Assem-VC: Realistic Voice Conversion by Assembling Modern Speech Synthesis Techniques

Autor:	Kim, Kang-wook, Park, Seung-won, Lee, Junhyeok, Joe, Myun-chul
Rok vydání:	2021
Předmět:	Electrical Engineering and Systems Science - Audio and Speech Processing Computer Science - Machine Learning Computer Science - Sound
Druh dokumentu:	Working Paper
Popis:	Recent works on voice conversion (VC) focus on preserving the rhythm and the intonation as well as the linguistic content. To preserve these features from the source, we decompose current non-parallel VC systems into two encoders and one decoder. We analyze each module with several experiments and reassemble the best components to propose Assem-VC, a new state-of-the-art any-to-many non-parallel VC system. We also examine that PPG and Cotatron features are speaker-dependent, and attempt to remove speaker identity with adversarial training. Code and audio samples are available at https://github.com/mindslab-ai/assem-vc.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2104.00931 Zobrazit plný text záznamu View this record from Arxiv