SUPPORT VECTOR MACHINES FOR THAI PHONEME RECOGNITION
2001 ◽
Vol 09
(06)
◽
pp. 803-813
◽
Keyword(s):
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.
2003 ◽
Vol 7
(1)
◽
pp. 19-24
◽
2011 ◽
Vol 204-210
◽
pp. 879-882
Keyword(s):
2018 ◽
Vol 265
(3)
◽
pp. 993-1004
◽
2008 ◽
pp. 1277-1282
2020 ◽
Vol 16
(10)
◽
pp. 155014772096383