Speech compression using voice excited linear predictive coding
Ms.Tosha sen, Ms.Kruti Jay Pancholi · Journal of Emerging Technologies and Innovative Research · 2015
The aim of the thesis is design good quality encode and decode transmission for long distance communication. One of the most powerful speech analysis techniques is the method of linear predictive analysis. This method has become the predominant technique for representing speech for low bit rate transmission or storage. The importance of this method lies both in its ability to provide extremely accurate estimates of the speech parameters and in its relative speed of computation. The basic idea behind linear predictive analysis is that the speech sample can be approximated as a linear combination of past samples. The linear predictor model provides a robust, reliable and accurate method for estimating parameters that characterize the linear, time varying system. In this project, we implement a voice excited LPC decoder for low bit rate speech compression. Index Terms: Autocorrelation, Discrete Cosine Transform, Levinson Durbin Recursion, and Linear predictive coding (LPC).