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

2 Jan 2021ACL 2021 5arXiv:2101.00390archive 2025-07-28

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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Tasks

Representation LearningSpeech Recognitionspeech-recognition

Datasets

Introduced by this paper, per the archive.

VoxPopuli

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Speech Recognition Common Voice French VoxPopuli-50K (n-gram) Test WER 9.6% #3 of 8 Archive leaderboard report
Speech Recognition Common Voice German VoxPopuli (n-gram) Test WER 7.8% #12 of 14 Archive leaderboard report
Speech Recognition Common Voice Spanish VoxPopuli-50K (n-gram) Test WER 10.0% #7 of 8 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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