VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation

ACL 2021  ·  Changhan Wang, Morgane Rivière, Ann Lee, Anne Wu, Chaitanya Talnikar, Daniel Haziza, Mary Williamson, Juan Pino, Emmanuel Dupoux ·

We introduce VoxPopuli, a large-scale multilingual corpus providing 100K hours of unlabelled speech data in 23 languages. It is the largest open data to date for unsupervised representation learning as well as semi-supervised learning. VoxPopuli also contains 1.8K hours of transcribed speeches in 16 languages and their aligned oral interpretations into 5 other languages totaling 5.1K hours. We provide speech recognition baselines and validate the versatility of VoxPopuli unlabelled data in semi-supervised learning under challenging out-of-domain settings. We will release the corpus at https://github.com/facebookresearch/voxpopuli under an open license.

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Datasets

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VoxPopuli

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LibriSpeech Common Voice Europarl-ST

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Ranked #3 on Speech Recognition on Common Voice French (using extra training data)

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Task Dataset Model Metric Name Metric Value Global Rank Uses Extra
Training Data 		Result Benchmark
Speech Recognition Common Voice French VoxPopuli-50K (n-gram) Test WER 9.6% # 3
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Speech Recognition Common Voice German VoxPopuli (n-gram) Test WER 7.8% # 12
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Speech Recognition Common Voice Spanish VoxPopuli-50K (n-gram) Test WER 10.0% # 6
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