ControlVC: Zero-Shot Voice Conversion with Time-Varying Controls on Pitch and Speed

Abstract

Recent developments in neural speech synthesis and vocoding have sparked a renewed interest in voice conversion (VC). Beyond timbre transfer, achieving controllability on para-linguistic parameters such as pitch and Speed is critical in deploying VC systems in many application scenarios. Existing studies, however, either only provide utterance-level global control or lack interpretability on the controls. In this paper, we propose ControlVC, the first neural voice conversion system that achieves time-varying controls on pitch and speed. ControlVC uses pre-trained encoders to compute pitch and linguistic embeddings from the source utterance and speaker embeddings from the target utterance. These embeddings are then concatenated and converted to speech using a vocoder. It achieves speed control through TD-PSOLA pre-processing on the source utterance, and achieves pitch control by manipulating the pitch contour before feeding it to the pitch encoder. Systematic subjective and objective evaluations are conducted to assess the speech quality and controllability. Results show that, on non-parallel and zero-shot conversion tasks, ControlVC significantly outperforms two other self-constructed baselines on speech quality, and it can successfully achieve time-varying pitch and speed control.

Audio samples: https://bit.ly/3PsrKLJ; Code: https://github.com/MelissaChen15/control-vc

References in corpus (5)

• VoxCeleb: a large-scale speaker identification dataset
• HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
• AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
• F0-consistent many-to-many non-parallel voice conversion via conditional autoencoder
• Fine-grained style control in Transformer-based Text-to-speech Synthesis