Adaptive cancellation of localised environmental noise

Noise cancellation systems are useful in applications such as speech and speaker recognition systems where the effects of environmental noise have to be taken into considerations. A robust method for the cancellation of localised noise in noisy speech signals using subband decomposition and adaptive...

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Main Authors: Abid Noor, Ali O., Al-Hussaini, Imad H.M., Salina Abdul Samad
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2018
Online Access:http://journalarticle.ukm.my/13793/1/7.pdf
http://journalarticle.ukm.my/13793/
http://www.ukm.my/jkukm/volume-302-2018/
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Institution: Universiti Kebangsaan Malaysia
Language: English
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spelling my-ukm.journal.137932019-12-19T23:47:25Z http://journalarticle.ukm.my/13793/ Adaptive cancellation of localised environmental noise Abid Noor, Ali O. Al-Hussaini, Imad H.M. Salina Abdul Samad, Noise cancellation systems are useful in applications such as speech and speaker recognition systems where the effects of environmental noise have to be taken into considerations. A robust method for the cancellation of localised noise in noisy speech signals using subband decomposition and adaptive filtering is presented and described in this paper. The subband decomposition technique is based on low complexity octave filters that split the noisy speech input into subsidiary bands. A thresholding technique is then applied to the subbands to determine the presence or absence of environmental noise. This is used to control an adaptive filter which only responds to the noisy parts of the speech spectrum hence localising the adaptation process only on these segments. The Normalised Least Mean Squares algorithm (NLMS) is used for the adaptation process. A comparison with a similar system without localising the environmental noise shows the superior performance of the proposed system. It has been shown to perform better in terms of computational costs and convergence rate when compared to a system that does not take advantage of the information regarding the presence or absence of noise in a specific part of the speech spectrum. More than 35 dB of noise has been eliminated in less iterations than in conventional approach which needs longer time to reach steady state. Penerbit Universiti Kebangsaan Malaysia 2018-10 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/13793/1/7.pdf Abid Noor, Ali O. and Al-Hussaini, Imad H.M. and Salina Abdul Samad, (2018) Adaptive cancellation of localised environmental noise. Jurnal Kejuruteraan, 30 (2). pp. 179-186. ISSN 0128-0198 http://www.ukm.my/jkukm/volume-302-2018/
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Noise cancellation systems are useful in applications such as speech and speaker recognition systems where the effects of environmental noise have to be taken into considerations. A robust method for the cancellation of localised noise in noisy speech signals using subband decomposition and adaptive filtering is presented and described in this paper. The subband decomposition technique is based on low complexity octave filters that split the noisy speech input into subsidiary bands. A thresholding technique is then applied to the subbands to determine the presence or absence of environmental noise. This is used to control an adaptive filter which only responds to the noisy parts of the speech spectrum hence localising the adaptation process only on these segments. The Normalised Least Mean Squares algorithm (NLMS) is used for the adaptation process. A comparison with a similar system without localising the environmental noise shows the superior performance of the proposed system. It has been shown to perform better in terms of computational costs and convergence rate when compared to a system that does not take advantage of the information regarding the presence or absence of noise in a specific part of the speech spectrum. More than 35 dB of noise has been eliminated in less iterations than in conventional approach which needs longer time to reach steady state.
format Article
author Abid Noor, Ali O.
Al-Hussaini, Imad H.M.
Salina Abdul Samad,
spellingShingle Abid Noor, Ali O.
Al-Hussaini, Imad H.M.
Salina Abdul Samad,
Adaptive cancellation of localised environmental noise
author_facet Abid Noor, Ali O.
Al-Hussaini, Imad H.M.
Salina Abdul Samad,
author_sort Abid Noor, Ali O.
title Adaptive cancellation of localised environmental noise
title_short Adaptive cancellation of localised environmental noise
title_full Adaptive cancellation of localised environmental noise
title_fullStr Adaptive cancellation of localised environmental noise
title_full_unstemmed Adaptive cancellation of localised environmental noise
title_sort adaptive cancellation of localised environmental noise
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2018
url http://journalarticle.ukm.my/13793/1/7.pdf
http://journalarticle.ukm.my/13793/
http://www.ukm.my/jkukm/volume-302-2018/
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