Online Censoring Based Acoustic Feedback Cancellation for Wearable Hearing Aids

Yusuf Eren, Buket Çolak Güvenç, Engin Cemal Menguc
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Abstract

This study introduces a novel online censoring-least mean square (OC-LMS) based acoustic feedback cancellation (AFC) system to eliminate undesired acoustic feedback that causes instability in hearing aids. The performance of the proposed OC-LMS based AFC system is tested on a sample feedback path measured from a behind-the-ear hearing aid and compared with its conventional LMS based version in terms of mean square deviation, misalignment, and added stable gain metrics. Simulation results shows that the proposed AFC system works at higher performance than its LMS based version with fewer data by censoring noninformative data thanks to its censoring mechanism. The proposed novel system will pave the way for the design of wearable hearing aids that work with both high performance and long battery life.
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基于在线审查的可穿戴助听器声反馈消除
本研究介绍了一种新颖的基于在线审查-最小均方(OC-LMS)的声反馈抵消(AFC)系统,以消除导致助听器不稳定的不希望的声反馈。在耳后助听器上测量的样本反馈路径上测试了基于OC-LMS的AFC系统的性能,并在均方差、失调和增加的稳定增益指标方面与基于传统LMS的AFC系统进行了比较。仿真结果表明,该AFC系统通过对非信息性数据的过滤,在数据量较少的情况下比基于LMS的AFC系统具有更高的性能。该新系统将为设计高性能和长电池寿命的可穿戴助听器铺平道路。
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