A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions

Hamed, Injy, Sabty, Caroline, Abdennadher, Slim, Vu, Ngoc Thang, Solorio, Thamar, Habash, Nizar

arXiv.org Artificial Intelligence 

Language in the Arab world presents a complex diglossic and multilingual setting, involving the use of Modern Standard Arabic, various dialects and sub-dialects, as well as multiple European languages. This diverse linguistic landscape has given rise to code-switching, both within Arabic varieties and between Arabic and foreign languages. The widespread occurrence of code-switching across the region makes it vital to address these linguistic needs when developing language technologies. In this paper, we provide a review of the current literature in the field of code-switched Arabic NLP, offering a broad perspective on ongoing efforts, challenges, research gaps, and recommendations for future research directions.

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