Performance Analysis of Adaptive Filters for Speech Signal

Adaptive filtering has become a spacious area of researcher since last few decades in the field of communication. Adaptive noise cancellation is an approach used for noise reduction in speech signal. The received speech signal at the receiver easily gets corrupted by background and channel noise where both speech signal and noise signal changes continuously with time, then to separate them adaptive filtering is needed. This paper deals with cancellation of noise on speech signal using two old (LMS and NLMS) and one new (UNANR) algorithm. The UNANR (Unbiased and Normalized Adaptive Noise Rejection) model does not contain a bias unit, and the coefficients are adaptively updated by using the steepest-descent algorithm. Two modulation techniques, AM and FM are applied separately in combination with two communication channels i.e. AWGN and Rician. Signal quality parameter PSNR with respect to SNR measured and compared. The results show that the performance of the UNANR based algorithm is superior to that of the LMS algorithm in noise reduction.