A hybrid speech enhancement technique based on discrete wavelet transform and spectral subtraction

Iqbal, Yasir and Zhang, Tao and Gunawan, Teddy Surya and Pratondo, Agus and Zhao, Xin and Geng, Yanzhang and Kartiwi, Mira and Saleem, Nasir and Bourouis, Sami (2025) A hybrid speech enhancement technique based on discrete wavelet transform and spectral subtraction. IEEE Access, 13. pp. 39765-39781. ISSN 2169-3536

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Abstract

Speech quality and intelligibility are often severely degraded by background noise in communication systems such as hearing aid (HA) and speech recognition technologies, compromising their effective use. In low Signal-to-Noise Ratio (SNR) conditions, various approaches and algorithms are applied to improve speech quality and intelligibility. This study introduces a novel hybrid speech enhancement framework that synergistically integrates Spectral Subtraction (SS) and Discrete Wavelet Transform (DWT) to address limitations of traditional noise reduction techniques. Traditional SS methods generate musical noise artifacts due to static noise estimation, while standard DWT approaches struggle with selective thresholding and static coefficient processing. To overcome these challenges, the proposed SS method incorporates iterative noise estimation, Voice Activity Detection (VAD), minimum statistics for dynamic noise adaptation, Spectral Smoothing and phase-aware spectral reconstruction. Concurrently, in the enhanced DWT method adaptive noise refinement with phase-aware soft thresholding is employed to detail coefficients, and the Spatial and Intensity filter is adapted to the approximation coefficients to improve low-frequency features and retain structural integrity while reducing distortion. The integrated SS-DWT framework significantly improves noise suppression, reduces musical noise artifacts, and enhances signal clarity as it leverages the strengths of both phase-aware spectral reconstruction in improved SS and phase-aware soft thresholding in DWT, particularly in adaptive noise refinement and thresholding. Proposed speech enhancement network evaluated and experimental results show that the hybrid SS-DWT method outperforms existing systems, achieving up to 34.15 dB in SDR, 0.98 in STOI, and 3.84 in PESQ, demonstrating significant improvements in speech quality under various noisy conditions.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Discrete wavelet transforms, Noise, Speech enhancement, Transforms, Noise reduction, Wavelet transforms, Noise measurement, Hearing aids, Voice activity detection, Distortion
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Engineering
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	08 May 2025 12:13
Last Modified:	08 May 2025 12:13
URI:	http://irep.iium.edu.my/id/eprint/120850

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