VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation (2021.acl-long)
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Changhan Wang, Morgane Riviere, Ann Lee, Anne Wu, Chaitanya Talnikar, Daniel Haziza, Mary Williamson, Juan Pino, Emmanuel Dupoux
| Challenge: | VoxPopuli provides 400K hours of unlabeled speech data in 23 languages . large amounts of multilingual audio data are needed to achieve similar progress for multilingual ASR and ST. |
| Approach: | They propose a large-scale multilingual corpus that provides 400K hours of unlabeled speech data in 23 languages. |
| Outcome: | The proposed corpus provides 400K hours of unlabeled speech data in 23 languages and 1.8K hours transcribed speeches in 15 languages and their aligned oral interpretations into 15 target languages totaling 17.3K hours. |
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