Chester: towards a personal medication advisor

  • Authors:

  • James Allen;George Ferguson;Nate Blaylock;Donna Byron;Nathanael Chambers;Myroslava Dzikovska;Lucian Galescu;Mary Swift

  • Affiliations:

  • Department of Computer Science, University of Rochester, Rochester, NY;Department of Computer Science, University of Rochester, Rochester, NY;Department of Computational Linguistics, Saarland University, Saarbrücken, Germany;Department of Computer Science and Engineering, Ohio State University, Columbus, OH;Institute for Human-Machine Cognition, Pensacola, FL;Human Communication Research Centre, School of Informatics, University of Edinburgh, Edinburgh, Scotland, UK;Institute for Human-Machine Cognition, Pensacola, FL;Department of Computer Science, University of Rochester, Rochester, NY

  • Venue:
  • Journal of Biomedical Informatics - Special issue: Dialog systems for health communications
  • Year:
  • 2006

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Abstract

Dialogue systems for health communication hold out the promise of providing intelligent assistance to patients through natural interfaces that require no training to use. But in order to make the development of such systems cost effective, we must be able to use generic techniques and components which are then specialized as needed to the specific health problem and patient population. In this paper, we describe Chester, a prototype intelligent assistant that interacts with its user via conversational natural spoken language to provide them with information and advice regarding their prescribed medications. Chester builds on our prior experience constructing conversational assistants in other domains. The emphasis of this paper is on the portability of our generic spoken dialogue technology, and presents a case study of the application of these techniques to the development of a dialogue system for health communication.