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FPGA implementation for GMM-based speaker identification

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Main Authors: EhKan, Phaklen, Allen, Timothy, Quigley, Steven F.
Other Authors: plen07@yahoo.co.uk
Format: Article
Language:English
Published: Hindawi Publishing Corporation 2011
Subjects:
Field Programmable Gate Array (FPGA)
Gaussian Mixture Model (GMM)
Personal identification systems
Biometric-based speaker identification
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/11509
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spelling my.unimap-115092011-06-09T08:00:26Z FPGA implementation for GMM-based speaker identification EhKan, Phaklen Allen, Timothy Quigley, Steven F. plen07@yahoo.co.uk Field Programmable Gate Array (FPGA) Gaussian Mixture Model (GMM) Personal identification systems Biometric-based speaker identification Link to publisher's homepage at http://www.hindawi.com/ In today's society, highly accurate personal identification systems are required. Passwords or pin numbers can be forgotten or forged and are no longer considered to offer a high level of security. The use of biological features, biometrics, is becoming widely accepted as the next level for security systems. Biometric-based speaker identification is a method of identifying persons from their voice. Speaker-specific characteristics exist in speech signals due to different speakers having different resonances of the vocal tract. These differences can be exploited by extracting feature vectors such as Mel-Frequency Cepstral Coefficients (MFCCs) from the speech signal. A well-known statistical modelling process, the Gaussian Mixture Model (GMM), then models the distribution of each speaker's MFCCs in a multidimensional acoustic space. The GMM-based speaker identification system has features that make it promising for hardware acceleration. This paper describes the hardware implementation for classification of a text-independent GMM-based speaker identification system. The aim was to produce a system that can perform simultaneous identification of large numbers of voice streams in real time. This has important potential applications in security and in automated call centre applications. A speedup factor of ninety was achieved compared to a software implementation on a standard PC. 2011-04-05T03:31:42Z 2011-04-05T03:31:42Z 2011 Article International Journal of Reconfigurable Computing, vol. 2011, 2011, pages 1-8 1687-7195 http://www.hindawi.com/journals/ijrc/2011/420369/ http://hdl.handle.net/123456789/11509 en Hindawi Publishing Corporation
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Field Programmable Gate Array (FPGA)
Gaussian Mixture Model (GMM)
Personal identification systems
Biometric-based speaker identification
spellingShingle Field Programmable Gate Array (FPGA)
Gaussian Mixture Model (GMM)
Personal identification systems
Biometric-based speaker identification
EhKan, Phaklen
Allen, Timothy
Quigley, Steven F.
FPGA implementation for GMM-based speaker identification
description Link to publisher's homepage at http://www.hindawi.com/
author2 plen07@yahoo.co.uk
author_facet plen07@yahoo.co.uk
EhKan, Phaklen
Allen, Timothy
Quigley, Steven F.
format Article
author EhKan, Phaklen
Allen, Timothy
Quigley, Steven F.
author_sort EhKan, Phaklen
title FPGA implementation for GMM-based speaker identification
title_short FPGA implementation for GMM-based speaker identification
title_full FPGA implementation for GMM-based speaker identification
title_fullStr FPGA implementation for GMM-based speaker identification
title_full_unstemmed FPGA implementation for GMM-based speaker identification
title_sort fpga implementation for gmm-based speaker identification
publisher Hindawi Publishing Corporation
publishDate 2011
url http://dspace.unimap.edu.my/xmlui/handle/123456789/11509
_version_ 1643790184780660736
score 13.222552

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