---
datasets:
- KTH/hungarian-single-speaker-tts
language:
- hu
base_model:
- microsoft/speecht5_tts
license: mit
pipeline_tag: text-to-speech
---

An experimental speechT5 finetune for Hungarian.

```
from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan
from datasets import load_dataset
import torch
from IPython.display import Audio

processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
model = SpeechT5ForTextToSpeech.from_pretrained("GaborMadarasz/speecht5_tts_KTH_hu")
vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")

inputs = processor(text="Azóta, hogy nem láttuk őket, nyolc esztendő telt el.", return_tensors="pt")

# load xvector containing speaker's voice characteristics from a dataset
embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
speaker_embeddings = torch.tensor(embeddings_dataset[7406]["xvector"]).unsqueeze(0)

speech = model.generate_speech(inputs["input_ids"], speaker_embeddings, vocoder=vocoder)


# Jupyter audio 
Audio(speech, rate=16000)
```