Automated Dual-Channel Speech Enhancement Using Adaptive Coherence Function with Optimised Discrete Wavelet Transform

Vanita Raj Tank and Shrinivas Padmakar Mahajan
Additional contact information
Vanita Raj Tank: School of Electronics and Communication, Dr. Vishwanath Karad, MIT World Peace University, Pune, Maharashtra, India
Shrinivas Padmakar Mahajan: Electronics and Telecommunication, College of Engineering, Savitribai Phule Pune University, Pune, Maharashtra, India

Journal of Information & Knowledge Management (JIKM), 2022, vol. 21, issue 03, 1-53

Abstract: Voice quality enhancement is a significant method for any speech communication model. Speech Enhancement (SE) and noise reduction approaches can significantly improve the perceptual voice quality of a hands-free communication system and increase the recognition rates of automatic speech recognition systems. Speech communications in real-world cases require high-performance enhancement techniques for addressing the distortions, which can corrupt the intelligibility and quality of the speech signal. Recent portable devices generally incorporate several microphones that can be easily used for improving signal quality. This paper plans to present a novel dual-channel SE model using the coherence function and heuristic concepts. The adaptive coherence function relates to the dual-microphone SE approach suitable for smartphones with primary and reference microphones. With this improved signal, the enhancement is performed by optimising denoising using Discrete Wavelet Transform (DWT) by Adaptive wind speed-based Deer Hunting Optimization Algorithm (AWS-DHOA). The considered objective function depends on the quality measure called Perceptual Evaluation of Speech Quality (PESQ) score. From the results, the RMSE of the proposed model using AWS-DHOA is 39.8%, 45.5%, 53.8% and 45.5% minimised than GWO-CFD, WOA-CFD, CSA-CFD, and RDA-CFD, respectively, on considering the babble noise. Finally, the comparative analysis confirmed that the proposed method improves speech quality and intelligibility by comparing diverse algorithms when different noise types corrupt the speech.

Keywords: Speech enhancement model; intelligibility and quality; adaptive coherence function; optimised denoising using discrete wavelet transform; adaptive wind speed-based deer hunting optimization algorithm; perceptual evaluation of speech quality (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S021964922250037X
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:jikmxx:v:21:y:2022:i:03:n:s021964922250037x

Ordering information: This journal article can be ordered from

DOI: 10.1142/S021964922250037X

Access Statistics for this article

Journal of Information & Knowledge Management (JIKM) is currently edited by Professor Suliman Hawamdeh

More articles in Journal of Information & Knowledge Management (JIKM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().