Mobile phone speaker recognition

Today in a society with well-developed technology, a high penetration rate of mobile devices clearly illustrated how well-woven our portable phones are, into our lives. Therefore, security and privacy is a growing issue. To solve this, biometric systems such as speaker recognition can be used to inc...

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Main Author: Thang, Hui Ru.
Other Authors: Chng Eng Siong
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/55031
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-550312023-03-03T20:53:41Z Mobile phone speaker recognition Thang, Hui Ru. Chng Eng Siong School of Computer Engineering DRNTU::Engineering::Computer science and engineering Today in a society with well-developed technology, a high penetration rate of mobile devices clearly illustrated how well-woven our portable phones are, into our lives. Therefore, security and privacy is a growing issue. To solve this, biometric systems such as speaker recognition can be used to increase protection level and security. The purpose of this project is to implement a speaker recognition system in Android platform, on S3. The system should allow users to record his speech utterance, extract MFCC features and test it against the speaker’s model. If the utterance is from the speaker, the system should accept it and reject if otherwise. Server-client architecture is used, where UBM is trained at server side and preloaded into android devices (client) in order to perform the verification task. Experimental results showed peak performance when 256 GMM was used. Above that, the problem of over-fitting occurs. More training data can be supplied and experiments can be extended to out-of set testing. Future enhancement includes storing the UBM online in a database to avoid manual transfer of UBM when large number of clients is used. The current verification system can also act as a baseline system and be compared with other systems created in the future, such as iVector and GMM-SVM. Bachelor of Engineering (Computer Science) 2013-12-04T01:38:44Z 2013-12-04T01:38:44Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/55031 en Nanyang Technological University 54 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Thang, Hui Ru.
Mobile phone speaker recognition
description Today in a society with well-developed technology, a high penetration rate of mobile devices clearly illustrated how well-woven our portable phones are, into our lives. Therefore, security and privacy is a growing issue. To solve this, biometric systems such as speaker recognition can be used to increase protection level and security. The purpose of this project is to implement a speaker recognition system in Android platform, on S3. The system should allow users to record his speech utterance, extract MFCC features and test it against the speaker’s model. If the utterance is from the speaker, the system should accept it and reject if otherwise. Server-client architecture is used, where UBM is trained at server side and preloaded into android devices (client) in order to perform the verification task. Experimental results showed peak performance when 256 GMM was used. Above that, the problem of over-fitting occurs. More training data can be supplied and experiments can be extended to out-of set testing. Future enhancement includes storing the UBM online in a database to avoid manual transfer of UBM when large number of clients is used. The current verification system can also act as a baseline system and be compared with other systems created in the future, such as iVector and GMM-SVM.
author2 Chng Eng Siong
author_facet Chng Eng Siong
Thang, Hui Ru.
format Final Year Project
author Thang, Hui Ru.
author_sort Thang, Hui Ru.
title Mobile phone speaker recognition
title_short Mobile phone speaker recognition
title_full Mobile phone speaker recognition
title_fullStr Mobile phone speaker recognition
title_full_unstemmed Mobile phone speaker recognition
title_sort mobile phone speaker recognition
publishDate 2013
url http://hdl.handle.net/10356/55031
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