ConVoice: Real-Time Zero-Shot Voice Style Transfer with Convolutional Network

Understand

We propose a neural network for zero-shot voice conversion (VC) without any parallel or transcribed data.

• Our approach uses pre-trained models for automatic speech recognition (ASR) and speaker embedding, obtained from a speaker verification task.
• Our model is fully convolutional and non-autoregressive except for a small pre-trained recurrent neural network for speaker encoding.
• ConVoice can convert speech of any length without compromising quality due to its convolutional architecture.