Support vector machines for Thai phoneme recognition

被引：0
|
作者：
Thubthong, Nuttakorn [1 ]
Kijsirikul, Boonserm [1 ]
机构：
[1] Mach. Intell. Knowledge Discov. Lab., Department of Computer Engineering, Chulalongkorn University, Bangkok, 10330, Thailand
来源：
International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems | 2001年 / 9卷 / 06期
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摘要：
The Support Vector Machine (SVM) has recently been introduced as a new pattern classification technique. It learns the boundary regions between samples belonging to two classes by mapping the input samples into a high dimensional space, and seeking a separating hyperplane in this space. This paper describes an application of SVMs to two phoneme recognition problems: 5 Thai tones, and 12 Thai vowels spoken in isolation. The best results on tone recognition are 96.09% and 90.57% for the inside test and outside test, respectively, and on vowel recognition are 95.51% and 87.08% for the inside test and outside test, respectively.
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页码：803 / 813
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