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Weight-based Word Sense Disambiguation Method for Myanmar-to-English Language Translation

Aye Mya Nyein, May Zin Oo

Abstract


In many natural language processing (NLP) techniques, machine translation is a popular and useful technique. Machine translation technique is a translation process from one to another language. This technique is thus very useful for people around the world. While translating the languages, ambiguity is a big challenge because many words have several meanings. Ambiguous words have damaging effects on the precision of machine translation. To solve this problem, word sense disambiguation (WSD) method is useful for automatically identifying the correct meaning of an ambiguous word. In order to have a better precision, weight-based WSD method is proposed by taking advantage of a Minkowski distance method. As the proposed method considers the weight values of each sense of training and input vectors while observing the ambiguous words, it is more effective than the simple translation system. Experimental results show that the weight-based WSD method gives a better precision approximately 51% when compared to the simple machine translation method.


Keywords


Natural Language Processing; Word Sense Disambiguation; Machine Translation; Ambiguity

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References


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