Usually this involves database of involved speakers speech signals. During the training phase, the voice conversion system learns a function to transform the source speakers acoustic data to target speakers acoustic data. A voice conversion system involves two phases, training phase and conversion phase. Till now, voice conversion systems have mainly focused on spectral characteristics and some others operate on prosodic level too.

Voice Conversion is the process of modifying the characteristics of source speaker in such a way that it is perceived as the voice of target speaker. KeywordsVoice Conversion, Gaussian Mixture Model, bilinear function, frequency warping, fuzzy amplitude scaling. This method despite its simplicity, achieves similar performance scores to the previously available methods based on Gaussian Mixture Model. Fuzzy logic is applied to the amplitude scaling process in order to improve the perceptional quality. The use of bilinear function is to warp the signal without any significant decrease in the quality scores. Amplitude scaling is done to compensate for the warping inaccuracy. Frequency warping is done so that spectrum of source speaker is moved towards their image in the target speakers spectrum.

The method basically involves two steps: Bilinear Frequency Warping and Amplitude Scaling. Cepstral Domain Voice Conversion Based on Constrained TransformationsДЄbstractThis paper proposes a method for voice conversion in cepstral domain.

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