NDLI: Word sense disambiguation system for Myanmar word in support of Myanmar-English machine translation

Content Provider	IEEE Xplore Digital Library
Author	Nyein Thwet Thwet Aung Ni Lar Thein
Copyright Year	2011
Description	Author affiliation: University of Computer Studies, Yangon, Myanmar (Nyein Thwet Thwet Aung; Ni Lar Thein)
Abstract	Word Sense Disambiguation (WSD) has always been a key problem in Natural Language Processing. WSD is defined as the task of finding the correct sense of a word in a specific context. It is an intermediate task essential to many natural language processing problems, including machine translation, information retrieval and speech processing. There is not any cited work for resolving ambiguity of words in Myanmar language. In this paper, we propose an approach to solve the ambiguity of Myanmar words for Myanmar-English machine translation. Our approach is based on Nearest Neighbor Cosine classifier to disambiguate ambiguous words with part-of-speech ‘noun’ and ‘verb’, which uses topical feature that represent co-occurring words in bag-of-word feature. The system uses Myanmar-English parallel corpus as training data. The proposed system can improve the translation accuracy for Myanmar-English machine translation system.
Starting Page	2835
Ending Page	2840
File Size	595306
Page Count	6
File Format	PDF
ISBN	9781457707148
e-ISBN	9784907764395
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-13
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	SICE (The Society of Instrument and Cont
Subject Keyword	Context Training Natural language processing Semantics Support vector machine classification Dairy products Dictionaries Myanmar-English parallel corpus Word Sense Disambiguation machine translation
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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