Affect detection and metaphor in e-drama

Li Zhang, John Barnden, Robert Hendley, Mark G. Lee, Alan Wallington, Zhigang Wen

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

We report work on adding affect-detection to an existing e-drama programme, a text-based software system for (human) dramatic improvisation in simple virtual scenarios, for use primarily in learning contexts. The system allows a human director to monitor improvisations and make interventions, for instance in reaction to excessive, insufficient or inappropriate emotions in the characters' speeches. Within an endeavour to partially automate directors' functions, and to allow for automated affective bit part characters, we have developed an affect-detection module. It is aimed at detecting affective aspect (concerning emotions, moods, rudeness, value judgments, etc.) of human-controlled characters' textual 'speeches'. The work also accompanies basic research into how affect is conveyed linguistically. A distinctive feature of the project is a focus on the metaphorical ways in which affect is conveyed. The project addresses the special issue themes such as making interactive narrative learning environments more usable, building them, and supporting reflection on narrative construction.
Original languageEnglish
Pages (from-to)234-252
JournalInternational Journal of Continuing Engineering Education and Life-Long Learning
Volume18
Issue number2
DOIs
Publication statusPublished - 2008

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