A Switched Algorithm for Adaptive Feedback Cancellation Using Pre-Filters in Hearing Aids

Abstract

Acoustic coupling between microphone and loudspeaker is a significant problem in open-fit digital hearing aids. An open-fit compared to a close-fit hearing aid significantly lowers the signal quality and limits the achievable maximum stable gain. Adaptive feedback cancellation (AFC) enables an efficient approach to reduce the impact of acoustic coupling. However, without careful consideration, it can also introduce bias in estimating the feedback path due to the high correlation between the loudspeaker signal and the incoming signal, especially when the incoming signal is spectrally coloured, e.g., speech and music. The prediction error method (PEM) is well known for reducing this bias. The presented study aims to propose a switched PEM with soft-clipping (swPEMSC) that allows for further improvement in convergence/tracking rates, resulting in a better ability to recover from unstable/howling status. This swPEMSC employs a new update rule inspired by a soft-clipping based stability detector (SCSD). It allows to pick up either the PEMSC-NLMS or PEMSC-APA depending on the magnitude of the effective feedback signal; howling corresponds to a large feedback signal. The PEMSC-NLMS with a small step-size ensures a low steady-state error, but slow convergence/tracking rates, while PEMSC-APA with a large step-size allows for fast convergence/tracking rates, but a high steady-state error. By combining those approaches, the proposed approach can take advantage of good characteristics from both. Experimental results using different types of incoming signals and an abrupt change of feedback paths show that the swPEMSC can shorten unstable periods (howling) by improving the convergence and tracking rates while retaining a low steady-state error and good signal quality.

An acoustic feedback canceler based on probe noise and informative data for hearing aids

“…Remark 1: When AFC is successfully performed, the AF path estimation is expected to be approximately equal to the actual AF path, that is, w(n) ∼ = w f (n) [13]. However, in equation ( 9), the optimum solution includes R xx (n) and p xd (n) expressions in addition to w f expression.…”

“…All simulation studies are performed on the well-known AF path [13], [24] measured from the behind-the-ear hearing aid. In addition, the AF path has a sampling frequency of 8 kHz and 100 weight coefficients [13], [24].…”

“…All simulation studies are performed on the well-known AF path [13], [24] measured from the behind-the-ear hearing aid. In addition, the AF path has a sampling frequency of 8 kHz and 100 weight coefficients [13], [24]. The amplitude and phase responses of the considered AF path are depicted in Figures 3a and 3b, respectively.…”

“…In the literature, many methods have been used to eliminate the bias effect caused by high correlation. The main ones of approaches are estimation error method (PEM) based decorrelation filter [13], phase modulation [14], frequency shift [15], and probe noise injection [16]. On the other hand, this study focuses on the probe noise injection approach in order to eliminate the bias effect.…”

Acoustic Feedback Noise Cancellation in Hearing Aids Using Adaptive Filter

“…In spite of its size constraints, body worn hearing aid provides large amplification, long battery life. It available for lower prices in the market compared to other aids [11][12][13]. Ear worn hearing aid is the most common hearing aid, used by the majority of hearing patients.…”