In this section
@article{Moore:2019:10.1121/1.5102173,
author = {Moore, AH and de, Haan JM and Pedersen, MS and Brookes, D and Naylor, PA and Jensen, J},
doi = {10.1121/1.5102173},
journal = {Journal of the Acoustical Society of America},
pages = {2971--2981},
title = {Personalized signal-independent beamforming for binaural hearing aids},
url = {http://dx.doi.org/10.1121/1.5102173},
volume = {145},
year = {2019}
}
TY - JOUR
AB - The effect of personalized microphone array calibration on the performance of hearing aid beamformers under noisy reverberant conditions is studied. The study makes use of a new, publicly available, database containing acoustic transfer function measurements from 29 loudspeakers arranged on a sphere to a pair of behind-the-ear hearing aids in a listening room when worn by 27 males, 14 females, and 4 mannequins. Bilateral and binaural beamformers are designed using each participant's hearing aid head-related impulse responses (HAHRIRs). The performance of these personalized beamformers is compared to that of mismatched beamformers, where the HAHRIR used for the design does not belong to the individual for whom performance is measured. The case where the mismatched HAHRIR is that of a mannequin is of particular interest since it represents current practice in commercially available hearing aids. The benefit of personalized beamforming is assessed using an intrusive binaural speech intelligibility metric and in a matrix speech intelligibility test. For binaural beamforming, both measures demonstrate a statistically signficant (p < 0.05) benefit of personalization. The benefit varies substantially between individuals with some predicted to benefit by as much as 1.5 dB.
AU - Moore,AH
AU - de,Haan JM
AU - Pedersen,MS
AU - Brookes,D
AU - Naylor,PA
AU - Jensen,J
DO - 10.1121/1.5102173
EP - 2981
PY - 2019///
SN - 0001-4966
SP - 2971
TI - Personalized signal-independent beamforming for binaural hearing aids
T2 - Journal of the Acoustical Society of America
UR - http://dx.doi.org/10.1121/1.5102173
UR - http://hdl.handle.net/10044/1/69868
VL - 145
ER -
Speech and Audio Processing Lab
CSP Group, EEE Department
Imperial College London
Exhibition Road, London, SW7 2AZ, United Kingdom