Revisiting Common Assumptions about Arabic Dialects in NLP

Arabic has diverse dialects, where one dialect can be substantially different from the others.In the NLP literature, some assumptions about these dialects are widely adopted (e.g., "Arabic dialects can be grouped into distinguishable regional dialects") and are manifested in different computational tasks such as Arabic Dialect Identification (ADI).However, these assumptions are not quantitatively verified.We identify four of these assumptions and examine them by extending and analyzing a multi-label dataset, where the validity of each sentence in 11 different country-level dialects is manually assessed by speakers of these dialects.Our analysis indicates that the four assumptions oversimplify reality, and some of them are not always accurate.This in turn might be hindering further progress in different Arabic NLP tasks.

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Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.acl-long.166
Citations
1
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
2.48

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article

Revisiting Common Assumptions about Arabic Dialects in NLP

Amr Keleg, Walid Magdy, Sharon Goldwater
1 citations
Natural Language Processing Techniques
2.48
article

Revisiting Common Assumptions about Arabic Dialects in NLP

Amr Keleg, Walid Magdy, Sharon Goldwater
article en
1 citations

Abstract

Arabic has diverse dialects, where one dialect can be substantially different from the others.In the NLP literature, some assumptions about these dialects are widely adopted (e.g., "Arabic dialects can be grouped into distinguishable regional dialects") and are manifested in different computational tasks such as Arabic Dialect Identification (ADI).However, these assumptions are not quantitatively verified.We identify four of these assumptions and examine them by extending and analyzing a multi-label dataset, where the validity of each sentence in 11 different country-level dialects is manually assessed by speakers of these dialects.Our analysis indicates that the four assumptions oversimplify reality, and some of them are not always accurate.This in turn might be hindering further progress in different Arabic NLP tasks.

Language Science (South Korea) (KR)
UK Research and Innovation
Quality Education
Openalex Percentile: Top 9%
Natural Language Processing Techniques
2.48
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