A noise reduction system based on hybrid noise estimation technique and post-filtering in arbitrary noise environments

In this paper, we propose a novel noise reduction system, using a hybrid noise estimation technique and post-filtering, to suppress both localized noises and non-localized noise simultaneously in arbitrary noise environments. To estimate localized noises, we present a hybrid noise estimation technique which combines a multi-channel estimation approach we previously proposed and a soft-decision single-channel estimation approach. Final estimation accuracy for localized noises is significantly improved by incorporating a robust and accurate speech absence probability (RA-SAP) estimator, which considers the strong correlation of SAPs between adjacent frequency bins and consecutive frames and makes full use of the high estimation accuracy of the multi-channel approach. The estimated spectra of localized noises are reduced from those of noisy observations by spectral subtraction. Non-localized noise is further reduced by a multi-channel post-filter which is based on the optimally modified log-spectral amplitude (OM-LSA) estimator. With the assumption of a diffuse noise field, we propose an estimator for the a priori SAP based on the coherence characteristic of the noise field at spectral subtraction output, high coherence at low frequencies and low coherence at high frequencies, improving the spectral enhancement of the desired speech signal. Experimental results demonstrates the effectiveness and superiorities of the proposed noise estimation/reduction methods in terms of objective and subjective measures in various noise conditions.