Affect and Semantic Interpretation of Virtual Drama

Zhang, Li and Barnden, John (2014) Affect and Semantic Interpretation of Virtual Drama. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 136. pp. 26-35. ISSN 1867-8211

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.1007/978-3-319-08189-2_4

Abstract

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 especially from user inputs with strong emotional indicators. However, we noticed that emotional expressions are diverse and many inputs with weak or no affect indicators also contain emotional indications but were regarded as neutral expressions by the previous processing. In this paper, we employ latent semantic analysis to perform topic theme detection and intended audience identification for such inputs. Then we also discuss how affect is detected for such inputs without strong emotional linguistic features with the consideration of emotions expressed by the most intended audiences and interpersonal relationships between speakers and audiences. Moreover, uncertainty-based active learning is also employed in this research in order to deal with more open-ended and imbalanced affect detection tasks within or going beyond the selected scenarios. Overall, the work presented here enables the intelligent agent to derive the underlying semantic structures embedded in emotional expressions and deal with challenging issues in affect detection tasks.

Item Type: Article
Uncontrolled Keywords: Affect detection, semantic interpretation and drama improvisation
Subjects: G700 Artificial Intelligence
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 11 Sep 2014 08:41
Last Modified: 13 Oct 2019 00:36
URI: http://nrl.northumbria.ac.uk/id/eprint/17572

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics