Recognition-Synthesis Based Non-Parallel Voice Conversion with Adversarial Learning

Understand

This paper presents an adversarial learning method for recognition-synthesis based non-parallel voice conversion.

• A recognizer is used to transform acoustic features into linguistic representations while a synthesizer recovers output features from the recognizer outputs together with the speaker identity.
• By separating the speaker characteristics from the linguistic representations, voice conversion can be achieved by replacing the speaker identity with the target one.
• In our proposed method, a speaker adversarial loss is adopted in order to obtain speaker-independent linguistic representations using the recognizer.