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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation Wang, Changhan; Rivière, Morgane; Lee, Ann. - : HAL CCSD, 2021 In: https://hal.inria.fr/hal-03329290 ; 2021, ⟨10.18653/v1/2021.acl-long.80⟩ (2021) BASE Show details 2 VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation ... Wang, Changhan; Rivière, Morgane; Lee, Ann. - : arXiv, 2021 BASE Show details 3 VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Dupoux, Emmanuel; Haziza, dhaziza@fb.com. - : Underline Science Inc., 2021 BASE Show details 4 CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus ... Wang, Changhan; Pino, Juan; Wu, Anne; Gu, Jiatao. - : arXiv, 2020 Abstract: Spoken language translation has recently witnessed a resurgence in popularity, thanks to the development of end-to-end models and the creation of new corpora, such as Augmented LibriSpeech and MuST-C. Existing datasets involve language pairs with English as a source language, involve very specific domains or are low resource. We introduce CoVoST, a multilingual speech-to-text translation corpus from 11 languages into English, diversified with over 11,000 speakers and over 60 accents. We describe the dataset creation methodology and provide empirical evidence of the quality of the data. We also provide initial benchmarks, including, to our knowledge, the first end-to-end many-to-one multilingual models for spoken language translation. CoVoST is released under CC0 license and free to use. We also provide additional evaluation data derived from Tatoeba under CC licenses. ... : LREC 2020 camera-ready ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2002.01320 https://arxiv.org/abs/2002.01320 BASE Hide details 5 CoVoST 2 and Massively Multilingual Speech-to-Text Translation ... Wang, Changhan; Wu, Anne; Pino, Juan. - : arXiv, 2020 BASE Show details

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