Pitch-based speech conversion model training method and speech conversion system

Abstract

The present disclosure provides a pitch-based speech conversion model training method and a speech conversion system, wherein an audio feature code is output by a priori encoder, and a pitch feature is extracted by a pitch extraction module. A linear spectrum corresponding to the reference speech is input into the posteriori encoder to obtain an audio latent variable. In addition, the audio feature code, a speech concatenation feature obtained by concatenation of the audio feature code and the pitch feature, and the audio latent variable are input into a temporal alignment module to obtain a converted speech code, and the converted speech code is decoded by a decoder to obtain a converted speech. The training loss of the converted speech is then calculated to determine the degree of convergence of the speech conversion model.