Title
BI-LEVEL STYLE AND PROSODY DECOUPLING MODELING FOR PERSONALIZED END-TO-END SPEECH SYNTHESIS
Abstract
End-to-end framework can generate high-quality and high-similarity speech in the personalized speech synthesis task. However, the generalization of out-of-domain texts is still a challenging task. Limited target data leads to unacceptable errors and poor prosody and similarity performance of the synthetic speech. In this paper, we present a bi-level function decoupling framework to realise separate modeling and controlling for solving above problems. Firstly, on the style representation modeling level, compared with the conventional methods that use single embedding to model all the text dependent discrepancies, it is proposed that the speaker embedding and prosody embedding are modeled separately based on the reference audio and phonetic posteriorgram (PPG) by a multi-head attention mechanism. Secondly, on the model structure level, the decoder model structure is factored into average-net and adaptation-net, where the duration prosody controlling and speaker timbre imitation are mainly designed in relatively separate areas. Experimental results on Mandarin dataset show that the proposed methods lead to an improvement on both robustness, naturalness and similarity.
Year
DOI
Venue
2021
10.1109/ICASSP39728.2021.9414422
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
Keywords
DocType
Citations 
Bi-level decoupling, prosody modeling, speaking style modeling, end-to-end, personalized speech synthesis
Conference
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Ruibo Fu115.11
Jianhua Tao2848138.00
Zhengqi Wen38624.41
Jiangyan Yi41917.99
Tao Wang502.70
Chunyu Qiang602.03