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Translation of Telugu-Marathi and Vice-Versa Using Rule Based Machine Translation

Authors

Siddhartha Ghosh, Sujata Thamke and Kalyani U.R.S, KMIT, India

Abstract

In today’s digital world automated Machine Translation of one language to another has covered a long way to achieve different kinds of success stories. Whereas Babel Fish supports a good number of foreign languages and only Hindi from Indian languages, the Google Translator takes care of about 10 Indian languages. Though most of the Automated Machine Translation Systems are doing well but handling Indian languages needs a major care while handling the local proverbs/ idioms. Most of the Machine Translation system follows the direct translation approach while translating one Indian language to other. Our research at KMIT R&D Lab found that handling the local proverbs/idioms is not given enough attention by the earlier research work. This paper focuses on two of the majorly spoken Indian languages Marathi and Telugu, and translation between them. Handling proverbs and idioms of both the languages have been given a special care, and the research outcome shows a significant achievement in this direction.

Keywords

Machine Translation, NLP, Parts Of Speech, Indian Languages.

Full Text  Volume 4, Number 5