Interpretable Style Transfer for Text-to-Speech with ControlVAE and Diffusion Bridge

Understand

With the demand for autonomous control and personalized speech generation, the style control and transfer in Text-to-Speech (TTS) is becoming more and more important.

• In this paper, we propose a new TTS system that can perform style transfer with interpretability and high fidelity.
• Firstly, we design a TTS system that combines variational autoencoder (VAE) and diffusion refiner to get refined mel-spectrograms.
• Specifically, a two-stage and a one-stage system are designed respectively, to improve the audio quality and the performance of style transfer.