Context-sensitive affect sensing and metaphor identification in virtual drama

Li Zhang, John Barnden

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

1 Citation (Scopus)

Abstract

Affect interpretation from story/dialogue context and metaphorical expressions is challenging but essential for the development of emotion inspired intelligent user interfaces. In order to achieve this research goal, we previously developed an AI actor with the integration of an affect detection component on detecting 25 emotions from literal text-based improvisational input. In this paper, we report updated development on metaphorical affect interpretation especially for sensory & cooking metaphors. Contextual affect detection with the integration of emotion modeling is also explored. Evaluation results for the new developments are provided. Our work benefits systems with intention to employ emotions embedded in the scenarios/characters and open-ended input for visual representation without detracting users from learning situations.
Original languageEnglish
Title of host publicationAffective Computing and Intelligent Interaction
PublisherSpringer
Pages173-182
Volume6975
ISBN (Electronic)978-3-642-24571-8
ISBN (Print)978-3-642-24570-1
DOIs
Publication statusPublished - 2011

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume6975

Keywords

  • affect detection/sensing
  • metaphor
  • emotion modeling and context

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