Myanmar to English verb translation disambiguation approach based on Naïve Bayesian classifier

Natural Language processing (NLP) is a field of computer science and linguistics concerned with the interactions between computers and human (natural) languages. Ambiguity is one of these problems which have been a great challenge for computational linguists. This paper concentrates on the problem of target word selection in Myanmar to English machine translation, for which the approach is directly applicable. However this system can only solve the ambiguities of verbs in Myanmar-English translations. This paper presents a corpus-based approach to word sense disambiguation that builds an ensemble of Naïve Bayesian classifiers, each of which based on lexical features. Moreover nouns are detail classified in our system. In this paper, we propose a framework to solve ambiguous verb problems. Our system will support to improve the accuracy of the Myanmar to English translation.