1.9k citations · 2.2k across the 28 of their papers we have counts for
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Self-Supervised Learning for speech recognition with Intermediate layer supervision
Chengyi Wang, Yu Wu, Sanyuan Chen +4
Recently, pioneer work finds that speech pre-trained models can solve full-stack speech processing tasks, because the model utilizes bottom layers to learn speaker-related informat…
UniSpeech-SAT: Universal Speech Representation Learning with Speaker Aware Pre-Training
Sanyuan Chen, Yu Wu, Chengyi Wang +8
Self-supervised learning (SSL) is a long-standing goal for speech processing, since it utilizes large-scale unlabeled data and avoids extensive human labeling. Recent years witness…
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
Sanyuan Chen, Chengyi Wang, Zhengyang Chen +15
Self-supervised learning (SSL) achieves great success in speech recognition, while limited exploration has been attempted for other speech processing tasks. As speech signal contai…
Large-scale Self-Supervised Speech Representation Learning for Automatic Speaker Verification
Zhengyang Chen, Sanyuan Chen, Yu Wu +5
The speech representations learned from large-scale unlabeled data have shown better generalizability than those from supervised learning and thus attract a lot of interest to be a…
Investigation of Practical Aspects of Single Channel Speech Separation for ASR
Jian Wu, Zhuo Chen, Sanyuan Chen +5
Speech separation has been successfully applied as a frontend processing module of conversation transcription systems thanks to its ability to handle overlapped speech and its flex…