research-article

Approaches, Methods, and Resources for Assessing the Readability of Arabic Texts

Authors:

Naoual Nassiri,

Violetta Cavalli-Sforza,

Abdelhak LakhouajaAuthors Info & Claims

ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 22, Issue 4

Article No.: 95, Pages 1 - 30

https://doi.org/10.1145/3571510

Published: 25 March 2023 Publication History

Abstract

Text readability assessment is a well-known problem that has acquired even more importance in today’s information-rich world. In this article, we survey various approaches to measuring and assessing the readability of texts. Our specific goal is to provide a perspective on the state-of-the-art in readability assessment research for Arabic, which differs significantly from other languages on which readability studies have tended to focus. We provide background on readability assessment research and tools for English, for which readability studies are the most advanced. We then survey approaches adopted for Arabic, both classical formula-based approaches and studies that combine Machine Learning (ML) with Natural Language Processing (NLP) techniques. The works we cover target text corpora for different audiences: school-age first language readers (L1), foreign language learners (L2), and adult readers in non-academic contexts. Therefore, we explore differences between reading in L1 and L2 and consider how they play out specifically in Arabic after describing language characteristics that may impact readability. Finally, we highlight challenges for Arabic readability research and propose multiple future directions to improve readability assessment and related applications that would benefit from more attention.

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Index Terms

Approaches, Methods, and Resources for Assessing the Readability of Arabic Texts
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 22, Issue 4

April 2023

682 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3588902

Editor:
Imed Zitouni
Google, USA

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Publication History

Published: 25 March 2023

Online AM: 17 November 2022

Accepted: 06 November 2022

Revised: 15 September 2022

Received: 13 September 2021

Published in TALLIP Volume 22, Issue 4

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