A Parametric Approach for Voice Conversion

In voice conversion, speech and signal processing techniques are used for the modification of speaker identity, i.e. for modifying the speech of a source speaker to sound as if it was spoken by a target speaker. In this paper, we describe a parametric framework for voice conversion. The parametric representation separates the speech signal into a vocal tract contribution estimated using linear prediction and into an excitation signal modeled using a scheme based on sinusoidal modeling. This parametric framework is in line with the theory of human speech production and it also lends itself into very efficient compression. An initial version of the proposed voice conversion scheme has been implemented and evaluated in listening tests. The results show that the proposed approach offers a promising framework for voice conversion but further development work is still needed to reach its full potential.