facebook/omnilingual-asr-corpus

Meta Omnilingual ASR Corpus

The Omnilingual ASR Corpus is a collection of spontaneous speech recordings and their transcriptions for 348 under-served languages. The corpus was collected as part of Meta FAIR’s Omnilingual ASR project (blog, model, paper) for the purposes of training automatic speech recognition (ASR) and spoken language identification models.

Data schema

{
    `language`: "lij_Latn",
    `iso_639_3`: "lij",
    `iso_15924`: "Latn",
    `glottocode`: "geno1240",
    `prompt_id`: "C086",
    `prompt`: "What was the last thing you ate? Can you describe how it is made?",
    `speaker_id`: "spk02",
    `segment_id`: "s01",
    `audio`: "<Audio data in FLAC format>",
    `raw_text`: "Me son tòsto fæto un panetto co-o formaggio, ma quello a-a catalaña, saiva à dî con o pan un pittin brustolio e pöi a tomata sciaccâ in çimma, tanto euio e un pittin de sâ, e dapeu se ghe mette o companægo, into mæ caxo o formaggio.",
}

Language codes

Language codes in the language column follow the format {lang}_{script}, where {lang} is an ISO 639-3 three-letter language code, and {script} is an ISO 15924 four-letter script code. To allow for greater granularity when warranted, we provide the additional glottocode column, containing Glottolog languoid codes.

Special tags

The following special tags were used in transcriptions (raw_text field) to mark laughter, fillers and other types of non-verbal content:

Tag	Purpose
<laugh>	The sound of laughter.
<hesitation>	A hesitation sound, often used by speakers while thinking of the next thing to say. In English, some common hesitation sounds are “err”, “um”, “huh”, etc.
<unintelligible>	A word or sequence of words that cannot be understood.
<noise>	Any other type of noise, such as the speaker coughing or clearing their throat, a car honking, the sound of something hitting the microphone, a phone buzzing, etc.

Disfluencies

Spontaneous speech naturally contains false starts, where only a fragment of a full word is produced. False starts were transcribed as they appeared in the recording and a hyphen was attached at the end of the word fragment (-), e.g.:

His name is Jo- Jona- Jonathan.

Repeated words were also faithfully transcribed, e.g.:

And then I went to the the the bed- the bedroom

License

This corpus is released under CC-BY-4.0.

Citation

If you make use of this dataset in your work, please cite:

@misc{omnilingualasr2025,
    title={{Omnilingual ASR}: Open-Source Multilingual Speech Recognition for 1600+ Languages},
    author={{Omnilingual ASR Team} and Keren, Gil and Kozhevnikov, Artyom and Meng, Yen and Ropers, Christophe and Setzler, Matthew and Wang, Skyler and Adebara, Ife and Auli, Michael and Chan, Kevin and Cheng, Chierh and Chuang, Joe and Droof, Caley and Duppenthaler, Mark and Duquenne, Paul-Ambroise and Erben, Alexander and Gao, Cynthia and Mejia Gonzalez, Gabriel and Lyu, Kehan and Miglani, Sagar and Pratap, Vineel and Sadagopan, Kaushik Ram and Saleem, Safiyyah and Turkatenko, Arina and Ventayol-Boada, Albert and Yong, Zheng-Xin and Chung, Yu-An and Maillard, Jean and Moritz, Rashel and Mourachko, Alexandre and Williamson, Mary and Yates, Shireen},
    year={2025},
    url={https://ai.meta.com/research/publications/omnilingual-asr-open-source-multilingual-speech-recognition-for-1600-languages/},
}