216 citations · 540 across the 33 of their papers we have counts for
7 papers · 1 filter
DurIAN: Duration Informed Attention Network For Multimodal Synthesis
Chengzhu Yu, Heng Lu, Na Hu +9
In this paper, we present a generic and robust multimodal synthesis system that produces highly natural speech and facial expression simultaneously. The key component of this syste…
Phrase-Level Class based Language Model for Mandarin Smart Speaker Query Recognition
Yiheng Huang, Liqiang He, Lei Han +2
The success of speech assistants requires precise recognition of a number of entities on particular contexts. A common solution is to train a class-based n-gram language model and…
A Random Gossip BMUF Process for Neural Language Modeling
Yiheng Huang, Jinchuan Tian, Lei Han +4
Neural network language model (NNLM) is an essential component of industrial ASR systems. One important challenge of training an NNLM is to leverage between scaling the learning pr…
Maximizing Mutual Information for Tacotron
Peng Liu, Xixin Wu, Shiyin Kang +3
End-to-end speech synthesis methods already achieve close-to-human quality performance. However compared to HMM-based and NN-based frame-to-frame regression methods, they are prone…
Teach an all-rounder with experts in different domains
Zhao You, Dan Su, Dong Yu
In many automatic speech recognition (ASR) tasks, an ideal model has to be applicable over multiple domains. In this paper, we propose to teach an all-rounder with experts in diffe…
End-to-End Multi-Channel Speech Separation
Rongzhi Gu, Jian Wu, Shi-Xiong Zhang +6
The end-to-end approach for single-channel speech separation has been studied recently and shown promising results. This paper extended the previous approach and proposed a new end…