Classifier based text simplification for improved machine translation

Author

Tyagi, Shruti ; Chopra, Deepti ; Mathur, Iti ; Joshi, Nisheeth

Author_Institution

Dept. of Comput. Sci., Banasthali Univ., Banasthali, India

fYear

2015

fDate

19-20 March 2015

Firstpage

46

Lastpage

50

Abstract

Machine Translation is one of the research fields of Computational Linguistics. The objective of many MT Researchers is to develop an MT System that produce good quality and high accuracy output translations and which also covers maximum language pairs. As internet and Globalization is increasing day by day, we need a way that improves the quality of translation. For this reason, we have developed a Classifier based Text Simplification Model for English-Hindi Machine Translation Systems. We have used support vector machines and Naïve Bayes Classifier to develop this model. We have also evaluated the performance of these classifiers.

Keywords

language translation; pattern classification; support vector machines; text analysis; English-Hindi machine translation systems; Internet; MT system; Naïve Bayes classifier; classifier based text simplification model; computational linguistics; globalization; improved machine translation; support vector machines; Computational linguistics; Computers; Pragmatics; Root mean square; Support vector machines; Syntactics; Training; Machine Translation; Naïve Bayes Classifier; Support Vector Machine Classifier; Text Simplification;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in

Conference_Location

Ghaziabad

Type

conf

DOI

10.1109/ICACEA.2015.7164711

Filename

7164711