activity
20162023
most citedSelf-Attention Transducers for End-to-End Speech Recognition

85 citations · 357 across the 31 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2021

Fast End-to-End Speech Recognition via Non-Autoregressive Models and Cross-Modal Knowledge Transferring from BERT

Ye Bai, Jiangyan Yi, Jianhua Tao +3

Attention-based encoder-decoder (AED) models have achieved promising performance in speech recognition. However, because the decoder predicts text tokens (such as characters or wor…

cs.CL2020

Adversarial Transfer Learning for Punctuation Restoration

Jiangyan Yi, Jianhua Tao, Ye Bai +2

Previous studies demonstrate that word embeddings and part-of-speech (POS) tags are helpful for punctuation restoration tasks. However, two drawbacks still exist. One is that word…

cs.CL20203 cited

Rnn-transducer with language bias for end-to-end Mandarin-English code-switching speech recognition

Shuai Zhang, Jiangyan Yi, Zhengkun Tian +2

Recently, language identity information has been utilized to improve the performance of end-to-end code-switching (CS) speech recognition. However, previous works use an additional…

cs.CL201933 cited

Conversational Emotion Analysis via Attention Mechanisms

Zheng Lian, Jianhua Tao, Bin Liu +1

Different from the emotion recognition in individual utterances, we propose a multimodal learning framework using relation and dependencies among the utterances for conversational…

cs.CL201918 cited

Reinforcement Learning Based Emotional Editing Constraint Conversation Generation

Jia Li, Xiao Sun, Xing Wei +2

In recent years, the generation of conversation content based on deep neural networks has attracted many researchers. However, traditional neural language models tend to generate g…

cs.CL2018

Distilling Knowledge Using Parallel Data for Far-field Speech Recognition

Jiangyan Yi, Jianhua Tao, Zhengqi Wen +1

In order to improve the performance for far-field speech recognition, this paper proposes to distill knowledge from the close-talking model to the far-field model using parallel da…