Among the numerous noise reduction techniques that were developed over the past several decades, the Wiener filter can be considered as one of the most fundamental noise reduction approaches, which has been delineated in different forms and adopted in various applications. An important parameter of numerous speech enhancement algorithms is the a priori signal-to-noise ratio (SNR). The Wiener filter emphasizes portions of the noisy signal spectrum where SNR is high and attenuates portions of the spectrum where the SNR is low. An adaptive time varying filter can be used for whitening the noisy speech signal corrupted by narrow-band noise whereas by enhancing the signal using Perceptual frequency weighting filter (PFWF), formant regions of the noisy speech spectrum can be made less affected for a given SNR. Incorporation of PFWF and/or NSSF (Noise spectrum shaping filter) into the Weiner denoising technique improves the performance of the speech enhancement system.