Head-steered channel selection method for hearing aid applications using remote microphones

TL;DR

This paper introduces a head-steered channel selection method for hearing aids that accurately identifies the target talker’s remote microphone signal using head orientation, outperforming existing methods in complex acoustic environments.

Contribution

It presents a novel maximum likelihood-based channel selection approach leveraging head orientation to improve target signal capture in hearing aids with remote microphones.

Findings

Outperforms existing methods in simulations

Accurately identifies target channels without extra sensors

Effective in multi-talker scenarios

Abstract

We propose a channel selection method for hearing aid applications using remote microphones, in the presence of multiple competing talkers. The proposed channel selection method uses the hearing aid user's head-steering direction to identify the remote channel originating from the frontal direction of the hearing aid user, which captures the target talker signal. We pose the channel selection task as a multiple hypothesis testing problem, and derive a maximum likelihood solution. Under realistic, simplifying assumptions, the solution selects the remote channel which has the highest weighted squared absolute correlation coefficient with the output of the head-steered hearing aid beamformer. We analyze the performance of the proposed channel selection method using close-talking remote microphones and table microphone arrays. Through simulations using realistic acoustic scenes, we show that the proposed channel selection method consistently outperforms existing methods in accurately finding the remote channel that captures the target talker signal, in the presence of multiple competing talkers, without the use of any additional sensors.