An improved voice conversion method using segmental GMMs and automatic GMM selection

In this paper, the idea of segmental GMMs is proposed for voice conversion. Also, to apply this idea to on-line voice conversion, we have developed an automatic GMM selection algorithm based on dynamic programming. In addition, to map a vector of DCC (discrete cepstrum coefficients) with only one Gaussian mixture, we have designed a mixture selection algorithm. For evaluating the performance of the idea, segmental GMMs, three voice conversion system are constructed and used to conduct listening tests. The results of the listening tests show that segmental GMMs proposed here can indeed help to improve the performances in both timbre similarity and voice quality.