@inproceedings{ngo-parmentier-2023-towards,
title = "Towards Sentence-level Text Readability Assessment for {F}rench",
author = "Ngo, Duy Van and
Parmentier, Yannick",
editor = "{\v{S}}tajner, Sanja and
Saggio, Horacio and
Shardlow, Matthew and
Alva-Manchego, Fernando",
booktitle = "Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.tsar-1.8",
pages = "78--84",
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.",
}
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%0 Conference Proceedings
%T Towards Sentence-level Text Readability Assessment for French
%A Ngo, Duy Van
%A Parmentier, Yannick
%Y Štajner, Sanja
%Y Saggio, Horacio
%Y Shardlow, Matthew
%Y Alva-Manchego, Fernando
%S Proceedings of the Second Workshop on Text Simplification, Accessibility and Readability
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F ngo-parmentier-2023-towards
%X 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.
%U https://aclanthology.org/2023.tsar-1.8
%P 78-84
Markdown (Informal)
[Towards Sentence-level Text Readability Assessment for French](https://aclanthology.org/2023.tsar-1.8) (Ngo & Parmentier, TSAR-WS 2023)
ACL