Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment

Some of the teething problems associated in the use of two-sensor noise cancellation systems are the nature of the noise signals—a problem that imposes the use of highly complex algorithms in reducing the noise. The usage of such methods can be impractical for many real time applications, where spee...

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Main Authors:	Roshahliza, M. Ramli, Noor, Ali O. Abid, Salina, Abdul Samad
Format:	Article
Language:	English
Published:	Springer 2017
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/17928/ http://umpir.ump.edu.my/id/eprint/17928/ http://umpir.ump.edu.my/id/eprint/17928/ http://umpir.ump.edu.my/id/eprint/17928/1/ftech-2017-rosha-noise%20cancellation.pdf

id	ump-17928
recordtype	eprints
spelling	ump-179282018-05-22T06:23:35Z http://umpir.ump.edu.my/id/eprint/17928/ Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment Roshahliza, M. Ramli Noor, Ali O. Abid Salina, Abdul Samad TK Electrical engineering. Electronics Nuclear engineering Some of the teething problems associated in the use of two-sensor noise cancellation systems are the nature of the noise signals—a problem that imposes the use of highly complex algorithms in reducing the noise. The usage of such methods can be impractical for many real time applications, where speed of convergence and processing time are critical. At the same time, the existing approaches are based on using a single, often complex adaptive filter to minimize noise, which has been determined to be inadequate and ineffective. In this paper, a new mechanism is proposed to reduce background noise from speech communications. The procedure is based on a two-sensor adaptive noise canceller that is capable of assigning an appropriate filter adapting to properties of the noise. The criterion to achieve this is based on measuring the eigenvalue spread based on the autocorrelation of the input noise. The proposed noise canceller (INC) applies an adaptive algorithm according to the characteristics of the input signal. Various experiments based on this technique using real-world signals are conducted to gauge the effectiveness of the approach. Initial results illustrated the system capabilities in executing noise cancellation under different types of environmental noise. The results based on the INC technique indicate fast convergence rates; improvements up to 30 dB in signal-to-noise ratio and at the same time shows 65% reduction of computational power compared to conventional method. Springer 2017 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/17928/1/ftech-2017-rosha-noise%20cancellation.pdf Roshahliza, M. Ramli and Noor, Ali O. Abid and Salina, Abdul Samad (2017) Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment. International Journal of Speech Technology, 20 (3). pp. 535-542. ISSN 1572-8110 http://dx.doi.org/10.1007/s10772-017-9425-1 doi: 10.1007/s10772-017-9425-1
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Roshahliza, M. Ramli Noor, Ali O. Abid Salina, Abdul Samad Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment
description	Some of the teething problems associated in the use of two-sensor noise cancellation systems are the nature of the noise signals—a problem that imposes the use of highly complex algorithms in reducing the noise. The usage of such methods can be impractical for many real time applications, where speed of convergence and processing time are critical. At the same time, the existing approaches are based on using a single, often complex adaptive filter to minimize noise, which has been determined to be inadequate and ineffective. In this paper, a new mechanism is proposed to reduce background noise from speech communications. The procedure is based on a two-sensor adaptive noise canceller that is capable of assigning an appropriate filter adapting to properties of the noise. The criterion to achieve this is based on measuring the eigenvalue spread based on the autocorrelation of the input noise. The proposed noise canceller (INC) applies an adaptive algorithm according to the characteristics of the input signal. Various experiments based on this technique using real-world signals are conducted to gauge the effectiveness of the approach. Initial results illustrated the system capabilities in executing noise cancellation under different types of environmental noise. The results based on the INC technique indicate fast convergence rates; improvements up to 30 dB in signal-to-noise ratio and at the same time shows 65% reduction of computational power compared to conventional method.
format	Article
author	Roshahliza, M. Ramli Noor, Ali O. Abid Salina, Abdul Samad
author_facet	Roshahliza, M. Ramli Noor, Ali O. Abid Salina, Abdul Samad
author_sort	Roshahliza, M. Ramli
title	Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment
title_short	Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment
title_full	Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment
title_fullStr	Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment
title_full_unstemmed	Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment
title_sort	noise cancellation using selectable adaptive algorithm for speech in variable noise environment
publisher	Springer
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/17928/ http://umpir.ump.edu.my/id/eprint/17928/ http://umpir.ump.edu.my/id/eprint/17928/ http://umpir.ump.edu.my/id/eprint/17928/1/ftech-2017-rosha-noise%20cancellation.pdf
first_indexed	2023-09-18T22:25:04Z
last_indexed	2023-09-18T22:25:04Z
_version_	1777415911136821248

Noise Cancellation using Selectable Adaptive Algorithm for Speech in Variable Noise Environment

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