Toward building a comprehensive phrase-based English Arabic statistical machine translation system

الملخص EN

This paper explores a phrase-based statistical machine translation (PBSMT) pipeline for English-Arabic (En-Ar) language pair.

The work surveys the most recent experiments conducted to enhance Arabic machine translation in the En-Ar direction.

It also focuses on free datasets and linguistically motivated ideas that enhance phrase-based En-Ar statistical machine translation (SMT) as it is as aims to use those only in order to build a large scale En-Ar SMT system.

In addition, the paper highlights Arabic linguistic challenges in Machine Translation (MT) in general.

This paper can be considered a guide for building an En-Ar PBSMT system.

Furthermore, the presented pipeline can be generalized to any language pairs.