Learning to Simplify Children Stories with Limited Data

  • Tu Thanh Vu
  • Giang Binh Tran
  • Son Bao Pham
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8397)

Abstract

In this paper, we examine children stories and propose a text simplification system to automatically generate simpler versions of the stories and, therefore, make them easier to understand for children, especially ones with difficulty in reading comprehension. Our system learns simplifications from limited data built from a small repository of short English stories for children and can perform important simplification operations, namely splitting, dropping, reordering, and substitution. Our experiment shows that our system outperforms other systems in a variety of automatic measures as well as human judgements with regard to simplicity, grammaticality, and semantic similarity.

Keywords

text simplification readability comparable corpora 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Tu Thanh Vu
    • 1
  • Giang Binh Tran
    • 2
  • Son Bao Pham
    • 1
  1. 1.University of Engineering and TechnologyVietnam National UniversityHanoiVietnam
  2. 2.L3S Research CenterGermany

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