Joint Late Reverberation and Noise Power Spectral Density Estimation in a Spatially Homogeneous Noise Field

Abstract

Many multi-channel dereverberation and noise reduction techniques such as the multi-channel Wiener filter (MWF) require an estimate of the late reverberation and noise power spectral densities (PSDs). State-of-the-art multi-channel methods for estimating the late reverberation PSD typically assume that the noise PSD matrix is known. Instead of assuming that the noise PSD matrix is known, in this paper we model the noise as a spatially homogeneous sound field with an unknown time-varying PSD and a known time-invariant spatial coherence matrix. Based on this model, two joint estimators of the late reverberation and noise PSDs are proposed, i.e., a non-blocking-based estimator which simultaneously estimates the target signal, late reverberation, and noise PSDs, and a blocking-based estimator which first estimates the late reverberation and noise PSDs at the output of a blocking matrix aiming to block the target signal. Experimental results show that the proposed blocking-based estimator yields the best performance when used in an MWF, even resulting in a similar or better performance than a state-of-the-art blocking-based estimator of the late reverberation PSD which assumes that the noise PSD matrix is known.