Robust signal selection for lineair prediction analysis of voiced speech

This paper investigates a weighted LPC analysis of voiced speech. In view of the speech production model, the weighting function is either chosen to be the short-time energy function of the preemphasized speech sample sequence with certain delays or is obtained by thresholding the short-time energy function. In this method, speech samples are selectively weighted based on how well they match the speech production model. Therefore, the estimates of the LPC coefficients obtained by this novel LPC analysis are more accurate than those obtained from the conventional LPC analysis. They are also less sensitive to the values of the fundamental frequency than conventional LPC.