Leveraging Large Language Models for Joint Linguistic and Technical Accessibility Improvement: A Case Study on University Webpages

Pierrette Bouillon, Johanna Gerlach, Raphael Rubino


Abstract
The aim of the study presented in this paper is to investigate whether Large Language Models can be leveraged to translate French content from existing websites into their B1-level simplified versions and to integrate them into an accessible HTML structure. We design a CMS agnostic approach to webpage accessibility improvement based on prompt engineering and apply it to Geneva University webpages. We conduct several automatic and manual evaluations to measure the accessibility improvement reached by several LLMs with various prompts in a zero-shot setting. Results show that LLMs are not all suitable for the task, while a large disparity is observed among results reached by different prompts. Manual evaluation carried out by a dyslexic crowd shows that some LLMs could produce more accessible websites and improve access to information.
Anthology ID:
2025.aielpl-1.1
Volume:
Proceedings of the 1st Workshop on Artificial Intelligence and Easy and Plain Language in Institutional Contexts (AI & EL/PL)
Month:
June
Year:
2025
Address:
Geneva, Switzerland
Editors:
María Isabel Rivas Ginel, Patrick Cadwell, Paolo Canavese, Silvia Hansen-Schirra, Martin Kappus, Anna Matamala, Will Noonan
Venue:
AIELPL
SIG:
Publisher:
European Association for Machine Translation
Note:
Pages:
1–13
Language:
URL:
https://aclanthology.org/2025.aielpl-1.1/
DOI:
Bibkey:
Cite (ACL):
Pierrette Bouillon, Johanna Gerlach, and Raphael Rubino. 2025. Leveraging Large Language Models for Joint Linguistic and Technical Accessibility Improvement: A Case Study on University Webpages. In Proceedings of the 1st Workshop on Artificial Intelligence and Easy and Plain Language in Institutional Contexts (AI & EL/PL), pages 1–13, Geneva, Switzerland. European Association for Machine Translation.
Cite (Informal):
Leveraging Large Language Models for Joint Linguistic and Technical Accessibility Improvement: A Case Study on University Webpages (Bouillon et al., AIELPL 2025)
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PDF:
https://aclanthology.org/2025.aielpl-1.1.pdf