Dataset Card for covost2

Dataset Summary

CoVoST 2 is a large-scale multilingual speech translation corpus covering translations from 21 languages into English
and from English into 15 languages. The dataset is created using Mozillas open-source Common Voice database of
crowdsourced voice recordings. There are 2,900 hours of speech represented in the corpus.

Supported Tasks and Leaderboards

speech-translation: The dataset can be used for Speech-to-text translation (ST). The model is presented with an audio file in one language and asked to transcribe the audio file to written text in another language. The most common evaluation metric is the BLEU score. Examples can be found at https://github.com/pytorch/fairseq/blob/master/examples/speech_to_text/docs/covost_example.md .

Languages

The dataset contains the audio, transcriptions, and translations in the following languages, French, German, Dutch, Russian, Spanish, Italian, Turkish, Persian, Swedish, Mongolian, Chinese, Welsh, Catalan, Slovenian, Estonian, Indonesian, Arabic, Tamil, Portuguese, Latvian, and Japanese.

Dataset Structure

Data Instances

A typical data point comprises the path to the audio file, usually called file, its transcription, called sentence, and the translation in target language called translation.

{'client_id': 'd277a1f3904ae00b09b73122b87674e7c2c78e08120721f37b5577013ead08d1ea0c053ca5b5c2fb948df2c81f27179aef2c741057a17249205d251a8fe0e658',
 'file': '/home/suraj/projects/fairseq_s2t/covst/dataset/en/clips/common_voice_en_18540003.mp3',
 'audio': {'path': '/home/suraj/projects/fairseq_s2t/covst/dataset/en/clips/common_voice_en_18540003.mp3',
           'array': array([-0.00048828, -0.00018311, -0.00137329, ...,  0.00079346, 0.00091553,  0.00085449], dtype=float32),
           'sampling_rate': 48000},
 'id': 'common_voice_en_18540003',
 'sentence': 'When water is scarce, avoid wasting it.',
 'translation': 'Wenn Wasser knapp ist, verschwenden Sie es nicht.'}

Data Fields

• file: A path to the downloaded audio file in .mp3 format.

• audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: dataset[0]["audio"] the audio file is automatically decoded and resampled to dataset.features["audio"].sampling_rate. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the "audio" column, i.e. dataset[0]["audio"] should always be preferred over dataset["audio"][0].

• sentence: The transcription of the audio file in source language.

• translation: The transcription of the audio file in the target language.

• id: unique id of the data sample.

Data Splits

Dataset Creation

Curation Rationale

[Needs More Information]

Source Data

Initial Data Collection and Normalization

[Needs More Information]

Who are the source language producers?

[Needs More Information]

Annotations

Annotation process

[Needs More Information]

Who are the annotators?

[Needs More Information]

Personal and Sensitive Information

The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset.

Considerations for Using the Data

Social Impact of Dataset

[Needs More Information]

Discussion of Biases

[Needs More Information]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

[Needs More Information]

Licensing Information

CC BY-NC 4.0

Citation Information

@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}

Contributions

Thanks to @patil-suraj for adding this dataset.