Robust LPC analysis of speech by extended correlation matching

Contamination of speech, for example by environmental noise, is sometimes unavoidable. Under such circumstances the familiar LPC analysis technique, either for low bit-rate coding or for automated recognition at the receiver, becomes fragile thus jeopardizing the system objective. In this paper we present an extended correlation matching approach for LPC analysis which results in good spectral matching between the true speech spectrum and the all-pole model spectrum, especially for the first three formants. The method has been tested on both synthetic as well as real speech and has been found to yield satisfactory results. Informal listening tests confirm the success of the technique developed.