Particle Swarm Optimization in Transliteration

International Journal of Computer Trends and Technology (IJCTT)          
© - Issue 2012 by IJCTT Journal
Volume-3 Issue-5                           
Year of Publication : 2012
Authors :Dr. Pothula Sujatha.


Dr. Pothula Sujatha."Particle Swarm Optimization in Transliteration"International Journal of Computer Trends and Technology (IJCTT),V3(5):554-557 Issue 2012 .ISSN Published by Seventh Sense Research Group.

Abstract: - — Transliteration is the process of transforming a word written in a source language into a word in a target language without the aid of a resource like a bilingual dictionary. This process generates the target language word for a given source language word, but need to find the similarity between source and target words. That is, in order to check how far the generated target word is right equivalent an edit distance calculation is needed between source and target languages words. Presently there was no automated process for finding edit cost between source and target languages words. This work proposes a new Particle Swarm Optimization (PSO) algorithm which is used in the transliteration algorithm process for finding optimal cost between source and target words.


[1] E. Bonabeau, M. Dorego and G. Theraulaz, “Swarm Intelligence: From natural to artificial systems” Bio-Inspired Computing, 2003.
[2] Julian Togelius , Renzo De Nardi , Alberto Moraglio, “Geometric PSO + GP = Particle Swarm Programming,” In: Proceedings of CEC 2008, pp. 3594–3600.
[3] M. Clerc, “Discrete particle swarm optimization, illustrated by the traveling salesman problem,” New Optimization Techniques in Engineering, Springer, 2004, pp. 219–239.
[4] J. Kennedy and R. C. Eberhart, A discrete binary version of the particle swarm algorithm, IEEE Transactions on Systems, Man, andCybernetics 5 (1997), 4104–4108.
[5] J. H. Oh and K. S. Choi, “An ensemble of transliteration models for information retrieval,” Information Processing and Management: an International Journal, v.42 n.4, pp. 980-1002, July 2006.
[6] S. Bilac and H. Tanaka, “Improving back-transliteration by combining information sources,” In Proceedings of IJC-NLP, pp. 542–547, 2003.
[7] D. Jurafskyand J. H. Martin, “Speech and Language processing: An introduction to natural language processing,” Computational Linguistics and Speech Recognition, 2007.
[8] S. Garnier, J. Gautrais and G. Theraulaz, “The biological principles of swarm intelligence,” Swarm Intelligence, pp. 3-31, 2007.
[9] Y. Mehdad, “Automatic cost estimation for tree edit distance using particle swarm optimization,” Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, pages 289–292, 2009.

Keywords—Swarm intelligence, particle swarm optimization, transliteration, grapheme, phoneme, hybrid.