straqen / muavic

MuAViC: A Multilingual Audio-Visual Corpus for Robust Speech Recognition and Robust Speech-to-Text Translation

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

MuAViC

https://arxiv.org/abs/2303.00628

A Multilingual Audio-Visual Corpus for Robust Speech Recognition and Robust Speech-to-Text Translation.

Overview

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)
MuAViC data statistics

The raw data is collected from TED/TEDx talk recordings.

Detailed statistics

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

Getting Data

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.git

and install required packages:

conda install -c conda-forge ffmpeg==4.2.2
pip install -r requirements.txt

Then 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}/audio for processed audio files
  • ${ROOT}/muavic/${SRC_LANG}/video for processed video files
  • ${ROOT}/muavic/${SRC_LANG}/*.tsv for AV-HuBERT AVSR training manifests
  • ${ROOT}/muavic/${SRC_LANG}/${TGT_LANG}*.tsv for AV-HuBERT AVST training manifests

License

CC-BY-NC 4.0

Citation

@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}
}

About

MuAViC: A Multilingual Audio-Visual Corpus for Robust Speech Recognition and Robust Speech-to-Text Translation

License:Other


Languages

Language:Python 100.0%