High Quality Voice Conversion through Phoneme-Based Linear Mapping Functions with STRAIGHT for Mandarin

Abstract

A novel voice conversion system using phoneme-based linear mapping functions on main vowel phonemes is proposed in this paper. Our voice conversion algorithm has the following three improvements. First, instead of using all the vocal tract resonance (VTR) vectors in the portion of a phoneme, we use the VTR vector at the steady-state of each phoneme to train phoneme-based GMM. Second, different linear mapping functions have been trained to describe the mapping relationships for corresponding phonemes. Third, in the transformation procedure, the transformed formant frequencies at the main vowel phonemes are obtained using the corresponding GMM. Besides, prosody parameters are also transformed. Finally the converted speech is re-synthesized with the transformed parameters by high quality speech manipulation framework STRAIGHT (Speech Transformation and Representation based on Adaptive Interpolation of weiGHTed spectrogram). Perceptual results for F-M and M-F conversion show that our MOS score of the converted voice is improved from 3.8 to 4.1 and ABX score from 3.3 to 3.8 compared with IBM's system. Comparisons with other systems are also given in this paper.