A Smoothed and Thresholded Linear Prediction Analysis for Efficient Speech Coding

Abstract

In this paper, we propose a new method of linear prediction (LP) analysis for estimating LP coefficients that are used in current speech coders. This method improves the robustness of LP coefficients computed from speech signals corrupted by noise as well as offering better quantisation efficiency. The quantisation performance and the noise-robustness obtained by the proposed LP coefficients were compared to that obtained by the LP coefficients computed using the autocorrelation and LP spectrum modification methods of LP Analysis, in terms of spectral distortion (SD). The results indicate that the proposed LP coefficients were more robust to noise and also offered transparent quantisation at lower bit-rates (savings of up to 2 bits/frame) than other LP coefficients.