Abstract:Voice conversion algorithm aims to provide high level of similarity to the target voice with an acceptable level of quality. The main object of this paper was to build a nonlinear relationship between the parameters for the acoustical features of source and target speaker using non-linear canonical correlation analysis (NLCCA) based on jointed Gaussian mixture model. Speaker individuality transformation was achieved mainly by altering vocal tract characteristics represented by line spectral frequencies (LSF). … Show more
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