---
task_categories:
- audio-classification
- automatic-speech-recognition
tags:
- speech-recognition
- emotion-classication
- age-detection
- gender-detection
- entity-tagging
- intent-detection
- speech-transcription
- librispeech
- common-voice
language:
- en
- de
- es
- it
- fr
- pt
---
# Meta Speech Recognition European Languages Dataset (v1)

This dataset contains only the metadata (JSON/Parquet) for European language speech recognition samples.  
**Audio files are NOT included.**

## Data Download Links

### CommonVoice
- [CommonVoice Dataset](https://commonvoice.mozilla.org/en/datasets)
  - German (de)
  - English (en)
  - Spanish (es)
  - French (fr)
  - Italian (it)
  - Portuguese (pt)

### Multilingual LibriSpeech (MLS)
- [Multilingual LibriSpeech Dataset](https://www.openslr.org/94/)
  - German: [mls_german.tar.gz](https://dl.fbaipublicfiles.com/mls/mls_german.tar.gz)
  - English: [mls_english.tar.gz](https://dl.fbaipublicfiles.com/mls/mls_english.tar.gz)
  - Spanish: [mls_spanish.tar.gz](https://dl.fbaipublicfiles.com/mls/mls_spanish.tar.gz)
  - French: [mls_french.tar.gz](https://dl.fbaipublicfiles.com/mls/mls_french.tar.gz)
  - Italian: [mls_italian.tar.gz](https://dl.fbaipublicfiles.com/mls/mls_italian.tar.gz)
  - Portuguese: [mls_portuguese.tar.gz](https://dl.fbaipublicfiles.com/mls/mls_portuguese.tar.gz)

### People's Speech
- [People's Speech Dataset](https://huggingface.co/datasets/MLCommons/peoples_speech)


## Dataset Statistics

### Splits and Sample Counts
- **train**: 5140607 samples
- **valid**: 194933 samples
- **test**: 208743 samples

## Example Samples
### train
```json
{
  "audio_filepath": "/cv/cv-corpus-15.0-2023-09-08/es/clips/common_voice_es_19698530.mp3",
  "text": "Habita en aguas poco profundas y rocosas. AGE_30_45 GER_MALE EMOTION_NEUTRAL INTENT_INFORM",
  "duration": 3.67,
  "source": "commonvoice_es"
}
```
```json
{
  "audio_filepath": "/cv/cv-corpus-15.0-2023-09-08/es/clips/common_voice_es_19987333.mp3",
  "text": "Opera principalmente vuelos de cabotaje y regionales de carga. AGE_18_30 GER_FEMALE EMOTION_NEUTRAL INTENT_INFORM",
  "duration": 6.86,
  "source": "commonvoice_es"
}
```

### valid
```json
{
  "audio_filepath": "/cv/cv-corpus-15.0-2023-09-08/fr/clips2/common_voice_fr_18031586.mp3",
  "text": "Je vais mordre dans cet oiseau. AGE_45_60 GER_MALE EMOTION_DISGUST INTENT_INFORM",
  "duration": 2.38,
  "source": "commonvoice_fr"
}
```
```json
{
  "audio_filepath": "/cv/cv-corpus-15.0-2023-09-08/fr/clips2/common_voice_fr_18031602.mp3",
  "text": "L'entrevue fut courte, mais bien affectueuse et bien douloureuse de part et d'autre. AGE_45_60 GER_MALE EMOTION_DISGUST INTENT_INFORM",
  "duration": 5.57,
  "source": "commonvoice_fr"
}
```

### test
```json
{
  "audio_filepath": "/librespeech-en/train-other-500/1646/121408/1646-121408-0038.flac",
  "text": "As I was re conducting, the young man for whom you have asked, he approached the glass door of the gallery, and gazed intently upon some object, doubtless the picture by Raphael, which is opposite the door, he reflected for a second, and then descended the stairs. AGE_30_45 GER_MALE EMOTION_NEU INTENT_DESCRIBE",
  "duration": 14.91,
  "source": "librispeech_en"
}
```
```json
{
  "audio_filepath": "/librespeech-en/train-other-500/3409/173540/3409-173540-0013.flac",
  "text": "Have suffered so much but my dear child, consult only your own heart. That is all I have to say, and concealing his unvarying emotion. AGE_45_60 GER_FEMALE EMOTION_SAD INTENT_INFORM",
  "duration": 12.47,
  "source": "librispeech_en"
}
```