Wiener variable step size and gradient spectral variance smoothing for double-talk-robust acoustic echo cancellation and acoustic feedback cancellation

Jose M. Gil-Cacho, Toon Van Waterschoot, Marc Moonen, Søren Holdt Jensen

Research output: Contribution to journalJournal articleResearchpeer-review

18 Citations (Scopus)

Abstract

Double-talk (DT)-robust acoustic echo cancellation (AEC) and acoustic feedback cancellation (AFC) are needed in speech communication systems, e.g., in hands-free communication systems and hearing aids. In this paper, we derive a practical and computationally efficient algorithm based on the frequency-domain adaptive filter prediction error method using row operations (FDAF-PEM-AFROW) for DT-robust AEC and AFC. The proposed algorithm features two main modifications: (a) the Wiener variable step size (WVSS) and (b) the gradient spectral variance smoothing (GSVS). In AEC simulations, the WVSS-GSVS-FDAF-PEM-AFROW algorithm obtains outstanding robustness and smooth adaptation in highly adverse scenarios such as in bursting DT at high levels, and in a change of acoustic path during continuous DT. Similarly, in AFC simulations, the algorithm outperforms state-of-the-art algorithms when using a low-order near-end speech model and in colored non-stationary noise.
Original languageEnglish
JournalSignal Processing
Volume104
Pages (from-to)1-14
Number of pages14
ISSN0165-1684
DOIs
Publication statusPublished - 2014

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Echo suppression
Acoustics
Feedback
Communication systems
Hearing aids
Speech communication
Adaptive filters

Cite this

@article{e6a73bf8b7c74b4294c51870456f53ea,
title = "Wiener variable step size and gradient spectral variance smoothing for double-talk-robust acoustic echo cancellation and acoustic feedback cancellation",
abstract = "Double-talk (DT)-robust acoustic echo cancellation (AEC) and acoustic feedback cancellation (AFC) are needed in speech communication systems, e.g., in hands-free communication systems and hearing aids. In this paper, we derive a practical and computationally efficient algorithm based on the frequency-domain adaptive filter prediction error method using row operations (FDAF-PEM-AFROW) for DT-robust AEC and AFC. The proposed algorithm features two main modifications: (a) the Wiener variable step size (WVSS) and (b) the gradient spectral variance smoothing (GSVS). In AEC simulations, the WVSS-GSVS-FDAF-PEM-AFROW algorithm obtains outstanding robustness and smooth adaptation in highly adverse scenarios such as in bursting DT at high levels, and in a change of acoustic path during continuous DT. Similarly, in AFC simulations, the algorithm outperforms state-of-the-art algorithms when using a low-order near-end speech model and in colored non-stationary noise.",
author = "Gil-Cacho, {Jose M.} and {Van Waterschoot}, Toon and Marc Moonen and Jensen, {S{\o}ren Holdt}",
year = "2014",
doi = "10.1016/j.sigpro.2014.03.020",
language = "English",
volume = "104",
pages = "1--14",
journal = "Signal Processing",
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Wiener variable step size and gradient spectral variance smoothing for double-talk-robust acoustic echo cancellation and acoustic feedback cancellation. / Gil-Cacho, Jose M.; Van Waterschoot, Toon ; Moonen, Marc; Jensen, Søren Holdt.

In: Signal Processing, Vol. 104, 2014, p. 1-14.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Wiener variable step size and gradient spectral variance smoothing for double-talk-robust acoustic echo cancellation and acoustic feedback cancellation

AU - Gil-Cacho, Jose M.

AU - Van Waterschoot, Toon

AU - Moonen, Marc

AU - Jensen, Søren Holdt

PY - 2014

Y1 - 2014

N2 - Double-talk (DT)-robust acoustic echo cancellation (AEC) and acoustic feedback cancellation (AFC) are needed in speech communication systems, e.g., in hands-free communication systems and hearing aids. In this paper, we derive a practical and computationally efficient algorithm based on the frequency-domain adaptive filter prediction error method using row operations (FDAF-PEM-AFROW) for DT-robust AEC and AFC. The proposed algorithm features two main modifications: (a) the Wiener variable step size (WVSS) and (b) the gradient spectral variance smoothing (GSVS). In AEC simulations, the WVSS-GSVS-FDAF-PEM-AFROW algorithm obtains outstanding robustness and smooth adaptation in highly adverse scenarios such as in bursting DT at high levels, and in a change of acoustic path during continuous DT. Similarly, in AFC simulations, the algorithm outperforms state-of-the-art algorithms when using a low-order near-end speech model and in colored non-stationary noise.

AB - Double-talk (DT)-robust acoustic echo cancellation (AEC) and acoustic feedback cancellation (AFC) are needed in speech communication systems, e.g., in hands-free communication systems and hearing aids. In this paper, we derive a practical and computationally efficient algorithm based on the frequency-domain adaptive filter prediction error method using row operations (FDAF-PEM-AFROW) for DT-robust AEC and AFC. The proposed algorithm features two main modifications: (a) the Wiener variable step size (WVSS) and (b) the gradient spectral variance smoothing (GSVS). In AEC simulations, the WVSS-GSVS-FDAF-PEM-AFROW algorithm obtains outstanding robustness and smooth adaptation in highly adverse scenarios such as in bursting DT at high levels, and in a change of acoustic path during continuous DT. Similarly, in AFC simulations, the algorithm outperforms state-of-the-art algorithms when using a low-order near-end speech model and in colored non-stationary noise.

U2 - 10.1016/j.sigpro.2014.03.020

DO - 10.1016/j.sigpro.2014.03.020

M3 - Journal article

VL - 104

SP - 1

EP - 14

JO - Signal Processing

JF - Signal Processing

SN - 0165-1684

ER -