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2018
Conference Paper
Title
Blind single-channel dereverberation using a recursive maximum-sparseness-power-prediction-model
Abstract
Several single-channel speech dereverberation techniques rely on a sufficiently precise estimate of the reverberation time T 60 . Blindly estimating the frequency dependent T 60 remains a challenging task, especially if only a short time section is available for the estimation. In this work, we first review an offline method which estimates both T 60 per frequency as well as the power spectral density (PSD) of the early reverberant speech and then derive a recursive and adaptive version thereof. These estimates can be used to suppress the late reverberation of reverberant speech signals. It is shown that the proposed algorithm can estimate the T 60 with a deviation of approximately ±20% w.r.t. the ground truth value. Moreover, objective quality measures show that the proposed dereverberation algorithm performs slightly better than two other existing methods.