Translation rules and ANN based model for english to urdu machine translation
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/336 http://repositorio.ufla.br/jspui/handle/1/14988 |
Resumo: | In this paper we discuss the working of our English to Urdu Machine Translation (MT) system. We used feed-forward back-propagation artificial neural network for the selection of Urdu words/tokens (such as verb, noun/pronoun etc.) and translation rules for grammar structure equivalent to English words/tokens and grammar structure rules respectively. As English is SVO class language while Urdu is SOV class language so grammar structure transfer is main task in English-Urdu machine translation problem. Our system is able to translate sentences having gerund, having infinitives (maximum two), having prepositions and prepositional objects (maximum three), direct object, indirect object etc. Neural network works as the knowledge base for linguistic rules and bilingual dictionary. Bilingual dictionary not only stores the meaning of English word in Urdu but also stores linguistic features attached to the word. The output of our system is presented in Romanized Urdu. The n-gram blue score achieved by the system is 0.6954; METEOR score achieved is 0.8583 and F-score of 0.8650. |
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Translation rules and ANN based model for english to urdu machine translationNeural networkBack-propagationRule based translationMachine translation systemArtificial IntelligenceIn this paper we discuss the working of our English to Urdu Machine Translation (MT) system. We used feed-forward back-propagation artificial neural network for the selection of Urdu words/tokens (such as verb, noun/pronoun etc.) and translation rules for grammar structure equivalent to English words/tokens and grammar structure rules respectively. As English is SVO class language while Urdu is SOV class language so grammar structure transfer is main task in English-Urdu machine translation problem. Our system is able to translate sentences having gerund, having infinitives (maximum two), having prepositions and prepositional objects (maximum three), direct object, indirect object etc. Neural network works as the knowledge base for linguistic rules and bilingual dictionary. Bilingual dictionary not only stores the meaning of English word in Urdu but also stores linguistic features attached to the word. The output of our system is presented in Romanized Urdu. The n-gram blue score achieved by the system is 0.6954; METEOR score achieved is 0.8583 and F-score of 0.8650.Universidade Federal de Lavras (UFLA)2011-09-012017-08-01T21:08:43Z2017-08-01T21:08:43Z2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/336SHAHNAWAZ, A.; MISHRA, R. B. Translation rules and ANN based model for english to urdu machine translation. INFOCOMP Journal of Computer Science, Lavras, v. 10, n. 3, p. 25-35, Sept. 2011.http://repositorio.ufla.br/jspui/handle/1/14988INFOCOMP; Vol 10 No 3 (2011): September, 2011; 25-351982-33631807-4545reponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttp://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/336/320Copyright (c) 2016 INFOCOMP Journal of Computer Scienceinfo:eu-repo/semantics/openAccessShahnawaz, AhmadMishra, R. B.2021-09-24T23:36:36Zoai:localhost:1/14988Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-09-24T23:36:36Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Translation rules and ANN based model for english to urdu machine translation |
title |
Translation rules and ANN based model for english to urdu machine translation |
spellingShingle |
Translation rules and ANN based model for english to urdu machine translation Shahnawaz, Ahmad Neural network Back-propagation Rule based translation Machine translation system Artificial Intelligence |
title_short |
Translation rules and ANN based model for english to urdu machine translation |
title_full |
Translation rules and ANN based model for english to urdu machine translation |
title_fullStr |
Translation rules and ANN based model for english to urdu machine translation |
title_full_unstemmed |
Translation rules and ANN based model for english to urdu machine translation |
title_sort |
Translation rules and ANN based model for english to urdu machine translation |
author |
Shahnawaz, Ahmad |
author_facet |
Shahnawaz, Ahmad Mishra, R. B. |
author_role |
author |
author2 |
Mishra, R. B. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Shahnawaz, Ahmad Mishra, R. B. |
dc.subject.por.fl_str_mv |
Neural network Back-propagation Rule based translation Machine translation system Artificial Intelligence |
topic |
Neural network Back-propagation Rule based translation Machine translation system Artificial Intelligence |
description |
In this paper we discuss the working of our English to Urdu Machine Translation (MT) system. We used feed-forward back-propagation artificial neural network for the selection of Urdu words/tokens (such as verb, noun/pronoun etc.) and translation rules for grammar structure equivalent to English words/tokens and grammar structure rules respectively. As English is SVO class language while Urdu is SOV class language so grammar structure transfer is main task in English-Urdu machine translation problem. Our system is able to translate sentences having gerund, having infinitives (maximum two), having prepositions and prepositional objects (maximum three), direct object, indirect object etc. Neural network works as the knowledge base for linguistic rules and bilingual dictionary. Bilingual dictionary not only stores the meaning of English word in Urdu but also stores linguistic features attached to the word. The output of our system is presented in Romanized Urdu. The n-gram blue score achieved by the system is 0.6954; METEOR score achieved is 0.8583 and F-score of 0.8650. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-09-01 2017-08-01T21:08:43Z 2017-08-01T21:08:43Z 2017-08-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/336 SHAHNAWAZ, A.; MISHRA, R. B. Translation rules and ANN based model for english to urdu machine translation. INFOCOMP Journal of Computer Science, Lavras, v. 10, n. 3, p. 25-35, Sept. 2011. http://repositorio.ufla.br/jspui/handle/1/14988 |
url |
http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/336 http://repositorio.ufla.br/jspui/handle/1/14988 |
identifier_str_mv |
SHAHNAWAZ, A.; MISHRA, R. B. Translation rules and ANN based model for english to urdu machine translation. INFOCOMP Journal of Computer Science, Lavras, v. 10, n. 3, p. 25-35, Sept. 2011. |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/336/320 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2016 INFOCOMP Journal of Computer Science info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2016 INFOCOMP Journal of Computer Science |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Lavras (UFLA) |
publisher.none.fl_str_mv |
Universidade Federal de Lavras (UFLA) |
dc.source.none.fl_str_mv |
INFOCOMP; Vol 10 No 3 (2011): September, 2011; 25-35 1982-3363 1807-4545 reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
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1807835158955425792 |