Recovery of LSP Coefficient in VoIP Systems using Evolving Takagi-Sugeno Fuzzy Models

Abstract

In order to deliver real time, high quality voice services in packet based voice system (e.g. voice over Internet protocol, VoIP) system designers must tackle inherent quality problems related to possible packet loss. To combat the inevitable speech quality deterioration resulting from the loss of transmitted packets of speech information, techniques that provide estimates of the lost information that is needed by the speech recovery process are of considerable interest. Furthermore, in VoIP systems employing linear predictive coding (LPC) based speech coders, a significant percentage of the coded speech information represent the values of LPC coefficients and thus a new approach for estimating missing LPC filter coefficients is presented in this paper. This approach employs a new formulation of LSP recovery system architecture where evolving fuzzy rule-based models and particularly so-called evolving Takagi-Sugeno models are deployed to generate the required estimates of missing LSPs. The proposed missing parameters estimation technique is generic and initial experimental results demonstrate its considerable potential in improving the quality of LPC based decoded speech in VoIP applications