https://arxiv.org/abs/2303.00628
A Multilingual Audio-Visual Corpus for Robust Speech Recognition and Robust Speech-to-Text Translation.
MuAViC provides
- 1200 hours of transcribed audio-visual speech for 9 languages (English, Arabic, German, Greek, Spanish, French, Italian, Portuguese and Russian)
- text translations for 6 English-to-X directions and 6 X-to-English directions (X = Greek, Spanish, French, Italian, Portuguese or Russian)
The raw data is collected from TED/TEDx talk recordings.
Audio-Visual Speech Recognition
| Language | Code | Train Hours (H+P) | Train Speakers |
|---|---|---|---|
| English | En | 436 + 0 | 4.7K |
| Arabic | Ar | 16 + 0 | 95 |
| German | De | 10 + 0 | 53 |
| Greek | El | 25 + 0 | 113 |
| Spanish | Es | 178 + 0 | 987 |
| French | Fr | 176 + 0 | 948 |
| Italian | It | 101 + 0 | 487 |
| Portuguese | Pt | 153 + 0 | 810 |
| Russian | Ru | 49 + 0 | 238 |
Audio-Visual En-X Speech-to-Text Translation
| Direction | Code | Train Hours (H+P) | Train Speakers |
|---|---|---|---|
| English-Greek | En-El | 17 + 420 | 4.7K |
| English-Spanish | En-Es | 21 + 416 | 4.7K |
| English-French | En-Fr | 21 + 416 | 4.7K |
| English-Italian | En-It | 20 + 417 | 4.7K |
| English-Portuguese | En-Pt | 18 + 419 | 4.7K |
| English-Russian | En-Ru | 20 + 417 | 4.7K |
Audio-Visual X-En Speech-to-Text Translation
| Direction | Code | Train Hours (H+P) | Train Speakers |
|---|---|---|---|
| Greek-English | El-En | 8 + 17 | 113 |
| Spanish-English | Es-En | 64 + 114 | 987 |
| French-English | Fr-En | 45 + 131 | 948 |
| Italian-English | It-En | 48 + 53 | 487 |
| Portuguese-English | Pt-En | 53 + 100 | 810 |
| Russian-English | Ru-En | 8 + 41 | 238 |
We provide scripts to generate the audio/video data and AV-HuBERT training manifests for MuAViC.
As the first step, clone this repo for the scripts
git clone https://github.com/facebookresearch/muavic.gitand install required packages:
conda install -c conda-forge ffmpeg==4.2.2
pip install -r requirements.txtThen get audio-visual speech recognition and translation data via
python get_data.py --root-path ${ROOT} --src-lang ${SRC_LANG}where the speech language ${SRC_LANG} is one of en, ar, de, el, es, fr, it, pt and ru.
Generated data will be saved to ${ROOT}/muavic:
${ROOT}/muavic/${SRC_LANG}/audiofor processed audio files${ROOT}/muavic/${SRC_LANG}/videofor processed video files${ROOT}/muavic/${SRC_LANG}/*.tsvfor AV-HuBERT AVSR training manifests${ROOT}/muavic/${SRC_LANG}/${TGT_LANG}*.tsvfor AV-HuBERT AVST training manifests
CC-BY-NC 4.0
@article{anwar2023muavic,
title={MuAViC: A Multilingual Audio-Visual Corpus for Robust Speech Recognition and Robust Speech-to-Text Translation},
author={Anwar, Mohamed and Shi, Bowen and Goswami, Vedanuj and Hsu, Wei-Ning and Pino, Juan and Wang, Changhan},
journal={arXiv preprint arXiv:2303.00628},
year={2023}
}