DocumentCode :
705445
Title :
Prediction-error-method-based adaptive feedback cancellation in hearing aids using pitch estimation
Author :
Kim Ngo ; van Waterschoot, Toon ; Christensen, Mads Grosboll ; Moonen, Marc ; Jensen, Soren Holdt ; Wouters, Jan
Author_Institution :
ESAT-SCD, Katholieke Univ. Leuven, Leuven, Belgium
fYear :
2010
fDate :
23-27 Aug. 2010
Firstpage :
40
Lastpage :
44
Abstract :
Acoustic feedback is a well-known problem in hearing aids, which is caused by the undesired acoustic coupling between the loudspeaker and the microphone. The goal of adaptive feedback cancellation (AFC) is to adaptively model the feedback path and estimate the feedback signal, which is then subtracted from the microphone signal. The main problem in identifying the feedback path model is the correlation between the near-end signal and the loudspeaker signal, which is caused by the closed signal loop. In this paper, a novel prediction-error-method (PEM)-based AFC is presented using a harmonic sinusoidal near-end signal model. Furthermore, the prediction error filter (PEF) is designed to incorporate a variable order and a variable amplitude next to a variable pitch. Simulation results for a hearing aid scenario indicate an improvement up to 6dB in maximum stable gain increase and up to 8dB improvement in terms of misadjustment.
Keywords :
acoustic signal processing; feedback; hearing aids; interference suppression; loudspeakers; microphones; AFC; PEF; feedback path; feedback signal estimation; harmonic sinusoidal near-end signal model; hearing aids; loudspeaker signal; microphone signal; pitch estimation; prediction error filter; prediction-error-method-based adaptive feedback cancellation; undesired acoustic coupling; Adaptation models; Estimation; Frequency control; Frequency estimation; Harmonic analysis; Microphones; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2010 18th European
Conference_Location :
Aalborg
ISSN :
2219-5491
Type :
conf
Filename :
7096718
Link To Document :
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