Paper Oral
in
Workshop: Machine Learning for Creativity and Design

Controllable and Interpretable Singing Voice Decomposition via Assem-VC

Kangwook Kim · Junhyeok Lee

2021 Paper Oral
in
Workshop: Machine Learning for Creativity and Design

Abstract

We propose a singing decomposition system that encodes time-aligned linguistic content, pitch, and source speaker identity via Assem-VC. With decomposed speaker-independent information and the target speaker's embedding, we could synthesize the singing voice of the target speaker. In conclusion, we made a perfectly synced duet with the user's singing voice and the target singer's converted singing voice.

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