MACHINE TRANSLATION WITH JAVANESE SPEECH LEVELS’ CLASSIFICATION
Andrew Nafalski
nafalski@unisa.edu.auUniversity 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 classifierReferences
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Authors
Andrew Nafalskinafalski@unisa.edu.au
University of South Australia, School of Engineering, Australia Australia
Authors
Aji Prasetya WibawaUniversitas Negeri Malang, Department of Electrical Engineering, Indonesia Indonesia
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