NEURAL NETWORK SYNTHESIZER OF PAUSE DURATION FOR MANDARINE TEXT-TO-SPEECH

Abstract

A neural network based approach of pause-duration synthesis for Mandarin text-to-speech is proposed. It uses an MLP to replace explicit synthesis rules for generating pause duration from input text. By properly training the MLP using a large set of utterances, phonological rules of producing pause duration are automatically learned. Experimental results confirmed that this is a promising approach.