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Lexicon-based word recognition using support vector machine and hidden markov model

Hybrid of Neural Network (NN) and Hidden Markov Model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capability. However, NN does not guarantee good generalization due to Empirical Risk minimization (ERM) principle that it uses. In...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Ahmad, A. R., Viard-Gaudin, C., Khalid, M.
التنسيق: Book Section
منشور في: Institute of Electrical and Electronics Engineers 2009
الموضوعات:
TK Electrical engineering. Electronics Nuclear engineering
الوصول للمادة أونلاين:http://eprints.utm.my/id/eprint/12930/
http://dx.doi.org/10.1109/ICDAR.2009.248
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id my.utm.12930
record_format eprints
spelling my.utm.129302011-07-07T04:31:41Z http://eprints.utm.my/id/eprint/12930/ Lexicon-based word recognition using support vector machine and hidden markov model Ahmad, A. R. Viard-Gaudin, C. Khalid, M. TK Electrical engineering. Electronics Nuclear engineering Hybrid of Neural Network (NN) and Hidden Markov Model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capability. However, NN does not guarantee good generalization due to Empirical Risk minimization (ERM) principle that it uses. In our work, we focus on online word recognition using the support vector machine (SVM) for character recognition. SVM's use of structural risk minimization (SRM) principle has allowed simultaneous optimization of representational and discriminative capability of the character recognizer. We evaluated SVM in isolated character recognition environment using IRONOFF and UNIPEN character database. We then demonstrate the practical issues in using SVM within a hybrid setting with HMM for word recognition by testing the hybrid system on the IRONOFF word database and obtained commendable results. Institute of Electrical and Electronics Engineers 2009 Book Section PeerReviewed Ahmad, A. R. and Viard-Gaudin, C. and Khalid, M. (2009) Lexicon-based word recognition using support vector machine and hidden markov model. In: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR. Institute of Electrical and Electronics Engineers, New York, pp. 161-165. ISBN 978-076953725-2 http://dx.doi.org/10.1109/ICDAR.2009.248 doi:10.1109/ICDAR.2009.248
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/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ahmad, A. R.
Viard-Gaudin, C.
Khalid, M.
Lexicon-based word recognition using support vector machine and hidden markov model
description Hybrid of Neural Network (NN) and Hidden Markov Model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capability. However, NN does not guarantee good generalization due to Empirical Risk minimization (ERM) principle that it uses. In our work, we focus on online word recognition using the support vector machine (SVM) for character recognition. SVM's use of structural risk minimization (SRM) principle has allowed simultaneous optimization of representational and discriminative capability of the character recognizer. We evaluated SVM in isolated character recognition environment using IRONOFF and UNIPEN character database. We then demonstrate the practical issues in using SVM within a hybrid setting with HMM for word recognition by testing the hybrid system on the IRONOFF word database and obtained commendable results.
format Book Section
author Ahmad, A. R.
Viard-Gaudin, C.
Khalid, M.
author_facet Ahmad, A. R.
Viard-Gaudin, C.
Khalid, M.
author_sort Ahmad, A. R.
title Lexicon-based word recognition using support vector machine and hidden markov model
title_short Lexicon-based word recognition using support vector machine and hidden markov model
title_full Lexicon-based word recognition using support vector machine and hidden markov model
title_fullStr Lexicon-based word recognition using support vector machine and hidden markov model
title_full_unstemmed Lexicon-based word recognition using support vector machine and hidden markov model
title_sort lexicon-based word recognition using support vector machine and hidden markov model
publisher Institute of Electrical and Electronics Engineers
publishDate 2009
url http://eprints.utm.my/id/eprint/12930/
http://dx.doi.org/10.1109/ICDAR.2009.248
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score 13.250246

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