Incorporation of phrase intonation to context clustering for average voice models in HMM-based Thai speech synthesis

This paper describes a novel approach to the context clustering process in a speaker independent HMM-based Thai speech synthesis for improvement of the tone intelligibility of the average voice and also the speaker adapted voice. A couple of phrase intonation features from a generative model including a baseline value of fundamental frequency and a phrase command amplitude are extracted and thereafter exploited in the context clustering process of HMM training stage. In the experiments, subjective evaluations of both average voice and adapted voice in terms of the intelligibility of tone are conducted. The results show that the tone correctness of the synthesized speech is significantly improved.