Title
ByteSing: A Chinese Singing Voice Synthesis System Using Duration Allocated Encoder-Decoder Acoustic Models and WaveRNN Vocoders
Abstract
This paper presents ByteSing, a Chinese singing voice synthesis (SVS) system based on duration allocated Tacotron-like acoustic models and WaveRNN neural vocoders. Different from the conventional SVS models, the proposed ByteSing employs Tacotron-like encoder-decoder structures as the acoustic models, in which the CBHG models and recurrent neural networks (RNNs) are explored as encoders and decoders respectively. Meanwhile an auxiliary phoneme duration prediction model is utilized to expand the input sequence, which can enhance the model controllable capacity, model stability and tempo prediction accuracy. WaveRNN vocoders are also adopted as neural vocoders to further improve the voice quality of synthesized songs. Both objective and subjective experimental results prove that the SVS method proposed in this paper can produce quite natural, expressive and high-fidelity songs by improving the pitch and spectrogram prediction accuracy and the models using attention mechanism can achieve best performance.
Year
DOI
Venue
2021
10.1109/ISCSLP49672.2021.9362104
2021 12th International Symposium on Chinese Spoken Language Processing (ISCSLP)
Keywords
DocType
ISBN
ByteSing,Singing voice synthesis,Tacotron,WaveRNN,Duration allocated
Conference
978-1-7281-6995-8
Citations 
PageRank 
References 
0
0.34
0
Authors
9
Name
Order
Citations
PageRank
Gu Yu100.34
Yin Xiang201.01
Rao Yonghui300.34
Wan Yuan400.34
Tang Benlai500.34
Zhang Yang600.34
Jitong Chen719910.01
Yu-Xuan Wang865032.68
Ma Zejun900.34