Speaker Transformation Using Length-Variable Moving Window Based GMM

Speaker transformation is that the speech of A is transformed to one of the B but the content of speech is not changeable. The pitch period is changeable during the pronunciation. The matching of feature parameters of two kinds of speech of speaker transformation applies moving window to extract the parameters of speech. Owing to the difference of period of speech signal, the matching error occurs. The proposed length-variable moving window algorithm is to select the different length moving window for speech segmentation, which caused each window to contain the same period of speech signal. Thus parameters difference caused by the difference of speech signal is eliminated. The experiments demonstrate the proposed algorithm enhance the performance of speech transformation.