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Binaural Beamforming Based on Automatic Interferer Selection

Citation Author(s):
Costas A. Kokke, Richard C. Hendriks, Andreas I. Koutrouvelis
Submitted by:
Costas Kokke
Last updated:
9 May 2019 - 4:48pm
Document Type:
Poster
Document Year:
2019
Event:
Presenters:
Costas A. Kokke
Paper Code:
2845
 

Binaural cues are important for sound localization. In addition, spatially separated sound sources are more intelligible than when they are co-located. Binaural cue preservation in multi-microphone hearing assistive devices is therefore important for the user's listening experience and safety.
A number of linearly-constrained-minimum-variance (LCMV) based methods
exist for this purpose. These are all limited in the number of sources for which they can preserve the binaural cues. We propose a method of automatically selecting the most important interfering sources using convex optimization.
The proposed method is compared, using simulation experiments, to existing methods in terms of noise suppression and localization errors.
It improves the performance of the joint binaural LCMV beamformer, by giving it more degrees of freedom for noise reduction and allows a larger number of (virtual) sources present in the scene.

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