Are Cohesive Features Relevant for Text Readability Evaluation?

Amalia Todirascu, Thomas François, Delphine Bernhard, Núria Gala, Anne-Laure Ligozat


Abstract
This paper investigates the effectiveness of 65 cohesion-based variables that are commonly used in the literature as predictive features to assess text readability. We evaluate the efficiency of these variables across narrative and informative texts intended for an audience of L2 French learners. In our experiments, we use a French corpus that has been both manually and automatically annotated as regards to co-reference and anaphoric chains. The efficiency of the 65 variables for readability is analyzed through a correlational analysis and some modelling experiments.
Anthology ID:
C16-1094
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Yuji Matsumoto, Rashmi Prasad
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
987–997
Language:
URL:
https://aclanthology.org/C16-1094
DOI:
Bibkey:
Cite (ACL):
Amalia Todirascu, Thomas François, Delphine Bernhard, Núria Gala, and Anne-Laure Ligozat. 2016. Are Cohesive Features Relevant for Text Readability Evaluation?. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 987–997, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Are Cohesive Features Relevant for Text Readability Evaluation? (Todirascu et al., COLING 2016)
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PDF:
https://preview.aclanthology.org/landing_page/C16-1094.pdf