An Explicit-Form Gain Factor for Speech Enhancement Using Spectral-Domain-Constrained Approach

Abstract

Employing noise masking threshold (NMT) to adapt a speech enhancement system has become popular due to the advantage of rendering the residual noise to perceptually white. Most methods employ the NMT to empirically adjust the parameters of a speech enhancement system according to the various properties of noise. In this article, without any predefined empirical factor, an explicit-form gain factor for a frequency bin is derived by perceptually constraining the residual noise below the NMT in spectral domain. This perceptual constraint preserves the spectrum of noisy speech when the level of residual noise is less than the NMT. If the level of residual noise exceeds the NMT, then the spectrum of noisy speech is suppressed to reduce the corrupting noise. Experimental results show that the proposed approach can efficiently remove the added noise in cases of various noise corruptions, and almost free from musical residual noise.