Multistage Speaker Feature Tracking Identification System Based on Continuous and Discrete Wavelet Transform

Abstract — Wavelet transform multi-stage identification system is presented. This paper intends to introduce high accuracy of identification the speech signal of very difficult nature that is non- stationary. Three methods are used to extract the essential speaker features based on Continuous, Discrete Wavelet Transform and Statistical Quality Evaluation Method. To have better identification rate three measurement methods are used. 95 % identification rate is accomplished. The presented system in this paper depends on multi-stage features extracting due to its better accuracy. The system works with excellent capability of features tracking. This is accomplished because of multistage features tracking based system using Wavelet Transform, which is suitable for non-stationary signal Key-words — Speaker identification; Continuous and discrete wavelet transform