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    Improving adaptive feedback cancellation in hearing AIDS using an affine combination of filters

    Access Status
    Fulltext not available
    Authors
    Schepker, H.
    Tran, Linh T.T.
    Nordholm, Sven
    Doclo, S.
    Date
    2016
    Type
    Conference Paper
    
    Metadata
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    Citation
    Schepker, H. and Tran, L. and Nordholm, S. and Doclo, S. 2016. Improving adaptive feedback cancellation in hearing AIDS using an affine combination of filters, International Conference on Acoustics, Speech and Signal Processing (ICASSP), 20-25 March 2016, pp. 231-235: IEEE.
    Source Title
    International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    DOI
    10.1109/ICASSP.2016.7471671
    ISBN
    9781479999880
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/50609
    Collection
    • Curtin Research Publications
    Abstract

    In adaptive feedback cancellation an adaptive filter is used to model the acoustic feedback path between the hearing aid loudspeaker and the microphone. An important parameter for adaptive filters is the step-size, providing a trade-off between fast convergence and low steady-state misalignment. In order to achieve both fast convergence as well as low steady-state misalignment, it has been proposed to use an affine combination scheme of two filters operating with different step-sizes. In this paper we apply such an affine combination scheme to the acoustic feedback cancellation problem in hearing aids. We show that for speech signals a time-domain affine combination scheme yields a biased solution. To reduce this bias we propose to use a partitioned-block frequency-domain affine combination scheme. Experimental results using measured acoustic feedback paths show that in terms of misalignment and added stable gain the proposed adaptive feedback cancellation system outperforms a system that only uses a single adaptive filter with either of the fixed step-sizes used for the affine combination scheme.

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