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Rank-1 Approximation Based Multichannel Wiener Filtering Algorithms For Noise Reduction In Cochlear Implants

Abstract : This paper presents multichannel Wiener filtering-based algorithms for noise reduction in cochlear implants. In a single speech scenario, the autocorrelation matrix of the speech signal can be approximated by a rank-1 matrix. It is then possible to derive noise reduction filters that deliver improved signal-to-noise ratio performance. The link between these different filters is investigated here and an eigenvalue decomposition based algorithm is demonstrated to be more stable at low input signal-to-noise ratio compared to previous algorithms.
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https://hal.archives-ouvertes.fr/hal-01393980
Contributor : Romain Serizel <>
Submitted on : Tuesday, November 8, 2016 - 2:27:46 PM
Last modification on : Thursday, February 21, 2019 - 10:31:47 AM
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  • HAL Id : hal-01393980, version 1

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Romain Serizel, Marc Moonen, Bas Dijk, Jan Wouters. Rank-1 Approximation Based Multichannel Wiener Filtering Algorithms For Noise Reduction In Cochlear Implants. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2013, Vancouver, Canada. ⟨hal-01393980⟩

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