Improving voice quality of HMM-based speech synthesis using voice conversion method
Yishan Jiao, Xiang Xie, Xingyu Na, Ming Tu · 2014
HMM-based speech synthesis system (HTS) often generates buzzy and muffled speech. Such degradation of voice quality makes synthetic speech sound robotically rather than naturally. From this point, we suppose that synthetic speech is in a different speaker space apart from the original. We propose to use voice conversion method to transform synthetic speech toward the original so as to improve its quality. Local linear transformation (LLT) combined with temporal decomposition (TD) is proposed as the conversion method. It can not only ensure smooth spectral conversion but also avoid over-smoothing problem. Moreover, we design a robust spectral selection and modification strategy to make the modified spectra stable. Preference test shows that the proposed method can improve the quality of HMM-based speech synthesis.