Machine Translation by Homograph Detector with the Help of Grammatical Base of Persian Words

Prof. Dr. Zafer Agdelen; Dr. Amir Reza Shahbazkia

Journal Title:International Journal of Computer Science and Mobile Computing - IJCSMC
Abstract

Language is core medium of communication and translation is core tool for the understand the information in unknown language. Machine translation helps the people to understand the information of unknown language without the help of Human translator. This study is brief introduction to machine Translation and the solution for homographs. machine translation have been developed for many popular languages and many researches and developments have been applied to those languages but a significant problem in Persian (the language of Iranian, Afghani, etc.) is detecting the homographs which is not generally problematic in any other languages except Arabic. Detection of homographs in Arabic have been extensively studied. However Persian and Arabic share 28 characters, having only 4 different characters, they are two quite different languages. Homographs, words with same spelling and different translations are more problematic to detect in Persian because not all the pronounced vowels are written in the text (only 20% of vowels are written in the text) so the number of homographs in Persian is about thousands of times more than in other languages except Arabic. In this paper we propose a new method for analysis and finding exact translation for homographs by algorithmic and grammatical rules.

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