stream burbling +tests/VGGSound/video/JJGG0i1B0e0_000334.mp4 playing timbales +tests/VGGSound/video/JJJsGblfDO4_000068.mp4 bathroom ventilation fan running +tests/VGGSound/video/JJMEP5noh34_000110.mp4 bird wings flapping +tests/VGGSound/video/JJTO6I15L6I_000037.mp4 playing shofar +tests/VGGSound/video/JJYrTD7P1Ys_000183.mp4 people nose blowing +tests/VGGSound/video/GEwEOl3uxC4_000250.mp4 fireworks banging +tests/VGGSound/video/JJcR5SHFcEM_000030.mp4 dog whimpering +tests/VGGSound/video/JK1VapgXi_c_000062.mp4 plastic bottle crushing +tests/VGGSound/video/JK1VapgXi_c_000115.mp4 plastic bottle crushing +tests/VGGSound/video/JKCvfKjTZX8_000050.mp4 firing cannon +tests/VGGSound/video/GFiFgEOFl_k_000433.mp4 squishing water +tests/VGGSound/video/GFkB9Par4M8_000580.mp4 chainsawing trees +tests/VGGSound/video/JKJ1okT8Vpw_000006.mp4 sea lion barking +tests/VGGSound/video/JKUSKYdYo9w_000000.mp4 people coughing +tests/VGGSound/video/JKX5mFZfLcY_000000.mp4 mouse clicking +tests/VGGSound/video/GG6XkHATIyw_000090.mp4 playing bass guitar +tests/VGGSound/video/JKbUVdMJAO8_000030.mp4 tapping guitar +tests/VGGSound/video/JKk65f_Twzk_000023.mp4 car engine idling +tests/VGGSound/video/JKpxK1rUW4A_000030.mp4 lawn mowing +tests/VGGSound/video/GGHhYzhaIgI_000300.mp4 playing harmonica +tests/VGGSound/video/JL9pKeXjNQ0_000010.mp4 chicken clucking +tests/VGGSound/video/GGpS5Zychoc_000053.mp4 lathe spinning +tests/VGGSound/video/GGpS5Zychoc_000222.mp4 lathe spinning +tests/VGGSound/video/GGpaLV0l1ys_000070.mp4 mouse clicking +tests/VGGSound/video/GGqC1H9BeTg_000180.mp4 electric grinder grinding +tests/VGGSound/video/JLKsLx_SGOU_000030.mp4 male speech, man speaking +tests/VGGSound/video/GH4Ae3x12Lk_000006.mp4 people sobbing +tests/VGGSound/video/JLfbuuIi720_000006.mp4 people sneezing +tests/VGGSound/video/JLtieDCSa6Y_000000.mp4 people coughing +tests/VGGSound/video/JLzD44Im1Ec_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/GHowpWCU9Lo_000030.mp4 ocean burbling +tests/VGGSound/video/GI1YUTNZxMM_000021.mp4 frog croaking +tests/VGGSound/video/GI3Vdc5WHJA_000214.mp4 warbler chirping +tests/VGGSound/video/GI3Vdc5WHJA_000225.mp4 warbler chirping +tests/VGGSound/video/JMF7NvH3qoE_000030.mp4 railroad car, train wagon +tests/VGGSound/video/GI7JterGTP0_000738.mp4 arc welding +tests/VGGSound/video/GII4Q_FEcU8_000028.mp4 tornado roaring +tests/VGGSound/video/GILXjY_tdME_000010.mp4 bird squawking +tests/VGGSound/video/GINmvzOpfvc_000006.mp4 bird chirping, tweeting +tests/VGGSound/video/GIQPZ8xVEXU_000024.mp4 hail +tests/VGGSound/video/JMVAOTC7hIU_000089.mp4 chopping food +tests/VGGSound/video/GIWJpC_OW1E_000023.mp4 people burping +tests/VGGSound/video/JMpqsef4w8g_000018.mp4 chopping wood +tests/VGGSound/video/GIvdJOuBLgI_000340.mp4 lip smacking +tests/VGGSound/video/JNDvDfDQnJQ_000030.mp4 firing cannon +tests/VGGSound/video/JNE-lrKk6Mg_000030.mp4 playing marimba, xylophone +tests/VGGSound/video/JNUF3mMSnSI_000010.mp4 church bell ringing +tests/VGGSound/video/JNbrtgeDFSk_000000.mp4 cat growling +tests/VGGSound/video/JNs5uQEJpJs_000030.mp4 sloshing water +tests/VGGSound/video/JNvGSWULJLA_000588.mp4 dinosaurs bellowing +tests/VGGSound/video/GK9b04Q2X90_000018.mp4 alarm clock ringing +tests/VGGSound/video/JO5CDrJHjHE_000130.mp4 pig oinking +tests/VGGSound/video/GKPDhTCffNw_000292.mp4 train wheels squealing +tests/VGGSound/video/GKPDhTCffNw_000468.mp4 train wheels squealing +tests/VGGSound/video/JOBCeJmvU5c_000348.mp4 penguins braying +tests/VGGSound/video/JOlFa2qjPig_000053.mp4 wind chime +tests/VGGSound/video/GL09sLcKW4M_000030.mp4 machine gun shooting +tests/VGGSound/video/JOwoXKwhiEs_000148.mp4 playing hockey +tests/VGGSound/video/GLIXnXZEOxY_000090.mp4 female singing +tests/VGGSound/video/JP637fg_ZC0_000030.mp4 playing theremin +tests/VGGSound/video/JP8ADbtN1UI_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/JPVRBbdykSw_000030.mp4 playing synthesizer +tests/VGGSound/video/JPZlyvPNZj4_000030.mp4 tapping guitar +tests/VGGSound/video/GMKY1SWCmIQ_000055.mp4 eletric blender running +tests/VGGSound/video/JPxi84TbWPo_000228.mp4 roller coaster running +tests/VGGSound/video/GMYaJVjQ8UQ_000424.mp4 hedge trimmer running +tests/VGGSound/video/JQ0I1NSdYkw_000015.mp4 elk bugling +tests/VGGSound/video/JQ1Z5-4HHK4_000040.mp4 subway, metro, underground +tests/VGGSound/video/JQ4RalNSjJk_000150.mp4 orchestra +tests/VGGSound/video/JQIBif9rBxQ_000065.mp4 playing washboard +tests/VGGSound/video/GN6kEiASxaE_000030.mp4 basketball bounce +tests/VGGSound/video/JQQcSiWzweM_000120.mp4 people marching +tests/VGGSound/video/JQ_4fYOd-R0_000030.mp4 toilet flushing +tests/VGGSound/video/GNQUA0bI5b0_000260.mp4 baby babbling +tests/VGGSound/video/GNSjTutOSG4_000119.mp4 playing bongo +tests/VGGSound/video/GNYKzDo4w7w_000110.mp4 machine gun shooting +tests/VGGSound/video/JQwirnKysXI_000030.mp4 dog barking +tests/VGGSound/video/GO26Uzae8JI_000227.mp4 people humming +tests/VGGSound/video/GO2Tf8KLJ14_000061.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/JR6hmr931Tw_000111.mp4 ice cracking +tests/VGGSound/video/JRIKh0r_We8_000098.mp4 playing congas +tests/VGGSound/video/JRIKh0r_We8_000229.mp4 playing congas +tests/VGGSound/video/GOTpllAaJe4_000000.mp4 people sneezing +tests/VGGSound/video/GOZBp_5NGtk_000016.mp4 playing bugle +tests/VGGSound/video/GO_1gBjIR1c_000030.mp4 helicopter +tests/VGGSound/video/JS68nchziLA_000029.mp4 playing congas +tests/VGGSound/video/GP2sIyEecxg_000126.mp4 driving snowmobile +tests/VGGSound/video/GPARKbP7AX4_000130.mp4 opening or closing car electric windows +tests/VGGSound/video/JSWC6dDd7UI_000320.mp4 bouncing on trampoline +tests/VGGSound/video/GPJ1uQwmNHk_000030.mp4 people screaming +tests/VGGSound/video/JSdALuTneBM_000030.mp4 playing synthesizer +tests/VGGSound/video/GPMfyC7Hcp0_000000.mp4 donkey, ass braying +tests/VGGSound/video/GQPPtMdnCFA_000007.mp4 eagle screaming +tests/VGGSound/video/GQPPtMdnCFA_000018.mp4 eagle screaming +tests/VGGSound/video/JU7451I9418_000030.mp4 playing bass guitar +tests/VGGSound/video/GQb6gTJD7zA_000000.mp4 playing flute +tests/VGGSound/video/GQge_Yn-SLM_000040.mp4 pumping water +tests/VGGSound/video/GQoZ_nRL5iA_000030.mp4 hair dryer drying +tests/VGGSound/video/GQvle2TmUtw_000010.mp4 cattle mooing +tests/VGGSound/video/JUnP6erXqAA_000075.mp4 people marching +tests/VGGSound/video/JUvqnkyxiSg_000013.mp4 sea lion barking +tests/VGGSound/video/GR5pgZNfU1U_000014.mp4 police car (siren) +tests/VGGSound/video/JV2OwVsxY_0_000000.mp4 otter growling +tests/VGGSound/video/GRYlCz5MWyo_000030.mp4 people sobbing +tests/VGGSound/video/JVD6Fl7US4E_000032.mp4 people gargling +tests/VGGSound/video/JVVbwIeoLxI_000271.mp4 spraying water +tests/VGGSound/video/JVZkqaHmc9Q_000050.mp4 playing accordion +tests/VGGSound/video/JV_iMt0idTU_000019.mp4 elk bugling +tests/VGGSound/video/GS8dnIAHj2A_000013.mp4 smoke detector beeping +tests/VGGSound/video/GSAMEMX_oAg_000200.mp4 playing ukulele +tests/VGGSound/video/GSAs2PDRs44_000010.mp4 playing squash +tests/VGGSound/video/JVjDa0NmfeE_000012.mp4 cat hissing +tests/VGGSound/video/JVjDa0NmfeE_000196.mp4 cat hissing +tests/VGGSound/video/GSSWxAo_oyo_000011.mp4 tap dancing +tests/VGGSound/video/GSTxgr6KkFs_000022.mp4 fire crackling +tests/VGGSound/video/JVtcvgiilEU_000030.mp4 playing harmonica +tests/VGGSound/video/JVu9sofg3yQ_000030.mp4 fire crackling +tests/VGGSound/video/JW3fRqCF5bY_000130.mp4 yodelling +tests/VGGSound/video/GT4WmInObm0_000236.mp4 footsteps on snow +tests/VGGSound/video/JWK-arpzfMo_000020.mp4 splashing water +tests/VGGSound/video/JWa9P_jRsCw_000321.mp4 people eating crisps +tests/VGGSound/video/JWd6vF4yfG8_000030.mp4 fire truck siren +tests/VGGSound/video/GTo5BqlFIZk_000007.mp4 airplane flyby +tests/VGGSound/video/GU782ddSBvk_000390.mp4 playing timpani +tests/VGGSound/video/GU7mq8uZgJo_000135.mp4 playing tennis +tests/VGGSound/video/GU7mq8uZgJo_000431.mp4 playing tennis +tests/VGGSound/video/JXMyZ929lpY_000173.mp4 race car, auto racing +tests/VGGSound/video/GUJCLsTnqTA_000174.mp4 telephone bell ringing +tests/VGGSound/video/JXZuAd9Lgew_000020.mp4 dog bow-wow +tests/VGGSound/video/GUJCLsTnqTA_000192.mp4 telephone bell ringing +tests/VGGSound/video/JXbDyO4vRiE_000192.mp4 car engine idling +tests/VGGSound/video/JXl3VdTNRtA_000020.mp4 people gargling +tests/VGGSound/video/JXmpEFLhr9E_000030.mp4 fireworks banging +tests/VGGSound/video/JXtOJM5Srs0_000003.mp4 sharpen knife +tests/VGGSound/video/JYeBZqAjKG8_000120.mp4 telephone bell ringing +tests/VGGSound/video/GVg8Oz2xqe4_000030.mp4 playing harpsichord +tests/VGGSound/video/GVj556hlo5A_000045.mp4 playing erhu +tests/VGGSound/video/GVk8l4S9NN0_000039.mp4 playing tympani +tests/VGGSound/video/JZHARPuQ6-w_000040.mp4 dog whimpering +tests/VGGSound/video/GW4XJ_zY-SQ_000010.mp4 ice cream truck, ice cream van +tests/VGGSound/video/JZnOGRCBW0I_000030.mp4 playing electric guitar +tests/VGGSound/video/GWTZtu3NOCc_000030.mp4 singing choir +tests/VGGSound/video/J_5UGUOiu3c_000000.mp4 elephant trumpeting +tests/VGGSound/video/GWlU-skSlAg_000100.mp4 black capped chickadee calling +tests/VGGSound/video/J_DCtp3XJ0Q_000030.mp4 printer printing +tests/VGGSound/video/GWvFDXjp9lU_000140.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/GX-QhoihLeI_000030.mp4 people running +tests/VGGSound/video/J_ZRXchuwNA_000030.mp4 horse clip-clop +tests/VGGSound/video/GX78OoBoroQ_000001.mp4 people crowd +tests/VGGSound/video/GX88nJyAb_I_000030.mp4 playing piano +tests/VGGSound/video/JaGUY5ULTok_000020.mp4 playing didgeridoo +tests/VGGSound/video/GXLeUXSVFYU_000030.mp4 playing banjo +tests/VGGSound/video/JaKy0YkFdsg_000071.mp4 bouncing on trampoline +tests/VGGSound/video/GXRooshOGuc_000030.mp4 playing banjo +tests/VGGSound/video/JaTfqRN3IrM_000020.mp4 sailing +tests/VGGSound/video/GXaiPM9oHWo_000010.mp4 mouse pattering +tests/VGGSound/video/GXuqtCdONDs_000091.mp4 playing bassoon +tests/VGGSound/video/GYDqNjRzkKM_000145.mp4 car engine idling +tests/VGGSound/video/GYQVFv7wGHY_000026.mp4 squishing water +tests/VGGSound/video/GYXA8WsJoFw_000030.mp4 sliding door +tests/VGGSound/video/GYZPCfnQpGU_000095.mp4 people marching +tests/VGGSound/video/JbJdDQT9pTQ_000176.mp4 squishing water +tests/VGGSound/video/GYZPCfnQpGU_000226.mp4 people marching +tests/VGGSound/video/JbPNmYKs7P0_000048.mp4 male speech, man speaking +tests/VGGSound/video/GYx6HNQbP1w_000030.mp4 playing electric guitar +tests/VGGSound/video/Jboz8dp-8nM_000000.mp4 lighting firecrackers +tests/VGGSound/video/GZFzwZiomoI_000010.mp4 wind chime +tests/VGGSound/video/JbuoNXVKqBo_000000.mp4 church bell ringing +tests/VGGSound/video/GZRZcKEtHzo_000010.mp4 playing harp +tests/VGGSound/video/GZkebn0ezfc_000000.mp4 zebra braying +tests/VGGSound/video/JcLpx0VveSw_000017.mp4 plastic bottle crushing +tests/VGGSound/video/JcLwOkkxaXo_000095.mp4 coyote howling +tests/VGGSound/video/JcMSFU-Twgw_000030.mp4 playing banjo +tests/VGGSound/video/JcMhOe-DHoE_000000.mp4 sea waves +tests/VGGSound/video/JcMhOe-DHoE_000018.mp4 sea waves +tests/VGGSound/video/JcZCmvfiwro_000030.mp4 car engine idling +tests/VGGSound/video/G_KiopmUUE0_000000.mp4 splashing water +tests/VGGSound/video/Jcxg_QuHyYE_000000.mp4 typing on typewriter +tests/VGGSound/video/Jcz09Kj0nAY_000490.mp4 typing on computer keyboard +tests/VGGSound/video/Jd9x5dQKzEM_000030.mp4 firing cannon +tests/VGGSound/video/JdBTLOZo3dA_000180.mp4 playing violin, fiddle +tests/VGGSound/video/G_jA6itU_FA_000125.mp4 beat boxing +tests/VGGSound/video/JdEUbNpEMQ4_000030.mp4 people farting +tests/VGGSound/video/JdNoEpN4kxE_000140.mp4 skateboarding +tests/VGGSound/video/JdfwV-zPImY_000024.mp4 people cheering +tests/VGGSound/video/GaK5NlF8CHY_000080.mp4 using sewing machines +tests/VGGSound/video/JdwokttDLSk_000180.mp4 sharpen knife +tests/VGGSound/video/JdzRzkTzmMw_000098.mp4 writing on blackboard with chalk +tests/VGGSound/video/GaSYzS6jVOM_000030.mp4 pumping water +tests/VGGSound/video/GaUw6QjaYPY_000093.mp4 ice cracking +tests/VGGSound/video/GafN7X_ifI0_000030.mp4 horse clip-clop +tests/VGGSound/video/Je_ZaBzYQpo_000360.mp4 roller coaster running +tests/VGGSound/video/JebRsHS1xic_000113.mp4 playing bassoon +tests/VGGSound/video/JebRsHS1xic_000144.mp4 playing bassoon +tests/VGGSound/video/JedVdAUc6ic_000077.mp4 playing hockey +tests/VGGSound/video/JefjXywAVzs_000171.mp4 telephone bell ringing +tests/VGGSound/video/JefjXywAVzs_000181.mp4 telephone bell ringing +tests/VGGSound/video/GbI7rZa22Zs_000005.mp4 otter growling +tests/VGGSound/video/JesyktMT-Dk_000010.mp4 playing cymbal +tests/VGGSound/video/GbI7rZa22Zs_000052.mp4 otter growling +tests/VGGSound/video/GbJ84ESfKOs_000030.mp4 playing harmonica +tests/VGGSound/video/Jf1fRu9YgfE_000064.mp4 hammering nails +tests/VGGSound/video/GbV_0hIYtqo_000049.mp4 cuckoo bird calling +tests/VGGSound/video/JfDeETDDwhM_000040.mp4 waterfall burbling +tests/VGGSound/video/Gbfx746UJN8_000030.mp4 tap dancing +tests/VGGSound/video/GbwEtN1P54M_000019.mp4 hail +tests/VGGSound/video/Gc0A0h1Wj-I_000560.mp4 playing tabla +tests/VGGSound/video/Jfw-FBJLiq8_000752.mp4 people eating apple +tests/VGGSound/video/GcbCOmNiVm8_000000.mp4 playing ukulele +tests/VGGSound/video/JgCZbn4JoRY_000030.mp4 people whispering +tests/VGGSound/video/JgKD-nqKTlQ_000021.mp4 striking pool +tests/VGGSound/video/JgKD-nqKTlQ_000297.mp4 striking pool +tests/VGGSound/video/GcqCHmHXEjo_000030.mp4 orchestra +tests/VGGSound/video/Gd0VJ127NYc_000010.mp4 people sobbing +tests/VGGSound/video/JgXnbgS_XBk_000480.mp4 skidding +tests/VGGSound/video/Jgg8HRAvNQM_000022.mp4 playing cornet +tests/VGGSound/video/GdFlyobMoAE_000009.mp4 playing bongo +tests/VGGSound/video/GdKodhqDt80_000265.mp4 eagle screaming +tests/VGGSound/video/JgxnHxZXzrI_000011.mp4 lighting firecrackers +tests/VGGSound/video/Jh-ills3nEQ_000030.mp4 eating with cutlery 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whale calling +tests/VGGSound/video/Gf-6YdQYRFQ_000013.mp4 cell phone buzzing +tests/VGGSound/video/Jj3Ie49Mzik_000020.mp4 people whistling +tests/VGGSound/video/GfA1vqAGWeY_000325.mp4 firing muskets +tests/VGGSound/video/JjGcpAvW-ks_000099.mp4 golf driving +tests/VGGSound/video/Gg0UlYgmSBA_000030.mp4 chinchilla barking +tests/VGGSound/video/JjmtxsOQEyg_000050.mp4 people crowd +tests/VGGSound/video/JjqHDGzcz6c_000100.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/Gg6Jx9UTBZI_000158.mp4 baltimore oriole calling +tests/VGGSound/video/GgEOurHF_No_000390.mp4 playing bagpipes +tests/VGGSound/video/GgI_d01sJ8I_000030.mp4 playing harmonica +tests/VGGSound/video/Jk5dHnmduAg_000320.mp4 goose honking +tests/VGGSound/video/Ggh5JPnDPNw_000035.mp4 playing double bass +tests/VGGSound/video/Ggh5JPnDPNw_000070.mp4 playing double bass +tests/VGGSound/video/GglIHiqClGM_000030.mp4 playing timpani +tests/VGGSound/video/Gh0gZF6SAFk_000192.mp4 air horn +tests/VGGSound/video/JkeCq47R1Mw_000009.mp4 hammering nails +tests/VGGSound/video/JkiZlL0YI0s_000090.mp4 playing trombone +tests/VGGSound/video/GhEPMDQZ174_000030.mp4 playing harpsichord +tests/VGGSound/video/JkqXWP4nddE_000012.mp4 snake hissing +tests/VGGSound/video/GhOXDKsmewM_000030.mp4 people babbling +tests/VGGSound/video/JlGNeE8vz9k_000001.mp4 penguins braying +tests/VGGSound/video/JlmUCZKjkuY_000244.mp4 playing violin, fiddle +tests/VGGSound/video/Gi7JTC44t18_000019.mp4 playing snare drum +tests/VGGSound/video/Jm5Qj05pMDQ_000250.mp4 raining +tests/VGGSound/video/JmBXrC4S5as_000525.mp4 forging swords +tests/VGGSound/video/GjATjLHsSQg_000200.mp4 playing zither +tests/VGGSound/video/Jmd7IviDxIU_000042.mp4 train horning +tests/VGGSound/video/GjOGszZsSj0_000000.mp4 opening or closing car doors +tests/VGGSound/video/GjYkSi1br2k_000324.mp4 playing lacrosse +tests/VGGSound/video/Jn7YGXtn09s_000322.mp4 airplane +tests/VGGSound/video/GjZbmBXxTBw_000340.mp4 playing squash +tests/VGGSound/video/GjoBV2mf8jo_000080.mp4 playing castanets +tests/VGGSound/video/GjoBV2mf8jo_000131.mp4 playing castanets +tests/VGGSound/video/GjqHhBTAO0U_000030.mp4 playing electronic organ +tests/VGGSound/video/JnXpTkm3nlc_000006.mp4 cat purring +tests/VGGSound/video/GkDN30ttEkc_000239.mp4 playing volleyball +tests/VGGSound/video/JnfMv9ti9Sw_000010.mp4 playing didgeridoo +tests/VGGSound/video/GkRcctMRKUc_000100.mp4 playing guiro +tests/VGGSound/video/GkStiQ3hR5g_000220.mp4 chicken crowing +tests/VGGSound/video/JoE9F2eO_jE_000080.mp4 using sewing machines +tests/VGGSound/video/JoKMKFX12x8_000003.mp4 dog baying +tests/VGGSound/video/JoRp-M_ZJ_k_000000.mp4 hail +tests/VGGSound/video/Gl64LXryFS8_000030.mp4 playing harp +tests/VGGSound/video/Gl91Nx0dVuU_000167.mp4 people eating apple +tests/VGGSound/video/Jogry7CVLzA_000007.mp4 people sneezing +tests/VGGSound/video/JorNR3IXDyc_000060.mp4 playing marimba, xylophone +tests/VGGSound/video/Jp3ggRQzpHM_000072.mp4 train whistling +tests/VGGSound/video/GlnhrMSrP5c_000014.mp4 cat growling 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engine accelerating, revving, vroom +tests/VGGSound/video/GwC4fiIM0mU_000611.mp4 ripping paper +tests/VGGSound/video/GwEpq_KxNyg_000000.mp4 air conditioning noise +tests/VGGSound/video/K-0qmhvJyzE_000010.mp4 playing marimba, xylophone +tests/VGGSound/video/GwWXDwqgWjo_000335.mp4 playing tuning fork +tests/VGGSound/video/K-JfatjTpQw_000119.mp4 hedge trimmer running +tests/VGGSound/video/K-PitCewkDg_000068.mp4 cheetah chirrup +tests/VGGSound/video/K-PitCewkDg_000080.mp4 cheetah chirrup +tests/VGGSound/video/K-Zg1-fR9kU_000088.mp4 forging swords +tests/VGGSound/video/Gx4Ua7b7qcI_000016.mp4 blowtorch igniting +tests/VGGSound/video/K082-sINKZI_000223.mp4 yodelling +tests/VGGSound/video/GxT7fj69ni4_000056.mp4 chimpanzee pant-hooting +tests/VGGSound/video/GxTD3hqJoM0_000146.mp4 writing on blackboard with chalk +tests/VGGSound/video/GxTD3hqJoM0_000564.mp4 writing on blackboard with chalk +tests/VGGSound/video/K0EiS8UsJPg_000030.mp4 people eating +tests/VGGSound/video/Gxn7TpFo64w_000114.mp4 mosquito buzzing +tests/VGGSound/video/GxnUY0u8fY8_000030.mp4 sailing +tests/VGGSound/video/GxqqrBIQPM8_000635.mp4 golf driving +tests/VGGSound/video/K0Y8oGYR7lw_000010.mp4 disc scratching +tests/VGGSound/video/K0nW8q0RzTU_000030.mp4 opening or closing drawers +tests/VGGSound/video/GyHmkrrU0ZM_000125.mp4 beat boxing +tests/VGGSound/video/GydL9SSi7U0_000070.mp4 pigeon, dove cooing +tests/VGGSound/video/K1ASf4xAexc_000030.mp4 parrot talking +tests/VGGSound/video/K1PzpuR6CqY_000010.mp4 playing trumpet +tests/VGGSound/video/K1R_N_pysRs_000033.mp4 tornado roaring +tests/VGGSound/video/K1WTjvf8hG8_000020.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/K1ZwAX4xO1w_000339.mp4 people eating apple +tests/VGGSound/video/K1dvHvl0RGo_000030.mp4 hair dryer drying +tests/VGGSound/video/GzE2uJf5vb4_000129.mp4 car engine idling +tests/VGGSound/video/K1mSyipUj38_000030.mp4 singing choir +tests/VGGSound/video/GzPqONtFJXA_000060.mp4 lions roaring +tests/VGGSound/video/GzQqeK3gL50_000472.mp4 hedge trimmer running +tests/VGGSound/video/Gzb4oL8wobU_000738.mp4 golf driving +tests/VGGSound/video/K2ObTK7rK58_000020.mp4 child speech, kid speaking +tests/VGGSound/video/K2TcJFtuvDE_000006.mp4 foghorn +tests/VGGSound/video/K2bRcQYebN4_000004.mp4 magpie calling +tests/VGGSound/video/K2h6UiZSoZ4_000030.mp4 people shuffling +tests/VGGSound/video/K2nicVw_XRM_000089.mp4 people cheering +tests/VGGSound/video/H-bTMbePj0A_000121.mp4 playing steelpan +tests/VGGSound/video/K2pP4vbDrBw_000108.mp4 playing congas +tests/VGGSound/video/H0AidwYu8hs_000184.mp4 people gargling +tests/VGGSound/video/K3ByFtd0ugA_000148.mp4 playing oboe +tests/VGGSound/video/K3CenN7d30Y_000030.mp4 chicken crowing +tests/VGGSound/video/H0MTqgT8UkU_000110.mp4 ocean burbling +tests/VGGSound/video/H0W4T1FCf_A_000052.mp4 tornado roaring +tests/VGGSound/video/K3Q8Gi6oPIg_000030.mp4 chicken crowing +tests/VGGSound/video/K3dENGPyIqc_000050.mp4 playing hammond organ +tests/VGGSound/video/H18aK9HhNSM_000030.mp4 playing ukulele 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barking +tests/VGGSound/video/K7dXkfKAano_000576.mp4 people eating noodle +tests/VGGSound/video/H4o97PEXzBA_000040.mp4 playing theremin +tests/VGGSound/video/H4rdJlSSt5Y_000030.mp4 playing banjo +tests/VGGSound/video/K8BC9e4Bspg_000151.mp4 hammering nails +tests/VGGSound/video/H5XxUukegis_000002.mp4 coyote howling +tests/VGGSound/video/K8IPtE5e0Ms_000070.mp4 swimming +tests/VGGSound/video/K8On7nUJuP8_000030.mp4 baby crying +tests/VGGSound/video/H5iBnsKsKMM_000000.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/H5rRqioLDxY_000030.mp4 baby laughter +tests/VGGSound/video/K8yPsF_C8V0_000070.mp4 splashing water +tests/VGGSound/video/H61TyC6jhEM_000460.mp4 playing hammond organ +tests/VGGSound/video/H692PyayBt4_000000.mp4 playing bagpipes +tests/VGGSound/video/H6H3B1LLWw8_000440.mp4 train horning +tests/VGGSound/video/K9bWqZczmeA_000780.mp4 people slapping +tests/VGGSound/video/K9wdSR3B7s0_000130.mp4 railroad car, train wagon +tests/VGGSound/video/H6RE7PjUrjI_000015.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/H6XSxmkHNxA_000030.mp4 frog croaking +tests/VGGSound/video/KAAt1is-Z04_000030.mp4 people finger snapping +tests/VGGSound/video/H6c8ZDrdUaM_000030.mp4 fire truck siren +tests/VGGSound/video/KAVxfY_grPQ_000000.mp4 playing trumpet +tests/VGGSound/video/KA_QeIcCnnc_000488.mp4 firing muskets +tests/VGGSound/video/KAdUPttkyIs_000285.mp4 francolin calling +tests/VGGSound/video/KAlc9vINwU8_000088.mp4 turkey gobbling +tests/VGGSound/video/KAuoWt8dTJs_000061.mp4 playing guiro +tests/VGGSound/video/KAuoWt8dTJs_000087.mp4 playing guiro +tests/VGGSound/video/KBAW9bg6tPk_000020.mp4 people crowd +tests/VGGSound/video/KBHROttRHyU_000516.mp4 air conditioning noise +tests/VGGSound/video/H7cajTyrLq4_000046.mp4 people humming +tests/VGGSound/video/KBOdG9xNLaA_000006.mp4 dog baying +tests/VGGSound/video/H7hvpCMoScQ_000030.mp4 dog barking +tests/VGGSound/video/H7leMctSTMc_000030.mp4 pig oinking +tests/VGGSound/video/H7rd0MW1s40_000005.mp4 penguins braying +tests/VGGSound/video/KBi5yWlVwpQ_000107.mp4 sailing +tests/VGGSound/video/KBi5yWlVwpQ_000182.mp4 sailing +tests/VGGSound/video/KBmULhoBXDY_000010.mp4 playing tennis +tests/VGGSound/video/H85puQUqrQY_000150.mp4 male speech, man speaking +tests/VGGSound/video/KC-wRA_SwK0_000140.mp4 helicopter +tests/VGGSound/video/H88-QfYsn2s_000496.mp4 swimming +tests/VGGSound/video/H88svrfkkNU_000000.mp4 basketball bounce +tests/VGGSound/video/H8CZG1Yu74Y_000040.mp4 splashing water +tests/VGGSound/video/H8GHEQR7iH4_000332.mp4 bouncing on trampoline +tests/VGGSound/video/H8IoMxnjzYw_000019.mp4 striking bowling +tests/VGGSound/video/H8KqQWxixQU_000030.mp4 playing harmonica +tests/VGGSound/video/KCXiP1di11k_000028.mp4 people booing +tests/VGGSound/video/H8q7kRegenA_000490.mp4 playing vibraphone +tests/VGGSound/video/H942QC8B3bc_000030.mp4 horse clip-clop +tests/VGGSound/video/H9JA9CibQmU_000210.mp4 baby babbling +tests/VGGSound/video/KDE80kI1Kf0_000040.mp4 owl hooting +tests/VGGSound/video/H9nKSRtcxiY_000080.mp4 turkey gobbling +tests/VGGSound/video/KDgNhw175fM_000089.mp4 yodelling +tests/VGGSound/video/H9ozCKhRl5A_000030.mp4 sliding door +tests/VGGSound/video/HA0eZ_FDVUg_000050.mp4 tractor digging +tests/VGGSound/video/HAEoz3VbaP8_000000.mp4 playing ukulele +tests/VGGSound/video/HAKTtmFemxQ_000120.mp4 cap gun shooting +tests/VGGSound/video/HALbfdYE3hM_000215.mp4 playing oboe +tests/VGGSound/video/HAVPN432kNA_000071.mp4 rope skipping +tests/VGGSound/video/KEprnXLR6Z4_000010.mp4 elk bugling +tests/VGGSound/video/HAiGGj4Dl1A_000025.mp4 gibbon howling +tests/VGGSound/video/HAkUrI9yU8U_000062.mp4 airplane flyby +tests/VGGSound/video/HAqkyELOqH0_000250.mp4 air conditioning noise +tests/VGGSound/video/HB0Jom8ro34_000159.mp4 foghorn +tests/VGGSound/video/KF8MZdTRk1Q_000117.mp4 playing tympani +tests/VGGSound/video/KG3ODTw7hM4_000090.mp4 mouse pattering +tests/VGGSound/video/KG4T5A7hfRc_000170.mp4 playing hammond organ +tests/VGGSound/video/HByDu4uOFY4_000246.mp4 playing trumpet +tests/VGGSound/video/KGXwmVakzjQ_000340.mp4 skateboarding +tests/VGGSound/video/KGYzC7wySkI_000159.mp4 wood thrush calling +tests/VGGSound/video/HC4f5gUkLME_000171.mp4 playing mandolin +tests/VGGSound/video/KGvBATcuyLY_000010.mp4 wind chime +tests/VGGSound/video/HCAiOseeH1o_000086.mp4 eagle screaming +tests/VGGSound/video/HCC9JldRsNc_000000.mp4 basketball bounce +tests/VGGSound/video/KH7rmkQNQgY_000260.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/HCQZOh2faww_000300.mp4 playing timpani +tests/VGGSound/video/HCVBXcpBIU0_000199.mp4 playing lacrosse +tests/VGGSound/video/KHVZFbmt8xk_000030.mp4 female speech, woman speaking +tests/VGGSound/video/KHdiD8unGsg_000030.mp4 horse neighing +tests/VGGSound/video/KHkVbX3cdcU_000127.mp4 wind chime +tests/VGGSound/video/HChruX6Mhaw_000509.mp4 air horn +tests/VGGSound/video/HClQ6AlwwVM_000006.mp4 fireworks banging +tests/VGGSound/video/HCmwbTIHIcw_000002.mp4 snake hissing +tests/VGGSound/video/HCnJrkCqimQ_000000.mp4 people slapping +tests/VGGSound/video/HCwHyViV2oU_000073.mp4 police radio chatter +tests/VGGSound/video/KI9f7Gclu28_000025.mp4 golf driving +tests/VGGSound/video/KI9f7Gclu28_000054.mp4 golf driving +tests/VGGSound/video/KI9v2anRrw4_000048.mp4 alarm clock ringing +tests/VGGSound/video/HDWZu2roOgU_000032.mp4 people giggling +tests/VGGSound/video/HDvPMEU33HM_000089.mp4 people cheering +tests/VGGSound/video/KIpOaDNuZG4_000110.mp4 eletric blender running +tests/VGGSound/video/HEBbCfH6xME_000003.mp4 telephone bell ringing +tests/VGGSound/video/KIudjmj3ac4_000390.mp4 eating with cutlery +tests/VGGSound/video/KJMpCjosdu4_000051.mp4 lathe spinning +tests/VGGSound/video/KJcjnqKzqfw_000115.mp4 playing congas +tests/VGGSound/video/HFQrHE2H8Ho_000080.mp4 playing piano +tests/VGGSound/video/KK5AClS1mxA_000651.mp4 chopping food +tests/VGGSound/video/KKFdi5WQ0V0_000256.mp4 train horning +tests/VGGSound/video/HFi-z3dCVZE_000000.mp4 playing trumpet +tests/VGGSound/video/KKYr8I5AxoQ_000006.mp4 sea waves +tests/VGGSound/video/HGE4FaX-Roc_000009.mp4 cat hissing +tests/VGGSound/video/KL0x2wC-vF0_000000.mp4 playing trumpet +tests/VGGSound/video/HGlv3xtLnTs_000024.mp4 people booing +tests/VGGSound/video/HGlv3xtLnTs_000058.mp4 people booing +tests/VGGSound/video/HGpEAOwHBuI_000004.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/KLWutuuzmco_000012.mp4 pheasant crowing +tests/VGGSound/video/KLd-rJMoeko_000020.mp4 duck quacking +tests/VGGSound/video/HHYa8yc6qv8_000009.mp4 cutting hair with electric trimmers +tests/VGGSound/video/HHg3q4Dl7bg_000214.mp4 shot football +tests/VGGSound/video/KM-k9Ozvuec_000291.mp4 people eating apple +tests/VGGSound/video/HIDb-C5YRa4_000010.mp4 people cheering +tests/VGGSound/video/HINQ5Td2jZc_000090.mp4 people sniggering +tests/VGGSound/video/HIQ63_WoKwg_000030.mp4 playing trombone +tests/VGGSound/video/HIT2YWOALto_000002.mp4 dinosaurs bellowing +tests/VGGSound/video/HIcEcJ7R1Qg_000160.mp4 strike lighter +tests/VGGSound/video/KMrpYyZNpWw_000025.mp4 sailing +tests/VGGSound/video/KMs0Ijf9pCM_000024.mp4 snake rattling +tests/VGGSound/video/HIn8Gt_bc5Y_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/HIvjBlAgzns_000341.mp4 bouncing on trampoline +tests/VGGSound/video/KNU7Ry8zjTI_000030.mp4 people burping +tests/VGGSound/video/HJ6T0inw2mo_000012.mp4 wood thrush calling +tests/VGGSound/video/HJGtRMubleU_000030.mp4 dog whimpering +tests/VGGSound/video/HJg4jZNv1pc_000150.mp4 people coughing +tests/VGGSound/video/HJhFxiKjBoo_000030.mp4 horse clip-clop +tests/VGGSound/video/HJrYNAIm1AY_000110.mp4 dog baying +tests/VGGSound/video/KO79WAx6G6M_000020.mp4 missile launch +tests/VGGSound/video/KOBKIOq594g_000030.mp4 cattle, bovinae cowbell +tests/VGGSound/video/KOFUT2G63qU_000038.mp4 woodpecker pecking tree +tests/VGGSound/video/HK6HLZqAe9I_000142.mp4 people battle cry +tests/VGGSound/video/KOVA158NXRQ_000030.mp4 playing french horn +tests/VGGSound/video/HKN2548Ts6A_000030.mp4 typing on computer keyboard +tests/VGGSound/video/KOVw582M79I_000220.mp4 driving buses +tests/VGGSound/video/KOay8stLOxw_000049.mp4 forging swords +tests/VGGSound/video/HKhBeY4I830_000009.mp4 cat hissing +tests/VGGSound/video/KP1MVFFFaEc_000043.mp4 sloshing water +tests/VGGSound/video/HKkTmjvMq38_000143.mp4 people sniggering +tests/VGGSound/video/KPG9s_s8siA_000030.mp4 playing vibraphone +tests/VGGSound/video/HKt34k7B7BA_000040.mp4 playing volleyball +tests/VGGSound/video/HKvc2fgaeak_000189.mp4 playing tambourine +tests/VGGSound/video/HKvimMUXe7c_000181.mp4 people eating crisps +tests/VGGSound/video/KPiPM6wF0rw_000030.mp4 horse neighing +tests/VGGSound/video/KPjiLF72m1g_000030.mp4 people eating +tests/VGGSound/video/KPlEhcc8gF8_000048.mp4 playing bugle +tests/VGGSound/video/HLn-Q2t8NH8_000000.mp4 playing washboard +tests/VGGSound/video/KPyYUly5xCc_000350.mp4 railroad car, train wagon +tests/VGGSound/video/HLncJNvEBH8_000030.mp4 wind rustling leaves +tests/VGGSound/video/HLsRePLObfI_000030.mp4 playing steelpan +tests/VGGSound/video/KQAR_64a35I_000011.mp4 lions roaring +tests/VGGSound/video/HLxIwN7KAks_000020.mp4 people sneezing +tests/VGGSound/video/HLz3N5nG8fQ_000030.mp4 people clapping +tests/VGGSound/video/KQGJCKwsFbA_000157.mp4 sharpen knife +tests/VGGSound/video/HMF7YxjVg6w_000030.mp4 playing electronic organ +tests/VGGSound/video/HMhAM5aicvI_000030.mp4 playing electronic organ +tests/VGGSound/video/HMnF8n9c5-Y_000030.mp4 people coughing +tests/VGGSound/video/KR5Iu9gyLXo_000030.mp4 playing bagpipes +tests/VGGSound/video/HMxxGXjfrpU_000085.mp4 rope skipping +tests/VGGSound/video/HMyRA33XJRM_000077.mp4 playing glockenspiel +tests/VGGSound/video/HN4KMLVaT74_000061.mp4 magpie calling +tests/VGGSound/video/KRE27QNl7Qs_000021.mp4 writing on blackboard with chalk +tests/VGGSound/video/KRKX_UtYV9c_000030.mp4 playing didgeridoo +tests/VGGSound/video/HNEGSr6z4oQ_000591.mp4 people marching +tests/VGGSound/video/HNNDBeHGlBc_000015.mp4 snake rattling +tests/VGGSound/video/HN_mjGAWjJ4_000171.mp4 playing timbales +tests/VGGSound/video/KRtYq1p2Tyg_000006.mp4 playing darts +tests/VGGSound/video/HNsCHTO1hLI_000031.mp4 plastic bottle crushing +tests/VGGSound/video/KRxX4rRL1Qs_000003.mp4 hail +tests/VGGSound/video/HNtNFaXeYQ4_000140.mp4 playing harp +tests/VGGSound/video/HO7EiiblQe4_000030.mp4 playing bagpipes +tests/VGGSound/video/HOGj4kLWmxs_000030.mp4 playing hammond organ +tests/VGGSound/video/HOOK6E_Hogg_000030.mp4 ambulance siren +tests/VGGSound/video/KSOxq1eovtw_000030.mp4 child speech, kid speaking +tests/VGGSound/video/HOTIBJemUB8_000087.mp4 playing bongo +tests/VGGSound/video/HO_dmqI-nmw_000152.mp4 ice cracking +tests/VGGSound/video/HOhpKjQWqxc_000030.mp4 people belly laughing +tests/VGGSound/video/HOm3GkVl8D8_000040.mp4 chinchilla barking +tests/VGGSound/video/KS_5Qiec4AI_000009.mp4 warbler chirping +tests/VGGSound/video/KS_5Qiec4AI_000200.mp4 warbler chirping +tests/VGGSound/video/HOqx0IZGgBk_000286.mp4 train whistling +tests/VGGSound/video/KSgolImRApk_000045.mp4 whale calling +tests/VGGSound/video/HOyov3OS0a0_000054.mp4 underwater bubbling +tests/VGGSound/video/HP4bUf_w4hU_000522.mp4 people eating noodle +tests/VGGSound/video/KSx1Y32_Wd0_000062.mp4 playing oboe +tests/VGGSound/video/KT-rYg9B_CM_000420.mp4 skateboarding +tests/VGGSound/video/KT85P9vU2GE_000138.mp4 foghorn +tests/VGGSound/video/HPOBl_BzybA_000005.mp4 door slamming +tests/VGGSound/video/KTHsyIQI2L0_000200.mp4 dog growling +tests/VGGSound/video/HPfBYRU8tVM_000030.mp4 female speech, woman speaking +tests/VGGSound/video/HPhPfOyOguw_000240.mp4 people finger snapping +tests/VGGSound/video/HPq-Zi2XlCM_000017.mp4 spraying water +tests/VGGSound/video/HQ8eR2lvjSE_000030.mp4 driving motorcycle +tests/VGGSound/video/HQAaW-5IwHo_000002.mp4 cricket chirping +tests/VGGSound/video/HQAaW-5IwHo_000016.mp4 cricket chirping +tests/VGGSound/video/KTo-TxTrfUE_000050.mp4 hair dryer drying +tests/VGGSound/video/HQOb1LjygAU_000030.mp4 sloshing water +tests/VGGSound/video/HQSHJVH2x4w_000024.mp4 lathe spinning +tests/VGGSound/video/HQb2jhmw1BE_000310.mp4 playing timpani +tests/VGGSound/video/KTwbiaP1JWw_000015.mp4 fox barking +tests/VGGSound/video/HQfF_JXrUUI_000030.mp4 sliding door +tests/VGGSound/video/KU0aL_iR0_I_000560.mp4 people belly laughing +tests/VGGSound/video/HQr1YvLzoZo_000146.mp4 disc scratching +tests/VGGSound/video/KUKKg1VS2Pg_000638.mp4 chimpanzee pant-hooting +tests/VGGSound/video/HREgdi88SL0_000035.mp4 chopping food +tests/VGGSound/video/KUoMl-m6w-o_000026.mp4 people burping +tests/VGGSound/video/KUrZc88Ma3g_000010.mp4 playing harmonica +tests/VGGSound/video/HRaMaCCoRCY_000210.mp4 child speech, kid speaking +tests/VGGSound/video/KVQ-hdv-b5w_000006.mp4 volcano explosion +tests/VGGSound/video/HRuuSVGbbns_000000.mp4 mouse squeaking +tests/VGGSound/video/KVqJ750fZmY_000010.mp4 playing gong +tests/VGGSound/video/KVuoi20iigU_000280.mp4 lighting firecrackers +tests/VGGSound/video/HS100sqEvVk_000002.mp4 writing on blackboard with chalk +tests/VGGSound/video/HS28EUWt8dE_000110.mp4 people screaming +tests/VGGSound/video/KWCQUZQ9D-Q_000030.mp4 child speech, kid speaking +tests/VGGSound/video/KWGON3DlOdw_000040.mp4 subway, metro, underground +tests/VGGSound/video/HSGejM8DhX4_000093.mp4 cupboard opening or closing +tests/VGGSound/video/HSPBrLMYWQA_000030.mp4 cat meowing +tests/VGGSound/video/HShbaC9ORSo_000410.mp4 driving motorcycle +tests/VGGSound/video/KWxQKX94CL4_000085.mp4 owl hooting +tests/VGGSound/video/HTGUvmdO8TI_000370.mp4 playing tabla +tests/VGGSound/video/HTM6oZp9Jg8_000140.mp4 bird chirping, tweeting +tests/VGGSound/video/HTPHilkU_BY_000010.mp4 playing zither +tests/VGGSound/video/KXO4lC4LjxI_000011.mp4 lathe spinning +tests/VGGSound/video/KXO4lC4LjxI_000095.mp4 lathe spinning +tests/VGGSound/video/KXRngbBe0bg_000080.mp4 tapping guitar +tests/VGGSound/video/KXVWbk9RRRs_000030.mp4 playing steelpan +tests/VGGSound/video/KXkPJ_xgPZg_000004.mp4 cat hissing +tests/VGGSound/video/HU7oqkJeItQ_000000.mp4 playing ukulele +tests/VGGSound/video/KXlV03qy1K4_000027.mp4 crow cawing +tests/VGGSound/video/KXn7InqM3yo_000030.mp4 people crowd +tests/VGGSound/video/KXuB62SMFvA_000030.mp4 playing theremin +tests/VGGSound/video/KY7vlwsv2ls_000320.mp4 swimming +tests/VGGSound/video/HUgKjkp-7M8_000013.mp4 owl hooting +tests/VGGSound/video/HUm2vzjI6DQ_000220.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/KYJrBYZ_EJI_000066.mp4 rope skipping +tests/VGGSound/video/HUyzxJCsM3k_000220.mp4 playing clarinet +tests/VGGSound/video/HV1J_actdHE_000110.mp4 cap gun shooting +tests/VGGSound/video/HVHe2kibCQU_000005.mp4 cupboard opening or closing +tests/VGGSound/video/HVHe2kibCQU_000019.mp4 cupboard opening or closing +tests/VGGSound/video/KYn98MMX3pg_000213.mp4 people eating noodle +tests/VGGSound/video/KYnOCgdquQU_000345.mp4 airplane +tests/VGGSound/video/HVSrOlC3270_000045.mp4 dog howling +tests/VGGSound/video/KZ1HTf3ifAI_000032.mp4 footsteps on snow +tests/VGGSound/video/KZ1j9f31yN4_000030.mp4 duck quacking +tests/VGGSound/video/HVnJ1PKOR-4_000077.mp4 slot machine +tests/VGGSound/video/KZFD1lRFNaw_000168.mp4 hammering nails +tests/VGGSound/video/KZdCMu_uTlI_000048.mp4 golf driving +tests/VGGSound/video/KZoSQEDgZG4_000001.mp4 child speech, kid speaking +tests/VGGSound/video/KZqhxN-3zzc_000024.mp4 police radio chatter +tests/VGGSound/video/HWAeBWk6O-g_000033.mp4 police car (siren) +tests/VGGSound/video/K_EsxukdNXM_000000.mp4 cattle mooing +tests/VGGSound/video/K_EsxukdNXM_000030.mp4 cattle mooing +tests/VGGSound/video/K_GkTGJxTSk_000019.mp4 chicken clucking +tests/VGGSound/video/HWjQnxlvwa0_000430.mp4 machine gun shooting +tests/VGGSound/video/K_UpUg4-MGw_000001.mp4 scuba diving +tests/VGGSound/video/K_UqUbZjYRA_000002.mp4 cat growling +tests/VGGSound/video/KaAMIcVOC9s_000408.mp4 scuba diving +tests/VGGSound/video/HXj5NUoTohs_000130.mp4 playing didgeridoo +tests/VGGSound/video/HXq7yu1jWJE_000035.mp4 sheep bleating +tests/VGGSound/video/HXqj_9oZReQ_000014.mp4 disc scratching +tests/VGGSound/video/HY-4ilSDR1o_000041.mp4 people gargling +tests/VGGSound/video/KacYEZwBTY4_000050.mp4 playing timbales +tests/VGGSound/video/HYQ8F3qtKEA_000083.mp4 playing erhu +tests/VGGSound/video/HYojEoDJiQc_000049.mp4 hammering nails +tests/VGGSound/video/KbIIrQtBjk8_000070.mp4 owl hooting +tests/VGGSound/video/KbOySeP46l4_000570.mp4 people belly laughing +tests/VGGSound/video/HZ-XFC5qzyM_000450.mp4 people running +tests/VGGSound/video/HZ5fPk0bS9g_000123.mp4 playing tuning fork +tests/VGGSound/video/HZ5fPk0bS9g_000276.mp4 playing tuning fork +tests/VGGSound/video/HZDIyvYqEC8_000001.mp4 magpie calling +tests/VGGSound/video/HZDIyvYqEC8_000066.mp4 magpie calling +tests/VGGSound/video/HZHb51xCZ24_000094.mp4 children shouting +tests/VGGSound/video/Kc1yfZngUms_000009.mp4 child singing +tests/VGGSound/video/HZRJxOXw2os_000207.mp4 people marching +tests/VGGSound/video/Kc9mICcGqp8_000076.mp4 arc welding +tests/VGGSound/video/KcC_g1wPovM_000080.mp4 waterfall burbling +tests/VGGSound/video/HZf02v6DyyY_000030.mp4 fire crackling +tests/VGGSound/video/KcV64MycgT4_000000.mp4 alligators, crocodiles hissing +tests/VGGSound/video/KcV64MycgT4_000019.mp4 alligators, crocodiles hissing +tests/VGGSound/video/H_-2X4LNDH0_000001.mp4 typing on typewriter +tests/VGGSound/video/KcWPqFhrna0_000030.mp4 baby laughter +tests/VGGSound/video/KcYCxfTPfY0_000000.mp4 sea lion barking +tests/VGGSound/video/H_DwA0vzKXI_000260.mp4 mosquito buzzing +tests/VGGSound/video/KcjSOd4R7VY_000021.mp4 frog croaking +tests/VGGSound/video/Kcv4qtxnA0Y_000192.mp4 arc welding +tests/VGGSound/video/Kd7aHdOwh0I_000030.mp4 playing electric guitar +tests/VGGSound/video/H_rYM_x08Iw_000070.mp4 basketball bounce +tests/VGGSound/video/KdBwrU3jrHw_000613.mp4 ripping paper +tests/VGGSound/video/KdIIocq3jeM_000409.mp4 lip smacking +tests/VGGSound/video/HaGQnzWOAUo_000434.mp4 hedge trimmer running +tests/VGGSound/video/HaLZD-2ppdU_000008.mp4 lions growling +tests/VGGSound/video/KdNOda5craI_000112.mp4 playing shofar +tests/VGGSound/video/KdPjKD7F1-Y_000390.mp4 people running +tests/VGGSound/video/KdhMumvB4vs_000030.mp4 rapping +tests/VGGSound/video/KdioKgAO4cQ_000059.mp4 playing timbales +tests/VGGSound/video/HaR6dHxe2B0_000009.mp4 people giggling +tests/VGGSound/video/KdxSaA69fm8_000030.mp4 singing choir +tests/VGGSound/video/Ke1oAMn5aXE_000060.mp4 ocean burbling +tests/VGGSound/video/HajY_r6RNy0_000090.mp4 playing accordion +tests/VGGSound/video/Ke78LgKo0bA_000061.mp4 playing volleyball +tests/VGGSound/video/KeKNhZElHtg_000560.mp4 mouse clicking +tests/VGGSound/video/Hb85aFzdR_I_000520.mp4 people crowd +tests/VGGSound/video/KeprFzFcbYU_000010.mp4 people hiccup +tests/VGGSound/video/HbKm3MFLDjQ_000000.mp4 opening or closing car electric windows +tests/VGGSound/video/Hbp4cnuQS_Q_000080.mp4 playing harmonica +tests/VGGSound/video/KfRnwi5tJUs_000040.mp4 zebra braying 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speaking +tests/VGGSound/video/HtnBcjEudhY_000300.mp4 goose honking +tests/VGGSound/video/KydSULgAHFI_000060.mp4 footsteps on snow +tests/VGGSound/video/KydSULgAHFI_000084.mp4 footsteps on snow +tests/VGGSound/video/KyebYm2Tx9A_000030.mp4 fire crackling +tests/VGGSound/video/KykQTH0dlwE_000590.mp4 playing banjo +tests/VGGSound/video/Hu1OmW6Glaw_000030.mp4 chopping wood +tests/VGGSound/video/Hu8H7Dt5vSA_000030.mp4 dog whimpering +tests/VGGSound/video/Kz4SvP0c_VE_000019.mp4 magpie calling +tests/VGGSound/video/KzCgXauRqKM_000017.mp4 disc scratching +tests/VGGSound/video/KzKDk-UgS54_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/KzLSsTfunLY_000030.mp4 car engine knocking +tests/VGGSound/video/KzdmGVwiPN0_000019.mp4 black capped chickadee calling +tests/VGGSound/video/KzerdnnE7iY_000437.mp4 playing tennis +tests/VGGSound/video/KzerdnnE7iY_000457.mp4 playing tennis +tests/VGGSound/video/HvGwWk3wjM4_000307.mp4 shot football +tests/VGGSound/video/HvMZHdzvmSM_000020.mp4 people farting +tests/VGGSound/video/KzvdKLdBw3s_000060.mp4 female speech, woman speaking +tests/VGGSound/video/HvYcAAf_0NY_000008.mp4 striking pool +tests/VGGSound/video/L-P2xqZMI8E_000050.mp4 pumping water +tests/VGGSound/video/HvtN3RsF85E_000030.mp4 sloshing water +tests/VGGSound/video/HvtmFczEZBU_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/HvyXGNx_jYc_000030.mp4 raining +tests/VGGSound/video/HvzbM3aqbEA_000096.mp4 arc welding +tests/VGGSound/video/L-qLeq5E6Xc_000013.mp4 bowling impact +tests/VGGSound/video/L-syzwlD05s_000000.mp4 driving motorcycle +tests/VGGSound/video/HwBF6_2E-xM_000020.mp4 slot machine +tests/VGGSound/video/HwEIzzTk_Xk_000076.mp4 playing tympani +tests/VGGSound/video/L0DtxpwfacQ_000047.mp4 underwater bubbling +tests/VGGSound/video/HwGK5RvNOFI_000030.mp4 typing on computer keyboard +tests/VGGSound/video/HwWQUXnD0oo_000117.mp4 playing trombone +tests/VGGSound/video/HwaeZS9P6GI_000180.mp4 rowboat, canoe, kayak rowing 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train horning +tests/VGGSound/video/L3FlG2uJgY8_000250.mp4 playing acoustic guitar +tests/VGGSound/video/L3LCrJ-h6Uc_000130.mp4 people farting +tests/VGGSound/video/HzSOK5rklH8_000077.mp4 missile launch +tests/VGGSound/video/HzXWXYxXyYA_000050.mp4 playing bass guitar +tests/VGGSound/video/L3a132_uApg_000090.mp4 railroad car, train wagon +tests/VGGSound/video/HzhiWSedtyQ_000023.mp4 child singing +tests/VGGSound/video/L3lYFx1wx-M_000195.mp4 people eating noodle +tests/VGGSound/video/L3t6q50x8JU_000037.mp4 gibbon howling +tests/VGGSound/video/L3wNweyCqdY_000394.mp4 smoke detector beeping +tests/VGGSound/video/I-DxUDHO_5Q_000275.mp4 people battle cry +tests/VGGSound/video/L4L0qHVVABs_000015.mp4 barn swallow calling +tests/VGGSound/video/L4LgDMosfxE_000229.mp4 foghorn +tests/VGGSound/video/I-HlrcP6Qg4_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/L4Z7XkS6CtA_000030.mp4 skateboarding +tests/VGGSound/video/I-Lr26bQ7nI_000448.mp4 ice cream truck, ice cream van +tests/VGGSound/video/I-W-XxXGbHc_000028.mp4 horse neighing +tests/VGGSound/video/I-XYm2Ck2r8_000030.mp4 tapping guitar +tests/VGGSound/video/I-bNKpYykUY_001034.mp4 lip smacking +tests/VGGSound/video/I-gq3pYlyJY_000030.mp4 playing harmonica +tests/VGGSound/video/L5UDz2PJ9sk_000030.mp4 playing didgeridoo +tests/VGGSound/video/I0CQd_aWJ9g_000030.mp4 people shuffling +tests/VGGSound/video/L5aBBOCALNo_000075.mp4 car engine idling +tests/VGGSound/video/L5ohzqF0ZHQ_000020.mp4 police car (siren) +tests/VGGSound/video/I0Rj_topRmI_000005.mp4 telephone bell ringing +tests/VGGSound/video/I0jA3pAj5VI_000027.mp4 plastic bottle crushing +tests/VGGSound/video/L6QtigLJD_4_000030.mp4 fireworks banging +tests/VGGSound/video/L6V8S8U9iLs_000312.mp4 playing congas +tests/VGGSound/video/I1GC1yWdM_c_000030.mp4 cat caterwauling +tests/VGGSound/video/I1NE3H6soBU_000300.mp4 chicken crowing +tests/VGGSound/video/L76AuckUoe8_000006.mp4 disc scratching +tests/VGGSound/video/L7E5Tv357Ys_000040.mp4 air conditioning noise +tests/VGGSound/video/I1RzkfmsZRc_000161.mp4 firing muskets +tests/VGGSound/video/I1fcUe9MoMw_000120.mp4 playing ukulele +tests/VGGSound/video/L7n3LkVpkwo_000030.mp4 car engine knocking +tests/VGGSound/video/I1puFLEIQcs_000387.mp4 fox barking +tests/VGGSound/video/L7wH_Co3RXY_000004.mp4 horse clip-clop +tests/VGGSound/video/I1xnDP0v7Bs_000167.mp4 parrot talking +tests/VGGSound/video/I2IYACECpWM_000031.mp4 spraying water +tests/VGGSound/video/I2IYACECpWM_000083.mp4 spraying water +tests/VGGSound/video/I2KxGucsrHw_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/I2N51CtFxxo_000212.mp4 eagle screaming +tests/VGGSound/video/I2S72eajLzw_000030.mp4 playing hammond organ +tests/VGGSound/video/L8MtMBVqOD0_000550.mp4 dog whimpering +tests/VGGSound/video/I2TVTrAxvnU_000270.mp4 lighting firecrackers +tests/VGGSound/video/L8W-5LTrwjM_000030.mp4 bird squawking +tests/VGGSound/video/I2bn465QJgI_000290.mp4 opening or closing drawers +tests/VGGSound/video/I3OYmetiXqA_000597.mp4 people slurping +tests/VGGSound/video/I3gYd_mSx18_000062.mp4 cutting hair with electric trimmers +tests/VGGSound/video/I3izYHSgVTQ_000570.mp4 railroad car, train wagon +tests/VGGSound/video/L9nIN8KrWfQ_000061.mp4 opening or closing car electric windows +tests/VGGSound/video/L9nIN8KrWfQ_000075.mp4 opening or closing car electric windows +tests/VGGSound/video/I3qbB4Kq3Y0_000030.mp4 playing banjo +tests/VGGSound/video/LA4CTzhrLu8_000008.mp4 mouse squeaking +tests/VGGSound/video/LA91bTw_08Q_000203.mp4 sharpen knife +tests/VGGSound/video/LAAB6eDASpE_000361.mp4 planing timber +tests/VGGSound/video/LALkgnffr0I_000030.mp4 horse clip-clop +tests/VGGSound/video/LAOf7hEPxTA_000030.mp4 playing tabla +tests/VGGSound/video/I4AsMxE3tFA_000188.mp4 people slapping +tests/VGGSound/video/LAeWwMC2EaI_000030.mp4 playing electric guitar +tests/VGGSound/video/I4XG-uLrzjk_000038.mp4 wood thrush calling +tests/VGGSound/video/I4YGt9SUYzg_000030.mp4 baby babbling +tests/VGGSound/video/LArzvx72wH0_000045.mp4 golf driving +tests/VGGSound/video/I4_cuFy_SHc_000220.mp4 typing on typewriter +tests/VGGSound/video/LBH0InPJ-pU_000105.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/LBXYlTnm0Fw_000054.mp4 lathe spinning +tests/VGGSound/video/I5W0Nnn1zFk_000030.mp4 frog croaking +tests/VGGSound/video/LBxiUTpsRxQ_000020.mp4 canary calling +tests/VGGSound/video/LC1Bw1Rgnj8_000481.mp4 people battle cry +tests/VGGSound/video/I5_9FYVk6cQ_000096.mp4 people nose blowing +tests/VGGSound/video/LC4vDpnkDtM_000063.mp4 bull bellowing +tests/VGGSound/video/LC4vDpnkDtM_000100.mp4 bull bellowing +tests/VGGSound/video/I5f96kvSXzU_000004.mp4 air horn +tests/VGGSound/video/LC79lWBAlR4_000410.mp4 playing bassoon +tests/VGGSound/video/I5yMAPfZsBQ_000360.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/LCFNAzdifzU_000003.mp4 people gargling +tests/VGGSound/video/I6BoigdgEBc_000030.mp4 rapping +tests/VGGSound/video/I6IWqqszDH0_000030.mp4 playing zither +tests/VGGSound/video/LCb5ac7dWyM_000030.mp4 people whispering +tests/VGGSound/video/I6Nly5f8NkU_000303.mp4 playing guiro +tests/VGGSound/video/I6bNIhsP0DY_000218.mp4 disc scratching +tests/VGGSound/video/LCoiDehvkWE_000312.mp4 playing shofar +tests/VGGSound/video/I6nRHMGe4Q8_000129.mp4 zebra braying +tests/VGGSound/video/LD6nP2qlsRI_000030.mp4 people shuffling +tests/VGGSound/video/I70DGW_g26g_000100.mp4 people slapping +tests/VGGSound/video/LDDOczcTYxI_000115.mp4 bull bellowing +tests/VGGSound/video/LDDOczcTYxI_000147.mp4 bull bellowing +tests/VGGSound/video/LDGzSk_vzPo_000260.mp4 bird wings flapping +tests/VGGSound/video/I7OqRsLtmh0_000310.mp4 church bell ringing +tests/VGGSound/video/I7QODcpToew_000080.mp4 playing bagpipes +tests/VGGSound/video/LDhGe9q2Svw_000160.mp4 bird squawking +tests/VGGSound/video/I7esm6vqqZ4_000030.mp4 driving buses +tests/VGGSound/video/LDoXsip0BEQ_000177.mp4 parrot talking +tests/VGGSound/video/I7gxE9VFb90_000067.mp4 skiing +tests/VGGSound/video/LDpBgaiKB2E_000020.mp4 car engine knocking +tests/VGGSound/video/I7t4FclogbI_000018.mp4 baltimore oriole calling +tests/VGGSound/video/LDykvT8PuQE_000475.mp4 magpie calling +tests/VGGSound/video/LDz3wd663kg_000030.mp4 frog croaking +tests/VGGSound/video/LDzb6mVK4nk_000127.mp4 playing volleyball +tests/VGGSound/video/LEFSHa_n9jE_000287.mp4 people cheering +tests/VGGSound/video/LEG7xkYOsWA_000020.mp4 playing ukulele +tests/VGGSound/video/LEJyA_IDpxg_000030.mp4 chicken crowing +tests/VGGSound/video/LEUkbkdBupE_000004.mp4 playing castanets +tests/VGGSound/video/LEZFcGFwJlc_000030.mp4 male speech, man speaking +tests/VGGSound/video/LEZfZZmiVsY_000011.mp4 people running +tests/VGGSound/video/LEn3f97acaw_000030.mp4 people clapping +tests/VGGSound/video/LEnZ2fTT1cE_000307.mp4 skiing +tests/VGGSound/video/LExYeHF-ypk_000130.mp4 playing cello +tests/VGGSound/video/LF-5BAUGvWI_000030.mp4 rapping +tests/VGGSound/video/I9DXY3uVflY_000119.mp4 opening or closing car doors +tests/VGGSound/video/I9DXY3uVflY_000152.mp4 opening or closing car doors +tests/VGGSound/video/LFUt_bj_5ng_000000.mp4 thunder +tests/VGGSound/video/LFYRuK8YstI_000030.mp4 playing banjo +tests/VGGSound/video/I9auMdqQlmY_000030.mp4 typing on computer keyboard +tests/VGGSound/video/I9zQLQjNu98_000030.mp4 fire crackling +tests/VGGSound/video/IA09qnlMgQU_000058.mp4 cutting hair with electric trimmers +tests/VGGSound/video/IAF_S5eNI3w_000766.mp4 blowtorch igniting +tests/VGGSound/video/LG94osOX9YA_000000.mp4 baby babbling +tests/VGGSound/video/IAG9PZmTGD4_000208.mp4 foghorn +tests/VGGSound/video/IAf3HUIy0lA_000030.mp4 fire crackling +tests/VGGSound/video/LGrpsZ7BsQA_000030.mp4 duck quacking +tests/VGGSound/video/IArDDikQbAg_000030.mp4 cap gun shooting +tests/VGGSound/video/LH08k5Kf4AI_000130.mp4 chainsawing trees +tests/VGGSound/video/IB5GpLct3c4_000042.mp4 playing tambourine +tests/VGGSound/video/IBGfcPIw-KY_000000.mp4 dog howling +tests/VGGSound/video/LHG0VAUtUpg_000187.mp4 volcano explosion +tests/VGGSound/video/IBVid9pEOwk_000005.mp4 striking bowling +tests/VGGSound/video/IBYer_XIT9Q_000030.mp4 sliding door +tests/VGGSound/video/LHVhSXvr6Ds_000028.mp4 squishing water +tests/VGGSound/video/IBnelTCAXKg_000270.mp4 people crowd +tests/VGGSound/video/LHY9L1MjQvQ_000030.mp4 cat meowing +tests/VGGSound/video/IBq1BKfKfIk_000256.mp4 snake hissing +tests/VGGSound/video/LHdbtxx9pMs_000340.mp4 firing muskets +tests/VGGSound/video/IC4Rpl0_dW8_000020.mp4 lighting firecrackers +tests/VGGSound/video/IC5x2ks6_ww_000164.mp4 car engine idling +tests/VGGSound/video/IC9hh-3zlQY_000792.mp4 wind chime +tests/VGGSound/video/LI-UBG1Z77o_000030.mp4 frog croaking +tests/VGGSound/video/LI46aCaqKQg_000108.mp4 playing congas +tests/VGGSound/video/LI85dkBB3Ho_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/ICIG9ubOR0Q_000054.mp4 underwater bubbling +tests/VGGSound/video/LIU7EYJEbYQ_000010.mp4 driving buses +tests/VGGSound/video/IClqeKMGVdQ_000058.mp4 slot machine +tests/VGGSound/video/LIluVun_dJk_000030.mp4 turkey gobbling +tests/VGGSound/video/ID9p52w2ah4_000079.mp4 playing erhu +tests/VGGSound/video/IDNjtuhsyok_000005.mp4 wood thrush calling +tests/VGGSound/video/LJbM0DMRM4Q_000000.mp4 horse clip-clop +tests/VGGSound/video/IDfaiqtHiEw_000080.mp4 chimpanzee pant-hooting +tests/VGGSound/video/LJkokwDPNiA_000131.mp4 alarm clock ringing +tests/VGGSound/video/IDzUjPhY080_000340.mp4 people burping +tests/VGGSound/video/LK0um3j89a0_000030.mp4 ocean burbling +tests/VGGSound/video/LK8NpgU9EZE_000030.mp4 people whispering +tests/VGGSound/video/IE4pLXxV7MQ_000000.mp4 bull bellowing +tests/VGGSound/video/IE4pLXxV7MQ_000036.mp4 bull bellowing +tests/VGGSound/video/IEJGDoi_QwI_000013.mp4 ferret dooking +tests/VGGSound/video/IEJGDoi_QwI_000032.mp4 ferret dooking +tests/VGGSound/video/IERQwxXxb2E_000103.mp4 cutting hair with electric trimmers +tests/VGGSound/video/IERQwxXxb2E_000163.mp4 cutting hair with electric trimmers +tests/VGGSound/video/IEVVHo9nr7g_000030.mp4 rapping +tests/VGGSound/video/LL436Co8SA8_000519.mp4 dinosaurs bellowing +tests/VGGSound/video/LLAjvllcjZ8_000291.mp4 ice cracking +tests/VGGSound/video/IEjaZmXmm4c_000020.mp4 telephone bell ringing +tests/VGGSound/video/IEwX4HhetxM_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/IF-77lLlMzE_000030.mp4 duck quacking +tests/VGGSound/video/LLkNFGrrgUo_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/IF6pEraHXjI_000145.mp4 playing washboard +tests/VGGSound/video/LLl-cqybths_000290.mp4 car engine idling +tests/VGGSound/video/IFM2fxyKzGU_000051.mp4 volcano explosion +tests/VGGSound/video/IFR7h0EFItM_000059.mp4 bathroom ventilation fan running +tests/VGGSound/video/IFXLc3VZldw_000030.mp4 playing zither +tests/VGGSound/video/IFclJMPODCA_000221.mp4 blowtorch igniting +tests/VGGSound/video/LMcCvGwYIS4_000022.mp4 gibbon howling +tests/VGGSound/video/LMfD-ZsuzOU_000030.mp4 playing clarinet +tests/VGGSound/video/IG5-s_G2csM_000030.mp4 playing electronic organ +tests/VGGSound/video/LMrVjK1otdM_000131.mp4 bowling impact +tests/VGGSound/video/LMv4Vt9otVg_000030.mp4 playing hammond organ +tests/VGGSound/video/IGF__xZmktU_000167.mp4 parrot talking +tests/VGGSound/video/IGLL0_qVomg_000013.mp4 sea waves +tests/VGGSound/video/LN92tji7ADA_000002.mp4 opening or closing car electric windows +tests/VGGSound/video/IGaF7wK8hvM_000098.mp4 playing bassoon +tests/VGGSound/video/LNHWLAdsxfo_000013.mp4 ferret dooking +tests/VGGSound/video/LNQ7fzfdLiY_000150.mp4 ambulance siren +tests/VGGSound/video/IHKjoCS9gs4_000028.mp4 chinchilla barking +tests/VGGSound/video/LNf7s1uPB1c_000222.mp4 chimpanzee pant-hooting +tests/VGGSound/video/IHSblFkJ6-Y_000029.mp4 cheetah chirrup +tests/VGGSound/video/IHSblFkJ6-Y_000039.mp4 cheetah chirrup +tests/VGGSound/video/IHg3nrJZQ1I_000100.mp4 lawn mowing +tests/VGGSound/video/IHlgJYdUxKo_000030.mp4 crow cawing +tests/VGGSound/video/LO29f7oGgmo_000158.mp4 bowling impact +tests/VGGSound/video/II0KddTM6H0_000105.mp4 turkey gobbling +tests/VGGSound/video/LOHw8cZZ9-U_000450.mp4 people belly laughing +tests/VGGSound/video/LOj1kNzRycU_000196.mp4 swimming +tests/VGGSound/video/IID8ylEYH5o_000062.mp4 canary calling +tests/VGGSound/video/IIKc_1iCxMQ_000014.mp4 playing bassoon +tests/VGGSound/video/IIamk2tYJHY_000365.mp4 playing oboe +tests/VGGSound/video/IIdwBaHYhE4_000070.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/IIv1mYMKQB0_000082.mp4 playing volleyball +tests/VGGSound/video/IIzMqbTNYOA_000410.mp4 ambulance siren +tests/VGGSound/video/IJ0jeaVklt8_000016.mp4 playing snare drum +tests/VGGSound/video/LPUBIiA6iHg_000022.mp4 playing volleyball +tests/VGGSound/video/LPjblqE3xHk_000218.mp4 fox barking +tests/VGGSound/video/IJNf5hJzf5M_000006.mp4 door slamming +tests/VGGSound/video/LPvJFjsxMj8_000030.mp4 cat meowing +tests/VGGSound/video/LPydM-Gilpg_000133.mp4 cutting hair with electric trimmers +tests/VGGSound/video/IJXrQCDz-wc_000233.mp4 people eating noodle +tests/VGGSound/video/IJquEOrTj1Y_000150.mp4 playing didgeridoo +tests/VGGSound/video/LQsjgYb7i90_000051.mp4 sea waves +tests/VGGSound/video/LQsjgYb7i90_000068.mp4 sea waves +tests/VGGSound/video/IKDGba7vsOA_000044.mp4 baby laughter +tests/VGGSound/video/LRODueKSk2M_000040.mp4 playing electronic organ +tests/VGGSound/video/LRhGAkeY8YA_000091.mp4 missile launch +tests/VGGSound/video/IKdDjrqrzoY_000160.mp4 squishing water +tests/VGGSound/video/LRlrFudaEs8_000000.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/LS6efNeNaFs_000187.mp4 wind chime +tests/VGGSound/video/IL3ThGKdOMk_000221.mp4 tractor digging +tests/VGGSound/video/ILIh--LeKHI_000275.mp4 chimpanzee pant-hooting +tests/VGGSound/video/ILKdRNizGCs_000594.mp4 people slurping +tests/VGGSound/video/LSXoi2-LOuU_000382.mp4 roller coaster running +tests/VGGSound/video/LSaLPObrnZw_000010.mp4 playing timpani +tests/VGGSound/video/LSdLFRi_h-g_000090.mp4 waterfall burbling +tests/VGGSound/video/LTA3ncpTnUo_000030.mp4 using sewing machines +tests/VGGSound/video/ILv7AQF-ltI_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/LTD5rh_DOTY_000260.mp4 owl hooting +tests/VGGSound/video/LTJ7hbP8y8g_000021.mp4 chopping wood +tests/VGGSound/video/IM88gSXv2e8_000310.mp4 people humming +tests/VGGSound/video/LTNgncM_otw_000010.mp4 plastic bottle crushing +tests/VGGSound/video/LTO3mhVLS4g_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/IMIuEADfRTQ_000140.mp4 bird wings flapping +tests/VGGSound/video/IMKIBJD-JSM_000013.mp4 disc scratching +tests/VGGSound/video/LTXXIMHSfo0_000014.mp4 volcano explosion +tests/VGGSound/video/LTaOEqQn2q8_000127.mp4 people gargling +tests/VGGSound/video/IMOQv1QHxSQ_000041.mp4 chipmunk chirping +tests/VGGSound/video/IMQtdwaG8I8_000101.mp4 forging swords +tests/VGGSound/video/IMTv4Ym0p6A_000023.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/IMWPb20akf8_000051.mp4 slot machine +tests/VGGSound/video/LU1CGfgJXfM_000080.mp4 cattle, bovinae cowbell +tests/VGGSound/video/LU2T3Q-xbu0_000027.mp4 owl hooting +tests/VGGSound/video/IMjpwQHZaWo_000033.mp4 bathroom ventilation fan running +tests/VGGSound/video/LUfzlkl-Dac_000001.mp4 baby crying +tests/VGGSound/video/LUg8N2STi2k_000540.mp4 playing theremin +tests/VGGSound/video/IN4Up4lZvB0_000014.mp4 people nose blowing +tests/VGGSound/video/INBx8CrIWcg_000030.mp4 playing synthesizer +tests/VGGSound/video/INC-NROLF9o_000054.mp4 cattle, bovinae cowbell +tests/VGGSound/video/INCP-fQ1HDQ_000007.mp4 children shouting +tests/VGGSound/video/INQWH7mOGeQ_000030.mp4 cricket chirping +tests/VGGSound/video/LVFYimyY7sU_000030.mp4 playing accordion +tests/VGGSound/video/LVYHbuggoj8_000050.mp4 missile launch +tests/VGGSound/video/LVg4FdXURmo_000000.mp4 firing muskets +tests/VGGSound/video/INdCGM4pQOs_000497.mp4 mynah bird singing +tests/VGGSound/video/INlc_zD_CKE_000150.mp4 people hiccup +tests/VGGSound/video/LWKaNv6asYM_000264.mp4 cell phone buzzing +tests/VGGSound/video/LWmpo5mho0Q_000440.mp4 playing marimba, xylophone +tests/VGGSound/video/IOA_DhIDXi8_000007.mp4 lions growling +tests/VGGSound/video/LX45Unyyosw_000108.mp4 playing badminton +tests/VGGSound/video/LX5Y1jcoUXE_000030.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/IObJnm1ohxI_000052.mp4 dinosaurs bellowing +tests/VGGSound/video/LXQ5yQP-mkM_000046.mp4 alligators, crocodiles hissing +tests/VGGSound/video/IOpMfRxQdrs_000014.mp4 baby crying +tests/VGGSound/video/LXZNhyX5SkE_000077.mp4 train wheels squealing +tests/VGGSound/video/LXZNhyX5SkE_000206.mp4 train wheels squealing +tests/VGGSound/video/IOqtQmToNFg_000010.mp4 playing vibraphone +tests/VGGSound/video/IOu7cOZgZE4_000272.mp4 tap dancing +tests/VGGSound/video/LXhmTaN0sEE_000140.mp4 printer printing +tests/VGGSound/video/LXiBeL5U3nk_000218.mp4 firing muskets +tests/VGGSound/video/IP0_FH73Hm0_000092.mp4 playing washboard +tests/VGGSound/video/LXuw0i0_aCI_000040.mp4 people farting +tests/VGGSound/video/LY1e2ZUVl8M_000030.mp4 horse clip-clop +tests/VGGSound/video/LY1m65KuOCc_000030.mp4 car engine knocking +tests/VGGSound/video/IPIS6TUVpSM_000030.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/LYHxPsVC2i8_000051.mp4 airplane +tests/VGGSound/video/IPYHy8k9Z34_000050.mp4 playing piano +tests/VGGSound/video/IPm036_I75o_000362.mp4 eagle screaming +tests/VGGSound/video/LYj9FpkFXTI_000030.mp4 people burping +tests/VGGSound/video/LYjYqGEschw_000004.mp4 lathe spinning +tests/VGGSound/video/LYo9ZUlwohs_000350.mp4 playing marimba, xylophone +tests/VGGSound/video/LYqVH6Z8ppw_000030.mp4 car passing by +tests/VGGSound/video/LYvgJX8p6YU_000030.mp4 owl hooting +tests/VGGSound/video/IQFRwjMKOrM_000485.mp4 playing darts +tests/VGGSound/video/LZFfZoHh-Vs_000030.mp4 thunder +tests/VGGSound/video/IQecgFqv4mI_000000.mp4 car engine knocking +tests/VGGSound/video/LZJmNr8L5d0_000200.mp4 pumping water +tests/VGGSound/video/IQszXcU_OBI_000147.mp4 air conditioning noise +tests/VGGSound/video/LZRj04MWEo8_000002.mp4 pheasant crowing +tests/VGGSound/video/IRD6JNSw4T0_000049.mp4 opening or closing car doors +tests/VGGSound/video/LZetbWJ01Oc_000310.mp4 wind rustling leaves +tests/VGGSound/video/IRYPJTybCu8_000130.mp4 warbler chirping +tests/VGGSound/video/IS2lQophwDw_000050.mp4 people hiccup +tests/VGGSound/video/IS5V2yjPp3k_000030.mp4 people shuffling +tests/VGGSound/video/LaBLXBBiCw4_000075.mp4 metronome +tests/VGGSound/video/LaGXHHzobMA_000012.mp4 crow cawing +tests/VGGSound/video/ISdguQ3flPA_000033.mp4 bouncing on trampoline +tests/VGGSound/video/LaUs2LAnO1w_000123.mp4 playing castanets +tests/VGGSound/video/LaiJ0mPbbdk_000016.mp4 horse neighing +tests/VGGSound/video/IT7iv85SaUQ_000086.mp4 civil defense siren +tests/VGGSound/video/LataVY-O5FA_000063.mp4 disc scratching +tests/VGGSound/video/LataVY-O5FA_000090.mp4 disc scratching +tests/VGGSound/video/ITKMtPL1pWw_000001.mp4 underwater bubbling +tests/VGGSound/video/ITYq5xoDGK0_000030.mp4 chicken clucking +tests/VGGSound/video/ITaflypbuAs_000015.mp4 playing shofar +tests/VGGSound/video/IThCRPbXPMI_000017.mp4 whale calling +tests/VGGSound/video/LbKz9Tn8xvs_000263.mp4 opening or closing car doors +tests/VGGSound/video/LbWDdMprV5k_000113.mp4 chicken clucking +tests/VGGSound/video/LbWDdMprV5k_000175.mp4 chicken clucking +tests/VGGSound/video/ITym6X1Cvzs_000000.mp4 duck quacking +tests/VGGSound/video/LbpVMYJZHKw_000011.mp4 pig oinking +tests/VGGSound/video/LbqKv3E9Xso_000071.mp4 opening or closing car doors +tests/VGGSound/video/Lc9o85m9imc_000233.mp4 airplane +tests/VGGSound/video/LcFXCaPmvbU_000155.mp4 people nose blowing +tests/VGGSound/video/LeKSh68pvMQ_000030.mp4 horse clip-clop +tests/VGGSound/video/IWYbTgMqixk_000012.mp4 alarm clock ringing +tests/VGGSound/video/Lep1tjEIkJc_000030.mp4 playing harp +tests/VGGSound/video/IXKMzUr2sIo_000094.mp4 disc scratching +tests/VGGSound/video/IXM05dPfKmo_000030.mp4 wind noise +tests/VGGSound/video/IXTJfi5PUdk_000000.mp4 black capped chickadee calling +tests/VGGSound/video/LfXdaE7ph_I_000011.mp4 baby crying 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rowboat, canoe, kayak rowing +tests/VGGSound/video/IZR4G9Hhy5U_000030.mp4 playing cello +tests/VGGSound/video/IZ_FwYrGGXA_000029.mp4 chinchilla barking +tests/VGGSound/video/Lhc5eE9X-ak_000030.mp4 cat purring +tests/VGGSound/video/LhgaG9ZtdwI_000003.mp4 alarm clock ringing +tests/VGGSound/video/Lhi9SJ6V8NQ_000014.mp4 smoke detector beeping +tests/VGGSound/video/IZtiMmPN0Xc_000000.mp4 playing harp +tests/VGGSound/video/LhpzNXhZ44c_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/Lhuh4mKOTqY_000109.mp4 foghorn +tests/VGGSound/video/LiHQ6oUWCNM_000070.mp4 people sneezing +tests/VGGSound/video/LiXfod3qOQw_000020.mp4 turkey gobbling +tests/VGGSound/video/I_xgEGprZYM_000737.mp4 mouse clicking +tests/VGGSound/video/Ia6C4k0o2hc_000020.mp4 ambulance siren +tests/VGGSound/video/Lj8Oo7QRjcQ_000030.mp4 people eating apple +tests/VGGSound/video/IaBCp-ZckT8_000120.mp4 francolin calling +tests/VGGSound/video/LjTQA8G6hoQ_000130.mp4 using sewing machines 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booing +tests/VGGSound/video/IdkAQNGihZU_000151.mp4 civil defense siren +tests/VGGSound/video/LmSnKdx4W_8_000000.mp4 race car, auto racing +tests/VGGSound/video/IdmhuP_16qM_000698.mp4 forging swords +tests/VGGSound/video/IdqTtYcY8L4_000140.mp4 splashing water +tests/VGGSound/video/LmlCcoUOaOs_000030.mp4 lighting firecrackers +tests/VGGSound/video/Ie8lI5HnSk4_000165.mp4 playing oboe +tests/VGGSound/video/LmtTU7Ihc4M_000350.mp4 machine gun shooting +tests/VGGSound/video/LmtgH_KHgX8_000080.mp4 eating with cutlery +tests/VGGSound/video/Ln3BmBHAJ-c_000430.mp4 playing cello +tests/VGGSound/video/LnKNEwJ8LHg_000002.mp4 golf driving +tests/VGGSound/video/LnVxCibEqko_000053.mp4 chopping food +tests/VGGSound/video/IeapE3z-v3Q_000074.mp4 playing bass drum +tests/VGGSound/video/IeapE3z-v3Q_000129.mp4 playing bass drum +tests/VGGSound/video/IedxNpk3Yns_000105.mp4 playing bongo +tests/VGGSound/video/IevRzGh8uMs_000134.mp4 train whistling +tests/VGGSound/video/If1yxmaJ14M_000170.mp4 playing acoustic guitar +tests/VGGSound/video/LoRLOQaZU48_000090.mp4 airplane +tests/VGGSound/video/LoSomwPzdGE_000121.mp4 writing on blackboard with chalk +tests/VGGSound/video/IfsB-8hbcL8_000030.mp4 people whispering +tests/VGGSound/video/Lp7-GR1vLwA_000410.mp4 opening or closing drawers +tests/VGGSound/video/IgVdF1Igzis_000110.mp4 frog croaking +tests/VGGSound/video/IgZ6SeMFFDE_000005.mp4 squishing water +tests/VGGSound/video/IgbGOMBaGmw_000013.mp4 chimpanzee pant-hooting +tests/VGGSound/video/IgiaGUeiVe4_000411.mp4 bowling impact +tests/VGGSound/video/Iglv2Kru0mw_000040.mp4 fly, housefly buzzing +tests/VGGSound/video/LpaMZAVe9Cg_000116.mp4 sharpen knife +tests/VGGSound/video/LphmNfEyJho_000008.mp4 penguins braying +tests/VGGSound/video/Ih0xy7tt2JY_000030.mp4 helicopter +tests/VGGSound/video/Ih3hZZRw9Fg_000146.mp4 bathroom ventilation fan running +tests/VGGSound/video/Ih3hZZRw9Fg_000415.mp4 bathroom ventilation fan running +tests/VGGSound/video/LpswiH_Vkes_000021.mp4 frog croaking 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meowing +tests/VGGSound/video/Ip1sAKybSHs_000153.mp4 chopping food +tests/VGGSound/video/Ip6FptuXHyk_000030.mp4 playing electric guitar +tests/VGGSound/video/LyTwxJiSt7A_000000.mp4 people burping +tests/VGGSound/video/IpCLfHuI_VM_000172.mp4 wind chime +tests/VGGSound/video/LyYLLg9xE68_000002.mp4 golf driving +tests/VGGSound/video/Lyj48v3SEzs_000075.mp4 lip smacking +tests/VGGSound/video/Lyk2HM8_zbg_000118.mp4 writing on blackboard with chalk +tests/VGGSound/video/LyravGP_Li8_000264.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/LysFhHBYTmE_000040.mp4 female speech, woman speaking +tests/VGGSound/video/IphL7mUqZ6A_000400.mp4 car engine starting +tests/VGGSound/video/IpqtJmqY4-w_000200.mp4 dog howling +tests/VGGSound/video/LzZ_nxuZ8Co_000030.mp4 driving buses +tests/VGGSound/video/IqG7MqzI1Qo_000164.mp4 snake hissing +tests/VGGSound/video/LzoAb4spthk_000042.mp4 slot machine +tests/VGGSound/video/M-bmsXbJBdw_000034.mp4 race car, auto racing 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motorboat, speedboat acceleration +tests/VGGSound/video/M5xJm4N_8pg_000014.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/M61BBJpvvx8_000030.mp4 using sewing machines +tests/VGGSound/video/Iy2HaWAAnvQ_000173.mp4 train whistling +tests/VGGSound/video/Iy47-2ecO1g_000250.mp4 playing congas +tests/VGGSound/video/M6NJA3tF044_000057.mp4 elk bugling +tests/VGGSound/video/M6StDnohba8_000082.mp4 people eating apple +tests/VGGSound/video/M6XLGqoquxI_000000.mp4 people sobbing +tests/VGGSound/video/IyL7GafTLfY_000030.mp4 chicken crowing +tests/VGGSound/video/IyV2j4BsEM8_000030.mp4 people babbling +tests/VGGSound/video/IyXxPbuvGSM_000011.mp4 ferret dooking +tests/VGGSound/video/Iyf2C0_SwuQ_000000.mp4 thunder +tests/VGGSound/video/M7GSBDc6s_w_000340.mp4 playing sitar +tests/VGGSound/video/M7NvD1WJQ7o_000070.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/M7QNk2-i0IM_000200.mp4 horse neighing +tests/VGGSound/video/M7kdWvNks4U_000060.mp4 playing clarinet 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playing timbales +tests/VGGSound/video/J07bcjxK3qM_000137.mp4 metronome +tests/VGGSound/video/MASDK7lg0w4_000010.mp4 mouse pattering +tests/VGGSound/video/MAbDEeLF4cQ_000030.mp4 skateboarding +tests/VGGSound/video/J0lA7ZDfPLE_000030.mp4 playing electric guitar +tests/VGGSound/video/MAhYAMZ50VI_000100.mp4 dog howling +tests/VGGSound/video/J1-Qvl7u2TI_000000.mp4 crow cawing +tests/VGGSound/video/MAqLrKdONiM_000030.mp4 playing french horn +tests/VGGSound/video/MAr-k9ZO3eA_000030.mp4 playing harpsichord +tests/VGGSound/video/J12HPLJd84Q_000120.mp4 chopping food +tests/VGGSound/video/MB23r3XMRNU_000023.mp4 dog baying +tests/VGGSound/video/J1SB5arXFf4_000006.mp4 snake hissing +tests/VGGSound/video/MBRmjThZops_000000.mp4 police car (siren) +tests/VGGSound/video/MBVEZnvdBUM_000019.mp4 metronome +tests/VGGSound/video/MBVEZnvdBUM_000060.mp4 metronome +tests/VGGSound/video/J1WfhSyPeus_000024.mp4 playing bongo +tests/VGGSound/video/MBjlZQZ4Sns_000044.mp4 eletric blender running 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metro, underground +tests/VGGSound/video/Pf9AaTV4-yw_000180.mp4 playing timpani +tests/VGGSound/video/MKC9LvRivTM_000030.mp4 playing french horn +tests/VGGSound/video/Sv9Pm4AburQ_000030.mp4 people clapping +tests/VGGSound/video/MKRuxljwsOs_000030.mp4 mosquito buzzing +tests/VGGSound/video/MKXeCiPtZwo_000280.mp4 child singing +tests/VGGSound/video/SvRtOYGMWV8_000050.mp4 raining +tests/VGGSound/video/MKikHxKeodA_000030.mp4 opening or closing drawers +tests/VGGSound/video/MKocTMZZnTs_000040.mp4 male speech, man speaking +tests/VGGSound/video/PdLEZFUyy84_000095.mp4 penguins braying +tests/VGGSound/video/ML8ZVFSC5I0_000335.mp4 people giggling +tests/VGGSound/video/MLHEeVVOx-E_000181.mp4 chipmunk chirping +tests/VGGSound/video/MLJvuEjyTTk_000057.mp4 people humming +tests/VGGSound/video/PdzDGNMpPZc_000520.mp4 horse neighing +tests/VGGSound/video/MLMRHScRnhs_000042.mp4 gibbon howling +tests/VGGSound/video/PeEy6rXMLyg_000035.mp4 arc welding +tests/VGGSound/video/PeN0BUbCdVE_000030.mp4 printer printing +tests/VGGSound/video/PeNLnpalp9s_000030.mp4 female speech, woman speaking +tests/VGGSound/video/MLxttVd-Jc4_000210.mp4 bird squawking +tests/VGGSound/video/MM-RnWEBd14_000005.mp4 people nose blowing +tests/VGGSound/video/SxabpNk83x8_000170.mp4 playing tabla +tests/VGGSound/video/PfF-ishRsno_000048.mp4 playing bongo +tests/VGGSound/video/SynYfHkxtRc_000058.mp4 chinchilla barking +tests/VGGSound/video/MMcIAn91Zrc_000005.mp4 wind chime +tests/VGGSound/video/PfP1Fhg3h1g_000010.mp4 playing drum kit +tests/VGGSound/video/MN-NfHbxdQE_000107.mp4 playing tympani +tests/VGGSound/video/PfXdcsW8dJI_000500.mp4 eating with cutlery +tests/VGGSound/video/MN56LjjbB8k_000018.mp4 playing glockenspiel +tests/VGGSound/video/MNEuyIAtj3U_000172.mp4 cow lowing +tests/VGGSound/video/MNN2LtdpPc0_000170.mp4 waterfall burbling +tests/VGGSound/video/MNXrgwjf4CY_000356.mp4 chopping wood +tests/VGGSound/video/MNnlykTxbB0_000030.mp4 motorboat, speedboat acceleration 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wind noise +tests/VGGSound/video/MTkvHwqj9v4_000305.mp4 wind noise +tests/VGGSound/video/T6cqaSkv9MQ_000084.mp4 baltimore oriole calling +tests/VGGSound/video/PlD_3nBXmdM_000090.mp4 stream burbling +tests/VGGSound/video/PlEkvxhtZwc_000150.mp4 bird squawking +tests/VGGSound/video/PlF1Z9YWZck_000029.mp4 elephant trumpeting +tests/VGGSound/video/PlF1Z9YWZck_000075.mp4 elephant trumpeting +tests/VGGSound/video/PlGrb1DKbao_000130.mp4 dog whimpering +tests/VGGSound/video/MUC3GjvBI7I_000030.mp4 horse clip-clop +tests/VGGSound/video/MUJmWnjGEBk_000000.mp4 dog howling +tests/VGGSound/video/PljzqcsQ62U_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/T7ZSZhcsfjA_000009.mp4 male singing +tests/VGGSound/video/Pm6vRblouxc_000170.mp4 playing timpani +tests/VGGSound/video/MV1qOqhaLXk_000016.mp4 playing table tennis +tests/VGGSound/video/MV3oOUCBNWM_000439.mp4 playing snare drum +tests/VGGSound/video/Pmow_aB00Ww_000195.mp4 forging swords +tests/VGGSound/video/MVDR9JeJA6o_000030.mp4 turkey gobbling +tests/VGGSound/video/MVLEz28ZdFU_000010.mp4 people coughing +tests/VGGSound/video/MVM5RlkTh6E_000030.mp4 ambulance siren +tests/VGGSound/video/MVRUgCHoGg4_000043.mp4 woodpecker pecking tree +tests/VGGSound/video/MW0ZTvRCS1o_000220.mp4 male speech, man speaking +tests/VGGSound/video/MW9rpgetBP0_000000.mp4 frog croaking +tests/VGGSound/video/T9dKp1EN4p8_000030.mp4 playing didgeridoo +tests/VGGSound/video/MWE5Rjht178_000156.mp4 plastic bottle crushing +tests/VGGSound/video/MWTTe0M9vi4_000030.mp4 lawn mowing +tests/VGGSound/video/MWWihdWE2FE_000060.mp4 typing on computer keyboard +tests/VGGSound/video/TAJ8u7TjF6Q_000138.mp4 writing on blackboard with chalk +tests/VGGSound/video/PoD9gVdeIS4_000010.mp4 playing electronic organ +tests/VGGSound/video/TB-SQhg1z9A_000030.mp4 ocean burbling +tests/VGGSound/video/MX5ei7dDgPc_000137.mp4 parrot talking +tests/VGGSound/video/TBCKVIvh7Ug_000030.mp4 fire crackling +tests/VGGSound/video/PovPsoVl7hw_000006.mp4 fox barking 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female speech, woman speaking +tests/VGGSound/video/TOJwVO7qO-4_000384.mp4 strike lighter +tests/VGGSound/video/MgD5JedaXGs_000020.mp4 dog barking +tests/VGGSound/video/TOhV_31U7QU_000256.mp4 rope skipping +tests/VGGSound/video/Mgd0Hsgl8gU_000100.mp4 machine gun shooting +tests/VGGSound/video/PyXQVNaAbHc_000030.mp4 people coughing +tests/VGGSound/video/PyZdYCL0s5c_000030.mp4 people farting +tests/VGGSound/video/PyponzntqzM_000036.mp4 people booing +tests/VGGSound/video/MhKSI8ggZ7Y_000030.mp4 skidding +tests/VGGSound/video/MhXao_uVwqk_000124.mp4 swimming +tests/VGGSound/video/MhgCbObAHZg_000030.mp4 people eating +tests/VGGSound/video/MhyCM-4Qy24_000205.mp4 bowling impact +tests/VGGSound/video/MhykaAoDgsI_000019.mp4 air conditioning noise +tests/VGGSound/video/Mi2PLjJbpQ0_000190.mp4 hammering nails +tests/VGGSound/video/Pzj3929ka4c_000000.mp4 typing on typewriter +tests/VGGSound/video/Pzy4xTPzMiM_000028.mp4 slot machine +tests/VGGSound/video/MiQZ0dGQuIA_000170.mp4 people screaming 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+tests/VGGSound/video/Q1n6LAxY7uY_000138.mp4 lions growling +tests/VGGSound/video/Q1n6LAxY7uY_000203.mp4 lions growling +tests/VGGSound/video/Mlh4Sa1VzhQ_000016.mp4 arc welding +tests/VGGSound/video/Q1yfkoqvz_Q_000000.mp4 bull bellowing +tests/VGGSound/video/Q22V0AgIHr8_000103.mp4 baltimore oriole calling +tests/VGGSound/video/MmMtqNIzmjg_000075.mp4 people eating noodle +tests/VGGSound/video/Q2m7w_aktCo_000000.mp4 ice cream truck, ice cream van +tests/VGGSound/video/MmgJAGpHOek_000190.mp4 mouse pattering +tests/VGGSound/video/Q3GTqMEjpvY_000181.mp4 playing bugle +tests/VGGSound/video/Mmq9YFHY_80_000000.mp4 ripping paper +tests/VGGSound/video/Mn8WGSW8jHY_000065.mp4 eletric blender running +tests/VGGSound/video/MnEZwnRuQR8_000030.mp4 firing cannon +tests/VGGSound/video/MnGVz1Xu4L4_000046.mp4 train wheels squealing +tests/VGGSound/video/MnGVz1Xu4L4_000075.mp4 train wheels squealing +tests/VGGSound/video/MnH4tzgKXVc_000030.mp4 chainsawing trees +tests/VGGSound/video/MnPRF4_N-LY_000043.mp4 warbler chirping +tests/VGGSound/video/MnSZAzs8BtU_000025.mp4 cattle mooing +tests/VGGSound/video/Mnk6590abfY_000030.mp4 playing steelpan +tests/VGGSound/video/TYa0xjMBupM_000613.mp4 lip smacking +tests/VGGSound/video/Mo0WiG_6T80_000011.mp4 playing gong +tests/VGGSound/video/Q4REEz5wars_000073.mp4 mynah bird singing +tests/VGGSound/video/MoG0nt_0iSw_000000.mp4 door slamming +tests/VGGSound/video/MoWyfzqzZrk_000019.mp4 black capped chickadee calling +tests/VGGSound/video/MoYPhggPrPg_000074.mp4 snake hissing +tests/VGGSound/video/MocXmVbat3s_000030.mp4 female singing +tests/VGGSound/video/T_0xzD3qM-E_000245.mp4 playing bassoon +tests/VGGSound/video/Moru2uzLB6I_000480.mp4 playing snare drum +tests/VGGSound/video/MosOtH1imQA_000030.mp4 female speech, woman speaking +tests/VGGSound/video/MovR7hxXYOg_000037.mp4 playing lacrosse +tests/VGGSound/video/Q5lS9H-7UYs_000052.mp4 hammering nails +tests/VGGSound/video/T_cHwVO2Eac_000147.mp4 air conditioning noise +tests/VGGSound/video/Q5zz22v6QR4_000012.mp4 mynah bird singing +tests/VGGSound/video/MpWGx5odhh8_000160.mp4 playing banjo +tests/VGGSound/video/T_kADs0ZIeM_000713.mp4 people marching +tests/VGGSound/video/Mp_87MQx6Ms_000040.mp4 mosquito buzzing +tests/VGGSound/video/Q6CqAFnP2Fg_000010.mp4 ambulance siren +tests/VGGSound/video/Q6Iqev-E150_000263.mp4 cat caterwauling +tests/VGGSound/video/Ta9R_TuzIUM_000153.mp4 driving snowmobile +tests/VGGSound/video/Q6ThTeKdgR0_000003.mp4 car passing by +tests/VGGSound/video/MpxSOi79GOM_000024.mp4 ice cracking +tests/VGGSound/video/Mq5u8qFdVjQ_000152.mp4 car engine idling +tests/VGGSound/video/Q6dVti1YVwM_000000.mp4 playing sitar +tests/VGGSound/video/MqJra27MtFc_000000.mp4 wind chime +tests/VGGSound/video/Q6hIvsdfCF8_000010.mp4 people finger snapping +tests/VGGSound/video/Q6nMNWRvWfM_000040.mp4 playing tabla +tests/VGGSound/video/Q6rij_svhuc_000030.mp4 typing on computer keyboard +tests/VGGSound/video/TauSQlIbIME_000030.mp4 people belly laughing +tests/VGGSound/video/Mqlg9NYMidw_000011.mp4 air conditioning noise +tests/VGGSound/video/Mqlg9NYMidw_000053.mp4 air conditioning noise +tests/VGGSound/video/Mr--N4d6lIM_000323.mp4 male speech, man speaking +tests/VGGSound/video/Mr2kGT6i7e4_000020.mp4 dog howling +tests/VGGSound/video/Mr87MY9Vdiw_000002.mp4 sea lion barking +tests/VGGSound/video/Mr8WsLsNp0A_000002.mp4 bowling impact +tests/VGGSound/video/MrHp70quN94_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/Mr_ckcZH4c0_000023.mp4 air conditioning noise +tests/VGGSound/video/Tca5mFJq8e8_000061.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/Ms-M0gM_Sy8_000030.mp4 race car, auto racing +tests/VGGSound/video/Q8krGIiCBBQ_000050.mp4 airplane +tests/VGGSound/video/Ms9NR9_hCuY_000038.mp4 playing bass drum +tests/VGGSound/video/Q93n3dvaaTI_000130.mp4 orchestra +tests/VGGSound/video/Q9DRfeNHKGw_000200.mp4 playing electronic organ +tests/VGGSound/video/MsXvOWXDlOI_000012.mp4 people hiccup +tests/VGGSound/video/Msl9dI5yweA_000000.mp4 playing marimba, xylophone +tests/VGGSound/video/TdpZLhPN_WM_000074.mp4 baltimore oriole calling +tests/VGGSound/video/Mt4F5APXeqI_000838.mp4 lip smacking +tests/VGGSound/video/Mt8jQmWWmEE_000030.mp4 raining +tests/VGGSound/video/QA4w3EcbBPE_000387.mp4 airplane +tests/VGGSound/video/MtjflptXd4M_000425.mp4 opening or closing car doors +tests/VGGSound/video/Mtkhv22SoZ8_000030.mp4 horse neighing +tests/VGGSound/video/QAIZ0EOUwKs_000171.mp4 chimpanzee pant-hooting +tests/VGGSound/video/QAK2QJ2_8WA_000057.mp4 eletric blender running +tests/VGGSound/video/QAWuHvVCI6g_000030.mp4 skidding +tests/VGGSound/video/TeweFm49s4M_000090.mp4 opening or closing drawers +tests/VGGSound/video/QAewYfDZPJA_000067.mp4 zebra braying +tests/VGGSound/video/QAgy9r331v0_000030.mp4 cat caterwauling +tests/VGGSound/video/QAjepby044Q_000040.mp4 playing violin, fiddle +tests/VGGSound/video/QAoCyTYnAuc_000011.mp4 tractor digging +tests/VGGSound/video/Tf_mav3pAoc_000030.mp4 eating with cutlery +tests/VGGSound/video/MueF0HZVVcg_000011.mp4 playing castanets +tests/VGGSound/video/QB1jroqGo6U_000060.mp4 bull bellowing +tests/VGGSound/video/Muk-rhftfYw_000001.mp4 volcano explosion +tests/VGGSound/video/Mv0N1qYWEns_000035.mp4 people humming +tests/VGGSound/video/QBMDnMRwQCc_000070.mp4 helicopter +tests/VGGSound/video/QBMM1ocXkhY_000030.mp4 rapping +tests/VGGSound/video/QBj5dyzsJkY_000007.mp4 cricket chirping +tests/VGGSound/video/QBjKntYuUIk_000030.mp4 lions roaring +tests/VGGSound/video/QBk4A5qgzNc_000200.mp4 people eating apple +tests/VGGSound/video/QC-JCBbOuNc_000030.mp4 duck quacking +tests/VGGSound/video/MvtQF5GsJuM_000247.mp4 people slurping +tests/VGGSound/video/MvuRDIQ9Kf0_000000.mp4 playing harpsichord +tests/VGGSound/video/Mw9Kg1um1pk_000050.mp4 playing djembe +tests/VGGSound/video/QCW2lhs0rt8_000020.mp4 church bell ringing +tests/VGGSound/video/MwW0f2xh-fE_000000.mp4 bowling impact +tests/VGGSound/video/MwW0f2xh-fE_000052.mp4 bowling impact +tests/VGGSound/video/TidMGBIjbd0_000060.mp4 scuba diving +tests/VGGSound/video/Mwy5Y0S5jfM_000240.mp4 playing ukulele +tests/VGGSound/video/QDPrQohgg6E_000075.mp4 people eating apple +tests/VGGSound/video/QDW_uCMnMMU_000000.mp4 people screaming +tests/VGGSound/video/QD_0GX7J2IE_000050.mp4 waterfall burbling +tests/VGGSound/video/TjP-9AlPShg_000140.mp4 people coughing +tests/VGGSound/video/QDfDR1bfMtQ_000020.mp4 lions roaring +tests/VGGSound/video/QDppmIicknY_000030.mp4 playing bagpipes +tests/VGGSound/video/MxSoqiN92v0_000134.mp4 elephant trumpeting +tests/VGGSound/video/QDqBJwoQcNY_000080.mp4 bird chirping, tweeting +tests/VGGSound/video/QEE70zlVRoM_000019.mp4 people sneezing +tests/VGGSound/video/MxlG--30VvM_000008.mp4 car engine idling +tests/VGGSound/video/MxxJWqd5948_000030.mp4 playing clarinet +tests/VGGSound/video/My0YmR6tYAk_000060.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/QEaBsR3qUKo_000180.mp4 singing bowl +tests/VGGSound/video/QEcZFvGVGf0_000111.mp4 playing theremin +tests/VGGSound/video/MyUItl-2v0U_000050.mp4 waterfall burbling +tests/VGGSound/video/QFIEGoEUJNk_000250.mp4 playing vibraphone +tests/VGGSound/video/QFIqELB7_xQ_000030.mp4 air horn +tests/VGGSound/video/QFnwnAHcttY_000030.mp4 toilet flushing +tests/VGGSound/video/MyjxrBI9k4o_000080.mp4 playing electric guitar +tests/VGGSound/video/QFovsFrNNfw_000136.mp4 skiing +tests/VGGSound/video/Mynx_hExwJw_000062.mp4 playing lacrosse +tests/VGGSound/video/QFyRflnHxxE_000020.mp4 cupboard opening or closing +tests/VGGSound/video/MzK0doyIM70_000500.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/QGhPi_IvNyk_000030.mp4 car engine knocking +tests/VGGSound/video/TmXQL325rjw_000450.mp4 slot machine +tests/VGGSound/video/N-6HKjQwPTo_000030.mp4 ambulance siren +tests/VGGSound/video/QHPJK945JVg_000010.mp4 reversing beeps +tests/VGGSound/video/QHVUSqKkrMc_000030.mp4 car engine knocking +tests/VGGSound/video/QHYI8sB-7hY_000254.mp4 cheetah chirrup +tests/VGGSound/video/QHeMFfKpBao_000141.mp4 smoke detector beeping +tests/VGGSound/video/QHkb-WsSsDI_000000.mp4 mouse clicking +tests/VGGSound/video/QHmGUrpOgAU_000070.mp4 playing mandolin +tests/VGGSound/video/N-kdCENmuAs_000039.mp4 penguins braying +tests/VGGSound/video/N-oRg5r2ndE_000034.mp4 plastic bottle crushing +tests/VGGSound/video/QI5VGU2pris_000060.mp4 ocean burbling +tests/VGGSound/video/N00JbKpZKKw_000446.mp4 playing oboe +tests/VGGSound/video/N0c6P3Po5J0_000062.mp4 cuckoo bird calling +tests/VGGSound/video/QIRX5273XKk_000030.mp4 people clapping +tests/VGGSound/video/N0c6P3Po5J0_000118.mp4 cuckoo bird calling +tests/VGGSound/video/N0d1cK2k1Eg_000000.mp4 cattle mooing +tests/VGGSound/video/N0eKjpEcyH4_000000.mp4 playing castanets +tests/VGGSound/video/N0jVgldCwAk_000000.mp4 bird chirping, tweeting +tests/VGGSound/video/QIVyLF2I7p0_000185.mp4 mosquito buzzing +tests/VGGSound/video/QIgtulpStxA_000030.mp4 playing flute +tests/VGGSound/video/N0tIa-fvjo0_000000.mp4 people nose blowing +tests/VGGSound/video/N0uNunAKh7w_000251.mp4 playing bongo +tests/VGGSound/video/QIuP8om7fYE_000069.mp4 popping popcorn +tests/VGGSound/video/QIumoU03aLY_000030.mp4 snake hissing +tests/VGGSound/video/TpX4tu7GrUw_000090.mp4 toilet flushing +tests/VGGSound/video/N1IM3f-TN4o_000000.mp4 smoke detector beeping +tests/VGGSound/video/QJAlLhhyawA_000070.mp4 donkey, ass braying +tests/VGGSound/video/N1KFGDFqWxM_000030.mp4 orchestra +tests/VGGSound/video/QJDLZ53UsLk_000320.mp4 car passing by +tests/VGGSound/video/QJEw9jknWlw_000050.mp4 bird wings flapping +tests/VGGSound/video/QJG6m9_iLBc_000182.mp4 hedge trimmer running +tests/VGGSound/video/QJGordCQPW0_000021.mp4 horse clip-clop +tests/VGGSound/video/N1c73HkaxvY_000000.mp4 cattle, bovinae cowbell +tests/VGGSound/video/N1dCXhy56po_000009.mp4 police car (siren) +tests/VGGSound/video/QJfusheJ-uE_000055.mp4 playing timbales +tests/VGGSound/video/QJumqm9_jz4_000030.mp4 orchestra +tests/VGGSound/video/QJzveo6IBsU_000000.mp4 playing timpani +tests/VGGSound/video/QK-mjNg8cPo_000050.mp4 playing banjo +tests/VGGSound/video/QK27EA8DmHQ_000385.mp4 disc scratching +tests/VGGSound/video/N2CdQ4bWCkE_000022.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/Ts04bBeY1d4_000030.mp4 playing acoustic guitar +tests/VGGSound/video/QKhVI1l78Uc_000014.mp4 missile launch +tests/VGGSound/video/QKkhwAAGLIE_000030.mp4 playing sitar +tests/VGGSound/video/QLEXmKz-MV4_000070.mp4 playing cymbal +tests/VGGSound/video/N3B-vKpsKoE_000125.mp4 cow lowing +tests/VGGSound/video/QLd4z4LPQC0_000000.mp4 air conditioning noise +tests/VGGSound/video/N3i32rhrX-s_000014.mp4 baby crying +tests/VGGSound/video/Tu1BmVrerAw_000330.mp4 hair dryer drying +tests/VGGSound/video/QMWp_fxNwqo_000330.mp4 plastic bottle crushing +tests/VGGSound/video/N4JQ0uzRjpA_000274.mp4 playing erhu +tests/VGGSound/video/QMc3zhoaU-Y_000057.mp4 chipmunk chirping +tests/VGGSound/video/N4QzDWQEhYE_000109.mp4 smoke detector beeping +tests/VGGSound/video/N4SfahxM8Z4_000004.mp4 airplane flyby +tests/VGGSound/video/QMp9444xI8c_000051.mp4 police car (siren) +tests/VGGSound/video/N4a0QKUEg90_000278.mp4 chopping food +tests/VGGSound/video/QMrxyrv_KXc_000226.mp4 volcano explosion +tests/VGGSound/video/N4yxwdPnRQk_000028.mp4 missile launch +tests/VGGSound/video/N54Bk7ZWm4g_000067.mp4 blowtorch igniting +tests/VGGSound/video/N5BAnG2zoUY_000030.mp4 pig oinking +tests/VGGSound/video/QNRche7AZkM_000270.mp4 male speech, man speaking +tests/VGGSound/video/QNekELxXfHw_000020.mp4 mouse pattering +tests/VGGSound/video/QNqDzw_QGpQ_000078.mp4 playing lacrosse +tests/VGGSound/video/QO00gXws7ak_000030.mp4 goose honking +tests/VGGSound/video/QOOL7pEKzYs_000371.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/N68rDUSvx9Y_000030.mp4 turkey gobbling +tests/VGGSound/video/QOqlkqTR82Q_000000.mp4 machine gun shooting +tests/VGGSound/video/QOxOf9ChFY4_000086.mp4 hail +tests/VGGSound/video/N6e5C5sXdBI_000000.mp4 dog howling +tests/VGGSound/video/N6jQ2uP0fcw_000080.mp4 bowling impact +tests/VGGSound/video/N6kPF5-9IOw_000034.mp4 barn swallow calling +tests/VGGSound/video/QPPapHk6lmU_000384.mp4 beat boxing +tests/VGGSound/video/QPR_tghZjAI_000030.mp4 people eating +tests/VGGSound/video/QPaUQdAWmLM_000236.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/QPw4_ga7J2o_000140.mp4 typing on typewriter +tests/VGGSound/video/QPyLES56O1w_000636.mp4 people slurping +tests/VGGSound/video/N7Ujd7RDg9g_000043.mp4 cat caterwauling +tests/VGGSound/video/N7_5mcVZgO8_000042.mp4 playing guiro +tests/VGGSound/video/N7tVUQOobkY_000289.mp4 people eating noodle +tests/VGGSound/video/QQXXuUz87nw_000030.mp4 playing harp +tests/VGGSound/video/U-1saFb-zRY_000006.mp4 playing djembe +tests/VGGSound/video/N8ImCT_PxL8_000070.mp4 singing bowl +tests/VGGSound/video/N8fI8HDoUGM_000118.mp4 people eating crisps +tests/VGGSound/video/QR0yjU4K2GM_000030.mp4 frog croaking +tests/VGGSound/video/N8iIq2UzZLk_000030.mp4 playing acoustic guitar +tests/VGGSound/video/QRKc90kuAaE_000560.mp4 playing cymbal +tests/VGGSound/video/QRbVHBt8dcE_000496.mp4 tractor digging +tests/VGGSound/video/QRlCOVibJs8_000270.mp4 pigeon, dove cooing +tests/VGGSound/video/N9C2AYVnas4_000130.mp4 people sniggering +tests/VGGSound/video/QRyTz1FCYuU_000030.mp4 cat purring +tests/VGGSound/video/N9N4AZXwWaM_000140.mp4 playing table tennis +tests/VGGSound/video/N9VpRM5Dx3g_000133.mp4 magpie calling +tests/VGGSound/video/QSCQG99jmnI_000003.mp4 yodelling +tests/VGGSound/video/N9hbVla0XmE_000087.mp4 playing bass drum +tests/VGGSound/video/N9o9qiAQv_U_000020.mp4 goat bleating +tests/VGGSound/video/QSaX7QfeWog_000030.mp4 playing mandolin +tests/VGGSound/video/NAVsBfOjc4c_000590.mp4 playing marimba, xylophone +tests/VGGSound/video/QTCgvm9f768_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/NAdLC19r7MU_000245.mp4 planing timber +tests/VGGSound/video/NAdLwXCxpS0_000162.mp4 planing timber +tests/VGGSound/video/NAiOfUtiXeM_000030.mp4 railroad car, train wagon +tests/VGGSound/video/QTT0Cc70d5k_000048.mp4 playing harpsichord +tests/VGGSound/video/U2Z3gH8r1hE_000160.mp4 people babbling +tests/VGGSound/video/QTbtvbzBs00_000038.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/QTbtvbzBs00_000063.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/QTyxozlbkkQ_000175.mp4 playing washboard +tests/VGGSound/video/NBEjt0DMzmQ_000190.mp4 smoke detector beeping +tests/VGGSound/video/QUX611hihf4_000190.mp4 playing accordion +tests/VGGSound/video/QUl8YgqhZPo_000028.mp4 playing bassoon +tests/VGGSound/video/NC6fdGYuHh4_000083.mp4 hail +tests/VGGSound/video/NCSXKxmlusY_000000.mp4 crow cawing +tests/VGGSound/video/NChR0sxb9ig_000039.mp4 spraying water +tests/VGGSound/video/QVprWKMTOz8_000030.mp4 people sobbing +tests/VGGSound/video/NCvAt5g3Zgo_000031.mp4 playing tennis +tests/VGGSound/video/ND5nBdo7Lwo_000090.mp4 cap gun shooting +tests/VGGSound/video/QW8-FlKlqAA_000480.mp4 playing bagpipes +tests/VGGSound/video/U6U6DxCLIqo_000325.mp4 train horning +tests/VGGSound/video/NDLPoJsqqoA_000060.mp4 wind noise +tests/VGGSound/video/NDkg1d91Yq0_000206.mp4 roller coaster running +tests/VGGSound/video/U7WkuGO-lps_000020.mp4 toilet flushing +tests/VGGSound/video/NDovY5OEt2o_000030.mp4 fire truck siren +tests/VGGSound/video/NDyi6BH9r38_000320.mp4 cat purring +tests/VGGSound/video/QWxrKBmwNw0_000030.mp4 typing on typewriter +tests/VGGSound/video/U7nHdo5Bx9g_000070.mp4 playing gong +tests/VGGSound/video/NEEr5ZgkrbE_000022.mp4 people eating +tests/VGGSound/video/NEGXDnMhd5A_000040.mp4 splashing water +tests/VGGSound/video/NEL02rjm79A_000074.mp4 dinosaurs bellowing +tests/VGGSound/video/NEUZUB2K1aI_000078.mp4 sea lion barking +tests/VGGSound/video/NE_DQerjrVU_000020.mp4 playing hammond organ +tests/VGGSound/video/QXSNf9K-YZw_000094.mp4 wind chime +tests/VGGSound/video/U8gvbrL-5DU_000315.mp4 airplane +tests/VGGSound/video/U8kJ9DFX6S0_000140.mp4 toilet flushing +tests/VGGSound/video/NEi-LsJkgE4_000030.mp4 singing choir +tests/VGGSound/video/QXe9BpTENCc_000030.mp4 playing sitar +tests/VGGSound/video/NEm4vbonbH4_000076.mp4 francolin calling +tests/VGGSound/video/U8rWZXjH2cU_000040.mp4 female singing +tests/VGGSound/video/NEwwubAohnk_000270.mp4 ripping paper +tests/VGGSound/video/QXnFAcMyAHA_000030.mp4 playing harp +tests/VGGSound/video/QXnJ2manIdI_000030.mp4 female speech, woman speaking +tests/VGGSound/video/NF1lwZ24RYI_000030.mp4 dog barking +tests/VGGSound/video/NF2SR1eHgU8_000030.mp4 people eating +tests/VGGSound/video/QYQEW3Alj78_000111.mp4 squishing water +tests/VGGSound/video/NFjonUQRHfE_000020.mp4 splashing water +tests/VGGSound/video/NFkZs_B6Cew_000006.mp4 people marching +tests/VGGSound/video/QYY8g4sMVWU_000030.mp4 basketball bounce +tests/VGGSound/video/QYYfs7ehzuc_000126.mp4 playing lacrosse +tests/VGGSound/video/NGG0Iosv8Lo_000108.mp4 playing squash +tests/VGGSound/video/NGG0Iosv8Lo_000183.mp4 playing squash 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+tests/VGGSound/video/NIRF2ugmr9o_000030.mp4 wind rustling leaves +tests/VGGSound/video/QaL51pYn4uQ_000020.mp4 playing harp +tests/VGGSound/video/NIRIm_X74e8_000101.mp4 golf driving +tests/VGGSound/video/NIUD5tnT_NQ_000308.mp4 people eating noodle +tests/VGGSound/video/NIXYf0CSnhE_000080.mp4 people hiccup +tests/VGGSound/video/Qa_6nlhGR9k_000051.mp4 canary calling +tests/VGGSound/video/NIklY_eIHdQ_000039.mp4 tap dancing +tests/VGGSound/video/NIuu97_y33A_000030.mp4 playing cello +tests/VGGSound/video/QalzlvZGJEw_000383.mp4 lip smacking +tests/VGGSound/video/NJJg575V_fc_000080.mp4 playing tambourine +tests/VGGSound/video/QbZlxKxp4Dw_000000.mp4 people nose blowing +tests/VGGSound/video/Qbf924lc3CQ_000402.mp4 sharpen knife +tests/VGGSound/video/NJUl3gPX07o_000030.mp4 chainsawing trees +tests/VGGSound/video/NJWBq2eQzg0_000030.mp4 duck quacking +tests/VGGSound/video/Qbo3Xrn8Ezk_000023.mp4 eagle screaming +tests/VGGSound/video/UFSp546472I_000010.mp4 people hiccup 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gargling +tests/VGGSound/video/NTyKi3QGd4k_000090.mp4 playing electronic organ +tests/VGGSound/video/QmYk9LxD_JE_000000.mp4 cell phone buzzing +tests/VGGSound/video/NUEfNw3Mdsw_000249.mp4 car engine idling +tests/VGGSound/video/NV0P4YtItzc_000110.mp4 people hiccup +tests/VGGSound/video/NV5_gB_6VLE_000005.mp4 duck quacking +tests/VGGSound/video/QnFmMOeStIs_000307.mp4 playing darts +tests/VGGSound/video/NVGscIW8Yuc_000010.mp4 baby babbling +tests/VGGSound/video/QnR9JhVGgu8_000348.mp4 car engine idling +tests/VGGSound/video/QnSGIwjh_ys_000087.mp4 spraying water +tests/VGGSound/video/QnSGIwjh_ys_000100.mp4 spraying water +tests/VGGSound/video/NVTJVKF_ZTw_000030.mp4 door slamming +tests/VGGSound/video/QnUf5DDKp8s_000050.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/Qna9qrV8_go_000030.mp4 driving buses +tests/VGGSound/video/UTYx0JO_65M_000260.mp4 subway, metro, underground +tests/VGGSound/video/NWL-P08eM-U_000030.mp4 rapping +tests/VGGSound/video/NWSPfogY_Ms_000570.mp4 playing cymbal 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saxophone +tests/VGGSound/video/UapBvuAH7p0_000110.mp4 opening or closing drawers +tests/VGGSound/video/NcIR-UiXJI0_000030.mp4 chicken crowing +tests/VGGSound/video/NcIt4xNctkA_000050.mp4 frog croaking +tests/VGGSound/video/NcKhJQPS_hs_000047.mp4 playing castanets +tests/VGGSound/video/NcPJaZwMrG8_000200.mp4 bird wings flapping +tests/VGGSound/video/NcRkQT2tP7s_000040.mp4 people belly laughing +tests/VGGSound/video/Ncdv7wCGgYE_000030.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/QupB4NN8fI0_000030.mp4 playing cello +tests/VGGSound/video/Quqx2Iga5b8_000086.mp4 chipmunk chirping +tests/VGGSound/video/NcllrpzRk38_000041.mp4 baltimore oriole calling +tests/VGGSound/video/Quz0khHKKAg_000262.mp4 playing timbales +tests/VGGSound/video/Nd2HKDBMkYo_000414.mp4 playing volleyball +tests/VGGSound/video/QvIuzUF1fWs_000217.mp4 playing tympani +tests/VGGSound/video/QvLeTxLGV_o_000030.mp4 playing banjo +tests/VGGSound/video/NdFLZw6nxxw_000145.mp4 shot football 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people sniggering +tests/VGGSound/video/Ng9bw-BkB94_000030.mp4 eletric blender running +tests/VGGSound/video/NgAEMX5d5iM_000083.mp4 train wheels squealing +tests/VGGSound/video/NgCb15bD3eo_000000.mp4 playing harmonica +tests/VGGSound/video/UfMr4FFsS28_000021.mp4 cat meowing +tests/VGGSound/video/QxoFXPR3nOI_000086.mp4 footsteps on snow +tests/VGGSound/video/Qy6DeQnCHuU_000030.mp4 horse clip-clop +tests/VGGSound/video/QyGfqIKBGFE_000005.mp4 shot football +tests/VGGSound/video/QyJ4Z0jRJ20_000030.mp4 dog whimpering +tests/VGGSound/video/QySssFgqGq0_000121.mp4 missile launch +tests/VGGSound/video/QyVrKAoUmW4_000287.mp4 playing hockey +tests/VGGSound/video/NgyeHliItww_000000.mp4 using sewing machines +tests/VGGSound/video/Nh0zABnSK6E_000017.mp4 bird wings flapping +tests/VGGSound/video/QyvAU6kcHBw_000083.mp4 cow lowing +tests/VGGSound/video/Qz-8mReB74w_000570.mp4 pigeon, dove cooing +tests/VGGSound/video/NhSTXTevuLo_000117.mp4 playing hockey +tests/VGGSound/video/NhWhPUIeSLM_000005.mp4 hail 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people nose blowing +tests/VGGSound/video/R1CqlyLZl28_000005.mp4 playing lacrosse +tests/VGGSound/video/R1DA-D5mA54_000038.mp4 hail +tests/VGGSound/video/NkUzNAvYKLA_000001.mp4 arc welding +tests/VGGSound/video/R1RGIgC-xKw_000030.mp4 playing banjo +tests/VGGSound/video/R1Tzk_uQGJ8_000304.mp4 yodelling +tests/VGGSound/video/R1zoAMguO3A_000150.mp4 helicopter +tests/VGGSound/video/R2Aq_j1TDSs_000040.mp4 helicopter +tests/VGGSound/video/NlCfScKw_Mk_000030.mp4 playing synthesizer +tests/VGGSound/video/R2LpN5yc8DA_000271.mp4 blowtorch igniting +tests/VGGSound/video/R2jQmn99gME_000260.mp4 church bell ringing +tests/VGGSound/video/Nluf6HIYXXQ_000030.mp4 dog howling +tests/VGGSound/video/Nlz4K0vYExA_000004.mp4 cutting hair with electric trimmers +tests/VGGSound/video/R371djhXr9w_000070.mp4 people screaming +tests/VGGSound/video/UmzWXYqphxI_000180.mp4 stream burbling +tests/VGGSound/video/UnMk7X7PM80_000139.mp4 canary calling +tests/VGGSound/video/R3ZTE3rmutA_000036.mp4 children shouting 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+tests/VGGSound/video/R4jlQEweREY_000030.mp4 playing didgeridoo +tests/VGGSound/video/No4Aig7t7YY_000018.mp4 baltimore oriole calling +tests/VGGSound/video/No4Aig7t7YY_000062.mp4 baltimore oriole calling +tests/VGGSound/video/Upq4yFKwiTM_000024.mp4 woodpecker pecking tree +tests/VGGSound/video/R5FhPTwWpm8_000140.mp4 skidding +tests/VGGSound/video/R5HBBqLJsCk_000247.mp4 squishing water +tests/VGGSound/video/R5JRh08zgMo_000030.mp4 mouse squeaking +tests/VGGSound/video/R5K3km8Fbs8_000019.mp4 printer printing +tests/VGGSound/video/R5VXim4mGjM_000139.mp4 strike lighter +tests/VGGSound/video/R5np0eUAWUU_000000.mp4 basketball bounce +tests/VGGSound/video/NouxIkaUjNA_000060.mp4 playing hammond organ +tests/VGGSound/video/UqMeR5Erq8I_000030.mp4 chicken crowing +tests/VGGSound/video/Np8xWk-a7a8_000008.mp4 people booing +tests/VGGSound/video/NpBQ1NpljTQ_000410.mp4 subway, metro, underground +tests/VGGSound/video/R60qQ3ag8y8_000100.mp4 playing piano +tests/VGGSound/video/R63TQ4aEGYA_000410.mp4 firing muskets +tests/VGGSound/video/NpGTa9fRvUU_000030.mp4 lawn mowing +tests/VGGSound/video/UqyvFyQthHo_000030.mp4 chainsawing trees +tests/VGGSound/video/R6EbA_Is4gc_000520.mp4 playing tabla +tests/VGGSound/video/UrgzGbGVV8I_000030.mp4 playing electric guitar +tests/VGGSound/video/Nq-jBzkOKwA_000004.mp4 opening or closing car doors +tests/VGGSound/video/R6hwadNOJcg_000052.mp4 playing oboe +tests/VGGSound/video/R6hwadNOJcg_000156.mp4 playing oboe +tests/VGGSound/video/NqFVTvBlxPw_000023.mp4 smoke detector beeping +tests/VGGSound/video/Nqb7nw58q08_000030.mp4 tapping guitar +tests/VGGSound/video/NqecEAJGCLA_000010.mp4 chipmunk chirping +tests/VGGSound/video/NqecEAJGCLA_000021.mp4 chipmunk chirping +tests/VGGSound/video/NqiYauilAA0_000073.mp4 rope skipping +tests/VGGSound/video/NqiuO8Ubwx0_000030.mp4 people shuffling +tests/VGGSound/video/UsWjp6XSz5g_000030.mp4 people burping +tests/VGGSound/video/UsdoUjuczY4_000030.mp4 playing cymbal +tests/VGGSound/video/R7EhJNlGPm0_000009.mp4 tornado roaring +tests/VGGSound/video/NqzZbJJl3E4_000030.mp4 reversing beeps +tests/VGGSound/video/Nr4A9fsk0bE_000034.mp4 scuba diving +tests/VGGSound/video/NrJMjHIcsto_000140.mp4 bowling impact +tests/VGGSound/video/R7j-rhd-D08_000030.mp4 printer printing +tests/VGGSound/video/UtLBZ7hS9nU_000030.mp4 people finger snapping +tests/VGGSound/video/UtMZGT9opoU_000265.mp4 people eating noodle +tests/VGGSound/video/UuBSbvH6ql8_000029.mp4 wood thrush calling +tests/VGGSound/video/Ns-iXXKmzzU_000030.mp4 male singing +tests/VGGSound/video/Ns9Zf0DrFlk_000212.mp4 cat caterwauling +tests/VGGSound/video/NsUPB1V0c50_000099.mp4 arc welding +tests/VGGSound/video/Uv8z7inZKpU_000230.mp4 skidding +tests/VGGSound/video/NsbLeONN0-c_000188.mp4 playing violin, fiddle +tests/VGGSound/video/R97UPoZ9V08_000263.mp4 playing guiro +tests/VGGSound/video/Nsjm00Bwebo_000140.mp4 bird squawking +tests/VGGSound/video/R9MmLB_WMzk_000560.mp4 bird wings flapping +tests/VGGSound/video/NszOg5SuMt4_000033.mp4 people slapping +tests/VGGSound/video/UvgwelALqcs_000040.mp4 cuckoo bird calling +tests/VGGSound/video/UvgwelALqcs_000181.mp4 cuckoo bird calling +tests/VGGSound/video/NtDrO2ZlnTs_000050.mp4 people slapping +tests/VGGSound/video/Uvvl1qfsh8A_000063.mp4 baltimore oriole calling +tests/VGGSound/video/NtM3gudMBCQ_000010.mp4 playing drum kit +tests/VGGSound/video/R9qOM83klNc_000081.mp4 children shouting +tests/VGGSound/video/NtlnhSzHhss_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/RA8ck5zeHM0_000000.mp4 toilet flushing +tests/VGGSound/video/Ntn6YvZM3kA_000000.mp4 people screaming +tests/VGGSound/video/NtrzegOYOyY_000020.mp4 people booing +tests/VGGSound/video/RAB0TWMYQHI_000000.mp4 ambulance siren +tests/VGGSound/video/UxBvDjoU8JI_000046.mp4 strike lighter +tests/VGGSound/video/NuD6d2B3QvA_000550.mp4 dog barking +tests/VGGSound/video/NuWl6FHUh7Y_000207.mp4 playing bugle +tests/VGGSound/video/R5dvHVDSXog_000048.mp4 train whistling +tests/VGGSound/video/UqtPREndv_0_000000.mp4 people eating crisps +tests/VGGSound/video/Ur5ce8KvhYs_000002.mp4 driving snowmobile +tests/VGGSound/video/UrUJ9tUJynA_000030.mp4 child singing +tests/VGGSound/video/UyCw7pCgYg8_000055.mp4 tap dancing +tests/VGGSound/video/NuqLe9Svlio_000443.mp4 playing erhu +tests/VGGSound/video/NuvgBjmUW1g_000140.mp4 dog growling +tests/VGGSound/video/Nuyu78uZcVE_000058.mp4 playing djembe +tests/VGGSound/video/RB3Lv2xNMY4_000000.mp4 golf driving +tests/VGGSound/video/Nuyu78uZcVE_000162.mp4 playing djembe +tests/VGGSound/video/Uyiq_U3Idso_000141.mp4 canary calling +tests/VGGSound/video/NvArhDtBvcg_000030.mp4 singing bowl +tests/VGGSound/video/NvIZAovN5s8_000308.mp4 airplane +tests/VGGSound/video/NvN2PoU3Pzs_000678.mp4 people slurping +tests/VGGSound/video/Nv_BiqJBsTs_000011.mp4 playing bugle +tests/VGGSound/video/RBvHrG87Jiw_000030.mp4 cattle mooing +tests/VGGSound/video/UzEFRNWEqQ4_000130.mp4 playing cello +tests/VGGSound/video/RCBdWzBxk0Y_000004.mp4 playing bass drum +tests/VGGSound/video/UzUTFdlYT68_000055.mp4 owl hooting +tests/VGGSound/video/Nvy70GTLwbM_000051.mp4 airplane flyby +tests/VGGSound/video/NvzT72qSSIE_000030.mp4 ocean burbling +tests/VGGSound/video/RCfTxRhPoNE_000071.mp4 barn swallow calling +tests/VGGSound/video/NwA9JSlK_lM_000030.mp4 playing banjo +tests/VGGSound/video/RCrvBDoPDGw_000000.mp4 sea waves +tests/VGGSound/video/NwBREzh6M_I_000050.mp4 opening or closing drawers +tests/VGGSound/video/NwGcF_Ud-ig_000000.mp4 driving motorcycle +tests/VGGSound/video/NwJA3sn2O78_000195.mp4 people marching +tests/VGGSound/video/RD7ho_gPnnY_000201.mp4 driving snowmobile +tests/VGGSound/video/RDCeLCJp7NM_000000.mp4 coyote howling +tests/VGGSound/video/NwWdqtapeqM_000230.mp4 typing on typewriter +tests/VGGSound/video/RDG7jY7P_8M_000088.mp4 penguins braying +tests/VGGSound/video/NwfEO8cjSK0_000030.mp4 playing synthesizer +tests/VGGSound/video/NwjeIU2xKE8_000238.mp4 hammering nails +tests/VGGSound/video/NwpT3VmaDGE_000205.mp4 playing bassoon +tests/VGGSound/video/V0ptxvriHOo_000127.mp4 civil defense siren +tests/VGGSound/video/NxP9CfxfJxg_000040.mp4 turkey gobbling +tests/VGGSound/video/REAlPEWq33c_000340.mp4 playing saxophone +tests/VGGSound/video/REDLY6m3Muw_000042.mp4 civil defense siren +tests/VGGSound/video/REREZlcbGvU_000046.mp4 opening or closing car electric windows +tests/VGGSound/video/REjC6sK5Msk_000156.mp4 airplane +tests/VGGSound/video/NyQLtzRw9-0_000046.mp4 air conditioning noise +tests/VGGSound/video/NyWZtL6Essc_000038.mp4 people belly laughing +tests/VGGSound/video/Nyi9_-u6-w0_000030.mp4 driving buses +tests/VGGSound/video/NyiNCt57BfE_000618.mp4 scuba diving +tests/VGGSound/video/NynrI4Tm9zo_000052.mp4 playing timbales +tests/VGGSound/video/RF3rog2YjYw_000030.mp4 baby laughter +tests/VGGSound/video/V2CS8ToddTE_000030.mp4 singing choir +tests/VGGSound/video/Nz4iLzJBTBo_000300.mp4 church bell ringing +tests/VGGSound/video/NzWgMNQX5xw_000018.mp4 fire crackling +tests/VGGSound/video/V2_U4WLNC9c_000025.mp4 police car (siren) +tests/VGGSound/video/RFbWkL818XQ_000030.mp4 playing banjo +tests/VGGSound/video/RFeU64gTvGQ_000000.mp4 people coughing +tests/VGGSound/video/RFjRJmGYrCg_000572.mp4 playing djembe +tests/VGGSound/video/NzvkMWY4EjA_000030.mp4 playing electric guitar +tests/VGGSound/video/RG-Tky7XSqw_000460.mp4 playing electronic organ +tests/VGGSound/video/RG3JF7GRfRE_000832.mp4 tornado roaring +tests/VGGSound/video/RGB0pMtcGhc_000090.mp4 playing saxophone +tests/VGGSound/video/V3aaPyUdIyo_000254.mp4 playing double bass +tests/VGGSound/video/O-AHz1rgAi0_000050.mp4 otter growling +tests/VGGSound/video/O-AHz1rgAi0_000122.mp4 otter growling +tests/VGGSound/video/RGTWqZoswAo_000030.mp4 playing didgeridoo +tests/VGGSound/video/RGWC7icTM_E_000031.mp4 male singing +tests/VGGSound/video/RGbFZcXDZJw_000008.mp4 slot machine +tests/VGGSound/video/O-UIOSuqzWA_000001.mp4 woodpecker pecking tree +tests/VGGSound/video/V4RmD_obUBo_000125.mp4 race car, auto racing +tests/VGGSound/video/O-VVb8Ag49g_000040.mp4 ocean burbling +tests/VGGSound/video/O-Y1CBYW0-M_000040.mp4 playing bagpipes +tests/VGGSound/video/O-ZZyuA5fRc_000028.mp4 cat hissing +tests/VGGSound/video/V54-dh4RQdQ_000000.mp4 singing bowl +tests/VGGSound/video/O2HttJtcec4_000030.mp4 playing acoustic guitar +tests/VGGSound/video/V8pFubugOSc_000037.mp4 cat growling +tests/VGGSound/video/RJlF5YycahI_000408.mp4 francolin calling +tests/VGGSound/video/RJmH-Tx9XuQ_000145.mp4 playing tennis +tests/VGGSound/video/RJtn6Td3rco_000068.mp4 missile launch +tests/VGGSound/video/RHYNFIUe7H8_000001.mp4 canary calling +tests/VGGSound/video/RI2T1BBL_8I_000030.mp4 people shuffling +tests/VGGSound/video/O0evobAsVkQ_000185.mp4 strike lighter +tests/VGGSound/video/RIGQjzXbvv4_000140.mp4 volcano explosion +tests/VGGSound/video/O0sDg-yLvlE_000030.mp4 playing mandolin +tests/VGGSound/video/RIQzc8Gx0q4_000026.mp4 electric grinder grinding +tests/VGGSound/video/O0yF1zdqpIc_000030.mp4 playing synthesizer +tests/VGGSound/video/O15hBKDfG1k_000350.mp4 people sobbing +tests/VGGSound/video/O1RmrE_HfpE_000030.mp4 playing didgeridoo +tests/VGGSound/video/V7edkwJsgN0_000030.mp4 playing cello +tests/VGGSound/video/O1jGNd4Deys_000050.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/RJFdWGEdzP4_000160.mp4 fox barking +tests/VGGSound/video/RJOBq50THOk_000030.mp4 sliding door +tests/VGGSound/video/V88sUJKgOsk_000034.mp4 missile launch +tests/VGGSound/video/V9EFYFKlYbE_000030.mp4 rapping +tests/VGGSound/video/O2y4wIUAlpg_000111.mp4 sharpen knife +tests/VGGSound/video/O30HsIQEeXc_000270.mp4 hair dryer drying +tests/VGGSound/video/RKIrnYwFosg_000352.mp4 playing badminton +tests/VGGSound/video/O3Cl6lDfdAo_000198.mp4 wind chime +tests/VGGSound/video/O3DrKE6qUT0_000001.mp4 people slapping +tests/VGGSound/video/RKOMrjtplik_000006.mp4 foghorn +tests/VGGSound/video/O3HG59u1yek_000030.mp4 people sobbing +tests/VGGSound/video/O3X4v0Kdtig_000226.mp4 slot machine +tests/VGGSound/video/O3ulYoQ5EiY_000030.mp4 playing sitar +tests/VGGSound/video/O41WqVK8Cjw_000100.mp4 playing shofar +tests/VGGSound/video/RL8F6782uuo_000014.mp4 heart sounds, heartbeat +tests/VGGSound/video/RLC6BxdpsqM_000150.mp4 church bell ringing +tests/VGGSound/video/RLJYigWchf0_000030.mp4 wind noise +tests/VGGSound/video/O4WYWXxjMwY_000000.mp4 mosquito buzzing +tests/VGGSound/video/RLij2FHY6VE_000009.mp4 dog bow-wow +tests/VGGSound/video/O4XYhK_tQnk_000028.mp4 playing violin, fiddle +tests/VGGSound/video/RLnAIkBccZk_000006.mp4 penguins braying +tests/VGGSound/video/O4kAF1fFCik_000030.mp4 people farting +tests/VGGSound/video/O4xrL3f3z4M_000017.mp4 car engine idling +tests/VGGSound/video/O4zq35Kga1c_000170.mp4 baby babbling +tests/VGGSound/video/RMKGMBFRYUQ_000165.mp4 cupboard opening or closing +tests/VGGSound/video/RMMcezvEugQ_000011.mp4 people battle cry +tests/VGGSound/video/RMPyriqNS-4_000013.mp4 cattle mooing +tests/VGGSound/video/O5IulN0n6d0_000030.mp4 rapping +tests/VGGSound/video/VE7k_K9kpsw_000096.mp4 bouncing on trampoline +tests/VGGSound/video/RMVwodtLI88_000500.mp4 sailing +tests/VGGSound/video/RMVwodtLI88_000631.mp4 sailing +tests/VGGSound/video/RMX2aviLZdo_000070.mp4 using sewing machines +tests/VGGSound/video/RN1ho4G-W0o_000040.mp4 wind noise +tests/VGGSound/video/O5v1-O5A-f0_000410.mp4 people sobbing +tests/VGGSound/video/VFXf1DTi2IA_000383.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/O67-3jP1DUs_000443.mp4 slot machine +tests/VGGSound/video/O69Yy17L9pY_000001.mp4 playing lacrosse +tests/VGGSound/video/O69hivnI5oM_000073.mp4 playing castanets +tests/VGGSound/video/O6G5efkuPYQ_000051.mp4 people slapping +tests/VGGSound/video/RN_qfzQUkeU_000300.mp4 cattle mooing +tests/VGGSound/video/ROCl79fqrSM_000519.mp4 playing tennis +tests/VGGSound/video/O7-ggV4SQRs_000030.mp4 helicopter +tests/VGGSound/video/O70kWGbFbbY_000204.mp4 playing congas +tests/VGGSound/video/RObYRwt7b8U_000189.mp4 playing tambourine +tests/VGGSound/video/O7D34TRxVTM_000061.mp4 playing washboard +tests/VGGSound/video/ROhlD0G2_ho_000017.mp4 wind rustling leaves +tests/VGGSound/video/O7NejftNvmc_000441.mp4 opening or closing car doors +tests/VGGSound/video/VHoOg4twnO0_000060.mp4 machine gun shooting +tests/VGGSound/video/ROtaeOZoTqU_000196.mp4 train wheels squealing +tests/VGGSound/video/VIQqrHGMJRQ_000173.mp4 playing bassoon +tests/VGGSound/video/O7oqO7fqmVs_000539.mp4 ripping paper +tests/VGGSound/video/RPA-QYPV_os_000030.mp4 fire crackling +tests/VGGSound/video/O7puBCRI2Bc_000030.mp4 playing flute +tests/VGGSound/video/RPMicSPIAlg_000030.mp4 female speech, woman speaking +tests/VGGSound/video/O84iR7J3oBU_000095.mp4 cell phone buzzing +tests/VGGSound/video/O8DtnVJN_dY_000030.mp4 fire truck siren +tests/VGGSound/video/RPscbFkdUto_000520.mp4 thunder +tests/VGGSound/video/O8S1mItzKFk_000115.mp4 disc scratching +tests/VGGSound/video/VJAJzwsogP8_000281.mp4 donkey, ass braying +tests/VGGSound/video/RQ85Tkl8i2k_000008.mp4 fireworks banging +tests/VGGSound/video/RQHsbSHEnYc_000009.mp4 running electric fan +tests/VGGSound/video/RQIVLqDLQzA_000050.mp4 using sewing machines +tests/VGGSound/video/RQMUz0NFx6o_000420.mp4 playing marimba, xylophone +tests/VGGSound/video/RQRipbhO86I_000040.mp4 playing volleyball +tests/VGGSound/video/O96eN6kkSsA_000011.mp4 pig oinking +tests/VGGSound/video/O97enrnp0MY_000328.mp4 planing timber +tests/VGGSound/video/O99ncoIkg2U_000000.mp4 wind noise +tests/VGGSound/video/O9ITnivTUXc_000028.mp4 chimpanzee pant-hooting +tests/VGGSound/video/O9KZqw2dyXM_000024.mp4 dog growling +tests/VGGSound/video/O9M7RtFP_-Y_000010.mp4 playing glockenspiel +tests/VGGSound/video/RQvbm3l3wmA_000110.mp4 playing drum kit +tests/VGGSound/video/RRAw_ogOfrk_000000.mp4 people farting +tests/VGGSound/video/O9dNbswLJu0_000331.mp4 playing congas +tests/VGGSound/video/O9sJ92Xn1jQ_000030.mp4 mouse squeaking +tests/VGGSound/video/RRdY9mWHqWo_000136.mp4 race car, auto racing +tests/VGGSound/video/OA-CIwRw6Qk_000030.mp4 playing french horn +tests/VGGSound/video/RRpcIanKONA_000025.mp4 smoke detector beeping +tests/VGGSound/video/OAEeDczKnCA_000200.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/VMWmX19efbw_000324.mp4 playing lacrosse +tests/VGGSound/video/RS43EP1EXz4_000030.mp4 playing ukulele +tests/VGGSound/video/RS8hMORLDPE_000091.mp4 playing shofar +tests/VGGSound/video/RSAyz5c3JmM_000160.mp4 ambulance siren +tests/VGGSound/video/RSPZSkLWsH4_000079.mp4 sheep bleating +tests/VGGSound/video/OAuVRzogngc_000340.mp4 mosquito buzzing +tests/VGGSound/video/OAyewg0sAeY_000000.mp4 snake hissing +tests/VGGSound/video/RSXUYIi95wo_000030.mp4 people whispering +tests/VGGSound/video/RSgmATBcCwE_000110.mp4 cow lowing +tests/VGGSound/video/OBAaK0pxdW0_000046.mp4 baby crying +tests/VGGSound/video/OBG8doMoB9I_000044.mp4 civil defense siren +tests/VGGSound/video/RSryuuvUfDM_000050.mp4 playing acoustic guitar +tests/VGGSound/video/RSvuhSQuSRc_000156.mp4 playing double bass +tests/VGGSound/video/OBR-aL7YXM8_000180.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/RT234P5SzJo_000460.mp4 lions roaring +tests/VGGSound/video/RTDr2L_OT0M_000030.mp4 printer printing +tests/VGGSound/video/OBwh-KGukE8_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/RTLGAJZ8WzM_000219.mp4 airplane +tests/VGGSound/video/VOkiX4gWRI0_000125.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/OCIQYk1eMHU_000120.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/VP0OZdz-0IY_000000.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/OCReBtZOo8A_000021.mp4 cow lowing +tests/VGGSound/video/OCTGiPOygds_000030.mp4 people clapping +tests/VGGSound/video/OCWQSILD8R4_000053.mp4 squishing water +tests/VGGSound/video/OD54eF2XKJA_000010.mp4 basketball bounce +tests/VGGSound/video/RVKBNv4mc6Y_000107.mp4 volcano explosion +tests/VGGSound/video/ODVjNjz3JYU_000000.mp4 penguins braying +tests/VGGSound/video/RVV2k3G6hes_000014.mp4 people slapping +tests/VGGSound/video/VS3vEkNN8uM_000100.mp4 police radio chatter +tests/VGGSound/video/ODoQDztFbaQ_000251.mp4 male speech, man speaking +tests/VGGSound/video/RUAomPTkvYM_000100.mp4 mynah bird singing +tests/VGGSound/video/OCaW_fZF1e8_000251.mp4 chimpanzee pant-hooting +tests/VGGSound/video/RUUZzoeVrK4_000020.mp4 orchestra +tests/VGGSound/video/VQbC7Oth7wQ_000030.mp4 typing on computer keyboard +tests/VGGSound/video/RUftlme_EtU_000010.mp4 cattle mooing +tests/VGGSound/video/OCwzCoB6p-4_000030.mp4 opening or closing drawers +tests/VGGSound/video/OD-fpsHQCFg_000080.mp4 playing trombone +tests/VGGSound/video/RUx39qofQ4M_000000.mp4 pumping water +tests/VGGSound/video/RW7x9AC7PZI_000030.mp4 playing piano +tests/VGGSound/video/RWVuRwtjGek_000210.mp4 subway, metro, underground +tests/VGGSound/video/VT-rnRYiNdo_000412.mp4 race car, auto racing +tests/VGGSound/video/RWZ8sRgIWBk_000120.mp4 firing cannon +tests/VGGSound/video/RWfQ46PM5jo_000011.mp4 mosquito buzzing 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+tests/VGGSound/video/OH2SQhJqZDg_000000.mp4 playing timpani +tests/VGGSound/video/OH8urnIthoQ_000060.mp4 playing electric guitar +tests/VGGSound/video/RYia-H9Hm88_000000.mp4 people clapping +tests/VGGSound/video/OHXzx_VG8_g_000110.mp4 bouncing on trampoline +tests/VGGSound/video/OHZIUdHm6b4_000078.mp4 people marching +tests/VGGSound/video/RZMgq7-EbUA_000024.mp4 pheasant crowing +tests/VGGSound/video/OHgO4UtGEtY_000104.mp4 cutting hair with electric trimmers +tests/VGGSound/video/OHkkIGrKEKk_000000.mp4 baltimore oriole calling +tests/VGGSound/video/RZajsvjHx74_000054.mp4 playing mandolin +tests/VGGSound/video/OI4vBlF4O-Y_000052.mp4 yodelling +tests/VGGSound/video/RZnC-ZFEqv8_000079.mp4 bowling impact +tests/VGGSound/video/OIDnou1IcNs_000042.mp4 playing congas +tests/VGGSound/video/VYyXt12fTHg_000240.mp4 playing tabla +tests/VGGSound/video/R_B5ruT7kAI_000000.mp4 train wheels squealing +tests/VGGSound/video/R_EnlXwBvtA_000078.mp4 playing squash 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harmonica +tests/VGGSound/video/OWuMapsvJ3w_000050.mp4 chainsawing trees +tests/VGGSound/video/VrimREPrM_o_000030.mp4 typing on typewriter +tests/VGGSound/video/Rn55rPN_JU4_000030.mp4 printer printing +tests/VGGSound/video/RnEA2zdAVE8_000015.mp4 people gargling +tests/VGGSound/video/OXi5eZwCoq0_000030.mp4 church bell ringing +tests/VGGSound/video/RncwRj1HhQc_000337.mp4 people eating noodle +tests/VGGSound/video/Rnf7M43L6NI_000195.mp4 train horning +tests/VGGSound/video/Rnk_a1FXc9I_000119.mp4 penguins braying +tests/VGGSound/video/Vsz6dpRCwSo_000380.mp4 chainsawing trees +tests/VGGSound/video/OYkZxbD0vr8_000040.mp4 people clapping +tests/VGGSound/video/RoS465ZH1lg_000013.mp4 cat hissing +tests/VGGSound/video/VtpsRl91doo_000064.mp4 electric grinder grinding +tests/VGGSound/video/VtuRGKGr3_Y_000008.mp4 police car (siren) +tests/VGGSound/video/Vu-x88iPIv8_000013.mp4 people shuffling +tests/VGGSound/video/OZ9ti0RBfr8_000029.mp4 playing tambourine +tests/VGGSound/video/OZJmpLg1Dgs_000097.mp4 ferret dooking +tests/VGGSound/video/OZJmpLg1Dgs_000151.mp4 ferret dooking +tests/VGGSound/video/Roq8wcXrs4w_000053.mp4 people nose blowing +tests/VGGSound/video/Rp37k5_Eci0_000030.mp4 lions roaring +tests/VGGSound/video/Rp39_WnX5Fk_000380.mp4 subway, metro, underground +tests/VGGSound/video/OZYy9dr0kGU_000023.mp4 chopping food +tests/VGGSound/video/Vuhp5vv5hoU_000360.mp4 playing snare drum +tests/VGGSound/video/OZjpYGdvMX0_000030.mp4 playing electric guitar +tests/VGGSound/video/RpGRpTpEHTs_000109.mp4 disc scratching +tests/VGGSound/video/OZk2KE5L7WU_000045.mp4 arc welding +tests/VGGSound/video/RpJnX6TNPRc_000400.mp4 baby babbling +tests/VGGSound/video/Vux4c-4LtVU_000059.mp4 sheep bleating +tests/VGGSound/video/OZv8mtQEgA0_000030.mp4 engine accelerating, revving, vroom +tests/VGGSound/video/O_8C1feaFac_000200.mp4 playing timpani +tests/VGGSound/video/RpkcGOcFHIs_000002.mp4 people booing +tests/VGGSound/video/RplzKlSlbR0_000035.mp4 people booing 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bird calling +tests/VGGSound/video/ObV0Fz5rJHQ_000035.mp4 cuckoo bird calling +tests/VGGSound/video/ObX2V23qOMc_000330.mp4 stream burbling +tests/VGGSound/video/ObdJilylBPw_000527.mp4 whale calling +tests/VGGSound/video/RsDl0An5QBI_000030.mp4 playing electric guitar +tests/VGGSound/video/ObhHyU04C40_000197.mp4 people slurping +tests/VGGSound/video/ObktirfMcns_000100.mp4 cricket chirping +tests/VGGSound/video/Oc9azgD3RJ8_000030.mp4 people babbling +tests/VGGSound/video/OcARIiLtPVg_000000.mp4 yodelling +tests/VGGSound/video/OcdrbkDm2LQ_000030.mp4 playing steelpan +tests/VGGSound/video/Oct7HCu1Vwo_000035.mp4 smoke detector beeping +tests/VGGSound/video/Od58AkKIPnA_000060.mp4 lathe spinning +tests/VGGSound/video/Rtg1SUrxOPY_000130.mp4 people coughing +tests/VGGSound/video/RtjWfV8ZZcc_000312.mp4 firing muskets +tests/VGGSound/video/RtsCVfcjlTo_000030.mp4 playing snare drum +tests/VGGSound/video/OdOu8yGpIig_000456.mp4 race car, auto racing +tests/VGGSound/video/RuCO6UGsRHI_000313.mp4 barn swallow calling +tests/VGGSound/video/RuHSkgQf3uw_000019.mp4 playing timbales +tests/VGGSound/video/OdteEPrGHrQ_000004.mp4 strike lighter +tests/VGGSound/video/W-QnsZHrJIs_000010.mp4 wind chime +tests/VGGSound/video/OePJCEQ8soo_000161.mp4 smoke detector beeping +tests/VGGSound/video/Rv99VXUmaIc_000000.mp4 spraying water +tests/VGGSound/video/OebTD1Qqjys_000055.mp4 cricket chirping +tests/VGGSound/video/RvHRucMiAbw_000000.mp4 bull bellowing +tests/VGGSound/video/RvOBWC1s28w_000015.mp4 mouse squeaking +tests/VGGSound/video/Oew6XicL4Ks_000150.mp4 people whistling +tests/VGGSound/video/RvWxnLolEbo_000056.mp4 heart sounds, heartbeat +tests/VGGSound/video/Of8M-fPb4bA_000247.mp4 barn swallow calling +tests/VGGSound/video/Of8y_rXXeSw_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/RwBKGPEg6uA_000440.mp4 railroad car, train wagon +tests/VGGSound/video/Ofjsr-iU7Vo_000000.mp4 lions roaring +tests/VGGSound/video/RxCzh7EoIFU_000025.mp4 missile launch 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playing accordion +tests/VGGSound/video/OhhSpbVbXYA_000145.mp4 playing tambourine +tests/VGGSound/video/OhmcZInYYwE_000173.mp4 playing tambourine +tests/VGGSound/video/W5eOW25vvbw_000030.mp4 playing bass guitar +tests/VGGSound/video/Oi5_iRBIKcA_000041.mp4 ice cracking +tests/VGGSound/video/Oi5mX1TqlX0_000000.mp4 striking bowling +tests/VGGSound/video/W5kJAQ_RI0M_000000.mp4 playing marimba, xylophone +tests/VGGSound/video/Oi855GiZQa0_000061.mp4 dinosaurs bellowing +tests/VGGSound/video/RzheyPWA3fA_000030.mp4 fire crackling +tests/VGGSound/video/W6KsrR_Nkrk_000000.mp4 metronome +tests/VGGSound/video/OjGbRQ7e_AU_000134.mp4 playing mandolin +tests/VGGSound/video/S-hZmb9byTg_000065.mp4 yodelling +tests/VGGSound/video/S-pO6kU4sO0_000082.mp4 golf driving +tests/VGGSound/video/S-rvkcb7xv8_000080.mp4 church bell ringing +tests/VGGSound/video/OjnIP1C1hMQ_000125.mp4 firing muskets +tests/VGGSound/video/OkAT5LKBbIE_000113.mp4 dog bow-wow +tests/VGGSound/video/OkAT5LKBbIE_000190.mp4 dog bow-wow +tests/VGGSound/video/W8N8mjzPjZk_000332.mp4 cutting hair with electric trimmers +tests/VGGSound/video/S0pMBvbIKRU_000030.mp4 playing zither +tests/VGGSound/video/S0tXw0I2l8M_000286.mp4 swimming +tests/VGGSound/video/OkMPd5IwM-w_000012.mp4 cuckoo bird calling +tests/VGGSound/video/OkYcKfqFNmM_000082.mp4 playing bugle +tests/VGGSound/video/S1Q2jwEX11U_000260.mp4 fireworks banging +tests/VGGSound/video/S1_mKhT8FVo_000028.mp4 playing hockey +tests/VGGSound/video/S1glY1D9qDU_000035.mp4 hedge trimmer running +tests/VGGSound/video/Okx87oCJg5g_000250.mp4 female singing +tests/VGGSound/video/S1zqcPCbOfk_000046.mp4 playing hockey +tests/VGGSound/video/OlBxrpelaUE_000040.mp4 playing tabla +tests/VGGSound/video/OlKY56Mdn4s_000386.mp4 ripping paper +tests/VGGSound/video/OlSY8_xG1CU_000167.mp4 strike lighter +tests/VGGSound/video/OleATZcF1P8_000056.mp4 children shouting +tests/VGGSound/video/Olfg9KK_bmE_000011.mp4 cricket chirping +tests/VGGSound/video/Olfiy3sCF88_000030.mp4 duck quacking +tests/VGGSound/video/S3cNSKFQkXo_000875.mp4 magpie calling +tests/VGGSound/video/OmlvTSN8aeo_000033.mp4 wood thrush calling +tests/VGGSound/video/OmvNQtdaX1A_000040.mp4 orchestra +tests/VGGSound/video/S3oZrMGDMMw_000010.mp4 people coughing +tests/VGGSound/video/On0BP2aY-nk_000061.mp4 mynah bird singing +tests/VGGSound/video/On2aeIUKoNY_000030.mp4 frog croaking +tests/VGGSound/video/On8mxembDtg_000550.mp4 railroad car, train wagon +tests/VGGSound/video/WCUOOS-CtZI_000131.mp4 playing squash +tests/VGGSound/video/OnGPRQdEPWw_000030.mp4 playing steelpan +tests/VGGSound/video/OnJaLTDVxjQ_000240.mp4 toilet flushing +tests/VGGSound/video/S4NcIl_T80Y_000109.mp4 golf driving +tests/VGGSound/video/OnRh-5IRG3A_000000.mp4 machine gun shooting +tests/VGGSound/video/Onbb3eEOuGQ_000010.mp4 lions roaring +tests/VGGSound/video/Onj6sJIPj7M_000006.mp4 arc welding +tests/VGGSound/video/S5-JYwnAqbU_000007.mp4 playing volleyball +tests/VGGSound/video/Oo3cKxlkQZc_000030.mp4 people finger snapping +tests/VGGSound/video/OoAUkRN1qEs_000139.mp4 eletric blender running +tests/VGGSound/video/OoTeWhAzPOU_000059.mp4 ice cracking +tests/VGGSound/video/S5Tff1ohiJE_000030.mp4 chopping wood +tests/VGGSound/video/OoUncWICg-s_000110.mp4 playing banjo +tests/VGGSound/video/S6-B6QfvS-I_000200.mp4 waterfall burbling +tests/VGGSound/video/S63LEKmzBis_000039.mp4 lathe spinning +tests/VGGSound/video/Op2FDOmuHE8_000198.mp4 metronome +tests/VGGSound/video/S6R2DpF6zzM_000018.mp4 baltimore oriole calling +tests/VGGSound/video/S6R2DpF6zzM_000060.mp4 baltimore oriole calling +tests/VGGSound/video/S6Y0ppbB65E_000000.mp4 people cheering +tests/VGGSound/video/Op6UazVNEQg_000003.mp4 telephone bell ringing +tests/VGGSound/video/WFV3FUlTzas_000061.mp4 missile launch +tests/VGGSound/video/WFgIargH3-4_000039.mp4 dog baying +tests/VGGSound/video/S7C51ZWaw6A_000034.mp4 airplane +tests/VGGSound/video/Oq0gZiJxP5Q_000018.mp4 goose honking +tests/VGGSound/video/WGOZNdTXITQ_000205.mp4 playing squash +tests/VGGSound/video/OqGQ72bre30_000035.mp4 playing table tennis +tests/VGGSound/video/S7tyzFdnDhA_000000.mp4 playing electronic organ +tests/VGGSound/video/S86Ql_59KMI_000211.mp4 playing erhu +tests/VGGSound/video/WGuc_McKm_4_000030.mp4 people sniggering +tests/VGGSound/video/OqUYjRzUis4_000120.mp4 train horning +tests/VGGSound/video/OqcyTQMUnMw_000057.mp4 donkey, ass braying +tests/VGGSound/video/OqcyTQMUnMw_000092.mp4 donkey, ass braying +tests/VGGSound/video/WHPs1ypOoNc_000327.mp4 playing lacrosse +tests/VGGSound/video/OqjRuWUFQy8_000140.mp4 railroad car, train wagon +tests/VGGSound/video/S8RC6WZFqjk_000072.mp4 playing timbales +tests/VGGSound/video/S8fjyxM7DgU_000010.mp4 thunder +tests/VGGSound/video/S8i_PSyGgYk_000061.mp4 playing shofar +tests/VGGSound/video/Or9l14hzfSA_000030.mp4 dog bow-wow +tests/VGGSound/video/WI9yLdGPtYQ_000218.mp4 playing washboard +tests/VGGSound/video/OrSfdkVVbOQ_000000.mp4 machine gun shooting +tests/VGGSound/video/OrVb-GSGKPI_000032.mp4 fly, housefly buzzing +tests/VGGSound/video/OrYHuCwfvb4_000000.mp4 playing cymbal +tests/VGGSound/video/OrZNGml0csQ_000022.mp4 car engine starting +tests/VGGSound/video/Orge4_UlvNI_000280.mp4 playing sitar +tests/VGGSound/video/OruJS8cr2qE_000005.mp4 parrot talking +tests/VGGSound/video/S9x1Kop188c_000253.mp4 electric grinder grinding +tests/VGGSound/video/SA18ixsI9fI_000044.mp4 ice cream truck, ice cream van +tests/VGGSound/video/SAFlijpaj0Q_000024.mp4 people shuffling +tests/VGGSound/video/Os_DQIRQgXw_000002.mp4 car engine starting +tests/VGGSound/video/WJLbFJxe11o_000030.mp4 playing harmonica +tests/VGGSound/video/Osm09kE9uCY_000030.mp4 stream burbling +tests/VGGSound/video/SAWpARHD724_000065.mp4 whale calling +tests/VGGSound/video/Osr4Sfb97xs_000060.mp4 people sneezing +tests/VGGSound/video/WJijwC4OgX8_000024.mp4 bowling impact +tests/VGGSound/video/WJkL2eAUNtQ_000143.mp4 disc scratching +tests/VGGSound/video/SAcpESN_Fk4_000089.mp4 female singing +tests/VGGSound/video/SAf8CL1pMFY_000102.mp4 playing double bass +tests/VGGSound/video/SB1dEgUQh3w_000168.mp4 electric grinder grinding +tests/VGGSound/video/SB1dEgUQh3w_000187.mp4 electric grinder grinding +tests/VGGSound/video/OtWlvdhCJj4_000051.mp4 woodpecker pecking tree +tests/VGGSound/video/Ota5gx9Axq8_000030.mp4 typing on typewriter +tests/VGGSound/video/SBVvm2xyVLU_000380.mp4 eating with cutlery +tests/VGGSound/video/SBeC9TISHz8_000030.mp4 playing mandolin +tests/VGGSound/video/Ou9HV5j8eho_000060.mp4 people sobbing +tests/VGGSound/video/SBsajFvgc7Y_000170.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/SBwyfAg28OE_000060.mp4 playing tabla +tests/VGGSound/video/OugiXVgs0tA_000069.mp4 blowtorch igniting +tests/VGGSound/video/OuvUTzK6Ix4_000040.mp4 cap gun shooting +tests/VGGSound/video/Ouxjt5e8x-o_000050.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/SCbqy_gry8c_000240.mp4 cell phone buzzing +tests/VGGSound/video/OvJJbbiz9y8_000042.mp4 cheetah chirrup +tests/VGGSound/video/OvJJbbiz9y8_000070.mp4 cheetah chirrup +tests/VGGSound/video/SCxlAcrMark_000021.mp4 cuckoo bird calling +tests/VGGSound/video/SCz5A__8owI_000030.mp4 singing bowl +tests/VGGSound/video/Ovm9kLKgLww_000120.mp4 car engine idling +tests/VGGSound/video/Ovwr3IroFXo_000005.mp4 police radio chatter +tests/VGGSound/video/SDdlINEPMPc_000030.mp4 wind rustling leaves +tests/VGGSound/video/OwAUGABGrqk_000030.mp4 people coughing +tests/VGGSound/video/SDhI4yyHlEM_000508.mp4 male singing +tests/VGGSound/video/SDtPpEVplNY_000080.mp4 cow lowing +tests/VGGSound/video/OwUXsddhkqA_000362.mp4 playing bass drum +tests/VGGSound/video/Ow_c5x0VaBI_000124.mp4 black capped chickadee calling +tests/VGGSound/video/OwbF9baVlN4_000264.mp4 hammering nails +tests/VGGSound/video/SEDfsU63w8I_000030.mp4 playing bass guitar +tests/VGGSound/video/Owg_XU9XmRM_000030.mp4 driving buses +tests/VGGSound/video/SEHxfje9Eio_000030.mp4 race car, auto racing +tests/VGGSound/video/OwkOp5fVJK4_000470.mp4 wind noise +tests/VGGSound/video/Ox06RFTPG6A_000162.mp4 playing squash +tests/VGGSound/video/Ox06RFTPG6A_000217.mp4 playing squash +tests/VGGSound/video/OxPfSWirUtk_000016.mp4 planing timber +tests/VGGSound/video/SFMXcbyHbF0_000011.mp4 turkey gobbling +tests/VGGSound/video/OxbHUMFOxnk_000030.mp4 baby laughter +tests/VGGSound/video/SFUCE899DkE_000030.mp4 duck quacking +tests/VGGSound/video/SF_kze7TG_8_000000.mp4 bouncing on trampoline +tests/VGGSound/video/SFcckZJ7y1E_000060.mp4 playing accordion +tests/VGGSound/video/SGFYFPs3Fic_000550.mp4 helicopter +tests/VGGSound/video/SGKYmf3POkE_000048.mp4 lip smacking +tests/VGGSound/video/SGWo9F3NbCE_000377.mp4 cheetah chirrup +tests/VGGSound/video/SGb_Uw_pKzk_000070.mp4 bird wings flapping +tests/VGGSound/video/SGnZxcS7VKA_000010.mp4 playing trumpet +tests/VGGSound/video/OzMAwy8qSEo_000030.mp4 people sobbing +tests/VGGSound/video/OzMvtTlUwzM_000133.mp4 playing glockenspiel +tests/VGGSound/video/SHTh_ewgLsY_000059.mp4 playing trombone +tests/VGGSound/video/SHk3gJAnm8U_000529.mp4 people sniggering +tests/VGGSound/video/SHkCnBJoZkc_000010.mp4 magpie calling +tests/VGGSound/video/OzvDaM8huEM_000273.mp4 playing tuning fork +tests/VGGSound/video/SHuQTeX-3Ms_000209.mp4 wind chime +tests/VGGSound/video/P-KszOT2TNw_000064.mp4 barn swallow calling +tests/VGGSound/video/P-NCCepeHdI_000125.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/SIZ5WUVzAMk_000216.mp4 driving snowmobile +tests/VGGSound/video/P-h317k111o_000182.mp4 people slurping +tests/VGGSound/video/P02Zdk3amjk_000030.mp4 baby crying +tests/VGGSound/video/SJ9TY-iqD9Q_000010.mp4 child singing +tests/VGGSound/video/SJN5vcGGF4I_000150.mp4 ocean burbling +tests/VGGSound/video/SJUl98voKZo_000003.mp4 woodpecker pecking tree +tests/VGGSound/video/P0iX1OyXMa0_000030.mp4 singing choir +tests/VGGSound/video/SJVuopldMyU_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/P15JhIEHVHg_000030.mp4 dog barking +tests/VGGSound/video/SJrVTQPbMXs_000016.mp4 fly, housefly buzzing +tests/VGGSound/video/P18VbGGgLcw_000000.mp4 opening or closing car electric windows +tests/VGGSound/video/P1LygmOqewM_000157.mp4 playing congas +tests/VGGSound/video/P1QoN7IyNiI_000030.mp4 pumping water +tests/VGGSound/video/SKK-sj5krTc_000073.mp4 people booing +tests/VGGSound/video/SKt_3Nv2DHo_000030.mp4 pig oinking +tests/VGGSound/video/P2ldhAT8KHc_000280.mp4 subway, metro, underground +tests/VGGSound/video/SL52ykhLo8A_000070.mp4 playing piano +tests/VGGSound/video/SL5xjLgQp1c_000070.mp4 playing flute +tests/VGGSound/video/SL90sfXc-jQ_000042.mp4 people booing +tests/VGGSound/video/SLAmK__qyXM_000010.mp4 firing cannon +tests/VGGSound/video/P3QhZuHbAUY_000076.mp4 disc scratching +tests/VGGSound/video/SLQAve85lDU_000188.mp4 disc scratching +tests/VGGSound/video/SLajIWg3BY8_000094.mp4 chopping food +tests/VGGSound/video/SLajIWg3BY8_000117.mp4 chopping food +tests/VGGSound/video/SM10Hrl5d7U_000010.mp4 playing electronic organ +tests/VGGSound/video/SM6m56nzTWM_000007.mp4 pheasant crowing +tests/VGGSound/video/SM756Ki9S9g_000164.mp4 people cheering +tests/VGGSound/video/SMAOB1Wt6QQ_000406.mp4 playing tennis +tests/VGGSound/video/SMAOB1Wt6QQ_000426.mp4 playing tennis +tests/VGGSound/video/P47dXlN_htA_000170.mp4 singing choir +tests/VGGSound/video/P47rLtTw5Mw_000000.mp4 playing flute +tests/VGGSound/video/SMkVCM9GfO8_000030.mp4 playing harpsichord +tests/VGGSound/video/SNA6ceTxJTQ_000050.mp4 people whistling +tests/VGGSound/video/P4ocWEaK3eg_000200.mp4 playing tabla +tests/VGGSound/video/P4x12uMeVVc_000086.mp4 tap dancing +tests/VGGSound/video/P5Au94IeCXc_000165.mp4 playing erhu +tests/VGGSound/video/P5F3YrbVe1M_000087.mp4 wind noise +tests/VGGSound/video/P5GxiEz81xw_000025.mp4 playing table tennis +tests/VGGSound/video/P5H8C-I7Qxc_000030.mp4 playing zither +tests/VGGSound/video/SNhfvhWPXNc_000030.mp4 playing electric guitar +tests/VGGSound/video/P5KM4kNgvr8_000039.mp4 yodelling +tests/VGGSound/video/SNt6zvI-Qzo_000030.mp4 people clapping +tests/VGGSound/video/SOCnHo6nlrQ_000209.mp4 wind chime +tests/VGGSound/video/P5tsRM1iokA_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/SOP4zO5Tk3w_000161.mp4 striking bowling +tests/VGGSound/video/P68FS_ooLAE_000030.mp4 lighting firecrackers +tests/VGGSound/video/SObG51xihGc_000210.mp4 people running +tests/VGGSound/video/SOr0nxRmf8o_000130.mp4 cat growling +tests/VGGSound/video/SPXhFGrgAoc_000091.mp4 hedge trimmer running +tests/VGGSound/video/SQ-pR4Kp9kc_000010.mp4 penguins braying +tests/VGGSound/video/SQ71Y_g116A_000090.mp4 ocean burbling +tests/VGGSound/video/SQKCDQrAKho_000020.mp4 squishing water +tests/VGGSound/video/SQNCsQqjuGw_000130.mp4 door slamming +tests/VGGSound/video/SQPQBndxiB4_000087.mp4 disc scratching +tests/VGGSound/video/P79MiEXW6Ns_000041.mp4 lions growling +tests/VGGSound/video/SQWKklcMKbE_000159.mp4 chinchilla barking +tests/VGGSound/video/SQaFz1SxUyo_000042.mp4 playing bass drum +tests/VGGSound/video/P7EZVAVSCtc_000175.mp4 playing hockey +tests/VGGSound/video/SQfTvzvUJ6k_000006.mp4 hammering nails +tests/VGGSound/video/SQfTvzvUJ6k_000029.mp4 hammering nails +tests/VGGSound/video/SQkoFk_gnE8_000005.mp4 air horn +tests/VGGSound/video/SR1a5VJqF8w_000080.mp4 playing cello +tests/VGGSound/video/P8KzsctEY7o_000113.mp4 civil defense siren +tests/VGGSound/video/SRjsxeOWFnw_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/P8Uwpp00DBk_000000.mp4 pheasant crowing +tests/VGGSound/video/P8Uwpp00DBk_000067.mp4 pheasant crowing +tests/VGGSound/video/P8VTcL2ecs8_000030.mp4 tapping guitar +tests/VGGSound/video/SSFFe1cVwgU_000080.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/P90rFZQFqWk_000030.mp4 playing electric guitar +tests/VGGSound/video/SSctjV--wAA_000050.mp4 playing didgeridoo +tests/VGGSound/video/SSe_TE8W2pE_000025.mp4 hammering nails +tests/VGGSound/video/SSor5MN-QJM_000056.mp4 barn swallow calling +tests/VGGSound/video/ST06L3u-WOo_000240.mp4 cricket chirping +tests/VGGSound/video/ST5bojWT3Jo_000108.mp4 sharpen knife +tests/VGGSound/video/P9r8EC83Y3k_000018.mp4 goose honking +tests/VGGSound/video/STdAr1JNXIU_000190.mp4 helicopter +tests/VGGSound/video/PA3y_gyX3m8_000004.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/STnJkHshBas_000010.mp4 mosquito buzzing +tests/VGGSound/video/STrIfVNpIGc_000006.mp4 playing shofar +tests/VGGSound/video/SU1SxRAbW2E_000029.mp4 forging swords +tests/VGGSound/video/SU9ZP2pbqyU_000010.mp4 playing ukulele +tests/VGGSound/video/SUFOgc9Pkd8_000030.mp4 dog growling +tests/VGGSound/video/SUclDZHax0w_000120.mp4 playing vibraphone +tests/VGGSound/video/SUu1E8uOGR4_000028.mp4 canary calling +tests/VGGSound/video/SUyaiLzdWDk_000030.mp4 sailing +tests/VGGSound/video/SVAkT8CfTtw_000003.mp4 cupboard opening or closing +tests/VGGSound/video/SVJcOva0JYI_000005.mp4 sheep bleating +tests/VGGSound/video/SVQ_3JHjJ8w_000560.mp4 car passing by +tests/VGGSound/video/SVoLykPMwAs_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/SVsg07esckU_000080.mp4 hair dryer drying +tests/VGGSound/video/SVvXfuS5eyY_000028.mp4 people cheering +tests/VGGSound/video/SW0qQMAZKfo_000030.mp4 dog howling +tests/VGGSound/video/SX07l57Ylmc_000031.mp4 gibbon howling +tests/VGGSound/video/SX5-0_j1leg_001008.mp4 forging swords +tests/VGGSound/video/SX6g8rItq3k_000044.mp4 fox barking +tests/VGGSound/video/SXeSsEP3ieo_000145.mp4 elk bugling +tests/VGGSound/video/SXvinNxNPiE_000080.mp4 playing hammond organ +tests/VGGSound/video/SY0xg2MmmYw_000042.mp4 metronome +tests/VGGSound/video/SY35Ms-l_9E_000030.mp4 fire truck siren +tests/VGGSound/video/SYEmTschjRg_000030.mp4 turkey gobbling +tests/VGGSound/video/SYH5NqTtNsI_000030.mp4 playing flute +tests/VGGSound/video/SZGBlB8DlYM_000016.mp4 roller coaster running +tests/VGGSound/video/SZQi2OfjB3w_000100.mp4 eagle screaming +tests/VGGSound/video/SZVguke6__M_000100.mp4 railroad car, train wagon +tests/VGGSound/video/SZnCYgHGjWE_000030.mp4 sloshing water +tests/VGGSound/video/S_-F4Nr-2Ig_000307.mp4 forging swords +tests/VGGSound/video/S_Hw4vkKBuk_000021.mp4 people giggling +tests/VGGSound/video/S_XSchdmUn4_000732.mp4 playing hockey +tests/VGGSound/video/S_wmiCKYUhE_000030.mp4 people shuffling +tests/VGGSound/video/S_yxvb7P0B4_000007.mp4 train horning +tests/VGGSound/video/SaUx9CZGCzU_000039.mp4 parrot talking +tests/VGGSound/video/SaWJzUJASIw_000347.mp4 rope skipping +tests/VGGSound/video/Sa_ovp-50Tc_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/Sb5nf9DkzTs_000050.mp4 baby laughter +tests/VGGSound/video/ScCa7fZ-xPA_000010.mp4 goat bleating +tests/VGGSound/video/ScNLWuogqpI_000150.mp4 turkey gobbling +tests/VGGSound/video/ScQ2F8LTkuY_000021.mp4 goat bleating +tests/VGGSound/video/ScYKvpZ5kZ4_000028.mp4 people eating crisps +tests/VGGSound/video/Sd3qUrm1UZk_000131.mp4 roller coaster running +tests/VGGSound/video/SdHsbNDd_zA_000220.mp4 thunder +tests/VGGSound/video/SdYcF6eaVhI_000010.mp4 wind chime +tests/VGGSound/video/SdeVFx40BKQ_000090.mp4 playing electric guitar +tests/VGGSound/video/SdfD3CEapkc_000177.mp4 roller coaster running +tests/VGGSound/video/SdtxQcBJjBs_000060.mp4 playing saxophone +tests/VGGSound/video/SeJgbt7DCY8_000080.mp4 playing bagpipes +tests/VGGSound/video/Sem8fMv0bKQ_000212.mp4 people slurping +tests/VGGSound/video/Sevpt7V3RiI_000004.mp4 people giggling +tests/VGGSound/video/SfoN3MJ1RCI_000030.mp4 owl hooting +tests/VGGSound/video/Sg-8q7jJq7A_000030.mp4 people whispering +tests/VGGSound/video/Sg0Jr79ObPo_000034.mp4 playing bugle +tests/VGGSound/video/SgCRYHWzTmU_000012.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/SgUdzDdeO78_000017.mp4 door slamming +tests/VGGSound/video/Sgdq22nyfTM_000240.mp4 subway, metro, underground +tests/VGGSound/video/SgfHJ5fkMiY_000040.mp4 cattle, bovinae cowbell +tests/VGGSound/video/SgrZjfpxsZk_000005.mp4 lip smacking +tests/VGGSound/video/SgtbfaaL8KQ_000000.mp4 skidding +tests/VGGSound/video/SgyeshD8RJY_000140.mp4 people clapping +tests/VGGSound/video/ShSRKoE7hHc_000128.mp4 sharpen knife +tests/VGGSound/video/Sh_ehsV4ofk_000179.mp4 playing castanets +tests/VGGSound/video/ShubbKmh5hQ_000162.mp4 lathe spinning +tests/VGGSound/video/SiXCZ-Ew0b0_000050.mp4 playing piano +tests/VGGSound/video/Sirb4ruDmVA_000386.mp4 metronome +tests/VGGSound/video/Sj9_5H1nqfo_000200.mp4 ambulance siren +tests/VGGSound/video/SjpIXXfSEBE_000011.mp4 playing volleyball +tests/VGGSound/video/SkFx45lxlvA_000060.mp4 lions roaring +tests/VGGSound/video/SkIDF7iNJQE_000030.mp4 playing synthesizer +tests/VGGSound/video/SkPEiTqLlf0_000030.mp4 dog howling +tests/VGGSound/video/SkQb0gnQg6s_000218.mp4 magpie calling +tests/VGGSound/video/SkbFczIabRY_000030.mp4 car passing by +tests/VGGSound/video/SkhVlPLx57w_000030.mp4 sliding door +tests/VGGSound/video/Skrr-UgHeHg_000008.mp4 lions growling +tests/VGGSound/video/SktasHTBGow_000145.mp4 rope skipping +tests/VGGSound/video/SkyxbPeBxNA_000000.mp4 playing marimba, xylophone +tests/VGGSound/video/SlAtd9ydvmE_000170.mp4 playing trombone +tests/VGGSound/video/Slcg717UTrM_000004.mp4 cat growling +tests/VGGSound/video/SmSOJiVYvv8_000247.mp4 electric grinder grinding +tests/VGGSound/video/SmpsJhL4yUY_000130.mp4 playing cymbal +tests/VGGSound/video/SmtW2FlpPX4_000057.mp4 barn swallow calling +tests/VGGSound/video/SmuyUnEZaJw_000030.mp4 crow cawing +tests/VGGSound/video/SmzESvmFENY_000014.mp4 fly, housefly buzzing +tests/VGGSound/video/SmzESvmFENY_000024.mp4 fly, housefly buzzing +tests/VGGSound/video/Snz2sQ5QxeE_000260.mp4 railroad car, train wagon +tests/VGGSound/video/So8G7UXguNA_000077.mp4 tractor digging +tests/VGGSound/video/SouyQhC7rSU_000039.mp4 scuba diving +tests/VGGSound/video/Sp9bKDHRfsM_000065.mp4 tornado roaring +tests/VGGSound/video/SpRqgH543_Q_000074.mp4 tractor digging +tests/VGGSound/video/Sq15LYn3fAY_000012.mp4 sharpen knife +tests/VGGSound/video/SqEWh1M2SIc_000030.mp4 ice cream truck, ice cream van +tests/VGGSound/video/SqWkV-UQ6CI_000030.mp4 skidding +tests/VGGSound/video/SqacR4nVfWM_000030.mp4 mouse squeaking +tests/VGGSound/video/Sqpkv9fnxqw_000210.mp4 ambulance siren +tests/VGGSound/video/Sr35u7b1OFI_000039.mp4 people eating apple +tests/VGGSound/video/SrLhnoBMyWM_000000.mp4 people burping +tests/VGGSound/video/SrYqJlCuppA_000130.mp4 waterfall burbling +tests/VGGSound/video/Ss1zpZjEaE8_000020.mp4 playing cello +tests/VGGSound/video/SsloEIMVDmk_000016.mp4 mouse clicking +tests/VGGSound/video/StFCmHcBNko_000120.mp4 playing lacrosse +tests/VGGSound/video/StO32FBBIH4_000011.mp4 baby crying +tests/VGGSound/video/StkBwGVNL-Q_000011.mp4 people eating apple +tests/VGGSound/video/StmGbhL9dgQ_000064.mp4 dog baying +tests/VGGSound/video/SuND8p4dhos_000367.mp4 playing harpsichord +tests/VGGSound/video/SuOSEt3nKEg_000143.mp4 cupboard opening or closing +tests/VGGSound/video/SuRVsbK22io_000320.mp4 people burping +tests/VGGSound/video/SuvLjNblJus_000044.mp4 metronome +tests/VGGSound/video/SvsCM0fLM5g_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/SwONnm4TKHw_000041.mp4 playing hockey +tests/VGGSound/video/SwRjY1-ojAU_000030.mp4 people babbling +tests/VGGSound/video/SwZxKE3CnEg_000080.mp4 bird wings flapping +tests/VGGSound/video/Swien0oGl7o_000090.mp4 playing banjo +tests/VGGSound/video/SwxdBiazu8M_000030.mp4 duck quacking +tests/VGGSound/video/Sx3WV9GSOmc_000060.mp4 playing cello +tests/VGGSound/video/Sx71y_cFKtY_000020.mp4 people finger snapping +tests/VGGSound/video/SxI3Lnzzmkw_000110.mp4 people screaming +tests/VGGSound/video/PeWX2XHqnTw_000005.mp4 playing double bass +tests/VGGSound/video/SyWbd9bOCps_000096.mp4 donkey, ass braying +tests/VGGSound/video/Sz6nE4hceXc_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/SzBgRzSZG6c_000030.mp4 sloshing water +tests/VGGSound/video/PfTeqgGPlSI_000297.mp4 playing bugle +tests/VGGSound/video/SzLx3qcIbtU_000290.mp4 playing sitar +tests/VGGSound/video/SzY85V52hgo_000016.mp4 dog howling +tests/VGGSound/video/SzhOVP7BXUE_000000.mp4 crow cawing +tests/VGGSound/video/Szwd-0tatdo_000120.mp4 thunder +tests/VGGSound/video/T-28g9G-WKo_000000.mp4 driving snowmobile +tests/VGGSound/video/T-3hHhrPBeg_000087.mp4 chimpanzee pant-hooting +tests/VGGSound/video/T-8xETNgtvE_000030.mp4 male speech, man speaking +tests/VGGSound/video/T-SCw4PMUYI_000490.mp4 playing harmonica +tests/VGGSound/video/PgLsFRfKMwU_000058.mp4 canary calling +tests/VGGSound/video/T0DQyRrjewU_000003.mp4 chicken clucking +tests/VGGSound/video/T0FNLDWBlSU_000081.mp4 sharpen knife +tests/VGGSound/video/T0IwubU2ZN8_000199.mp4 cutting hair with electric trimmers +tests/VGGSound/video/T0S4-E8BE0A_000060.mp4 playing electronic organ +tests/VGGSound/video/Ph2SI18iz7o_000010.mp4 people sneezing +tests/VGGSound/video/T0nvf328Ll4_000013.mp4 donkey, ass braying +tests/VGGSound/video/T0x6z65J-_M_000334.mp4 swimming +tests/VGGSound/video/T1_nZvxh5kI_000008.mp4 cattle mooing +tests/VGGSound/video/T29-jYwTQ9A_000056.mp4 squishing water +tests/VGGSound/video/T2F6euNVT5Y_000010.mp4 machine gun shooting +tests/VGGSound/video/Pi_2255ToZg_000111.mp4 playing squash +tests/VGGSound/video/Pj2t-6P7dDQ_000030.mp4 pig oinking +tests/VGGSound/video/T4UHGzC8gKY_000071.mp4 scuba diving +tests/VGGSound/video/T4aReg7Awxo_000040.mp4 playing clarinet +tests/VGGSound/video/T4k5jj440kk_000017.mp4 cheetah chirrup +tests/VGGSound/video/PkDHPoMjvJ8_000030.mp4 bird squawking +tests/VGGSound/video/PkPplRX9rJc_000067.mp4 train whistling +tests/VGGSound/video/T5OwLsluH6A_000366.mp4 scuba diving +tests/VGGSound/video/T6Jy1yIF61M_000099.mp4 sea lion barking +tests/VGGSound/video/T6NG4llF5Yw_000032.mp4 playing erhu +tests/VGGSound/video/T6mrHDa7GcE_000065.mp4 people giggling +tests/VGGSound/video/T7SR0jZj4zA_000000.mp4 playing gong +tests/VGGSound/video/T7SjVkqAn8U_000028.mp4 striking bowling +tests/VGGSound/video/PlrV0NcUkqE_000058.mp4 train horning +tests/VGGSound/video/T7aPB5yvDs0_000013.mp4 pig oinking +tests/VGGSound/video/T7fsXVDXFQo_000300.mp4 playing erhu +tests/VGGSound/video/T834Iasgjs4_000336.mp4 playing erhu +tests/VGGSound/video/T8Vq2711kQU_000572.mp4 striking bowling +tests/VGGSound/video/T8jK1bELCfs_000030.mp4 mouse squeaking +tests/VGGSound/video/Pn-J9-LQRw8_000030.mp4 singing bowl +tests/VGGSound/video/PnDQGrMCnts_000280.mp4 railroad car, train wagon +tests/VGGSound/video/T9GkukfZaU8_000164.mp4 missile launch +tests/VGGSound/video/T9NtIobol04_000070.mp4 skateboarding +tests/VGGSound/video/T9QD0bCD7tU_000012.mp4 cupboard opening or closing +tests/VGGSound/video/PnlvBFdNje4_000145.mp4 playing washboard +tests/VGGSound/video/TA-O_bVnvLY_000540.mp4 playing sitar +tests/VGGSound/video/TA-iHSeEUYk_000040.mp4 people coughing +tests/VGGSound/video/Po2kalrDi-w_000055.mp4 barn swallow calling +tests/VGGSound/video/TAHDbSl7F_4_000290.mp4 cattle mooing +tests/VGGSound/video/TAexBL5eToE_000022.mp4 playing washboard +tests/VGGSound/video/TAexBL5eToE_000052.mp4 playing washboard +tests/VGGSound/video/TB3VhNczX88_000010.mp4 people coughing +tests/VGGSound/video/TC3Z6NuoFz8_000460.mp4 thunder +tests/VGGSound/video/TCjpetxykx0_000210.mp4 playing sitar +tests/VGGSound/video/Ppqv5jc1wUw_000314.mp4 playing volleyball +tests/VGGSound/video/TD2O6KbnF-Q_000044.mp4 cutting hair with electric trimmers +tests/VGGSound/video/TDNnNmgqhNI_000030.mp4 turkey gobbling +tests/VGGSound/video/TDORLm3QYyA_000003.mp4 lighting firecrackers +tests/VGGSound/video/PqlmyFDIeUM_000039.mp4 playing mandolin +tests/VGGSound/video/TEA5dT6nDNE_000016.mp4 fly, housefly buzzing +tests/VGGSound/video/PrEpx-QUOwg_000120.mp4 lions roaring +tests/VGGSound/video/TEKIRndnL5Y_000014.mp4 people eating +tests/VGGSound/video/PtNaufJnqQs_000000.mp4 air horn +tests/VGGSound/video/Ptcyg0EyJY4_000077.mp4 popping popcorn +tests/VGGSound/video/TINrhV9gacY_000046.mp4 people hiccup +tests/VGGSound/video/TIllmI1n5cw_000129.mp4 alarm clock ringing +tests/VGGSound/video/TJ4aeESZ6e8_000100.mp4 playing piano +tests/VGGSound/video/TJmkBfkJGsQ_000077.mp4 heart sounds, heartbeat +tests/VGGSound/video/TK2lPYfkG-8_000030.mp4 people running +tests/VGGSound/video/PuNLqr0oZeo_000170.mp4 baby laughter +tests/VGGSound/video/TKSFbf-wQ8I_000030.mp4 fire crackling +tests/VGGSound/video/TKZIwdxeQIQ_000209.mp4 underwater bubbling +tests/VGGSound/video/PuvTDLP8lwM_000030.mp4 typing on computer keyboard +tests/VGGSound/video/TKxGWjvYmT8_000200.mp4 sliding door +tests/VGGSound/video/TLiywGNShzs_000197.mp4 foghorn +tests/VGGSound/video/TM23x21Qs2Q_000030.mp4 dog growling +tests/VGGSound/video/PwazdGn6ldc_000030.mp4 pig oinking +tests/VGGSound/video/TNERQa_7oB8_000013.mp4 snake rattling +tests/VGGSound/video/TO7d2wx7Cq8_000058.mp4 lathe spinning +tests/VGGSound/video/PxpGb6RozhI_000024.mp4 ice cracking +tests/VGGSound/video/TOEwQXeyNe8_000210.mp4 bull bellowing +tests/VGGSound/video/TOEwQXeyNe8_000227.mp4 bull bellowing +tests/VGGSound/video/TOUHOWRpQYA_000230.mp4 mouse clicking +tests/VGGSound/video/TOUHOWRpQYA_000247.mp4 mouse clicking +tests/VGGSound/video/TOpAW-8jlKQ_000030.mp4 playing cymbal +tests/VGGSound/video/TP-uSCjMiYY_000250.mp4 playing squash +tests/VGGSound/video/TP-uSCjMiYY_000264.mp4 playing squash +tests/VGGSound/video/TP50fDa5Cls_000000.mp4 people giggling +tests/VGGSound/video/PyponzntqzM_000163.mp4 people booing +tests/VGGSound/video/TP_CVBCc4-U_000090.mp4 people screaming +tests/VGGSound/video/Pyt8O3N6-wk_000110.mp4 dog growling +tests/VGGSound/video/TPeA5xENWIM_000065.mp4 cuckoo bird calling +tests/VGGSound/video/TPtB2NqlAlc_000125.mp4 bouncing on trampoline +tests/VGGSound/video/Pz8w3ZDCD3w_000030.mp4 turkey gobbling +tests/VGGSound/video/PzS_cNwa4xM_000000.mp4 bird wings flapping +tests/VGGSound/video/TQpSa_i6UF8_000027.mp4 spraying water +tests/VGGSound/video/TQsjIE2VHqw_000110.mp4 chainsawing trees +tests/VGGSound/video/TR4-xSB97w8_000030.mp4 crow cawing +tests/VGGSound/video/TRW3OqA1cXE_000030.mp4 playing clarinet +tests/VGGSound/video/TRk-fdiqqSA_000490.mp4 people whistling +tests/VGGSound/video/TS7NsVkl3P4_000261.mp4 mynah bird singing +tests/VGGSound/video/TSpGd9p17n0_000202.mp4 elk bugling +tests/VGGSound/video/TT8xhjDC3Cg_000250.mp4 typing on typewriter +tests/VGGSound/video/TU7DNkZtG1I_000109.mp4 train whistling +tests/VGGSound/video/TUHXmAN0Qbc_000017.mp4 francolin calling +tests/VGGSound/video/TUjlH1HqPEE_000364.mp4 blowtorch igniting +tests/VGGSound/video/TUpX4p-Ej_o_000336.mp4 train wheels squealing +tests/VGGSound/video/TUpX4p-Ej_o_000390.mp4 train wheels squealing +tests/VGGSound/video/TVM03oDWLWI_000210.mp4 playing clarinet +tests/VGGSound/video/TVUT7DgoCCc_000170.mp4 chimpanzee pant-hooting +tests/VGGSound/video/TWAHrAE69ic_000121.mp4 lip smacking +tests/VGGSound/video/TWFlTwAIvd0_000013.mp4 dog baying +tests/VGGSound/video/TW_dVmqr9ac_000107.mp4 smoke detector beeping +tests/VGGSound/video/TXW3Qm9qT0c_000030.mp4 people shuffling +tests/VGGSound/video/TY7UehpsaFQ_000144.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/Q3aNijPpxGU_000033.mp4 chinchilla barking +tests/VGGSound/video/TYHcP8Hjwpg_000110.mp4 dog whimpering +tests/VGGSound/video/Q4Er5d3L6S0_000005.mp4 playing volleyball +tests/VGGSound/video/Q4T6urZF_HA_000000.mp4 civil defense siren +tests/VGGSound/video/Q4cVLAbRVDc_000045.mp4 wind chime +tests/VGGSound/video/TZGKriaJKAY_000163.mp4 sharpen knife +tests/VGGSound/video/TZl2cGkWZL4_000030.mp4 dog bow-wow +tests/VGGSound/video/Q5o7RYwXkvI_000070.mp4 woodpecker pecking tree +tests/VGGSound/video/Q5uKTmF5ut0_000170.mp4 sliding door +tests/VGGSound/video/T_psjQ4wzFQ_000016.mp4 printer printing +tests/VGGSound/video/Ta3F2prvIZY_000091.mp4 slot machine +tests/VGGSound/video/Ta5bgIdRUjE_000048.mp4 chipmunk chirping +tests/VGGSound/video/Ta6H02Kf6ws_000150.mp4 driving buses +tests/VGGSound/video/Ta9R_TuzIUM_000341.mp4 driving snowmobile +tests/VGGSound/video/Q6pnggPsxDw_000070.mp4 ice cream truck, ice cream van +tests/VGGSound/video/TakkuFZJsis_000030.mp4 rapping +tests/VGGSound/video/Taw3uTEkfSo_000530.mp4 pumping water +tests/VGGSound/video/Tb2KyzcQoJE_000000.mp4 door slamming +tests/VGGSound/video/Tc9sb71px5I_000030.mp4 firing cannon +tests/VGGSound/video/TdGJdqDxrNc_000091.mp4 baltimore oriole calling +tests/VGGSound/video/TdJu6gXS7Rw_000375.mp4 skiing +tests/VGGSound/video/TeQ3b3P8290_000170.mp4 splashing water +tests/VGGSound/video/TeUgb183cGM_000024.mp4 pheasant crowing +tests/VGGSound/video/Tf5WWrpzSj8_000095.mp4 cat growling +tests/VGGSound/video/Tfj3_pJLdjM_000747.mp4 playing table tennis +tests/VGGSound/video/QB1jroqGo6U_000117.mp4 bull bellowing +tests/VGGSound/video/Tfv2TARaCfg_000079.mp4 tap dancing +tests/VGGSound/video/TgJHM5oSWio_000008.mp4 people sneezing +tests/VGGSound/video/TgQA1mgDudE_000208.mp4 shot football +tests/VGGSound/video/Tgb2q9H8Qok_000298.mp4 heart sounds, heartbeat +tests/VGGSound/video/Tgqb1VUysMM_000490.mp4 chicken crowing +tests/VGGSound/video/Th6Tf6kA8RU_000030.mp4 duck quacking +tests/VGGSound/video/ThFhtKGxjZM_000001.mp4 alarm clock ringing +tests/VGGSound/video/ThLQka_yZNY_000261.mp4 beat boxing +tests/VGGSound/video/ThVGE9TjEjM_000136.mp4 magpie calling +tests/VGGSound/video/QCSbiaMxR28_000000.mp4 people farting +tests/VGGSound/video/Ti0Ck0xTdw4_000030.mp4 typing on computer keyboard +tests/VGGSound/video/Ti2XbGtfyNg_000225.mp4 playing guiro +tests/VGGSound/video/Tib2GX8Mb20_000126.mp4 francolin calling +tests/VGGSound/video/TipVfZMxZbk_000010.mp4 playing saxophone +tests/VGGSound/video/QD9V6AwZar4_000350.mp4 chicken crowing +tests/VGGSound/video/Tiye0BqxJS4_000030.mp4 playing harp +tests/VGGSound/video/TjF7KY9R8Kc_000020.mp4 thunder +tests/VGGSound/video/QDfyTkOWfyM_000236.mp4 dinosaurs bellowing +tests/VGGSound/video/Tk0Sl9H0CE0_000324.mp4 cutting hair with electric trimmers +tests/VGGSound/video/Tk2GV1Eo-gM_000037.mp4 air horn +tests/VGGSound/video/TkrtTUPxHNI_000030.mp4 playing harpsichord +tests/VGGSound/video/Tlzma5yXcgM_000287.mp4 writing on blackboard with chalk +tests/VGGSound/video/TmJZxQ_Lo8M_000147.mp4 playing tympani +tests/VGGSound/video/TmLrqd7tm8A_000290.mp4 wind noise +tests/VGGSound/video/TmukiN_btGw_000500.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/TmwM6LCcIBg_000130.mp4 playing sitar +tests/VGGSound/video/TnI1JdrjyS0_000209.mp4 bathroom ventilation fan running +tests/VGGSound/video/TnUCfcISSw0_000271.mp4 chopping wood +tests/VGGSound/video/TnZ7lewZgns_000044.mp4 volcano explosion +tests/VGGSound/video/TnzGGN9Q__s_000010.mp4 playing zither +tests/VGGSound/video/ToIdgjI3u4Q_000030.mp4 playing trombone +tests/VGGSound/video/TpCxOe0iYJM_000105.mp4 telephone bell ringing +tests/VGGSound/video/TpJdup-AdIA_000016.mp4 train horning +tests/VGGSound/video/TpPHH7wQz_M_000030.mp4 playing bagpipes +tests/VGGSound/video/TpU5dZlW2pg_000040.mp4 planing timber +tests/VGGSound/video/Tpg9LiS6K-M_000234.mp4 train whistling +tests/VGGSound/video/TqWhTzMtNyw_000133.mp4 playing bass drum +tests/VGGSound/video/Tr7PDdzq40o_000180.mp4 playing harpsichord +tests/VGGSound/video/Tr9Xd0qwVrU_000320.mp4 playing steelpan +tests/VGGSound/video/TrvI6t4pAP0_000030.mp4 rapping +tests/VGGSound/video/Ts3ZcUaELzA_000030.mp4 playing electric guitar +tests/VGGSound/video/QKu30d-ZlQo_000113.mp4 chimpanzee pant-hooting +tests/VGGSound/video/TsHBKTYuBUM_000062.mp4 whale calling +tests/VGGSound/video/TsJkj3BotEo_000580.mp4 thunder +tests/VGGSound/video/TsUPben7NCw_000269.mp4 people humming +tests/VGGSound/video/TsWy5u8dCtU_000253.mp4 firing muskets +tests/VGGSound/video/QLEBKY7baBg_000030.mp4 goat bleating +tests/VGGSound/video/TslB1VMKXmM_000010.mp4 toilet flushing +tests/VGGSound/video/TsqbxwQLeEE_000030.mp4 people farting +tests/VGGSound/video/TstsLM4IUV8_000128.mp4 playing violin, fiddle +tests/VGGSound/video/TtO9wzZ3LFA_000030.mp4 hair dryer drying +tests/VGGSound/video/TtP63IOhg1Y_000030.mp4 goat bleating +tests/VGGSound/video/TuHHUDnFSO0_000096.mp4 playing castanets +tests/VGGSound/video/TuRlMGut6iY_000564.mp4 swimming +tests/VGGSound/video/Tvwi_YuLehk_000030.mp4 playing mandolin +tests/VGGSound/video/QOEFVFFrv_Q_000077.mp4 elk bugling +tests/VGGSound/video/TwbVQetLqfM_000003.mp4 otter growling +tests/VGGSound/video/TwucF4h5v3U_000084.mp4 missile launch +tests/VGGSound/video/TxEAwc91Qos_000200.mp4 thunder +tests/VGGSound/video/TxELr6cZr7s_000018.mp4 cuckoo bird calling +tests/VGGSound/video/TxK2ZBfuuQY_000070.mp4 playing saxophone +tests/VGGSound/video/TxS9ytraxnY_000076.mp4 opening or closing car doors +tests/VGGSound/video/TxS9ytraxnY_000112.mp4 opening or closing car doors +tests/VGGSound/video/TxXjcJo7Q2I_000531.mp4 turkey gobbling +tests/VGGSound/video/Txu61YwnnJg_000220.mp4 stream burbling +tests/VGGSound/video/TxuwrWYaUD0_000000.mp4 fireworks banging +tests/VGGSound/video/TyMZJqYmrwE_000490.mp4 playing ukulele +tests/VGGSound/video/QP_ZCssCySw_000340.mp4 thunder +tests/VGGSound/video/TzVFAvWdiV0_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/Tzdtjub_HUM_000060.mp4 opening or closing drawers +tests/VGGSound/video/U-L9YCIdLbg_000080.mp4 playing electric guitar +tests/VGGSound/video/U-O1FcXeZCk_000200.mp4 playing vibraphone +tests/VGGSound/video/U-Qe9aNkrdE_000030.mp4 female speech, woman speaking +tests/VGGSound/video/U-hpbrpact0_000112.mp4 bathroom ventilation fan running +tests/VGGSound/video/U07bPALXCmM_000401.mp4 ice cream truck, ice cream van +tests/VGGSound/video/U0Cg_t_3TdI_000030.mp4 eating with cutlery +tests/VGGSound/video/U0SjklNoHDU_000069.mp4 playing timbales +tests/VGGSound/video/QRLfJ0FuEbc_000267.mp4 sea lion barking +tests/VGGSound/video/U0uy9GWzSQ8_000065.mp4 snake hissing +tests/VGGSound/video/QS31Gm9tIig_000000.mp4 machine gun shooting +tests/VGGSound/video/U19MDXMg_BI_000150.mp4 playing sitar +tests/VGGSound/video/QS9exOjY2u0_000026.mp4 playing shofar +tests/VGGSound/video/U1Me-1aACSg_000328.mp4 striking bowling +tests/VGGSound/video/U24BkLFGDtg_000490.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/U2Ek06LbrYs_000030.mp4 crow cawing +tests/VGGSound/video/U2Fuor5iG98_000068.mp4 playing tympani +tests/VGGSound/video/U2TFN0L9NgU_000310.mp4 opening or closing drawers +tests/VGGSound/video/U2b4s0B7nxw_000051.mp4 ferret dooking +tests/VGGSound/video/QTx6C9nhAUM_000270.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/QUALZucjUOk_000112.mp4 civil defense siren +tests/VGGSound/video/U37ysgI02r8_000020.mp4 playing glockenspiel +tests/VGGSound/video/U3OC4jICMlI_000020.mp4 people sobbing +tests/VGGSound/video/U3VHxih0ofE_000260.mp4 baby babbling +tests/VGGSound/video/U3Zom0wPRg0_000030.mp4 playing electronic organ +tests/VGGSound/video/U3_X26NjUXk_000082.mp4 wood thrush calling +tests/VGGSound/video/QUte9W0g2Yo_000017.mp4 eletric blender running +tests/VGGSound/video/QUygd54m8uc_000112.mp4 playing trombone +tests/VGGSound/video/U4LITdDmjvg_000011.mp4 toilet flushing +tests/VGGSound/video/U4UtZeTl2DE_000030.mp4 playing sitar +tests/VGGSound/video/U4mjEABM6qw_000007.mp4 sheep bleating +tests/VGGSound/video/QVPPz-WQEiY_000125.mp4 ice cracking +tests/VGGSound/video/U595LzVDCAY_000015.mp4 baltimore oriole calling +tests/VGGSound/video/QVpsAY9oR_4_000190.mp4 playing steelpan +tests/VGGSound/video/U5wpGWF816Q_000030.mp4 people sobbing +tests/VGGSound/video/U6_Ui8bpY9g_000042.mp4 people eating apple +tests/VGGSound/video/U6y8tw4vKXc_000105.mp4 playing hockey +tests/VGGSound/video/U7GDDe_Oqyo_000496.mp4 golf driving +tests/VGGSound/video/U7q-Z-vQImE_000277.mp4 whale calling +tests/VGGSound/video/U7vFb50UjgY_000040.mp4 lions roaring +tests/VGGSound/video/U8LzhDe8lzY_000273.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/U8XhUYPJxUM_000019.mp4 volcano explosion +tests/VGGSound/video/U8b_M6pMv8s_000360.mp4 car engine starting +tests/VGGSound/video/U8golAIXZps_000001.mp4 children shouting +tests/VGGSound/video/U8hJTpSZVWE_000103.mp4 yodelling +tests/VGGSound/video/U8iIARsN4a4_000004.mp4 zebra braying +tests/VGGSound/video/U95UReP4mdo_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/U9PyY8Ldf9A_000005.mp4 people sneezing +tests/VGGSound/video/U9o30JY6aYc_000030.mp4 cap gun shooting +tests/VGGSound/video/U9oonzVSTtY_000056.mp4 gibbon howling +tests/VGGSound/video/UAlfXv5Aabc_000046.mp4 air conditioning noise +tests/VGGSound/video/QZvynGXvyF0_000400.mp4 heart sounds, heartbeat +tests/VGGSound/video/Q_FvbcPieNo_000030.mp4 basketball bounce +tests/VGGSound/video/UBg665RgDeQ_000018.mp4 people belly laughing +tests/VGGSound/video/Q_J3XkD5Ims_000000.mp4 sea waves +tests/VGGSound/video/UBw5ujeODmE_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/UBzbRcWlsKI_000747.mp4 cow lowing +tests/VGGSound/video/UC3J31Brgnw_000022.mp4 dog growling +tests/VGGSound/video/UC_LgGxdMH4_000034.mp4 wood thrush calling +tests/VGGSound/video/UCgErb1ImPY_000031.mp4 hedge trimmer running +tests/VGGSound/video/UCgwLe70Lto_000000.mp4 magpie calling +tests/VGGSound/video/UCtiIWMRy-M_000004.mp4 sea lion barking +tests/VGGSound/video/UDSjSpHKu1I_000462.mp4 magpie calling +tests/VGGSound/video/UDlc1slA8PA_000590.mp4 helicopter +tests/VGGSound/video/QayWG1ZPKGE_000012.mp4 gibbon howling +tests/VGGSound/video/UESue-_05Vs_000000.mp4 people whistling +tests/VGGSound/video/UEbEmg3RuDM_000002.mp4 swimming +tests/VGGSound/video/UEbdKNPT96M_000030.mp4 cat purring +tests/VGGSound/video/UEjPRKwLvZ0_000170.mp4 playing sitar +tests/VGGSound/video/UF0HDsK0fwo_000070.mp4 chainsawing trees +tests/VGGSound/video/UFIBEBkm7ao_000030.mp4 driving motorcycle +tests/VGGSound/video/UFT9k3oraWE_000060.mp4 tapping guitar +tests/VGGSound/video/UFcUTwPlFAU_000019.mp4 baby crying +tests/VGGSound/video/UFyOGqmITjM_000000.mp4 playing violin, fiddle +tests/VGGSound/video/UG61vT34YRU_000210.mp4 people farting +tests/VGGSound/video/UH1uFyuicWw_000064.mp4 chopping food +tests/VGGSound/video/UHCrnOMZdGs_000075.mp4 mynah bird singing +tests/VGGSound/video/UHFViYh6h6A_000114.mp4 woodpecker pecking tree +tests/VGGSound/video/UHTpbtmXze0_000553.mp4 smoke detector beeping +tests/VGGSound/video/Qdr2xmK84Jo_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/Qe71m678qEU_000030.mp4 tapping guitar +tests/VGGSound/video/UILmgKExLgk_000095.mp4 wind chime +tests/VGGSound/video/UIM4OykJJrc_000046.mp4 dog growling +tests/VGGSound/video/UIll96Hdmd4_000094.mp4 parrot talking +tests/VGGSound/video/UKE1k7JR-ME_000004.mp4 warbler chirping +tests/VGGSound/video/UKgZCUgOSfo_000062.mp4 warbler chirping +tests/VGGSound/video/ULEv1rbzqIU_000768.mp4 people slurping +tests/VGGSound/video/ULLEA-jLmpI_000030.mp4 people finger snapping +tests/VGGSound/video/ULZ6auGvLAw_000311.mp4 sharpen knife +tests/VGGSound/video/UMidlzROhC0_000082.mp4 eletric blender running +tests/VGGSound/video/Qj3ptAKRGQg_000031.mp4 parrot talking +tests/VGGSound/video/UP30sk9je00_000049.mp4 tractor digging +tests/VGGSound/video/UPJO0UCBmPU_000246.mp4 playing timbales +tests/VGGSound/video/UPrYFfu-EXs_000130.mp4 people farting +tests/VGGSound/video/QlaW568SeDc_000310.mp4 playing marimba, xylophone +tests/VGGSound/video/UR-2P-NHz1w_000240.mp4 cattle mooing +tests/VGGSound/video/Qm7qy9cJcO8_000023.mp4 penguins braying +tests/VGGSound/video/QmENgS2Fk88_000023.mp4 mynah bird singing +tests/VGGSound/video/URLLMlOjf_w_000061.mp4 fly, housefly buzzing +tests/VGGSound/video/URLLMlOjf_w_000093.mp4 fly, housefly buzzing +tests/VGGSound/video/URXTbbVjq70_000040.mp4 playing squash +tests/VGGSound/video/URkpx3lxx1E_000450.mp4 typing on typewriter +tests/VGGSound/video/URosKU18wTk_000018.mp4 squishing water +tests/VGGSound/video/URtpQZsUmBY_000030.mp4 cattle, bovinae cowbell +tests/VGGSound/video/USE3sms5L_Q_000022.mp4 chinchilla barking +tests/VGGSound/video/USjBFzEGEqc_000298.mp4 planing timber +tests/VGGSound/video/USlCCt8En7A_000460.mp4 people belly laughing +tests/VGGSound/video/UTE0j8Fa6N8_000030.mp4 singing bowl +tests/VGGSound/video/QoffZQFqxkQ_000003.mp4 ice cream truck, ice cream van +tests/VGGSound/video/UUjPZPtqG5k_000000.mp4 chicken crowing +tests/VGGSound/video/UUoEKp0yqLY_000120.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/UUuXfyfCaL4_000170.mp4 people clapping +tests/VGGSound/video/UVCxSYZ2Now_000030.mp4 baby crying +tests/VGGSound/video/UVMBRVJTvzg_000030.mp4 playing steelpan +tests/VGGSound/video/QpKhFTFh0B8_000029.mp4 coyote howling +tests/VGGSound/video/UVPgh1SYQ9M_000456.mp4 airplane flyby +tests/VGGSound/video/UVsgxlTzy-c_000073.mp4 playing washboard +tests/VGGSound/video/UVy8bgD5Pbg_000003.mp4 whale calling +tests/VGGSound/video/UWFjhEYXbbU_000009.mp4 cricket chirping +tests/VGGSound/video/UWZg6DiLRgc_000080.mp4 people babbling +tests/VGGSound/video/UWizNEHrzCY_000017.mp4 dog barking +tests/VGGSound/video/UWz5OIijWM4_000030.mp4 driving motorcycle +tests/VGGSound/video/UX7R8WWJLoI_000160.mp4 playing harp +tests/VGGSound/video/QqyUVqi3fOg_000095.mp4 train wheels squealing +tests/VGGSound/video/UXZxgKr4nSo_000275.mp4 chipmunk chirping +tests/VGGSound/video/UY4v-zjlnlo_000010.mp4 playing violin, fiddle +tests/VGGSound/video/UYDvZc4lWYk_000240.mp4 playing gong +tests/VGGSound/video/UYScnXPxERQ_000150.mp4 playing electronic organ +tests/VGGSound/video/UYo1QYMJSXM_000014.mp4 opening or closing car electric windows +tests/VGGSound/video/UYydcVnnhYo_000221.mp4 volcano explosion +tests/VGGSound/video/UZ6zyRcElGw_000070.mp4 francolin calling +tests/VGGSound/video/Qsd19T8rN_8_000190.mp4 pigeon, dove cooing +tests/VGGSound/video/U_RBTwYagwk_000053.mp4 playing badminton +tests/VGGSound/video/U_bYlL9ap-o_000060.mp4 owl hooting +tests/VGGSound/video/U_mKoVq3kbE_000040.mp4 goose honking +tests/VGGSound/video/U_mxX7h_I_4_000000.mp4 sea waves +tests/VGGSound/video/U_qOjkaHjPI_000000.mp4 car passing by +tests/VGGSound/video/UaFiUiC_Izo_000054.mp4 squishing water +tests/VGGSound/video/UaUwUrSyUDA_000172.mp4 eagle screaming +tests/VGGSound/video/Ub7DXmyQonI_000030.mp4 playing flute +tests/VGGSound/video/UbPJ8MIGZNA_000000.mp4 fireworks banging +tests/VGGSound/video/Ubd5GQAZMEo_000373.mp4 slot machine +tests/VGGSound/video/Ubmh-lOoe3Y_000010.mp4 baby babbling +tests/VGGSound/video/Ubo-gKFkdM4_000030.mp4 pig oinking +tests/VGGSound/video/UbrXzBhg96Y_000042.mp4 roller coaster running +tests/VGGSound/video/UcJci08essY_000090.mp4 basketball bounce +tests/VGGSound/video/UcRfbzTOipc_000050.mp4 squishing water +tests/VGGSound/video/UcabTrKowlI_000030.mp4 rapping +tests/VGGSound/video/QvpIrEHvZWI_000171.mp4 disc scratching +tests/VGGSound/video/Qw468qlDaAE_000180.mp4 playing synthesizer +tests/VGGSound/video/UdWyYaDcEMs_001257.mp4 lip smacking +tests/VGGSound/video/UeEMaZqMRp0_000030.mp4 people shuffling +tests/VGGSound/video/UfJg3VBTLow_000420.mp4 driving buses +tests/VGGSound/video/UfkehxAd_M4_000040.mp4 people babbling +tests/VGGSound/video/UgPrbrCXNlQ_000013.mp4 playing squash +tests/VGGSound/video/QymYi-QzlJo_000080.mp4 playing vibraphone +tests/VGGSound/video/UhEQ1E8XPp4_000003.mp4 chicken clucking +tests/VGGSound/video/UhEQ1E8XPp4_000017.mp4 chicken clucking +tests/VGGSound/video/UiaGn5Id5tY_000004.mp4 underwater bubbling +tests/VGGSound/video/UiqhcbbvAs8_000297.mp4 lip smacking +tests/VGGSound/video/R-aMYx9f0Ho_000030.mp4 playing acoustic guitar +tests/VGGSound/video/Uj2Os8tYIIQ_000400.mp4 eating with cutlery +tests/VGGSound/video/R-dvwqS5vLQ_000033.mp4 planing timber +tests/VGGSound/video/UjQHWBPbySQ_000087.mp4 people slapping +tests/VGGSound/video/UjUxNykTQYo_000052.mp4 chipmunk chirping +tests/VGGSound/video/UkIOg1Spd5A_000030.mp4 singing choir +tests/VGGSound/video/UkKDHtVKDrc_000473.mp4 driving snowmobile +tests/VGGSound/video/UkO0Xiqpx5A_000080.mp4 people burping +tests/VGGSound/video/UkQRD1PBszA_000454.mp4 playing darts +tests/VGGSound/video/Uka_Qhmi9cY_000017.mp4 zebra braying +tests/VGGSound/video/Uka_Qhmi9cY_000037.mp4 zebra braying +tests/VGGSound/video/Ukwj5AKxt0E_000000.mp4 goat bleating +tests/VGGSound/video/R1dfaoCfy88_000003.mp4 playing trombone +tests/VGGSound/video/UlOEjgkNdMU_000010.mp4 dog howling +tests/VGGSound/video/UltPy7eml7I_000012.mp4 mynah bird singing +tests/VGGSound/video/UmE1pLOIF44_000401.mp4 people sniggering +tests/VGGSound/video/UmGzdua2Ayc_000014.mp4 people belly laughing +tests/VGGSound/video/Uml273ueGDE_000080.mp4 wind noise +tests/VGGSound/video/UnfkJ5q1BAE_000173.mp4 barn swallow calling +tests/VGGSound/video/UoN2qtdE1YI_000090.mp4 lions roaring +tests/VGGSound/video/R449t87u6V0_000384.mp4 playing steelpan +tests/VGGSound/video/UoSID1KzWuI_000030.mp4 playing acoustic guitar +tests/VGGSound/video/UoelVWyciuE_000010.mp4 cat purring +tests/VGGSound/video/UoxPrTAyq2g_000000.mp4 elephant trumpeting +tests/VGGSound/video/Up72EgZT_B0_000049.mp4 bathroom ventilation fan running +tests/VGGSound/video/Up72EgZT_B0_000060.mp4 bathroom ventilation fan running +tests/VGGSound/video/UpMhsxYAadk_000108.mp4 playing bongo +tests/VGGSound/video/UpTkrr-4feg_000015.mp4 ferret dooking +tests/VGGSound/video/R5I7L3qtgNk_000061.mp4 ice cracking +tests/VGGSound/video/Uq-owMVP9qI_000030.mp4 people whispering +tests/VGGSound/video/Uq3iKbCNDCM_000060.mp4 playing harpsichord +tests/VGGSound/video/UrluLxHLwQM_000110.mp4 toilet flushing +tests/VGGSound/video/Urpfo3V0EPw_000030.mp4 people eating +tests/VGGSound/video/R6qqlyIDHfM_000006.mp4 people sneezing +tests/VGGSound/video/Us0qIYoVRvU_000144.mp4 slot machine +tests/VGGSound/video/Us9BSO3TeLw_000084.mp4 plastic bottle crushing +tests/VGGSound/video/UsNUR6tsoTs_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/R77XPtKgvy4_000030.mp4 playing bass guitar +tests/VGGSound/video/UsTk4M-U7-4_000246.mp4 fire crackling +tests/VGGSound/video/Usz7ZnOHaxY_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/R7ls6ZQJ5UM_000570.mp4 playing marimba, xylophone +tests/VGGSound/video/UtZofZjccBs_000290.mp4 skateboarding +tests/VGGSound/video/UtlddariDo4_000030.mp4 cattle, bovinae cowbell +tests/VGGSound/video/Uv3K_pEUlX8_000020.mp4 helicopter +tests/VGGSound/video/Uvn7waPvseo_000030.mp4 typing on computer keyboard +tests/VGGSound/video/Uw8xdpugGNc_000060.mp4 opening or closing car electric windows +tests/VGGSound/video/UwKwH8VH418_000001.mp4 mouse clicking +tests/VGGSound/video/UxBvDjoU8JI_000067.mp4 strike lighter +tests/VGGSound/video/UxEyOSK9nxo_000030.mp4 fire crackling +tests/VGGSound/video/UxPpGZTaf9E_000015.mp4 playing badminton +tests/VGGSound/video/UxZYiE92UYQ_000152.mp4 footsteps on snow +tests/VGGSound/video/UyCfhj3LXVk_000002.mp4 goat bleating +tests/VGGSound/video/UycDO8tQwsA_000420.mp4 bird squawking +tests/VGGSound/video/RBNdYzLHx5Q_000270.mp4 pumping water +tests/VGGSound/video/UynKj68K0VU_000030.mp4 people clapping +tests/VGGSound/video/UypQOtbE8wg_000000.mp4 bird wings flapping +tests/VGGSound/video/UzAXqTsdtjY_000560.mp4 playing didgeridoo +tests/VGGSound/video/UztuiHbZvCw_000991.mp4 lip smacking +tests/VGGSound/video/RCk6hxXs03M_000240.mp4 sharpen knife +tests/VGGSound/video/V-Kl0SDidHI_000020.mp4 door slamming +tests/VGGSound/video/V-RJWk8ZtnI_000160.mp4 running electric fan +tests/VGGSound/video/RDCeLCJp7NM_000040.mp4 coyote howling +tests/VGGSound/video/V-lj5QvZYBo_000030.mp4 firing cannon +tests/VGGSound/video/V-luZXfkZ9k_000000.mp4 playing cello +tests/VGGSound/video/RDnrb0xSkrs_000070.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/V0_pJYAyWoA_000098.mp4 zebra braying +tests/VGGSound/video/V0iF61-c6e0_000072.mp4 cheetah chirrup +tests/VGGSound/video/V0qdgPxgU2M_000023.mp4 playing volleyball +tests/VGGSound/video/V0zQHNmz0gU_000030.mp4 playing theremin +tests/VGGSound/video/V131AERGFH8_000058.mp4 chopping food +tests/VGGSound/video/V1M3HiUz0ZQ_000070.mp4 skateboarding +tests/VGGSound/video/V1PFTBG6WJE_000000.mp4 heart sounds, heartbeat +tests/VGGSound/video/V1iHWOwTbUQ_000159.mp4 plastic bottle crushing +tests/VGGSound/video/V22H0fpX_Vg_000054.mp4 children shouting +tests/VGGSound/video/V23UiMHeJF4_000000.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/RF8fPkV9HNc_000010.mp4 people screaming +tests/VGGSound/video/V2CoRIDCU3U_000030.mp4 goose honking +tests/VGGSound/video/V2OjPsg7ydY_000060.mp4 machine gun shooting +tests/VGGSound/video/V2XG0N1k2Po_000381.mp4 spraying water +tests/VGGSound/video/V2YcUPfFy6U_000335.mp4 hedge trimmer running +tests/VGGSound/video/V2znI68sdJQ_000030.mp4 typing on computer keyboard +tests/VGGSound/video/V3Mh5k7AOxE_000063.mp4 playing bongo +tests/VGGSound/video/V3PyScAbdV0_000381.mp4 ripping paper +tests/VGGSound/video/V3aaPyUdIyo_000244.mp4 playing double bass +tests/VGGSound/video/V3srC9WNp4c_000030.mp4 door slamming +tests/VGGSound/video/V4I4dNkN1xs_000064.mp4 wood thrush calling +tests/VGGSound/video/RH1q8tAbo5k_000076.mp4 chimpanzee pant-hooting +tests/VGGSound/video/V4YUpQKeKD4_000020.mp4 playing vibraphone +tests/VGGSound/video/V5a0OUeceeY_000042.mp4 snake rattling +tests/VGGSound/video/V5dlaF4rqrA_000060.mp4 fireworks banging +tests/VGGSound/video/RHfFQSSPmCo_000290.mp4 cap gun shooting +tests/VGGSound/video/V5xL8hLFY58_000030.mp4 playing mandolin +tests/VGGSound/video/V6YuDO6Mz2s_000030.mp4 sliding door +tests/VGGSound/video/V6hMByaSFVY_000029.mp4 bull bellowing +tests/VGGSound/video/V7GTs7ivqyY_000681.mp4 yodelling +tests/VGGSound/video/V7M8J64sUZs_000077.mp4 people eating crisps +tests/VGGSound/video/RIrwRBosuIw_000000.mp4 underwater bubbling +tests/VGGSound/video/V7WHQs_3HJ0_000003.mp4 whale calling +tests/VGGSound/video/RJFdWGEdzP4_000111.mp4 fox barking +tests/VGGSound/video/V89-wTa6qcY_000070.mp4 mynah bird singing +tests/VGGSound/video/RJSOdjarLtk_000020.mp4 airplane +tests/VGGSound/video/RJSOdjarLtk_000044.mp4 airplane +tests/VGGSound/video/V8L152xzOJo_000001.mp4 scuba diving +tests/VGGSound/video/V8doyquJFyw_000000.mp4 elephant trumpeting +tests/VGGSound/video/V8sGSG45U14_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/V8tcqAyPSYw_000064.mp4 missile launch +tests/VGGSound/video/V9jIsOTC1lY_000030.mp4 playing steelpan +tests/VGGSound/video/VAV0cP55KIw_000330.mp4 pumping water +tests/VGGSound/video/VAfO711tnQA_000030.mp4 playing acoustic guitar +tests/VGGSound/video/VAqgpoyD2jc_000030.mp4 playing banjo +tests/VGGSound/video/VB-yZzj969U_000240.mp4 people burping +tests/VGGSound/video/VBQPcmmUkkg_000010.mp4 playing harpsichord +tests/VGGSound/video/VC0c22cJTbM_000424.mp4 writing on blackboard with chalk +tests/VGGSound/video/VCWoxeOUJzc_000011.mp4 alligators, crocodiles hissing +tests/VGGSound/video/VCWoxeOUJzc_000083.mp4 alligators, crocodiles hissing +tests/VGGSound/video/VCdHfU5YbsQ_000080.mp4 owl hooting +tests/VGGSound/video/VEmOUHxessE_000010.mp4 cap gun shooting +tests/VGGSound/video/VF2-Xbyvs_I_000109.mp4 yodelling +tests/VGGSound/video/VFCB7xV6chI_000110.mp4 pumping water +tests/VGGSound/video/VFT28TnDQ5g_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/VFTNOF77bMs_000500.mp4 playing trumpet +tests/VGGSound/video/VFovON0CWco_000521.mp4 striking bowling +tests/VGGSound/video/VG6-MlmCgzI_000030.mp4 playing sitar +tests/VGGSound/video/VGcDgVyf5Ok_000038.mp4 hail +tests/VGGSound/video/VH-0wYC3_lQ_000070.mp4 spraying water +tests/VGGSound/video/VHMrs4fni58_000100.mp4 forging swords +tests/VGGSound/video/VHUZvGxQbFA_000000.mp4 typing on computer keyboard +tests/VGGSound/video/ROsVbzFlnp0_000024.mp4 bathroom ventilation fan running +tests/VGGSound/video/RP5mput8V9A_000000.mp4 frog croaking +tests/VGGSound/video/VJ9E_Td0_dk_000030.mp4 people sniggering +tests/VGGSound/video/VJAJzwsogP8_000446.mp4 donkey, ass braying +tests/VGGSound/video/VJHPp490Xow_000070.mp4 splashing water +tests/VGGSound/video/VKVcOb8oFqY_000019.mp4 planing timber +tests/VGGSound/video/VKVcOb8oFqY_000500.mp4 planing timber +tests/VGGSound/video/VKekx2cvfcM_000030.mp4 playing gong +tests/VGGSound/video/VKfgSYvbohY_000042.mp4 playing oboe +tests/VGGSound/video/VKnQSCz2IVs_000000.mp4 tractor digging +tests/VGGSound/video/VLNKqrVmD9g_000030.mp4 female speech, woman speaking +tests/VGGSound/video/VLyLt6Rfw6U_000360.mp4 machine gun shooting +tests/VGGSound/video/VM-U7MyZAck_000030.mp4 playing bass guitar +tests/VGGSound/video/RRyiYofOuPs_000030.mp4 people burping +tests/VGGSound/video/VMbJTgzMhKE_000030.mp4 waterfall burbling +tests/VGGSound/video/VN4AS5J25os_000040.mp4 playing hammond organ +tests/VGGSound/video/VN5W9piaNOw_000063.mp4 swimming +tests/VGGSound/video/VN9Vq3wM-vI_000013.mp4 underwater bubbling +tests/VGGSound/video/RSPZSkLWsH4_000252.mp4 sheep bleating +tests/VGGSound/video/VNzEAjztgxg_000030.mp4 playing synthesizer +tests/VGGSound/video/VO1QA-Ihceo_000368.mp4 playing guiro +tests/VGGSound/video/VOWGbyg4KZY_000030.mp4 playing acoustic guitar +tests/VGGSound/video/VP2WctM2tzU_000000.mp4 typing on typewriter +tests/VGGSound/video/VPM383zJz68_000030.mp4 railroad car, train wagon +tests/VGGSound/video/VPhcuvPn6L4_000250.mp4 people finger snapping +tests/VGGSound/video/VQ3h0ZA3FQ0_000260.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/VQ60kd-BrC8_000030.mp4 church bell ringing +tests/VGGSound/video/RUfBSmbs6j0_000025.mp4 hammering nails +tests/VGGSound/video/VR3BEMxNhz8_000030.mp4 fire crackling +tests/VGGSound/video/VRaLq9Gb9xI_000180.mp4 using sewing machines +tests/VGGSound/video/VS81egrQqC0_000024.mp4 opening or closing car doors +tests/VGGSound/video/VSf-6xznJyk_000240.mp4 people sobbing +tests/VGGSound/video/VSkdiYt87rg_000030.mp4 people sobbing +tests/VGGSound/video/VSqtCFd5120_000029.mp4 heart sounds, heartbeat +tests/VGGSound/video/VSxoWInFsIA_000030.mp4 mouse squeaking +tests/VGGSound/video/VTI1k--NxMk_000030.mp4 pig oinking +tests/VGGSound/video/VToLYUUD5Dw_000022.mp4 bowling impact +tests/VGGSound/video/VU-NQMhwnEs_000150.mp4 sea lion barking +tests/VGGSound/video/VUO27HxWQfI_000406.mp4 race car, auto racing +tests/VGGSound/video/VUeoWEgUMrg_000016.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/VUosI4YQook_000030.mp4 rowboat, canoe, kayak rowing 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playing darts +tests/VGGSound/video/RhsXiHgKzyY_000023.mp4 gibbon howling +tests/VGGSound/video/VkcsBNzy1UA_000091.mp4 yodelling +tests/VGGSound/video/RhzsxX39VMU_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/Ri1yo_ahtaQ_000190.mp4 opening or closing drawers +tests/VGGSound/video/Ri47GANmuQ4_000016.mp4 elephant trumpeting +tests/VGGSound/video/VlJHwd84GSo_000197.mp4 people humming +tests/VGGSound/video/RiERI_EEtac_000007.mp4 playing darts +tests/VGGSound/video/VldL5A1xugE_000048.mp4 cupboard opening or closing +tests/VGGSound/video/Vlh9AMaTrLQ_000441.mp4 playing oboe +tests/VGGSound/video/Vlh9AMaTrLQ_000451.mp4 playing oboe +tests/VGGSound/video/Vlj9AOEP6_c_000026.mp4 playing squash +tests/VGGSound/video/VmYPBzrkKGw_000140.mp4 playing oboe +tests/VGGSound/video/VmoG9nSADn8_000030.mp4 helicopter +tests/VGGSound/video/RjVLYi4jQYc_000043.mp4 people battle cry +tests/VGGSound/video/RjW-A2yB9pY_000027.mp4 missile launch +tests/VGGSound/video/Vo7TOX5_EPQ_000001.mp4 sea lion barking +tests/VGGSound/video/Rk5dBZo4aFA_000030.mp4 playing bagpipes +tests/VGGSound/video/VoQu9t04E6w_000055.mp4 lions growling +tests/VGGSound/video/Vo_BuHqpf40_000077.mp4 metronome +tests/VGGSound/video/VojIJTqZM5k_000861.mp4 alligators, crocodiles hissing +tests/VGGSound/video/Vp4lOXVBQzQ_000010.mp4 owl hooting +tests/VGGSound/video/VpCCJy5atYU_000144.mp4 ice cream truck, ice cream van +tests/VGGSound/video/VpIhbDN58mA_000030.mp4 playing timpani +tests/VGGSound/video/VpU4twmXFiI_000010.mp4 people whistling +tests/VGGSound/video/VpYJRHq8TC0_000110.mp4 singing bowl +tests/VGGSound/video/VpZ7mkQBLrY_000065.mp4 popping popcorn +tests/VGGSound/video/VpuNCFDYgnA_000070.mp4 playing trombone +tests/VGGSound/video/VqBGj3jhiJ0_000030.mp4 fire crackling +tests/VGGSound/video/VqI5IF3HmBo_000098.mp4 playing volleyball +tests/VGGSound/video/Rm2XQrio0QE_000099.mp4 playing bongo +tests/VGGSound/video/Vr2EzXVNb_s_000041.mp4 playing bassoon +tests/VGGSound/video/RmKcbiWqFOw_000046.mp4 cutting hair with electric trimmers +tests/VGGSound/video/RmUG1ffgKFw_000170.mp4 playing saxophone +tests/VGGSound/video/RmdvTlx9C0k_000030.mp4 people shuffling +tests/VGGSound/video/VrZkUqz2WZI_000290.mp4 toilet flushing +tests/VGGSound/video/Rn0GEJVNV7I_000002.mp4 sloshing water +tests/VGGSound/video/Rn0JiZUTcv0_000078.mp4 zebra braying +tests/VGGSound/video/VrljAMqy9dA_000420.mp4 playing saxophone +tests/VGGSound/video/VrwW35FmP0w_000025.mp4 waterfall burbling +tests/VGGSound/video/Vs6_ORAIitU_000056.mp4 woodpecker pecking tree +tests/VGGSound/video/VsQMbITqgx8_000225.mp4 planing timber +tests/VGGSound/video/RnXiQh8x--c_000126.mp4 telephone bell ringing +tests/VGGSound/video/Vsl9vfhmbN8_000030.mp4 orchestra +tests/VGGSound/video/Ro3st3CwwwY_000030.mp4 sloshing water +tests/VGGSound/video/VtcXTrVLwb8_000598.mp4 beat boxing +tests/VGGSound/video/RoKx3X5tdV8_000000.mp4 skiing +tests/VGGSound/video/VuXmHBFFkPw_000030.mp4 dog bow-wow +tests/VGGSound/video/VudaWX3XJoQ_000129.mp4 golf driving 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dinosaurs bellowing +tests/VGGSound/video/WJUtEDBS0Dw_000295.mp4 dinosaurs bellowing +tests/VGGSound/video/WJV6Ey6hXEw_000005.mp4 dog growling +tests/VGGSound/video/WJVc82XgbZk_000014.mp4 woodpecker pecking tree +tests/VGGSound/video/SAcTgna3oOY_000003.mp4 dog baying +tests/VGGSound/video/WK78KAj2WWs_000000.mp4 fly, housefly buzzing +tests/VGGSound/video/WKBgoWKeWz4_000011.mp4 swimming +tests/VGGSound/video/WKYOzgjKdqI_000030.mp4 pig oinking +tests/VGGSound/video/WKbADRKJLo0_000138.mp4 coyote howling +tests/VGGSound/video/SBLZADwyPPc_000057.mp4 volcano explosion +tests/VGGSound/video/WKjzhyE0j4g_000055.mp4 children shouting +tests/VGGSound/video/WKlLEyxuUqo_000410.mp4 playing didgeridoo +tests/VGGSound/video/WKlfyztuZ7I_000062.mp4 forging swords +tests/VGGSound/video/WLEZDT_vGuM_000016.mp4 air conditioning noise +tests/VGGSound/video/WLL4th4kUZ4_000020.mp4 fire crackling +tests/VGGSound/video/WLPj0LIokkM_000020.mp4 chainsawing trees +tests/VGGSound/video/WLX3Db60418_000020.mp4 driving motorcycle +tests/VGGSound/video/WLmYzJjwWr0_000026.mp4 airplane +tests/VGGSound/video/WMPQ44bukK0_000397.mp4 people slurping +tests/VGGSound/video/WMXkrLwPVCU_000098.mp4 cheetah chirrup +tests/VGGSound/video/WMZ3ZAMcE3s_000204.mp4 cat hissing +tests/VGGSound/video/WMZ3ZAMcE3s_000220.mp4 cat hissing +tests/VGGSound/video/WMbdMQ7rdFs_000030.mp4 sliding door +tests/VGGSound/video/WMcin-2RF7s_000078.mp4 striking bowling +tests/VGGSound/video/WMxMPVft4HE_000016.mp4 car engine idling +tests/VGGSound/video/WO7xbZEsKvc_000131.mp4 playing hockey +tests/VGGSound/video/WOoi5Sr2ux0_000021.mp4 underwater bubbling +tests/VGGSound/video/WPY9SLh8dwY_000390.mp4 baby babbling +tests/VGGSound/video/Z__IjjEMaxw_000092.mp4 chopping food +tests/VGGSound/video/Z_a_PuxKUwc_000000.mp4 lighting firecrackers +tests/VGGSound/video/WPsoHV3zRPQ_000290.mp4 goose honking +tests/VGGSound/video/Z_prZn13JXY_000093.mp4 tornado roaring +tests/VGGSound/video/Za8bwlW9dNE_000089.mp4 bull bellowing 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cornet +tests/VGGSound/video/Y5Qrawu3guY_000030.mp4 playing banjo +tests/VGGSound/video/Y5TOBR2w3Gc_000138.mp4 tornado roaring +tests/VGGSound/video/Y5ZGlOUUcs8_000290.mp4 bird wings flapping +tests/VGGSound/video/aJKu_6M6WMw_000484.mp4 playing badminton +tests/VGGSound/video/aJNiSRqdCco_000011.mp4 people booing +tests/VGGSound/video/Y5oaCVCDhYI_000033.mp4 whale calling +tests/VGGSound/video/Y5t8KSDEeOs_000000.mp4 opening or closing car electric windows +tests/VGGSound/video/Y6-EXl7Njzg_000030.mp4 people babbling +tests/VGGSound/video/Y612uIsQ9HM_000012.mp4 lions roaring +tests/VGGSound/video/aJoauH7KaGw_000175.mp4 playing shofar +tests/VGGSound/video/aJpAmCQy3HY_000057.mp4 train wheels squealing +tests/VGGSound/video/aJy80ff2TbU_000030.mp4 wind rustling leaves +tests/VGGSound/video/Y6lUctPmnoc_000007.mp4 donkey, ass braying +tests/VGGSound/video/aKWG9CWMoWo_000696.mp4 mouse clicking +tests/VGGSound/video/aKZ3NJi8GVU_000000.mp4 baltimore oriole calling 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dooking +tests/VGGSound/video/YElBZnW40Ng_000021.mp4 mosquito buzzing +tests/VGGSound/video/YEmbpZxiZPw_000062.mp4 playing tympani +tests/VGGSound/video/YFHYP_TSWII_000030.mp4 playing electric guitar +tests/VGGSound/video/YFMe9taghFg_000030.mp4 playing hockey +tests/VGGSound/video/YFO26ojd-sI_000007.mp4 rope skipping +tests/VGGSound/video/aTY-qvtDbrc_000024.mp4 playing castanets +tests/VGGSound/video/YFXSbPFaxcA_000030.mp4 printer printing +tests/VGGSound/video/YFY4CjiJ6hE_000554.mp4 hedge trimmer running +tests/VGGSound/video/aTdpU4HGxXA_000109.mp4 alarm clock ringing +tests/VGGSound/video/YFmO4K_mdTo_000181.mp4 hedge trimmer running +tests/VGGSound/video/YFoWfT2ijhw_000475.mp4 striking pool +tests/VGGSound/video/YFwzNNEuOSY_000050.mp4 wind noise +tests/VGGSound/video/aU3PT6cU-5g_000395.mp4 playing tambourine +tests/VGGSound/video/aU8dxXh2yqk_000390.mp4 chicken crowing +tests/VGGSound/video/aUG81LArlcM_000049.mp4 baltimore oriole calling +tests/VGGSound/video/YGj2ZPZ5cew_000290.mp4 turkey gobbling +tests/VGGSound/video/YGv1xUgz2pY_000045.mp4 playing tympani +tests/VGGSound/video/aUVT2tUbPN8_000187.mp4 spraying water +tests/VGGSound/video/YH3QrPYosKY_000017.mp4 woodpecker pecking tree +tests/VGGSound/video/aUfDxRelPHg_000022.mp4 lions roaring +tests/VGGSound/video/aUq3toj7jDo_000018.mp4 people running +tests/VGGSound/video/aUx0xMF9pwU_000020.mp4 playing vibraphone +tests/VGGSound/video/YIN5D9ffrtE_000031.mp4 coyote howling +tests/VGGSound/video/YIN5D9ffrtE_000049.mp4 coyote howling +tests/VGGSound/video/YIPcA-V0wcg_000070.mp4 people burping +tests/VGGSound/video/aW3_8p1ElDw_000030.mp4 lighting firecrackers +tests/VGGSound/video/aW9PDD_Eb7s_000240.mp4 people whispering +tests/VGGSound/video/YIZ4aSKT3mo_000128.mp4 volcano explosion +tests/VGGSound/video/aWJDNhMn408_000025.mp4 barn swallow calling +tests/VGGSound/video/YIkaXXmw8ME_000000.mp4 people finger snapping +tests/VGGSound/video/aWaMcq7HuKw_000000.mp4 playing didgeridoo 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disc scratching +tests/VGGSound/video/aZ3FpqWTJjQ_000160.mp4 subway, metro, underground +tests/VGGSound/video/YLGxmdhFdrY_000025.mp4 gibbon howling +tests/VGGSound/video/aZ731aR_SBY_000000.mp4 playing timpani +tests/VGGSound/video/aZNrJFxR9HU_000013.mp4 cat hissing +tests/VGGSound/video/YLduYJDnL5c_000010.mp4 dog whimpering +tests/VGGSound/video/YM27M-R0kIA_000000.mp4 horse neighing +tests/VGGSound/video/aZfszZqR7i4_000120.mp4 subway, metro, underground +tests/VGGSound/video/YMHuJvqphUw_000440.mp4 playing tabla +tests/VGGSound/video/aZj3L_Pjz8A_000100.mp4 children shouting +tests/VGGSound/video/aZmN_hzwJAs_000026.mp4 people battle cry +tests/VGGSound/video/aZxm-nYkpNs_000003.mp4 cricket chirping +tests/VGGSound/video/YMq4wE6KxmQ_000030.mp4 people running +tests/VGGSound/video/a_HZ5bMXveM_000033.mp4 baltimore oriole calling +tests/VGGSound/video/a_HzXa0YVIo_000170.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/YN5CTUvVDGw_000200.mp4 playing gong 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playing gong +tests/VGGSound/video/adnbNvLOI48_000306.mp4 skiing +tests/VGGSound/video/ae-0CmRei-k_000063.mp4 eletric blender running +tests/VGGSound/video/YRmyucD5GhI_000217.mp4 blowtorch igniting +tests/VGGSound/video/YRyK_1g4VWQ_000010.mp4 cat caterwauling +tests/VGGSound/video/YS-Gtu-RuaE_000051.mp4 cupboard opening or closing +tests/VGGSound/video/YS-Gtu-RuaE_000061.mp4 cupboard opening or closing +tests/VGGSound/video/aeFlHmaZMoU_000144.mp4 otter growling +tests/VGGSound/video/aeFlHmaZMoU_000200.mp4 otter growling +tests/VGGSound/video/YSHiuRUGOBs_000232.mp4 strike lighter +tests/VGGSound/video/YSKv2zqj4VI_000030.mp4 mosquito buzzing +tests/VGGSound/video/YSLun3TqE08_000150.mp4 playing cello +tests/VGGSound/video/aec791kXVms_000011.mp4 dog baying +tests/VGGSound/video/YSgzZEeYOms_000030.mp4 orchestra +tests/VGGSound/video/YSsLH9_cisM_000236.mp4 bull bellowing +tests/VGGSound/video/YSusDxOzgks_000340.mp4 playing double bass +tests/VGGSound/video/YTFJUFWcRns_000030.mp4 skidding 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opening or closing drawers +tests/VGGSound/video/YhIrgcaaXS8_000280.mp4 playing french horn +tests/VGGSound/video/av-1Ih0S82s_000030.mp4 playing timpani +tests/VGGSound/video/avMMHoVQdTI_000039.mp4 playing washboard +tests/VGGSound/video/avPEH7IukYc_000030.mp4 playing tympani +tests/VGGSound/video/avcRRcIRnbY_000030.mp4 horse neighing +tests/VGGSound/video/YiYb6WwdTDA_000030.mp4 playing sitar +tests/VGGSound/video/avhgeclEu8k_000050.mp4 driving motorcycle +tests/VGGSound/video/avtZJKydB-E_000079.mp4 snake rattling +tests/VGGSound/video/Yj4i4C-CZ7M_000000.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/awQP-69K3rY_000420.mp4 bird chirping, tweeting +tests/VGGSound/video/YjJa2bx67BY_000330.mp4 playing cello +tests/VGGSound/video/YjNQ5TGRChs_000030.mp4 firing cannon +tests/VGGSound/video/YjOOi6WAjtI_000023.mp4 cow lowing +tests/VGGSound/video/YjScrri_F7U_000000.mp4 skateboarding +tests/VGGSound/video/awfbE0KxEjE_000380.mp4 airplane flyby +tests/VGGSound/video/awn0pAyJJYk_000030.mp4 goat bleating +tests/VGGSound/video/awu8YzLtqF0_000050.mp4 people farting +tests/VGGSound/video/Yk4r9XfKd2E_000261.mp4 playing bass drum +tests/VGGSound/video/ax7iCns3xz8_000090.mp4 people whistling +tests/VGGSound/video/YkTTlw86Yqw_000049.mp4 tornado roaring +tests/VGGSound/video/axSlCt0ZHVI_000151.mp4 eagle screaming +tests/VGGSound/video/axXpdF1Z9II_000039.mp4 alarm clock ringing +tests/VGGSound/video/axgPZWQgGfA_000030.mp4 duck quacking +tests/VGGSound/video/Ykv1CiXNXLQ_000134.mp4 yodelling +tests/VGGSound/video/YlI9xWmyMzg_000010.mp4 chicken clucking +tests/VGGSound/video/axzMyhAbU4I_000030.mp4 pig oinking +tests/VGGSound/video/YlLC5aGq4Yw_000009.mp4 alligators, crocodiles hissing +tests/VGGSound/video/YlLqWCeiVPw_000030.mp4 cat meowing +tests/VGGSound/video/ay05WMzpmAk_000035.mp4 forging swords +tests/VGGSound/video/YlpOZqnLeEs_000125.mp4 alarm clock ringing +tests/VGGSound/video/ayrzdxBwzGw_000080.mp4 wind rustling leaves +tests/VGGSound/video/Ymr297idqMA_000260.mp4 train horning 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babbling +tests/VGGSound/video/YrGQKTbiG1g_000030.mp4 skateboarding +tests/VGGSound/video/YrH0TXyYSNM_000010.mp4 mouse squeaking +tests/VGGSound/video/YrheeLTG-5U_000002.mp4 plastic bottle crushing +tests/VGGSound/video/YrheeLTG-5U_000042.mp4 plastic bottle crushing +tests/VGGSound/video/b3teffaC_eE_000140.mp4 raining +tests/VGGSound/video/b3vr1k3gAQE_000000.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/Ys2ri7Pw2gw_001404.mp4 footsteps on snow +tests/VGGSound/video/Ys9Tvftkin0_000070.mp4 people hiccup +tests/VGGSound/video/YsHxZjm-zg8_000120.mp4 playing violin, fiddle +tests/VGGSound/video/YsUCzO0gfro_000060.mp4 people coughing +tests/VGGSound/video/YsX-dUhC-_4_000000.mp4 people hiccup +tests/VGGSound/video/Ysjdu0ZZmQE_000100.mp4 warbler chirping +tests/VGGSound/video/YsphDAFz1DA_000100.mp4 wind noise +tests/VGGSound/video/Ysqh1uzqGrc_000000.mp4 child singing +tests/VGGSound/video/Ysrlv2UlG8A_000030.mp4 playing synthesizer +tests/VGGSound/video/b4glNhNvMYU_000340.mp4 playing flute 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child singing +tests/VGGSound/video/Yw40aGSoGYw_000078.mp4 cell phone buzzing +tests/VGGSound/video/b8Ak4qtNXfk_000007.mp4 playing tambourine +tests/VGGSound/video/b8AzwUMbgb4_000021.mp4 cat growling +tests/VGGSound/video/b8Qv5KWswiI_000007.mp4 baby crying +tests/VGGSound/video/b8fp8ZcYdG4_000036.mp4 sheep bleating +tests/VGGSound/video/YwUa3OS92ZQ_000030.mp4 pig oinking +tests/VGGSound/video/YweMTt5aAVY_000070.mp4 splashing water +tests/VGGSound/video/b93GiuJ3KpY_000030.mp4 people burping +tests/VGGSound/video/YwoYv1REVss_000050.mp4 church bell ringing +tests/VGGSound/video/Yx5pH0S0Clc_000062.mp4 black capped chickadee calling +tests/VGGSound/video/YxCVP-9lvZ4_000215.mp4 playing double bass +tests/VGGSound/video/b9QbvDDoPsU_000160.mp4 playing saxophone +tests/VGGSound/video/b9_0h4gfccw_000000.mp4 waterfall burbling +tests/VGGSound/video/YxIScOdROZE_000090.mp4 dog growling +tests/VGGSound/video/bA8idGxNUkQ_000026.mp4 dog growling +tests/VGGSound/video/bA8mt0JI0Ko_000030.mp4 police car 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+tests/VGGSound/video/bNsdqz8CYbs_000230.mp4 opening or closing drawers +tests/VGGSound/video/ZBk-DylU4Ac_000013.mp4 ice cream truck, ice cream van +tests/VGGSound/video/bNvp4y9WSGM_000030.mp4 playing violin, fiddle +tests/VGGSound/video/ZBqMDXvp9Ak_000096.mp4 playing volleyball +tests/VGGSound/video/bO6gUBBcniY_000030.mp4 people clapping +tests/VGGSound/video/ZC2-HlTYjqA_000050.mp4 ocean burbling +tests/VGGSound/video/bO9-u7AH8B8_000030.mp4 cattle mooing +tests/VGGSound/video/bOCkO_RtPIo_000300.mp4 sailing +tests/VGGSound/video/bOD-pt3NWYc_000018.mp4 ice cream truck, ice cream van +tests/VGGSound/video/bOOJRGRy0zc_000030.mp4 rapping +tests/VGGSound/video/bOtUES6eNxs_000010.mp4 machine gun shooting +tests/VGGSound/video/ZD86LBLgawc_000658.mp4 race car, auto racing +tests/VGGSound/video/bPTk9xTSWr4_000325.mp4 shot football +tests/VGGSound/video/ZDtQSsioywU_000958.mp4 opening or closing car electric windows +tests/VGGSound/video/bPvol3UhlNs_000087.mp4 smoke detector beeping +tests/VGGSound/video/bPwAxV8iEfA_000100.mp4 playing trumpet +tests/VGGSound/video/bPzCbrmKoVY_000019.mp4 bathroom ventilation fan running +tests/VGGSound/video/bQABY9H1h1Y_000280.mp4 cricket chirping +tests/VGGSound/video/ZECeW7EAQtM_000010.mp4 driving buses +tests/VGGSound/video/bQOqX1W3ejA_000030.mp4 people sneezing +tests/VGGSound/video/ZENfhZYyv-M_000030.mp4 crow cawing +tests/VGGSound/video/ZEP87KTkyNM_000277.mp4 driving snowmobile +tests/VGGSound/video/bR8fbwavKtc_000060.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/bRCzdN1jfk0_000000.mp4 alarm clock ringing +tests/VGGSound/video/bRMhCq4dB9k_000003.mp4 wind chime +tests/VGGSound/video/ZFS_SPkhO30_000015.mp4 cutting hair with electric trimmers +tests/VGGSound/video/bSHxNkxMr74_000018.mp4 bouncing on trampoline +tests/VGGSound/video/ZFs03gCSB_g_000270.mp4 typing on computer keyboard +tests/VGGSound/video/bSItOIS0k5w_000008.mp4 playing guiro +tests/VGGSound/video/bSUGa1r7Vpo_000125.mp4 people eating apple +tests/VGGSound/video/bS_1Sv24jso_000000.mp4 people finger snapping +tests/VGGSound/video/ZGYQX-172io_000011.mp4 dog bow-wow +tests/VGGSound/video/ZGYQX-172io_000022.mp4 dog bow-wow +tests/VGGSound/video/bSpAlQLisrI_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/bTFB6JC2sIM_000000.mp4 mosquito buzzing +tests/VGGSound/video/ZGubbE6cRL0_000040.mp4 people burping +tests/VGGSound/video/ZH2ncVKeG6I_000004.mp4 people nose blowing +tests/VGGSound/video/ZH4YSF-i5dY_000301.mp4 cat caterwauling +tests/VGGSound/video/ZH5b3e8ivvM_000010.mp4 playing bagpipes +tests/VGGSound/video/ZHIwj6hmd4A_000000.mp4 bird squawking +tests/VGGSound/video/ZHK2VTTMMWs_000370.mp4 opening or closing drawers +tests/VGGSound/video/ZHeCQUEStf8_000219.mp4 black capped chickadee calling +tests/VGGSound/video/ZHksjiNWM-0_000030.mp4 lighting firecrackers +tests/VGGSound/video/bTuKGXDrqdQ_000030.mp4 playing didgeridoo +tests/VGGSound/video/bU2DcKTehgo_000240.mp4 skateboarding +tests/VGGSound/video/ZHoUO-Mpao8_000065.mp4 playing snare drum +tests/VGGSound/video/ZHspqva9lCM_000015.mp4 disc scratching +tests/VGGSound/video/ZHspqva9lCM_000231.mp4 disc scratching +tests/VGGSound/video/ZHzhdhKEjMc_000030.mp4 duck quacking +tests/VGGSound/video/bUW928MqrnU_000230.mp4 playing steelpan +tests/VGGSound/video/ZIIHbHQKgjo_000024.mp4 playing guiro +tests/VGGSound/video/ZIPScztJi0M_000049.mp4 cricket chirping +tests/VGGSound/video/bV7Vr3sUq_s_000078.mp4 cutting hair with electric trimmers +tests/VGGSound/video/bV8qnp-Vos8_000330.mp4 baby laughter +tests/VGGSound/video/ZIgZ_OKQyF0_000215.mp4 donkey, ass braying +tests/VGGSound/video/ZIgZ_OKQyF0_000225.mp4 donkey, ass braying +tests/VGGSound/video/ZIktpr-Ic4U_000010.mp4 people running +tests/VGGSound/video/ZIm_awdgw_Q_000181.mp4 bowling impact +tests/VGGSound/video/ZIuVIb_LeOU_000044.mp4 people humming +tests/VGGSound/video/bVPLdRReUZ8_000013.mp4 firing cannon +tests/VGGSound/video/bVR288WbDXc_000030.mp4 car passing by +tests/VGGSound/video/ZJ3rcQ7kvA8_000632.mp4 mouse clicking +tests/VGGSound/video/ZJ9JzDLeGt4_000020.mp4 people farting +tests/VGGSound/video/bVg-KMzzrVA_000137.mp4 ice cream truck, ice cream van +tests/VGGSound/video/ZJHBBH9gh2Y_000000.mp4 playing french horn +tests/VGGSound/video/ZJHlHb-VyDc_000030.mp4 playing sitar +tests/VGGSound/video/bVo174I2ydc_000279.mp4 playing snare drum +tests/VGGSound/video/ZJIgxpYf20I_000030.mp4 typing on typewriter +tests/VGGSound/video/ZJKJWpW9BJI_000067.mp4 playing darts +tests/VGGSound/video/ZJOblt2XUJI_000004.mp4 mosquito buzzing +tests/VGGSound/video/bW2Tw3pJFqQ_000000.mp4 playing electronic organ +tests/VGGSound/video/bWKYTH7OYXk_000220.mp4 waterfall burbling +tests/VGGSound/video/bWZO5eziPnU_000042.mp4 cupboard opening or closing +tests/VGGSound/video/bWaNlcXuGmI_000270.mp4 playing theremin +tests/VGGSound/video/ZK2rF-mQ1Qk_000010.mp4 slot machine +tests/VGGSound/video/bWyrxAZCOhA_000020.mp4 playing cello +tests/VGGSound/video/bX8TQimHigU_000066.mp4 tornado roaring +tests/VGGSound/video/ZKc97rLhU_k_000079.mp4 roller coaster running +tests/VGGSound/video/bXTlmnjGx0Y_000049.mp4 alligators, crocodiles hissing +tests/VGGSound/video/bXTlmnjGx0Y_000107.mp4 alligators, crocodiles hissing +tests/VGGSound/video/bXZduPL_O60_001056.mp4 blowtorch igniting +tests/VGGSound/video/ZKocFGL8LIE_000000.mp4 thunder +tests/VGGSound/video/ZKsNHjqLM1s_000046.mp4 cuckoo bird calling +tests/VGGSound/video/bXtS2woenCY_000000.mp4 people running +tests/VGGSound/video/ZKyVMjSiP7c_000211.mp4 shot football +tests/VGGSound/video/bY2cN3BgPsU_000070.mp4 people booing +tests/VGGSound/video/bY2cN3BgPsU_000140.mp4 people booing +tests/VGGSound/video/ZL9Jgk9qDlY_000115.mp4 plastic bottle crushing +tests/VGGSound/video/ZLX7NZF2-KE_000340.mp4 eating with cutlery +tests/VGGSound/video/bYQyHfbrq74_000004.mp4 elk bugling +tests/VGGSound/video/ZLhwJe2uawk_000862.mp4 electric grinder grinding +tests/VGGSound/video/bYwoYjbPm-I_000030.mp4 wind rustling leaves +tests/VGGSound/video/ZLtKerokcPg_000080.mp4 playing tabla +tests/VGGSound/video/bZOJYhzt5_U_000240.mp4 playing oboe +tests/VGGSound/video/ZMN2Bs_Cr1A_000450.mp4 basketball bounce +tests/VGGSound/video/bZadyuv2utE_000080.mp4 cat purring +tests/VGGSound/video/bZpxpqedQTQ_000193.mp4 hammering nails +tests/VGGSound/video/ZMZHRrtBZ6w_000108.mp4 people humming +tests/VGGSound/video/ZMcJY8yLjUs_000011.mp4 magpie calling +tests/VGGSound/video/ZMd8mAKe-k8_000030.mp4 playing sitar +tests/VGGSound/video/ZN1L5NaaikI_000002.mp4 children shouting +tests/VGGSound/video/b_RtXz277T0_000030.mp4 door slamming +tests/VGGSound/video/ZNEEzZXROTo_000058.mp4 people cheering +tests/VGGSound/video/b_U7bnvkvOk_000095.mp4 sheep bleating +tests/VGGSound/video/b_hJemPlLbg_000173.mp4 smoke detector beeping +tests/VGGSound/video/b_kvMCmoZw0_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/ZNe6E93k6tI_000050.mp4 people burping +tests/VGGSound/video/ba43-gH05H4_000040.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/ba6ArmDZjW4_000314.mp4 forging swords +tests/VGGSound/video/baayJxbQepY_000188.mp4 playing timbales +tests/VGGSound/video/ZOTPrbPDynk_000055.mp4 writing on blackboard with chalk +tests/VGGSound/video/ZOk7NejyH9Y_000050.mp4 mouse pattering +tests/VGGSound/video/ZOkDV5Z3Nn8_000012.mp4 playing congas +tests/VGGSound/video/ZOnuS52Fsu0_000000.mp4 baltimore oriole calling +tests/VGGSound/video/ZOnuS52Fsu0_000039.mp4 baltimore oriole calling +tests/VGGSound/video/bbR9xUdh-A4_000010.mp4 raining +tests/VGGSound/video/ZP0aFBkk3WE_000092.mp4 popping popcorn +tests/VGGSound/video/ZPBscuJXkO0_000580.mp4 firing cannon +tests/VGGSound/video/bbmnFurz1iA_000166.mp4 metronome +tests/VGGSound/video/ZPO1zpDqQ8I_000080.mp4 ocean burbling +tests/VGGSound/video/ZPXK1-_fYy0_000259.mp4 playing erhu +tests/VGGSound/video/bcBixpb5TdI_000098.mp4 pheasant crowing +tests/VGGSound/video/bcBixpb5TdI_000113.mp4 pheasant crowing +tests/VGGSound/video/ZPeG32vKQ3w_000030.mp4 typing on typewriter +tests/VGGSound/video/bcZ3ZPQQbYA_000011.mp4 mynah bird singing +tests/VGGSound/video/ZQ6q-mvWhKk_000116.mp4 shot football +tests/VGGSound/video/ZQ9ZV5uZZyQ_000028.mp4 playing glockenspiel +tests/VGGSound/video/bciLCctZfjE_000200.mp4 cap gun shooting +tests/VGGSound/video/bcm_HtYj_98_000000.mp4 cupboard opening or closing +tests/VGGSound/video/ZQ_d8kWsrUc_000637.mp4 planing timber +tests/VGGSound/video/bcuKTheCcsE_000003.mp4 fly, housefly buzzing +tests/VGGSound/video/bd4H-XjFNiM_000213.mp4 rope skipping +tests/VGGSound/video/ZQqgwiTnKII_000494.mp4 train horning +tests/VGGSound/video/ZRBdcMCPFV8_000039.mp4 footsteps on snow +tests/VGGSound/video/ZRC7nfJChUc_000007.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/ZRQ3vw3wNQ0_000010.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/ZRVktsXO9FI_000066.mp4 scuba diving +tests/VGGSound/video/ZRXUru_3Big_000112.mp4 electric grinder grinding +tests/VGGSound/video/ZS4Chf9yh8s_000020.mp4 mouse squeaking +tests/VGGSound/video/ZS7bf3avohU_000001.mp4 civil defense siren +tests/VGGSound/video/beb6mgkt16g_000029.mp4 writing on blackboard with chalk +tests/VGGSound/video/betIn2CIoDw_000000.mp4 basketball bounce +tests/VGGSound/video/ZSQLjxIsDYI_000026.mp4 hedge trimmer running +tests/VGGSound/video/bf551OyAH-Y_000030.mp4 cattle, bovinae cowbell +tests/VGGSound/video/bf81gVdcgUg_000436.mp4 running electric fan +tests/VGGSound/video/bf81gVdcgUg_000451.mp4 running electric fan +tests/VGGSound/video/ZSjJ0Wop4m0_000000.mp4 mouse squeaking +tests/VGGSound/video/bfLqa4vlmFI_000274.mp4 race car, auto racing +tests/VGGSound/video/bfOLFECH_W8_000350.mp4 lighting firecrackers +tests/VGGSound/video/ZSqKAFe326w_000063.mp4 dinosaurs bellowing +tests/VGGSound/video/bf_I0tRLfh4_000030.mp4 playing trombone +tests/VGGSound/video/ZT3jQW3tvt0_000015.mp4 canary calling +tests/VGGSound/video/bg7FiCQH3D4_000112.mp4 ice cracking +tests/VGGSound/video/bg9fsF7o0HY_000060.mp4 thunder +tests/VGGSound/video/bgGgPPudjlQ_000209.mp4 arc welding +tests/VGGSound/video/bgl8r_eRI1I_000000.mp4 people belly laughing +tests/VGGSound/video/ZU24o8WBd8M_000470.mp4 splashing water +tests/VGGSound/video/bh3M0wYsW1k_000076.mp4 alarm clock ringing +tests/VGGSound/video/bhA-HX-Z8h8_000200.mp4 subway, metro, underground +tests/VGGSound/video/bha-d3HXdMI_000060.mp4 playing bass guitar +tests/VGGSound/video/ZUp2sBZvw5Q_000082.mp4 train wheels squealing +tests/VGGSound/video/ZV9-hp6TMug_000000.mp4 playing clarinet +tests/VGGSound/video/bhvuDEOfMxo_000143.mp4 playing timbales +tests/VGGSound/video/ZVKgp2DGpcI_000010.mp4 dog bow-wow +tests/VGGSound/video/ZVKgp2DGpcI_000021.mp4 dog bow-wow +tests/VGGSound/video/ZVLfLLSbG5A_000107.mp4 cutting hair with electric trimmers +tests/VGGSound/video/bi5E6H04BhM_000552.mp4 people cheering +tests/VGGSound/video/ZV_ZbmjPpkw_000030.mp4 tapping guitar +tests/VGGSound/video/ZW7eH1DORJg_000030.mp4 people eating +tests/VGGSound/video/bi_GLOAbrKA_000060.mp4 bird wings flapping +tests/VGGSound/video/bizmBpWUwFk_000130.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/ZX2fVPmUidA_000030.mp4 playing banjo +tests/VGGSound/video/ZX3cWUG1njg_000059.mp4 coyote howling +tests/VGGSound/video/ZXDg02kHzPA_000149.mp4 playing glockenspiel +tests/VGGSound/video/bjSuO7h7YTQ_000041.mp4 missile launch +tests/VGGSound/video/bjb7QtMEBUg_000283.mp4 tornado roaring +tests/VGGSound/video/bjvnTxWP7vo_000090.mp4 playing cymbal +tests/VGGSound/video/ZXbnWlzc0ro_000540.mp4 lawn mowing +tests/VGGSound/video/ZXsQAXx_ao0_000050.mp4 male speech, man speaking +tests/VGGSound/video/bkCqeOhqCFU_000000.mp4 pheasant crowing +tests/VGGSound/video/bkFvzo2HSrU_000032.mp4 playing congas +tests/VGGSound/video/bkGy646dRjQ_000030.mp4 people whispering +tests/VGGSound/video/bkH3khklMuk_000110.mp4 airplane flyby +tests/VGGSound/video/bkIBHUh7LrE_000115.mp4 cricket chirping +tests/VGGSound/video/bkIBHUh7LrE_000126.mp4 cricket chirping +tests/VGGSound/video/ZYpeoQ6g7yY_000145.mp4 playing tympani +tests/VGGSound/video/bkgPeHxZs94_000000.mp4 metronome +tests/VGGSound/video/bkgPeHxZs94_000019.mp4 metronome +tests/VGGSound/video/bkzGHRpx5MM_000030.mp4 playing bass guitar +tests/VGGSound/video/ZZ6GRocWW38_000090.mp4 baby laughter +tests/VGGSound/video/ZZDvShjLnAE_000030.mp4 people shuffling +tests/VGGSound/video/bl5PHVntD70_000009.mp4 fly, housefly buzzing +tests/VGGSound/video/ZZO50JTetDE_000580.mp4 ambulance siren +tests/VGGSound/video/ZZ_rDlqB9YM_000207.mp4 firing muskets +tests/VGGSound/video/blRJgHaFyNM_000024.mp4 chipmunk chirping +tests/VGGSound/video/blT66g8x458_000180.mp4 ocean burbling +tests/VGGSound/video/blYYW-EUGDA_000030.mp4 playing bass guitar +tests/VGGSound/video/ZZhkohnlobs_000382.mp4 penguins braying +tests/VGGSound/video/ZZk09BLi2mU_000020.mp4 playing sitar +tests/VGGSound/video/bln5A2hopKQ_000092.mp4 playing table tennis +tests/VGGSound/video/ZZoM-leT_0U_000028.mp4 dog baying +tests/VGGSound/video/ZZoM-leT_0U_000041.mp4 dog baying +tests/VGGSound/video/bltHehYBdy8_000070.mp4 dog howling +tests/VGGSound/video/ZZx7tmufUYg_000102.mp4 running electric fan +tests/VGGSound/video/ZZzjG_Gd9t0_000056.mp4 people battle cry +tests/VGGSound/video/bm5IT7e2vvI_000120.mp4 playing marimba, xylophone +tests/VGGSound/video/bmKtI808DsU_000009.mp4 lions growling +tests/VGGSound/video/bmakSi9M2Ww_000220.mp4 cattle, bovinae cowbell +tests/VGGSound/video/bmefVbk2-lM_000114.mp4 playing djembe +tests/VGGSound/video/bn1TUcXPHfA_000223.mp4 playing bugle +tests/VGGSound/video/bnFZy6N2TS0_000327.mp4 male speech, man speaking +tests/VGGSound/video/bnQlBzGQ0Sc_000220.mp4 baby babbling +tests/VGGSound/video/bncyJqamESw_000020.mp4 people farting +tests/VGGSound/video/bnjo2Bx3_RE_000071.mp4 people humming +tests/VGGSound/video/bnlkXcONaBs_000236.mp4 playing tuning fork +tests/VGGSound/video/boPZxCznYbc_000030.mp4 crow cawing +tests/VGGSound/video/bovpIaQBYtk_000000.mp4 opening or closing car electric windows +tests/VGGSound/video/bp-XBkdA4rM_000385.mp4 people marching +tests/VGGSound/video/bpXRRH_CxJM_000140.mp4 footsteps on snow +tests/VGGSound/video/bppgcyxMKvQ_000620.mp4 child singing +tests/VGGSound/video/bpxK2ub-qCs_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/bq6C0_tAbJM_000030.mp4 helicopter +tests/VGGSound/video/bqMgL5qmZ-k_000030.mp4 playing didgeridoo +tests/VGGSound/video/bqmWNU5oLZM_000007.mp4 crow cawing +tests/VGGSound/video/bqvl7IbPteU_000030.mp4 playing electric guitar +tests/VGGSound/video/bqwHCsEztNE_000030.mp4 singing bowl +tests/VGGSound/video/brfKKehFtmw_000030.mp4 chainsawing trees +tests/VGGSound/video/brfMnl3U64M_000004.mp4 playing bongo +tests/VGGSound/video/brn460KXgfM_000079.mp4 playing hockey +tests/VGGSound/video/brpJxppIbDI_000140.mp4 chicken crowing +tests/VGGSound/video/bsHlyV39TG4_000000.mp4 basketball bounce +tests/VGGSound/video/fAns8GJzYeQ_000030.mp4 waterfall burbling +tests/VGGSound/video/fAwWq02NG5I_000034.mp4 playing badminton +tests/VGGSound/video/fB7K_IM8cQo_000036.mp4 missile launch +tests/VGGSound/video/bsi2kUrwjf8_000030.mp4 playing bass guitar +tests/VGGSound/video/fB9W0awy06E_000160.mp4 electric grinder grinding +tests/VGGSound/video/fBNRPy9yRy0_000026.mp4 squishing water +tests/VGGSound/video/fB_tldbRb28_000220.mp4 cap gun shooting +tests/VGGSound/video/bt6HajgJ9Ls_000420.mp4 people babbling +tests/VGGSound/video/fBsDFIe_TWc_000007.mp4 lighting firecrackers +tests/VGGSound/video/btzP6UEH1pI_000412.mp4 slot machine +tests/VGGSound/video/bu-zB_kmBao_000043.mp4 firing muskets +tests/VGGSound/video/bu2JMRlDl94_000150.mp4 playing french horn +tests/VGGSound/video/fCdjNwWJ5y4_000115.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/buJRhrg6l2E_000030.mp4 playing zither +tests/VGGSound/video/buOEFwXhoe0_000310.mp4 skidding +tests/VGGSound/video/fCx7XGkuLfk_000030.mp4 crow cawing +tests/VGGSound/video/fD7OpfzE87w_000089.mp4 bowling impact +tests/VGGSound/video/bv9PhRwJ9Yc_000000.mp4 bird chirping, tweeting +tests/VGGSound/video/bvsXA4ba8_4_000030.mp4 playing electronic organ +tests/VGGSound/video/fE7-2gllNvE_000230.mp4 using sewing machines +tests/VGGSound/video/fESL2PLuIwA_000140.mp4 ocean burbling +tests/VGGSound/video/fEfe8jznp5Q_000030.mp4 duck quacking +tests/VGGSound/video/fEuitN-94sg_000015.mp4 striking pool +tests/VGGSound/video/fF3u_xLxF9Q_000120.mp4 squishing water +tests/VGGSound/video/bwvpRZ11cYk_000105.mp4 cow lowing +tests/VGGSound/video/fFKL_Njts_U_000371.mp4 playing drum kit +tests/VGGSound/video/bxKdKUZP41Y_000030.mp4 playing zither +tests/VGGSound/video/fFPn4nfp0YA_000030.mp4 lawn mowing +tests/VGGSound/video/fFQmyJ39gQs_000530.mp4 people finger snapping +tests/VGGSound/video/fFSnuSjcrzw_000039.mp4 alligators, crocodiles hissing +tests/VGGSound/video/bxhcNqy0Jc8_000000.mp4 eagle screaming +tests/VGGSound/video/fFVT_CtL62M_000020.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/fFX04tOPv8s_000000.mp4 dog whimpering +tests/VGGSound/video/bxts5znycds_000012.mp4 otter growling +tests/VGGSound/video/bxts5znycds_000067.mp4 otter growling +tests/VGGSound/video/fFu6-om7EU4_000270.mp4 hair dryer drying +tests/VGGSound/video/fFucfdLwSPM_000010.mp4 people cheering +tests/VGGSound/video/fFucfdLwSPM_000042.mp4 people cheering +tests/VGGSound/video/fGLsqnEJTKk_000280.mp4 bird chirping, tweeting +tests/VGGSound/video/bydVpoBELn8_000235.mp4 mouse clicking +tests/VGGSound/video/bydY3lfv7mY_000044.mp4 people battle cry +tests/VGGSound/video/fGvhcD5G82M_000007.mp4 dog whimpering +tests/VGGSound/video/fH4p_x1ZvN0_000124.mp4 otter growling +tests/VGGSound/video/byqu6vJWCIY_000068.mp4 striking bowling +tests/VGGSound/video/byqu6vJWCIY_000513.mp4 striking bowling +tests/VGGSound/video/fHCVGpMGkrA_000097.mp4 cat purring +tests/VGGSound/video/fHD5X6Uw1Gw_000032.mp4 playing snare drum +tests/VGGSound/video/bz20Ve-c1xI_000030.mp4 cap gun shooting +tests/VGGSound/video/bzHZ7yvmVMk_000138.mp4 dinosaurs bellowing +tests/VGGSound/video/bzOeufhFITk_000030.mp4 people sniggering +tests/VGGSound/video/bzRimnuUqVc_000017.mp4 ice cream truck, ice cream van +tests/VGGSound/video/c-8SLUH5pp4_000030.mp4 playing bass guitar +tests/VGGSound/video/fIer0uCLqSM_000030.mp4 people coughing +tests/VGGSound/video/c-_S5Tt-gbw_000490.mp4 typing on typewriter +tests/VGGSound/video/fIvbiwYuQC0_000018.mp4 cuckoo bird calling +tests/VGGSound/video/c-qYpm6h0Ew_000220.mp4 driving motorcycle +tests/VGGSound/video/c-vmzVd5nsE_000014.mp4 donkey, ass braying +tests/VGGSound/video/fJEkkvr19I8_000030.mp4 people whispering +tests/VGGSound/video/c0Oe4MG96Zo_000007.mp4 smoke detector beeping +tests/VGGSound/video/fJL5Vr3ysTY_000030.mp4 sloshing water +tests/VGGSound/video/fJNauQt9Di0_000150.mp4 playing violin, fiddle +tests/VGGSound/video/fJxvIHuKPBE_000015.mp4 alligators, crocodiles hissing +tests/VGGSound/video/fK39zLd_OrM_000706.mp4 train horning +tests/VGGSound/video/c1Qp3gEj0OY_000465.mp4 squishing water +tests/VGGSound/video/fK9v-WqcoJA_000022.mp4 striking pool +tests/VGGSound/video/c1Zpqc-fISI_000015.mp4 opening or closing car doors +tests/VGGSound/video/c1dZNH8YiGU_000162.mp4 playing hockey +tests/VGGSound/video/c1klSUY4RdA_000000.mp4 underwater bubbling +tests/VGGSound/video/c1prFYuA4LM_000416.mp4 ripping paper +tests/VGGSound/video/c25HvZPRCsA_000330.mp4 playing harpsichord +tests/VGGSound/video/fL6pMyvoGVg_000024.mp4 playing glockenspiel +tests/VGGSound/video/fLD-oO3md6g_000023.mp4 planing timber +tests/VGGSound/video/fLEM7amr21o_000250.mp4 forging swords +tests/VGGSound/video/fLMDVMm1uV8_000170.mp4 bird chirping, tweeting +tests/VGGSound/video/fLNiZuKgPtM_000030.mp4 sliding door +tests/VGGSound/video/fLPEAElOWho_000137.mp4 playing bass drum +tests/VGGSound/video/fLPEAElOWho_000148.mp4 playing bass drum +tests/VGGSound/video/c2akbbdS7I4_000030.mp4 people shuffling +tests/VGGSound/video/fLZ5jPkCUOQ_000004.mp4 gibbon howling +tests/VGGSound/video/fLZ5jPkCUOQ_000014.mp4 gibbon howling +tests/VGGSound/video/c2q8tK3tOQk_000030.mp4 goose honking +tests/VGGSound/video/c3AJOT4VwSE_000510.mp4 opening or closing drawers +tests/VGGSound/video/c3Fd0b7PLz4_000198.mp4 playing hockey +tests/VGGSound/video/c3LAEOrcrrc_000150.mp4 playing steelpan +tests/VGGSound/video/c3OHPJY7nhA_000022.mp4 snake hissing +tests/VGGSound/video/c3S3FoxyI1c_000040.mp4 yodelling +tests/VGGSound/video/fMRkwcjjozw_000250.mp4 playing steelpan +tests/VGGSound/video/fMZaRGIpPIE_000035.mp4 hail +tests/VGGSound/video/fMqCV2R-PF0_000095.mp4 francolin calling +tests/VGGSound/video/c40hgtfiYm0_000010.mp4 typing on typewriter +tests/VGGSound/video/fMtJPzrUsJQ_000024.mp4 playing lacrosse +tests/VGGSound/video/fN25nqizhbU_000164.mp4 playing hockey +tests/VGGSound/video/fNNhE0Cz2QY_000000.mp4 door slamming +tests/VGGSound/video/fNWjxc5K3Gw_000051.mp4 spraying water +tests/VGGSound/video/fNgXgJZHxDE_000140.mp4 pumping water +tests/VGGSound/video/c4mDnV5pqC8_000044.mp4 playing glockenspiel +tests/VGGSound/video/fNttvad732o_000006.mp4 otter growling +tests/VGGSound/video/c4oagWg6CWI_000128.mp4 people slurping +tests/VGGSound/video/c4r8Kd6Q1n8_000008.mp4 airplane flyby +tests/VGGSound/video/c5D90N1qrD0_000030.mp4 playing didgeridoo +tests/VGGSound/video/c5HA9u6VbxM_000000.mp4 playing french horn +tests/VGGSound/video/c5Il2Mx1Wrw_000280.mp4 people running +tests/VGGSound/video/fOc6JNNdLaQ_000030.mp4 people eating +tests/VGGSound/video/c5OHWKb2Z8E_000167.mp4 car engine starting +tests/VGGSound/video/c5_FYMwxnPc_000019.mp4 sea lion barking +tests/VGGSound/video/fPAsWpYozPM_000112.mp4 chipmunk chirping +tests/VGGSound/video/c5_FYMwxnPc_000051.mp4 sea lion barking +tests/VGGSound/video/fPFpRsKbzfU_000000.mp4 owl hooting +tests/VGGSound/video/c5jByWm1IaU_000216.mp4 firing muskets +tests/VGGSound/video/fPMwOPwurKU_000010.mp4 playing vibraphone +tests/VGGSound/video/fPV1g05NMfE_000078.mp4 tap dancing +tests/VGGSound/video/fPiRBxijEok_000694.mp4 lip smacking +tests/VGGSound/video/c6VWQGFmNUE_000030.mp4 thunder +tests/VGGSound/video/fQRh2QW5RX8_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/c7IL4fDqs_I_000070.mp4 playing synthesizer +tests/VGGSound/video/c7YGJfuV_2Q_000140.mp4 police car (siren) +tests/VGGSound/video/c7xtFAL66Zg_000018.mp4 people slapping +tests/VGGSound/video/fRhLjcR1DtQ_000631.mp4 striking bowling +tests/VGGSound/video/c84MEg-AzuQ_000054.mp4 shot football +tests/VGGSound/video/fRwJFYI0K0w_000010.mp4 playing zither +tests/VGGSound/video/c8AulW4IZVs_000030.mp4 playing electronic organ +tests/VGGSound/video/fSEpr4pZviU_000108.mp4 airplane flyby +tests/VGGSound/video/c8iV3QIK574_000406.mp4 playing hockey +tests/VGGSound/video/c8j3tDbIeuk_000030.mp4 printer printing +tests/VGGSound/video/c8lfu6yJ0K4_000003.mp4 car passing by +tests/VGGSound/video/fSbFFvSeYF4_000029.mp4 ferret dooking +tests/VGGSound/video/c8uE3Q8p9Jo_000050.mp4 playing theremin +tests/VGGSound/video/fSq_FkcHCk8_000087.mp4 people humming +tests/VGGSound/video/fTGzxGJUcfw_000025.mp4 chipmunk chirping +tests/VGGSound/video/c9k4tTlQwmU_000030.mp4 firing cannon +tests/VGGSound/video/fTcSVQJ2h8g_000050.mp4 police car (siren) +tests/VGGSound/video/cADT8fUucLQ_000030.mp4 rapping +tests/VGGSound/video/cAcUuNgYYr4_000082.mp4 air horn +tests/VGGSound/video/fTxaj8RU_gE_000093.mp4 playing erhu +tests/VGGSound/video/fUA3_Ay6TSw_000030.mp4 dog whimpering +tests/VGGSound/video/fUCVZRETzvo_000003.mp4 train horning +tests/VGGSound/video/fUNXFAJ2Dcs_000013.mp4 beat boxing +tests/VGGSound/video/cBF73TX0xZk_000030.mp4 opening or closing drawers +tests/VGGSound/video/fV1gMUp83Y4_000170.mp4 stream burbling +tests/VGGSound/video/cC0FeLVsg7c_000633.mp4 playing double bass +tests/VGGSound/video/fVI4zUDeZww_000094.mp4 playing tympani +tests/VGGSound/video/cCHaRVUxi5o_000000.mp4 chinchilla barking +tests/VGGSound/video/cCVd_I1M_fs_000030.mp4 people sobbing +tests/VGGSound/video/cCliiSDuhlI_000004.mp4 woodpecker pecking tree +tests/VGGSound/video/cD7zMUwX7T4_000038.mp4 playing violin, fiddle +tests/VGGSound/video/fW6NVxZZekE_000100.mp4 playing piano +tests/VGGSound/video/fWLjGFgL-2Q_000024.mp4 sailing +tests/VGGSound/video/fWLowSAYH8s_000365.mp4 firing muskets +tests/VGGSound/video/fWVfi9pAh_4_000010.mp4 subway, metro, underground +tests/VGGSound/video/fWjgRBl7LNc_000060.mp4 playing zither +tests/VGGSound/video/cE5Yihyqup4_000070.mp4 male speech, man speaking +tests/VGGSound/video/cEEoKQ38fHY_000030.mp4 driving buses +tests/VGGSound/video/fX2Augg8Zk8_000030.mp4 ocean burbling +tests/VGGSound/video/fXGErRbyv6M_000079.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/cEjYmO5-dLk_000010.mp4 playing cello +tests/VGGSound/video/fXdrKhNxjCo_000030.mp4 fireworks banging +tests/VGGSound/video/fXe8WecFvBk_000010.mp4 thunder +tests/VGGSound/video/fYhJdb8ka3k_000030.mp4 typing on computer keyboard +tests/VGGSound/video/fYnJ1cXVezA_000179.mp4 playing double bass +tests/VGGSound/video/cG6OF9vcGPE_000081.mp4 people humming +tests/VGGSound/video/fZOzFfVl07o_000052.mp4 metronome +tests/VGGSound/video/fZS9lPmqgl0_000030.mp4 helicopter +tests/VGGSound/video/fZ_U28ayAFc_000051.mp4 cheetah chirrup +tests/VGGSound/video/cGNLoPOKZy0_000400.mp4 people booing +tests/VGGSound/video/cGUhG5PZp0A_000030.mp4 male speech, man speaking +tests/VGGSound/video/cGhQEyMT6ac_000190.mp4 stream burbling +tests/VGGSound/video/fZsd2XIqeKs_000000.mp4 playing trombone +tests/VGGSound/video/cGqbnUxMHDY_000022.mp4 canary calling +tests/VGGSound/video/fZyq2pM2-dI_000030.mp4 playing sitar +tests/VGGSound/video/cGzNyfp3mW4_000030.mp4 race car, auto racing +tests/VGGSound/video/f_8Jnw9bU64_000008.mp4 magpie calling +tests/VGGSound/video/cHAKzHAZPs0_000110.mp4 playing bugle +tests/VGGSound/video/f_cBi2vT3Qw_000002.mp4 alligators, crocodiles hissing +tests/VGGSound/video/cHm1cYBAXMI_000030.mp4 ambulance siren +tests/VGGSound/video/fa0lR26K23E_000450.mp4 playing vibraphone +tests/VGGSound/video/fa7iZnVDrJk_000000.mp4 volcano explosion +tests/VGGSound/video/cIDVqtnnsvA_000470.mp4 playing clarinet +tests/VGGSound/video/cIDiFidOMvA_000032.mp4 air horn +tests/VGGSound/video/cIFLW7R3_po_000002.mp4 cupboard opening or closing +tests/VGGSound/video/cIGTj5lSvQs_000013.mp4 black capped chickadee calling +tests/VGGSound/video/cIGTj5lSvQs_000024.mp4 black capped chickadee calling +tests/VGGSound/video/cIHmmSm947Q_000000.mp4 people finger snapping +tests/VGGSound/video/cIS8PcMk0Uw_000030.mp4 waterfall burbling +tests/VGGSound/video/fakJJOOLBhw_000083.mp4 elk bugling +tests/VGGSound/video/fakJJOOLBhw_000140.mp4 elk bugling +tests/VGGSound/video/favWHteInt0_000448.mp4 wind chime +tests/VGGSound/video/cIjZv7BPYew_000009.mp4 skiing +tests/VGGSound/video/cLMvr2qKG6Y_000050.mp4 cap gun shooting +tests/VGGSound/video/fdFk48aKQ_c_000239.mp4 people eating crisps +tests/VGGSound/video/fdOYVf1E8O4_000005.mp4 playing tennis +tests/VGGSound/video/fdadZ_KrZVw_000090.mp4 playing timpani +tests/VGGSound/video/cLi55MV04a8_000100.mp4 playing cymbal +tests/VGGSound/video/cLpDBj--as0_000008.mp4 people sneezing +tests/VGGSound/video/fdoSpr2hpIA_000121.mp4 cupboard opening or closing +tests/VGGSound/video/cLx0L_7fXnE_000051.mp4 chimpanzee pant-hooting +tests/VGGSound/video/fdxlA8UoNB0_000030.mp4 playing banjo +tests/VGGSound/video/fe3dZmkaq0Q_000070.mp4 tap dancing +tests/VGGSound/video/feC0L9MtghM_000190.mp4 playing sitar +tests/VGGSound/video/feMC18447Ec_000024.mp4 airplane flyby +tests/VGGSound/video/cM_VbOBRWK8_000000.mp4 playing harmonica +tests/VGGSound/video/ff21Bursam0_000160.mp4 cattle mooing +tests/VGGSound/video/ff68_2YIAvE_000329.mp4 striking bowling +tests/VGGSound/video/ff7CHJ9kvnk_000003.mp4 playing djembe +tests/VGGSound/video/cN5WLE0XTsE_000185.mp4 playing timbales +tests/VGGSound/video/cNNv7S3viJk_000051.mp4 airplane flyby +tests/VGGSound/video/cNPwX7nKmOs_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/fg2xsB3kWHA_000087.mp4 francolin calling +tests/VGGSound/video/cNqTAf7urnk_000254.mp4 tornado roaring +tests/VGGSound/video/fgbeeAqRWsc_000030.mp4 people eating +tests/VGGSound/video/cONmLYsDHl0_000018.mp4 people marching +tests/VGGSound/video/cOPRJb3sKCo_000106.mp4 people nose blowing +tests/VGGSound/video/fh3Hoio2oAo_000070.mp4 mosquito buzzing +tests/VGGSound/video/fh3sWiAtViA_000033.mp4 people slurping +tests/VGGSound/video/fhAAzi6MSXw_000070.mp4 cat caterwauling +tests/VGGSound/video/cOgNXgF21u4_000030.mp4 playing acoustic guitar +tests/VGGSound/video/fhKxzcGgIjM_000005.mp4 chicken clucking +tests/VGGSound/video/cP6CiaQSYxE_000023.mp4 driving snowmobile +tests/VGGSound/video/fhVy75I226w_000020.mp4 telephone bell ringing +tests/VGGSound/video/fhvDFoXRhu8_000045.mp4 spraying water +tests/VGGSound/video/cPgO0qGByu0_000010.mp4 people sneezing +tests/VGGSound/video/fiAJqNva0oA_000030.mp4 playing clarinet +tests/VGGSound/video/cPzezkikR-0_000030.mp4 mosquito buzzing +tests/VGGSound/video/cQFhIYk_dKY_000281.mp4 opening or closing car electric windows +tests/VGGSound/video/fi_Z6DdOqwU_000030.mp4 rapping +tests/VGGSound/video/ficqj4JyX4c_000098.mp4 eletric blender running +tests/VGGSound/video/cQaO6vpSGhk_000009.mp4 volcano explosion +tests/VGGSound/video/fil2wCcFeY0_000001.mp4 gibbon howling +tests/VGGSound/video/finB1G4B-Ic_000052.mp4 people nose blowing +tests/VGGSound/video/cQiVY6w90_8_000260.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/cQjxonV53eo_000022.mp4 coyote howling +tests/VGGSound/video/cQqDrbtd9Ec_000050.mp4 sharpen knife +tests/VGGSound/video/cRCeYK81z_I_000013.mp4 people eating crisps +tests/VGGSound/video/cRT5SWbyA54_000004.mp4 lions roaring +tests/VGGSound/video/cRTOP_vJihU_000273.mp4 strike lighter +tests/VGGSound/video/fjJPvFZswhg_000030.mp4 singing bowl +tests/VGGSound/video/cReLETAjLHI_000030.mp4 chainsawing trees +tests/VGGSound/video/fjWN2sQcR2s_000030.mp4 ambulance siren +tests/VGGSound/video/cRlp5v9BHeE_000011.mp4 car passing by +tests/VGGSound/video/cRmK3sTf-Ow_000065.mp4 cheetah chirrup +tests/VGGSound/video/cRvAv1Nn-WQ_000043.mp4 ferret dooking +tests/VGGSound/video/cRvAv1Nn-WQ_000085.mp4 ferret dooking +tests/VGGSound/video/fjiv34te9vc_000030.mp4 cat meowing +tests/VGGSound/video/cSAIhmcH4oY_000081.mp4 footsteps on snow +tests/VGGSound/video/fkGPfJmuElE_000042.mp4 playing glockenspiel +tests/VGGSound/video/fkGPfJmuElE_000052.mp4 playing glockenspiel +tests/VGGSound/video/fkJM0danKK4_000030.mp4 playing zither +tests/VGGSound/video/cSdSH0LQHfI_000030.mp4 ferret dooking +tests/VGGSound/video/fkgaF6Oj5Q4_000030.mp4 playing sitar +tests/VGGSound/video/cSnTCET2CsA_005584.mp4 race car, auto racing +tests/VGGSound/video/flBqK-cHE7w_000030.mp4 horse neighing +tests/VGGSound/video/flLjMZMydXc_000030.mp4 playing banjo +tests/VGGSound/video/flj3t61PIKk_000014.mp4 ferret dooking +tests/VGGSound/video/flj3t61PIKk_000024.mp4 ferret dooking +tests/VGGSound/video/cTrxMjSFgB4_000043.mp4 playing cornet +tests/VGGSound/video/fllbxiLid5c_000530.mp4 pumping water +tests/VGGSound/video/cTsXnOrhupA_000081.mp4 train whistling +tests/VGGSound/video/flzEpa8jtkI_000070.mp4 car engine idling +tests/VGGSound/video/fmSvZ3RR8YY_000380.mp4 machine gun shooting +tests/VGGSound/video/cUzDGcBVrlE_000030.mp4 playing hammond organ +tests/VGGSound/video/fn41SZiLTUQ_000083.mp4 opening or closing car electric windows +tests/VGGSound/video/fn41SZiLTUQ_000137.mp4 opening or closing car electric windows +tests/VGGSound/video/cVQsteRY8F4_000020.mp4 skidding +tests/VGGSound/video/fnCf7sDpVXo_000170.mp4 playing gong +tests/VGGSound/video/cVetDS8webU_000011.mp4 police radio chatter +tests/VGGSound/video/cVlRlVmrZyI_000015.mp4 chopping food +tests/VGGSound/video/fnj0Bhpamqo_000115.mp4 squishing water +tests/VGGSound/video/cVtLUQcdZqI_000148.mp4 shot football +tests/VGGSound/video/cVwrv5-V1gs_000016.mp4 playing trombone +tests/VGGSound/video/cVynU0KCtRc_000000.mp4 bouncing on trampoline +tests/VGGSound/video/foCxXd7nev4_000268.mp4 spraying water +tests/VGGSound/video/foMCFJxrWnE_000270.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/foQ8lV0bsb4_000013.mp4 fly, housefly buzzing +tests/VGGSound/video/foQ8lV0bsb4_000071.mp4 fly, housefly buzzing +tests/VGGSound/video/cWWzSdDG-xc_000033.mp4 sheep bleating +tests/VGGSound/video/cWZLGpaVwwE_000030.mp4 typing on computer keyboard +tests/VGGSound/video/cWskti2sCCM_000030.mp4 ambulance siren +tests/VGGSound/video/fou66e3D0VM_000013.mp4 sheep bleating +tests/VGGSound/video/fowc2nadbvE_000000.mp4 playing trumpet +tests/VGGSound/video/cX07OqOBwK8_000030.mp4 duck quacking +tests/VGGSound/video/fp86HeXZCdo_000068.mp4 fox barking +tests/VGGSound/video/fp9LFqu3LVQ_000084.mp4 strike lighter +tests/VGGSound/video/cXEJWtj2kT8_000030.mp4 playing bass guitar +tests/VGGSound/video/fpCo9vXA3EM_000112.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/cXHEvHylsHg_000230.mp4 playing harmonica +tests/VGGSound/video/fpLnClEY4IU_000000.mp4 people sniggering +tests/VGGSound/video/fpSYKbJ0TE0_000013.mp4 penguins braying +tests/VGGSound/video/cXXD34V2Lvw_000016.mp4 playing volleyball +tests/VGGSound/video/cY27F0cqnSU_000230.mp4 dog whimpering +tests/VGGSound/video/cY6KAjqmoaY_000030.mp4 turkey gobbling +tests/VGGSound/video/fqCbR15OlVM_000078.mp4 lathe spinning +tests/VGGSound/video/cYM7vTqRUJ0_000198.mp4 playing guiro +tests/VGGSound/video/cYS85XxZMuE_000120.mp4 toilet flushing +tests/VGGSound/video/fqZlpAZ4RkQ_000193.mp4 chimpanzee pant-hooting +tests/VGGSound/video/fqvUeh_JTic_000001.mp4 chinchilla barking +tests/VGGSound/video/fqvUeh_JTic_000072.mp4 chinchilla barking +tests/VGGSound/video/cZBUN4-Vu2g_000118.mp4 chipmunk chirping +tests/VGGSound/video/cZBUN4-Vu2g_000231.mp4 chipmunk chirping +tests/VGGSound/video/frCqvzJkCUQ_000053.mp4 playing tambourine +tests/VGGSound/video/cZbAbLDhtOw_000020.mp4 lawn mowing +tests/VGGSound/video/cZhfGauqj20_000030.mp4 skidding +tests/VGGSound/video/fri3IgZex_c_000184.mp4 spraying water +tests/VGGSound/video/fruUoi4bWvo_000018.mp4 air horn +tests/VGGSound/video/c_PsOVPaW4w_000001.mp4 donkey, ass braying +tests/VGGSound/video/c_PsOVPaW4w_000059.mp4 donkey, ass braying +tests/VGGSound/video/fsHgHsYyJbs_000030.mp4 playing bass guitar +tests/VGGSound/video/fsJdW_6HePY_000080.mp4 playing tennis +tests/VGGSound/video/fsXfBoNcLeM_000030.mp4 rapping +tests/VGGSound/video/c_lsE2w0HQA_000006.mp4 smoke detector beeping +tests/VGGSound/video/c_xLtBGQbAg_000040.mp4 people eating noodle +tests/VGGSound/video/ca-rGWC4xPc_000030.mp4 playing ukulele +tests/VGGSound/video/ca9cb9AGvi4_000030.mp4 people farting +tests/VGGSound/video/ftVOFLwSxCg_000022.mp4 dinosaurs bellowing +tests/VGGSound/video/caI1iADQPVA_000130.mp4 toilet flushing +tests/VGGSound/video/caYu_xoFeF4_000040.mp4 playing tabla +tests/VGGSound/video/cagBxHqLuKA_000011.mp4 playing trumpet +tests/VGGSound/video/ftxxMmqrYQ8_000003.mp4 snake rattling +tests/VGGSound/video/cb2348GeL-8_000172.mp4 playing ukulele +tests/VGGSound/video/fuEoJnJwm4M_000000.mp4 thunder +tests/VGGSound/video/fuHTeKmz5vw_000530.mp4 playing tabla +tests/VGGSound/video/fuKUA573aPQ_000040.mp4 chicken crowing +tests/VGGSound/video/fuUWloQVZD8_000040.mp4 playing clarinet +tests/VGGSound/video/cbUYhlymUfc_000020.mp4 dog whimpering +tests/VGGSound/video/cbXK-IMJHtk_000015.mp4 sloshing water +tests/VGGSound/video/fujIcWQsUhE_000001.mp4 eagle screaming +tests/VGGSound/video/cbieKCgNvvU_000200.mp4 playing flute +tests/VGGSound/video/fumA4irXnyQ_000030.mp4 fire crackling +tests/VGGSound/video/cbmaM2VhdAU_000030.mp4 goose honking +tests/VGGSound/video/fuwbfvaUMAw_000211.mp4 playing badminton +tests/VGGSound/video/cbq6Q2htPRM_000030.mp4 rapping +tests/VGGSound/video/cdusG_Hpa9g_000090.mp4 people whistling +tests/VGGSound/video/ce6gtnd6qDc_000440.mp4 playing tabla +tests/VGGSound/video/ce9zi0YdC00_000205.mp4 swimming +tests/VGGSound/video/ceJxRCjUEWk_000158.mp4 sheep bleating +tests/VGGSound/video/fx3uAv4YGZM_000130.mp4 playing steelpan +tests/VGGSound/video/fxFdyngJSb0_000237.mp4 arc welding +tests/VGGSound/video/ceYRr2xK3XI_000018.mp4 playing cornet +tests/VGGSound/video/ce_9wpa4mQw_000066.mp4 sheep bleating +tests/VGGSound/video/ce_9wpa4mQw_000230.mp4 sheep bleating +tests/VGGSound/video/fxJCUa4gihw_000211.mp4 hammering nails +tests/VGGSound/video/cef972vNfUE_000030.mp4 people whispering +tests/VGGSound/video/fxRqbj5xiRg_000029.mp4 playing tympani +tests/VGGSound/video/fxUSMBlLOso_000012.mp4 train wheels squealing +tests/VGGSound/video/fy8xJQ3gXRU_000000.mp4 playing tuning fork +tests/VGGSound/video/fyM-gTgZeM8_000456.mp4 running electric fan +tests/VGGSound/video/fybJWy6rywA_000089.mp4 alarm clock ringing +tests/VGGSound/video/cfi_mCKjbyw_000040.mp4 people belly laughing +tests/VGGSound/video/fymM6VcMwoI_000183.mp4 chopping food +tests/VGGSound/video/cfsOIuZ9G9k_000052.mp4 playing bongo +tests/VGGSound/video/cg25DwGFBpw_000165.mp4 playing snare drum +tests/VGGSound/video/cgLHn7xt_GY_000130.mp4 bird wings flapping +tests/VGGSound/video/fzFpEjzWgSI_000296.mp4 train whistling +tests/VGGSound/video/fzG0Ntou1sc_000081.mp4 playing tennis +tests/VGGSound/video/fzOqjKHcx0w_000229.mp4 playing tympani +tests/VGGSound/video/ch4uegReLhc_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/ch71KS9DYec_000030.mp4 metronome +tests/VGGSound/video/ch95AXuMsM0_000001.mp4 people nose blowing +tests/VGGSound/video/fzjl3I47rFQ_000077.mp4 hail +tests/VGGSound/video/fzlYfY5A5sM_000250.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/chP180PR-9g_000041.mp4 cat growling +tests/VGGSound/video/g-9SK0or81c_000030.mp4 playing synthesizer +tests/VGGSound/video/g-FzdV9ZTJQ_000018.mp4 cat hissing +tests/VGGSound/video/g-IjfDszLvY_000030.mp4 duck quacking +tests/VGGSound/video/g-ZGr5uUJO8_000030.mp4 helicopter +tests/VGGSound/video/chjb1YwdgS4_000250.mp4 cap gun shooting 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+tests/VGGSound/video/cj3VU7koYZg_000030.mp4 chopping food +tests/VGGSound/video/g1A_nijCVqs_000169.mp4 race car, auto racing +tests/VGGSound/video/g1B7AXhFQ1I_000060.mp4 slot machine +tests/VGGSound/video/g1D25N2Q0fI_000250.mp4 machine gun shooting +tests/VGGSound/video/g1DRqWpcyrk_000079.mp4 plastic bottle crushing +tests/VGGSound/video/g1Mn4tB463U_000160.mp4 playing djembe +tests/VGGSound/video/cjSTp2d8mBI_000291.mp4 sea waves +tests/VGGSound/video/cjSTp2d8mBI_000459.mp4 sea waves +tests/VGGSound/video/g1P3w8kwGN0_000070.mp4 wind chime +tests/VGGSound/video/cjkEA5qjNJo_000210.mp4 francolin calling +tests/VGGSound/video/g247CEZ9p70_000010.mp4 people whistling +tests/VGGSound/video/g27CnmPRgdI_000031.mp4 woodpecker pecking tree +tests/VGGSound/video/g295Y8wuo7w_000024.mp4 playing trumpet +tests/VGGSound/video/ck13el7VmW8_000009.mp4 sea waves +tests/VGGSound/video/ck5S__5JJvE_000005.mp4 bull bellowing +tests/VGGSound/video/g2LJ1i7222c_000030.mp4 typing on typewriter +tests/VGGSound/video/ckIK43SCbkw_000036.mp4 alligators, crocodiles hissing +tests/VGGSound/video/ckNV5Oos3ac_000109.mp4 playing darts +tests/VGGSound/video/g2at4AqJsqk_000142.mp4 dog growling +tests/VGGSound/video/ckpj7O0Et28_000180.mp4 door slamming +tests/VGGSound/video/cku_hmDB0T8_000943.mp4 forging swords +tests/VGGSound/video/ckzLHmauwI8_000030.mp4 chainsawing trees +tests/VGGSound/video/g3DCGCibPQw_000020.mp4 people belly laughing +tests/VGGSound/video/g3J2VYx8zYE_000060.mp4 train whistling +tests/VGGSound/video/g3JUdaGVCLk_000030.mp4 goat bleating +tests/VGGSound/video/g3bUrhq5Vpw_000296.mp4 people gargling +tests/VGGSound/video/g3bUrhq5Vpw_000394.mp4 people gargling +tests/VGGSound/video/g3eW5ca-DKw_000030.mp4 raining +tests/VGGSound/video/g3kkGbxwSLQ_000030.mp4 typing on computer keyboard +tests/VGGSound/video/g42ZMJZWuvE_000198.mp4 people humming +tests/VGGSound/video/g4E8Tl7dEs8_000338.mp4 playing snare drum +tests/VGGSound/video/cm62raVagEE_000060.mp4 playing timpani +tests/VGGSound/video/cmB8l4mQ1XQ_000030.mp4 playing accordion +tests/VGGSound/video/g4xhZgKwiNo_000030.mp4 playing acoustic guitar +tests/VGGSound/video/g5FVJveyyVM_000030.mp4 lions roaring +tests/VGGSound/video/cocA3THl4S0_000040.mp4 eagle screaming +tests/VGGSound/video/cocA3THl4S0_000057.mp4 eagle screaming +tests/VGGSound/video/codJp5NQYy0_000000.mp4 dog growling +tests/VGGSound/video/g6FX9VjYD-w_000030.mp4 bird squawking +tests/VGGSound/video/g6GSkrfyK2E_000010.mp4 stream burbling +tests/VGGSound/video/cor2HckYTE8_000000.mp4 playing synthesizer +tests/VGGSound/video/corrUpd5ENc_000230.mp4 people eating noodle +tests/VGGSound/video/cp8t27oT_ww_000000.mp4 playing ukulele +tests/VGGSound/video/cpGLTc_21MA_000320.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/cpLm-Yaay2k_000018.mp4 donkey, ass braying +tests/VGGSound/video/cpUEWtVa8PQ_000045.mp4 beat boxing +tests/VGGSound/video/cpjQzfkXoeA_000030.mp4 ocean burbling +tests/VGGSound/video/cpxofMBzU8g_000181.mp4 canary calling +tests/VGGSound/video/cq5rnI5NauM_000252.mp4 missile launch +tests/VGGSound/video/g7bhQwjUSq0_000080.mp4 bird chirping, tweeting +tests/VGGSound/video/cqCnU2AqzPA_000030.mp4 people eating +tests/VGGSound/video/cqMfCSUQ8zs_000030.mp4 sloshing water +tests/VGGSound/video/g7lFa-fTWpM_000000.mp4 playing flute +tests/VGGSound/video/cqalBFm19UA_000221.mp4 tractor digging +tests/VGGSound/video/g87FgSOzbvo_000023.mp4 playing trumpet +tests/VGGSound/video/g8ATSr0C6K8_000013.mp4 bull bellowing +tests/VGGSound/video/g8E6gteawKY_000030.mp4 people shuffling +tests/VGGSound/video/g8USMvt9np0_000010.mp4 playing vibraphone +tests/VGGSound/video/crS5cwurdfY_000160.mp4 lawn mowing +tests/VGGSound/video/g8jDz8UVMH8_000030.mp4 tornado roaring +tests/VGGSound/video/crToMuDxmL8_000050.mp4 playing banjo +tests/VGGSound/video/g9MeGil2Kys_000057.mp4 ice cracking +tests/VGGSound/video/g9Qah25_yH0_000014.mp4 baby crying +tests/VGGSound/video/g9q3jv6SpTA_000160.mp4 people humming +tests/VGGSound/video/cscwHKeJ9n4_000000.mp4 playing violin, fiddle +tests/VGGSound/video/gA4PlwSKj8A_000039.mp4 dinosaurs bellowing +tests/VGGSound/video/gA9Nmsj3j1M_000013.mp4 stream burbling +tests/VGGSound/video/gAAaCdIv_Jg_000179.mp4 sharpen knife +tests/VGGSound/video/csl70KUkeKI_000017.mp4 lighting firecrackers +tests/VGGSound/video/gA_MFQncHyc_000012.mp4 sheep bleating +tests/VGGSound/video/gAflXwf_Jpw_000066.mp4 cuckoo bird calling +tests/VGGSound/video/gAqXWyyk1BE_000030.mp4 people eating +tests/VGGSound/video/gB1ytjgpcW4_000190.mp4 people screaming +tests/VGGSound/video/gBHlKMGENc0_000551.mp4 people slurping +tests/VGGSound/video/gBRTGtmHZW0_000154.mp4 slot machine +tests/VGGSound/video/cuINEhfQW98_000109.mp4 ice cracking +tests/VGGSound/video/cuINEhfQW98_000289.mp4 ice cracking +tests/VGGSound/video/gBq3ufewetU_000405.mp4 writing on blackboard with chalk +tests/VGGSound/video/gBq3ufewetU_000420.mp4 writing on blackboard with chalk +tests/VGGSound/video/gCAWIBbcGJA_000243.mp4 playing washboard +tests/VGGSound/video/gCHF0oBPZv8_000030.mp4 dog howling +tests/VGGSound/video/culudqMRJM4_000503.mp4 people eating crisps +tests/VGGSound/video/cur9zG87bAQ_000004.mp4 baby laughter +tests/VGGSound/video/cv901tRE0rQ_000030.mp4 cat caterwauling +tests/VGGSound/video/cvOFGQE9qCA_000040.mp4 mosquito buzzing +tests/VGGSound/video/gCnOTL_Fzik_000210.mp4 ambulance siren +tests/VGGSound/video/cvyER04xhA0_000112.mp4 playing darts +tests/VGGSound/video/cw9_3bI1Kv8_000081.mp4 ice cracking +tests/VGGSound/video/cwhLkH1Ie-4_000235.mp4 hedge trimmer running +tests/VGGSound/video/cwq3iq632ys_000030.mp4 singing choir +tests/VGGSound/video/gE-0JxMtUh0_000020.mp4 people screaming +tests/VGGSound/video/gE-sdOo_bck_000000.mp4 people sobbing +tests/VGGSound/video/cwzG9KvA--Y_000006.mp4 air conditioning noise +tests/VGGSound/video/gEBm_DYH-xA_000030.mp4 dog whimpering +tests/VGGSound/video/gEbqh2WEfKU_000156.mp4 train horning +tests/VGGSound/video/cxkCPSXyT-Y_000020.mp4 turkey gobbling +tests/VGGSound/video/cxw91PSTRq8_000120.mp4 machine gun shooting +tests/VGGSound/video/cy7yYRlsmwA_000030.mp4 raining +tests/VGGSound/video/cy8lehO7nqg_000030.mp4 mouse squeaking +tests/VGGSound/video/gEvCUcZ6w88_000030.mp4 female speech, woman speaking +tests/VGGSound/video/cyHNChAtP5g_000010.mp4 cuckoo bird calling +tests/VGGSound/video/gF5gfblw13c_000370.mp4 people babbling +tests/VGGSound/video/cyZ9arOPVb8_000030.mp4 goat bleating +tests/VGGSound/video/gFJjYWXeBn0_000030.mp4 skidding +tests/VGGSound/video/gFOOUbMXsqc_000028.mp4 chimpanzee pant-hooting +tests/VGGSound/video/gF_94kA99HY_000032.mp4 underwater bubbling +tests/VGGSound/video/gFs6lRAQsLg_000160.mp4 people whispering +tests/VGGSound/video/d-1th_S4J0U_000000.mp4 people belly laughing +tests/VGGSound/video/d-4OPdDD7WQ_000026.mp4 telephone bell ringing +tests/VGGSound/video/gGhgsrlwkaw_000069.mp4 people whistling +tests/VGGSound/video/gGmWm1i6pVo_000030.mp4 driving motorcycle +tests/VGGSound/video/gGmvLozUXgE_000024.mp4 ice cream truck, ice cream van +tests/VGGSound/video/d-agvXRvcMQ_000089.mp4 beat boxing +tests/VGGSound/video/d-m8eXCpeDg_000030.mp4 driving motorcycle +tests/VGGSound/video/d-qCd8Src3E_000072.mp4 striking pool +tests/VGGSound/video/d-qCd8Src3E_000839.mp4 striking pool +tests/VGGSound/video/d02plYWj5mE_000098.mp4 playing darts +tests/VGGSound/video/d0Uz_RnRV88_000460.mp4 playing acoustic guitar +tests/VGGSound/video/d0a5UlkfV2g_000264.mp4 underwater bubbling +tests/VGGSound/video/d0sfQ41wx6c_000300.mp4 playing tabla +tests/VGGSound/video/gIODEFkvjTA_000030.mp4 playing zither +tests/VGGSound/video/d16xAFjwcVw_000020.mp4 people finger snapping +tests/VGGSound/video/gIZ9kKdx8ho_000149.mp4 playing badminton +tests/VGGSound/video/d1QQRXy2pTM_000006.mp4 cat hissing +tests/VGGSound/video/d1VB1vA-UsI_000220.mp4 playing didgeridoo +tests/VGGSound/video/gItGfthUf8E_000203.mp4 playing bass drum +tests/VGGSound/video/d1oaZO31t4o_000015.mp4 playing glockenspiel +tests/VGGSound/video/gJ1EjXFq5vQ_000410.mp4 people whistling +tests/VGGSound/video/d203T66G1lk_000093.mp4 rope skipping +tests/VGGSound/video/d2g3eW0EoNM_000001.mp4 chinchilla barking +tests/VGGSound/video/d2nT1ZwZiZw_000051.mp4 opening or closing car electric windows +tests/VGGSound/video/d2wSzdo88gA_000340.mp4 using sewing machines +tests/VGGSound/video/gJxlJNXizr4_000011.mp4 dinosaurs bellowing +tests/VGGSound/video/d2yDN-nN2k0_000040.mp4 cattle, bovinae cowbell +tests/VGGSound/video/d2yLX6TwS_c_000030.mp4 dog barking +tests/VGGSound/video/gJydcG-d1cs_000000.mp4 playing flute +tests/VGGSound/video/gKCdntEVJVU_000011.mp4 playing tennis +tests/VGGSound/video/d352jaSSiFw_000030.mp4 duck quacking +tests/VGGSound/video/gKZrAlTJURs_000030.mp4 cattle mooing +tests/VGGSound/video/d3eq6JLipyk_000270.mp4 raining +tests/VGGSound/video/d3gMwtMK6Gs_000030.mp4 skidding +tests/VGGSound/video/d3gUXsTbmQQ_000038.mp4 zebra braying +tests/VGGSound/video/gLP4QkflB-o_000020.mp4 people farting +tests/VGGSound/video/gLPkzyEy--c_000876.mp4 people eating apple +tests/VGGSound/video/d4C6qujTJtc_000031.mp4 ferret dooking +tests/VGGSound/video/gLSoyIcevss_000030.mp4 playing violin, fiddle +tests/VGGSound/video/d4G_b-s_Odw_000030.mp4 people burping +tests/VGGSound/video/gLifHKl6khE_000034.mp4 wood thrush calling +tests/VGGSound/video/gLo62wS-sbc_000184.mp4 forging swords +tests/VGGSound/video/d4riR8ZeH9k_000040.mp4 eagle screaming +tests/VGGSound/video/gM1DIbory6A_000120.mp4 wind noise +tests/VGGSound/video/gM5DTduPHZA_000254.mp4 people eating apple +tests/VGGSound/video/gMBz6lX9HNQ_000202.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/gMDf19Ad_qA_000058.mp4 people belly laughing +tests/VGGSound/video/gMaUQCIYVSY_000450.mp4 bird squawking +tests/VGGSound/video/gMvxkbFe2M4_000019.mp4 canary calling +tests/VGGSound/video/d5qR0aff0Kk_000030.mp4 turkey gobbling +tests/VGGSound/video/gMwbOxrQP9Q_000030.mp4 lions roaring +tests/VGGSound/video/gNmZoBiNLzU_000180.mp4 playing accordion +tests/VGGSound/video/gNx6DV8EcF8_000107.mp4 airplane flyby +tests/VGGSound/video/gNywrPYiLCM_000162.mp4 hammering nails +tests/VGGSound/video/d6np1zhRar0_000240.mp4 playing saxophone +tests/VGGSound/video/d6u0HKvr_cw_000342.mp4 cheetah chirrup +tests/VGGSound/video/d6ubqBBBiYY_000030.mp4 people eating +tests/VGGSound/video/d7-vdIhBo6c_000011.mp4 volcano explosion +tests/VGGSound/video/gOIOGyPfy0c_000003.mp4 tractor digging +tests/VGGSound/video/d75jRtnpIa8_000010.mp4 bird wings flapping +tests/VGGSound/video/d7I4Z5t8Xdo_000110.mp4 wind noise +tests/VGGSound/video/d7Xf7brOPzw_000149.mp4 cat caterwauling +tests/VGGSound/video/gPE8O7DU7ns_000128.mp4 playing volleyball +tests/VGGSound/video/d8LvZQyYZpQ_000010.mp4 canary calling +tests/VGGSound/video/gPaoJv-NrEU_000030.mp4 people clapping +tests/VGGSound/video/gPekns88rQA_000270.mp4 cattle, bovinae cowbell +tests/VGGSound/video/d8bhrEHxJsA_000344.mp4 lathe spinning +tests/VGGSound/video/d8hPjmvBv5I_000251.mp4 disc scratching +tests/VGGSound/video/d8ya35A6yzk_000075.mp4 airplane flyby +tests/VGGSound/video/gPw-sP3px30_000002.mp4 wind chime +tests/VGGSound/video/gPw-sP3px30_000208.mp4 wind chime +tests/VGGSound/video/gQKWGk5HBcs_000220.mp4 child singing +tests/VGGSound/video/gQSjOkhrDf0_000434.mp4 race car, auto racing +tests/VGGSound/video/gQUhn5sq5rs_000009.mp4 lions growling +tests/VGGSound/video/gQXJt2cE-8c_000070.mp4 orchestra +tests/VGGSound/video/gQby3qzwwQw_000120.mp4 turkey gobbling +tests/VGGSound/video/gR1wqInzmyY_000153.mp4 roller coaster running +tests/VGGSound/video/gRDt262JpQQ_000080.mp4 car engine knocking +tests/VGGSound/video/gRSJoFczYEo_000030.mp4 door slamming +tests/VGGSound/video/dAqJBtqmijc_000005.mp4 chinchilla barking +tests/VGGSound/video/gS-JeQ0dbTQ_000400.mp4 playing tabla +tests/VGGSound/video/gS7sZgzT7_k_000020.mp4 cat purring +tests/VGGSound/video/dBSRk9afGgE_000035.mp4 chinchilla barking +tests/VGGSound/video/dBeRmZn2qCE_000030.mp4 people farting +tests/VGGSound/video/dBl76lmp-d0_000035.mp4 dog growling +tests/VGGSound/video/dBxAjOGP6os_000069.mp4 cuckoo bird calling +tests/VGGSound/video/dC1TVxwiitc_000030.mp4 race car, auto racing +tests/VGGSound/video/gT1HfA-JhYc_000129.mp4 playing erhu +tests/VGGSound/video/dCMSLNyb8OA_000040.mp4 cupboard opening or closing +tests/VGGSound/video/gTFCK9TuLOQ_000023.mp4 train whistling +tests/VGGSound/video/dCcCTlI_neI_000722.mp4 lip smacking +tests/VGGSound/video/gTUu9V5zAME_000078.mp4 playing shofar +tests/VGGSound/video/gTXz4thnsYQ_000100.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/gTylPieYBcI_000125.mp4 fox barking +tests/VGGSound/video/gTylPieYBcI_000384.mp4 fox barking +tests/VGGSound/video/gUNC_cONok8_000060.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/dEArsn030N4_000001.mp4 cuckoo bird calling +tests/VGGSound/video/gUZOZP-sgng_000330.mp4 typing on computer keyboard +tests/VGGSound/video/dEKMvDkP41A_000015.mp4 volcano explosion +tests/VGGSound/video/gUxQ5nOqusk_000291.mp4 mouse clicking +tests/VGGSound/video/dEZKBTNubi8_000365.mp4 whale calling +tests/VGGSound/video/dEalicSMdE8_000155.mp4 yodelling +tests/VGGSound/video/dEalkJ7fbY4_000049.mp4 train whistling +tests/VGGSound/video/gVDOQ2ke0bQ_000174.mp4 barn swallow calling +tests/VGGSound/video/dEsYWbxla08_000030.mp4 people whispering +tests/VGGSound/video/dEuEtrdRX9o_000030.mp4 playing zither +tests/VGGSound/video/gVW13w2fXh8_000030.mp4 female speech, woman speaking +tests/VGGSound/video/gVWLvp-ZpEU_000134.mp4 playing erhu +tests/VGGSound/video/gVhRQtMGmoM_000099.mp4 shot football +tests/VGGSound/video/dF4XD6bFsWY_000290.mp4 cap gun shooting +tests/VGGSound/video/gVn7YEKnq0I_000013.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/dFGvNxBqYFI_000030.mp4 playing didgeridoo +tests/VGGSound/video/dFKYXLU3hWg_000098.mp4 police car (siren) +tests/VGGSound/video/dFM6UIayPtQ_000026.mp4 coyote howling +tests/VGGSound/video/dFZ5xSbP8f8_000073.mp4 police radio chatter +tests/VGGSound/video/dFcVaitADW8_000130.mp4 playing hammond organ +tests/VGGSound/video/dFiGYIa6wfY_000000.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/gWSppirU_18_000000.mp4 playing tambourine +tests/VGGSound/video/gWU-e1qUrls_000030.mp4 car engine knocking +tests/VGGSound/video/gWUiWpxDBH0_000000.mp4 baltimore oriole calling +tests/VGGSound/video/gWgWw9oYDcw_000000.mp4 horse neighing +tests/VGGSound/video/dG7RFy7mAyY_000030.mp4 dog whimpering +tests/VGGSound/video/dGD-Y3XEHgI_000010.mp4 playing tambourine +tests/VGGSound/video/dGLGY5zeLSM_000030.mp4 pig oinking +tests/VGGSound/video/gX-HTzpXCkU_000178.mp4 chopping wood +tests/VGGSound/video/gXDltX0l33E_000005.mp4 chimpanzee pant-hooting +tests/VGGSound/video/dGnbCweP0pI_000162.mp4 opening or closing car doors +tests/VGGSound/video/dHM1QdoRmiU_000030.mp4 firing cannon +tests/VGGSound/video/gXpT8TZjAnI_000030.mp4 people sniggering +tests/VGGSound/video/dHZcD20flqY_000153.mp4 chopping food +tests/VGGSound/video/dHebN5DsE2g_000006.mp4 wood thrush calling +tests/VGGSound/video/dI3xU5LXeoE_000081.mp4 train whistling +tests/VGGSound/video/gYtyV6CyBko_000030.mp4 mouse squeaking +tests/VGGSound/video/dIIiaO12I5Q_000006.mp4 baby crying +tests/VGGSound/video/gYw7UgO2usI_000030.mp4 playing harpsichord +tests/VGGSound/video/gYxWz9JAbjE_000048.mp4 slot machine +tests/VGGSound/video/gZ4u6eUJxV4_000371.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/gZ7snULupqE_000000.mp4 playing didgeridoo +tests/VGGSound/video/dIloYYVJIO4_000000.mp4 sheep bleating +tests/VGGSound/video/dIloYYVJIO4_000124.mp4 sheep bleating +tests/VGGSound/video/gZX50sNGgwE_000010.mp4 car engine starting +tests/VGGSound/video/gZbqznxxrbE_000367.mp4 airplane +tests/VGGSound/video/dIxfiXWmRJE_000260.mp4 people hiccup +tests/VGGSound/video/dIy0sMn4HsY_000001.mp4 lathe spinning +tests/VGGSound/video/dIzQVYDYtKA_000008.mp4 tap dancing +tests/VGGSound/video/dIzQVYDYtKA_000085.mp4 tap dancing +tests/VGGSound/video/g_DBLppDZAs_000030.mp4 police car (siren) +tests/VGGSound/video/g_EQ7Ir1d_0_000000.mp4 gibbon howling +tests/VGGSound/video/g_H9ViHZ8PA_000045.mp4 chimpanzee pant-hooting +tests/VGGSound/video/g_gGgzxln3k_000150.mp4 gibbon howling +tests/VGGSound/video/g_p6sqfaXHM_000110.mp4 bird chirping, tweeting +tests/VGGSound/video/g_xHi_VQRRg_000100.mp4 mouse pattering +tests/VGGSound/video/dKC0F_5tdsU_000005.mp4 whale calling +tests/VGGSound/video/ga6Q5sJLaqU_000030.mp4 people burping +tests/VGGSound/video/gaFQgJLQHtU_000090.mp4 car engine starting +tests/VGGSound/video/gaHt8mT4u9U_000030.mp4 canary calling +tests/VGGSound/video/dKRodtrybvM_000027.mp4 cat growling +tests/VGGSound/video/gaZ7NCQwmlE_000000.mp4 playing piano +tests/VGGSound/video/dKmLgjd8rks_000021.mp4 church bell ringing +tests/VGGSound/video/garZ8KkuBds_000220.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/dL8HIuBPZV4_000000.mp4 sheep bleating +tests/VGGSound/video/dL8HIuBPZV4_000016.mp4 sheep bleating +tests/VGGSound/video/gbX-3uq95X0_000030.mp4 car engine knocking +tests/VGGSound/video/dLLRg0sur6g_000060.mp4 striking bowling +tests/VGGSound/video/dLRlnhW9_Pc_000070.mp4 machine gun shooting +tests/VGGSound/video/dLWfam3rWy0_000052.mp4 writing on blackboard with chalk +tests/VGGSound/video/dLZEZTNhFwM_000032.mp4 bull bellowing +tests/VGGSound/video/gc9Ceh4ltaE_000030.mp4 pumping water +tests/VGGSound/video/dMAp3dvs3kE_000170.mp4 male singing +tests/VGGSound/video/dMDeKRA1Qm4_000054.mp4 eagle screaming +tests/VGGSound/video/dMQANiWPPME_000030.mp4 sailing +tests/VGGSound/video/dMS5TJzMTfs_000081.mp4 people giggling +tests/VGGSound/video/dMW3YcQPPhk_000412.mp4 people eating crisps +tests/VGGSound/video/gcWV2rYemQo_000011.mp4 sloshing water +tests/VGGSound/video/dMzQiu2mUlE_000030.mp4 playing bagpipes +tests/VGGSound/video/gcyPMu7k1LM_000184.mp4 playing timbales +tests/VGGSound/video/gd2-qjVH_DI_000020.mp4 playing timbales +tests/VGGSound/video/dN7HHeTZ44Y_000096.mp4 rope skipping +tests/VGGSound/video/gd2-qjVH_DI_000032.mp4 playing timbales +tests/VGGSound/video/dN7ZWYBJeUE_000040.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/gd77_8KaHc8_000000.mp4 pig oinking +tests/VGGSound/video/dNH6plDW4mo_000297.mp4 playing bongo +tests/VGGSound/video/dNK9bD3LNCc_000060.mp4 playing banjo +tests/VGGSound/video/gdR6nuDBghI_000134.mp4 magpie calling +tests/VGGSound/video/dNNoEFMJ_94_000000.mp4 firing muskets +tests/VGGSound/video/dNdmkIq2h5Q_000011.mp4 cow lowing +tests/VGGSound/video/gdrXDL_exmA_000326.mp4 skiing +tests/VGGSound/video/ge191yHHQio_000030.mp4 playing harpsichord +tests/VGGSound/video/ge3cIE2a9yU_000574.mp4 ripping paper +tests/VGGSound/video/dOQfuOw6okA_000381.mp4 airplane +tests/VGGSound/video/gedTn4z7wd4_000181.mp4 hedge trimmer running +tests/VGGSound/video/gefp9ta8LTA_000030.mp4 playing accordion +tests/VGGSound/video/dP2M0N8a-64_000250.mp4 cap gun shooting +tests/VGGSound/video/dP6opIF4AEA_000350.mp4 cricket chirping +tests/VGGSound/video/gf1y74QzhTI_000030.mp4 dog growling +tests/VGGSound/video/dPM24O4my-Q_000000.mp4 skidding +tests/VGGSound/video/gfCl8WGI9qQ_000037.mp4 people eating noodle +tests/VGGSound/video/gfFpHArBxQU_000030.mp4 playing hammond organ +tests/VGGSound/video/gfT6IacNjJ0_000031.mp4 tornado roaring +tests/VGGSound/video/dPcgzRPF_yA_000031.mp4 planing timber +tests/VGGSound/video/gfVNNXPbkW8_000030.mp4 goose honking +tests/VGGSound/video/dPcgzRPF_yA_000484.mp4 planing timber +tests/VGGSound/video/gflvYpShFzo_000001.mp4 playing tuning fork +tests/VGGSound/video/gg6yoeBoYxg_000000.mp4 children shouting +tests/VGGSound/video/dQVMQyrIxEo_000010.mp4 people burping +tests/VGGSound/video/dQcXyoJFASE_000308.mp4 playing lacrosse +tests/VGGSound/video/dQfQGU2qF2w_000117.mp4 people gargling +tests/VGGSound/video/dQpqPwiKva0_000054.mp4 yodelling +tests/VGGSound/video/dQv6_xbhRss_000110.mp4 disc scratching +tests/VGGSound/video/dR3KEENsVbs_000000.mp4 playing marimba, xylophone +tests/VGGSound/video/gg_wdPHtU7Y_000001.mp4 hair dryer drying +tests/VGGSound/video/ggb93ZYIeaA_000082.mp4 mynah bird singing +tests/VGGSound/video/ggjbkDEZKXQ_000090.mp4 wood thrush calling +tests/VGGSound/video/gh4oE_5g4YY_000439.mp4 people slurping +tests/VGGSound/video/ghOfjHwwA-o_000223.mp4 playing tennis +tests/VGGSound/video/ghRyW0bkt8c_000105.mp4 smoke detector beeping +tests/VGGSound/video/dS0NCJkkj0E_000283.mp4 playing erhu +tests/VGGSound/video/giATGEw8nAk_000107.mp4 police radio chatter +tests/VGGSound/video/gigAXFw9yzQ_000223.mp4 police radio chatter +tests/VGGSound/video/dSzZWgbJ378_000030.mp4 train horning +tests/VGGSound/video/gihNVuDY-OQ_000127.mp4 playing congas +tests/VGGSound/video/dT4dvRrlBL0_000272.mp4 ice cracking +tests/VGGSound/video/dT4dvRrlBL0_000321.mp4 ice cracking +tests/VGGSound/video/dTV7UbA_QB8_000003.mp4 whale calling +tests/VGGSound/video/gj57rI1_JX8_000030.mp4 crow cawing +tests/VGGSound/video/dTlAkkMLPDg_000030.mp4 playing marimba, xylophone +tests/VGGSound/video/dU5GJkZ2Ltw_000044.mp4 parrot talking +tests/VGGSound/video/gkH_Zxasn8o_000040.mp4 subway, metro, underground +tests/VGGSound/video/dUjpH8UAycU_000012.mp4 goat bleating +tests/VGGSound/video/gkIENhK7fxg_000020.mp4 cattle, bovinae cowbell +tests/VGGSound/video/dUoUDZYKBzM_000167.mp4 magpie calling +tests/VGGSound/video/gkaTHw410NA_000011.mp4 playing cornet +tests/VGGSound/video/dV9YwT62U_g_000030.mp4 people shuffling +tests/VGGSound/video/gklbB7TYoK4_000030.mp4 baby laughter +tests/VGGSound/video/gksGyZQWxgw_000090.mp4 printer printing +tests/VGGSound/video/dVYjJc2KdnY_000090.mp4 frog croaking +tests/VGGSound/video/dV_7-zHqOfs_000040.mp4 black capped chickadee calling +tests/VGGSound/video/gl9j63Ln1y4_000144.mp4 people eating noodle +tests/VGGSound/video/glAxzomb7ws_000030.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/dVll2c5zbN0_000002.mp4 warbler chirping +tests/VGGSound/video/glLQrEijrKg_000300.mp4 playing hammond organ +tests/VGGSound/video/glLssX4biLE_000094.mp4 playing washboard +tests/VGGSound/video/dW-rmWpBj88_000520.mp4 people shuffling +tests/VGGSound/video/dWM_a65_MrQ_000054.mp4 playing table tennis +tests/VGGSound/video/dWRS0q8d2tw_000030.mp4 sliding door +tests/VGGSound/video/gm7VuxbyNkw_000772.mp4 ripping paper +tests/VGGSound/video/gm7VuxbyNkw_000835.mp4 ripping paper +tests/VGGSound/video/gmNVDMv1wAE_000118.mp4 people eating apple +tests/VGGSound/video/gmNVDMv1wAE_000180.mp4 people eating apple +tests/VGGSound/video/gmdmwR01IdY_000040.mp4 car engine knocking +tests/VGGSound/video/gmy8czZ3uLc_000030.mp4 car passing by +tests/VGGSound/video/gmyjKCxNFwY_000030.mp4 playing accordion +tests/VGGSound/video/dY1Qd53MF4I_000310.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/dY3hVWRmYGM_000152.mp4 playing glockenspiel +tests/VGGSound/video/dYL0n0ZJxkA_000039.mp4 train whistling +tests/VGGSound/video/dYQ-nXyfhho_000030.mp4 playing drum kit +tests/VGGSound/video/dYea6bmdaSY_000040.mp4 opening or closing drawers +tests/VGGSound/video/goUSbvvuRt8_000097.mp4 opening or closing car doors +tests/VGGSound/video/gotJrqh0V3w_000030.mp4 pig oinking +tests/VGGSound/video/dZ7a5F_NZKE_000158.mp4 ripping paper +tests/VGGSound/video/dZEigzNRtB0_000030.mp4 frog croaking +tests/VGGSound/video/gpIWcn9yiXg_000350.mp4 playing harp +tests/VGGSound/video/gpJFhQtQ4cs_000133.mp4 playing tympani +tests/VGGSound/video/gpLe7H5RxnM_000013.mp4 elephant trumpeting +tests/VGGSound/video/gpO6rllg_84_000000.mp4 playing congas +tests/VGGSound/video/d_3P7vuZwUY_000190.mp4 eating with cutlery +tests/VGGSound/video/d_5uYgIBZyo_000028.mp4 civil defense siren +tests/VGGSound/video/d_6Ykd2ntDE_000131.mp4 telephone bell ringing +tests/VGGSound/video/d_CwI6yqE5k_000050.mp4 mynah bird singing +tests/VGGSound/video/d_Hdkt1_ivo_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/gpvYlHv1Ra4_000300.mp4 rapping +tests/VGGSound/video/gpyUJCmt3vE_000363.mp4 playing trumpet +tests/VGGSound/video/gqE8fkrtBjc_000212.mp4 air conditioning noise +tests/VGGSound/video/d_zeI_sbGB0_000093.mp4 rope skipping +tests/VGGSound/video/gqYkg6Y3MHg_000011.mp4 playing table tennis +tests/VGGSound/video/da-UIZplRqE_000030.mp4 playing gong +tests/VGGSound/video/gqf4xmzoQ4w_000030.mp4 frog croaking +tests/VGGSound/video/gqfo078B23o_000086.mp4 bouncing on trampoline +tests/VGGSound/video/daD9q2qZt10_000070.mp4 people sneezing +tests/VGGSound/video/daFkjcIjCVY_000030.mp4 dog whimpering +tests/VGGSound/video/grG6GPjDgU8_000030.mp4 chicken crowing +tests/VGGSound/video/grXXPSNjOak_000000.mp4 playing marimba, xylophone +tests/VGGSound/video/davLHMXIHDM_000320.mp4 reversing beeps +tests/VGGSound/video/grfr3IrdlGA_000290.mp4 orchestra +tests/VGGSound/video/dbD0nVfy9RU_000000.mp4 playing trumpet +tests/VGGSound/video/griyZ1JUOs0_000304.mp4 people gargling +tests/VGGSound/video/grryyLLuWk0_000034.mp4 wind chime +tests/VGGSound/video/grwLuzfleWw_000052.mp4 striking pool +tests/VGGSound/video/grygJyKvYgs_000030.mp4 basketball bounce +tests/VGGSound/video/gs-lSymjBVE_000030.mp4 ice cream truck, ice cream van +tests/VGGSound/video/gsEgN-dbQjo_000320.mp4 people eating +tests/VGGSound/video/dbunjNOhz2w_000210.mp4 eating with cutlery +tests/VGGSound/video/gseikrqMhAY_000029.mp4 owl hooting +tests/VGGSound/video/gsoxPkxJw_4_000380.mp4 playing marimba, xylophone +tests/VGGSound/video/dcfjgDYMJSk_000000.mp4 rapping +tests/VGGSound/video/dcjbs7R1yL8_000190.mp4 cattle mooing +tests/VGGSound/video/ddAkcDFK2mg_000045.mp4 playing volleyball +tests/VGGSound/video/ddHMstEKZko_000010.mp4 playing clarinet +tests/VGGSound/video/gu1K5iQTrCQ_000003.mp4 cattle mooing +tests/VGGSound/video/gu742sT-4Y0_000330.mp4 playing cello +tests/VGGSound/video/gu93aupykWE_000070.mp4 people whistling +tests/VGGSound/video/ddeSMfFLYTI_000420.mp4 telephone bell ringing +tests/VGGSound/video/guD3o7aspko_000030.mp4 people sniggering +tests/VGGSound/video/guFDo0MYm84_000000.mp4 foghorn +tests/VGGSound/video/guFu4Z4g1GE_000030.mp4 tapping guitar +tests/VGGSound/video/guGNQyMTm8Y_000101.mp4 playing castanets +tests/VGGSound/video/guGNQyMTm8Y_000218.mp4 playing castanets +tests/VGGSound/video/ddrPr5hBDLY_000211.mp4 opening or closing car electric windows +tests/VGGSound/video/ddshpQOcrG4_000120.mp4 playing erhu +tests/VGGSound/video/guRyU4B5LlA_000030.mp4 male speech, man speaking +tests/VGGSound/video/ddtqWAxjBI8_000031.mp4 elk bugling +tests/VGGSound/video/ddtqWAxjBI8_000049.mp4 elk bugling +tests/VGGSound/video/guYWKdxrtIg_000030.mp4 playing bass guitar +tests/VGGSound/video/ddySWSpptVo_000122.mp4 wood thrush calling +tests/VGGSound/video/gu_xJEyk5qg_000065.mp4 civil defense siren +tests/VGGSound/video/de8skUrbdUc_000030.mp4 cricket chirping +tests/VGGSound/video/gv16SOIvEnk_000021.mp4 mosquito buzzing +tests/VGGSound/video/deSs0MV_mJw_000060.mp4 train whistling +tests/VGGSound/video/deVyPq-AHfc_000430.mp4 playing harpsichord +tests/VGGSound/video/deX7R9RbmX0_000120.mp4 ocean burbling +tests/VGGSound/video/dexMfOlM1W0_000035.mp4 cell phone buzzing +tests/VGGSound/video/deyvkq2LZoY_000006.mp4 fox barking +tests/VGGSound/video/df4PKpleovw_000013.mp4 playing badminton +tests/VGGSound/video/gvcDHXQfIN0_000026.mp4 civil defense siren +tests/VGGSound/video/gvuoL6ugzvw_000040.mp4 chainsawing trees +tests/VGGSound/video/gwAP-vfQyRU_000006.mp4 fire truck siren +tests/VGGSound/video/gwIRjBMGTmo_000580.mp4 playing tabla +tests/VGGSound/video/dfXl7_lnt0U_000109.mp4 bouncing on trampoline +tests/VGGSound/video/dfYYRopvVx0_000030.mp4 female speech, woman speaking +tests/VGGSound/video/gwWVuexAvEs_000001.mp4 scuba diving +tests/VGGSound/video/gwi6bU0Rbbc_000000.mp4 skateboarding +tests/VGGSound/video/dfrps0BtQQQ_000080.mp4 playing vibraphone +tests/VGGSound/video/dfsvT5xImNg_000080.mp4 people screaming +tests/VGGSound/video/dfwr8wgZU8M_000040.mp4 car passing by +tests/VGGSound/video/gwkS8ABnslI_000258.mp4 popping popcorn +tests/VGGSound/video/dg7oSv2R4AE_000044.mp4 playing trumpet +tests/VGGSound/video/gx6wJrRxq-4_000030.mp4 rowboat, canoe, kayak rowing +tests/VGGSound/video/gx7Ylk3LVaU_000020.mp4 ocean burbling +tests/VGGSound/video/gxVhAVNjSU0_000030.mp4 driving buses +tests/VGGSound/video/dgpEiV4huf4_000690.mp4 striking bowling +tests/VGGSound/video/gy0qpNaxPm0_000002.mp4 canary calling +tests/VGGSound/video/gyP7-OSixNk_000030.mp4 playing hammond organ +tests/VGGSound/video/gyW4t5ogLyE_000030.mp4 crow cawing +tests/VGGSound/video/gyhxCxzvIps_000010.mp4 cat meowing +tests/VGGSound/video/gyiAvHSYyVY_000006.mp4 plastic bottle crushing +tests/VGGSound/video/gyiAvHSYyVY_000018.mp4 plastic bottle crushing +tests/VGGSound/video/dhvZfhfH4HA_000062.mp4 playing erhu +tests/VGGSound/video/gykTJfcqaH4_000234.mp4 ice cream truck, ice cream van +tests/VGGSound/video/di7eVZNlpkw_000040.mp4 car passing by +tests/VGGSound/video/diHn7q-YQEo_000061.mp4 blowtorch igniting +tests/VGGSound/video/gywN2QJ3QOs_000140.mp4 stream burbling +tests/VGGSound/video/dimiHRN4ro8_000024.mp4 sea waves +tests/VGGSound/video/djJ4ETLTBWE_000090.mp4 wood thrush calling +tests/VGGSound/video/djJV4GQBOkk_000060.mp4 singing bowl +tests/VGGSound/video/djdbIEu2K-Y_000110.mp4 sloshing water +tests/VGGSound/video/djoF51W8zqw_000048.mp4 people giggling +tests/VGGSound/video/h-BybUUIH-g_000468.mp4 playing table tennis +tests/VGGSound/video/h-Krpgn00Ik_000250.mp4 playing marimba, xylophone +tests/VGGSound/video/h-Vk4f8pz-o_000580.mp4 cap gun shooting +tests/VGGSound/video/dkpsxpeLY-M_000150.mp4 lighting firecrackers +tests/VGGSound/video/dlFXGfbcYvg_000027.mp4 wood thrush calling +tests/VGGSound/video/dlTE7W6vPJE_000022.mp4 tornado roaring +tests/VGGSound/video/h0-6U948u7Y_000050.mp4 playing sitar +tests/VGGSound/video/h0AQxQzzNt8_000030.mp4 playing french horn +tests/VGGSound/video/dln3mKCm29o_000070.mp4 playing trombone +tests/VGGSound/video/dm0UmJcbAGM_000185.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/dm5DJNfGJTs_000032.mp4 playing djembe +tests/VGGSound/video/dm5DJNfGJTs_000122.mp4 playing djembe +tests/VGGSound/video/dmDn2Tqsyeg_000030.mp4 hair dryer drying +tests/VGGSound/video/dmHcDWrMH-8_000060.mp4 playing violin, fiddle +tests/VGGSound/video/dmOYEzKEWew_000085.mp4 train wheels squealing +tests/VGGSound/video/dmOYEzKEWew_000158.mp4 train wheels squealing +tests/VGGSound/video/dmdMvf8RkSQ_000030.mp4 fire crackling +tests/VGGSound/video/h0vsyCyimhY_000155.mp4 people eating crisps +tests/VGGSound/video/h1HgO5pza24_000130.mp4 orchestra +tests/VGGSound/video/h1LxMPb7WD8_000085.mp4 playing castanets +tests/VGGSound/video/h1QxsOmXVCE_000187.mp4 airplane flyby +tests/VGGSound/video/h1v97wZQSPs_000000.mp4 people farting +tests/VGGSound/video/dn7CK_jxV_U_000148.mp4 race car, auto racing +tests/VGGSound/video/dnBRWaI4E38_000020.mp4 cat meowing +tests/VGGSound/video/dnQvS3jATno_000150.mp4 duck quacking +tests/VGGSound/video/h2f_CKjQQg8_000070.mp4 people clapping +tests/VGGSound/video/dnjPwzmnCbk_000293.mp4 black capped chickadee calling +tests/VGGSound/video/do1y1bkL14M_000300.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/doAZt2wBHI4_000012.mp4 cat purring +tests/VGGSound/video/h3BVONRNnu0_000000.mp4 car engine knocking +tests/VGGSound/video/doFrrF9ybU8_000240.mp4 hair dryer drying +tests/VGGSound/video/doS_7NMUGjY_000000.mp4 baby crying +tests/VGGSound/video/h3P2Si6bC6Y_000560.mp4 wind noise +tests/VGGSound/video/h3RdxdQEv4U_000085.mp4 playing lacrosse +tests/VGGSound/video/doX8FjlNPf8_000030.mp4 playing sitar +tests/VGGSound/video/h3cFTbRIzdY_000106.mp4 hammering nails +tests/VGGSound/video/doaQC-S8de8_000000.mp4 playing trumpet +tests/VGGSound/video/h4IhBsi2dcw_000170.mp4 mouse squeaking +tests/VGGSound/video/dp5VlGurxM4_000091.mp4 alarm clock ringing +tests/VGGSound/video/dp5VlGurxM4_000128.mp4 alarm clock ringing +tests/VGGSound/video/h4MaAn43I20_000069.mp4 yodelling +tests/VGGSound/video/dpEVjaFAhAs_000360.mp4 hair dryer drying +tests/VGGSound/video/h4eqSW3ME0E_000030.mp4 dog whimpering +tests/VGGSound/video/dpTKSxH3asA_000030.mp4 playing electronic organ +tests/VGGSound/video/dpURejDIKn8_000000.mp4 children shouting +tests/VGGSound/video/dpeUDViV6oA_000043.mp4 people giggling +tests/VGGSound/video/h55nHk2mJgY_000022.mp4 electric grinder grinding +tests/VGGSound/video/dq32VQZwRx0_000002.mp4 civil defense siren +tests/VGGSound/video/dq75lff004o_000001.mp4 elk bugling +tests/VGGSound/video/dqJSTTS7HTY_000030.mp4 playing acoustic guitar +tests/VGGSound/video/h5NTDVXiTiI_000050.mp4 chainsawing trees +tests/VGGSound/video/dqt_MzUQ20M_000080.mp4 chicken clucking +tests/VGGSound/video/dqu_dkIqqrw_000085.mp4 lathe spinning +tests/VGGSound/video/h5gvpYSIifs_000080.mp4 playing marimba, xylophone +tests/VGGSound/video/h5vhADC8z3I_000168.mp4 underwater bubbling +tests/VGGSound/video/h68KSTu7nv4_000030.mp4 mouse pattering +tests/VGGSound/video/h6HkOxlVt5c_000070.mp4 chicken clucking +tests/VGGSound/video/h6NMBTwaOss_000000.mp4 striking bowling +tests/VGGSound/video/drnnulHw5CM_000030.mp4 mouse pattering +tests/VGGSound/video/h6YMk2FOHHM_000017.mp4 tap dancing +tests/VGGSound/video/ds-nE2iRIRw_000106.mp4 swimming +tests/VGGSound/video/h6zc38gOkA4_000130.mp4 playing clarinet +tests/VGGSound/video/dsa76YLjmmw_000008.mp4 skiing +tests/VGGSound/video/h7Ge_EYH2Dc_000032.mp4 train whistling +tests/VGGSound/video/h7aDUFAAwFE_000560.mp4 thunder +tests/VGGSound/video/dt9d70BGio4_000019.mp4 playing squash +tests/VGGSound/video/h7hGEzZUXQQ_000000.mp4 elk bugling +tests/VGGSound/video/h8-Z6EtIYQA_000030.mp4 ocean burbling +tests/VGGSound/video/dtGl5xh6g0g_000138.mp4 tractor digging +tests/VGGSound/video/dtHVjFWdBhw_000308.mp4 heart sounds, heartbeat +tests/VGGSound/video/dt_BStmnAWk_000187.mp4 people gargling +tests/VGGSound/video/dtjPWoaOz60_000450.mp4 ripping paper +tests/VGGSound/video/h8fMUaesCrA_000168.mp4 playing trombone +tests/VGGSound/video/h9DKRk_i7f0_000041.mp4 yodelling +tests/VGGSound/video/duXP5p9KnAo_000265.mp4 police radio chatter +tests/VGGSound/video/ducLv0cfwVQ_000004.mp4 children shouting +tests/VGGSound/video/dufRvpDEZS8_000380.mp4 raining +tests/VGGSound/video/dulZ4FPi7gg_000170.mp4 toilet flushing +tests/VGGSound/video/h9nNUlpuh0U_000020.mp4 bird squawking +tests/VGGSound/video/h9vUucEhRN4_000090.mp4 cat caterwauling +tests/VGGSound/video/dvR0Km6r2KI_000380.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/dvUScIfbsOY_000051.mp4 cow lowing +tests/VGGSound/video/hAehs6GdfIQ_000030.mp4 printer printing +tests/VGGSound/video/dvzwRooVGJI_000140.mp4 dog howling +tests/VGGSound/video/dwAo0dKCyBI_000030.mp4 rapping +tests/VGGSound/video/hAukn8dWZ2M_000030.mp4 people sniggering +tests/VGGSound/video/dwEU1TXu5bw_000174.mp4 slot machine +tests/VGGSound/video/hB2DZcypK0Y_000187.mp4 playing tennis +tests/VGGSound/video/dweVBqei9LA_000160.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/hBQFoDI3NMI_000030.mp4 tapping guitar +tests/VGGSound/video/hBTte9j8Xrk_000136.mp4 squishing water +tests/VGGSound/video/hBXiZt-8zo0_000000.mp4 playing washboard +tests/VGGSound/video/hB_UbXeQsjU_000053.mp4 disc scratching +tests/VGGSound/video/dxDbrvoKTD8_000331.mp4 eletric blender running +tests/VGGSound/video/dxN1J8CvLdE_000000.mp4 playing trumpet +tests/VGGSound/video/hBjE3FVevZA_000190.mp4 dog baying +tests/VGGSound/video/dxVMVOPXRUQ_000069.mp4 playing oboe +tests/VGGSound/video/hBrcjmbJq0k_000044.mp4 thunder +tests/VGGSound/video/hC7sSMWLwDo_000016.mp4 baby crying +tests/VGGSound/video/dxrg1wawqvY_000000.mp4 people screaming +tests/VGGSound/video/hCJ5hEnQo4s_000030.mp4 lawn mowing +tests/VGGSound/video/dxvhJNXKIw0_000030.mp4 fire crackling +tests/VGGSound/video/hCR2_Lrjw8I_000048.mp4 canary calling +tests/VGGSound/video/hCX2DpwEBQY_000030.mp4 fireworks banging +tests/VGGSound/video/dy7klgwlfNs_000280.mp4 eating with cutlery +tests/VGGSound/video/dyFoyYMZu-E_000508.mp4 lip smacking +tests/VGGSound/video/hCbPUyqgdPY_000191.mp4 people gargling +tests/VGGSound/video/dySzuSBqPnE_000007.mp4 ripping paper +tests/VGGSound/video/dySzuSBqPnE_000040.mp4 ripping paper +tests/VGGSound/video/dyX9ElZE7TQ_000070.mp4 playing clarinet +tests/VGGSound/video/hDDBWwEJX60_000000.mp4 people eating apple +tests/VGGSound/video/hDGiU8zHWdU_000030.mp4 playing clarinet +tests/VGGSound/video/hDIziLujP38_000160.mp4 people eating crisps +tests/VGGSound/video/dyz5v3kxF3Y_000001.mp4 mosquito buzzing +tests/VGGSound/video/hDnMfsCScSc_000096.mp4 air horn +tests/VGGSound/video/hDvi0lXcDKA_000055.mp4 magpie calling +tests/VGGSound/video/dzah9kCDVJs_000540.mp4 hair dryer drying +tests/VGGSound/video/hEWlxtiO6Sw_000150.mp4 horse clip-clop +tests/VGGSound/video/dzw5qQo-i4Y_000000.mp4 pumping water +tests/VGGSound/video/hFKmJx0_Fkg_000030.mp4 church bell ringing +tests/VGGSound/video/hFdTLz4HW78_000280.mp4 eating with cutlery +tests/VGGSound/video/hFkC9DzHoho_000099.mp4 playing bassoon +tests/VGGSound/video/hFkC9DzHoho_000189.mp4 playing bassoon +tests/VGGSound/video/e03gY44qb9g_000030.mp4 goat bleating +tests/VGGSound/video/hG8odscqlfI_000490.mp4 wind noise +tests/VGGSound/video/hGMrZZaTRSE_000450.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/e0VpiSzf57Y_000006.mp4 mosquito buzzing +tests/VGGSound/video/e0i5J6wbnwM_000392.mp4 squishing water +tests/VGGSound/video/hGogSm0O5aE_000024.mp4 missile launch +tests/VGGSound/video/e1QHcaaO4IA_000049.mp4 tornado roaring +tests/VGGSound/video/hH6thMA3640_000120.mp4 playing banjo +tests/VGGSound/video/e1nqsYDLGSg_000263.mp4 playing badminton +tests/VGGSound/video/e2AaF6siR1A_000540.mp4 people screaming +tests/VGGSound/video/hHb0Eq1I7Fk_000000.mp4 skateboarding +tests/VGGSound/video/hHbJRPjqgXQ_000090.mp4 race car, auto racing +tests/VGGSound/video/hHceJPFc1Iw_000140.mp4 cricket chirping +tests/VGGSound/video/hIYihNrwF2Q_000440.mp4 cap gun shooting +tests/VGGSound/video/hIazzIF19gY_000110.mp4 splashing water +tests/VGGSound/video/hIcRxMF0-n4_000262.mp4 chopping wood +tests/VGGSound/video/e2yjPsXo4_M_000016.mp4 crow cawing +tests/VGGSound/video/hIo3lkALDlg_000050.mp4 playing flute +tests/VGGSound/video/hIqYFdJ9v0o_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/e42ylHtkQ5M_000030.mp4 typing on typewriter +tests/VGGSound/video/e4RCfcPk5Ck_000196.mp4 playing glockenspiel +tests/VGGSound/video/e4Xh8ZImhUA_000097.mp4 police car (siren) +tests/VGGSound/video/hK3V1i7MSHY_000020.mp4 baby babbling +tests/VGGSound/video/e4qVs0kpC_w_000510.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/hKQb8SijZO4_000240.mp4 baby babbling +tests/VGGSound/video/e4ttSpHfJ1Y_000020.mp4 goose honking +tests/VGGSound/video/e53eD7dpQi0_000030.mp4 mouse squeaking +tests/VGGSound/video/hKcSZfv9gms_000001.mp4 playing trumpet +tests/VGGSound/video/e57SBRbMXbI_000080.mp4 lions roaring +tests/VGGSound/video/e5ME1cZa2Yk_000045.mp4 metronome +tests/VGGSound/video/hLCA2KW9dC8_000002.mp4 people gargling +tests/VGGSound/video/e5VbU4nhYa0_000003.mp4 eletric blender running +tests/VGGSound/video/e5Wu9El1mI4_000156.mp4 fireworks banging +tests/VGGSound/video/e5aCQbqUY9I_000000.mp4 donkey, ass braying +tests/VGGSound/video/hLkYXlhG224_000300.mp4 splashing water +tests/VGGSound/video/e5sOqiyIhkc_000171.mp4 people humming +tests/VGGSound/video/hMRiqTGvxHc_000193.mp4 playing volleyball +tests/VGGSound/video/e6Apd0uUxkY_000012.mp4 roller coaster running +tests/VGGSound/video/hMsu6w5Ay44_000030.mp4 horse clip-clop +tests/VGGSound/video/e7Awkja4J04_000120.mp4 lions roaring +tests/VGGSound/video/hNL5kuYOnok_000119.mp4 car engine starting +tests/VGGSound/video/hNSQ9XuhiFA_000006.mp4 chimpanzee pant-hooting +tests/VGGSound/video/hNubz3rGwrA_000000.mp4 playing piano +tests/VGGSound/video/e8OMvCTmsX0_000363.mp4 playing tympani +tests/VGGSound/video/hO7Y77gKIMo_000150.mp4 raining +tests/VGGSound/video/e8iKX9r6nEA_000000.mp4 people belly laughing +tests/VGGSound/video/e8l9BGprwb0_000016.mp4 lions growling +tests/VGGSound/video/e9ECf2ZGBdk_000215.mp4 striking bowling +tests/VGGSound/video/e9EUmQBO498_000000.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/hOua7RdPg38_000090.mp4 baby laughter +tests/VGGSound/video/hP6IA_FD-j4_000038.mp4 francolin calling +tests/VGGSound/video/e9vBt3krCh4_000060.mp4 cat growling +tests/VGGSound/video/eA1dUOMkkvM_000000.mp4 smoke detector beeping +tests/VGGSound/video/hPUhu0HEkBU_000269.mp4 playing tympani +tests/VGGSound/video/hPUhu0HEkBU_000279.mp4 playing tympani +tests/VGGSound/video/hQ1L0ZhzGqo_000500.mp4 stream burbling +tests/VGGSound/video/hQ4oiJEIugg_000014.mp4 underwater bubbling +tests/VGGSound/video/eB0kQ_zYdHc_000180.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/hQMkT2YEnNA_000030.mp4 people coughing +tests/VGGSound/video/hQYRDNl-lGI_000382.mp4 race car, auto racing +tests/VGGSound/video/eBF0zRHCbZE_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/hQqM8iNebYw_000070.mp4 playing hammond organ +tests/VGGSound/video/hQyI4uLmrig_000050.mp4 playing timpani +tests/VGGSound/video/hR6PtBiWneE_000030.mp4 playing squash +tests/VGGSound/video/hRHKxyErgZw_000030.mp4 crow cawing +tests/VGGSound/video/eBwcofimB3M_000165.mp4 spraying water +tests/VGGSound/video/eC2QpruaH0g_000040.mp4 cheetah chirrup +tests/VGGSound/video/hRc5mInvrYA_000003.mp4 rope skipping +tests/VGGSound/video/hRdkmwuv13s_000220.mp4 fire truck siren +tests/VGGSound/video/hSAVR0LcQp8_000280.mp4 police car (siren) +tests/VGGSound/video/hSAgDYarzOs_000060.mp4 helicopter +tests/VGGSound/video/eCcMwDKQLCA_000040.mp4 typing on typewriter +tests/VGGSound/video/hSV8LmYR6TY_000010.mp4 pigeon, dove cooing +tests/VGGSound/video/hT2FAykn0Ao_000035.mp4 gibbon howling +tests/VGGSound/video/hT8dAeHe7Ow_000050.mp4 playing hammond organ +tests/VGGSound/video/hTAWbHXCJ2A_000060.mp4 people finger snapping +tests/VGGSound/video/hTDVhi-O1I4_000061.mp4 planing timber +tests/VGGSound/video/eE2OsnPVzzI_000157.mp4 canary calling +tests/VGGSound/video/hTxXqAik2UU_000003.mp4 coyote howling +tests/VGGSound/video/hTxXqAik2UU_000058.mp4 coyote howling +tests/VGGSound/video/hU3_3_MjKl8_000011.mp4 people booing +tests/VGGSound/video/hU9mxdQctYQ_000047.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/eEn3IreUkas_000000.mp4 sliding door +tests/VGGSound/video/hUJWpx4ji1M_000092.mp4 playing bongo +tests/VGGSound/video/hUcuXIvDN2E_000030.mp4 playing bass guitar +tests/VGGSound/video/hVG4p9QJHk0_000030.mp4 sliding door +tests/VGGSound/video/eFueCoTecKY_000159.mp4 train wheels squealing +tests/VGGSound/video/eFwVC47pOig_000100.mp4 playing piano +tests/VGGSound/video/eFzyxoc1w1g_000010.mp4 bird squawking +tests/VGGSound/video/eGINdu-eQaI_000000.mp4 snake hissing +tests/VGGSound/video/eGheWZgpYqs_000060.mp4 people hiccup +tests/VGGSound/video/eGzcSSGZzqM_000000.mp4 cap gun shooting +tests/VGGSound/video/eI4PbSh6g_Y_000030.mp4 playing steelpan +tests/VGGSound/video/hXrQd_8rOs0_000143.mp4 people slapping +tests/VGGSound/video/eIkUuCRE_0U_000030.mp4 reversing beeps +tests/VGGSound/video/eIlin6nSUd0_000100.mp4 mouse pattering +tests/VGGSound/video/hY0BwM5s6F0_000000.mp4 playing bagpipes +tests/VGGSound/video/hY1yRiy-Zy4_000270.mp4 stream burbling +tests/VGGSound/video/eIxOyj3LfJM_000007.mp4 police car (siren) +tests/VGGSound/video/eJ2AKzgNkyA_000120.mp4 playing vibraphone +tests/VGGSound/video/hY7xFCcshxE_000011.mp4 sloshing water +tests/VGGSound/video/eJSpibgl0-c_000030.mp4 motorboat, speedboat acceleration +tests/VGGSound/video/hYk2rw9wcXc_000070.mp4 male speech, man speaking +tests/VGGSound/video/eJsVdyNPVh0_000500.mp4 raining +tests/VGGSound/video/eJwNvNpCMN4_000030.mp4 hair dryer drying +tests/VGGSound/video/hZ4oCZEjcWE_000129.mp4 playing tympani +tests/VGGSound/video/hZKPDpfzokM_000030.mp4 goose honking +tests/VGGSound/video/hZQ5AlAjgVI_000068.mp4 eagle screaming +tests/VGGSound/video/eKMhRfdwwWI_000030.mp4 people sniggering +tests/VGGSound/video/h_AQyNKifwQ_000128.mp4 opening or closing car electric windows +tests/VGGSound/video/h_AQyNKifwQ_000145.mp4 opening or closing car electric windows +tests/VGGSound/video/h_GXTAWpJC8_000002.mp4 cat growling +tests/VGGSound/video/h_MVI_0kIkI_000030.mp4 people farting +tests/VGGSound/video/h_Q_2UKcQX0_000368.mp4 fireworks banging +tests/VGGSound/video/h_U-Seegsmo_000018.mp4 footsteps on snow +tests/VGGSound/video/h__4MI_GgpM_000140.mp4 firing cannon +tests/VGGSound/video/h_hwxcgSr3g_000031.mp4 donkey, ass braying +tests/VGGSound/video/h_hwxcgSr3g_000065.mp4 donkey, ass braying +tests/VGGSound/video/h_m8EqsraXs_000072.mp4 lions growling +tests/VGGSound/video/h_m8EqsraXs_000206.mp4 lions growling +tests/VGGSound/video/eM0PkfqGmIE_000030.mp4 playing bass guitar +tests/VGGSound/video/eM4nDN84gNc_000107.mp4 child singing +tests/VGGSound/video/eMN-HFZMaKc_000160.mp4 playing gong +tests/VGGSound/video/eMQQRvh-BUI_000030.mp4 door slamming +tests/VGGSound/video/eMQu7p-mw8I_000467.mp4 playing bass drum +tests/VGGSound/video/ha8lvNZ7n7c_000046.mp4 playing oboe +tests/VGGSound/video/eMQySEjyCUw_000160.mp4 playing vibraphone +tests/VGGSound/video/haEhBq0E5Eo_000119.mp4 eletric blender running +tests/VGGSound/video/haVBNvKQsEI_000020.mp4 mynah bird singing +tests/VGGSound/video/eMpg3l9nI2s_000030.mp4 dog barking +tests/VGGSound/video/eNekiwtQkdc_000325.mp4 popping popcorn +tests/VGGSound/video/eNf20D3BlIs_000015.mp4 hedge trimmer running +tests/VGGSound/video/hbLS-Dlgj_o_000002.mp4 opening or closing car electric windows +tests/VGGSound/video/eO8SL6GZeqc_000004.mp4 playing glockenspiel +tests/VGGSound/video/hboxHDBnQrA_000023.mp4 cupboard opening or closing +tests/VGGSound/video/eO_Z0BiT43M_000292.mp4 playing shofar +tests/VGGSound/video/eOrV9yNuT3o_000030.mp4 bird squawking +tests/VGGSound/video/eOwKvuuMl74_000070.mp4 people cheering +tests/VGGSound/video/eOwKvuuMl74_000103.mp4 people cheering +tests/VGGSound/video/hcOkk03PnZE_000110.mp4 playing electronic organ 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eating +tests/VGGSound/video/heZw1TTrtTU_000080.mp4 using sewing machines +tests/VGGSound/video/hekfjJRfSXM_000032.mp4 golf driving +tests/VGGSound/video/hf6qJx4tZ6k_000005.mp4 chinchilla barking +tests/VGGSound/video/hfBuRqBEBo4_000250.mp4 people eating noodle +tests/VGGSound/video/hfGPgIdj0WM_000055.mp4 eletric blender running +tests/VGGSound/video/hfIfBPkH8Fo_000300.mp4 waterfall burbling +tests/VGGSound/video/eSKFXcMdFXI_000606.mp4 alligators, crocodiles hissing +tests/VGGSound/video/eSKFXcMdFXI_000716.mp4 alligators, crocodiles hissing +tests/VGGSound/video/eSMCZfnJ5gI_000030.mp4 dog barking +tests/VGGSound/video/eSSs8vV3VNc_000491.mp4 forging swords +tests/VGGSound/video/hfdMfiv2R9w_000058.mp4 people giggling +tests/VGGSound/video/hfewjg0CTQM_000060.mp4 church bell ringing +tests/VGGSound/video/hfhordJxh9Y_000030.mp4 sliding door +tests/VGGSound/video/hflYLQsp9VY_000002.mp4 people slapping +tests/VGGSound/video/hfqUU1lUFLw_000010.mp4 chinchilla barking 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grinding +tests/VGGSound/video/iJX8yWBTJw8_000020.mp4 people humming +tests/VGGSound/video/f6wrXzvByrg_000030.mp4 playing banjo +tests/VGGSound/video/f724u5z_UDw_000030.mp4 driving motorcycle +tests/VGGSound/video/f77SKdyn-1Y_001228.mp4 sea waves +tests/VGGSound/video/iKWclBFnR2M_000001.mp4 mynah bird singing +tests/VGGSound/video/iKwWzXGr_NY_000330.mp4 crow cawing +tests/VGGSound/video/f8MFow7FEgU_000091.mp4 playing erhu +tests/VGGSound/video/iLaDu_GNqb4_000013.mp4 ice cream truck, ice cream van +tests/VGGSound/video/f8cJ5g7Pe88_000030.mp4 crow cawing +tests/VGGSound/video/f8mOApBc_ao_000178.mp4 squishing water +tests/VGGSound/video/iM93yND9Ghw_000010.mp4 airplane flyby +tests/VGGSound/video/iMKk662Z7E0_000074.mp4 smoke detector beeping +tests/VGGSound/video/iMNEd2l5Ff8_000030.mp4 firing cannon +tests/VGGSound/video/f9gjQDw0I5Q_000134.mp4 playing castanets +tests/VGGSound/video/f9gjQDw0I5Q_000419.mp4 playing castanets +tests/VGGSound/video/f9rfsCGlpes_000000.mp4 dog whimpering 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people shuffling +tests/VGGSound/video/iROgD3JRJFY_000090.mp4 baby laughter +tests/VGGSound/video/iRXQiy4dReE_000045.mp4 elk bugling +tests/VGGSound/video/iS8YQGp2_ng_000030.mp4 rapping +tests/VGGSound/video/iSZc5I90ddA_000030.mp4 printer printing +tests/VGGSound/video/iSu2BRhUcLQ_000490.mp4 playing marimba, xylophone +tests/VGGSound/video/iSyWKTPonhQ_000121.mp4 electric grinder grinding +tests/VGGSound/video/iTCfi5_b4Ow_000035.mp4 playing erhu +tests/VGGSound/video/iTkzTbXi23U_000075.mp4 smoke detector beeping +tests/VGGSound/video/iTmNN9uGRfs_000314.mp4 snake hissing +tests/VGGSound/video/iUcepAhtxcc_000147.mp4 playing hockey +tests/VGGSound/video/lnWP_zWFpBg_000030.mp4 playing steelpan +tests/VGGSound/video/iUoFC-GUq8o_000113.mp4 sloshing water +tests/VGGSound/video/lnZakZnnpMo_000080.mp4 people finger snapping +tests/VGGSound/video/iUtE4nRvBsM_000040.mp4 people coughing +tests/VGGSound/video/lndowS7ZYlA_000166.mp4 playing darts +tests/VGGSound/video/iV8CpHmiyrI_000030.mp4 wind rustling leaves +tests/VGGSound/video/lnxJm8OjSjE_000063.mp4 rope skipping +tests/VGGSound/video/lo3yvn1av2E_000030.mp4 fireworks banging +tests/VGGSound/video/loKkvegkPJ8_000030.mp4 people whispering +tests/VGGSound/video/iW4pt41OuA0_000030.mp4 crow cawing +tests/VGGSound/video/iW8es1xXsG4_000225.mp4 people marching +tests/VGGSound/video/iW8es1xXsG4_000533.mp4 people marching +tests/VGGSound/video/iWak8wPMXV4_000558.mp4 swimming +tests/VGGSound/video/loh7D-LwTag_000216.mp4 playing badminton +tests/VGGSound/video/iWiNV03Wa6Y_000072.mp4 snake hissing +tests/VGGSound/video/iWmdwmSL_xk_000336.mp4 wind chime +tests/VGGSound/video/iX2pK_rV6aA_000029.mp4 cutting hair with electric trimmers +tests/VGGSound/video/iX53Jb72Nwk_000140.mp4 playing didgeridoo +tests/VGGSound/video/iX5fyNvNOuk_000010.mp4 playing piano +tests/VGGSound/video/iX71wBMIn5k_000380.mp4 frog croaking +tests/VGGSound/video/iXFMyZm8fZY_000047.mp4 forging swords +tests/VGGSound/video/iXNnJE6gNEk_000020.mp4 baby laughter 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castanets +tests/VGGSound/video/lvP08twtwdg_000315.mp4 running electric fan +tests/VGGSound/video/idS-vH-vTw0_000111.mp4 people slapping +tests/VGGSound/video/idUZsNLnyDg_000030.mp4 tapping guitar +tests/VGGSound/video/lv_tTIdHC2Q_000130.mp4 playing djembe +tests/VGGSound/video/lvabmASz47c_000142.mp4 people battle cry +tests/VGGSound/video/idmwtF7qPLI_000176.mp4 parrot talking +tests/VGGSound/video/ie47-Wjj4Zw_000027.mp4 ferret dooking +tests/VGGSound/video/ie47-Wjj4Zw_000063.mp4 ferret dooking +tests/VGGSound/video/lwTJnSlhz-Q_000417.mp4 popping popcorn +tests/VGGSound/video/ieZmQbzQYtw_000000.mp4 people belly laughing +tests/VGGSound/video/lwWitgspvqo_000051.mp4 strike lighter +tests/VGGSound/video/lwYZnPB1i0o_000030.mp4 fire crackling +tests/VGGSound/video/lwdbb4Rc7_A_000030.mp4 bird wings flapping +tests/VGGSound/video/ifCmvLNQl3s_000030.mp4 crow cawing +tests/VGGSound/video/ifGuIUPl1hE_000030.mp4 lions roaring +tests/VGGSound/video/ifHRDBx-ctw_000030.mp4 playing accordion 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+tests/VGGSound/video/m4emitvY_Dg_000178.mp4 tractor digging +tests/VGGSound/video/iosDKvAHUCI_000012.mp4 ice cream truck, ice cream van +tests/VGGSound/video/iotIxAR-eH8_000240.mp4 bird squawking +tests/VGGSound/video/ip6sz3xorFo_000010.mp4 people farting +tests/VGGSound/video/ipKCHDizaQI_000030.mp4 people sneezing +tests/VGGSound/video/ipSnR0fR_uA_000044.mp4 pheasant crowing +tests/VGGSound/video/ipSnR0fR_uA_000058.mp4 pheasant crowing +tests/VGGSound/video/m5CR9WA20dE_000020.mp4 airplane +tests/VGGSound/video/m5HN3-l_f-U_000150.mp4 playing cymbal +tests/VGGSound/video/m5I_M9d80Wg_000030.mp4 cat meowing +tests/VGGSound/video/m5REmzwlmOE_000070.mp4 chicken crowing +tests/VGGSound/video/m5eWlvtbamk_000130.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/ipxCuhWJ3oA_000003.mp4 chinchilla barking +tests/VGGSound/video/ipx_reb1Kfc_000000.mp4 baby babbling +tests/VGGSound/video/m5sIS0q8yy8_000000.mp4 chinchilla barking +tests/VGGSound/video/iq5Lh7AB1Ns_000019.mp4 playing glockenspiel 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coughing +tests/VGGSound/video/j6n_MNU52Ns_000030.mp4 lawn mowing +tests/VGGSound/video/mNfUI620AIs_000000.mp4 playing timpani +tests/VGGSound/video/j6s-UMrMIE8_000190.mp4 snake hissing +tests/VGGSound/video/mNkqURQhM0c_000041.mp4 writing on blackboard with chalk +tests/VGGSound/video/j7LDdHAhIbo_000030.mp4 fire crackling +tests/VGGSound/video/mOOx10X0iG4_000039.mp4 skiing +tests/VGGSound/video/j7Vej9AOKY0_000031.mp4 elephant trumpeting +tests/VGGSound/video/mOPJRy2Nv_o_000134.mp4 tractor digging +tests/VGGSound/video/j7p1kbECybQ_000167.mp4 people battle cry +tests/VGGSound/video/j8vekQPmE4E_000020.mp4 playing accordion +tests/VGGSound/video/mPU9j7icxs0_000123.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/j99DUjxpCWY_000030.mp4 door slamming +tests/VGGSound/video/mPtIJOdWFso_000030.mp4 pig oinking +tests/VGGSound/video/j9PGC-rAfzg_000000.mp4 woodpecker pecking tree +tests/VGGSound/video/j9Z63H5hvrQ_000010.mp4 subway, metro, underground 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sailing +tests/VGGSound/video/mZ6ALw9GOUU_000030.mp4 playing harp +tests/VGGSound/video/jIqAaU2Bgf0_000530.mp4 reversing beeps +tests/VGGSound/video/mZIBXZlICgw_000000.mp4 driving motorcycle +tests/VGGSound/video/mZKUFZhLXAE_000021.mp4 beat boxing +tests/VGGSound/video/mZNANTTOh7w_000249.mp4 car engine idling +tests/VGGSound/video/jJ6FWcy7B6M_000052.mp4 train wheels squealing +tests/VGGSound/video/jJBgSsVyQns_000010.mp4 playing bagpipes +tests/VGGSound/video/mZXjs-SYlCA_000005.mp4 people giggling +tests/VGGSound/video/mZ_z2lorJeY_000070.mp4 male speech, man speaking +tests/VGGSound/video/jJRbB0Oahls_000000.mp4 church bell ringing +tests/VGGSound/video/mZuhtrwOS7Q_000020.mp4 people burping +tests/VGGSound/video/jJkCnY3keZk_000090.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/jJp1gPilmxs_000009.mp4 playing harmonica +tests/VGGSound/video/jK32YxTVs1M_000013.mp4 underwater bubbling +tests/VGGSound/video/m_dE5TdJ3c0_000036.mp4 arc welding 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trimmers +tests/VGGSound/video/mcBEkWVDcmc_000107.mp4 bull bellowing +tests/VGGSound/video/mcDE08Bi64k_000030.mp4 playing french horn +tests/VGGSound/video/mcYd-WlyCIw_000006.mp4 telephone bell ringing +tests/VGGSound/video/mcrf1Mb99d4_000068.mp4 playing tympani +tests/VGGSound/video/mdC78ZNupCE_000128.mp4 playing cornet +tests/VGGSound/video/jNXnXlF2Cgo_000500.mp4 playing bagpipes +tests/VGGSound/video/jNr33exAsGg_000051.mp4 cuckoo bird calling +tests/VGGSound/video/jOMEUwArKss_000004.mp4 eagle screaming +tests/VGGSound/video/jOezpKDolRQ_000221.mp4 golf driving +tests/VGGSound/video/mdrKLSXXZNc_000302.mp4 black capped chickadee calling +tests/VGGSound/video/jP3F__n2uRs_000030.mp4 playing clarinet +tests/VGGSound/video/meA5z8lSHhU_000054.mp4 swimming +tests/VGGSound/video/jPGn0rqkLPY_000080.mp4 playing gong +tests/VGGSound/video/jPIEgoO4cL0_000024.mp4 baby crying +tests/VGGSound/video/jPKhBkLgFLk_000016.mp4 playing violin, fiddle +tests/VGGSound/video/meLyeGrTL1I_000049.mp4 scuba diving +tests/VGGSound/video/melKLfB6gjY_000024.mp4 firing muskets +tests/VGGSound/video/meoZvdQ2qBs_000162.mp4 missile launch +tests/VGGSound/video/jPoPMzmjtLg_000137.mp4 opening or closing car electric windows +tests/VGGSound/video/mfA8XGaLTNo_000016.mp4 people humming +tests/VGGSound/video/mfJ5bk_gGTU_000050.mp4 mosquito buzzing +tests/VGGSound/video/jQEi2K1fvRI_000263.mp4 black capped chickadee calling +tests/VGGSound/video/mfPRLpelDuQ_000190.mp4 thunder +tests/VGGSound/video/jQFmaTURf3Q_000000.mp4 foghorn +tests/VGGSound/video/jQK1Dv2ZbaY_000063.mp4 bouncing on trampoline +tests/VGGSound/video/jQOIioBX-bo_000032.mp4 spraying water +tests/VGGSound/video/jR-H47v1arg_000080.mp4 pigeon, dove cooing +tests/VGGSound/video/mg2EyWA0Jxc_000030.mp4 playing drum kit +tests/VGGSound/video/mg6Gg4StHH0_000531.mp4 lip smacking +tests/VGGSound/video/jRImoxsY_uo_000030.mp4 mouse squeaking +tests/VGGSound/video/jRRAu-hdI2g_000025.mp4 car passing by +tests/VGGSound/video/mgY1ZoRaaAA_000030.mp4 people finger snapping +tests/VGGSound/video/jRaUjtDSHBM_000020.mp4 electric grinder grinding +tests/VGGSound/video/mgihmWi364U_000080.mp4 typing on computer keyboard +tests/VGGSound/video/jS93Dp3LPSY_000000.mp4 playing saxophone +tests/VGGSound/video/mh6JxDJ0Bno_000030.mp4 female speech, woman speaking +tests/VGGSound/video/mhCzYK5JCBM_000030.mp4 duck quacking +tests/VGGSound/video/mhQGbJQlVns_000002.mp4 baby crying +tests/VGGSound/video/mhRdop55WeQ_000300.mp4 playing cello +tests/VGGSound/video/jSTohhfh8wU_000082.mp4 coyote howling +tests/VGGSound/video/mhZMQF-y8n0_000061.mp4 playing snare drum +tests/VGGSound/video/mhZMQF-y8n0_000097.mp4 playing snare drum +tests/VGGSound/video/mhhqLEAF-jA_000037.mp4 foghorn +tests/VGGSound/video/jSjIdwRgqCY_000071.mp4 ripping paper +tests/VGGSound/video/mhmVWT-tH1U_000139.mp4 ripping paper +tests/VGGSound/video/mhmVWT-tH1U_000285.mp4 ripping paper +tests/VGGSound/video/mi6DQRlrD7g_000030.mp4 playing steel guitar, slide guitar 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singing +tests/VGGSound/video/moLATfN79Yo_000040.mp4 lighting firecrackers +tests/VGGSound/video/moZ49NEGqfk_000310.mp4 lawn mowing +tests/VGGSound/video/mo_x30i1gns_000099.mp4 playing glockenspiel +tests/VGGSound/video/mofxODOJLAU_000030.mp4 sloshing water +tests/VGGSound/video/mohlfADrrP0_000000.mp4 church bell ringing +tests/VGGSound/video/moiUAO3CKbM_000420.mp4 cattle mooing +tests/VGGSound/video/molzJ-iOKrI_000021.mp4 foghorn +tests/VGGSound/video/momJJOUPFzU_000017.mp4 wood thrush calling +tests/VGGSound/video/ja-tlXByr4Q_000161.mp4 playing double bass +tests/VGGSound/video/mpEh3S2rspM_000003.mp4 striking bowling +tests/VGGSound/video/jaI41fTAM54_000030.mp4 church bell ringing +tests/VGGSound/video/jaK5VEN7fKY_000030.mp4 typing on typewriter +tests/VGGSound/video/mpNxnTHMCHs_000164.mp4 playing tambourine +tests/VGGSound/video/jaQ48brABIk_000340.mp4 goose honking +tests/VGGSound/video/jaSK_t8QP1E_000030.mp4 driving buses +tests/VGGSound/video/mpPrCXLKfGU_000002.mp4 playing tuning fork +tests/VGGSound/video/mpXv8WKFHRc_000435.mp4 strike lighter +tests/VGGSound/video/jaXf_AlCBK4_000100.mp4 arc welding +tests/VGGSound/video/jas53wmLSNU_000188.mp4 arc welding +tests/VGGSound/video/jb3vjhlybhE_000017.mp4 police radio chatter +tests/VGGSound/video/jbEYZDagytA_000030.mp4 people sobbing +tests/VGGSound/video/jbH4PifIg-g_000006.mp4 playing tambourine +tests/VGGSound/video/jbVBpTeK53M_000140.mp4 bird squawking +tests/VGGSound/video/jbaZyROpitQ_000010.mp4 people hiccup +tests/VGGSound/video/jbffNajOX7M_000019.mp4 chimpanzee pant-hooting +tests/VGGSound/video/mr8uEQKL1GY_000161.mp4 running electric fan +tests/VGGSound/video/mr8uEQKL1GY_000178.mp4 running electric fan +tests/VGGSound/video/mrWO0Ib5HE4_000570.mp4 hair dryer drying +tests/VGGSound/video/jc1CQQpJY7Q_000278.mp4 whale calling +tests/VGGSound/video/jcIFYIRgzbY_000165.mp4 rope skipping +tests/VGGSound/video/jcKRIZHO37k_000082.mp4 wood thrush calling +tests/VGGSound/video/jcoTSA5FxpE_000030.mp4 dog barking 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cap gun shooting +tests/VGGSound/video/jh0nGY4dzHg_000280.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/mwoQMUhI9nY_000139.mp4 playing table tennis +tests/VGGSound/video/jhTQR8w9SYI_000057.mp4 playing timbales +tests/VGGSound/video/mx0fKYM90vQ_000030.mp4 mouse squeaking +tests/VGGSound/video/mx2J7tKL66w_000050.mp4 playing snare drum +tests/VGGSound/video/mxH5Ueh1fYo_000536.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/mxJJB7Y__Ao_000030.mp4 hair dryer drying +tests/VGGSound/video/jhp75b6frMw_000033.mp4 otter growling +tests/VGGSound/video/mxQ37FEFLKY_000030.mp4 people whispering +tests/VGGSound/video/jhp75b6frMw_000067.mp4 otter growling +tests/VGGSound/video/jhplcoP39vM_000118.mp4 dog baying +tests/VGGSound/video/mx_t1glv_uE_000000.mp4 train horning +tests/VGGSound/video/ji3FsCD0OzU_000220.mp4 playing zither +tests/VGGSound/video/mxczypKrxSc_000002.mp4 sailing +tests/VGGSound/video/mxczypKrxSc_000013.mp4 sailing +tests/VGGSound/video/ji4meumtHT4_000030.mp4 cat hissing +tests/VGGSound/video/mxlvULNwlpU_000110.mp4 playing sitar +tests/VGGSound/video/jiNF8appg9Y_000043.mp4 people eating apple +tests/VGGSound/video/mxy5qcJckDQ_000195.mp4 playing bass drum +tests/VGGSound/video/ji_YCMygNHQ_000008.mp4 driving buses +tests/VGGSound/video/jii46gf1UkM_000140.mp4 cattle, bovinae cowbell +tests/VGGSound/video/jin4FoKXn1o_000180.mp4 orchestra +tests/VGGSound/video/myD-He_i2Ao_000199.mp4 elk bugling +tests/VGGSound/video/myOH_8igzTw_000161.mp4 playing djembe +tests/VGGSound/video/jj4EkRkf4Rs_000038.mp4 car engine idling +tests/VGGSound/video/mywsmUl_07o_000020.mp4 playing cello +tests/VGGSound/video/jjkB91FBcBI_000119.mp4 fly, housefly buzzing +tests/VGGSound/video/jjobvHzPstY_000020.mp4 typing on typewriter +tests/VGGSound/video/mzAfTmC3It0_000030.mp4 playing snare drum +tests/VGGSound/video/jkUcFF4VmO4_000022.mp4 bouncing on trampoline +tests/VGGSound/video/mzjPED4K-s4_000127.mp4 cuckoo bird calling +tests/VGGSound/video/jkvXuu8XltI_000080.mp4 helicopter +tests/VGGSound/video/mzw5MWr-SZY_000300.mp4 mosquito buzzing +tests/VGGSound/video/n-1ho8xiSGU_000002.mp4 beat boxing +tests/VGGSound/video/n-A3BJEpmz8_000010.mp4 sailing +tests/VGGSound/video/jlSuqrGSWAk_000370.mp4 basketball bounce +tests/VGGSound/video/n-eMAdCZnNI_000030.mp4 sloshing water +tests/VGGSound/video/jlgz0tRGQYM_000010.mp4 machine gun shooting +tests/VGGSound/video/n-tBbgUkFxo_000021.mp4 woodpecker pecking tree +tests/VGGSound/video/n-tBbgUkFxo_000032.mp4 woodpecker pecking tree +tests/VGGSound/video/jlmyAZSidOQ_000290.mp4 toilet flushing +tests/VGGSound/video/n0Bbn5VNaMg_000043.mp4 playing bass drum +tests/VGGSound/video/jm4ipHk0QX4_000001.mp4 children shouting +tests/VGGSound/video/n0cQ9m7SXqU_000135.mp4 donkey, ass braying +tests/VGGSound/video/n156ypVdysY_000449.mp4 golf driving +tests/VGGSound/video/n1VpqsLRy1E_000006.mp4 gibbon howling +tests/VGGSound/video/n1fY-23ffl0_000240.mp4 playing mandolin +tests/VGGSound/video/jna6r3skNeg_000180.mp4 pigeon, dove cooing +tests/VGGSound/video/jnrA1sig4t8_000020.mp4 ocean burbling +tests/VGGSound/video/n2JanKszFoQ_000200.mp4 playing cello +tests/VGGSound/video/joVUa4PjmhU_000200.mp4 playing steelpan +tests/VGGSound/video/jomEE8zBjlg_000022.mp4 people whistling +tests/VGGSound/video/n3KI7wQaDXI_000130.mp4 people eating apple +tests/VGGSound/video/n3Pfv9Fo3zk_000009.mp4 cat growling +tests/VGGSound/video/jpEcGnA4tco_000322.mp4 barn swallow calling +tests/VGGSound/video/jpGLGUsbHPU_000170.mp4 church bell ringing +tests/VGGSound/video/jpHrNr6bDmU_000230.mp4 playing electronic organ +tests/VGGSound/video/n3rUVrPeFAQ_000135.mp4 elephant trumpeting +tests/VGGSound/video/n3t92d8Xgp8_000020.mp4 typing on typewriter +tests/VGGSound/video/n4-THBrsn4o_000106.mp4 coyote howling +tests/VGGSound/video/n4-THBrsn4o_000123.mp4 coyote howling +tests/VGGSound/video/jpvK6ACozAY_000030.mp4 chainsawing trees +tests/VGGSound/video/n4SP34zUHu8_000388.mp4 elk bugling +tests/VGGSound/video/n4jf0RXGw7I_000019.mp4 canary calling +tests/VGGSound/video/n4ppElF9kQE_000002.mp4 eagle screaming +tests/VGGSound/video/jqqjc0XrU58_000092.mp4 playing djembe +tests/VGGSound/video/n51vOkMOXdQ_000039.mp4 yodelling +tests/VGGSound/video/jr1v6zC2ejk_000330.mp4 cupboard opening or closing +tests/VGGSound/video/jr2kxASSRBY_000030.mp4 baby crying +tests/VGGSound/video/n5SqYqXBMXQ_000005.mp4 playing oboe +tests/VGGSound/video/n5cvuVxjDoI_000098.mp4 canary calling +tests/VGGSound/video/jrXzvQLuC-c_000000.mp4 underwater bubbling +tests/VGGSound/video/n5waffUQuxU_000382.mp4 playing volleyball +tests/VGGSound/video/jrwhxVnvMdk_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/n6OjK7igcg0_000051.mp4 playing darts +tests/VGGSound/video/n6SvDBZaCUQ_000000.mp4 ambulance siren +tests/VGGSound/video/jtRq_vXe9uQ_000246.mp4 lathe spinning +tests/VGGSound/video/n7t58h1fwc0_000168.mp4 playing cornet +tests/VGGSound/video/jtfG2FbwINE_000121.mp4 people giggling +tests/VGGSound/video/jtlOOOTpZYM_000263.mp4 arc welding 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+tests/VGGSound/video/jw-9ndWahTg_000001.mp4 sea lion barking +tests/VGGSound/video/jw7wqfei3Fw_000020.mp4 vacuum cleaner cleaning floors +tests/VGGSound/video/jwZHGy2SI88_000215.mp4 driving snowmobile +tests/VGGSound/video/nB7FX1TBv34_000030.mp4 playing french horn +tests/VGGSound/video/jwxvQraiIGs_000032.mp4 pheasant crowing +tests/VGGSound/video/jwxvQraiIGs_000084.mp4 pheasant crowing +tests/VGGSound/video/nBM7eqh4C0Q_000055.mp4 whale calling +tests/VGGSound/video/nBV-l2UuGFo_000081.mp4 slot machine +tests/VGGSound/video/jxC-0T5lXw4_000250.mp4 using sewing machines +tests/VGGSound/video/nBuw_KZXT_k_000010.mp4 people coughing +tests/VGGSound/video/jxHGWVlnSUI_000108.mp4 whale calling +tests/VGGSound/video/jxS2922zU88_000053.mp4 elephant trumpeting +tests/VGGSound/video/jxaMR0I4YSY_000016.mp4 skidding +tests/VGGSound/video/nC-c2cRp1ho_000677.mp4 police radio chatter +tests/VGGSound/video/nC1p4WWdMgY_000267.mp4 lip smacking +tests/VGGSound/video/nC1p4WWdMgY_000316.mp4 lip smacking 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+tests/VGGSound/video/nJPOGVKPbcw_000210.mp4 waterfall burbling +tests/VGGSound/video/nJSmEj97SII_000691.mp4 hammering nails +tests/VGGSound/video/k3uGdspoVtg_000119.mp4 popping popcorn +tests/VGGSound/video/k45PjHhGXbo_000129.mp4 dinosaurs bellowing +tests/VGGSound/video/k4ExqQTNklk_000210.mp4 toilet flushing +tests/VGGSound/video/nKFa6uSX0_k_000060.mp4 baby babbling +tests/VGGSound/video/nKIxqC6L24k_000069.mp4 train whistling +tests/VGGSound/video/nKM-84B_FN8_000028.mp4 foghorn +tests/VGGSound/video/k4jbk1lVqB8_000162.mp4 people slurping +tests/VGGSound/video/k4k-ULQJzAI_000030.mp4 toilet flushing +tests/VGGSound/video/nKe3zn_yk94_000031.mp4 slot machine +tests/VGGSound/video/k5OqgeB7bvo_000207.mp4 tornado roaring +tests/VGGSound/video/nLKEdmVu3FY_000040.mp4 orchestra +tests/VGGSound/video/k5rDbr_0Ik8_000200.mp4 forging swords +tests/VGGSound/video/nLjl6I4astk_000717.mp4 people marching +tests/VGGSound/video/nLyeNi7WnrY_000010.mp4 playing flute +tests/VGGSound/video/k6ROAVZxzqM_000017.mp4 sea lion barking +tests/VGGSound/video/nLzSz0qDT68_000010.mp4 police car (siren) +tests/VGGSound/video/nMOlAg-Kjf8_000017.mp4 playing trombone +tests/VGGSound/video/nMT7ANtG8cA_000117.mp4 swimming +tests/VGGSound/video/nMU8Ypq7fjw_000070.mp4 hedge trimmer running +tests/VGGSound/video/nMUUYby3ZQQ_000064.mp4 airplane flyby +tests/VGGSound/video/k7WzaCeUIrI_000136.mp4 people humming +tests/VGGSound/video/nMoJVla31tc_000120.mp4 splashing water +tests/VGGSound/video/k7rGUmOV6wQ_000261.mp4 shot football +tests/VGGSound/video/k7vN56aM7sE_000030.mp4 bird chirping, tweeting +tests/VGGSound/video/nNHE-JTZL4Y_000078.mp4 parrot talking +tests/VGGSound/video/nNI2yUaXclM_000074.mp4 eagle screaming +tests/VGGSound/video/k81ocZGxQ4c_000110.mp4 bathroom ventilation fan running +tests/VGGSound/video/nNI2yUaXclM_000168.mp4 eagle screaming +tests/VGGSound/video/k8YMZkfLIvE_000319.mp4 playing tambourine +tests/VGGSound/video/nNxzM0aVlF0_000080.mp4 playing harp +tests/VGGSound/video/k8lCsWaHiko_000030.mp4 goose honking +tests/VGGSound/video/k8nX_e6MK9w_000067.mp4 playing badminton +tests/VGGSound/video/k91ukyGncNI_000077.mp4 baby crying +tests/VGGSound/video/nOr0M1EXZSg_000200.mp4 tornado roaring +tests/VGGSound/video/k9ULTEUI7gs_000035.mp4 opening or closing car doors +tests/VGGSound/video/k9bi4ygv1m0_000033.mp4 cat hissing +tests/VGGSound/video/kA8ZUNl5vss_000030.mp4 people sneezing +tests/VGGSound/video/kAE_Lb-f39I_000007.mp4 dog baying +tests/VGGSound/video/kAHzcdl4qXY_000601.mp4 playing volleyball +tests/VGGSound/video/kAOsa6_9wBY_000103.mp4 spraying water +tests/VGGSound/video/nPszP0u7qdg_000021.mp4 cell phone buzzing +tests/VGGSound/video/kC34iOvwo40_000293.mp4 playing tympani +tests/VGGSound/video/nRMmafPUAEU_000080.mp4 people screaming +tests/VGGSound/video/kCX1Kn-5C44_000050.mp4 cell phone buzzing +tests/VGGSound/video/nRZ4Vi-4qMQ_000000.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/kCy30T5bh74_000042.mp4 cutting hair with electric trimmers +tests/VGGSound/video/nSBDyxxscks_000220.mp4 female speech, woman speaking +tests/VGGSound/video/nSBO3brcr58_000225.mp4 volcano explosion +tests/VGGSound/video/nSMZD-CIi30_000044.mp4 gibbon howling +tests/VGGSound/video/nSoebc2LfAo_000530.mp4 cricket chirping +tests/VGGSound/video/kDqQCjkuxuo_000090.mp4 playing ukulele +tests/VGGSound/video/nTcGKRvqIbM_000003.mp4 chicken clucking +tests/VGGSound/video/kEMNy7-6le8_000030.mp4 playing accordion +tests/VGGSound/video/nTkRP49OtCs_000159.mp4 people gargling +tests/VGGSound/video/kEa1IlvIW0k_000039.mp4 playing tambourine +tests/VGGSound/video/nTtxF9Wyw6o_000030.mp4 playing synthesizer +tests/VGGSound/video/kEnOc-apG_o_000078.mp4 beat boxing +tests/VGGSound/video/nU7x170OvJ4_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/kFZhc_d-2V4_000370.mp4 lighting firecrackers +tests/VGGSound/video/nUdUlJtyPcg_000233.mp4 chopping food +tests/VGGSound/video/nUp8SPAWYFo_000070.mp4 bird squawking +tests/VGGSound/video/nUpVb7dWnVc_000030.mp4 magpie calling +tests/VGGSound/video/nUs5SJyQPnM_000350.mp4 playing sitar +tests/VGGSound/video/kG64kC8XlR8_000490.mp4 subway, metro, underground +tests/VGGSound/video/nVAuOCnzv08_000030.mp4 cat purring +tests/VGGSound/video/kGCW-Aw_0Xg_000005.mp4 footsteps on snow +tests/VGGSound/video/nVf6lDcm_Z4_000100.mp4 bird squawking +tests/VGGSound/video/nVpU4g6jWu8_000030.mp4 turkey gobbling +tests/VGGSound/video/kGo-dAQXtsA_000025.mp4 tapping guitar +tests/VGGSound/video/kGwrxzwJdRA_000030.mp4 people babbling +tests/VGGSound/video/nWlDkrIzc0g_000530.mp4 machine gun shooting +tests/VGGSound/video/nWld0wzTZ7E_000112.mp4 shot football +tests/VGGSound/video/kH6Z9sSDc3U_000000.mp4 car engine idling +tests/VGGSound/video/kH6fFjIZkB0_000030.mp4 reversing beeps +tests/VGGSound/video/kHCleUsjw3g_000030.mp4 pig oinking +tests/VGGSound/video/kHNWRR0hJ08_000022.mp4 chainsawing trees +tests/VGGSound/video/nXY2Vrfm0vY_000001.mp4 slot machine +tests/VGGSound/video/kHum8R_CcR0_000091.mp4 airplane +tests/VGGSound/video/kI04KR_InWQ_000000.mp4 gibbon howling +tests/VGGSound/video/nXtEwct1VUE_000022.mp4 people cheering +tests/VGGSound/video/kIG_vvycI0g_000285.mp4 shot football +tests/VGGSound/video/kINKoZD2m-M_000093.mp4 strike lighter +tests/VGGSound/video/nYM95RKzxEs_000235.mp4 playing shofar +tests/VGGSound/video/kIYqf7kHzFU_000030.mp4 people eating +tests/VGGSound/video/kIphX0k-ED4_000059.mp4 children shouting +tests/VGGSound/video/kJ1AWz_mhmE_000030.mp4 car engine knocking +tests/VGGSound/video/kJ3G_kQXiYs_000188.mp4 blowtorch igniting +tests/VGGSound/video/nYt4AoZTVFE_000013.mp4 playing castanets +tests/VGGSound/video/nZ6QXWP3XJI_000180.mp4 playing mandolin +tests/VGGSound/video/nZAkDZIEVlY_000294.mp4 air conditioning noise +tests/VGGSound/video/kJaUTXwvy7o_000030.mp4 playing bagpipes +tests/VGGSound/video/nZoC4wf7k9Y_000160.mp4 playing gong +tests/VGGSound/video/nZu-pLopvtw_000220.mp4 typing on typewriter +tests/VGGSound/video/kK4aLN6sn0A_000056.mp4 civil defense siren +tests/VGGSound/video/kKMK_8N0klM_000011.mp4 cheetah chirrup +tests/VGGSound/video/kKPQ2keMp-4_000193.mp4 playing timbales +tests/VGGSound/video/n_MNkvDX5Dk_000170.mp4 playing gong +tests/VGGSound/video/kKTBsC_L8kE_000176.mp4 playing snare drum +tests/VGGSound/video/kKTBsC_L8kE_000677.mp4 playing snare drum +tests/VGGSound/video/kKafEAL6m7A_000236.mp4 sharpen knife +tests/VGGSound/video/kKihNQ44dDQ_000100.mp4 playing bass guitar +tests/VGGSound/video/n_cWAuLcUKQ_000043.mp4 people slapping +tests/VGGSound/video/kKqIgmARIoA_000030.mp4 owl hooting +tests/VGGSound/video/kKrcq_JPMFM_000162.mp4 lip smacking +tests/VGGSound/video/n_k5FKt3X64_000030.mp4 sloshing water +tests/VGGSound/video/kLNtUnSm7lc_000060.mp4 subway, metro, underground +tests/VGGSound/video/naOF_vNjzxU_000024.mp4 people eating noodle +tests/VGGSound/video/naR97KBQ4y0_000030.mp4 goat bleating +tests/VGGSound/video/naXplhurrCU_000088.mp4 whale calling +tests/VGGSound/video/kLXnAOe7U0U_000015.mp4 playing bongo +tests/VGGSound/video/kL_-XdzJQ3g_000000.mp4 people coughing +tests/VGGSound/video/naaS0yiZ2pA_000054.mp4 chopping food +tests/VGGSound/video/kLsZZrklCGw_000027.mp4 mouse clicking +tests/VGGSound/video/kLsZZrklCGw_000071.mp4 mouse clicking +tests/VGGSound/video/kLtAyepYMZ4_000010.mp4 waterfall burbling +tests/VGGSound/video/navn7jCBp_o_000120.mp4 playing steelpan +tests/VGGSound/video/kLySMIzASNE_000030.mp4 typing on typewriter +tests/VGGSound/video/kMM-QZptLmE_000540.mp4 church bell ringing +tests/VGGSound/video/nbPY6Y1ffgo_000040.mp4 people cheering +tests/VGGSound/video/nbS9NjA7Ywg_000078.mp4 squishing water +tests/VGGSound/video/kMqmT6WFe2s_000282.mp4 shot football +tests/VGGSound/video/nb_7c2xPKYA_000400.mp4 playing mandolin +tests/VGGSound/video/nbdm5Cs2ug4_000006.mp4 bathroom ventilation fan running +tests/VGGSound/video/kNKfoDp0uUw_000030.mp4 driving buses +tests/VGGSound/video/nbjXrDmWMQg_000184.mp4 playing erhu +tests/VGGSound/video/kNW4IaBjX9o_000019.mp4 heart sounds, heartbeat +tests/VGGSound/video/nbq_65qlNQs_000156.mp4 cutting hair with electric trimmers +tests/VGGSound/video/nbuyVi6v7SY_000030.mp4 firing cannon +tests/VGGSound/video/ncHAOlb2wgw_000019.mp4 coyote howling +tests/VGGSound/video/ncHAOlb2wgw_000068.mp4 coyote howling +tests/VGGSound/video/ncJgdczUs_8_000000.mp4 bird squawking +tests/VGGSound/video/ncVm9aZPbHg_000095.mp4 missile launch +tests/VGGSound/video/kO6CR2aAM3I_000024.mp4 hair dryer drying +tests/VGGSound/video/kO8TVRcXI98_000303.mp4 elk bugling +tests/VGGSound/video/ncfUAo5uxwk_000012.mp4 people booing +tests/VGGSound/video/kOHIIEOam_8_000000.mp4 roller coaster running +tests/VGGSound/video/nd40lIYtQmA_000138.mp4 playing table tennis +tests/VGGSound/video/nd40lIYtQmA_000228.mp4 playing table tennis +tests/VGGSound/video/kO_VmIHmggc_000045.mp4 cuckoo bird calling +tests/VGGSound/video/kOheqjodDmw_000050.mp4 people coughing +tests/VGGSound/video/kOkmzQhIyXY_000210.mp4 people gargling +tests/VGGSound/video/kP5V1uJct5A_000031.mp4 fly, housefly buzzing +tests/VGGSound/video/neDB4I93EZI_000030.mp4 female speech, woman speaking +tests/VGGSound/video/neLRPsl8-XA_000140.mp4 driving buses +tests/VGGSound/video/negr4U79PUE_000270.mp4 playing bass guitar +tests/VGGSound/video/kQ2cRYlbdMc_000029.mp4 elk bugling +tests/VGGSound/video/kQ7tkcg8Xag_000300.mp4 people marching +tests/VGGSound/video/kQ7tkcg8Xag_000415.mp4 people marching +tests/VGGSound/video/kQDKsJ7piLU_000039.mp4 baltimore oriole calling +tests/VGGSound/video/nf9NQGhq2rY_000048.mp4 playing snare drum +tests/VGGSound/video/kQQrsmLvoCE_000120.mp4 dog howling +tests/VGGSound/video/nfFldYRXbDM_000098.mp4 playing djembe +tests/VGGSound/video/nfdEqi5YMjk_000210.mp4 playing drum kit +tests/VGGSound/video/kQ_5qrWH7v4_000338.mp4 airplane flyby +tests/VGGSound/video/nfitcQXx-Y0_000020.mp4 gibbon howling +tests/VGGSound/video/kQbPRaBLQRA_000158.mp4 firing muskets +tests/VGGSound/video/nfitcQXx-Y0_000058.mp4 gibbon howling +tests/VGGSound/video/nfzZeT_liEQ_000130.mp4 hair dryer drying +tests/VGGSound/video/kRoKSjo1ONs_000226.mp4 people eating noodle +tests/VGGSound/video/kRqRKQoKluE_000033.mp4 snake hissing +tests/VGGSound/video/kSE2Lav5ZCs_000120.mp4 goose honking +tests/VGGSound/video/nhAiQyirHe0_000127.mp4 wood thrush calling +tests/VGGSound/video/nhDAmqYHxdA_000417.mp4 squishing water +tests/VGGSound/video/kSKXtXXAD70_000030.mp4 printer printing +tests/VGGSound/video/kSLcpzvKJ1U_000322.mp4 heart sounds, heartbeat +tests/VGGSound/video/kSeiFzV1J9w_000110.mp4 people finger snapping +tests/VGGSound/video/kShykuz60oA_000036.mp4 police car (siren) +tests/VGGSound/video/nhYrHtdEeXw_000010.mp4 fireworks banging +tests/VGGSound/video/nhe959Sn-JU_000009.mp4 otter growling +tests/VGGSound/video/kSjvt2Z_pBo_000030.mp4 ambulance siren +tests/VGGSound/video/nhxCeq3sg2U_000153.mp4 police radio chatter +tests/VGGSound/video/kTOX4xMk89M_000100.mp4 train whistling +tests/VGGSound/video/kTS0z-5T0nc_000027.mp4 playing guiro +tests/VGGSound/video/niO21pQgixA_000001.mp4 hail +tests/VGGSound/video/kTflV6v77qU_000043.mp4 beat boxing +tests/VGGSound/video/kTizt7af0PE_000020.mp4 playing djembe +tests/VGGSound/video/kTu8XtF-gzc_000057.mp4 rope skipping +tests/VGGSound/video/nj6_A9IY8jA_000085.mp4 roller coaster running +tests/VGGSound/video/kTyq_6AnoSw_000040.mp4 firing cannon +tests/VGGSound/video/kUIG2LX3zqY_000040.mp4 cattle, bovinae cowbell +tests/VGGSound/video/njPYTlo0oAc_000010.mp4 playing trombone +tests/VGGSound/video/kUR6_bQLU-E_000154.mp4 plastic bottle crushing +tests/VGGSound/video/njpsToHDHN0_000045.mp4 heart sounds, heartbeat +tests/VGGSound/video/kUvSPJkuNWE_000030.mp4 typing on typewriter +tests/VGGSound/video/nkVbTjlB0rs_000080.mp4 playing washboard +tests/VGGSound/video/kV9bDDyCiEM_000008.mp4 playing trumpet +tests/VGGSound/video/kVR18Eie7mM_000187.mp4 playing darts +tests/VGGSound/video/nlDpRreRKO4_000030.mp4 fireworks banging +tests/VGGSound/video/nlYlNF30bVg_000030.mp4 people screaming +tests/VGGSound/video/kVuG_F3qCuY_000176.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/nljhIF3wxz4_000035.mp4 playing table tennis +tests/VGGSound/video/kWPAWeNuBKc_000506.mp4 lathe spinning +tests/VGGSound/video/nmCg4Nw-bPA_000148.mp4 writing on blackboard with chalk +tests/VGGSound/video/nmMqbo6pcTU_000144.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/nmMvKTSIvSE_000202.mp4 bowling impact +tests/VGGSound/video/nmNgFcyQoRk_000000.mp4 lawn mowing +tests/VGGSound/video/kW_dSjvD3fg_000003.mp4 people shuffling +tests/VGGSound/video/kWdmJHAFMxk_000031.mp4 electric grinder grinding +tests/VGGSound/video/nmRMfbrXwt0_000001.mp4 electric shaver, electric razor shaving +tests/VGGSound/video/kWh2ty55r_E_000580.mp4 church bell ringing +tests/VGGSound/video/kWntScEF5_c_000014.mp4 chopping wood +tests/VGGSound/video/kX4-OMWCdCc_000150.mp4 playing cello +tests/VGGSound/video/nmp9yqhsjqg_000350.mp4 playing piano +tests/VGGSound/video/kXAfPnwvchE_000111.mp4 playing djembe +tests/VGGSound/video/nmyh0HX45EY_000155.mp4 smoke detector beeping +tests/VGGSound/video/kXLwb3bvCKo_000080.mp4 bird squawking +tests/VGGSound/video/nn25vUXHhdE_000400.mp4 skidding +tests/VGGSound/video/kXQNBY7Wa14_000030.mp4 wind rustling leaves +tests/VGGSound/video/nn5WR8xkcVM_000313.mp4 bouncing on trampoline +tests/VGGSound/video/kXkwTwKkC9o_001138.mp4 playing tuning fork +tests/VGGSound/video/kY5sWKso__o_000160.mp4 splashing water +tests/VGGSound/video/kY6RTq-DSew_000013.mp4 people nose blowing +tests/VGGSound/video/nnkzdwz1D8Q_000280.mp4 cricket chirping +tests/VGGSound/video/kYV-JxDfdYM_000080.mp4 playing piano +tests/VGGSound/video/kYXS4eqiMyA_000507.mp4 train whistling +tests/VGGSound/video/kYs6dijZaY8_000108.mp4 magpie calling +tests/VGGSound/video/no6AAqgGIv8_000150.mp4 bird wings flapping +tests/VGGSound/video/kYvoPTLXwwE_000000.mp4 sliding door +tests/VGGSound/video/kYvyOw8ZDS4_000016.mp4 bull bellowing +tests/VGGSound/video/noH950QMOLg_000198.mp4 playing snare drum +tests/VGGSound/video/kZ3KwoFNklY_000063.mp4 people slapping +tests/VGGSound/video/noN35nW5gl4_000000.mp4 cattle mooing +tests/VGGSound/video/kZAwXjidHmM_000001.mp4 people sneezing +tests/VGGSound/video/noXur3qKPQY_000280.mp4 playing tympani +tests/VGGSound/video/kZQkCqkUBVA_000168.mp4 people slurping +tests/VGGSound/video/nokwrsZW6YE_000308.mp4 writing on blackboard with chalk +tests/VGGSound/video/kZegES0woJo_000035.mp4 snake hissing +tests/VGGSound/video/nou1eQNbW30_000002.mp4 parrot talking +tests/VGGSound/video/npcdmOfFZis_000050.mp4 playing harmonica +tests/VGGSound/video/k_WVsQIocmI_000182.mp4 yodelling +tests/VGGSound/video/nqHztbgP_4U_000100.mp4 pigeon, dove cooing +tests/VGGSound/video/k_ry9us3pAQ_000090.mp4 people sneezing +tests/VGGSound/video/nqd6uO6hDSo_000030.mp4 dog howling +tests/VGGSound/video/nqgT85S5Rno_000110.mp4 playing double bass +tests/VGGSound/video/kaHPxMgc6vY_000026.mp4 police car (siren) +tests/VGGSound/video/nqj-gzVhkQY_000021.mp4 cattle mooing +tests/VGGSound/video/nqnviB5WXSM_000030.mp4 dog whimpering +tests/VGGSound/video/kaYBmFJzseo_000030.mp4 playing gong +tests/VGGSound/video/nqsycWEgIio_000209.mp4 parrot talking +tests/VGGSound/video/kanqhIJjNk4_000011.mp4 striking bowling +tests/VGGSound/video/kaz5auB2okE_000126.mp4 people gargling +tests/VGGSound/video/nrWb1MVZY0g_000153.mp4 people slapping +tests/VGGSound/video/kb0m_n54vcY_000172.mp4 playing volleyball +tests/VGGSound/video/kb3tfk8dxvU_000030.mp4 firing cannon +tests/VGGSound/video/nrfhuA6L3E4_000094.mp4 sea lion barking +tests/VGGSound/video/kbCh5HrmgN0_000080.mp4 playing steelpan +tests/VGGSound/video/kbPEgFG0sxc_000030.mp4 duck quacking +tests/VGGSound/video/ns9o7NoLVr8_000030.mp4 playing shofar +tests/VGGSound/video/nsF7XYUGx7g_000308.mp4 tornado roaring +tests/VGGSound/video/nsNtEAfJfd0_000055.mp4 playing castanets +tests/VGGSound/video/kbs7SQMR1ek_000248.mp4 airplane +tests/VGGSound/video/nsgI3a1ZodQ_000014.mp4 playing hockey +tests/VGGSound/video/nstNNjnev5k_000827.mp4 playing bass drum +tests/VGGSound/video/kcVxxsZdhds_000030.mp4 goose honking +tests/VGGSound/video/nt9PKJU4LLk_000047.mp4 child singing +tests/VGGSound/video/ntfgS4Tdpmg_000540.mp4 playing harp +tests/VGGSound/video/ntfyeC178Tg_000030.mp4 playing vibraphone +tests/VGGSound/video/kdAs1Kcttvw_000030.mp4 mouse pattering +tests/VGGSound/video/ntmttPBZemM_000416.mp4 forging swords +tests/VGGSound/video/ntqyUbRYiOc_000030.mp4 duck quacking +tests/VGGSound/video/nttdTFHmH3g_000028.mp4 chopping food +tests/VGGSound/video/nu47dWioSZM_000060.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/kdanFLQ7A_s_000000.mp4 playing cymbal +tests/VGGSound/video/kdbA6lP1bmU_000037.mp4 missile launch +tests/VGGSound/video/kdfC_yWnkHw_000033.mp4 skiing +tests/VGGSound/video/nup1eVraTqE_000152.mp4 sharpen knife +tests/VGGSound/video/keLE6HCvm4o_000030.mp4 playing sitar +tests/VGGSound/video/keVZ4cpnWXU_000490.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/nvIIa2B7P_0_000440.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/nvT6R77PBKc_000010.mp4 snake hissing +tests/VGGSound/video/kf0YrFpuNKQ_000030.mp4 machine gun shooting +tests/VGGSound/video/nvd_moe8RQ0_000030.mp4 sliding door +tests/VGGSound/video/kfa-8WSjCxY_000030.mp4 people eating apple +tests/VGGSound/video/nvvXOfLs-ng_000150.mp4 playing ukulele +tests/VGGSound/video/kfl9X8KIMTg_000000.mp4 playing electronic organ +tests/VGGSound/video/nwORnZ_cvMY_000010.mp4 warbler chirping +tests/VGGSound/video/nwT3Euwx7uU_000114.mp4 heart sounds, heartbeat +tests/VGGSound/video/nwdZrUBojGs_000100.mp4 playing vibraphone +tests/VGGSound/video/kgf4GdKlSWs_000030.mp4 playing ukulele +tests/VGGSound/video/kh77cZfsDvc_000037.mp4 bull bellowing +tests/VGGSound/video/kh77cZfsDvc_000089.mp4 bull bellowing +tests/VGGSound/video/khAfL-JGSkI_000323.mp4 people gargling +tests/VGGSound/video/khC7ed0_Kvs_000190.mp4 people coughing +tests/VGGSound/video/nxklbthehL0_000100.mp4 people cheering +tests/VGGSound/video/khfvz1zD9HY_000107.mp4 plastic bottle crushing +tests/VGGSound/video/ny0RU5o_A_4_000000.mp4 scuba diving +tests/VGGSound/video/khgvtI-pnOE_000012.mp4 barn swallow calling +tests/VGGSound/video/ny11DBcW3hI_000019.mp4 playing timbales +tests/VGGSound/video/ny4wkNf3P40_000001.mp4 fox barking +tests/VGGSound/video/kiA86HI-GLU_000140.mp4 playing zither +tests/VGGSound/video/kiAMVnSBGw0_000030.mp4 male speech, man speaking +tests/VGGSound/video/nyVzNA-Xasg_000450.mp4 goose honking +tests/VGGSound/video/nyWoGpyQD4A_000082.mp4 playing lacrosse +tests/VGGSound/video/nygHRktgEmw_000160.mp4 sloshing water +tests/VGGSound/video/kie47qxRmEQ_000566.mp4 forging swords +tests/VGGSound/video/kim5sxAzWM0_000022.mp4 striking bowling +tests/VGGSound/video/kjGjMDpTzvs_000320.mp4 eating with cutlery +tests/VGGSound/video/nzpnWuk3RjU_000170.mp4 playing timpani +tests/VGGSound/video/nzrNxN3vG1w_000030.mp4 female singing +tests/VGGSound/video/nzwmPWAAQFg_000030.mp4 baby crying +tests/VGGSound/video/o-HDwb0wIXA_000066.mp4 electric grinder grinding +tests/VGGSound/video/o-xlfN7kkOA_000030.mp4 playing ukulele +tests/VGGSound/video/o0Aq9oY4JNk_000006.mp4 playing violin, fiddle +tests/VGGSound/video/o0Bn4m6dQbI_000100.mp4 playing accordion +tests/VGGSound/video/kl2E2erlkRg_000050.mp4 playing flute +tests/VGGSound/video/kl3HZbyUNys_000030.mp4 chicken clucking +tests/VGGSound/video/o0Sb9ZZaZa0_000000.mp4 opening or closing car doors +tests/VGGSound/video/o0auMW1-gjE_000458.mp4 people slurping +tests/VGGSound/video/klExMKT88MQ_000160.mp4 playing electronic organ +tests/VGGSound/video/o0iBZi-ARq0_000067.mp4 roller coaster running +tests/VGGSound/video/o0mATRdzZSc_000050.mp4 wood thrush calling +tests/VGGSound/video/o1K1Bpk08ig_000020.mp4 car engine knocking +tests/VGGSound/video/o1T_hzWDymk_000254.mp4 mynah bird singing +tests/VGGSound/video/kmMPfIR46aI_000123.mp4 writing on blackboard with chalk +tests/VGGSound/video/o1psbzO1YPU_000065.mp4 fly, housefly buzzing +tests/VGGSound/video/kmV2hj-I7Xo_000097.mp4 playing violin, fiddle +tests/VGGSound/video/o1zsMr2DL_I_000019.mp4 tornado roaring +tests/VGGSound/video/kmktokIWVMQ_000017.mp4 zebra braying +tests/VGGSound/video/kmvLXRZp5oI_000163.mp4 playing bongo +tests/VGGSound/video/o2x75MH0G08_000030.mp4 playing cymbal +tests/VGGSound/video/o2y4WuK8wr8_000250.mp4 bird wings flapping +tests/VGGSound/video/o3F3tUpmVaw_000030.mp4 police car (siren) +tests/VGGSound/video/o3HACXmd6xo_000042.mp4 people eating crisps +tests/VGGSound/video/knzA9iuVOdw_000010.mp4 lawn mowing +tests/VGGSound/video/o3OBabEppEA_000075.mp4 striking bowling +tests/VGGSound/video/o3cRTYrLXnk_000046.mp4 foghorn +tests/VGGSound/video/o3qLyDuP37w_000000.mp4 thunder +tests/VGGSound/video/o46GWTkVASI_000030.mp4 wind rustling leaves +tests/VGGSound/video/koUiidVz8-E_000061.mp4 sheep bleating +tests/VGGSound/video/koUnrPY_3n8_000007.mp4 cricket chirping +tests/VGGSound/video/o4HqWhVTW2o_000000.mp4 playing washboard +tests/VGGSound/video/o4HqWhVTW2o_000043.mp4 playing washboard +tests/VGGSound/video/korCJgM6ex4_000054.mp4 cuckoo bird calling +tests/VGGSound/video/korCJgM6ex4_000081.mp4 cuckoo bird calling +tests/VGGSound/video/o4SLkvEa8Mk_000184.mp4 popping popcorn +tests/VGGSound/video/kp5PZawm-X4_000046.mp4 people gargling +tests/VGGSound/video/kpBkoalXnXM_000228.mp4 people gargling +tests/VGGSound/video/o4Z9DJi8AJo_000050.mp4 people hiccup +tests/VGGSound/video/kpNBSTCVEx4_000082.mp4 playing violin, fiddle +tests/VGGSound/video/kpRmoK3V6NQ_000049.mp4 striking pool +tests/VGGSound/video/o505NNzv0TI_000035.mp4 playing timbales +tests/VGGSound/video/o5LsmKXZTCQ_000030.mp4 people sniggering +tests/VGGSound/video/kpqMjTYU64g_000253.mp4 fly, housefly buzzing +tests/VGGSound/video/kprADc7y-rE_000002.mp4 playing tuning fork +tests/VGGSound/video/kps82JmgoVg_000074.mp4 airplane +tests/VGGSound/video/kpsYSXR1wao_000300.mp4 playing accordion +tests/VGGSound/video/kq6PDicCx9Q_000084.mp4 playing timbales +tests/VGGSound/video/kqC9pgKN--c_000365.mp4 ripping paper +tests/VGGSound/video/kqMKI1W3YRU_000054.mp4 fox barking +tests/VGGSound/video/kqcMkJGvx-E_000104.mp4 police radio chatter +tests/VGGSound/video/kqnxnbVbO5Q_000023.mp4 playing lacrosse +tests/VGGSound/video/o7I9BknIZKY_000256.mp4 playing squash +tests/VGGSound/video/o7I9BknIZKY_000416.mp4 playing squash +tests/VGGSound/video/kr8ssbrDDMY_000030.mp4 fire truck siren +tests/VGGSound/video/o7QGPyy4lvs_000089.mp4 playing badminton +tests/VGGSound/video/o7UGDvP1lhk_000563.mp4 planing timber +tests/VGGSound/video/o7iSjJZYr5A_000000.mp4 ripping paper +tests/VGGSound/video/o7jBSQRJzuQ_000023.mp4 cat growling +tests/VGGSound/video/krghmEqeJtU_000122.mp4 tap dancing +tests/VGGSound/video/krr95aiOUh8_000090.mp4 splashing water +tests/VGGSound/video/krwEhbbxSw4_000070.mp4 wind noise +tests/VGGSound/video/ks0EpvbEO7Y_000083.mp4 people sniggering +tests/VGGSound/video/o8JY_sqvaQc_000057.mp4 playing shofar +tests/VGGSound/video/o8JY_sqvaQc_000075.mp4 playing shofar +tests/VGGSound/video/ksCMf478CrE_000210.mp4 baby babbling +tests/VGGSound/video/ksHBqxzvbhM_000019.mp4 slot machine +tests/VGGSound/video/o8_9STVfnvI_000059.mp4 horse clip-clop +tests/VGGSound/video/kse2WhdmJq0_000030.mp4 shot football +tests/VGGSound/video/ksfpCXlY-hA_000100.mp4 popping popcorn +tests/VGGSound/video/ksk9rjj5WB0_000030.mp4 people shuffling +tests/VGGSound/video/o8uxxMXuhZ8_000030.mp4 people sniggering +tests/VGGSound/video/o9C7LfMo4zo_000000.mp4 people cheering +tests/VGGSound/video/o9Fiss83B1c_000557.mp4 people slurping +tests/VGGSound/video/ktGL1UtXXBw_000230.mp4 opening or closing car doors +tests/VGGSound/video/ktLR-WjB_C8_000044.mp4 ripping paper +tests/VGGSound/video/ktXc8h6LfvY_000030.mp4 rapping +tests/VGGSound/video/ktY_rsii-Pg_000030.mp4 duck quacking +tests/VGGSound/video/o9b54vMIu7c_000000.mp4 people cheering +tests/VGGSound/video/ktis2aZfphM_000010.mp4 playing cello +tests/VGGSound/video/ktso7GeckG8_000130.mp4 cattle, bovinae cowbell +tests/VGGSound/video/ktvOqV10lW0_000030.mp4 playing drum kit +tests/VGGSound/video/ktxdNOu2P4E_000011.mp4 lions growling +tests/VGGSound/video/oAOD7KIvkMk_000012.mp4 missile launch +tests/VGGSound/video/kuNDPraGm58_000004.mp4 footsteps on snow +tests/VGGSound/video/kuihSZXsIJ4_000030.mp4 car engine knocking +tests/VGGSound/video/kuszXUbEiIA_000014.mp4 francolin calling +tests/VGGSound/video/oAjBZqhxuOs_000100.mp4 dog growling +tests/VGGSound/video/kv335KZ0ZR8_000030.mp4 basketball bounce +tests/VGGSound/video/kvIt_9P79Ro_000030.mp4 pig oinking +tests/VGGSound/video/kvKMz_laff4_000055.mp4 volcano explosion +tests/VGGSound/video/oBY7XYM4gi0_000155.mp4 wood thrush calling +tests/VGGSound/video/oBsTZmqrpFQ_000070.mp4 playing drum kit +tests/VGGSound/video/oBxeVm_9GXY_000000.mp4 playing drum kit +tests/VGGSound/video/oCVRgGxkKo4_000090.mp4 people babbling +tests/VGGSound/video/kwJKOXT5XR8_000255.mp4 train wheels squealing +tests/VGGSound/video/kwPl5Nrc1zs_000212.mp4 cutting hair with electric trimmers +tests/VGGSound/video/kwPl5Nrc1zs_000279.mp4 cutting hair with electric trimmers +tests/VGGSound/video/oD0Xp--xxjE_000030.mp4 playing drum kit +tests/VGGSound/video/oD4bkJ2Suyo_000103.mp4 train horning +tests/VGGSound/video/kwgkbAGGORU_000090.mp4 people whistling +tests/VGGSound/video/kwsgIBkX-3k_000300.mp4 waterfall burbling +tests/VGGSound/video/kx25bJyyzMw_000410.mp4 singing bowl +tests/VGGSound/video/oDSMG0gcwzc_000165.mp4 dog baying +tests/VGGSound/video/kxTwZeZxuvo_000036.mp4 fly, housefly buzzing +tests/VGGSound/video/kxTwZeZxuvo_000099.mp4 fly, housefly buzzing +tests/VGGSound/video/kx_G2a2hL6U_000153.mp4 people sniggering +tests/VGGSound/video/kxkk4w2yzbk_000030.mp4 playing electronic organ +tests/VGGSound/video/oE2ei00EhWI_000063.mp4 snake hissing +tests/VGGSound/video/oE2ei00EhWI_000110.mp4 snake hissing 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+tests/VGGSound/video/l-iIfi3SNpw_000120.mp4 people screaming +tests/VGGSound/video/l-kcXXZIVLs_000190.mp4 playing cello +tests/VGGSound/video/oHp-J8QgAd8_000030.mp4 sliding door +tests/VGGSound/video/l-qyJLFOVYI_000000.mp4 cheetah chirrup +tests/VGGSound/video/l-s4_WiLAAw_000016.mp4 opening or closing car electric windows +tests/VGGSound/video/l0LSwtnLCsY_000081.mp4 shot football +tests/VGGSound/video/oIUof9ZzRcs_000001.mp4 chinchilla barking +tests/VGGSound/video/oIUof9ZzRcs_000018.mp4 chinchilla barking +tests/VGGSound/video/oIaNEBreHTI_000047.mp4 striking bowling +tests/VGGSound/video/oIgPIGUQ8yY_000030.mp4 playing trombone +tests/VGGSound/video/oInlR3rUanI_000080.mp4 cattle, bovinae cowbell +tests/VGGSound/video/l0wtTeAUdhI_000069.mp4 writing on blackboard with chalk +tests/VGGSound/video/l13XyX-sMwk_000406.mp4 lip smacking +tests/VGGSound/video/l13XyX-sMwk_001613.mp4 lip smacking +tests/VGGSound/video/l1NjISbLXY8_000017.mp4 playing squash +tests/VGGSound/video/l1NjISbLXY8_000214.mp4 playing squash +tests/VGGSound/video/l1S8rIqKfq4_000050.mp4 slot machine +tests/VGGSound/video/oJbeLScZK1o_000049.mp4 cat growling +tests/VGGSound/video/l1coM570kVw_000030.mp4 male singing +tests/VGGSound/video/oJe-kIzMuiU_000041.mp4 playing mandolin +tests/VGGSound/video/oJyyNWuyig4_000030.mp4 wind rustling leaves +tests/VGGSound/video/l1vEAtUWXHU_000034.mp4 dinosaurs bellowing +tests/VGGSound/video/oK2d2JF27Qk_000000.mp4 playing mandolin +tests/VGGSound/video/oKVfrZKftHs_000030.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/oKdF5E37uac_000196.mp4 ripping paper +tests/VGGSound/video/l2ONckkeGGQ_000115.mp4 civil defense siren +tests/VGGSound/video/l2oI7ZsKPKs_000084.mp4 hail +tests/VGGSound/video/l30pHj4I0Ps_000580.mp4 using sewing machines +tests/VGGSound/video/l3GbL9gwidg_000111.mp4 skiing +tests/VGGSound/video/oLUnCxodva0_000078.mp4 playing cornet +tests/VGGSound/video/oLYZ4FyktN0_000040.mp4 people sobbing +tests/VGGSound/video/l3abwXzDR1g_000030.mp4 playing electronic organ +tests/VGGSound/video/oMFZJxn9Yog_000102.mp4 people slapping +tests/VGGSound/video/oMOSgo1nT04_000011.mp4 playing tympani +tests/VGGSound/video/oMS_MSzv6cg_000030.mp4 mouse pattering +tests/VGGSound/video/l4iBXc4x-WY_000004.mp4 tap dancing +tests/VGGSound/video/l4yv0-9H7nU_000270.mp4 lawn mowing +tests/VGGSound/video/l52-LCtXNeE_000010.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/l59Gy1sqDSM_000003.mp4 people giggling +tests/VGGSound/video/oNXXcLtvuoA_000238.mp4 people eating crisps +tests/VGGSound/video/oNj-Q5gtYz4_000030.mp4 typing on computer keyboard +tests/VGGSound/video/l5O87Umi7DI_000210.mp4 playing bass guitar +tests/VGGSound/video/oNp2zzKIhgk_000029.mp4 hedge trimmer running +tests/VGGSound/video/oNrtgNcQfas_000069.mp4 playing tuning fork +tests/VGGSound/video/oNyiXxPxENY_000196.mp4 ferret dooking +tests/VGGSound/video/oOBByUjJtLY_000000.mp4 playing gong +tests/VGGSound/video/l5g1RkSYZdw_000030.mp4 playing harmonica +tests/VGGSound/video/l5l0Awx8eeQ_000023.mp4 parrot talking +tests/VGGSound/video/oOiwmRV1PBk_000000.mp4 playing timpani +tests/VGGSound/video/l6HsxUNdkd4_000010.mp4 cap gun shooting +tests/VGGSound/video/oOoxb4Fr65k_000000.mp4 duck quacking +tests/VGGSound/video/l6N2qa0jUIU_000335.mp4 heart sounds, heartbeat +tests/VGGSound/video/l6RTgFxEWFY_000181.mp4 race car, auto racing +tests/VGGSound/video/oPBrZeFpToY_000090.mp4 baby laughter +tests/VGGSound/video/l6Z7BbaxEeM_000158.mp4 playing volleyball +tests/VGGSound/video/l6eWoKOAylA_000050.mp4 people finger snapping +tests/VGGSound/video/oPR7tUEUptk_000030.mp4 fire truck siren +tests/VGGSound/video/l6q7shFb8zs_000041.mp4 playing castanets +tests/VGGSound/video/oPlat3jrels_000120.mp4 playing trombone +tests/VGGSound/video/l70yarlcd-I_000029.mp4 fire truck siren +tests/VGGSound/video/l78ooOwvRyY_000000.mp4 toilet flushing +tests/VGGSound/video/oPzAaB7LoqU_000030.mp4 baby crying +tests/VGGSound/video/l7RTgupQWcc_000030.mp4 fireworks banging +tests/VGGSound/video/l7Wo_s7HFIY_000190.mp4 ambulance siren +tests/VGGSound/video/l7bje9Ay9Ig_000020.mp4 train wheels squealing +tests/VGGSound/video/l7oD9WX-1CU_000010.mp4 people sobbing +tests/VGGSound/video/l7xsreSdKHE_000020.mp4 rope skipping +tests/VGGSound/video/oR4pWUTh4Ns_000029.mp4 wood thrush calling +tests/VGGSound/video/l8huGsnYzus_000023.mp4 wind chime +tests/VGGSound/video/oRLzsvwP-0I_000030.mp4 wind noise +tests/VGGSound/video/l9ElMSuNwnI_000134.mp4 police radio chatter +tests/VGGSound/video/l9I2UmvDhpw_000326.mp4 roller coaster running +tests/VGGSound/video/l9J1v5htrHs_000050.mp4 chopping food +tests/VGGSound/video/l9L7_RaTw6I_000060.mp4 playing clarinet +tests/VGGSound/video/lA3KGYqG5rQ_000458.mp4 bull bellowing +tests/VGGSound/video/oSME-ts1WnQ_000110.mp4 dog growling +tests/VGGSound/video/lA3KGYqG5rQ_000484.mp4 bull bellowing +tests/VGGSound/video/oSUCIMc3Vp8_000055.mp4 people belly laughing +tests/VGGSound/video/lAA0QneMahs_000038.mp4 playing shofar +tests/VGGSound/video/lAF6nVFk6Is_000077.mp4 dog growling +tests/VGGSound/video/oSeytBzkBuA_000030.mp4 people eating +tests/VGGSound/video/lAQMH50jym8_000000.mp4 people belly laughing +tests/VGGSound/video/oSj9IbDiWks_000000.mp4 playing cymbal +tests/VGGSound/video/lAXpiE0dm_k_000340.mp4 playing piano +tests/VGGSound/video/oSqoyk9FenQ_000000.mp4 playing gong +tests/VGGSound/video/oT8Vg7egGwI_000043.mp4 people booing +tests/VGGSound/video/oT8Vg7egGwI_000077.mp4 people booing +tests/VGGSound/video/lAy3z-935w8_000019.mp4 playing hockey +tests/VGGSound/video/lAznHBBQkp4_000030.mp4 female speech, woman speaking +tests/VGGSound/video/lBG_42BAUs8_000224.mp4 opening or closing car doors +tests/VGGSound/video/oTfkeIJmkHw_000201.mp4 elk bugling +tests/VGGSound/video/oTfkeIJmkHw_000224.mp4 elk bugling +tests/VGGSound/video/lBZuY85aYKU_000048.mp4 sloshing water +tests/VGGSound/video/lBftiRlNTYI_000363.mp4 alarm clock ringing +tests/VGGSound/video/lBkMCUiitNU_000030.mp4 child singing +tests/VGGSound/video/lBm9NJCDgBU_000105.mp4 cuckoo bird calling +tests/VGGSound/video/lBo0SbWA9u0_000014.mp4 playing darts +tests/VGGSound/video/oU9hqerWWRw_000000.mp4 skidding +tests/VGGSound/video/lBzEk72sMr0_000370.mp4 eating with cutlery +tests/VGGSound/video/oUUTJref1jE_000500.mp4 playing french horn +tests/VGGSound/video/oU_MZilklxE_000188.mp4 cutting hair with electric trimmers +tests/VGGSound/video/oUaGeoOA6i0_000224.mp4 playing timbales +tests/VGGSound/video/oUovG1mLKv0_000147.mp4 running electric fan +tests/VGGSound/video/lDABsoatahM_000000.mp4 playing cello +tests/VGGSound/video/lDpJ-RBGMQc_000180.mp4 pumping water +tests/VGGSound/video/lDrPt18E7Rs_000118.mp4 popping popcorn +tests/VGGSound/video/oVcQgIsw2Ac_000030.mp4 playing accordion +tests/VGGSound/video/oVd-PG3vmQo_000013.mp4 car passing by +tests/VGGSound/video/oWAZJV6g6fY_000000.mp4 people farting +tests/VGGSound/video/lEOsGdslGO0_000397.mp4 chipmunk chirping +tests/VGGSound/video/oWYHKdf6N0E_000010.mp4 frog croaking +tests/VGGSound/video/oW_MNFMOM84_000000.mp4 snake rattling +tests/VGGSound/video/lEjV0us_eF0_000021.mp4 yodelling +tests/VGGSound/video/oWr0gGzyG98_000090.mp4 baby laughter +tests/VGGSound/video/lEqhWC0R38A_000030.mp4 playing flute +tests/VGGSound/video/lF1C6JSDZJU_000209.mp4 disc scratching +tests/VGGSound/video/oXiB2dl-7fw_000136.mp4 blowtorch igniting +tests/VGGSound/video/oXiGISLYBrM_000022.mp4 metronome +tests/VGGSound/video/lFM2QsQb6nA_000010.mp4 playing cymbal +tests/VGGSound/video/oY1T2xMn1pE_000082.mp4 bouncing on trampoline +tests/VGGSound/video/oY9G944VcmI_000534.mp4 playing erhu +tests/VGGSound/video/oYEzy8gH6q8_000030.mp4 tapping guitar +tests/VGGSound/video/oYFvyJtgE2E_000108.mp4 people nose blowing +tests/VGGSound/video/oYYd7duzdBY_000030.mp4 mouse pattering +tests/VGGSound/video/lGZKkiZEDBY_000003.mp4 alligators, crocodiles hissing +tests/VGGSound/video/lGZKkiZEDBY_000014.mp4 alligators, crocodiles hissing +tests/VGGSound/video/lGjXKrsWDYc_000008.mp4 sheep bleating 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woodpecker pecking tree +tests/VGGSound/video/ouvOmkKBFM0_000614.mp4 turkey gobbling +tests/VGGSound/video/lcGYtyHeKR4_000055.mp4 wood thrush calling +tests/VGGSound/video/ov4fdnGwzWU_000520.mp4 playing trumpet +tests/VGGSound/video/lcRSwt2-uhA_000030.mp4 wind rustling leaves +tests/VGGSound/video/ovFG_3EjFac_000005.mp4 people shuffling +tests/VGGSound/video/lchja4Ln8lw_000037.mp4 people gargling +tests/VGGSound/video/lchja4Ln8lw_000153.mp4 people gargling +tests/VGGSound/video/ov_g-r7Vo8M_000030.mp4 playing cymbal +tests/VGGSound/video/ldPA6OQdxQ4_000062.mp4 cat growling +tests/VGGSound/video/ovgelLpt148_000030.mp4 firing cannon +tests/VGGSound/video/ovmrWtaq3og_000017.mp4 playing cornet +tests/VGGSound/video/ldVtte9jK-s_000030.mp4 firing cannon +tests/VGGSound/video/owFisMijVkI_000000.mp4 civil defense siren +tests/VGGSound/video/le5_Y3GBqGk_000050.mp4 playing theremin +tests/VGGSound/video/owVJ_Pbaqog_000439.mp4 playing darts +tests/VGGSound/video/owZDBEq6WdU_000030.mp4 chainsawing trees +tests/VGGSound/video/leIanf9R2R0_000230.mp4 typing on computer keyboard +tests/VGGSound/video/leTMkrc4KGI_000106.mp4 wood thrush calling +tests/VGGSound/video/lehPGCdtNmY_000030.mp4 baby laughter +tests/VGGSound/video/oxS8-HPkWmA_000013.mp4 dinosaurs bellowing +tests/VGGSound/video/lfQyTxvpKRk_000030.mp4 fire crackling +tests/VGGSound/video/lfSWthnCbHo_000324.mp4 shot football +tests/VGGSound/video/lf_8Pp5QDng_000001.mp4 race car, auto racing +tests/VGGSound/video/lfmfjfLlKB0_000010.mp4 playing french horn +tests/VGGSound/video/oyFmwQmDXmM_000114.mp4 bowling impact +tests/VGGSound/video/lg2f7KERKFY_000092.mp4 bouncing on trampoline +tests/VGGSound/video/lg6lt9pvfKY_000684.mp4 canary calling +tests/VGGSound/video/oyVYqVPSL-c_000224.mp4 electric grinder grinding +tests/VGGSound/video/lgB6_lVDpvc_000020.mp4 stream burbling +tests/VGGSound/video/oyxhHkOel2I_000115.mp4 playing tennis +tests/VGGSound/video/oz-UP7-mCEY_000004.mp4 footsteps on snow 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mouse clicking +tests/VGGSound/video/pIhCGGAsoaA_000107.mp4 mouse clicking +tests/VGGSound/video/syIwNMo2TUA_000000.mp4 people screaming +tests/VGGSound/video/syJs8zsdI8o_000034.mp4 playing gong +tests/VGGSound/video/syjglspQinE_000004.mp4 playing tympani +tests/VGGSound/video/syn7nPwCkGU_000013.mp4 popping popcorn +tests/VGGSound/video/pJOOABIxqKc_000010.mp4 firing muskets +tests/VGGSound/video/pJSUhAfuZfs_000059.mp4 ferret dooking +tests/VGGSound/video/pJaLxsCM7rc_000190.mp4 fire truck siren +tests/VGGSound/video/szZJa2XhkMM_000034.mp4 strike lighter +tests/VGGSound/video/pJnmT-ViaBk_000012.mp4 baltimore oriole calling +tests/VGGSound/video/pJpAIDrXzJY_000120.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/t-6BSzXBNbM_000051.mp4 penguins braying +tests/VGGSound/video/pK5UyBgIZQU_000071.mp4 playing tambourine +tests/VGGSound/video/pKG3RMK__dc_000110.mp4 car passing by +tests/VGGSound/video/t-yy7v7P0IE_000100.mp4 playing bass guitar +tests/VGGSound/video/pKVmqlyFNb8_000051.mp4 playing volleyball +tests/VGGSound/video/t0E2aNbebu0_000010.mp4 child singing +tests/VGGSound/video/pKt19mzJKCo_000243.mp4 people battle cry +tests/VGGSound/video/pL4zRe6Purs_000070.mp4 playing flute +tests/VGGSound/video/t0txEC0Rhdg_000000.mp4 helicopter +tests/VGGSound/video/pMWFhplFSEQ_000000.mp4 playing vibraphone +tests/VGGSound/video/pMYaAyjyR5w_000044.mp4 woodpecker pecking tree +tests/VGGSound/video/pMfpDNSFc-w_000009.mp4 otter growling +tests/VGGSound/video/t1nkAcgSC3E_000205.mp4 cow lowing +tests/VGGSound/video/pMqwq6KkVh0_000025.mp4 arc welding +tests/VGGSound/video/pMslr--gpnk_000050.mp4 hedge trimmer running +tests/VGGSound/video/pNIN0FTNHTk_000190.mp4 sloshing water +tests/VGGSound/video/t3-n6Edtbuw_000047.mp4 striking bowling +tests/VGGSound/video/pNe78oBtedY_000047.mp4 cell phone buzzing +tests/VGGSound/video/pNin81AXlRY_000005.mp4 lions growling +tests/VGGSound/video/t3fZ7cgYVFc_000030.mp4 pig oinking +tests/VGGSound/video/pNnLCdsc11g_000087.mp4 volcano explosion +tests/VGGSound/video/pNrnDUg0dng_000030.mp4 fire truck siren +tests/VGGSound/video/pOfr9zC3OIc_000439.mp4 bathroom ventilation fan running +tests/VGGSound/video/t4h65x4f46I_000049.mp4 playing bongo +tests/VGGSound/video/t4plaa_X5mk_000093.mp4 eletric blender running +tests/VGGSound/video/t4xL3tWVGu8_000017.mp4 striking bowling +tests/VGGSound/video/pOvO5y-p550_000170.mp4 people burping +tests/VGGSound/video/pOxG6h1okWY_000275.mp4 metronome +tests/VGGSound/video/pP0fJ64QFHE_000430.mp4 people sobbing +tests/VGGSound/video/t5UDtbACVe4_000047.mp4 heart sounds, heartbeat +tests/VGGSound/video/pPiZRPr_htM_000098.mp4 playing tambourine +tests/VGGSound/video/pPk9HpXZLj8_000030.mp4 baby babbling +tests/VGGSound/video/pPljucNzQJY_000038.mp4 plastic bottle crushing +tests/VGGSound/video/t5kpBQv8trY_000015.mp4 alligators, crocodiles hissing +tests/VGGSound/video/t5xJ9pkdX-0_000530.mp4 train whistling +tests/VGGSound/video/t6AXyglx5X4_000360.mp4 race car, auto racing +tests/VGGSound/video/t6WCPvOtL6k_000169.mp4 strike lighter +tests/VGGSound/video/t6jlx6jAb-Q_000070.mp4 playing mandolin +tests/VGGSound/video/t6ofi6eVHSw_000310.mp4 playing harpsichord +tests/VGGSound/video/t7GM_V8yLqs_000085.mp4 playing table tennis +tests/VGGSound/video/t7GM_V8yLqs_000107.mp4 playing table tennis +tests/VGGSound/video/pQsPEY4MjWk_000003.mp4 zebra braying +tests/VGGSound/video/pQsPEY4MjWk_000026.mp4 zebra braying +tests/VGGSound/video/t7NFJjYWpwo_000000.mp4 otter growling +tests/VGGSound/video/t7oAteGa55g_000090.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/t8BwqzzqcDs_000108.mp4 people booing +tests/VGGSound/video/t8BwqzzqcDs_000134.mp4 people booing +tests/VGGSound/video/t925JwYXhVA_000000.mp4 playing snare drum +tests/VGGSound/video/pRm4t8VZxKw_000208.mp4 cuckoo bird calling +tests/VGGSound/video/t9PEpPvVNzI_000310.mp4 machine gun shooting +tests/VGGSound/video/pRwaEwxraWw_000130.mp4 playing accordion +tests/VGGSound/video/tA90BqRu_Ko_000068.mp4 playing bongo +tests/VGGSound/video/pSVtqy6NzH0_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/pSlVtxLOYiM_000050.mp4 playing cymbal +tests/VGGSound/video/tA_NrYVTlps_000024.mp4 horse clip-clop +tests/VGGSound/video/pSzTPGlNa5U_000030.mp4 playing theremin +tests/VGGSound/video/tAefxi1qmhU_000005.mp4 fox barking +tests/VGGSound/video/tAs0wdIydrI_000006.mp4 people giggling +tests/VGGSound/video/tB67geb0fVg_000063.mp4 forging swords +tests/VGGSound/video/pTRiK6Cc9fo_000000.mp4 wind noise +tests/VGGSound/video/tBHO4b-dZAI_000041.mp4 blowtorch igniting +tests/VGGSound/video/pTY56E9D_cE_000154.mp4 squishing water +tests/VGGSound/video/tBUVgCiHFds_000009.mp4 bathroom ventilation fan running +tests/VGGSound/video/tCgCW9Pk6cg_000042.mp4 heart sounds, heartbeat +tests/VGGSound/video/pUgCQ4wICKc_000008.mp4 chicken clucking +tests/VGGSound/video/pUn8YqN2meU_000009.mp4 playing cornet +tests/VGGSound/video/pUn8YqN2meU_000059.mp4 playing cornet +tests/VGGSound/video/pVf84f6xrBw_000070.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/tEDkAulFrSg_000018.mp4 fireworks banging +tests/VGGSound/video/pWLDewht-Kw_000156.mp4 black capped chickadee calling +tests/VGGSound/video/pWjfnwWIXQ4_000150.mp4 bird wings flapping +tests/VGGSound/video/pWked2HMtkY_000027.mp4 dog howling +tests/VGGSound/video/tFLGKmOa0dc_000030.mp4 cattle mooing +tests/VGGSound/video/pX0Jhk6e2Uw_000030.mp4 playing trumpet +tests/VGGSound/video/tFUIVRLXD68_000030.mp4 cat purring +tests/VGGSound/video/tFVvupXoRoM_000030.mp4 playing bass guitar +tests/VGGSound/video/tFfqWnybHEM_000040.mp4 playing bass guitar +tests/VGGSound/video/tFg6E-f1Ep8_000022.mp4 pig oinking +tests/VGGSound/video/tFhWe7lscQw_000159.mp4 rope skipping +tests/VGGSound/video/tFnfJ5XKIrI_000027.mp4 people slapping +tests/VGGSound/video/pXGuj0q9ai0_000105.mp4 male singing +tests/VGGSound/video/pXTGeMMU1S0_000092.mp4 golf driving +tests/VGGSound/video/tGKi7ueROn8_000197.mp4 eletric blender running +tests/VGGSound/video/tGUWSgewh0A_000270.mp4 playing bass drum +tests/VGGSound/video/pXxTz9z4t8w_000210.mp4 skiing +tests/VGGSound/video/tGhxTy-CjV8_000010.mp4 baltimore oriole calling +tests/VGGSound/video/pYJbZ9c-_pE_000117.mp4 pheasant crowing +tests/VGGSound/video/tHOs4zebKis_000270.mp4 airplane flyby +tests/VGGSound/video/tI1v26P8feE_000030.mp4 playing synthesizer +tests/VGGSound/video/tI5h94hKdVs_000005.mp4 tractor digging +tests/VGGSound/video/tIPnM_oW39U_000173.mp4 yodelling +tests/VGGSound/video/tIRHm8VhK_4_000030.mp4 playing sitar +tests/VGGSound/video/tISWNV_n32g_000070.mp4 hair dryer drying +tests/VGGSound/video/pZG7CaFjEiQ_000751.mp4 people slurping +tests/VGGSound/video/tIa9A8Xelug_000024.mp4 playing ukulele +tests/VGGSound/video/tJJ8UdNSDqc_000021.mp4 playing hockey +tests/VGGSound/video/p_6nbBAJNxI_000032.mp4 otter growling +tests/VGGSound/video/tJT4SruI5Hs_000018.mp4 chimpanzee pant-hooting +tests/VGGSound/video/tJTDa31Bw_k_000209.mp4 playing bongo 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hiccup +tests/VGGSound/video/pc-FTQNfxx0_000266.mp4 disc scratching +tests/VGGSound/video/tMN_lfBNsm0_000006.mp4 dinosaurs bellowing +tests/VGGSound/video/pcGbob7fSgE_000040.mp4 people marching +tests/VGGSound/video/tMXsrzj5YYA_000030.mp4 playing piano +tests/VGGSound/video/pcGbob7fSgE_000071.mp4 people marching +tests/VGGSound/video/tMeM2z6NCL4_000030.mp4 lions roaring +tests/VGGSound/video/pcbfKzW8zFI_000016.mp4 cow lowing +tests/VGGSound/video/tMzxjJygrH4_000002.mp4 playing table tennis +tests/VGGSound/video/tNU_9HOjmqQ_000023.mp4 dog baying +tests/VGGSound/video/pdXr166xPeU_000240.mp4 lighting firecrackers +tests/VGGSound/video/tNzp5xotBjs_000120.mp4 playing double bass +tests/VGGSound/video/pdqoxoWlQTo_000094.mp4 police radio chatter +tests/VGGSound/video/tOTQJaRkmaY_000381.mp4 playing congas +tests/VGGSound/video/peM5etsoQhY_000093.mp4 ice cracking +tests/VGGSound/video/pf00DOALuZ0_000275.mp4 people eating crisps +tests/VGGSound/video/pf00DOALuZ0_000293.mp4 people eating crisps +tests/VGGSound/video/tPE0GmzqkRY_000030.mp4 male speech, man speaking +tests/VGGSound/video/pfB7MFteFFY_000095.mp4 chimpanzee pant-hooting +tests/VGGSound/video/tPnrH7BlprM_000070.mp4 people sobbing +tests/VGGSound/video/tPtXIGJ6yOY_000150.mp4 people running +tests/VGGSound/video/tQamQOhxjwY_000225.mp4 planing timber +tests/VGGSound/video/pfteERYuKuA_000060.mp4 penguins braying +tests/VGGSound/video/pfz77dq_XGM_000067.mp4 otter growling +tests/VGGSound/video/tQi00qSZC60_000003.mp4 baltimore oriole calling +tests/VGGSound/video/tQi00qSZC60_000031.mp4 baltimore oriole calling +tests/VGGSound/video/tQpSR44-vLY_000150.mp4 lathe spinning +tests/VGGSound/video/tR4zs1xwI98_000009.mp4 police car (siren) +tests/VGGSound/video/pgQxDv8Iugo_000160.mp4 people eating noodle +tests/VGGSound/video/ph0-RkqW1vM_000000.mp4 playing piano +tests/VGGSound/video/tRYgfHwu-_U_000019.mp4 snake rattling +tests/VGGSound/video/ph2g0DZNiZI_000094.mp4 people slapping +tests/VGGSound/video/tRfJMsacjpk_000044.mp4 playing double bass +tests/VGGSound/video/tRsClUJDxCQ_000029.mp4 playing bugle +tests/VGGSound/video/phLQ4OZMQ4g_000003.mp4 metronome +tests/VGGSound/video/tSPEtpVP5b4_000092.mp4 baltimore oriole calling +tests/VGGSound/video/tSX2jYLgPng_000030.mp4 dog bow-wow +tests/VGGSound/video/phib36cTLiI_000062.mp4 elk bugling +tests/VGGSound/video/pi2Vyqa-wgE_000087.mp4 dinosaurs bellowing +tests/VGGSound/video/tTNZYyuU_X4_000030.mp4 people running +tests/VGGSound/video/pignXMaONpY_000411.mp4 playing bongo +tests/VGGSound/video/piyECZa_kX8_000357.mp4 race car, auto racing +tests/VGGSound/video/tTsvjXYDwQQ_000012.mp4 playing snare drum +tests/VGGSound/video/pjrK11MwQcs_000030.mp4 mouse pattering +tests/VGGSound/video/pjtJGwhmi9I_000066.mp4 running electric fan +tests/VGGSound/video/pjuHVmcoVFc_000036.mp4 playing oboe +tests/VGGSound/video/pjuyGQPd4S4_000039.mp4 playing djembe +tests/VGGSound/video/tUrlSBYq_0o_000030.mp4 playing accordion +tests/VGGSound/video/pkFxWAshbWE_000022.mp4 people running +tests/VGGSound/video/tV3rvUSlVnY_000030.mp4 playing steelpan +tests/VGGSound/video/pkLw94kshuQ_000326.mp4 playing snare drum +tests/VGGSound/video/tVF4KMwuvZ0_000045.mp4 missile launch +tests/VGGSound/video/pkdT-CS1jzw_000020.mp4 fire crackling +tests/VGGSound/video/tVK9-hEfbnY_000021.mp4 chinchilla barking +tests/VGGSound/video/tWJxVNq0N5E_000220.mp4 sailing +tests/VGGSound/video/tWi-PtHOMSE_000178.mp4 dog growling +tests/VGGSound/video/plboimUNc4o_000100.mp4 playing washboard +tests/VGGSound/video/pldcfQAiPK0_000350.mp4 splashing water +tests/VGGSound/video/plfLL0Niy9k_000110.mp4 lighting firecrackers +tests/VGGSound/video/tXDtxe4ugzQ_000073.mp4 airplane flyby +tests/VGGSound/video/pljrosvt-o8_000017.mp4 cat hissing +tests/VGGSound/video/tXIvahZojCs_000253.mp4 playing hockey +tests/VGGSound/video/tXLaQKRWM8I_000000.mp4 dog baying +tests/VGGSound/video/pm3n1DgGURo_000008.mp4 chinchilla barking +tests/VGGSound/video/tXevNDmTzyo_000141.mp4 heart sounds, heartbeat +tests/VGGSound/video/pmTVoCl7GB8_000002.mp4 people humming +tests/VGGSound/video/tYCgvipu3ko_000043.mp4 snake rattling +tests/VGGSound/video/tYEIYOHYtso_000000.mp4 people hiccup +tests/VGGSound/video/pmdoDcNBt0E_000030.mp4 female singing +tests/VGGSound/video/pmzYu1HZbtc_000260.mp4 mosquito buzzing +tests/VGGSound/video/pnIQWNmKlQs_000030.mp4 duck quacking +tests/VGGSound/video/tZFs-kLTpyg_000003.mp4 train whistling +tests/VGGSound/video/pnRvEfIkgSA_000013.mp4 parrot talking +tests/VGGSound/video/pnsntPDPfxg_000064.mp4 penguins braying +tests/VGGSound/video/t_36kmJA8f4_000020.mp4 sharpen knife +tests/VGGSound/video/t_RxQe51MVo_000010.mp4 dog baying +tests/VGGSound/video/t_UXhBi6ZGQ_000011.mp4 people cheering +tests/VGGSound/video/t_UXhBi6ZGQ_000021.mp4 people cheering +tests/VGGSound/video/t_nChjR23qA_000031.mp4 alligators, crocodiles hissing +tests/VGGSound/video/t_nChjR23qA_000109.mp4 alligators, crocodiles hissing +tests/VGGSound/video/ta9gY--DRag_000024.mp4 cupboard opening or closing +tests/VGGSound/video/pp4xXyiezA8_000020.mp4 people sobbing +tests/VGGSound/video/tagcgGVNKZo_000023.mp4 airplane flyby +tests/VGGSound/video/tav0edwEqow_000059.mp4 people eating crisps +tests/VGGSound/video/tbLODtr1dIw_000031.mp4 playing mandolin +tests/VGGSound/video/pqCySqmhVwQ_000293.mp4 skiing +tests/VGGSound/video/pqHot_n_kB8_000150.mp4 cattle, bovinae cowbell +tests/VGGSound/video/tcZ7hytrOO4_000319.mp4 tractor digging +tests/VGGSound/video/td4T1Yl0lB0_000050.mp4 splashing water +tests/VGGSound/video/przrSPZgOkY_000090.mp4 thunder +tests/VGGSound/video/tdF2l30DZ18_000089.mp4 playing lacrosse +tests/VGGSound/video/td_zqOBT6ac_000079.mp4 zebra braying +tests/VGGSound/video/psamoHEfoHg_000020.mp4 opening or closing drawers +tests/VGGSound/video/psbURlY7H2g_000011.mp4 pheasant crowing +tests/VGGSound/video/psbURlY7H2g_000085.mp4 pheasant crowing +tests/VGGSound/video/te8Yhl8mOyY_000040.mp4 people belly laughing +tests/VGGSound/video/pt41PSOsG8c_000001.mp4 dog baying +tests/VGGSound/video/pt67dyEbwGY_000039.mp4 playing snare drum +tests/VGGSound/video/teat8XuzuU4_000000.mp4 cricket chirping +tests/VGGSound/video/tej3zK91UVQ_000208.mp4 tornado roaring +tests/VGGSound/video/telZ8Dc0i_M_000294.mp4 people sniggering +tests/VGGSound/video/teoER4j9H14_000290.mp4 car engine starting +tests/VGGSound/video/pttd--gmIUY_000030.mp4 fire crackling +tests/VGGSound/video/ptw48aDb4Ms_000124.mp4 playing castanets +tests/VGGSound/video/tf2KhTHbKLQ_000010.mp4 cheetah chirrup +tests/VGGSound/video/tf7iVpC0nrU_000337.mp4 people eating noodle +tests/VGGSound/video/tfAxJ2-Urco_000029.mp4 pheasant crowing +tests/VGGSound/video/puQFxYICkII_000000.mp4 playing oboe +tests/VGGSound/video/tfY-mdSTgvM_000108.mp4 bowling impact +tests/VGGSound/video/puWLQ77Iq74_000064.mp4 tractor digging +tests/VGGSound/video/tfhKYv0UNAY_000337.mp4 francolin calling +tests/VGGSound/video/tg0KFj-fkfs_000000.mp4 people burping +tests/VGGSound/video/puoRo9q7-ec_000009.mp4 disc scratching +tests/VGGSound/video/tgPq6ApMOWk_000028.mp4 cat hissing +tests/VGGSound/video/tgRjq29TIJo_000010.mp4 baby crying +tests/VGGSound/video/puxjtmU7H70_000077.mp4 people slapping +tests/VGGSound/video/tgTYzeHEuzQ_000171.mp4 eletric blender running +tests/VGGSound/video/pv6hda1OnnI_000037.mp4 elk bugling +tests/VGGSound/video/tgotVTkTSwo_000052.mp4 playing erhu +tests/VGGSound/video/thCn14bf1r8_000380.mp4 machine gun shooting +tests/VGGSound/video/pvV13-PcsY0_000030.mp4 mosquito buzzing +tests/VGGSound/video/pvoVuY82-Gc_000002.mp4 people eating crisps +tests/VGGSound/video/ti2rs-r9r3A_000001.mp4 people nose blowing +tests/VGGSound/video/ti2rs-r9r3A_000110.mp4 people nose blowing +tests/VGGSound/video/ti3oPHlZGQY_000067.mp4 people gargling +tests/VGGSound/video/ti3oPHlZGQY_000088.mp4 people gargling +tests/VGGSound/video/pwKHEMzqG00_000020.mp4 frog croaking +tests/VGGSound/video/pwV5A_VVYmU_000010.mp4 playing cymbal +tests/VGGSound/video/tiMD7FdhbPo_000050.mp4 playing trumpet +tests/VGGSound/video/tj77zzeFPsc_000267.mp4 people eating noodle +tests/VGGSound/video/px6RnApJYgk_000040.mp4 bird wings flapping +tests/VGGSound/video/pxAbZ6YwO3g_000178.mp4 train whistling +tests/VGGSound/video/pxEmmUYLHrE_000030.mp4 playing mandolin +tests/VGGSound/video/tjKzkajbKc0_000030.mp4 smoke detector beeping +tests/VGGSound/video/pxU78kiZqCM_000030.mp4 playing electronic organ +tests/VGGSound/video/pxfDwsH7jk8_000398.mp4 running electric fan +tests/VGGSound/video/tjqqCEt7A8c_000224.mp4 people humming +tests/VGGSound/video/tk1WqHXdPuY_000015.mp4 train whistling +tests/VGGSound/video/tk4s-nlhmEQ_000030.mp4 baby crying +tests/VGGSound/video/py6G9r0fydU_000030.mp4 sliding door +tests/VGGSound/video/tkAY3tXAoHc_000083.mp4 dinosaurs bellowing +tests/VGGSound/video/pyDI0mBb2Gc_000005.mp4 people hiccup +tests/VGGSound/video/tkq3HREJFi8_000071.mp4 playing trumpet +tests/VGGSound/video/pzAiXfVmLGA_000504.mp4 people eating noodle +tests/VGGSound/video/tlFgdrl3NQA_000065.mp4 turkey gobbling +tests/VGGSound/video/tlovZjft0Gw_000245.mp4 tractor digging +tests/VGGSound/video/pzRIDUOCOlA_000471.mp4 driving snowmobile +tests/VGGSound/video/pzZBnD-EL80_000085.mp4 hammering nails +tests/VGGSound/video/pzbO6YfqYII_000030.mp4 door slamming +tests/VGGSound/video/tm0Em1IlvsA_000318.mp4 people eating apple +tests/VGGSound/video/tmXq_W2sb-A_000003.mp4 playing tuning fork +tests/VGGSound/video/tm_fzEvkBkI_000030.mp4 stream burbling +tests/VGGSound/video/tmabzx6yxqs_000030.mp4 pig oinking +tests/VGGSound/video/tmdrHw6-yUY_000181.mp4 dog bow-wow +tests/VGGSound/video/tmkOomSM_So_000080.mp4 cattle, bovinae cowbell +tests/VGGSound/video/tmziKIRUbac_000108.mp4 playing hockey +tests/VGGSound/video/q-bOXZszzkw_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/tnepPZChA5U_000219.mp4 playing violin, fiddle +tests/VGGSound/video/q-lVsfgGuq4_000826.mp4 foghorn +tests/VGGSound/video/q-mib8XkZDo_000338.mp4 airplane +tests/VGGSound/video/tnmwXN4aTyw_000123.mp4 donkey, ass braying 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bowling +tests/VGGSound/video/qL-ifTe9Reg_000007.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/qLQVG0dFvwg_000135.mp4 playing shofar +tests/VGGSound/video/qLVjaU5V9f0_000150.mp4 car passing by +tests/VGGSound/video/qMKO8bQpzMg_000090.mp4 playing piano +tests/VGGSound/video/qMMhRUyckDE_000000.mp4 cattle, bovinae cowbell +tests/VGGSound/video/qMbGFWz9who_000020.mp4 people sobbing +tests/VGGSound/video/uA6Ycad4cLg_000173.mp4 blowtorch igniting +tests/VGGSound/video/uAB0hA7zxKI_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/uAcYglB_pRw_000390.mp4 bird wings flapping +tests/VGGSound/video/uAgizG1hYw0_000060.mp4 playing bass guitar +tests/VGGSound/video/uAl_7AUPI2Q_000036.mp4 playing shofar +tests/VGGSound/video/qNRlfoUJ15A_000069.mp4 cupboard opening or closing +tests/VGGSound/video/uBBjaf6ehLo_000087.mp4 playing squash +tests/VGGSound/video/uBLjl4cOQ5Q_000030.mp4 people humming +tests/VGGSound/video/qNj8RLCaoL4_000446.mp4 disc scratching 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people slapping +tests/VGGSound/video/qPYA_MVHDbY_000001.mp4 eagle screaming +tests/VGGSound/video/qPaXT7mWUj0_000991.mp4 playing hockey +tests/VGGSound/video/uDqVzJtaxOc_000020.mp4 playing synthesizer +tests/VGGSound/video/qPsoKSYzuyo_000010.mp4 splashing water +tests/VGGSound/video/uEMANxR3vwc_000338.mp4 police radio chatter +tests/VGGSound/video/uEVID59IoHE_000030.mp4 playing flute +tests/VGGSound/video/uEtmoOj6wHY_000086.mp4 sea lion barking +tests/VGGSound/video/uF7G9AuI1Qk_000030.mp4 smoke detector beeping +tests/VGGSound/video/qQhNzixQvM4_000220.mp4 mouse pattering +tests/VGGSound/video/uFfjq0JGXcI_000154.mp4 train horning +tests/VGGSound/video/uG4Y4HedL60_000015.mp4 air horn +tests/VGGSound/video/qRW1-q1SU5U_000043.mp4 snake rattling +tests/VGGSound/video/uGgSgK2Jy68_000246.mp4 train wheels squealing +tests/VGGSound/video/uGm1isE8Apg_000011.mp4 people cheering +tests/VGGSound/video/uGog-Ck0ZaU_000015.mp4 air horn +tests/VGGSound/video/uH56Q1Cn8vs_000028.mp4 snake hissing 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elephant trumpeting +tests/VGGSound/video/qYMsdQCggKI_000240.mp4 elephant trumpeting +tests/VGGSound/video/qYauQjr6oi0_000106.mp4 barn swallow calling +tests/VGGSound/video/uNDLAH1xjO4_000095.mp4 playing washboard +tests/VGGSound/video/qYjhJeSVJ2A_000030.mp4 singing bowl +tests/VGGSound/video/qZUmCONB6YQ_000022.mp4 playing guiro +tests/VGGSound/video/uO34zKivHzI_000260.mp4 playing oboe +tests/VGGSound/video/qZelT2DOG4g_000267.mp4 mouse clicking +tests/VGGSound/video/uOOGqzu-I_U_000128.mp4 people eating noodle +tests/VGGSound/video/qZqfctv2CHg_000419.mp4 strike lighter +tests/VGGSound/video/uOpAbMljiA0_000042.mp4 roller coaster running +tests/VGGSound/video/q_K7AV8EWks_000026.mp4 playing bongo +tests/VGGSound/video/q_Sx6S-MQec_000064.mp4 francolin calling +tests/VGGSound/video/uOwKP7vCiJA_000025.mp4 spraying water +tests/VGGSound/video/q_huhNjRrFs_000811.mp4 playing badminton +tests/VGGSound/video/q_rKv5CdCfI_000030.mp4 vehicle horn, car horn, honking 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oinking +tests/VGGSound/video/uwH37lkK6OQ_000070.mp4 otter growling +tests/VGGSound/video/uwH37lkK6OQ_000278.mp4 otter growling +tests/VGGSound/video/qxnBcZ0CETg_000171.mp4 airplane +tests/VGGSound/video/uwoOyOAsbY4_000004.mp4 playing tuning fork +tests/VGGSound/video/uwxoy9R6WdI_000030.mp4 dog whimpering +tests/VGGSound/video/ux7HhOxMRE4_000020.mp4 dog barking +tests/VGGSound/video/qyQNZMPZLtU_000060.mp4 bee, wasp, etc. buzzing +tests/VGGSound/video/qyaKDCbV0nc_000587.mp4 ripping paper +tests/VGGSound/video/uxy0ovI6cNU_000220.mp4 sailing +tests/VGGSound/video/uyElGwaWFnI_000017.mp4 dog whimpering +tests/VGGSound/video/qz-TAJdo8W4_000159.mp4 planing timber +tests/VGGSound/video/qz66f98CiBg_000086.mp4 opening or closing car doors +tests/VGGSound/video/uz-_ROIn0bM_000035.mp4 blowtorch igniting +tests/VGGSound/video/uz1Bh1_28As_000020.mp4 singing bowl +tests/VGGSound/video/uzZ0s6k6vzE_000360.mp4 footsteps on snow +tests/VGGSound/video/r-5NCjm4GlQ_000053.mp4 tap dancing 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+tests/VGGSound/video/rJftCcAQZEY_000460.mp4 cricket chirping +tests/VGGSound/video/rJg75xog4hs_000029.mp4 spraying water +tests/VGGSound/video/rJn8Ir3YN0g_000112.mp4 people eating noodle +tests/VGGSound/video/rKByT8fOXpk_000007.mp4 footsteps on snow +tests/VGGSound/video/vUn1NaMwqjg_000047.mp4 underwater bubbling +tests/VGGSound/video/vUn1NaMwqjg_000223.mp4 underwater bubbling +tests/VGGSound/video/rKwsKLBKTIY_000059.mp4 people humming +tests/VGGSound/video/vUui_D_rT9c_000034.mp4 chicken clucking +tests/VGGSound/video/rLDm254jtZA_000021.mp4 playing tennis +tests/VGGSound/video/rLDm254jtZA_000056.mp4 playing tennis +tests/VGGSound/video/rLRi-RsRTcI_000025.mp4 air horn +tests/VGGSound/video/vVItJE6Djsk_000054.mp4 train whistling +tests/VGGSound/video/rLa17dibI70_000175.mp4 children shouting +tests/VGGSound/video/rLe9N0YyjqY_000006.mp4 beat boxing +tests/VGGSound/video/rLmNuF9xTPI_000030.mp4 typing on computer keyboard +tests/VGGSound/video/vVle7Qb4tDU_000056.mp4 tractor digging +tests/VGGSound/video/rM0mOUPtSpU_000060.mp4 people sneezing +tests/VGGSound/video/vWKefG-sIrU_000000.mp4 dog baying +tests/VGGSound/video/rMJacNNPAYo_000134.mp4 people humming +tests/VGGSound/video/rMSlTa8tWhA_000113.mp4 driving snowmobile +tests/VGGSound/video/vX779FBlyfk_000129.mp4 otter growling +tests/VGGSound/video/vXBBhgvMCkM_000210.mp4 lawn mowing +tests/VGGSound/video/rMrXgKbKssw_000051.mp4 playing tympani +tests/VGGSound/video/rMwYBw7zMmY_000073.mp4 mynah bird singing +tests/VGGSound/video/vY2m4W8pUFA_000015.mp4 people eating crisps +tests/VGGSound/video/vY7O2jWCWdQ_000374.mp4 playing mandolin +tests/VGGSound/video/rNHbhgnEskY_000030.mp4 playing bagpipes +tests/VGGSound/video/rNQ0EBdxPvM_000030.mp4 using sewing machines +tests/VGGSound/video/rNQBarDe0xQ_000072.mp4 francolin calling +tests/VGGSound/video/vZPygZ5oN2s_000170.mp4 playing piano +tests/VGGSound/video/rNyJbdv2KF4_000060.mp4 airplane +tests/VGGSound/video/rO0jmZHwV8Q_000120.mp4 people sniggering +tests/VGGSound/video/rOFTDCoxedc_000340.mp4 singing bowl +tests/VGGSound/video/rOGWjfzN7D8_000023.mp4 playing tuning fork +tests/VGGSound/video/rOMU791E9zg_000230.mp4 bird wings flapping +tests/VGGSound/video/v_oFiTzjGN8_000010.mp4 skidding +tests/VGGSound/video/rOQt6_E-x_0_000000.mp4 people humming +tests/VGGSound/video/vaErFk6zS30_000044.mp4 people sneezing +tests/VGGSound/video/vaFi4gE92i8_000150.mp4 singing bowl +tests/VGGSound/video/vao3k4Z115k_000235.mp4 slot machine +tests/VGGSound/video/rOolowH8rI4_000023.mp4 chimpanzee pant-hooting +tests/VGGSound/video/vb1SalyslCs_000050.mp4 sailing +tests/VGGSound/video/rPGgxEE2hjk_000091.mp4 pheasant crowing +tests/VGGSound/video/rPGgxEE2hjk_000118.mp4 pheasant crowing +tests/VGGSound/video/vbd491cweJ0_000866.mp4 ripping paper +tests/VGGSound/video/rQ3IPqTLi-I_000058.mp4 tap dancing +tests/VGGSound/video/rQUz1GGqc6E_000333.mp4 playing double bass +tests/VGGSound/video/rQV5hHwzj4Y_000030.mp4 mosquito buzzing +tests/VGGSound/video/vcLmtZ7--iI_000217.mp4 people marching +tests/VGGSound/video/vcZ3gN9ZRcA_000100.mp4 playing congas +tests/VGGSound/video/vchsE_Dn7mo_000112.mp4 playing timbales +tests/VGGSound/video/vchsE_Dn7mo_000147.mp4 playing timbales +tests/VGGSound/video/vcnUR0H4pnY_000012.mp4 playing tuning fork +tests/VGGSound/video/vcspniRIpNk_000023.mp4 arc welding +tests/VGGSound/video/rR0_80jfUmo_000057.mp4 playing squash +tests/VGGSound/video/rR1h4DuOER0_000108.mp4 playing badminton +tests/VGGSound/video/vd2Ov9nGycg_000031.mp4 playing mandolin +tests/VGGSound/video/rR39rDVGPXk_000166.mp4 ice cracking +tests/VGGSound/video/rREf2jL0jQs_000010.mp4 playing snare drum +tests/VGGSound/video/vdXs8rFvovo_000009.mp4 chipmunk chirping +tests/VGGSound/video/vdh5LqgvSLU_000037.mp4 penguins braying +tests/VGGSound/video/rRVTA8SlJvM_000233.mp4 lathe spinning +tests/VGGSound/video/rRvtQ18RBH8_000000.mp4 waterfall burbling +tests/VGGSound/video/rRzWGIhwWAI_000030.mp4 playing flute 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+tests/VGGSound/video/vgrwGiSIY9U_000032.mp4 hail +tests/VGGSound/video/vgtB9UHIFpo_000269.mp4 mouse clicking +tests/VGGSound/video/rTyQuGidCBU_000040.mp4 airplane flyby +tests/VGGSound/video/rU7WZkmqSGc_000072.mp4 baltimore oriole calling +tests/VGGSound/video/rUBBfqfV76Y_000124.mp4 roller coaster running +tests/VGGSound/video/vh8Uh1zTLQw_000035.mp4 bull bellowing +tests/VGGSound/video/vh8Uh1zTLQw_000058.mp4 bull bellowing +tests/VGGSound/video/rUIGOcQMaSE_000040.mp4 playing vibraphone +tests/VGGSound/video/vhJeDYQVtdQ_000040.mp4 wind noise +tests/VGGSound/video/rUU-ScAcnW4_000030.mp4 playing hammond organ +tests/VGGSound/video/vhKjv9GuARQ_000013.mp4 tornado roaring +tests/VGGSound/video/vhKjv9GuARQ_000043.mp4 tornado roaring +tests/VGGSound/video/vhUM-UOKpSk_000053.mp4 playing ukulele +tests/VGGSound/video/vhyVvH6FPYI_000056.mp4 playing bassoon +tests/VGGSound/video/viYxkl1BW9U_000100.mp4 playing drum kit +tests/VGGSound/video/rVlc15B6v-s_000015.mp4 playing tuning fork +tests/VGGSound/video/rVlc15B6v-s_000030.mp4 playing tuning fork +tests/VGGSound/video/rW0Vwotvx3s_000119.mp4 playing glockenspiel +tests/VGGSound/video/rW0Vwotvx3s_000178.mp4 playing glockenspiel +tests/VGGSound/video/vjx-jzh9q7U_000189.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/rWOYkvyr5o0_000033.mp4 fly, housefly buzzing +tests/VGGSound/video/vkYoVvLldiM_000110.mp4 splashing water +tests/VGGSound/video/rXHHLtG_iGQ_000562.mp4 tap dancing +tests/VGGSound/video/rXU4vJ4Rz4A_000032.mp4 footsteps on snow +tests/VGGSound/video/vkxPLFRLAy0_000000.mp4 fox barking +tests/VGGSound/video/vl60ONQpA_8_000000.mp4 swimming +tests/VGGSound/video/vlNuy9e-79o_000030.mp4 playing bass drum +tests/VGGSound/video/vlVN2yCot7M_000170.mp4 car engine starting +tests/VGGSound/video/vmBkZflwViA_000010.mp4 playing piano +tests/VGGSound/video/vmQcsFtmxG8_000000.mp4 people hiccup +tests/VGGSound/video/rYCF5tUINZU_000127.mp4 playing tuning fork +tests/VGGSound/video/vn_LymlQAnc_000440.mp4 cap gun shooting +tests/VGGSound/video/rYmiCpCbsm0_000020.mp4 bird squawking +tests/VGGSound/video/rYojIIvr1w8_000250.mp4 cap gun shooting +tests/VGGSound/video/vnlZ_V13P0A_000268.mp4 golf driving +tests/VGGSound/video/vnvMxxgYlgo_000200.mp4 playing piano +tests/VGGSound/video/rZZCrhMLxF0_000000.mp4 playing piano +tests/VGGSound/video/rZctZoTH7TY_000037.mp4 chopping wood +tests/VGGSound/video/vpyjAR_k70Y_000066.mp4 car engine starting +tests/VGGSound/video/vq4jQd5-PL0_000030.mp4 people sniggering +tests/VGGSound/video/r_TgaHCsYB0_000030.mp4 playing timpani +tests/VGGSound/video/r_h19mlagUE_000042.mp4 opening or closing car doors +tests/VGGSound/video/vr18I1PCECg_000000.mp4 playing french horn +tests/VGGSound/video/raCETItMU_g_000299.mp4 playing bassoon +tests/VGGSound/video/raCIGB3B4mg_000271.mp4 driving snowmobile +tests/VGGSound/video/raCIGB3B4mg_000286.mp4 driving snowmobile +tests/VGGSound/video/raIIQCRNwu0_000080.mp4 playing accordion +tests/VGGSound/video/rajXrf_Dzfw_000000.mp4 cattle mooing +tests/VGGSound/video/rajXrf_Dzfw_000010.mp4 cattle mooing +tests/VGGSound/video/rajXrf_Dzfw_000029.mp4 cattle mooing +tests/VGGSound/video/rask8MYJaB4_000233.mp4 striking pool +tests/VGGSound/video/vsCHW_rvUx0_000198.mp4 plastic bottle crushing +tests/VGGSound/video/vsCHW_rvUx0_000241.mp4 plastic bottle crushing +tests/VGGSound/video/vsM67sj0Joc_000060.mp4 people sobbing +tests/VGGSound/video/vsmkIaKIbNI_000643.mp4 ripping paper +tests/VGGSound/video/vuGwgfWdi5Q_000000.mp4 gibbon howling +tests/VGGSound/video/rcYPDpD7Bu8_000130.mp4 mosquito buzzing +tests/VGGSound/video/vuM1fLlNR4o_000030.mp4 stream burbling +tests/VGGSound/video/vuYE5G1C9MQ_000025.mp4 playing bassoon +tests/VGGSound/video/rcaxwyTo-E4_000150.mp4 dog growling +tests/VGGSound/video/rccs9c1gteQ_000000.mp4 playing synthesizer +tests/VGGSound/video/rcnaWIJ2QOw_000010.mp4 vehicle horn, car horn, honking +tests/VGGSound/video/rd4AgYS_oJE_000348.mp4 cat hissing +tests/VGGSound/video/vwAXcR6wRuQ_000010.mp4 people sobbing +tests/VGGSound/video/rdVo1ikBoJA_000000.mp4 people sobbing +tests/VGGSound/video/vw_q2SV_YOY_000130.mp4 turkey gobbling +tests/VGGSound/video/vwtuiXmg-ms_000255.mp4 disc scratching +tests/VGGSound/video/vwx5yb-qnuo_000033.mp4 underwater bubbling +tests/VGGSound/video/reAsBqZsfyo_000110.mp4 playing saxophone +tests/VGGSound/video/reGGOP8tYLU_000000.mp4 eating with cutlery +tests/VGGSound/video/vx664sJFpV0_000173.mp4 zebra braying +tests/VGGSound/video/res8Qtx-MHE_000020.mp4 lawn mowing +tests/VGGSound/video/rf3ye_WX4Ic_000080.mp4 shot football +tests/VGGSound/video/rf8nGoe0u2M_000043.mp4 footsteps on snow +tests/VGGSound/video/rfK_uUg-vKM_000030.mp4 people eating +tests/VGGSound/video/vyYpxGJr7zI_000030.mp4 dog barking +tests/VGGSound/video/rf_2xYkZcM4_000030.mp4 people burping +tests/VGGSound/video/rfa-iUp5UQc_000050.mp4 playing steel guitar, slide guitar +tests/VGGSound/video/rffMu_Y9rSY_000480.mp4 mouse pattering +tests/VGGSound/video/rflXOdLx4t8_000070.mp4 plastic bottle crushing +tests/VGGSound/video/rfnyfe1ALGQ_000013.mp4 bull bellowing +tests/VGGSound/video/rg4bhfytF9A_000022.mp4 playing tympani +tests/VGGSound/video/rg4bhfytF9A_000039.mp4 playing tympani +tests/VGGSound/video/vzY4mHyr-F8_000214.mp4 people humming +tests/VGGSound/video/vzqv9lqcdkg_000060.mp4 barn swallow calling +tests/VGGSound/video/w-5phSpjv8E_000018.mp4 people booing +tests/VGGSound/video/rglibN33aks_000012.mp4 opening or closing car electric windows +tests/VGGSound/video/w-EbQnMNuyw_000427.mp4 roller coaster running +tests/VGGSound/video/rgqJFceVM2I_000066.mp4 chicken clucking +tests/VGGSound/video/rhAwhUVsWRo_000005.mp4 goat bleating +tests/VGGSound/video/rhMpRPQlwmY_000030.mp4 firing cannon +tests/VGGSound/video/rhQwPnEYWI4_000030.mp4 people sniggering +tests/VGGSound/video/rhT8kzRAEEM_000117.mp4 playing washboard +tests/VGGSound/video/rhWrIKdn8ic_000116.mp4 people whispering +tests/VGGSound/video/rh_rFJsOmis_000340.mp4 singing bowl +tests/VGGSound/video/rhgBTv9bDQk_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/rhnT1UeL8BI_000012.mp4 planing timber +tests/VGGSound/video/w1-Rli9XnlI_000068.mp4 playing bugle +tests/VGGSound/video/riLxPF82qhA_000011.mp4 planing timber +tests/VGGSound/video/w1h40C729DU_000010.mp4 children shouting +tests/VGGSound/video/rj5DZMMg3eQ_000192.mp4 tornado roaring +tests/VGGSound/video/rjGjz5DolWA_000030.mp4 dog barking +tests/VGGSound/video/w2bAs3lug3c_000030.mp4 goat bleating +tests/VGGSound/video/rjYPJUBcoN8_000033.mp4 donkey, ass braying +tests/VGGSound/video/rjYPJUBcoN8_000050.mp4 donkey, ass braying +tests/VGGSound/video/w2vMywh5Nto_000010.mp4 playing mandolin +tests/VGGSound/video/rjued58Yqpc_000109.mp4 air horn +tests/VGGSound/video/rkMa9cC-zDQ_000022.mp4 playing guiro +tests/VGGSound/video/rkQr7lgIjpY_000179.mp4 alarm clock ringing +tests/VGGSound/video/rkaM1yOncZ4_000000.mp4 baby crying +tests/VGGSound/video/w4iq4qYdu2k_000015.mp4 skidding +tests/VGGSound/video/rlCetbDzOfE_000061.mp4 people marching +tests/VGGSound/video/w5ROR0xBAco_000113.mp4 playing castanets +tests/VGGSound/video/rlxmevufILI_000040.mp4 playing harmonica +tests/VGGSound/video/w5qf9O6c20o_000030.mp4 playing theremin +tests/VGGSound/video/rmI5PeG9tSY_000030.mp4 playing violin, fiddle +tests/VGGSound/video/rmL21Z7wZuk_000020.mp4 blowtorch igniting +tests/VGGSound/video/w61G4C8ZFfE_000008.mp4 playing tambourine +tests/VGGSound/video/rmPfJgDBeQ8_000020.mp4 stream burbling +tests/VGGSound/video/rmQhPCwioJw_000000.mp4 dog howling +tests/VGGSound/video/rmxRhByMBMU_000030.mp4 car engine knocking +tests/VGGSound/video/rmyjT-6mWwk_000170.mp4 playing flute +tests/VGGSound/video/rmzDww6glq8_000200.mp4 playing electronic organ +tests/VGGSound/video/rmzYDIM8xsM_000028.mp4 woodpecker pecking tree +tests/VGGSound/video/w6ePxZrd0Dw_000019.mp4 mynah bird singing +tests/VGGSound/video/w6h01lI5TKQ_000035.mp4 people sniggering +tests/VGGSound/video/w6inG9Js2Fg_000048.mp4 people marching +tests/VGGSound/video/w6mVxso5NOo_000002.mp4 zebra braying +tests/VGGSound/video/rnAR_z3mw48_000132.mp4 people nose blowing +tests/VGGSound/video/rnSSF1DaXww_000420.mp4 cap gun shooting +tests/VGGSound/video/rnWPIQBf54c_000030.mp4 cattle, bovinae cowbell +tests/VGGSound/video/rnsPxfODN4M_000009.mp4 door slamming +tests/VGGSound/video/ro4p6tXgNIA_000450.mp4 splashing water +tests/VGGSound/video/w7rYHuTG6qI_000030.mp4 fire crackling +tests/VGGSound/video/ro_xNfE2_8Q_000219.mp4 parrot talking +tests/VGGSound/video/ror99LVvtFo_000192.mp4 arc welding +tests/VGGSound/video/rosiOZ0VIHA_000338.mp4 playing badminton +tests/VGGSound/video/w8naAN5Sgic_000136.mp4 strike lighter +tests/VGGSound/video/w8r0MxrGQ18_000451.mp4 playing tuning fork +tests/VGGSound/video/w8u3udq84LY_000151.mp4 swimming +tests/VGGSound/video/w8wqxVdgAxA_000039.mp4 lathe spinning +tests/VGGSound/video/w9IrUp87_UQ_000120.mp4 donkey, ass braying +tests/VGGSound/video/rpkGCytpKzg_000042.mp4 cutting hair with electric trimmers +tests/VGGSound/video/rpoClsGXZWA_000000.mp4 warbler chirping +tests/VGGSound/video/rpxgZXOkr1A_000030.mp4 people eating +tests/VGGSound/video/rq4oQdSxrnI_000079.mp4 airplane flyby +tests/VGGSound/video/rqFPtPKpnpo_000011.mp4 children shouting +tests/VGGSound/video/rqNRRqAjk6g_000533.mp4 lathe spinning +tests/VGGSound/video/w9wfVOg6d1M_000006.mp4 beat boxing +tests/VGGSound/video/rr3ROJ0yOdk_000112.mp4 volcano explosion +tests/VGGSound/video/rrWsWt-rDrQ_000100.mp4 playing trombone +tests/VGGSound/video/wAtQza_yZE0_000432.mp4 fox barking +tests/VGGSound/video/wBU6_43ofGY_000070.mp4 people eating crisps +tests/VGGSound/video/rsOO65qFPv8_000380.mp4 people eating noodle +tests/VGGSound/video/rssAK31eM6I_000098.mp4 forging swords +tests/VGGSound/video/rssKOEp0xWI_000804.mp4 people eating noodle +tests/VGGSound/video/wCPEfqnHzNc_000067.mp4 alarm clock ringing +tests/VGGSound/video/wCQ1f3-d0wk_000030.mp4 people hiccup +tests/VGGSound/video/wCS4CGftfd8_000022.mp4 pig oinking +tests/VGGSound/video/rtTPwl-kz6k_000382.mp4 striking pool +tests/VGGSound/video/rtmgVQY5idQ_000004.mp4 chipmunk chirping +tests/VGGSound/video/wDE1b30zmJ8_000433.mp4 woodpecker pecking tree +tests/VGGSound/video/ruK8QzIWrSY_000080.mp4 canary calling +tests/VGGSound/video/wDg2v3NuCoQ_000075.mp4 hedge trimmer running +tests/VGGSound/video/rv4TRa-btas_000003.mp4 sloshing water +tests/VGGSound/video/wEBR--EtZAM_000413.mp4 chopping wood +tests/VGGSound/video/rvNKfBj-Nnk_000030.mp4 pig oinking +tests/VGGSound/video/rvjDcbLtU5I_000079.mp4 alligators, crocodiles hissing +tests/VGGSound/video/rvxT9Wk8B7o_000007.mp4 zebra braying +tests/VGGSound/video/rw0KRJIyyM4_000046.mp4 playing darts +tests/VGGSound/video/rwU2Pr9gxjo_000108.mp4 playing bugle +tests/VGGSound/video/wFOgHXUWFFM_000007.mp4 playing tuning fork +tests/VGGSound/video/wFTlySgdWX4_000030.mp4 playing vibraphone +tests/VGGSound/video/rwka0Ui94-w_000235.mp4 cow lowing +tests/VGGSound/video/wFhs7WVvuXk_000144.mp4 thunder +tests/VGGSound/video/rwmtZb4cEiY_000031.mp4 sea lion barking +tests/VGGSound/video/wFmekjmLAp4_000030.mp4 people whispering +tests/VGGSound/video/wFmxQZ_9nL0_000049.mp4 black capped chickadee calling +tests/VGGSound/video/rx3fg5zGSxg_000350.mp4 police car (siren) +tests/VGGSound/video/wG1EGAx0rRY_000033.mp4 metronome +tests/VGGSound/video/wGHq188CAs4_000090.mp4 sharpen knife +tests/VGGSound/video/wGJljLdNCag_000005.mp4 cutting hair with electric trimmers +tests/VGGSound/video/wGcq9cUby6A_000044.mp4 tap dancing +tests/VGGSound/video/wGms6MZt-vU_000040.mp4 people finger snapping +tests/VGGSound/video/ryOReH0GHx4_000147.mp4 canary calling +tests/VGGSound/video/ryWnOaICR80_000014.mp4 cat hissing +tests/VGGSound/video/rysEBq2ZeP4_000007.mp4 cat growling +tests/VGGSound/video/ryskM4LGrtk_000530.mp4 playing tambourine +tests/VGGSound/video/rysr8w7aTuQ_000000.mp4 cap gun shooting +tests/VGGSound/video/rzsynvpZKMg_000030.mp4 people running +tests/VGGSound/video/wILfzGo6uV0_000030.mp4 dog howling +tests/VGGSound/video/rzxqz7XqLHA_000220.mp4 helicopter 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impact +tests/VGGSound/video/s2avsLDhTUM_000062.mp4 cricket chirping +tests/VGGSound/video/s2pX9wHh-4E_000046.mp4 people gargling +tests/VGGSound/video/s2rKr07YOiM_000110.mp4 cat purring +tests/VGGSound/video/wM9UMHourhM_000164.mp4 playing glockenspiel +tests/VGGSound/video/wMLgi-rb6UM_000000.mp4 playing steelpan +tests/VGGSound/video/s3R9GaX6XrA_000000.mp4 people burping +tests/VGGSound/video/s3YWJr87Jsc_000017.mp4 air conditioning noise +tests/VGGSound/video/wMfSmB7V8ag_000080.mp4 playing harmonica +tests/VGGSound/video/wMi_0eEIpcM_000220.mp4 playing drum kit +tests/VGGSound/video/wNG49_jvQto_000030.mp4 people sniggering +tests/VGGSound/video/s477WHLPoOU_000000.mp4 playing piano +tests/VGGSound/video/s4BRktytaS4_000018.mp4 playing tennis +tests/VGGSound/video/wNpfisnFMtQ_000010.mp4 people screaming +tests/VGGSound/video/s4PCAzr_fdY_000046.mp4 golf driving +tests/VGGSound/video/s4PCAzr_fdY_000286.mp4 golf driving +tests/VGGSound/video/s4PN7iTLdVM_000050.mp4 playing steelpan 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+tests/VGGSound/video/s7VWJZhC4SY_000022.mp4 blowtorch igniting +tests/VGGSound/video/s87IYYmn1fQ_000060.mp4 playing saxophone +tests/VGGSound/video/s8PkY2iW4e8_000030.mp4 goose honking +tests/VGGSound/video/wRnBUv5KA94_000024.mp4 train wheels squealing +tests/VGGSound/video/s9EclzUqn9o_000157.mp4 playing djembe +tests/VGGSound/video/wSCbYNNeBhc_000050.mp4 mosquito buzzing +tests/VGGSound/video/s9GDIk99v54_000045.mp4 playing bassoon +tests/VGGSound/video/s9HV3WrbSno_000007.mp4 woodpecker pecking tree +tests/VGGSound/video/s9PftT7RgGo_000135.mp4 wood thrush calling +tests/VGGSound/video/s9d-2nhuJCQ_000030.mp4 playing drum kit +tests/VGGSound/video/wSb_KND6sa0_000029.mp4 air horn +tests/VGGSound/video/s9tf9PpC5yw_000010.mp4 bird wings flapping +tests/VGGSound/video/sAGJCkak8V0_000060.mp4 eating with cutlery +tests/VGGSound/video/sAL3qAUtF20_000001.mp4 playing castanets +tests/VGGSound/video/sAL3qAUtF20_000101.mp4 playing castanets +tests/VGGSound/video/sAMjMyCdGOc_000030.mp4 driving motorcycle +tests/VGGSound/video/wTN2MR0oMZ0_000032.mp4 playing glockenspiel +tests/VGGSound/video/wTOSS0cx50s_000170.mp4 people running +tests/VGGSound/video/wTduj6YOVuU_000010.mp4 baby laughter +tests/VGGSound/video/wTujz_6ZG9E_000061.mp4 airplane flyby +tests/VGGSound/video/wTviJbMRU18_000223.mp4 heart sounds, heartbeat +tests/VGGSound/video/sBDA78U_dps_000090.mp4 baby laughter +tests/VGGSound/video/wUc6HadpbBc_000000.mp4 door slamming +tests/VGGSound/video/wV7rzsXOBHA_000292.mp4 sharpen knife +tests/VGGSound/video/wVDpGmvoBns_000030.mp4 fire crackling +tests/VGGSound/video/wVK0m7FDkGs_000058.mp4 otter growling +tests/VGGSound/video/wVK0m7FDkGs_000107.mp4 otter growling +tests/VGGSound/video/wVLyIVxZ4PY_000533.mp4 people eating apple +tests/VGGSound/video/wVVBhbrnj9s_000040.mp4 people sobbing +tests/VGGSound/video/wVuG3imDmLU_000338.mp4 metronome +tests/VGGSound/video/wWEk1Hl2hK0_000134.mp4 mynah bird singing +tests/VGGSound/video/sE7fflraCpY_000009.mp4 playing gong 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+tests/VGGSound/video/wdbIsk487Fw_000100.mp4 playing violin, fiddle +tests/VGGSound/video/weC_DJ-hxx8_000187.mp4 people humming +tests/VGGSound/video/weFQftCey64_000087.mp4 gibbon howling +tests/VGGSound/video/sQ3NiBJoqtc_000112.mp4 playing shofar +tests/VGGSound/video/sQNdEhz_yNg_000110.mp4 playing cymbal +tests/VGGSound/video/sQbEIVxAfQ4_000583.mp4 planing timber +tests/VGGSound/video/sRKyvq20rY4_000002.mp4 dog growling +tests/VGGSound/video/sRdCCjXkFRU_000030.mp4 sheep bleating +tests/VGGSound/video/wfRWvI16wxw_000047.mp4 lions growling +tests/VGGSound/video/wfRWvI16wxw_000086.mp4 lions growling +tests/VGGSound/video/sS2GJNAXeWc_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/sS4SfCOFWxw_000030.mp4 people burping +tests/VGGSound/video/sSJAzADv_pw_000030.mp4 baby laughter +tests/VGGSound/video/wgIE51p26u8_000021.mp4 elk bugling +tests/VGGSound/video/wgT4rbZ5kvc_000022.mp4 people burping +tests/VGGSound/video/wgY59Dh8XMo_000141.mp4 francolin calling +tests/VGGSound/video/wgg6YgGx4Rk_000030.mp4 firing cannon +tests/VGGSound/video/wh1k5gFwumM_000334.mp4 police radio chatter +tests/VGGSound/video/sUHdX7FS5js_000001.mp4 cattle, bovinae cowbell +tests/VGGSound/video/sUK2ModmFU8_000140.mp4 sloshing water +tests/VGGSound/video/sUktuuWltHc_000010.mp4 donkey, ass braying +tests/VGGSound/video/sUlbABPLj7E_000047.mp4 chopping wood +tests/VGGSound/video/sVF7Q_IwoWY_000330.mp4 race car, auto racing +tests/VGGSound/video/sVGVLQV75AE_000037.mp4 playing bugle +tests/VGGSound/video/whdTql5vKno_000711.mp4 people eating crisps +tests/VGGSound/video/sVGmh0ZTXVs_000440.mp4 baby babbling +tests/VGGSound/video/when3v7NVFk_000000.mp4 train horning +tests/VGGSound/video/whqCUE1I98U_000009.mp4 writing on blackboard with chalk +tests/VGGSound/video/wi9wTTvdJjU_000314.mp4 arc welding +tests/VGGSound/video/sWXpzTZWNAI_000030.mp4 people belly laughing +tests/VGGSound/video/wiOUhsE48-g_000461.mp4 black capped chickadee calling 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+tests/VGGSound/video/s_8Mu0lIyFg_000151.mp4 striking pool +tests/VGGSound/video/wlmwUt4FU7k_000015.mp4 snake rattling +tests/VGGSound/video/s_8zsm4UHV4_000259.mp4 playing snare drum +tests/VGGSound/video/wlybajwoWlY_000226.mp4 train horning +tests/VGGSound/video/s_cGx_GByNQ_000030.mp4 skidding +tests/VGGSound/video/wm4O1oQKpcU_000073.mp4 woodpecker pecking tree +tests/VGGSound/video/wmQyktOSKv4_000030.mp4 people whispering +tests/VGGSound/video/wmStqt_0Ja4_000192.mp4 chimpanzee pant-hooting +tests/VGGSound/video/samyE_r0sXs_000130.mp4 goose honking +tests/VGGSound/video/wn0eOX4NW2w_000092.mp4 whale calling +tests/VGGSound/video/wn8XiU5i9HM_000000.mp4 opening or closing car electric windows +tests/VGGSound/video/sbZ5Ls141fg_000030.mp4 baby laughter +tests/VGGSound/video/wnLybpPLXk0_000012.mp4 woodpecker pecking tree +tests/VGGSound/video/wnQskk_yWkI_000011.mp4 owl hooting +tests/VGGSound/video/sbkfFiRlJXc_000021.mp4 owl hooting +tests/VGGSound/video/sbpW3Z87Nbc_000030.mp4 cattle mooing +tests/VGGSound/video/wnpgfk58Ws8_000039.mp4 bathroom ventilation fan running +tests/VGGSound/video/sc7KNFUEdfY_000030.mp4 duck quacking +tests/VGGSound/video/woE-jw5aYwU_000356.mp4 chopping wood +tests/VGGSound/video/woWw2_6KmN0_000004.mp4 gibbon howling +tests/VGGSound/video/scoFHRlgDjs_000009.mp4 chipmunk chirping +tests/VGGSound/video/scoFHRlgDjs_000069.mp4 chipmunk chirping +tests/VGGSound/video/sdJgpGJBQcI_000560.mp4 goat bleating +tests/VGGSound/video/sdLmwKPEBLg_000057.mp4 female singing +tests/VGGSound/video/se62EZurO8Q_000070.mp4 lawn mowing +tests/VGGSound/video/wpt_0upWXBY_000301.mp4 arc welding +tests/VGGSound/video/wq2BsXHkz4E_000378.mp4 playing djembe +tests/VGGSound/video/sfXt8h7KAHM_000030.mp4 pig oinking +tests/VGGSound/video/sfmAeijj5cM_000030.mp4 playing ukulele +tests/VGGSound/video/wqUdoAuKyDY_000027.mp4 playing squash +tests/VGGSound/video/sgO17DWwtoY_000280.mp4 playing cymbal +tests/VGGSound/video/wqe7p4y85ls_000030.mp4 people whispering 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+tests/VGGSound/video/skxOyyYReQk_000030.mp4 sailing +tests/VGGSound/video/sl37XQfkJCQ_000030.mp4 playing synthesizer +tests/VGGSound/video/wtiaDouhixI_000217.mp4 ice cracking +tests/VGGSound/video/wtvKeNPMwPk_000066.mp4 yodelling +tests/VGGSound/video/slOgYIKuAx4_000240.mp4 playing glockenspiel +tests/VGGSound/video/slbhA0hwhFY_000071.mp4 air horn +tests/VGGSound/video/wuIdKobdk7g_000017.mp4 playing bass drum +tests/VGGSound/video/wuIdKobdk7g_000142.mp4 playing bass drum +tests/VGGSound/video/wurA98TaEr4_000031.mp4 airplane flyby +tests/VGGSound/video/wurnc8yDd70_000037.mp4 scuba diving +tests/VGGSound/video/wuz0curb_hg_000180.mp4 cap gun shooting +tests/VGGSound/video/wv7lLolLuo0_000055.mp4 dog baying +tests/VGGSound/video/wvlhGSXTEoE_000430.mp4 people sobbing +tests/VGGSound/video/wxCduHF0GKI_000000.mp4 police car (siren) +tests/VGGSound/video/wxaWzq2zh38_000250.mp4 cattle, bovinae cowbell +tests/VGGSound/video/wy5edFMFcyM_000370.mp4 splashing water 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ventilation fan running +tests/VGGSound/video/x_2cbIrHG1k_000030.mp4 pigeon, dove cooing +tests/VGGSound/video/x_5t0os3A2I_000009.mp4 playing bongo +tests/VGGSound/video/x_5t0os3A2I_000025.mp4 playing bongo +tests/VGGSound/video/x_CFMV_BSPE_000212.mp4 race car, auto racing +tests/VGGSound/video/x_i_FLv7pNA_000021.mp4 cow lowing +tests/VGGSound/video/x_v89ZU2Zsk_000083.mp4 electric grinder grinding +tests/VGGSound/video/x_v89ZU2Zsk_000193.mp4 electric grinder grinding +tests/VGGSound/video/xa-lg7S1vns_000051.mp4 cat purring +tests/VGGSound/video/xa_eoYZRhbM_000210.mp4 firing muskets +tests/VGGSound/video/xakn94F6y7A_000099.mp4 hail +tests/VGGSound/video/xanOeYcQpcM_000020.mp4 lawn mowing +tests/VGGSound/video/xb07gLlmkL8_000030.mp4 playing synthesizer +tests/VGGSound/video/xbD2eVjgebU_000001.mp4 bull bellowing +tests/VGGSound/video/xbD9dc3D4tw_000034.mp4 eletric blender running +tests/VGGSound/video/xdTbo10j5tE_000242.mp4 bowling impact +tests/VGGSound/video/xdcjFp3L0FE_000003.mp4 baltimore oriole calling +tests/VGGSound/video/xbpucbIm_2Y_000100.mp4 civil defense siren +tests/VGGSound/video/xc0092TjO14_000063.mp4 zebra braying +tests/VGGSound/video/xcATi4rdSu8_000002.mp4 wood thrush calling +tests/VGGSound/video/xcYIvw3nMLE_000000.mp4 tractor digging +tests/VGGSound/video/xcoDPmy-UAY_000684.mp4 sea waves +tests/VGGSound/video/xcpTytjZNoQ_000135.mp4 train whistling +tests/VGGSound/video/xdlRZfywYdc_000000.mp4 singing bowl +tests/VGGSound/video/xez6gH4HbNY_000123.mp4 scuba diving +tests/VGGSound/video/xf0K_JCwmwg_000594.mp4 strike lighter +tests/VGGSound/video/xfGXhVboW9U_000050.mp4 turkey gobbling +tests/VGGSound/video/xfMpeoTViWw_000038.mp4 foghorn +tests/VGGSound/video/xfSN6wDm41o_000290.mp4 child singing +tests/VGGSound/video/xgD2aYuzcDQ_000000.mp4 swimming +tests/VGGSound/video/xgIHNLQdsNQ_000027.mp4 yodelling +tests/VGGSound/video/xgXd06kKFIQ_000000.mp4 playing vibraphone +tests/VGGSound/video/xgwzTQ8vnso_000030.mp4 playing synthesizer 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finger snapping +tests/VGGSound/video/xmTfE3F2huE_000854.mp4 chopping food +tests/VGGSound/video/xnA7O5ESAbY_000030.mp4 playing violin, fiddle +tests/VGGSound/video/xnMI64kXQA8_000252.mp4 cricket chirping +tests/VGGSound/video/xnVcy1PFlYM_000095.mp4 tornado roaring +tests/VGGSound/video/xneiSfKk0Lo_000030.mp4 lions roaring +tests/VGGSound/video/xoXTlNWkC7w_000170.mp4 playing congas +tests/VGGSound/video/xohOGGDgwZ8_000024.mp4 penguins braying +tests/VGGSound/video/xohrYDd1KCU_000140.mp4 playing bugle +tests/VGGSound/video/xooxjB2CNgE_000166.mp4 bouncing on trampoline +tests/VGGSound/video/xoxlmx1OfuQ_000112.mp4 playing bugle +tests/VGGSound/video/xpNdK4BcIks_000043.mp4 mouse clicking +tests/VGGSound/video/xqWpfNB7AzE_000110.mp4 people belly laughing +tests/VGGSound/video/xqhQTB860Lc_000036.mp4 people hiccup +tests/VGGSound/video/xrXgoZHnDko_000057.mp4 telephone bell ringing +tests/VGGSound/video/xsHb8V7bKbo_000010.mp4 people finger snapping +tests/VGGSound/video/xtEfTSC1PKc_000187.mp4 lathe spinning +tests/VGGSound/video/xtU4NZPuylU_000000.mp4 fireworks banging +tests/VGGSound/video/xuMBy2NoROI_000030.mp4 driving motorcycle +tests/VGGSound/video/xubIj3ag5t4_000233.mp4 playing erhu +tests/VGGSound/video/xuxKtxzq2Cs_000030.mp4 child singing +tests/VGGSound/video/xv35vO58cjY_000271.mp4 cell phone buzzing +tests/VGGSound/video/xv3l1Blx6JQ_000250.mp4 people belly laughing +tests/VGGSound/video/xvM2s-tXEZY_000134.mp4 bowling impact +tests/VGGSound/video/xvS7Izhl40o_000014.mp4 whale calling +tests/VGGSound/video/xvVz2LbGiMM_000167.mp4 people gargling +tests/VGGSound/video/xvVz2LbGiMM_000312.mp4 people gargling +tests/VGGSound/video/xvWXCKygxJQ_000030.mp4 playing flute +tests/VGGSound/video/xvdOFvI6tAY_000060.mp4 cupboard opening or closing +tests/VGGSound/video/xvuvBU9es1Y_000516.mp4 people slurping +tests/VGGSound/video/xvw3Z5-6h1A_000010.mp4 splashing water +tests/VGGSound/video/xw3yx95ZsLg_000030.mp4 singing bowl +tests/VGGSound/video/xwDJy7bJurM_000277.mp4 black capped chickadee calling +tests/VGGSound/video/xwJ4G84jc1w_000018.mp4 playing bugle +tests/VGGSound/video/xwJ4G84jc1w_000051.mp4 playing bugle +tests/VGGSound/video/xwaoejkBDe0_000009.mp4 chipmunk chirping +tests/VGGSound/video/xwrpD8jQupw_000081.mp4 chopping food +tests/VGGSound/video/xxxorj7BKe0_000064.mp4 playing squash +tests/VGGSound/video/xy9rQMXfKBE_000146.mp4 electric grinder grinding +tests/VGGSound/video/xyco-5DC_K8_000030.mp4 playing sitar +tests/VGGSound/video/y-3Z8vypfDs_000038.mp4 playing bongo +tests/VGGSound/video/y05npVHuQtg_000024.mp4 cattle mooing +tests/VGGSound/video/y0CtU8_Den0_000000.mp4 playing vibraphone +tests/VGGSound/video/y0TDJyuco0I_000010.mp4 playing drum kit +tests/VGGSound/video/y0d6Crj5U8g_000069.mp4 driving snowmobile +tests/VGGSound/video/y0rbS-AJVc0_000338.mp4 scuba diving +tests/VGGSound/video/y1DgTYLdesA_000136.mp4 beat boxing +tests/VGGSound/video/y1orCLNC7bw_000245.mp4 people slurping +tests/VGGSound/video/y2J_kErcaDI_000245.mp4 wood thrush calling 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slamming +tests/VGGSound/video/yO5YnmljmoQ_000001.mp4 children shouting +tests/VGGSound/video/yO8Jl8Jbdik_000005.mp4 blowtorch igniting +tests/VGGSound/video/yOP7z54BXYo_000030.mp4 playing harpsichord +tests/VGGSound/video/yOq3d33TSic_000240.mp4 wind noise +tests/VGGSound/video/yP4p5P3h8ag_000213.mp4 yodelling +tests/VGGSound/video/yPou7kokTgA_000030.mp4 playing sitar +tests/VGGSound/video/yQDWqmzQ7RQ_000100.mp4 stream burbling +tests/VGGSound/video/yQMi8hinORM_000140.mp4 playing steelpan +tests/VGGSound/video/yQQG03dAoLU_000020.mp4 driving motorcycle +tests/VGGSound/video/yQWGYlXiqXk_000002.mp4 swimming +tests/VGGSound/video/yQa3SuKpfLE_000093.mp4 people eating apple +tests/VGGSound/video/yQhUzCu4kQY_000015.mp4 woodpecker pecking tree +tests/VGGSound/video/yRBKGI1DjXc_000411.mp4 footsteps on snow +tests/VGGSound/video/yRH-c9RbkAQ_000376.mp4 people eating apple +tests/VGGSound/video/yRek1QAtFgU_000013.mp4 spraying water +tests/VGGSound/video/ySNRJCMMTu4_000040.mp4 playing volleyball 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