Urdu Language Translation using LESSA

Muhammad Naeem Ul Hassan¹

1. Dept. of Computer Science, Kunming University of Science and Technology, Xishan, China.

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.5 , pp.36-40, Oct-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i5.3640

Online published on Oct 31, 2018

Copyright © Muhammad Naeem Ul Hassan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Pakistan has a population of 140 million speaking more than 56 different languages. Urdu is the lingua franca of these people, as many speak Urdu as a second language, also the national language of Pakistan. Being a developing population, Pakistani people need access to information. Most of the information over the ICT infrastructure is only available in English and only 5-10% of these people are familiar with English. This paper presents a system for translation from English to Urdu. A module LESSA is used that uses a rule based algorithm to read the input text in English language, understand it and translate it into Urdu language. The designed approach was further incorporated to translate the complete website from English language o Urdu language.

Key-Words / Index Term :
Natural Language Translation, Text Understanding, Knowledge extraction, Text Processing

References :
[1] Bajwa, I.S., Choudhary, M.A. (2006) “A Rule Based System for Speech Language Context Understanding” Journal of Donghua University, (English Edition) 23 (6), pp. 39-42.
[2] Gómez-Pérez Asunción, Fernández-López Mariano, Corcho Oscar, (2004) Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. Springer.
[3] Drouin Patrick. (2004) "Detection of Domain Specific Terminology Using Corpora Comparison." Proceedings of the Fourth International Conference on Language Resources.
[4] Bajwa, I.S., Hyder, I. (2007), "UCD-Generator - A LESSA Application for Use Case Design", Proceedings of IEEE- International Conference on Information and Emerging Technologies- ICIET, pp-182-187
[5] Chomsky, N. (1965) “Aspects of the Theory of Syntax. MIT Press, Cambridge, Mass, 1965.
[6] Chow, C., & Liu, C. (1968) “Approximating discrete probability distributions with dependence trees”. IEEE Transactions on Information Theory, 1968, IT-14(3), 462–467.
[7] Krovetz, R., & Croft, W. B. (1992) “Lexical ambiguity and information retrieval”, ACM Transactions on Information Systems, 10, 1992, pp. 115–141
[8] Salton, G., & McGill, M. (1995) “Introduction to Modern Information Retrieval” McGraw-Hill, New York., 1995
[9] Maron, M. E. & Kuhns, J. L. (1997) “On relevance, probabilistic indexing, and information retrieval” Journal of the ACM, 1997, 7, 216– 244.
[10] Losee, R. M. (1988) “Parameter estimation for probabilistic document retrieval models”. Journal of the American Society for Information Science, 39(1), 1988, pp. 8–16.
[11] Imran Sarwar Bajwa, Riaz-Ul-Amin, M. Asif Naeem, Muhammad Nawaz (2006), “Web Information Mining Framework using XML Based Knowledge Representation Engine, Proceedings of 2nd International Conference on Software Engineering, 2006, Lahore, Pakistan
[12] J. M. Zelle and R. J. Mooney, (1993), “Learning semantic grammars with constructive inductive logic programming”, in: Proceedings of the 11th National Conference on Artificial Intelligence (AAAI Press/MIT Press, Washington, D.C.) , pp. 817–822.