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English to Telugu Rule based Machine Translation System: A Hybrid Approach

by Keerthi Lingam, E. Ramalakshmi, Srujana Inturi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 101 - Number 2
Year of Publication: 2014
Authors: Keerthi Lingam, E. Ramalakshmi, Srujana Inturi
10.5120/17659-8474

Keerthi Lingam, E. Ramalakshmi, Srujana Inturi . English to Telugu Rule based Machine Translation System: A Hybrid Approach. International Journal of Computer Applications. 101, 2 ( September 2014), 19-24. DOI=10.5120/17659-8474

@article{ 10.5120/17659-8474,
author = { Keerthi Lingam, E. Ramalakshmi, Srujana Inturi },
title = { English to Telugu Rule based Machine Translation System: A Hybrid Approach },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 101 },
number = { 2 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume101/number2/17659-8474/ },
doi = { 10.5120/17659-8474 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:30:38.469782+05:30
%A Keerthi Lingam
%A E. Ramalakshmi
%A Srujana Inturi
%T English to Telugu Rule based Machine Translation System: A Hybrid Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 101
%N 2
%P 19-24
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper deals with adaptive rule based machine translation from English to Telugu. This approach is based on rule-based methodologies. If-then methods to select the best rules for target language in translation, Probability based appropriate word selection for a given sentence and rough sets to classify a given sentence are the approaches used in this technique. Set of production rules of English and Telugu, Training set and Dictionary for both the languages are developed for this purpose. User gives and input, which is an English sentence. The given input sentence is then tokenized into individual words. These words are tagged with their respective parts of speech. All other words that are not found in the pre-defined database are tagged using grammatical rules that are formulated. Using these POS tags, the respective word translations are retrieved from the database. These individual words are then concatenated to form a sentence that is the result of user's input.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Machine Translation Natural Language Processing Rule Based Approach English to Telugu.