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Reseach Article

Ambiguous Myanmar Word Disambiguation System for Myanmar-English Statistical Machine Translation

by Nyein Thwet Thwet Aung, Khin Mar Soe, Ni Lar Thein
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 27 - Number 8
Year of Publication: 2011
Authors: Nyein Thwet Thwet Aung, Khin Mar Soe, Ni Lar Thein
10.5120/3323-4568

Nyein Thwet Thwet Aung, Khin Mar Soe, Ni Lar Thein . Ambiguous Myanmar Word Disambiguation System for Myanmar-English Statistical Machine Translation. International Journal of Computer Applications. 27, 8 ( August 2011), 5-11. DOI=10.5120/3323-4568

@article{ 10.5120/3323-4568,
author = { Nyein Thwet Thwet Aung, Khin Mar Soe, Ni Lar Thein },
title = { Ambiguous Myanmar Word Disambiguation System for Myanmar-English Statistical Machine Translation },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 27 },
number = { 8 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 5-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume27/number8/3323-4568/ },
doi = { 10.5120/3323-4568 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:13.619011+05:30
%A Nyein Thwet Thwet Aung
%A Khin Mar Soe
%A Ni Lar Thein
%T Ambiguous Myanmar Word Disambiguation System for Myanmar-English Statistical Machine Translation
%J International Journal of Computer Applications
%@ 0975-8887
%V 27
%N 8
%P 5-11
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In Statistical Machine Translation (SMT), there are many source words that can present different translations or senses. Word Sense Disambiguation (WSD) system is designed to determine which one of the senses of an ambiguous word is invoked in a particular context around the word. 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. This paper presents a new WSD method for ambiguous Myanmar words. It is based on supervised learning approach, Nearest Neighbor Cosine Classifier. The system uses Myanmar-English Parallel Corpus as a training resource. As an advantage, the system can overcome the problem of translation ambiguity from Myanmar to English language translation.

References
  1. Phil, Kat. 2005. Supervised Word Sense Disambiguation using Python.
  2. Mohammad, T. U., and Shun, I. 2006. A Word Sense Disambiguation System Using Modified Naïve Bayesian Algorithms for Indonesian Language. Information and Media Technologies 1(1): pp.257-274.
  3. Pongpinigpinyo and Wanchai, R. 2006. Distributional Semantics Approach to Thai Word Sense Disambiguation. In Proceedings of the International Journal of Computational Intelligence 2:3.
  4. Samir, E., Taher, H., and Hatem M. N. 2008. Naïve Bayes Classifier for Arabic Word Sense Disambiguation. In Proceedings of the INFOS2008, Cairo-Egypt, March 27-29.
  5. Farag, A., and Andreas, N. 2008. Arabic/English Word Translation Disambiguation using Parallel Corpora and Matching Schemes. In Proceedings of the 12th EAMT conference, Hamburg, Germany, 22-23 September.
  6. Farag, A., and Andreas, N. 2009. Corpora based Approach for Arabic/English Word Translation Disambiguation. Speech and Language Technology, Volume 11.
  7. Yu, Z., Deng, B., Hou, B., Han, L., and Guo, J. 2009. Word Sense Disambiguation Based on Bayes Model and Information Gain. In the Proceedings of the International Journal of Advanced Science and Technology, Vol.3, February.
  8. Zhang, Z., and Zhu, S. 2009. A New Approach to Word Sense Disambiguation in MT System. World Congress on Computer Science and Information Engineering.
  9. Asma, N., and Sarmad, H. 2009. Supervised Word Sense Disambiguation for Urdu Using Bayesian Classification. Unpublished.
  10. Laroussi, M., Anis, Z., and Mounir, Z. 2010. Ambiguous Arabic Words Disambiguation. 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.
  11. Zheng, Y. N., Dong, H. J., and Chew, L. T. 2004. Optimizing Feature Set for Chinese Word Sense Disambiguation. In Proceedings of the SENSEVAL-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text, Barcelona, Spain, July.
  12. Nancy, I., and Jean, V. 1998.Word Sense Disambiguation: The State of the Art. Computational Linguistics, Department of Computer Science. Vassar College, Poughkeepsie, New York.
  13. Cuong, A. L., and Akira, S. 2004. High WSD accuracy using Naïve Bayesian classifier with rich features, In Proceedings of the PACLIC 18, Waseda University, Tokyo, December 8th-10th.
  14. Guo, J., and Zhang, Y. 2010. Study on Multiple Classifier for Chinese WSD. International Conference on Artificial Intelligence and Computational Intelligence.
  15. Jong, H. O., and Key, S. C., 2002. Word Sense Disambiguation using Static and Dynamic Sense Vectors. 19th International Conference on Computational Linguistics.
Index Terms

Computer Science
Information Sciences

Keywords

Myanmar Language ambiguous Myanmar words supervised learning Nearest Neighbor Cosine Classifier Myanmar-English Parallel Corpus