CLJan 23, 2025

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

arXiv:2501.13419v121 citationsh-index: 39COLING
Originality Synthesis-oriented
AI Analysis

This survey helps researchers and developers address linguistic needs in the Arab world, but it is incremental as it reviews existing work rather than presenting new methods.

The paper reviews literature on code-switched Arabic NLP, addressing the complex diglossic and multilingual setting in the Arab world, and identifies ongoing efforts, challenges, research gaps, and future directions.

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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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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