MACHINE TRANSLATION WITH JAVANESE SPEECH LEVELS’ CLASSIFICATION

Andrew Nafalski

nafalski@unisa.edu.au
University of South Australia, School of Engineering, Australia (Australia)

Aji Prasetya Wibawa


Universitas Negeri Malang, Department of Electrical Engineering, Indonesia (Indonesia)

Abstract

A hybrid corpus-based machine processing has been developed to produce a proper Javanese speech level translation. The developed statistical memory-based machine translation shows significantly accurate results. Integration of an automatic text classifier and an expert system is proposed to help Javanese in classifying the speech levels used for a specific interlocutor. Javanese rule-based expert system is designed while naive Bayes classifier is selected after outperforming simple logic probability approach. As a result, the average of translation accuracy (72.3%) indicates that the integrated intelligent interfaces could effectively solve the Javanese language pragmatic translation problems.


Keywords:

expert system, hybrid corpus-based machine translation, Javanese speech levels, text classifier

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Published
2016-02-04

Cited by

Nafalski, A., & Wibawa, A. P. . (2016). MACHINE TRANSLATION WITH JAVANESE SPEECH LEVELS’ CLASSIFICATION. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 6(1), 21–25. https://doi.org/10.5604/20830157.1194260

Authors

Andrew Nafalski 
nafalski@unisa.edu.au
University of South Australia, School of Engineering, Australia Australia

Authors

Aji Prasetya Wibawa 

Universitas Negeri Malang, Department of Electrical Engineering, Indonesia Indonesia

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