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

被引：0

作者：

Wang, Changhan ^{[1
]}

Riviere, Morgane ^{[1
]}

Lee, Ann ^{[1
]}

Wu, Anne ^{[1
]}

Talnikar, Chaitanya ^{[1
]}

Haziza, Daniel ^{[1
]}

Williamson, Mary ^{[1
]}

Pino, Juan ^{[1
]}

Dupoux, Emmanuel ^{[1
]}

机构：

[1] Facebook AI Research, Menlo Pk, CA 94025 USA

来源：

59TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 11TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING, VOL 1 (ACL-IJCNLP 2021) | 2021年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce VoxPopuli, a large-scale multilingual corpus providing 400K hours of unlabeled 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 15 languages and their aligned oral interpretations into 15 target languages totaling 17.3K hours. We provide speech recognition (ASR) baselines and validate the versatility of VoxPopuli unlabeled data in semi-supervised ASR and speech-to-text translation under challenging out-of-domain settings.

引用

页码：993 / 1003

页数：11

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