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  1. University of Information Technology
  2. Faculty of Computer Science

Word Alignment System Based on Hybrid Approach for Myanmar-English Machine Translation

https://meral.edu.mm/records/6752
https://meral.edu.mm/records/6752
93ca44e1-81e9-4a42-be55-9846c1b20c79
952cb22f-1ff7-4cf4-8e43-cfc523b8ca62
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4-Word 4-Word Alignment System Based on Hybrid Approach for Myanmar English Machine Translation.pdf (340 Kb)
© 2011 SICE
Publication type
Conference paper
Upload type
Publication
Title
Title Word Alignment System Based on Hybrid Approach for Myanmar-English Machine Translation
Language en
Publication date 2011-09-18
Authors
Khin Thandar Nwet
Ni Lar Thein
Description
Word alignment is a basic and critical process in the Statistical Machine Translation (SMT). Word alignmentis to identify word correspondence that are translations of each other based on information found on parallel text. Essential for building parallel corpora is the alignment of translated segments with source segments. A parallel corpus is a collection of texts in two languages, one of which is the translation equivalent of the other. Nowadays,Myanmar-English word-aligned parallel corpora are not available. This paper describes the construction of an alignedMyanmar- English parallel corpus to be able to use as a resource in Myanmar-English machine translation. The proposed system uses the combination of corpus-based approach and the dictionary lookup approach. The corpus-based approach is based on the first three IBM models and Expectation Maximization (EM) algorithm. For the dictionarylookup approach, the proposed system uses the bilingual Myanmar-English Dictionary. The system also uses a list of cognates and morphological analysis to get better alignment accuracy. Accuracy of modern statistical machine translation depends on good word alignment.
Keywords
Word Alignment, IBM Models, Word-aligned Parallel Corpus
Conference papers
SICE 2011
13-18 September, 2011
The Society of Instrument and Control Engineers (SICE) Annual Conference
Waseda University, Tokyo, Japan
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