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Reseach Article

Automatic Ranking of MT Outputs using Approximations

by Pooja Gupta, Nisheeth Joshi, Iti Mathur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 17
Year of Publication: 2013
Authors: Pooja Gupta, Nisheeth Joshi, Iti Mathur
10.5120/14217-2463

Pooja Gupta, Nisheeth Joshi, Iti Mathur . Automatic Ranking of MT Outputs using Approximations. International Journal of Computer Applications. 81, 17 ( November 2013), 27-31. DOI=10.5120/14217-2463

@article{ 10.5120/14217-2463,
author = { Pooja Gupta, Nisheeth Joshi, Iti Mathur },
title = { Automatic Ranking of MT Outputs using Approximations },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 17 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 27-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number17/14217-2463/ },
doi = { 10.5120/14217-2463 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:20.209160+05:30
%A Pooja Gupta
%A Nisheeth Joshi
%A Iti Mathur
%T Automatic Ranking of MT Outputs using Approximations
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 17
%P 27-31
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Since long, research on machine translation has been ongoing. Still, we do not get good translations from MT engines so developed. Manual ranking of these outputs tends to be very time consuming and expensive. Identifying which one is better or worse than the others is a very taxing task. In this paper, we show an approach which can provide automatic ranks to MT outputs (translations) taken from different MT Engines and which is based on N-gram approximations. We provide a solution where no human intervention is required for ranking systems. Further we also show the evaluations of our results which show equivalent results as that of human ranking.

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Index Terms

Computer Science
Information Sciences

Keywords

N-gram Language Models Trigram Approximations Maximum Likelihood Estimation