We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Analysis on Translation Quality of English to Hindi Online Translation Systems- A Review

by Ekta Gupta, Shailendra Shrivastava
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 152 - Number 10
Year of Publication: 2016
Authors: Ekta Gupta, Shailendra Shrivastava
10.5120/ijca2016911749

Ekta Gupta, Shailendra Shrivastava . Analysis on Translation Quality of English to Hindi Online Translation Systems- A Review. International Journal of Computer Applications. 152, 10 ( Oct 2016), 42-46. DOI=10.5120/ijca2016911749

@article{ 10.5120/ijca2016911749,
author = { Ekta Gupta, Shailendra Shrivastava },
title = { Analysis on Translation Quality of English to Hindi Online Translation Systems- A Review },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2016 },
volume = { 152 },
number = { 10 },
month = { Oct },
year = { 2016 },
issn = { 0975-8887 },
pages = { 42-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume152/number10/26363-2016911749/ },
doi = { 10.5120/ijca2016911749 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:57:53.160420+05:30
%A Ekta Gupta
%A Shailendra Shrivastava
%T Analysis on Translation Quality of English to Hindi Online Translation Systems- A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 152
%N 10
%P 42-46
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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 the language you speak and in a number of areas it works in all kinds of study and official. Nowadays several on-line translator technologies use completely different computational linguistics approach. Like every translation approaches completely different characteristics, the outcome of the explanation would differ. Bing Translator and Google Translate free on-line machine translators is exploitation statistical computational linguistics each translators are of the most accepted. It keeps increasing the language selection and increasing its usability. As a result of the most important reverse characteristics of every machine translator services and their needed role for the development of machine translators mainly in web platform, it's determined to own a study concerning their comparison. Bing translator and Google translate within the whole world have to be obliged to use automatic on-line translation system is employed broadly in India is additionally as a outcome of it's a free and reliable. The aspire of this study is to make understanding concerning the different performance of the 2 on-line translation services due to the same actions they need. The experimentation designed is meant show however the 2 on-line translation services possess advantages and disadvantages which may have a consequence on their performance. Secondary aim of this study is to look for out the typical problems that will occur in translation between English and Hindi and to look for out from the 2 on-line translation services, which is more proper. To get a completely automatic top quality machine translation system is a troublesome task. In this document, we have a tendency to explain the web translation systems like Microsoft Bing Translator and Google Translate for English to Hindi translation and its conversion quality. Researches focused on survey of on-line translation resolutions for English to Hindi translation and examine its translation quality. The evaluation parameters that are considered here are Accuracy, translation speed, output fluency, Adequacy,

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 Online HindiLyrics”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. Ojha, 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. 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”
  10. 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]
  11. 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.
  12. Latha R. Nair David Peter S, “Machine translation systems for Indian language”, IJCA Journal 2012, Volume 39 - Number 1
  13. LDC. 2005. Linguistic data consortium Chinese training dataresources.http://www.ldc.upenn.edu/Projects/TIDES/mt2005cn.htm.
  14. Malcolm Williams "The Application of Argumentation Theory to Translation Quality Assessment”
  15. Mary Hearne, Andy Way” Statistical Machine Translation: A Guide for Linguists and translator “[School of Computing, Dublin City University].
  16. Rafal S Uzar “A corpus methodology for analyzing translation “[University of Lodz] .
  17. Riccardo Schiaffino, Franco Zearo “Translation Quality Measurement in Practice”, 46th ATA Conference, Seattle. Aliquantum …, 2005
  18. 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.
  19. Yongwei Yang, James Harter, Eldin J. Ehrlich “A Methodological Analysis of Translation Quality”, Journal of Cross-Cultural Psychology, Vol. 37 No. 5, September 2006.
  20. B. Hettige, A. S. Karunananda “Developing Lexicon Databases for English to Sinhala Machine Translation”, University of Sri Jayewardenepura, Sri Lanka.
  21. 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.
  22. Neeraj Tomer, Deepa Sinha “Evaluating Machine Translation Evaluation’s BLEU Metric for English to Hindi Language Machine Translation”, Volume 1, No. 6, August 2012.
  23. Ondřej Bojar, Vojtěch Diatkay, Pavel Rychlýz, Pavel Straňák “HindEnCorp – Hindi-English and Hindi-only Corpus for Machine Translation”, Charles University in Prague.
  24. Nisheeth Joshi, Iti Mathur “Design of English-Hindi Translation Memory for Efficient Translation”, National Conference on Recent
  25. Raji P., “Reordering Approach in English-Malayalam Statistical Machine Translation,”Master’sThesis,Coimbatore, India, 2010.
  26. Sukhadeve P. and Dwivedi S., “Advancement ofClinical Stemmer,” available at: http:// languageinindia.com/may2011/kommaluricomplete.pdf#page=51, last visited 2013.
  27. 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.
  28. 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.
  29. The Stanford Natural Language Processing Group., available at: http://nlp.stanford.edu/software/tagger.html, last visited 2013.
  30. 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.