Subband noise estimation for speech enhancement using a perceptual Wiener filter

The paper proposes a fast noise estimation algorithm for speech enhancement using a perceptual Wiener filter. The noisy speech is decomposed using a critical-band-rate filterbank so that a perceptual modification of Wiener filtering can be applied in speech denoising. The subband noise estimate is updated by adaptively smoothing the noisy signal power. The smoothing parameter is chosen as a function of the estimated signal-to-noise ratio. This noise estimation technique gives accurate results even at very low signal-to-noise ratios, and works continuously, even in the presence of speech. It is effective for both non-stationary and coloured noise. Enhanced speech of good quality is obtained by the perceptual Wiener filter.