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.


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

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Published : 2016-02-04

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.

Andrew Nafalski
University of South Australia, School of Engineering, Australia  Australia
Aji Prasetya Wibawa 
Universitas Negeri Malang, Department of Electrical Engineering, Indonesia  Indonesia