Affect sensing and contextual affect modeling from improvisational interaction

Zhang, Li (2011) Affect sensing and contextual affect modeling from improvisational interaction. International Journal of Computational Linguistics, 1 (4). pp. 45-60. ISSN 2180-1266

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We report work on adding an improvisational AI actor to an existing virtual improvisational environment, a text-based software system for dramatic improvisation in simple virtual scenarios, for use primarily in learning contexts. The improvisational AI actor has an affect-detection component which is aimed at detecting affective aspects (concerning emotions, moods, value judgements, etc) of human-controlled characters' textual "speeches". The AI actor will also make an appropriate response based on this affective understanding, which intends to stimulate the improvisation. 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. Moreover, we have also introduced affect detection using context profiles. Finally, we have reported user testing conducted for the improvisational AI actor and evaluation results of the affect detection component. Our work contributes to the journal themes on affective user interfaces, affect sensing and improvisational or dramatic natural language interaction.

Item Type: Article
Uncontrolled Keywords: affect detection, metaphorical language, intelligent conversational agents, dramatic improvisation and context profiles
Subjects: G400 Computer Science
G700 Artificial Intelligence
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Ay Okpokam
Date Deposited: 12 Dec 2011 12:51
Last Modified: 13 Oct 2019 00:31

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