Combined acoustic echo control and noise reduction for hands-free telephony

Gustafsson, Stefan; Martin, Rainer; Vary, Peter

doi:10.1016/s0165-1684(97)00173-4

Cited by 82 publications

(55 citation statements)

References 11 publications

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“…When residual echo and noise are suppressed, Gustafsson et al [30] and Jeannès et al [11] concluded that the best result is obtained by suppressing both interferences together after the AEC. The main advantage of this approach is that the residual echo and noise suppression does not suffer from the existence of a strong acoustic echo component.…”

Section: Generalized Postfiltermentioning

confidence: 99%

“…Using the initial power (see Appendix C), we can now estimate using (29) where can be calculated using (30) where denotes the smoothing parameter. In general, a value ms yields good results.…”

Section: Late Residual Echo Spectral Variance Estimationmentioning

confidence: 99%

“…Note that in some cases it might be desirable to reduce one of the interferences at the cost of larger speech distortion, while other interferences are reduced less to avoid distortion. Gustafsson et al also used separate a priori SIRs in [13], [30] for two interferences, i.e., background noise and residual echo. In this section we show how the Decision Directed approach can be used to estimate the individual a priori SIRs, and we propose a slightly different way of combining them.…”

Section: Appendix a A Priori Sir Estimatormentioning

confidence: 99%

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Joint Dereverberation and Residual Echo Suppression of Speech Signals in Noisy Environments

Habets

Gannot

Cohen

et al. 2008

IEEE Trans. Audio Speech Lang. Process.

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Abstract-Hands-free devices are often used in a noisy and reverberant environment. Therefore, the received microphone signal does not only contain the desired near-end speech signal but also interferences such as room reverberation that is caused by the near-end source, background noise and a far-end echo signal that results from the acoustic coupling between the loudspeaker and the microphone. These interferences degrade the fidelity and intelligibility of near-end speech. In the last two decades, postfilters have been developed that can be used in conjunction with a single microphone acoustic echo canceller to enhance the near-end speech. In previous works, spectral enhancement techniques have been used to suppress residual echo and background noise for single microphone acoustic echo cancellers. However, dereverberation of the near-end speech was not addressed in this context. Recently, practically feasible spectral enhancement techniques to suppress reverberation have emerged. In this paper, we derive a novel spectral variance estimator for the late reverberation of the near-end speech. Residual echo will be present at the output of the acoustic echo canceller when the acoustic echo path cannot be completely modeled by the adaptive filter. A spectral variance estimator for the so-called late residual echo that results from the deficient length of the adaptive filter is derived. Both estimators are based on a statistical reverberation model. The model parameters depend on the reverberation time of the room, which can be obtained using the estimated acoustic echo path. A novel postfilter is developed which suppresses late reverberation of the near-end speech, residual echo and background noise, and maintains a constant residual background noise level. Experimental results demonstrate the beneficial use of the developed system for reducing reverberation, residual echo, and background noise. S. Gannot is with the School of Engineering, Bar-Ilan University, Ramat-Gan 52900, Israel (e-mail: gannot@eng.biu.ac.il).I. Cohen is with the Department of Electrical Engineering, Technion-Israel Institute of Technology, Haifa 32000, Israel (e-mail: icohen@ee.technion.ac.il). P. C. W. Sommen is with the Signal Processing

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Section: Generalized Postfiltermentioning

confidence: 99%

Section: Late Residual Echo Spectral Variance Estimationmentioning

confidence: 99%

Section: Appendix a A Priori Sir Estimatormentioning

confidence: 99%

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Joint Dereverberation and Residual Echo Suppression of Speech Signals in Noisy Environments

Habets

Gannot

Cohen

et al. 2008

IEEE Trans. Audio Speech Lang. Process.

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“…Global approaches based on optimal "ltering to reduce simultaneously echo and noise disturbances have been presented recently [4,29,64].…”

Section: Combined Acoustic Echo Cancellation and Noise Reductionmentioning

confidence: 99%

Innovative speech processing for mobile terminals: an annotated bibliography

et al. 2000

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This paper gives an overview of recent bibliographic references dealing with speech processing in mobile terminals. Its purpose is to point out state of the art issues in the area; thus a fairly large list of references taken from many conferences proceedings and journals is given and commented. General considerations about speech processing in mobile communications are "rstly introduced; then we deal with audio processing for speech enhancement in mobile terminals and with low bit-rate speech coding. Speech recognition is addressed with some accent put on mobile applications. A short overview of implementation aspects of speech processing algorithms in mobile terminals is also given. Finally, open issues and problems are listed.2000 Published by Elsevier Science B.V. All rights reserved. ZusammenfassungDiese Arbeit gibt einen U G berblick auf neue bibliogra"sche Referenzen, die sich mit der Sprachverarbeitung in mobilen Einheiuten beschaK ftigen. Unser Ziel ist es, den Stand der technischen VeroK !entlichungen auf diesem Gebiet zu ermitteln; somit ist eine recht lange Liste von Referenzen aus vielen Konferenzen und Zeitschiften und die zugehoK rigen Kommentare angegeben. Allgemeine U G berlegungen zur Sprachverarbeitung in der Mobilkommunikation werden als erstes angefuK hrt; anschlie{end behandeln wir Verfahren zur Spracheverbesserung in mobilen Systemen basierend auf niedrigen Bitraten. Bei der anschlieend behandelten Spracherkennung wird ein gewisser Schwerpunkt auf mobile Systeme gelegt. Ein kurzer U G berblick zum Implementierungsaspekt der Sparchverarbeitungsverfahren in mobilen EndgeraK ten ist ebenfalls angegeben. Schlielich werden o!ene Themen und Probleme aufgezeigt.2000 Published by Elsevier Science B.V. All rights reserved. Re2 sume2Cet article passe en revue la bibliographie reH cente concernant le traitement de la parole dans les terminaux mobiles. Son objectif est de mettre l'accent sur l'eH tat de l'art dans le domaine; en conseH quence une importante liste de reH feH rences recueillies dans des actes de congre`s et des revues est donneH e et commenteH e. En premier lieu, des consideH rations geH neH rales sur le traitement de la parole dans les communications mobiles sont preH senteH es; puis nous discutons de traitements de rehaussement de la parole dans les terminaux mobiles ainsi que du codage de la parole a`bas deH bits. La reconnaissance vocale est traiteH e avec un accent particulier mis sur les applications mobiles. L'implantation des algorithmes de traitement de la parole dans les terminaux mobiles est aussi brie`vement traiteH e. En"n, certaines questions et proble`mes ouverts sont citeH s.

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“…7, 91058 Erlangen, Germany echo suppression, where the microphone signal is filtered in a way such that a distortion of the local acoustic scene cannot be avoided [8,9]. However, acoustic echo suppression is often also used as a post-filtering method after AEC [10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm

Schneider

Kellermann

2016

EURASIP J. Adv. Signal Process.

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Acoustic echo cancellation (AEC) is a well-known application of adaptive filters in communication acoustics. To implement AEC for multichannel reproduction systems, powerful adaptation algorithms like the generalized frequency-domain adaptive filtering (GFDAF) algorithm are required for satisfactory convergence behavior. In this paper, the GFDAF algorithm is rigorously derived as an approximation of the block recursive least-squares (RLS) algorithm. Thereby, the original formulation of the GFDAF algorithm is generalized while avoiding an error that has been in the original derivation. The presented algorithm formulation is applied to pruned transform-domain loudspeaker-enclosure-microphone models in a mathematically consistent manner. Such pruned models have recently been proposed to cope with the tremendous computational demands of massive multichannel AEC. Beyond its generalization, a regularization of the GFDAF is shown to have a close relation to the well-known block least-mean-squares algorithm.

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Combined acoustic echo control and noise reduction for hands-free telephony

Cited by 82 publications

References 11 publications

Joint Dereverberation and Residual Echo Suppression of Speech Signals in Noisy Environments

Joint Dereverberation and Residual Echo Suppression of Speech Signals in Noisy Environments

Innovative speech processing for mobile terminals: an annotated bibliography

The generalized frequency-domain adaptive filtering algorithm as an approximation of the block recursive least-squares algorithm

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