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Task: MT
Release Date: 5/15/2026
Format: MP3, TSV
Size: 127.28 MB
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CoVoST 2 is a large-scale multilingual speech to text translation corpus based on Mozilla Common Voice 4.0. This segment of the corpus contains the Latvian audio (4 hours) and the translations in English.
Licensing
Creative Commons Attribution Non Commercial 4.0 International (CC-BY-NC-4.0)
https://spdx.org/licenses/CC-BY-NC-4.0.htmlRestrictions/Special Constraints
Research and non-commercial use only.
Forbidden Usage
You agree not to attempt to determine the identity of speakers in this dataset. You agree not to train models for public distribution on this dataset. Any attempt to clone the voice or train models that imitate the speakers in this dataset is forbidden.
Ethical Review
This dataset contains data from speakers who have asked to be removed from the Mozilla Common Voice dataset, we expect that you will treat it with care. We expect it to be used only for research and non-commercial purposes only.
Intended Use
Replication experiments involving the CoVoST 2 datasets.
This dataset contains 5094 audio clips totalling 04:13:11 of audio in Latvian with the corresponding translations in English.
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.
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.
path sentence translation client_id
common_voice_lv_19396785.mp3 Nenoturējās biznesā diez ko ilgi, bet tas ir ļoti neparedzams bizness. He didn’t last too long in business, but it’s a very unpredictable business. 861eba97cfcab54709d73b55bf539dd28bd3489304153452e1b6d32e515c6df5df8ea4a4561a9cb1441f1604077e876c7fb050e346b77e75fc96be59ce3eed1e
common_voice_lv_19396798.mp3 Interesanta doma. An interesting thought. 861eba97cfcab54709d73b55bf539dd28bd3489304153452e1b6d32e515c6df5df8ea4a4561a9cb1441f1604077e876c7fb050e346b77e75fc96be59ce3eed1e
common_voice_lv_19396799.mp3 Es nebiju baznīcā. Es neticu laulībām. I wasn’t in church. I don’t believe in marriage. 861eba97cfcab54709d73b55bf539dd28bd3489304153452e1b6d32e515c6df5df8ea4a4561a9cb1441f1604077e876c7fb050e346b77e75fc96be59ce3eed1e
common_voice_lv_19396800.mp3 Viņš noteikti nospiedīs to pogu. He’ll definitely press the button. 861eba97cfcab54709d73b55bf539dd28bd3489304153452e1b6d32e515c6df5df8ea4a4561a9cb1441f1604077e876c7fb050e346b77e75fc96be59ce3eed1e
| # clips | |
|---|---|
| Train | 2338 |
| Dev | 1126 |
| Test | 1630 |
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}
}