Operational Rate-Constrained Beamforming in Binaural Hearing AIDS

Conference Paper (2018)
Author(s)

Jamal Amini (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Richard C. Hendriks (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Richard Heusdens (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Meng Guo (Oticon A/S)

Jesper Rindom Jensen (Oticon A/S, Aalborg University)

Research Group
Signal Processing Systems
DOI related publication
https://doi.org/10.23919/EUSIPCO.2018.8553403 Final published version
More Info
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Publication Year
2018
Language
English
Research Group
Signal Processing Systems
Article number
8553403
Pages (from-to)
2504-2508
ISBN (print)
978-1-5386-3736-4
ISBN (electronic)
978-9-0827-9701-5
Event
EUSIPCO 2018 (2018-09-03 - 2018-09-07), Rome, Italy
Downloads counter
177

Abstract

Modern binaural hearing aids (HAs) can collaborate wirelessly with each other as well as with other assistive (wireless) devices. This enables multi-microphone noise reduction over small wireless acoustic sensor networks (WASNs) to increase the intelligibility under adverse conditions. In this work, we assume one of the HAs to serve as the fusion center (FC). The optimal beamforming strategy for processing the received data at the FC depends on the acoustic scene and physical constraints (e.g., the bit-rate for transmission to the FC), and might be frequency dependent. Selection of the optimal beamforming strategy, while satisfying rate constraints on the communication between the different devices is an important challenge in such setups. In this paper, we propose an operational rate-constrained beamforming system for optimal rate allocation and strategy selection across frequency. We show an example of the proposed framework, where both the algorithm selection as well as the required rates to transmit the necessary microphone signals are optimized using uniform quantizers, while minimizing the mean-square error (MSE) distortion measure. In contrast to a well-known (theoretically optimal) reference method based on remote source coding for two devices, the presented algorithm is practically implementable and only requires knowledge of joint signal statistics at the FC. Evaluations (based on simulation experiments) show clear improvement over other practically implementable strategies.