Survey of Machine Translation for Indian Languages to English and Its Approaches

Authors(2) :-Namrata G Kharate, Dr. Varsha H. Patil

This paper presents a survey of Machine translation system for Indian Regional languages to English language. Machine translation is important for breaking language barrier. Out of 1.3 billion India population, hardly 10% people can speak, read and write English with varied degree of proficiency. With the advent of Information Technology many documents and web pages are coming up in a local language so there is a large need of good MT systems to address all these issues in order to establish a proper communication between states and union governments to exchange information amongst the people of different states. This paper discusses the various approaches which have been applied in translation systems for Indian languages to English languages. Some of the important Indian language translation systems implemented with these techniques along with their capabilities and limitations are also discussed.

Authors and Affiliations

Namrata G Kharate
Department of Computer Engineering, VIIT,Pune, Maharashtra, India
Dr. Varsha H. Patil
Head of department, Department of Computer Engineering, MCOERC, Nashik, Maharashtra, India

Machine translation, Indian Languages, Rule-based, Statistical, Knowledge-based, Hybrid Machine Translation, Interlingua-based MT

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 613-622
Manuscript Number : CSEIT1831102
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Namrata G Kharate, Dr. Varsha H. Patil, "Survey of Machine Translation for Indian Languages to English and Its Approaches", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.613-622, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT1831102

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