Voive conversion based on a statistical model

In this paper, we propose to use a voice conversion method based on transformation of the characteristic features of a source speaker towards a target. The main objective of the work involves building a nonlinear relationship between parameters for the acoustical features of two speakers, based on a probabilistic model. The conversion rules involve the probabilistic classification and a cross correlation probability between the acoustic features of the two speakers. The parameters of the conversion rules are estimated by estimating the maximum likelihood of the training data. A comparative study of voice conversion with the proposed method and conventional vector quantization (VQ) is conducted. The experimental results of voice conversion evaluated using subjective and objective measures indicated that the performance can be dramatically improved by the proposed method.