BLISS: An agent for collecting spoken dialogue data about health and well-being

Jelte van Waterschoot*, Iris Hendrickx, Arif Khan, Esther Klabbers, Marcel de Korte, Helmer Strik, Catia Cucchiarini, Mariët Theune

*Corresponding author for this work

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Abstract

An important objective in health-technology is the ability to gather information about people's well-being. Structured interviews can be used to obtain this information, but these are time-consuming and not scalable. Questionnaires provide an alternative way to extract such information, yet they typically lack depth. In this paper, we present our first prototype of the Behaviour-based Language-Interactive Speaking Systems (BLISS), an artificial intelligent agent which intends to automatically discover what makes people happy and healthy. The goal of BLISS is to understand the motivations behind people's happiness by conducting a personalized spoken dialogue based on a happiness model. We built our first prototype of the model to collect 55 spoken dialogues, in which the BLISS agent asked questions to users about their happiness and well-being. Apart from a description of the BLISS architecture, we also provide details about our dataset, which contains mentions of over 120 activities and 100 motivations and is made available for usage.

Original languageEnglish
Title of host publicationProceedings of the12th International Conference on Language Resources and Evaluation (LREC 2020)
EditorsNicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
PublisherEuropean Language Resources Association (ELRA)
Pages449-458
Number of pages10
ISBN (Electronic)9791095546344
Publication statusPublished - 2020

Keywords

  • Conversational
  • Happiness model
  • Healthcare
  • Natural language generation
  • Spoken dialogue system
  • Spoken Dutch

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