TSD 2010: Text, Speech and Dialogue pp 523-530 | Cite as

Using Knowledge about Misunderstandings to Increase the Robustness of Spoken Dialogue Systems

  • Ramón López-Cózar
  • Zoraida Callejas
  • Nieves Ábalos
  • Gonzalo Espejo
  • David Griol
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6231)

Abstract

This paper proposes a new technique to enhance the performance of spoken dialogue systems employing a method that automatically corrects semantic frames which are incorrectly generated by the semantic analyser of these systems. Experiments have been carried out using two spoken dialogue systems previously developed in our lab: Saplen and Viajero, which employ prompt-dependent and prompt-independent language models for speech recognition. The results obtained from 10,000 simulated dialogues show that the technique improves the performance of the two systems for both kinds of language modelling, especially for the prompt-independent language model. Using this type of model the Saplen system increased sentence understanding by 19.54%, task completion by 26.25%, word accuracy by 7.53%, and implicit recovery of speech recognition errors by 20.30%, whereas for the Viajero system these figures increased by 14.93%, 18.06%, 6.98% and 15.63%, respectively.

Keywords

Spoken dialogue systems speech recognition spoken language understanding user simulation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ramón López-Cózar
    • 1
    • 2
  • Zoraida Callejas
    • 1
    • 2
  • Nieves Ábalos
    • 1
    • 2
  • Gonzalo Espejo
    • 1
    • 2
  • David Griol
    • 1
    • 2
  1. 1.Dept. of LSI, CITIC-UGRUniversity of GranadaSpain
  2. 2.Dept. of Computer ScienceCarlos III University of MadridSpain

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