Classical Arabic English machine translation using rule-based approach

Arabic machine translation has been taking place in machine translation projects during last decade and so, many projects have been carried out to enhance the quality of translation from and into Arabic. This research concentrates on the translation of Classical Arabic (CA) rather than Modern Standard Arabic. The challenges of this research are the difficulty of delivering the appropriate meaning of the CA terms in the target language (English), different sentence structure between two languages, word agreement and ordering problem. Focusing on these issues, the research purpose was to create an automatic translation system to translate text from CA into English using Rule-based approach. The developed system Classical Arabic Machine Translation (CAMT) involves three phases which are: analysis, transfer and generation. In the analysis phase the CA input text is analyzed morphologically and syntactically. The transfer stage includes constructing reasonable rule of the CA input text structure and its equivalent rule in the target language (English). In the final phase, the Arabic source text will be generated to obtain the target text in English. The evaluation process is done by comparing the output produced by our system with the original human translation using IBLEU metric. An accuracy of 89.4% was the results produced by IBLEU algorithm, which prove that using Rule-based approach provides good results in translating CA into English. © 2013 Asian Network for Scientific Information.