PERFORMANCE ANALYSIS OF SPEECH ENHANCEMENT USING DIFFERENT ADAPTIVE FILTERS WITH DIFFERENT MODULATION TECHNIQUES

Abstract

Adaptive filtering has become a vast area of researchers since last few decades in the field of electronics and communication. Adaptive noise cancellation is a method used for noise reduction in the speech signal. In this paper, deals with cancellation of noise on the speech signal using two old algorithms i.e. Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS) and one new Unbiased and Normalized Adaptation Noise Reduction (UNANR) algorithm. The UNANR algorithm model does not contain any bias unit, and the coefficients are adaptively updated by using the steepest-descent algorithm. The Amplitude Modulation (AM) and Frequency Modulation (FM) are used separately in combination with Additive White Gaussian Noise (AWGN) channel. The channel signal quality parameter Peak Signal to Noise Ratio (PSNR) and Root Mean-Square Error (RMSE) are measured and compared. The simulations result of LMS, NLMS and UNANR are compared and shows that the performance of the UNANR based algorithm is superior to that of the LMS algorithm in noise reduction.