Evaluation of source separation using projection pursuit algorithm for computer-based auditory training system

Abstract

Difficulty of understanding speech in noise among the elderly community necessitates the need for Auditory Training which has made a renewal of interest in the last decade with the auditory training applications. This interest is perhaps spurred by advances in computer-based technology. In computer-based training, speech signals are considered as training stimuli where input speech signals need to be verified prior to training as the speech signals are mixed with noise signals in real-life acoustic environment. Computer-based Auditory Training System can be embedded with input speech verifying module. Input speech verifying module is employed with speech and noise separator simulator. This simulator needs to guarantee accurate separation of speech from noise signals. Therefore, in this research, Projection Pursuit (PP) algorithm under Blind Source Separation (BSS) method is intended to separate the speech source signals which are mixed with speech babble. This article uses Malay language based sentences which differ in word length and hence number of sample values. The experimental simulation considers two-channel random and linear mixing of speech sources and speech babble as noise signal. The aim of this study is to evaluate the performance of the anticipated PP algorithm for various sample values of speech signals which varies in time duration due to word length dissimilarity. Simulation results show that PP algorithm is feasible for source separation. As a consequence, high correlation value of r ≥ 0.99 is obtained between extracted speech signal and original speech signal for all categories of speech signals. It is further verified by the maximum nongaussianity of extracted speech signal which has high kurtosis value of 32.