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A Convex Framework for the Multichannel Wiener Filter with Preservation of Binaural in Hearing Aids

EasyChair Preprint 9018

6 pagesDate: October 6, 2022

Abstract

Noise reduction is a fundamental step in signal processing in binaural hearing aids. In general, this procedure is characterized by an optimization algorithm that minimizes a cost function composed of a combination of the Wiener multichannel filter and constraints or penalty terms that aim to guarantee the preservation of binaural spatial information. However, the cost function is non-convex, which makes its solution demand a high computational cost. In this work we propose a computationally efficient approach for noise reduction with preservation of binaural spatial information, based on a convex relaxation of the original optimization problem. Experiments indicate that the proposed technique achieves performance comparable to state-of-the-art algorithms in terms of noise reduction and preservation of the perception of the spatial location of point sources, but with an extremely reduced processing time.

Keyphrases: Aparelho auditivo, pistas biauriculares, redução de ruído

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:9018,
  author    = {Diego Carmo and Ricardo Borsoi and Marcio Costa},
  title     = {A Convex Framework for the Multichannel Wiener Filter with Preservation of Binaural in Hearing Aids},
  howpublished = {EasyChair Preprint 9018},
  year      = {EasyChair, 2022}}
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