Using Knowledge of Misunderstandings to Increase the Robustness of Spoken Dialogue Systems Articles uri icon

publication date

  • julio 2010

start page

  • 471

end page

  • 485

issue

  • 5

volume

  • 23

international standard serial number (ISSN)

  • 0950-7051

electronic international standard serial number (EISSN)

  • 1872-7409

abstract

  • This paper proposes a new technique to increase the robustness of spoken dialogue systems employing an automatic procedure that aims to correct frames incorrectly generated by the system's component that deals with
    spoken language understanding. To do this the technique carries out a
    training that takes into account knowledge of previous system
    misunderstandings. The correction is transparent for the user as he is
    not aware of some mistakes made by the speech recogniser and thus
    interaction with the system can proceed more naturally. 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 increases sentence understanding by
    19.54%, task completion by 26.25%, word accuracy by 7.53%, and implicit
    recovery of speech recognition errors by 20.3%, whereas for the Viajero
    system these figures increase by 14.93%, 18.06%, 6.98% and 15.63%,
    respectively.