Optimal Binaural LCMV Beamforming in Complex Acoustic Scenarios: Theoretical and Practical Insights
This work addresses improving speech quality and spatial perception in hearing aids for users in complex acoustic scenarios, but it is incremental as it builds on existing BLCMV methods.
The paper tackled the problem of optimally setting interference scaling parameters in the BLCMV beamformer for binaural hearing aids in noisy environments, showing that short observation intervals suffice for decent noise reduction and a proposed threshold reduces binaural cue errors.
Binaural beamforming algorithms for head-mounted assistive listening devices are crucial to improve speech quality and speech intelligibility in noisy environments, while maintaining the spatial impression of the acoustic scene. While the well-known BMVDR beamformer is able to preserve the binaural cues of one desired source, the BLCMV beamformer uses additional constraints to also preserve the binaural cues of interfering sources. In this paper, we provide theoretical and practical insights on how to optimally set the interference scaling parameters in the BLCMV beamformer for an arbitrary number of interfering sources. In addition, since in practice only a limited temporal observation interval is available to estimate all required beamformer quantities, we provide an experimental evaluation in a complex acoustic scenario using measured impulse responses from hearing aids in a cafeteria for different observation intervals. The results show that even rather short observation intervals are sufficient to achieve a decent noise reduction performance and that a proposed threshold on the optimal interference scaling parameters leads to smaller binaural cue errors in practice.