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Evaluation of sparsifying algorithms for speech signals

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.

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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.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 4119/28998
Uncontrolled Keywords: Sparsity , sparsity measures , speech compression
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Depositing User: Yusnizar Fuad
Date Deposited: 14 Feb 2013 08:36
Last Modified: 14 Feb 2013 08:36
URI: http://irep.iium.edu.my/id/eprint/28998

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