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Assessing French Readability for Adults with Low Literacy: A Global and Local Perspective

Title: Assessing French Readability for Adults with Low Literacy: A Global and Local Perspective
Authors: Aissa, Wafa; Bañeras-Roux, Thibault; Vanzeveren, Elodie; Gao, Lingyun; Souza Wilkens, Rodrigo; François, Thomas; 2025 Conference on Empirical Methods in Natural Language Processing
Contributors: UCL - SSH/ILC/PLIN - Pôle de recherche en linguistique; UCL - SSH/TALN - Centre de traitement automatique du langage
Publisher Information: Association for Computational Linguistics
Publication Year: 2025
Collection: DIAL@USL-B (Université Saint-Louis, Bruxelles)
Description: This study presents a novel approach to assessing French text readability for adults with low literacy skills, addressing both global (full-text) and local (segment-level) difficulty. We introduce a dataset of 461 texts annotated using a difficulty scale developed specifically for this population. Using this corpus, we conducted a systematic comparison of key readability modeling approaches, including machine learning techniques based on linguistic variables, fine-tuning of CamemBERT, a hybrid approach combining CamemBERT with linguistic variables, and the use of generative language models (LLMs) to carry out readability assessment at both global and local levels.
Document Type: conference object
Language: English
Relation: info:eu-repo/grantAgreement/European Commission/HORIZON- CL2-2022-TRANSFORMATIONS-01-07/1010094837; info:eu-repo/grantAgreement/FNRS/PDR/40013622; boreal:310339; https://hdl.handle.net/2078.1/310339
DOI: 10.18653/v1/2025.emnlp-main.1036
Availability: https://hdl.handle.net/2078.1/310339; https://doi.org/10.18653/v1/2025.emnlp-main.1036
Rights: info:eu-repo/semantics/openAccess
Accession Number: edsbas.E9B7C535
Database: BASE