COMPARATIVE STUDY OF CLASSIFICATION METHODS USED FOR IDENTIFYING VIETNAMESE – ENGLISH – FRENCH

  • Le Trung Hieu Hung Yen University of Technology and Education
  • Pham Quoc Hung Hung Yen University of Technology and Education
  • Nguyen Vinh Quy Hung Yen University of Technology and Education
  • Chu Ba Thanh Hung Yen University of Technology and Education
Keywords: Language Identification; Vietnamese; English; French; SVM; SMO; Weka.

Abstract

There are many different methods and models which researched and applied for identification of languages such as GMM, HMM, SVM, ANN models, etc. The article presents test results identify three languages Vietnamese, English, French which use SMO (Sequential Minimal Optimization), iBK, Multilayer Perceptron classifier of Weka with features was extracted by OpenSMILE, the number of features are 384 coefficient. The test results with SMO classifiers show out the highest Vietnamese recognition rate was 98.75%, the highest French recognition was 93,5% when used Multilayer Perceptron classifier and SMO classifier and the highest English recognition was 94,75% with Multilayer Perceptron classifier.

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Published
2017-10-11
How to Cite
Le Trung Hieu, Pham Quoc Hung, Nguyen Vinh Quy, & Chu Ba Thanh. (2017). COMPARATIVE STUDY OF CLASSIFICATION METHODS USED FOR IDENTIFYING VIETNAMESE – ENGLISH – FRENCH. UTEHY Journal of Science and Technology, 15, 43-48. Retrieved from http://tapchi.utehy.edu.vn/index.php/jst/article/view/162