Single channel speech enhancement using Wiener filter and compressive sensing

The speech enhancement algorithms are utilized to overcome multiple limitation factors in recent applications such as mobile phone and communication channel. The challenges focus on corrupted speech solution between noise reduction and signal distortion. We used a modified Wiener filter and compress...

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Main Authors:	Sulong, Amart, Gunawan, Teddy Surya, Khalifa, Othman Omran, Kartiwi, Mira, Dao, Hassan
Format:	Article
Language:	English English
Published:	Institute of Advanced Engineering and Science 2017
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/57755/ http://irep.iium.edu.my/57755/ http://irep.iium.edu.my/57755/1/AmartSpeechEnhancement_7733-8387-1-Published.pdf http://irep.iium.edu.my/57755/7/57755_Single%20channel%20speech%20enhancement_scopus.pdf

id	iium-57755
recordtype	eprints
spelling	iium-577552017-12-04T07:27:33Z http://irep.iium.edu.my/57755/ Single channel speech enhancement using Wiener filter and compressive sensing Sulong, Amart Gunawan, Teddy Surya Khalifa, Othman Omran Kartiwi, Mira Dao, Hassan TK Electrical engineering. Electronics Nuclear engineering The speech enhancement algorithms are utilized to overcome multiple limitation factors in recent applications such as mobile phone and communication channel. The challenges focus on corrupted speech solution between noise reduction and signal distortion. We used a modified Wiener filter and compressive sensing (CS) to investigate and evaluate the improvement of speech quality. This new method adapted noise estimation and Wiener filter gain function in which to increase weight amplitude spectrum and improve mitigation of interested signals. The CS is then applied using the gradient projection for sparse reconstruction (GPSR) technique as a study system to empirically investigate the interactive effects of the corrupted noise and obtain better perceptual improvement aspects to listener fatigue with noiseless reduction conditions. The proposed algorithm shows an enhancement in testing performance evaluation of objective assessment tests outperform compared to other conventional algorithms at various noise type conditions of 0, 5, 10, 15 dB SNRs. Therefore, the proposed algorithm significantly achieved the speech quality improvement and efficiently obtained higher performance resulting in better noise reduction compare to other conventional algorithms. Institute of Advanced Engineering and Science 2017-08 Article PeerReviewed application/pdf en http://irep.iium.edu.my/57755/1/AmartSpeechEnhancement_7733-8387-1-Published.pdf application/pdf en http://irep.iium.edu.my/57755/7/57755_Single%20channel%20speech%20enhancement_scopus.pdf Sulong, Amart and Gunawan, Teddy Surya and Khalifa, Othman Omran and Kartiwi, Mira and Dao, Hassan (2017) Single channel speech enhancement using Wiener filter and compressive sensing. International Journal of Electrical and Computer Engineering (IJECE), 7 (3). pp. 1941-1951. ISSN 2088-8708 http://iaesjournal.com/en/index.php/IJECE/article/view/14117
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Sulong, Amart Gunawan, Teddy Surya Khalifa, Othman Omran Kartiwi, Mira Dao, Hassan Single channel speech enhancement using Wiener filter and compressive sensing
description	The speech enhancement algorithms are utilized to overcome multiple limitation factors in recent applications such as mobile phone and communication channel. The challenges focus on corrupted speech solution between noise reduction and signal distortion. We used a modified Wiener filter and compressive sensing (CS) to investigate and evaluate the improvement of speech quality. This new method adapted noise estimation and Wiener filter gain function in which to increase weight amplitude spectrum and improve mitigation of interested signals. The CS is then applied using the gradient projection for sparse reconstruction (GPSR) technique as a study system to empirically investigate the interactive effects of the corrupted noise and obtain better perceptual improvement aspects to listener fatigue with noiseless reduction conditions. The proposed algorithm shows an enhancement in testing performance evaluation of objective assessment tests outperform compared to other conventional algorithms at various noise type conditions of 0, 5, 10, 15 dB SNRs. Therefore, the proposed algorithm significantly achieved the speech quality improvement and efficiently obtained higher performance resulting in better noise reduction compare to other conventional algorithms.
format	Article
author	Sulong, Amart Gunawan, Teddy Surya Khalifa, Othman Omran Kartiwi, Mira Dao, Hassan
author_facet	Sulong, Amart Gunawan, Teddy Surya Khalifa, Othman Omran Kartiwi, Mira Dao, Hassan
author_sort	Sulong, Amart
title	Single channel speech enhancement using Wiener filter and compressive sensing
title_short	Single channel speech enhancement using Wiener filter and compressive sensing
title_full	Single channel speech enhancement using Wiener filter and compressive sensing
title_fullStr	Single channel speech enhancement using Wiener filter and compressive sensing
title_full_unstemmed	Single channel speech enhancement using Wiener filter and compressive sensing
title_sort	single channel speech enhancement using wiener filter and compressive sensing
publisher	Institute of Advanced Engineering and Science
publishDate	2017
url	http://irep.iium.edu.my/57755/ http://irep.iium.edu.my/57755/ http://irep.iium.edu.my/57755/1/AmartSpeechEnhancement_7733-8387-1-Published.pdf http://irep.iium.edu.my/57755/7/57755_Single%20channel%20speech%20enhancement_scopus.pdf
first_indexed	2023-09-18T21:21:39Z
last_indexed	2023-09-18T21:21:39Z
_version_	1777411922007687168

Single channel speech enhancement using Wiener filter and compressive sensing

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