CoVoST 2 French - English

Description

This dataset contains 236897 audio clips totalling 276:40:21 of audio in French with the corresponding translations in English.

Background

End-to-end speech-to-text translation (ST) has recently witnessed an increased interest given its system simplicity, lower inference latency and less compounding errors compared to cascaded ST (i.e. speech recognition + machine translation). End-to-end ST model training, however, is often hampered by the lack of parallel data. Thus, we created CoVoST, a large-scale multilingual ST corpus based on Common Voice, to foster ST research with the largest ever open dataset. Its latest version covers translations from English into 15 languages---Arabic, Catalan, Welsh, German, Estonian, Persian, Indonesian, Japanese, Latvian, Mongolian, Slovenian, Swedish, Tamil, Turkish, Chinese---and from 21 languages into English, including the 15 target languages as well as Spanish, French, Italian, Dutch, Portuguese, Russian. It has total 2,880 hours of speech and is diversified with 78K speakers.

Fields

• path: Filename of the audio file

• sentence: The sentence in the source language

• translation: The sentence in the target language

• client_id: The ID of the speaker of the source language, used for maintaining hygiene in the splits.

Example

['path\tsentence\ttranslation\tclient_id\n', 'common_voice_fr_17732749.mp3\tMadame la baronne Pfeffers.\tMadam Pfeffers the baroness.\t796d9ae74694eadea3f343a7e0dfe35f89a6a321d534846c71bf4c56ee1d4629b9d8c116fc8a3adb1b6b79af91e6719becb103c3b2ccf0b84f7ffd277598784e\n', 'common_voice_fr_17732750.mp3\tVous savez aussi bien que moi que de nombreuses molécules innovantes ont malheureusement déçu.\tYou know as well as I do that many new molecules have unfortunately been disappointing.\t796d9ae74694eadea3f343a7e0dfe35f89a6a321d534846c71bf4c56ee1d4629b9d8c116fc8a3adb1b6b79af91e6719becb103c3b2ccf0b84f7ffd277598784e\n', 'common_voice_fr_17732751.mp3\tOh ! parce que maintenant, quand on parle de boire, je m’en vais !\tOh! Because now, when we talk about drinking, I leave!\t796d9ae74694eadea3f343a7e0dfe35f89a6a321d534846c71bf4c56ee1d4629b9d8c116fc8a3adb1b6b79af91e6719becb103c3b2ccf0b84f7ffd277598784e\n', 'common_voice_fr_17732752.mp3\tLes questions sanitaires placent l’enfant au cœur de la problématique de l’évolution humaine.\tThe sanitary issues put the child at the heart of the human evolution question.\t796d9ae74694eadea3f343a7e0dfe35f89a6a321d534846c71bf4c56ee1d4629b9d8c116fc8a3adb1b6b79af91e6719becb103c3b2ccf0b84f7ffd277598784e\n']

Splits

Citation

If you use this dataset in your work please cite

@misc{wang2020covost,
    title={CoVoST 2: A Massively Multilingual Speech-to-Text Translation Corpus},
    author={Changhan Wang and Anne Wu and Juan Pino},
    year={2020},
    eprint={2007.10310},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}