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Measuring text readability with machine comprehension: a pilot study

Marc Benzahra 1 François Yvon 1
1 TLP - Traitement du Langage Parlé
LIMSI - Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur : 247329
Abstract : This article studies the relationship between text readability indice and automatic machine understanding systems. Our hypothesis is that the simpler a text is, the better it should be understood by a machine. We thus expect to a strong correlation between readability levels on the one hand, and performance of automatic reading systems on the other hand. We test this hypothesis with several understanding systems based on language models of varying strengths, measuring this correlation on two corpora of journalistic texts. Our results suggest that this correlation is rather small that existing comprehension systems are far to reproduce the gradual improvement of their performance on texts of decreasing complexity.
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Submitted on : Monday, August 19, 2019 - 2:18:36 PM
Last modification on : Monday, February 10, 2020 - 6:14:12 PM
Document(s) archivé(s) le : Thursday, January 9, 2020 - 2:55:29 PM


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  • HAL Id : hal-02267546, version 1


Marc Benzahra, François Yvon. Measuring text readability with machine comprehension: a pilot study. Workshop on Building Educational Applications Using NLP, Aug 2019, Florence, Italy. pp.412 - 422. ⟨hal-02267546⟩



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