TY - JOUR
T1 - Spatially Correct Rate-Constrained Noise Reduction For Binaural Hearing Aids in Wireless Acoustic Sensor Networks
AU - Amini, Jamal
AU - Hendriks, Richard Christian
AU - Heusdens, Richard
AU - Guo, Meng
AU - Jensen, Jesper
PY - 2020/10
Y1 - 2020/10
N2 - Compared to monaural hearing aids (HAs), binaural hearing aid systems, in which there is a communication link between the two devices, have improved noise reduction capabilities and the ability to preserve binaural spatial information. However, the limited HA battery lifetime puts constraints on the amount of information that can be shared between the two devices. In other words, the rate of transmission between the devices is an important constraint that needs to be considered, while preserving the spatial information. In this article, a linearly constrained noise reduction problem is proposed, which jointly finds the optimal rate allocation and the optimal estimation (beamforming) weights across all sensors and frequencies, while preserving the binaural spatial cues of point sources. The proposed method considers a rate constraint together with linear constraints to preserve the binaural spatial cues of point sources. Minimizing the mean square error on the estimated target speech at the left and the right side beamformers, the optimal weights are found to be rate-constrained linearly constrained minimum variance (LCMV) filters, and the optimal rates are found to be the solutions to a set of reverse water filling problems. The performance of the proposed method is evaluated using the averaged binaural signal-to-noise ratio (SNR), the interaural level difference (ILD) error and the interaural time difference (ITD) error. The results show that the proposed method outperforms spatially correct noise reduction approaches that use naive/random rate allocation strategies.
AB - Compared to monaural hearing aids (HAs), binaural hearing aid systems, in which there is a communication link between the two devices, have improved noise reduction capabilities and the ability to preserve binaural spatial information. However, the limited HA battery lifetime puts constraints on the amount of information that can be shared between the two devices. In other words, the rate of transmission between the devices is an important constraint that needs to be considered, while preserving the spatial information. In this article, a linearly constrained noise reduction problem is proposed, which jointly finds the optimal rate allocation and the optimal estimation (beamforming) weights across all sensors and frequencies, while preserving the binaural spatial cues of point sources. The proposed method considers a rate constraint together with linear constraints to preserve the binaural spatial cues of point sources. Minimizing the mean square error on the estimated target speech at the left and the right side beamformers, the optimal weights are found to be rate-constrained linearly constrained minimum variance (LCMV) filters, and the optimal rates are found to be the solutions to a set of reverse water filling problems. The performance of the proposed method is evaluated using the averaged binaural signal-to-noise ratio (SNR), the interaural level difference (ILD) error and the interaural time difference (ITD) error. The results show that the proposed method outperforms spatially correct noise reduction approaches that use naive/random rate allocation strategies.
KW - Wireless acoustic sensor networks
KW - multi-microphone noise reduction
KW - rate-distortion trade-off
UR - http://www.scopus.com/inward/record.url?scp=85094890826&partnerID=8YFLogxK
U2 - 10.1109/TASLP.2020.3028264
DO - 10.1109/TASLP.2020.3028264
M3 - Journal article
SN - 2329-9290
VL - 28
SP - 2731
EP - 2742
JO - IEEE/ACM Transactions on Audio, Speech, and Language Processing
JF - IEEE/ACM Transactions on Audio, Speech, and Language Processing
M1 - 9210875
ER -