Enhancement of Speech Communication Technology Performance Using Adaptive-Control Factor Based Spectral Subtraction Method

Abstract

This paper presents speech enhancement technique based on Spectral Subtraction (SS) method. SS is a renowned noise reduction technique that works on the principle that noise spectrum estimate over the entire speech spectrum can be subtracted from the noisy signal. On the contrary, most of the noise encountered in the real-world conditions is majorly colored. Unlike Additive White Gaussian Noise (AWGN), colored noise does not affect the speech signal uniformly over the entire spectrum. To mitigate effects of colored noise on the processed signal, we propose a Multi-Band Spectral Subtraction (MBSS) method using novel Adaptive-Control Factor (ACF). The spectrum is divided into frequency sub bands based on a nonlinear multi-band frame and various signal-to-noise ratios (SNRs) are considered. The proposed scheme results in better system performance with quality signal and unlike the basic SS method. It mitigates the effects of anomaly known as “musical” tones artifacts in the processed signal that result in residual noise and speech distortion. The computational complexity involved is minimal. Furthermore, simulation results show that the proposed algorithm removes more colored noise without removing the relatively low amplitude speech signal over the entire speech spectrum. Subjective listening tests, with clean speech signals and different noise levels, show discernable performance of our proposed method when compared with the conventional SS approach.