Jingbei Li

Adversarially Learning Disentangled Speech Representations for Robust Multi-Factor Voice Conversion

2021

Factorizing speech as disentangled speech representations is vital to achieve highly controllable style transfer in voice conversion (VC).Conventional speech representation learning methods in VC only factorize speech as speaker and content, lacking controllability on other …

Enhancing Speaking Styles in Conversational Text-to-Speech Synthesis with Graph-based Multi-modal Context Modeling

2021 · arXiv (Cornell University)

Comparing with traditional text-to-speech (TTS) systems, conversational TTS systems are required to synthesize speeches with proper speaking style confirming to the conversational context. However, state-of-the-art context modeling methods in conversational TTS only model the textual …