14 citations · 44 across the 5 of their papers we have counts for
9 papers
Speech Pre-training with Acoustic Piece
Shuo Ren, Shujie Liu, Yu Wu +2
Previous speech pre-training methods, such as wav2vec2.0 and HuBERT, pre-train a Transformer encoder to learn deep representations from audio data, with objectives predicting eithe…
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…
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…
Template-Based Named Entity Recognition Using BART
Leyang Cui, Yu Wu, Jian Liu +2
There is a recent interest in investigating few-shot NER, where the low-resource target domain has different label sets compared with a resource-rich source domain. Existing method…
Curriculum Pre-training for End-to-End Speech Translation
Chengyi Wang, Yu Wu, Shujie Liu +2
End-to-end speech translation poses a heavy burden on the encoder, because it has to transcribe, understand, and learn cross-lingual semantics simultaneously. To obtain a powerful…
Low Latency End-to-End Streaming Speech Recognition with a Scout Network
Chengyi Wang, Yu Wu, Shujie Liu +4
The attention-based Transformer model has achieved promising results for speech recognition (SR) in the offline mode. However, in the streaming mode, the Transformer model usually…