Modeling Fluctuations of Voiced Excitation for Speech Generation Based on Recursive Volterra Systems

Abstract

For the modeling of the speech production system linear models are widely used. However, not all features of speech can be covered by linear systems. Therefore nonlinear systems are interesting in speech processing. In this contribution a time variable recursive Volterra system is used to model the fluctuations of the voiced excitation while a linear system models the resonances of the speech production system. The estimation of the Volterra system is performed by a prediction algorithm. The prediction problem is solved with the aid of an approximation by series expansion. Speech examples show that the use of a time variable Volterra system improves the naturalness of the synthetic speech.