Affect detection from text-based virtual improvisation and emotional gesture recognition

Zhang, Li and Yap, Bryan (2012) Affect detection from text-based virtual improvisation and emotional gesture recognition. Advances in Human-Computer Interaction, 2012. ISSN 1687 5893

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We have developed an intelligent agent to engage with users in virtual drama improvisation previously. The intelligent agent was able to perform sentence-level affect detection from user inputs with strong emotional indicators. However, we noticed that many inputs with weak or no affect indicators also contain emotional implication but were regarded as neutral expressions by the previous interpretation. In this paper, we employ latent semantic analysis to perform topic theme detection and identify target audiences for such inputs. We also discuss how such semantic interpretation of the dialog contexts is used to interpret affect more appropriately during virtual improvisation. Also, in order to build a reliable affect analyser, it is important to detect and combine weak affect indicators from other channels such as body language. Such emotional body language detection also provides a nonintrusive channel to detect users' experience without interfering with the primary task. Thus, we also make initial exploration on affect detection from several universally accepted emotional gestures.

Item Type: Article
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 21 Jan 2015 13:05
Last Modified: 13 Oct 2019 00:31

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