Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/12753
Title: Nonlinear acoustic echo cancellation with kernelized adaptive filters
Authors: Sankar S.
Kar, Asutosh
Burra S.
SWAMY M.
Mladenovic, Vladimir
Issue Date: 2020
Abstract: © 2020 Elsevier Ltd A well-known problem in speech communication is the occurrence of acoustic echo in hands-free telephony. There are several classical adaptive filters that have been used as a stand alone approach for linear acoustic echo cancellation(AEC). A common assumption in most AEC techniques is that the echo path is linear. However, in real scenarios, owing to distortions introduced by other acoustic artefacts in handheld devices, the echo path is nonlinear. Therefore, there is a need to employ a nonlinear echo canceller. In this paper, a kernel expansion on a family of adaptive filtering algorithms based on least mean square filter is proposed. Kernel methods help model the nonlinear echo path and attain global minimum easily by finding the optimal set of filter weights. The simulations are carried out for speech signal with and without noise under different signal-to-noise ratio values. The results show that the proposed method achieves a significant improvement in a nonlinear acoustic echo cancellation environment in terms of echo return loss enhancement.
URI: https://scidar.kg.ac.rs/handle/123456789/12753
Type: article
DOI: 10.1016/j.apacoust.2020.107329
ISSN: 0003-682X
SCOPUS: 2-s2.0-85082684331
Appears in Collections:Faculty of Technical Sciences, Čačak

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