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 November 2024
Reseach Article

A Neural Network based Approach for English to Hindi Machine Translation

by Shahnawaz, R. B. Mishra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 53 - Number 18
Year of Publication: 2012
Authors: Shahnawaz, R. B. Mishra
10.5120/8526-2129

Shahnawaz, R. B. Mishra . A Neural Network based Approach for English to Hindi Machine Translation. International Journal of Computer Applications. 53, 18 ( September 2012), 50-56. DOI=10.5120/8526-2129

@article{ 10.5120/8526-2129,
author = { Shahnawaz, R. B. Mishra },
title = { A Neural Network based Approach for English to Hindi Machine Translation },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 53 },
number = { 18 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 50-56 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume53/number18/8526-2129/ },
doi = { 10.5120/8526-2129 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:54:27.404231+05:30
%A Shahnawaz
%A R. B. Mishra
%T A Neural Network based Approach for English to Hindi Machine Translation
%J International Journal of Computer Applications
%@ 0975-8887
%V 53
%N 18
%P 50-56
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper we are discussing the working of our English to Hindi Machine Translation system. Our system is able to translate English language's simple sentences into Hindi. This system has been implemented using feed-forward back-propagation artificial neural network. ANN model does the selection of translation rules for grammar structure and Hindi words/tokens (such as verb, noun/pronoun etc. ). Neural network is used as the knowledge base and for mapping process from bilingual dictionary and linguistic rules. Bilingual dictionary is implemented using neural network, stores the meaning and linguistic features attached to the word of English and Hindi. The transformation of one natural language grammar to other natural language is the core of the machine translation specifically when the languages have different grammatical class such English and Hindi. Grammatical Structure analysis is done with the help of Stanford Tagger and Stanford Parser. The developed module is able to translate simple sentence of English language. The evaluation score achieved by the system for around 500 test sentences is: n-gram blue score 0. 604; METEOR score achieved is 0. 830 and F-score of 0. 816.

References
  1. A. N. Jain: Parsing Complex Sentences with Structured Connectionist Networks, Neural Computation, 3, pp. 110-120, 1991.
  2. A. Waibel, A. N. Jain, A. E. MCNAIR, H. Saito, A. G. Hauptmann and J. Tebelskis: JANUS: A Speech-to-Speech Translation System using Connectionist and Symbolic Processing Strategies, Proceedings of the 1991 International Conference on caustics, Speech and Signal Processing (ICASSP-91), pp. 793-796, Toronto, Canada, 1991.
  3. B. Yegnanarayana, Artificial Neural Networks, New Delhi, India: Prentice-Hall of India, 1999.
  4. Banerjee S. and Lavie A. , METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments, 2005
  5. Martin T. Hagan and Mohammad B. Menhaj, Training Feedforward Networks with the Marquardt Algorithm, IEEE Transactions on neural networks, Vol. 5, No. 6, November 1994.
  6. Mishra V. , and Mishra R. B. , ANN and Rule Based Model for English to Sanskrit Machine Translation. INFOCOMP Journal of Computer Science, 9, 80-89, (2010a).
  7. Mishra V. , and Mishra R. B. , Approach of English to Sanskrit machine translation based on case based reasoning, artificial neural networks and translation rules. Int. J. of Knowl. Eng. Soft Data Paradigm, 2, 328-348, (2010b).
  8. Mishra, Vimal and Mishra R. B. , Performance Evaluation of English to Sanskrit Machine Translation System, International Journal of Computer Aided Engineering and Technology (IJCAET), InderScience Publication, UK, Vol. 4, No. 4, pp 340-359, 2012.
  9. NenadKoncar, Dr. Gregory Guthrie: A natural language translation neural network, In International Conference of the International Conference on New Methods in Language Porcessing (NeMLaP), pages 71 -77, Manchester, UK, 1994.
  10. Papineni K. , Roukos S. , Ward T. , and Zhu W. -Jing, BLEU: a Method for Automatic Evaluation of Machine Translation, Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, Philadelphia, p. 311-318, July 2002.
  11. Sergei Nirenburg , Victor Raskin: The Subworld Concept Lexicon And The Lexicon Management System, Computational Linguistics, Vol (13), pages 276-289, 1987
  12. Shahnawaz and Mishra R. B. , Translation Rules and ANN based model for English to Urdu Machine Translation. INFOCOMP Journal of Computer Science, 10, 36-47, 2011.
  13. Shahnawaz, Mishra R. B. ANN and Rule Based Model for English to Urdu-Hindi Machine Translation System. Proceedings of National Conference on Artificial Intelligence and agents:Theory& Application (AIAIATA 2011), 2011, pp 115-121
  14. Stanford Parser, http://nlp. stanford. edu/software/lex-parser. shtml, online access 2012
  15. Stanford Tagger, http://nlp. stanford. edu/software/tagger. shtml, online access 2012
  16. Turian J. and Shen L. and Melamed I. D. , Evaluation of Machine Translation and its Evaluation, In Proceedings of MT Summit IX, 2003.
  17. W. J. Hutchins: Machine translation: past, present, future. (Ellis Horwood Series in Computers and their Applications. ) Chichester, Ellis Horwood, 1986. 382p. ISBN: 0-85312-788-3.
  18. World Statistics,http://www. nationmaster. com, online access 2012
Index Terms

Computer Science
Information Sciences

Keywords

Neural Network back-propagation Machine Translation Hindi English