Semantic-based affect and metaphor interpretation in virtual drama

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 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 context is used to interpret affect and recognize metaphorical phenomena. Our work contributes to the conference themes on emotion and affect and semantic-based dialogue processing. © 2012 Springer-Verlag.