Exploration of Metaphorical and Contextual Affect Sensing in a Virtual Improvisational Drama

Li Zhang

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)


Real-time affect detection from open-ended text-based dialogue is challenging but essential for the building of effective intelligent user interfaces. In this paper, we report updated developments of an affect detection model from text, including affect detection from one particular type of metaphorical affective expression (cooking metaphor) and affect detection based on context. The overall affect detection model has been embedded in an intelligent conversational AI agent interacting with human users under loose scenarios. Evaluation for the updated affect detection component is also provided. Our work contributes to the conference themes on engagement and emotion, interactions in games, storytelling and narrative in education, and virtual characters/agents development.
Original languageEnglish
Title of host publicationTransactions on Edutainment IV
EditorsZhigeng Pan, Adrian David Cheok, Wolfgang Müller, Xiaopeng Zhang, Kevin Wong
Place of PublicationLondon
ISBN (Print)978-3642144837
Publication statusPublished - 28 Aug 2010

Publication series

NameLecture notes in Computer Science
ISSN (Electronic)0302-9743


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