Myanmar-English Bidirectional Machine Translation System with Numerical Particles Identification

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Yin Yin Win 1,* Aye Thida 1

1. University of Computer Studies, Mandalay, Myanmar

* Corresponding author.


Received: 3 Jul. 2015 / Revised: 18 Oct. 2015 / Accepted: 15 Feb. 2016 / Published: 8 Jun. 2016

Index Terms

RBMT, SCFG, Tree to Tree Transformation


This paper the development of Myanmar-English bidirectional machine translation system is implemented applying Rule based machine translation approach. Stanford and ML2KR parsers are used for preprocessing step. From this step, parsers generate corresponding parse tree structures. Used parsers generate corresponding CFG rules which are collected and created as synchronous context free grammar SCFG rules. Myanmar language can be written free order style, but it must be verb final structure. Therefore, CFG rules are required for reordering the structure of the two languages. After that tree to tree transformation is carried on the source tree structure which corresponds with used parser (Stanford parser or ML2KR's parser). When source parse tree is transformed as target parse tree, it is changed according to the SCFG rules. And then system carries out the morphological synthesis. In this stage, we need to solve only for English to Myanmar machine translation because Myanmar language is morphologically rich language. Therefore, particles for Myanmar language can be solved in this system by proposed algorithm. After finishing morphological synthesis, this system generates meaningful and appropriate smoothing sentences.

Cite This Paper

Yin Yin Win, Aye Thida, "Myanmar-English Bidirectional Machine Translation System with Numerical Particles Identification", International Journal of Information Technology and Computer Science(IJITCS), Vol.8, No.6, pp.37-43, 2016. DOI:10.5815/ijitcs.2016.06.05


[1]P. J. Antony, “Machine Translation Approaches and Survey for Indian Languages” The Association for Computational Linguistics and Chinese Language Processing Vol. 18, No. 1, March 2013, pp. 47-78.

[2]S.R.Priyanga, AP, A.AzhaguSindhu, AP, “Rule Based Statistical Hybrid Machine Translation”, Internnational Journal of Science and Modern Engineering (IJISME) ISSN: 2319-6386, Volume-1, Issue-5, April 2013. 

[3]Khaled Shaalan, “An English-Arabic Bi-directional Machine Translation Tool in the Agriculture Domain”, IFIP International Federation for Information Processing 2010.

[4]Mr.Uday C. Patkar, “Transformation of Multiple English Text Sentences To Vocal Sanskrit Using Rule Based Technique”, International Journal of Computers and Distributed Systems, Vol. No.2, Issue 1, December 2012.

[5]Fai Wong, “Handheld Machine Translation System Based on Constraint Synchronous Grammar”, Machine Translation Summit XIII, Sep. 2011, p. 439-446.

[6]Shibli Syeed Ashrafi, “English to BanglaMachine Translation System Using Context-Free Grammars”, IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 3, No 2, May 2013.

[7]T. T. Zin et al, “Myanmar Phrases Translation Model with Morphological Analysis for Statistical Myanmar to English Translation System”, International Journal of Computer Applications, Volume 28, No 1, 2011, pp 13-19

[8] translation

[9]http://nlp. stanford. edu/ software/ lex-parser.shtml

[10]S.L. Phyue, “Development Of Lexico-Conceptual Knowledge Resources And Syntax Analyzer For Myanmar Language”, Ph.D Thesis, University of Computer Studies, Mandalay, 2013.

[11]R. Harsha Wardhan, “Rule Based Machine Translation System for English to Malayalam Language”, Centre for Excellence in Computational Engineering and Networking, December, 2011

[12]A. Lopez, “Statistical machine translation”, ACM Computing Surveys (CSUR), 40(3), p.8, 2008.

[13]T.W. Mamta, “Survey of Approaches Used in Machine Translation System”, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)Volume 4 Issue 5, May 2015

[14]R.S. Narayanan, “English-Telugu Rule Based Machine Translation system”, 2012.

[15]S. Pal, "Improved Alignment in Phrase Based Statistical Machine Translation System." PhD diss., Jadavpur University, Kolkata, 2013.