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Autorzy (2)

• AGHFraś Mieszko
• AGHKowalczyk Konrad

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Dane bibliometryczne

ID BaDAP	141925
Data dodania do BaDAP	2022-09-06
Tekst źródłowy	URL
DOI	10.1109/LSP.2022.3203665
Rok publikacji	2022
Typ publikacji	artykuł w czasopiśmie
Otwarty dostęp
Czasopismo/seria	IEEE Signal Processing Letters

Abstract

In this letter, we address the problem of simultaneous separation and dereverberation of overlapped speech recorded in reverberant conditions. The majority of state-of-theart techniques are tailored for either of the two problems, which for the joint task leads to sub-optimum performance or solutions which involve subsequent, cascade processing. In contrast, we propose a jointly optimum approach in which we formulate a single optimization criterion that minimizes variance of undesired signal components at the output of a convolutional filter, weighted with the desired speech variance, subject to a constraint which allows to control the amount of distortions in the estimated speech signal. We then derive a closed-form solution of the proposed convolutional weighted parametric multichannel Wiener (CWPMW) filter which integrates linear-prediction based dereverberation and speech-distortion weighted Wiener filtering in a jointly optimum manner. The results of experiments performed using measured and simulated data indicate superior performance of the proposed approach in comparison with state-of-the-art, which includes sub-optimum cascades of optimum filters for individual tasks, as well as the recently presented jointly optimum, weighted\ power minimization distortionless response (WPD) beamformer.

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