Predicting user mental states in spoken dialogue systems View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-12

AUTHORS

Zoraida Callejas, David Griol, Ramón López-Cózar

ABSTRACT

In this paper we propose a method for predicting the user mental state for the development of more efficient and usable spoken dialogue systems. This prediction, carried out for each user turn in the dialogue, makes it possible to adapt the system dynamically to the user needs. The mental state is built on the basis of the emotional state of the user and their intention, and is recognized by means of a module conceived as an intermediate phase between natural language understanding and the dialogue management in the architecture of the systems. We have implemented the method in the UAH system, for which the evaluation results with both simulated and real users show that taking into account the user's mental state improves system performance as well as its perceived quality. More... »

PAGES

6

References to SciGraph publications

  • 2008. Two-Level Fusion to Improve Emotion Classification in Spoken Dialogue Systems in TEXT, SPEECH AND DIALOGUE
  • 2010. A Methodology for Learning Optimal Dialog Strategies in TEXT, SPEECH AND DIALOGUE
  • 2006-12. Testing the performance of spoken dialogue systems by means of an artificially simulated user in ARTIFICIAL INTELLIGENCE REVIEW
  • 2008-12. Mental states as multi-context systems in ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE
  • 2008. Adaptive Dialogue Management in the NIMITEK Prototype System in PERCEPTION IN MULTIMODAL DIALOGUE SYSTEMS
  • 2010-03. Emotion recognition and adaptation in spoken dialogue systems in INTERNATIONAL JOURNAL OF SPEECH TECHNOLOGY
  • 2005. Grounding Emotions in Human-Machine Conversational Systems in INTELLIGENT TECHNOLOGIES FOR INTERACTIVE ENTERTAINMENT
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/1687-6180-2011-6

    DOI

    http://dx.doi.org/10.1186/1687-6180-2011-6

    DIMENSIONS

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