Cognitively motivated features for readability assessment

  • Authors:
  • Lijun Feng;Noémie Elhadad;Matt Huenerfauth

  • Affiliations:
  • The City University of New York, New York, NY;Columbia University, New York, NY;The City University of New York, New York, NY

  • Venue:
  • EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
  • Year:
  • 2009

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Abstract

We investigate linguistic features that correlate with the readability of texts for adults with intellectual disabilities (ID). Based on a corpus of texts (including some experimentally measured for comprehension by adults with ID), we analyze the significance of novel discourse-level features related to the cognitive factors underlying our users' literacy challenges. We develop and evaluate a tool for automatically rating the readability of texts for these users. Our experiments show that our discourse-level, cognitively-motivated features improve automatic readability assessment.