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Personality-Dependent Referring Expression Generation

  • Ivandré ParaboniEmail author
  • Danielle Sampaio Monteiro
  • Alex Gwo Jen Lan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10415)

Abstract

This paper addresses the issue of how Big Five personality traits may influence the content selection task in Referring Expression generation (REG.) To this end, we build a corpus of referring expressions annotated with personality information, and then use it as the input to a machine learning approach to REG that takes the personality of the target speakers into account. Results show that personality-dependent REG outperforms standard REG algorithms, and that it may be a viable alternative to speaker-dependent approaches that require examples of descriptions produced by every individual under consideration.

Keywords

Text generation Referring expressions Big five personality traits 

Notes

Acknowledgements

This work has been supported by FAPESP grant 2016/14223-0.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ivandré Paraboni
    • 1
    Email author
  • Danielle Sampaio Monteiro
    • 1
  • Alex Gwo Jen Lan
    • 1
  1. 1.School of Arts, Sciences and HumanitiesUniversity of São PauloSão PauloBrazil

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