Readability assessment for text simplification

  • Authors:
  • Sandra Aluisio;Lucia Specia;Caroline Gasperin;Carolina Scarton

  • Affiliations:
  • University of São Paulo, São Carlos - SP, Brazil;University of Wolverhampton, Wolverhampton, UK;University of São Paulo, São Carlos - SP, Brazil;University of São Paulo, São Carlos - SP, Brazil

  • Venue:
  • IUNLPBEA '10 Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications
  • Year:
  • 2010

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Abstract

We describe a readability assessment approach to support the process of text simplification for poor literacy readers. Given an input text, the goal is to predict its readability level, which corresponds to the literacy level that is expected from the target reader: rudimentary, basic or advanced. We complement features traditionally used for readability assessment with a number of new features, and experiment with alternative ways to model this problem using machine learning methods, namely classification, regression and ranking. The best resulting model is embedded in an authoring tool for Text Simplification.