Academy & Industry Research Collaboration Center (AIRCC)

Volume 11, Number 20, November 2021

Common Ground, Frames and Slots for Comprehension in Dialogue Systems

  Authors

Philippe Blache and Matthis Houlès, Laboratoire Parole et Langage, CNRS, Aix-en-Provence, France

  Abstract

This paper presents a dialogue system for training doctors to break bad news. The originality of this work lies in its knowledge representation. All information known before the dialogue (the universe of discourse, the context, the scenario of the dialogue) as well as the knowledge transferred from the doctor to the patient during the conversation is represented in a shared knowledge structure called common ground, that constitute the core of the system. The Natural Language Understanding and the Natural Language Generation modules of the system take advantage on this structure and we present in this paper different original techniques making it possible to implement them efficiently.

  Keywords

Dialogue systems, common ground, natural language understanding.