Improving Phrasebased Statistical Myanmar to English Machine Translation with Morphological Analysis

Abstract

This paper presents Myanmar phrases translation model with morphology analysis. The system is based on statistical approach. In statistical machine translation, large amount of information is needed to guide the translation process. When small amount of training data is available, morphological analysis is needed especially for morphology rich language. Myanmar language is inflected language and there are very few creations and researches of corpora in Myanmar, comparing to other language such as English, French, and Czech etc. Therefore, Myanmar phrases translation model is based on syntactic structure and morphology of Myanmar language. Bayes rule is also used to reformulate the translation probability of phrase pairs. Experiment results showed that proposed system can improve translation quality by applying morphological analysis on Myanmar language.