1.9k citations · 3.5k across the 108 of their papers we have counts for
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Semantic Mask for Transformer based End-to-End Speech Recognition
Chengyi Wang, Yu Wu, Yujiao Du +7
Attention-based encoder-decoder model has achieved impressive results for both automatic speech recognition (ASR) and text-to-speech (TTS) tasks. This approach takes advantage of t…
Speaker Adaptation for Attention-Based End-to-End Speech Recognition
Zhong Meng, Yashesh Gaur, Jinyu Li +1
We propose three regularization-based speaker adaptation approaches to adapt the attention-based encoder-decoder (AED) model with very limited adaptation data from target speakers…
Improving RNN Transducer Modeling for End-to-End Speech Recognition
Jinyu Li, Rui Zhao, Hu Hu +1
In the last few years, an emerging trend in automatic speech recognition research is the study of end-to-end (E2E) systems. Connectionist Temporal Classification (CTC), Attention E…
Adversarial Speaker Adaptation
Zhong Meng, Jinyu Li, Yifan Gong
We propose a novel adversarial speaker adaptation (ASA) scheme, in which adversarial learning is applied to regularize the distribution of deep hidden features in a speaker-depende…
Adversarial Speaker Verification
Zhong Meng, Yong Zhao, Jinyu Li +1
The use of deep networks to extract embeddings for speaker recognition has proven successfully. However, such embeddings are susceptible to performance degradation due to the misma…
Attentive Adversarial Learning for Domain-Invariant Training
Zhong Meng, Jinyu Li, Yifan Gong
Adversarial domain-invariant training (ADIT) proves to be effective in suppressing the effects of domain variability in acoustic modeling and has led to improved performance in aut…