2021/04/02 by Kang-wook Kim, Seung-won Park, Seungwon Park +6
Computer Science · Engineering · #Music and Audio Processing #Speech Recognition and Synthesis #Speech and Audio Processing #cs.LG #cs.SD #eess.AS
paper · pdf · doi:10.48550/arxiv.2104.00931
arxiv created 2021/10/11 · arxiv updated 2021/10/12
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.