85 citations · 410 across the 77 of their papers we have counts for
5 papers · 1 filter
Synchronous Transformers for End-to-End Speech Recognition
Zhengkun Tian, Jiangyan Yi, Ye Bai +3
For most of the attention-based sequence-to-sequence models, the decoder predicts the output sequence conditioned on the entire input sequence processed by the encoder. The asynchr…
Integrating Knowledge into End-to-End Speech Recognition from External Text-Only Data
Ye Bai, Jiangyan Yi, Jianhua Tao +3
Attention-based encoder-decoder (AED) models have achieved promising performance in speech recognition. However, because of the end-to-end training, an AED model is usually trained…
Self-Attention Transducers for End-to-End Speech Recognition
Zhengkun Tian, Jiangyan Yi, Jianhua Tao +2
Recurrent neural network transducers (RNN-T) have been successfully applied in end-to-end speech recognition. However, the recurrent structure makes it difficult for parallelizatio…
Discriminative Learning for Monaural Speech Separation Using Deep Embedding Features
Cunhang Fan, Bin Liu, Jianhua Tao +2
Deep clustering (DC) and utterance-level permutation invariant training (uPIT) have been demonstrated promising for speaker-independent speech separation. DC is usually formulated…
Learn Spelling from Teachers: Transferring Knowledge from Language Models to Sequence-to-Sequence Speech Recognition
Ye Bai, Jiangyan Yi, Jianhua Tao +2
Integrating an external language model into a sequence-to-sequence speech recognition system is non-trivial. Previous works utilize linear interpolation or a fusion network to inte…