Efficient spectral matching of the LPC residual signal

A basic reason for the loss of quality in LPC synthesized speech is the spectral mismatch between the LPC model and the analyzed speech. Since the residual signal contains the spectral information not extracted by the LPC analyzer, existing methods for improving the synthesized speech quality are based on encoding the residual signal or reducing its information content by improved pole-zero models. In this work we study an approach in which the spectral envelope of the residual signal is divided into three main components which are separately represented to provide an overall more efficient representation of the residual signal. The three spectral components are the antiresonances due to nasalized sounds, fixed or slowly varying spectral contributions due to input spectral shaping, and the remaining spectral matching error. An analysis-synthesis system based on the cepstral representation of the residual signal is developed and is shown to provide a particularly convenient framework for separating and representing by zeroes and cepstral residuals the different spectral components. Preliminary results of the study are presented on the basis of simulations with telephone bandwidth speech.