Speech Signal Processing

Title Estimation of the Noise Correlation Matrix
Authors Richard C. Hendriks, Timo Gerkmann
Conference Int. Conf. Acoustics, Speech, Signal Processing (ICASSP)
Organization IEEE
Date May 2011
Prague, Czech Republic


To harvest the potential of multi-channel noise reduction methods, it is crucial to have an accurate estimate of the noise correlation matrix. Existing algorithms either assume speech absence and exploit a voice activity detector (VAD), or make use of additional assumptions like a diffuse noise field. Therefore, these algorithms are limited with respect to their tracking speed and the type of noise fields for which they can estimate the correlation matrix.

In this paper we present a new method for noise correlation matrix estimation that makes no assumptions about the type of noise field, nor uses a VAD. The presented method exploits the existence of accurate single-channel noise PSD estimators, as well as the availability of one noise reference per microphone pair. For spatially and temporally non-stationary noise fields, the proposed method leads to improved performance compared to widely used state-of-the-art reference methods in terms of both segmental SNR and beamformer response error.

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