Word agreement and ordering in english-arabic machine translation

Abstract

Machine Translation has been defined as the process that utilizes computer software to translate text from one natural language to another. This definition involves accounting for the grammatical structure of each language and using rules and grammars to transfer the grammatical structure of the source language (SL) into the target language (TL). Agreement and Word-ordering play an important role with this structure, as MT should handle agreement between the subject and verb where the number gender, person and features of the subject are important factors in the derivation of the verb as s well as the features of the verb itself. Other agreements are required between the adjective and the noun where Arabic adjectives depend on the number, gender and person as well as the definiteness and indefiniteness of the noun. Some other agreements also exist between the numbers and the countable nouns. This paper examines the agreement and word-order rules hi tackling Arabic MT systems. Special attention is given to Tarjim by Sakhr Software Company which pioneered a new generation of Arabic Natural Language Processing (NLP) technologies. The approach adopted is flexible and scalable, and the main advantages are first, it is a rule-based approach, and second, it can be applied on other languages with minor modifications. A major design goal of this system is that it can be used as a stand-alone tool and can be very well integrated with a general machine translation system for English sentence.