Towards English to Arabic Machine Translation
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Abstract
Nowadays, the understanding and generation of cognitive processes of natural language are becoming easier and better understood to
perform machine translation. In this paper, we develop a system of machine translation to translate from English to Arabic, which runs on PC
compatibles with English/Arabic interface. The system task was to analyze the natural language of English and Arabic to get accurate translation
based on reordering per sentence at least one time. It based on identifying the Part Of Speech (POS) for each word in sentence from English
dictionary, which used for reordering purpose. English dictionary also used to translate single word based on finding word meaning relative to
categories (POS). The transfer of English words order in sentence from English structure to Arabic structure based on synchronize words
between English and Arabic that based on matching between both language rules grammar. The meaning of words in sentences get from Bilingual
dictionary that used to translate single word consists of only word meaning relative to categories (POS). This system applies on abstracts
from European Psychiatry Journal domain that includes twenty (20) abstracts containing ninety five (95) sentences. The result obtained shows
that the reordering rules is 81.9% accuracy on a translation from English Language to Arabic using abstracts from the European Journal of
Psychiatry.
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Keywords: MT; Natural language processing; Part Of Speech; Reordering
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