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Speech compression using compressive sensing on a multicore system

Gunawan, Teddy Surya and Khalifa, Othman Omran and Shafie, Amir Akramin and Ambikairajah, Eliathamby (2011) Speech compression using compressive sensing on a multicore system. In: 4th International Conference on Mechatronics (ICOM 2011), 17-19 May, 2011, Kuala Lumpur, Malaysia.

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Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals, i.e. speech signal. Compressive sensing is a new paradigm of acquiring signals, fundamentally different from uniform rate digitization followed by compression, often used for transmission or storage. In this paper, a novel algorithm for speech coding utilizing CS principle is developed. The sparsity of speech signals is exploited using gammatone filterbank and Discrete Cosine Transform (DCT) in which the compressive sensing principle is then applied to the sparse subband signals. All parameters will be optimized using informal listening test and Perceptual Evaluation of Speech Quality (PESQ). In order to further reduce the bit requirement, vector quantization using codebook of the training signals will be added to the system. The performance of overall algorithms will be evaluated based on the processing time and speech quality. Finally, to speed up the process, the proposed algorithm will be implemented in a multicore system, i.e. six cores, using Single Program Multiple Data (SPMD) parallel paradigm.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 5588/2313
Uncontrolled Keywords: Compressive sensing, speech coding, PESQ, listening test, multicore system, SPMD
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Prof. Dr. Teddy Surya Gunawan
Date Deposited: 20 Sep 2011 16:05
Last Modified: 10 May 2012 08:06
URI: http://irep.iium.edu.my/id/eprint/2313

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