A Thorough Investigation on Speech Enhancement Techniques for Hearing Aids

Abstract

In recent years, speech development has become an interesting area in the field of signal processing especially in the applications of hearing aids. In hearing aid applications, the speech enhancement technique has been employed mainly for dipping the additive background noise. During the speech enhancement process, high background noise occurs due to the rapture nature of the speech. In order to overcome this problem, various methods have been employed for increasing the speech quality of hearing aid application. This paper provides an outlook of the speech enhancement techniques in a detailed manner with various speech enhancement algorithms such as Wiener filtering, beamformer, generalized singular value decomposition, transformations, and spectral subtraction technique. These methods have been designed with the main aim of reducing background noise. This paper discussed the merits and demerits of all speech enhancement algorithms with their unique characteristic features. The performance of the algorithm has been evaluated with the help of parameter metrics such as PSEQ and SNR.

CNN-based noise reduction for multi-channel speech enhancement system with discrete wavelet transform (DWT) preprocessing

“…Despite the challenges, there are several algorithms developed and experimented such as subtraction algorithms, over subtraction algorithms, non-linear spectral subtraction, non-linear weighted subtraction, etc . These algorithms improved the performance of speech quality in noisy environments; however, they’re computationally intensive and not effective at suppressing noisy audio signals, especially when the SNR is low i.e., −10 dB to 10 dB ( Shanmugapriya & Chandra, 2014 ; Upadhyay & Karmakar, 2015 ; Saleem et al, 2022 ). This environmental noise is difficult to filter because it has different characteristics in terms of noisy levels in decibels, frequencies etc .…”