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Development of a real-time speaker recognition system using TMS320C31

Speaker recognition systems based on Malay language have been developed in the personal computer environment. This thesis outlines a hardware implementation of a real-time speaker recognition using Malay language. Various speaker recognition classifiers have been investigated in term of feasibility...

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Main Author:	Sowndappan, Prakash
Format:	Thesis
Language:	English
Published:	2006
Subjects:	TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science
Online Access:	http://eprints.utm.my/id/eprint/5339/1/PrakashSowndappanMFKE2006.pdf http://eprints.utm.my/id/eprint/5339/
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id	my.utm.5339
record_format	eprints
spelling	my.utm.53392018-03-07T20:57:42Z http://eprints.utm.my/id/eprint/5339/ Development of a real-time speaker recognition system using TMS320C31 Sowndappan, Prakash TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science Speaker recognition systems based on Malay language have been developed in the personal computer environment. This thesis outlines a hardware implementation of a real-time speaker recognition using Malay language. Various speaker recognition classifiers have been investigated in term of feasibility in a stand-alone hardware platform. Computational and memory requirement are given consideration, along with processing optimizations. A speaker recognition board is implemented based on a TMS32C31 digital signal processor (DSP). The speaker recognition techniques used are the Linear Predictive Coding (LPC) Cepstral analysis for feature extraction, Vector Quantization (VQ) for feature compression and the Dynamic Time Warping (DTW) for speaker feature matching. This system is trained and tested using a population of ten users, with additional testing using ten impostors. The average entry success of a true user is 93.4%. The speaker recognition board is successfully tested as a speaker recognition door access system, with true access success rate of 88.7%. The speaker recognition system shows good performance, as well as being operational in real-time. 2006-03 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/5339/1/PrakashSowndappanMFKE2006.pdf Sowndappan, Prakash (2006) Development of a real-time speaker recognition system using TMS320C31. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering QA75 Electronic computers. Computer science Sowndappan, Prakash Development of a real-time speaker recognition system using TMS320C31
description	Speaker recognition systems based on Malay language have been developed in the personal computer environment. This thesis outlines a hardware implementation of a real-time speaker recognition using Malay language. Various speaker recognition classifiers have been investigated in term of feasibility in a stand-alone hardware platform. Computational and memory requirement are given consideration, along with processing optimizations. A speaker recognition board is implemented based on a TMS32C31 digital signal processor (DSP). The speaker recognition techniques used are the Linear Predictive Coding (LPC) Cepstral analysis for feature extraction, Vector Quantization (VQ) for feature compression and the Dynamic Time Warping (DTW) for speaker feature matching. This system is trained and tested using a population of ten users, with additional testing using ten impostors. The average entry success of a true user is 93.4%. The speaker recognition board is successfully tested as a speaker recognition door access system, with true access success rate of 88.7%. The speaker recognition system shows good performance, as well as being operational in real-time.
format	Thesis
author	Sowndappan, Prakash
author_facet	Sowndappan, Prakash
author_sort	Sowndappan, Prakash
title	Development of a real-time speaker recognition system using TMS320C31
title_short	Development of a real-time speaker recognition system using TMS320C31
title_full	Development of a real-time speaker recognition system using TMS320C31
title_fullStr	Development of a real-time speaker recognition system using TMS320C31
title_full_unstemmed	Development of a real-time speaker recognition system using TMS320C31
title_sort	development of a real-time speaker recognition system using tms320c31
publishDate	2006
url	http://eprints.utm.my/id/eprint/5339/1/PrakashSowndappanMFKE2006.pdf http://eprints.utm.my/id/eprint/5339/
_version_	1643644297301458944
score	13.211869

Development of a real-time speaker recognition system using TMS320C31

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