Thai monosyllabic words recognition using ant-miner algorithm
Joint Authors
Predawan, Saritchai
Kimpan, Chom
Wutiwiwatchai, Chai
Source
The International Arab Journal of Information Technology
Issue
Vol. 10, Issue 4 (31 Jul. 2013)8 p.
Publisher
Publication Date
2013-07-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Topics
Abstract EN
in this paper, unti-Miner software is used to develop classification rules for Thai monosyllabic words.
The hypothetical words used in this paper are composed of 65 command monosyllabic Thai words.
The binary desired outputs were used during training 520 Thai words consist of 10 numerals and single-syllable, 65 words in each group were used for system evaluation.
In order to improve recognition accuracy, initial consonants, vowels, final consonants and tonal level detected were conducted for speech preclassification.
The parameters used in the metaheuritstic algorithms are optimized using pruning algorithm with the aim of improving the accuracy by generating minimum number of rule in order to cover more patterns.
Thai monosyllabic words recognition using Ant-Miner yielded Thai monosysllabic words accuracy of recognition on test set of 88.65 %, 87.69 % and 91.54 % for 50, 100 and 250 number of ants respectively.
American Psychological Association (APA)
Predawan, Saritchai& Kimpan, Chom& Wutiwiwatchai, Chai. 2013. Thai monosyllabic words recognition using ant-miner algorithm. The International Arab Journal of Information Technology،Vol. 10, no. 4.
https://search.emarefa.net/detail/BIM-311884
Modern Language Association (MLA)
Predawan, Saritchai…[et al.]. Thai monosyllabic words recognition using ant-miner algorithm. The International Arab Journal of Information Technology Vol. 10, no. 4 (Jul. 2013).
https://search.emarefa.net/detail/BIM-311884
American Medical Association (AMA)
Predawan, Saritchai& Kimpan, Chom& Wutiwiwatchai, Chai. Thai monosyllabic words recognition using ant-miner algorithm. The International Arab Journal of Information Technology. 2013. Vol. 10, no. 4.
https://search.emarefa.net/detail/BIM-311884
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references.
Record ID
BIM-311884