Submission from SRCB for Voice Conversion Challenge 2020
Qiuyue Ma, Ruolan Liu, Wen Xue, Chunhui Lu, Xiao Chen · 2020
This paper presents the intra-lingual and cross-lingual voice conversion system for Voice Conversion Challenge 2020(VCC 2020).Voice conversion (VC) modifies a source speaker's speech so that the result sounds like a target speaker.This becomes particularly difficult when source and target speakers speak different languages.In this work we focus on building a voice conversion system achieving consistent improvements in accent and intelligibility evaluations.Our voice conversion system is constituted by a bilingual phoneme recognition based speech representation module, a neural network based speech generation module and a neural vocoder.More concretely, we extract general phonation from the source speakers' speeches of different languages, and improve the sound quality by optimizing the speech synthesis module and adding a noise suppression post-process module to the vocoder.This framework ensures high intelligible and high natural speech, which is very close to human quality (MOS=4.17rank 2 in Task 1, MOS=4.13 rank 2 in Task 2).