96 citations · 282 across the 13 of their papers we have counts for
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eess.AS2021★ 2 cited
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…
eess.AS2021★ 30 cited
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
Junyi Ao, Rui Wang, Long Zhou +11
Motivated by the success of T5 (Text-To-Text Transfer Transformer) in pre-trained natural language processing models, we propose a unified-modal SpeechT5 framework that explores th…
eess.AS2021★ 9 cited
UniSpeech at scale: An Empirical Study of Pre-training Method on Large-Scale Speech Recognition Dataset
Chengyi Wang, Yu Wu, Shujie Liu +4
Recently, there has been a vast interest in self-supervised learning (SSL) where the model is pre-trained on large scale unlabeled data and then fine-tuned on a small labeled datas…