System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh

This thesis will show how the voice recognition technique can be combined with template matching technique (Vector Quantization) to validate a login process. This system will be divided into two modules; Enrollment and Verification During the Enrollment process,the person offers a 'live sample&...

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Main Author: Metrius, Benedict Sunggoh
Format: Thesis
Published: 2003
Subjects:
Online Access:http://studentsrepo.um.edu.my/9130/
http://studentsrepo.um.edu.my/9130/1/System_login_authentication_using_voice_recogniyion.pdf
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author Metrius, Benedict Sunggoh
author_facet Metrius, Benedict Sunggoh
author_sort Metrius, Benedict Sunggoh
building UM Research Repository
collection Online Access
description This thesis will show how the voice recognition technique can be combined with template matching technique (Vector Quantization) to validate a login process. This system will be divided into two modules; Enrollment and Verification During the Enrollment process,the person offers a 'live sample' of his/her voice.The feature of this voice will be extracted using MFCC technique which involves Frame Blocking, Windowing, Fast Fourier Transform, Mel-frequency Wrapping and Cepstrum. The feature extracted by the MFCC will be processed and stored as codebooks. A codebook is created for each user. To confirm the identity at a future time, the individual will present the 'live sample', which will be matched against the stored template (codebook). Vector Quantization technique will be used to compare the codebook and the feature from the voice provided by the user during login session.
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format Thesis
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institution University Malaya
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spelling um-91302018-11-14T17:41:36Z System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh Metrius, Benedict Sunggoh T Technology (General) This thesis will show how the voice recognition technique can be combined with template matching technique (Vector Quantization) to validate a login process. This system will be divided into two modules; Enrollment and Verification During the Enrollment process,the person offers a 'live sample' of his/her voice.The feature of this voice will be extracted using MFCC technique which involves Frame Blocking, Windowing, Fast Fourier Transform, Mel-frequency Wrapping and Cepstrum. The feature extracted by the MFCC will be processed and stored as codebooks. A codebook is created for each user. To confirm the identity at a future time, the individual will present the 'live sample', which will be matched against the stored template (codebook). Vector Quantization technique will be used to compare the codebook and the feature from the voice provided by the user during login session. 2003 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/9130/1/System_login_authentication_using_voice_recogniyion.pdf Metrius, Benedict Sunggoh (2003) System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh. Undergraduates thesis, University of Malaya. http://studentsrepo.um.edu.my/9130/
spellingShingle T Technology (General)
Metrius, Benedict Sunggoh
System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh
title System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh
title_full System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh
title_fullStr System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh
title_full_unstemmed System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh
title_short System login authentication using voice recognition and ai methods / Metrius Benedict Sunggoh
title_sort system login authentication using voice recognition and ai methods / metrius benedict sunggoh
topic T Technology (General)
url http://studentsrepo.um.edu.my/9130/
http://studentsrepo.um.edu.my/9130/1/System_login_authentication_using_voice_recogniyion.pdf