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A Neural Network based Approach for English to Hindi Machine Translation

by Shahnawaz, R. B. Mishra
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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.

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Index Terms

Computer Science
Information Sciences

Keywords

Neural Network back-propagation Machine Translation Hindi English

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