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Building English-Punjabi Parallel corpus for Machine Translation

by Shishpal Jindal, Vishal Goyal, Jaskarn Singh Bhullar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 8
Year of Publication: 2017
Authors: Shishpal Jindal, Vishal Goyal, Jaskarn Singh Bhullar
10.5120/ijca2017916036

Shishpal Jindal, Vishal Goyal, Jaskarn Singh Bhullar . Building English-Punjabi Parallel corpus for Machine Translation. International Journal of Computer Applications. 180, 8 ( Dec 2017), 26-29. DOI=10.5120/ijca2017916036

@article{ 10.5120/ijca2017916036,
author = { Shishpal Jindal, Vishal Goyal, Jaskarn Singh Bhullar },
title = { Building English-Punjabi Parallel corpus for Machine Translation },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2017 },
volume = { 180 },
number = { 8 },
month = { Dec },
year = { 2017 },
issn = { 0975-8887 },
pages = { 26-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number8/28821-2017916036/ },
doi = { 10.5120/ijca2017916036 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:00:06.651482+05:30
%A Shishpal Jindal
%A Vishal Goyal
%A Jaskarn Singh Bhullar
%T Building English-Punjabi Parallel corpus for Machine Translation
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 8
%P 26-29
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Objective Parallel corpus is the key resource for English Punjabi machine translation. At wide level there is no availability of English-Punjabi corpora. There is a primary requirement of parallel corpus for the training of statistical machine translation. Methods/Analysis In this paper, authors focus on building English-Punjabi corpus at large scale. It posed difficulties and the intensive labor to develop the corpus. We are intricate on the collection as well as the flow of work for the construction of parallel corpus. Now after getting the raw text, we need to refine the corpus in such a way that every source language sentence should have corresponding target language sentence. Findings The paper attempts to explore existing tools as well as building new tools. One of the goals is alignment of bilingual corpus. The alignment algorithms are used to tune the sentences. The accuracy depends on the type of corpus. Novelty/Improvement A cautious endeavor has been made to capture different types of texts.

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Index Terms

Computer Science
Information Sciences

Keywords

Bilingual corpora Machine-translation English Punjabi NLP.

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