A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion

Understand

The goal of voice conversion is to transform source speech into a target voice, keeping the content unchanged.

• In this paper, we focus on self-supervised representation learning for voice conversion.
• Specifically, we compare discrete and soft speech units as input features.
• We find that discrete representations effectively remove speaker information but discard some linguistic content - leading to mispronunciations.