Online Estimation of Reverberation Parameters For Late Residual Echo Suppression

Abstract

In hands-free telephony and other distant-talk applications, often a short AEC filter is used to achieve fast convergence at low computational cost. As a result, a significant amount of late residual echo (LRE) may remain, especially in highly reverberant environments. This LRE can be suppressed using a postfilter in the subband domain, which requires an estimate of the power spectral density (PSD) of the LRE. To estimate the LRE PSD, an exponentially decaying model with frequency-dependent reverberation scaling and decay parameters has frequently been assumed. State-of-the-art methods estimate both reverberation parameters independently of each other, either in offline or in online mode. In this article, we propose two signal-based methods (i.e. output error and equation error) to jointly estimate both reverberation parameters in online mode. The estimated parameters are then used to generate an estimate for the LRE PSD, which is fed into a postfilter for the purpose of late residual echo suppression. We derive several gradient-descent-based algorithms to simultaneously update both reverberation parameters, minimizing either the mean squared error or the mean squared log error cost function. The proposed methods are compared with state-of-the-art methods in terms of the accuracy of the estimated reverberation parameters and the corresponding LRE PSD estimate. Extensive simulation results using both artificial as well as measured room impulse responses show that the proposed output error method with mean squared log error minimization outperforms state-of-the-art methods in all considered scenarios.