Example-Based English to Arabic Machine Translation: Matching Stage Using Internal Medicine Publications

Abstract

Automatic machine translation becomes an important source of translation nowadays. It is a software system that translates a text from one natural language to one (many) natural language. On the web, there are many machine translation systems that give the reasonable translation, although the systems are not very good. Medical records contain complex information that must be translated correctly according to its medical meaning not its English meaning only. So, the quality of a machine translation in this domain is very important. In this paper, we present using matching stage from Example-Based Machine Translation technique to translate a medical text from English as source language to Arabic as the target language. We have used 259 medical sentences that are extracted from internal medicine publications for our system. Experimental results on BLUE metrics showed a decreased performance 0.486 comparing to GOOGLE translation which has an accuracy result about 0.536.