Comparison of Statistical Methods and Auditory Models for Acoustic Feedback Suppression in Binaural Hearing Aids For Presbycusis's patients

Abstract

Binaural hearing aids are widely used in managing binaural hearing loss, including Presbycusis, they amplifies sounds regardless of their source, Presbycusis require increased gain along with a gradual decline in hearing, this leads to a greater probability of occurrence of wheezing, which is affecting the performance of hearing aids.

The acoustic feedback is a major problem when designing a hearing aid because it increases with increasing gain. Many researchers have reduced it in different ways using Adaptive Filters, Auditory Models, and Statistical Methods. These methods show an acceptable performance in feedback reduction for English and Persian                                    speakers [1-5,12,23].

In this paper, we present a comparison between statistical methods and auditory models for Acoustic Feedback Suppression in binaural hearing aids for Presbycusis's Patients using Arabic and English speech data of both sexes and with gain from (75 to 90 dB) for patients with severe and profound Presbycusis.

The aim of this paper is identifying the most Effective method for Acoustic Feedback Suppression in Arabic-Speaking Countries.

The results showed that the performance of the statistically blind source separation method (BSS + GMM) is better than the performance of auditory models (CASA) by improving the average values ​​for both the signal to noise ratio (SNR) and the signal-to-feedback ratio (SFR) for Arabic and English speech data. Moreover, (BSS+GMM) allowed the user to increase the gain of the hearing aid without affecting the sound quality.