Evaluation of sparsifying algorithms for speech signals

Sparse representations of signals have been used in many areas of signal and image processing. It has also played an important role in compressive sensing algorithms since it performs well in sparse signals. A sparse representation is one in which small number of coefficients contain large proportio...

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Main Authors:	Kassim, Liban A., Khalifa, Othman Omran, Gunawan, Teddy Surya
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE Explore 2012
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://irep.iium.edu.my/28998/ http://irep.iium.edu.my/28998/ http://irep.iium.edu.my/28998/1/EVALUATION_OF_SPARSIFYING_ALGORITHMS_FOR_SPEECH_SIGNALS.pdf

id	iium-28998
recordtype	eprints
spelling	iium-289982013-02-14T00:36:57Z http://irep.iium.edu.my/28998/ Evaluation of sparsifying algorithms for speech signals Kassim, Liban A. Khalifa, Othman Omran Gunawan, Teddy Surya TA Engineering (General). Civil engineering (General) Sparse representations of signals have been used in many areas of signal and image processing. It has also played an important role in compressive sensing algorithms since it performs well in sparse signals. A sparse representation is one in which small number of coefficients contain large proportion of the energy. Sparsity is important also in speech compression and coding, where the signal can be compressed in pre-processing stages. It leads to efficient and robust methods for compression, detection denoising and signal separation. The objective of this paper is to evaluate several transforms which is used to sparsify the speech signals. Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) will be compared and evaluated based on Gini Index. Sparsity properties and measures will be reviewed in this paper. Finally, sparse applications in speech compression and compressive sensing will be discussed. IEEE Explore 2012 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/28998/1/EVALUATION_OF_SPARSIFYING_ALGORITHMS_FOR_SPEECH_SIGNALS.pdf Kassim, Liban A. and Khalifa, Othman Omran and Gunawan, Teddy Surya (2012) Evaluation of sparsifying algorithms for speech signals. In: International Conference on Computer and Communication Engineering (ICCCE 2012), 3-5 July 2012, Seri Pacific Hotel Kuala Lumpur. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6271202&tag=1
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Kassim, Liban A. Khalifa, Othman Omran Gunawan, Teddy Surya Evaluation of sparsifying algorithms for speech signals
description	Sparse representations of signals have been used in many areas of signal and image processing. It has also played an important role in compressive sensing algorithms since it performs well in sparse signals. A sparse representation is one in which small number of coefficients contain large proportion of the energy. Sparsity is important also in speech compression and coding, where the signal can be compressed in pre-processing stages. It leads to efficient and robust methods for compression, detection denoising and signal separation. The objective of this paper is to evaluate several transforms which is used to sparsify the speech signals. Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) will be compared and evaluated based on Gini Index. Sparsity properties and measures will be reviewed in this paper. Finally, sparse applications in speech compression and compressive sensing will be discussed.
format	Conference or Workshop Item
author	Kassim, Liban A. Khalifa, Othman Omran Gunawan, Teddy Surya
author_facet	Kassim, Liban A. Khalifa, Othman Omran Gunawan, Teddy Surya
author_sort	Kassim, Liban A.
title	Evaluation of sparsifying algorithms for speech signals
title_short	Evaluation of sparsifying algorithms for speech signals
title_full	Evaluation of sparsifying algorithms for speech signals
title_fullStr	Evaluation of sparsifying algorithms for speech signals
title_full_unstemmed	Evaluation of sparsifying algorithms for speech signals
title_sort	evaluation of sparsifying algorithms for speech signals
publisher	IEEE Explore
publishDate	2012
url	http://irep.iium.edu.my/28998/ http://irep.iium.edu.my/28998/ http://irep.iium.edu.my/28998/1/EVALUATION_OF_SPARSIFYING_ALGORITHMS_FOR_SPEECH_SIGNALS.pdf
first_indexed	2018-09-07T05:09:25Z
last_indexed	2018-09-07T05:09:25Z
_version_	1610924126758764544

Evaluation of sparsifying algorithms for speech signals

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