Grammar-based and example-based techniques in machine translation from English to Arabic

In the modern world, there is an increased need for language translation. This paper presents English to Arabic approach for translating well-structured English sentences into well-structured Arabic sentences, using a grammar-based and example-translation techniques to handle the problems of ordering and agreement. This technique combines rule-based MT (RBMT) and example-based MT (EBMT) which is called hybrid-based MT (HERBMT). The proposed methodology is flexible and scalable. The main advantages of HERBMT are that it combines the advantages of RBMT and EBMT, and it can be applied to other languages with minor modifications. EBMT extracts an example of target language sentences that are analogous to input source language sentences. The extraction of appropriate translated sentences is preceded by an analysis stage for the decomposition of input sentences into appropriate fragments. RBMT is used when examples of the source language to be translated into the target language are not found in the machine database. The OAK Parser is used to analyze the input English text to get the part of speech (POS) for each word in the text as a pre-translation process. A major design goal of this system is that it will be used as a stand-alone tool, and can be integrated with a general machine translation system for English sentences. The evaluation is carried out on 250 independent test suites, and the analysis indicates that HERBMT achieved good performance with an average of 97.2% precision.