Translation model of myanmar phrases for statistical machine translation

Authors:
Thet Thet Zin;Khin Mar Soe;Ni Lar Thein
Affiliations:
University of Computer Studies, Yangon, Myanmar;Natural Language Processing Laboratory, University of Computer Studies, Yangon, Myanmar;University of Computer Studies, Yangon, Myanmar
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

In this paper, we present a translation model which uses syntactic structure and morphology of Myanmar language to improve Myanmar to English machine translation system. This system is implemented as a subsystem of Myanmar to English translation system and based on statistical approach by using Myanmar-English Bilingual corpus. It also uses two types of information: language model and translation model. The source language model is based on N-gram method to extract phrases from segmented Myanmar sentences and the translation model is based on syntactic structure, morphology of Myanmar language and Bayes rule to reformulate the translation probability. Experimental results showed that the proposed system gets a BLEU-score improvement of more than 22.08% in comparison with baseline SMT system.