Model development project demonstrates automated grammatical error detection in Modern Standard Arabic, highlighting deep learning applications for complex Semitic language grammar.
Modern Standard Arabic (MSA) is the official language in the Arab world. It is a Semitic language that has rich and complex grammar. Arabic grammar rules are numerous and complicated and might cause confusions to both Arabic natives and learners. This confusion contributes to the proliferation of errors in written Arabic texts. Developing a system for automating error detection in Arabic writing could help produce better quality text. This paper presents a work-in-progress project for developing a web-based tool that performs Arabic Grammatical error detection by employing a deep learning model.
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Madi et al. (2018) studied this question.
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