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Communication Dans Un Congrès Année : 2013

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

Résumé

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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Dates et versions

hal-01393980 , version 1 (08-11-2016)

Identifiants

  • HAL Id : hal-01393980 , version 1

Citer

Romain Serizel, Marc Moonen, Bas Van 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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