Abstract

Acoustic feedback in hearing aids occurs due to the coupling between the hearing aid loudspeaker and microphones. In order to reduce acoustic feedback, adaptive filters are often used to estimate the feedback path. To increase the convergence speed and decrease the computational complexity of the adaptive algorithms, it has been proposed to split the acoustic feedback path into a time-invariant fixed part and a time-varying variable part. A key question of this approach is how to determine the fixed part. In this paper, two approaches are investigated: (1) a digital filter design approach that makes use of the signals of at least two hearing aid microphones and (2) a defined physical location approach using an electro-acoustic model and the signals of one hearing aid microphone and an additional ear canal microphone. An experimental comparison using measured acoustic feedback paths showed that both approaches enable one to reduce the number of variable part coefficients. It is shown that individualization of the fixed part increases the performance. Furthermore, the two approaches offer solutions for different requirements on the effort to a specific hearing aid design on the one hand and the effort during the hearing aid fitting on the other hand.

Highlights

  • In recent years the number of hearing-impaired persons supplied with open-fitting hearing aids has been steadily increasing

  • While the feedback path model based on digital filter design (DFD) requires the measurement of multiple acoustic feedback paths, e.g., at different microphone locations of the BTE unit, the acoustic feedback path models based on a defined physical location (DPL) for the decomposition make use of an ear canal microphone to estimate the fixed part of the acoustic feedback path

  • The wall and the telephone condition (Fig. 11) the models based on a defined physical location achieve significantly better added stable gain (ASG) values compared to the models based on digital filter design that used only the free-field measurements for optimization (DFD ee and DFD wee)

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Summary

INTRODUCTION

In recent years the number of hearing-impaired persons supplied with open-fitting hearing aids has been steadily increasing. Models based on digital filter design aim at finding a set of common filter coefficients that optimize either the least-squares error (Giri and Zhang, 2017; Hashemgeloogerdi and Bocko, 2018; Ma et al, 2011; Schepker and Doclo, 2016b) or the maximum stable gain of the hearing aid (Schepker and Doclo, 2015, 2016a) While these models do not relate the fixed part to the underlying physical and electro-acoustic properties of the feedback path, they have been shown to be successful in reducing the number of variable part parameters and improving the performance of a state-of-the-art AFC algorithm (Schepker and Doclo, 2016a,b).

SCENARIO
FEEDBACK PATH MODELS
Feedback path model based on digital filter design
AfiÀ1ðejXÞ
Feedback path model based on electro-acoustic modeling
Decomposition of the feedback path model based on electro-acoustic modeling
Parameters of the feedback path model based on electro-acoustic modeling
Combined models using electro-acoustic modeling to derive the fixed part
Combined model using a measured transfer function as the fixed part
Acoustic setup and performance measures
Algorithmic parameters
General parameters
Parameters of the feedback path model based on digital filter design
Comparison of feedback path models
Practical considerations and robustness
Findings
Number of parameters
CONCLUSION
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