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Correlation Detection for Adaptive Feedback Cancellation in Hearing Aids

Strasser, F. ; Puder, H. (2016)
Correlation Detection for Adaptive Feedback Cancellation in Hearing Aids.
In: IEEE Signal Processing Letters, 23 (7)
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Acoustic feedback is a well-known phenomenon in hearing aids. Under certain conditions, it causes the so-called howling effect, which is highly annoying for the hearing aid user and limits the maximum amplification of the hearing aid. The standard adaptive feedback cancellation algorithms suffer from a biased adaptation if the input signal is spectrally colored or tonal, as it is for speech and music signals. Due to this bias distortion artifacts (entrainment) are generated. In this letter, we present a method to detect tonal, high correlated parts of the input signal. In particular, the method is able to distinguish between correlation resulting from the input signal and from feedback path changes. A subband feedback cancellation system which applies decorrelation methods is the basis for the proposed method. Additionally, we suggest to use the correlation detection to increase the performance of the mentioned feedback cancellation system. The performance is measured by preventing entrainment and reacting to feedback path changes.

Typ des Eintrags: Artikel
Erschienen: 2016
Autor(en): Strasser, F. ; Puder, H.
Art des Eintrags: Bibliographie
Titel: Correlation Detection for Adaptive Feedback Cancellation in Hearing Aids
Sprache: Englisch
Publikationsjahr: Juli 2016
Titel der Zeitschrift, Zeitung oder Schriftenreihe: IEEE Signal Processing Letters
Jahrgang/Volume einer Zeitschrift: 23
(Heft-)Nummer: 7
URL / URN: http://ieeexplore.ieee.org/abstract/document/7482781/
Kurzbeschreibung (Abstract):

Acoustic feedback is a well-known phenomenon in hearing aids. Under certain conditions, it causes the so-called howling effect, which is highly annoying for the hearing aid user and limits the maximum amplification of the hearing aid. The standard adaptive feedback cancellation algorithms suffer from a biased adaptation if the input signal is spectrally colored or tonal, as it is for speech and music signals. Due to this bias distortion artifacts (entrainment) are generated. In this letter, we present a method to detect tonal, high correlated parts of the input signal. In particular, the method is able to distinguish between correlation resulting from the input signal and from feedback path changes. A subband feedback cancellation system which applies decorrelation methods is the basis for the proposed method. Additionally, we suggest to use the correlation detection to increase the performance of the mentioned feedback cancellation system. The performance is measured by preventing entrainment and reacting to feedback path changes.

Freie Schlagworte: Acoustics;Auditory system;Correlation;Decorrelation;Frequency control;Loudspeakers;Stability analysis;Adaptation control;Adaptive feedback cancellation;NLMS filter adaptation;adaptation control;adaptive feedback cancellation (AFC);correlation detection;frequency shift;frequency shift (FS);hearing aids;hearing aids (HAs);prediction error filter;prediction error filter (PEF);variable step size
Fachbereich(e)/-gebiet(e): Exzellenzinitiative > Graduiertenschulen > Graduate School of Computational Engineering (CE)
Exzellenzinitiative > Graduiertenschulen
Exzellenzinitiative
Hinterlegungsdatum: 27 Feb 2017 13:31
Letzte Änderung: 27 Feb 2017 13:31
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