Emotional reading of medical texts using conversational agents

ABSTRACT

In this paper, we present a prototype that helps visualizing the relative importance of sentences extracted from medical texts using Embodied Conversational Agents (ECA). We propose to map rhetorical structures automatically recognized in the documents onto a set of communicative acts controlling the expression of an ECA. As a consequence, the ECA will dramatize a sentence to reflect its perceived importance and rhetorical strength (advice, requirement, open proposal, etc). This prototype is constituted of three sub-systems: i) G-DEE, a text analysis module ii) a mapping module which converts rhetorical structures produced by the text analysis module into communicative functions driving the ECA animation and iii) an ECA system. By bringing the text to life, this system could help their authors (in our application, expert physicians) to reflect on the potential impact of the writing style they have adopted. The use of ECA reintroduces an affective element which cannot easily be captured by other methods for analyzing document's style.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.1 Multimedia Information Systems
          Subjects: Animations

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence

  J. Computer Applications
  J.3 LIFE AND MEDICAL SCIENCES

General Terms:
Algorithms, Human Factors

Keywords:
document engineering, embodied conversational agents, markup languages