YODAS: Youtube-Oriented Dataset for Audio and Speech
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866911900454879232 |
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| author | Li, Xinjian Takamichi, Shinnosuke Saeki, Takaaki Chen, William Shiota, Sayaka Watanabe, Shinji |
| author_facet | Li, Xinjian Takamichi, Shinnosuke Saeki, Takaaki Chen, William Shiota, Sayaka Watanabe, Shinji |
| contents | In this study, we introduce YODAS (YouTube-Oriented Dataset for Audio and Speech), a large-scale, multilingual dataset comprising currently over 500k hours of speech data in more than 100 languages, sourced from both labeled and unlabeled YouTube speech datasets. The labeled subsets, including manual or automatic subtitles, facilitate supervised model training. Conversely, the unlabeled subsets are apt for self-supervised learning applications. YODAS is distinctive as the first publicly available dataset of its scale, and it is distributed under a Creative Commons license. We introduce the collection methodology utilized for YODAS, which contributes to the large-scale speech dataset construction. Subsequently, we provide a comprehensive analysis of speech, text contained within the dataset. Finally, we describe the speech recognition baselines over the top-15 languages. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_00899 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | YODAS: Youtube-Oriented Dataset for Audio and Speech Li, Xinjian Takamichi, Shinnosuke Saeki, Takaaki Chen, William Shiota, Sayaka Watanabe, Shinji Computation and Language Sound Audio and Speech Processing In this study, we introduce YODAS (YouTube-Oriented Dataset for Audio and Speech), a large-scale, multilingual dataset comprising currently over 500k hours of speech data in more than 100 languages, sourced from both labeled and unlabeled YouTube speech datasets. The labeled subsets, including manual or automatic subtitles, facilitate supervised model training. Conversely, the unlabeled subsets are apt for self-supervised learning applications. YODAS is distinctive as the first publicly available dataset of its scale, and it is distributed under a Creative Commons license. We introduce the collection methodology utilized for YODAS, which contributes to the large-scale speech dataset construction. Subsequently, we provide a comprehensive analysis of speech, text contained within the dataset. Finally, we describe the speech recognition baselines over the top-15 languages. |
| title | YODAS: Youtube-Oriented Dataset for Audio and Speech |
| topic | Computation and Language Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2406.00899 |