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Reseach Article

A Result Analysis of Translation Techniques of English to Hindi Online Translation Systems

by Ekta Gupta, Shailendra Kumar Shrivastava
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 156 - Number 12
Year of Publication: 2016
Authors: Ekta Gupta, Shailendra Kumar Shrivastava
10.5120/ijca2016912501

Ekta Gupta, Shailendra Kumar Shrivastava . A Result Analysis of Translation Techniques of English to Hindi Online Translation Systems. International Journal of Computer Applications. 156, 12 ( Dec 2016), 12-15. DOI=10.5120/ijca2016912501

@article{ 10.5120/ijca2016912501,
author = { Ekta Gupta, Shailendra Kumar Shrivastava },
title = { A Result Analysis of Translation Techniques of English to Hindi Online Translation Systems },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 156 },
number = { 12 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume156/number12/26760-2016912501/ },
doi = { 10.5120/ijca2016912501 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:02:24.891482+05:30
%A Ekta Gupta
%A Shailendra Kumar Shrivastava
%T A Result Analysis of Translation Techniques of English to Hindi Online Translation Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 156
%N 12
%P 12-15
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

If the term “translation process” makes we consider of dictionaries, grammar rules, and debates about linguistic details, we’re absolutely not alone. However, the translation process does not begin or end with transferring information from one language into another. In developing countries like Asian country and India where English is mainly half-hour recognize there automatic computational linguistics systems in education, analysis and industrial activities of very necessary role. Asian country has state a large assembly in Hindi is that the language you speak and in a very range of areas it works in all types of study and official. These days many on-line translator technologies use fully different computational linguistics approach. Like every translation approaches fully different characteristics, the result of the explanation would take issue. The purpose of this study is to create understanding about the different performance of the two online translation services due to the same actions they have. The experiment designed is meant show how the two online translation services have its have advantages and drawbacks which can affect their performance.

References
  1. Bhojraj singh dhakar, sitesh kumar sinha, krishna kumar pandey “A Survey of Translation Quality of English to Hindi Online Translation Systems (Google and Bing)”, International Journal of Scientific and Research Publications, Volume 3, Issue 1, January 2013
  2. Kanika Gupta, Monojit Choudhury, Kalika Bali “Mining Hindi-English Transliteration pair from OnlineHindiLyrics”http://www.google.com/intl/en/press/zeitgeist2010/regions/ in.html
  3. Sanjay Dwivedi and Pramod Sukhadeve “Translation Rules for English to Hindi Machine Translation System: Homoeopathy Domain”, The International Arab Journal of Information Technology, Vol. 12, No. 6A, 2015
  4. Atul Kr. Johan, Akanksha Bansal, Sumedh Hadke and Girish Nath Jha “Evaluation of Hindi-English MT Systems”, http://translate.google.co.in/
  5. Prashant Mathur “Automatic Translation of Noun Compounds from English to Hindi”, Language Technology Research Center International Institute of Information Technology Hyderabad - 500032, INDIA October, 2011
  6. Akshar Bharati, Amba Kulkarni” English from Hindi viewpoint: A Paaninian Perspective” Satyam Computer Services Limited, [Presented at Platinum Jubilee conference of Linguistic Society of India, held at CALTS, University of Hyderabad, Hyderabad, during 6th8th [Dec 2005]
  7. R.M.K. Sinha , A. Jain “An English to Hindi Machine-Aided Translation System” Indian Institute of Technology, Kanpur, India.
  8. Kunal Sachdeva, Rishabh Srivastava, Sambhav Jain, Dipti Misra Sharma “Hindi to English Machine Translation:Using Effective Selection in Multi-Model SMT”Language Technologies Research Center, International Institute of Information Technology, Hyderabad.
  9. B. Hettige, A. S. Karunananda “Developing Lexicon Databases for English to Sinhala Machine Translation”, University of Sri Jayewardenepura, Sri Lanka
  10. Latha R. Nair David Peter S, “Machine translation systems for Indian language”, IJCA Journal 2012, Volume 39 - Number 1.
  11. Nisheeth Joshi, Iti Mathur “Design of English-Hindi Translation Memory for Efficient Translation”, National Conference on Recent Advances of Computer Engineering, 2011, Jaipur, India.
  12. Aditi Kalyani, Hemant Kumud, Shashi Pal Singh “Assessing the Quality of MT Systems for Hindi to English Translation”, International Journal of Computer Applications (0975 – 8887)Volume 89 – No 15, March 2014.
  13. Charles Schafer, David Smith “An Overview of Statistical Machine Translation” [Johns Hopkins University] http://www.nist.gov/speech/tests/mt” Automatic Evaluation of Machine Translation Quality Using N-gram Co-Occurrence Statistics”
  14. Jonathan H. Clark Chris Dyer Alon Lavie Noah A. Smith “Better Hypothesis Testing for Statistical Machine Translation: Controlling for Optimizer Instability “[Language Technologies Institute Carnegie Mellon University Pittsburgh, PA 15213, USA]
  15. Kishore Papineni, Salim Roukos, ToddWard, andWei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proc. of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), pages 311–318, Philadelphia, PA, July.
  16. LDC. 2005. Linguistic data consortium Chinese training data resources.
  17. http://www.ldc.upenn.edu/Projects/TIDES/mt2005cn.htm.
  18. Malcolm Williams "The Application of Argumentation Theory to Translation Quality Assessment”
  19. Mary Hearne, Andy Way” Statistical Machine Translation: A Guide for Linguists and translator “[School of Computing, Dublin City University].
  20. Rafal S Uzar “A corpus methodology for analyzing translation “[University of Lodz] .
  21. Riccardo Schiaffino, Franco Zearo “Translation Quality Measurement in Practice”, 46th ATA Conference, Seattle. Aliquantum …, 2005
  22. G V Garje and G K Kharate “survey of machine translation systems India”, International Journal on Natural Language Computing (IJNLC) Vol. 2, No.4, October2013.
  23. Yongwei Yang, James Harter, Eldin J. Ehrlich “A Methodological Analysis of Translation Quality”, Journal of Cross-Cultural Psychology, Vol. 37 No. 5, September 2006.
  24. B. Hettige, A. S. Karunananda “Developing Lexicon Databases for English to Sinhala Machine Translation”, University of Sri Jayewardenepura, Sri Lanka.
  25. Niladri Chatterjeea, Anish Johnsonb, Madhav Krishnab “Some Improvements over the BLEU Metric for Measuring Translation Quality for Hindi”, Indian Institute of Technology, Hauz Khas, New Delhi.
  26. Neeraj Tomer, Deepa Sinha “Evaluating Machine Translation Evaluation’s BLEU Metric for English to Hindi Language Machine Translation”, Volume 1, No. 6, August 2012.
  27. Nakul harma, Prateek Bhatia “English to Hindi Statistical Manchine Translation System”Thapar University Patiala june 2011.
  28. Sukhadeve P. and Dwivedi S., “Developing Hindi POS Tagger for homoeopathy Clinical language,” in Proceedings of the 2nd International Conference Advances in Computer Science and Information Technology, Bangalore, India, pp. 310-316, 2012.
  29. Sukhadeve P. and Dwivedi S., “Enlargement of Clinical Stemmer in Hindi Language of Homoeopathy Province,” in Proceedings of the 2nd International Conference Advances in Computer Science and Information Technology, Bangalore, India, pp. 239-248, 2012.
  30. The Stanford Natural Language Processing Group., available at: http://nlp.stanford.edu/software/tagger.html, last visited 2013.
  31. Unnikrishnan P., Antony P., and Soman K., “A Novel Approach for English to South Dravidian Language Statistical Machine Translation System,” the International Journal on Computer Science and Engineering, vol. 2, no. 8, pp. 2749- 2759, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Translation Quality Analysis Translation Quality of Online Translation System for English to Hindi Translation.