Speaker recognition using adaptively boosted decision tree classifier

Speaker recognition using adaptively boosted decision tree classifier

In this paper, a novel approach for speaker recognition is proposed. The approach makes use of adaptive boosting (AdaBoost) and C4.5 decision trees for closed set, text-dependent speaker recognition. A subset of 20 speakers, 10 male and 10 female, drawn from the YOHO speaker verification corpus is...

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Main Authors: Foo, Say Wei, Lim, Eng Guan
Other Authors: IEEE International Conference on Acoustics, Speech and Signal Processing (2002 : Orlando, Florida, US)
Format: Conference or Workshop Item
Language:English
Published: 2009
Online Access:https://hdl.handle.net/10356/79870
http://hdl.handle.net/10220/4615
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-798702019-12-06T13:35:46Z Speaker recognition using adaptively boosted decision tree classifier Foo, Say Wei Lim, Eng Guan IEEE International Conference on Acoustics, Speech and Signal Processing (2002 : Orlando, Florida, US) In this paper, a novel approach for speaker recognition is proposed. The approach makes use of adaptive boosting (AdaBoost) and C4.5 decision trees for closed set, text-dependent speaker recognition. A subset of 20 speakers, 10 male and 10 female, drawn from the YOHO speaker verification corpus is used to assess the performance of the system. Results reveal that an accuracy of 99.5% of speaker identification may be achieved. Published version 2009-05-25T03:17:31Z 2019-12-06T13:35:46Z 2009-05-25T03:17:31Z 2019-12-06T13:35:46Z 2002 2002 Conference Paper Foo, S. W., & Lim, E. G. (2002). Speaker recognition using adaptively boosted decision tree classifier. IEEE International Conference on Acoustics, Speech and Signal Processing 2002. (pp. 157-160). https://hdl.handle.net/10356/79870 http://hdl.handle.net/10220/4615 en IEEE International Conference on Acoustics, Speech and Signal Processing. Journal can be found at http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=7874 4 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
description In this paper, a novel approach for speaker recognition is proposed. The approach makes use of adaptive boosting (AdaBoost) and C4.5 decision trees for closed set, text-dependent speaker recognition. A subset of 20 speakers, 10 male and 10 female, drawn from the YOHO speaker verification corpus is used to assess the performance of the system. Results reveal that an accuracy of 99.5% of speaker identification may be achieved.
author2 IEEE International Conference on Acoustics, Speech and Signal Processing (2002 : Orlando, Florida, US)
author_facet IEEE International Conference on Acoustics, Speech and Signal Processing (2002 : Orlando, Florida, US)
Foo, Say Wei
Lim, Eng Guan
format Conference or Workshop Item
author Foo, Say Wei
Lim, Eng Guan
spellingShingle Foo, Say Wei
Lim, Eng Guan
Speaker recognition using adaptively boosted decision tree classifier
author_sort Foo, Say Wei
title Speaker recognition using adaptively boosted decision tree classifier
title_short Speaker recognition using adaptively boosted decision tree classifier
title_full Speaker recognition using adaptively boosted decision tree classifier
title_fullStr Speaker recognition using adaptively boosted decision tree classifier
title_full_unstemmed Speaker recognition using adaptively boosted decision tree classifier
title_sort speaker recognition using adaptively boosted decision tree classifier
publishDate 2009
url https://hdl.handle.net/10356/79870
http://hdl.handle.net/10220/4615
_version_ 1681037684759330816

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