On using warping function for LSFs transformation in a voice conversion system

In this paper, a new approach to line spectral frequencies transformation is introduced and employed in the voice conversion framework. This approach stems from the fact that LSFs are some specific points on the frequency axis and their positions determined the shape of the spectral envelope. Thus, they could be transformed directly by frequency axis warping. Two warping functioned were designed specially for LSFs and compared with the traditional GMM-based conversion function. Listening tests and mathematical evaluation revealed that speech transformed by using proposed warping functions is of higher quality and does not suffer from oversmoothing which is common for GMM-based transformation. On the other hand, the speaker identity is slightly better transformed by GMM-based conversion. However, it is possible to combine these two approaches to obtain a compromise between quality and speaker identity.