Towards Sentence-level Text Readability Assessment for French

Duy Van Ngo, Yannick Parmentier


Abstract
In this paper, we report on some experiments aimed at exploring the relation between document-level and sentence-level readability assessment for French. These were run on an open-source tailored corpus, which was automatically created by aggregating various sources from children’s literature. On top of providing the research community with a freely available corpus, we report on sentence readability scores obtained when applying both classical approaches (aka readability formulas) and state-of-the-art deep learning techniques (e.g. fine-tuning of large language models). Results show a relatively strong correlation between document-level and sentence-level readability, suggesting ways to reduce the cost of building annotated sentence-level readability datasets.
Anthology ID:
2023.tsar-1.8
Volume:
Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability
Month:
September
Year:
2023
Address:
Varna, Bulgaria
Editors:
Sanja Štajner, Horacio Saggio, Matthew Shardlow, Fernando Alva-Manchego
Venues:
TSAR | WS
SIG:
Publisher:
INCOMA Ltd., Shoumen, Bulgaria
Note:
Pages:
78–84
Language:
URL:
https://aclanthology.org/2023.tsar-1.8
DOI:
Bibkey:
Cite (ACL):
Duy Van Ngo and Yannick Parmentier. 2023. Towards Sentence-level Text Readability Assessment for French. In Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability, pages 78–84, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
Cite (Informal):
Towards Sentence-level Text Readability Assessment for French (Ngo & Parmentier, TSAR-WS 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.tsar-1.8.pdf