Speech coding using Best Tree Encoding (BTE) technique based on LPC and trigonometric features

Abstract

Over the past several years there has been considerable attention focused on coding and enhancement of speech signals. This interest is progressed towards the development of new techniques capable of producing good quality speech at the output. Speech coding is a process of converting human speech into efficient encoded representations that can be decoded to produce a close approximation of the original signal. This paper deals with the problem of speech coding. It proposes novel approach called Best Tree Encoding (BTE) to encode the wavelet packet Best Tree Structure into a vector of four elements. This research is introducing BTE for solving another problem for speech compression and syntheses. Tree node data coefficients are encoded using LPC Filters and trigonometric features. The encoded vector consists of 4 elements from BTE analysis as well as LPC and trigonometric vector for each leaf node. The quality of the reproduced speech is evaluated for both understanding and quality. The quality of speech signal is measured on the basis of signal to noise ratio, log likelihood ratio, and spectral distortion.