216 citations · 500 across the 47 of their papers we have counts for
7 papers · 1 filter
Synthesising Expressiveness in Peking Opera via Duration Informed Attention Network
Yusong Wu, Shengchen Li, Chengzhu Yu +4
This paper presents a method that generates expressive singing voice of Peking opera. The synthesis of expressive opera singing usually requires pitch contours to be extracted as t…
Learning Singing From Speech
Liqiang Zhang, Chengzhu Yu, Heng Lu +5
We propose an algorithm that is capable of synthesizing high quality target speaker's singing voice given only their normal speech samples. The proposed algorithm first integrate s…
PitchNet: Unsupervised Singing Voice Conversion with Pitch Adversarial Network
Chengqi Deng, Chengzhu Yu, Heng Lu +2
Singing voice conversion is to convert a singer's voice to another one's voice without changing singing content. Recent work shows that unsupervised singing voice conversion can be…
Minimum Bayes Risk Training of RNN-Transducer for End-to-End Speech Recognition
Chao Weng, Chengzhu Yu, Jia Cui +2
In this work, we propose minimum Bayes risk (MBR) training of RNN-Transducer (RNN-T) for end-to-end speech recognition. Specifically, initialized with a RNN-T trained model, MBR tr…
Overlapped speech recognition from a jointly learned multi-channel neural speech extraction and representation
Bo Wu, Meng Yu, Lianwu Chen +3
We propose an end-to-end joint optimization framework of a multi-channel neural speech extraction and deep acoustic model without mel-filterbank (FBANK) extraction for overlapped s…
DFSMN-SAN with Persistent Memory Model for Automatic Speech Recognition
Zhao You, Dan Su, Jie Chen +2
Self-attention networks (SAN) have been introduced into automatic speech recognition (ASR) and achieved state-of-the-art performance owing to its superior ability in capturing long…
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…