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A Turing Test to Evaluate a Complex Summarization Task

  • Alejandro Molina
  • Eric SanJuan
  • Juan-Manuel Torres-Moreno
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8138)

Abstract

This paper deals with a new strategy to evaluate a Natural Language Processing (NLP) complex task using the Turing test. Automatic summarization based on sentence compression requires to asses informativeness and modify inner sentence structures. This is much more intrinsically related with real rephrasing than plain sentence extraction and ranking paradigm so new evaluation methods are needed. We propose a novel imitation game to evaluate Automatic Summarization by Compression (ASC). Rationale of this Turing-like evaluation could be applied to many other NLP complex tasks like Machine translation or Text Generation. We show that a state of the art ASC system can pass such a test and simulate a human summary in 60% of the cases.

Keywords

Natural Language Processing Machine Translation Turing Test Simulation Game Human Player 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alejandro Molina
    • 1
  • Eric SanJuan
    • 1
    • 2
  • Juan-Manuel Torres-Moreno
    • 1
    • 2
    • 3
  1. 1.LIAUniversité d’Avignon et des Pays de VaucluseAvignon Cedex 9France
  2. 2.Brain & Language Research InstituteAix-en-Provence Cedex 1France
  3. 3.École Polytechnique de MontréalMontréalCanada

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