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eess.AS2021★ 3 cited
Improving Pseudo-label Training For End-to-end Speech Recognition Using Gradient Mask
Shaoshi Ling, Chen Shen, Meng Cai +1
In the recent trend of semi-supervised speech recognition, both self-supervised representation learning and pseudo-labeling have shown promising results. In this paper, we propose…
eess.AS2020★ 5 cited
Improving RNN transducer with normalized jointer network
Mingkun Huang, Jun Zhang, Meng Cai +5
Recurrent neural transducer (RNN-T) is a promising end-to-end (E2E) model in automatic speech recognition (ASR). It has shown superior performance compared to traditional hybrid AS…
eess.AS2020★ 2 cited
Dynamic latency speech recognition with asynchronous revision
Mingkun Huang, Meng Cai, Jun Zhang +4
In this work we propose an inference technique, asynchronous revision, to unify streaming and non-streaming speech recognition models. Specifically, we achieve dynamic latency with…