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Modifying LPC Parameter Dynamics to Improve Speech Coder Eciency

Reducing the transmission bandwidth and achieving higher speech quality are primary concerns in developing new speech coding algorithms. The goal of this thesis is to improve the perceptual speech quality of algorithms that employ linear predictive coding (LPC). Most LPC-based speech coders extract parameters representing an all-pole filter. This LPC analysis is performed on each block or frame of speech. To smooth out the evolution of the LPC tracks, each block is divided into subframes for which the LPC parameters are interpolated. This improves the perceptual quality without additional transmission bit rate. A method of modifying the interpolation endpoints to improve the spectral match over all the subframes is introduced. The spectral distortion and weighted Euclidean LSF (Line Spectral Frequencies) distance are used as objective measures of the performance of this warping method. The algorithm has been integrated in a floating point C-version of the Adaptive Multi Rate (AMR) speech coder and these results are presented.