An approach to voice conversion using feature statistical mapping

The voice conversion (VC) technique recently has emerged as a new branch of speech synthesis dealing with speaker identity. In this work, a linear prediction (LP) analysis is carried out on speech signals to obtain acoustical parameters related to speaker identity – the speech fundamental frequency, or pitch, voicing decision, signal energy, and vocal tract parameters. Once these parameters are established for two different speakers designated as source and target speakers, statistical mapping functions can then be applied to modify the established parameters. The mapping functions are derived from these parameters in such a way that the source parameters resemble those of the target. Finally, the modified parameters are used to produce the new speech signal. To illustrate the feasibility of the proposed approach, a simple to use voice conversion software has been developed. This VC technique has shown satisfactory results. The synthesized speech signal virtually matching that of the target speaker.