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License:
CC-BY-NC-4.0
Steward:
MDC Curators
Task: MT
Release Date: 5/9/2026
Format: MP3, TSV
Size: 148.21 MB
Share
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 Arabic audio 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.
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_ar_19134079.mp3 .هذه ملحوظة مهمة للغاية That’s a very important note. f5332db8ce939969b03ff6f9ca6dc548cd0bafcd3da7a06131547f24b0c1ce72a63e3124e6a6801678287c33a7cdd546b78523ee69689f9418d5448809febfc1
common_voice_ar_19134080.mp3 من اخترع هذه الآلة ؟ Who invented this machine? f5332db8ce939969b03ff6f9ca6dc548cd0bafcd3da7a06131547f24b0c1ce72a63e3124e6a6801678287c33a7cdd546b78523ee69689f9418d5448809febfc1
common_voice_ar_19134081.mp3 ليس لديه بيت ليعيش فيه. He doesn't have a house to live in. f5332db8ce939969b03ff6f9ca6dc548cd0bafcd3da7a06131547f24b0c1ce72a63e3124e6a6801678287c33a7cdd546b78523ee69689f9418d5448809febfc1
common_voice_ar_19134082.mp3 ماذا ستفعل في عطلة نهاية الأسبوع ؟ What are you doing this weekend? f5332db8ce939969b03ff6f9ca6dc548cd0bafcd3da7a06131547f24b0c1ce72a63e3124e6a6801678287c33a7cdd546b78523ee69689f9418d5448809febfc1
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}
}