Real-time affect detection from open-ended text-based dialogue is challenging but essential for the building of effective intelligent user interfaces. In this paper, we report updated developments of an affect detection model from text, including affect detection from one particular type of metaphorical affective expression (cooking metaphor) and affect detection based on context. The overall affect detection model has been embedded in an intelligent conversational AI agent interacting with human users under loose scenarios. Evaluation for the updated affect detection component is also provided. Our work contributes to the conference themes on engagement and emotion, interactions in games, storytelling and narrative in education, and virtual characters/agents development.
|Title of host publication||Transactions on Edutainment IV|
|Editors||Zhigeng Pan, Adrian David Cheok, Wolfgang Müller, Xiaopeng Zhang, Kevin Wong|
|Place of Publication||London|
|Publication status||Published - 28 Aug 2010|
|Name||Lecture notes in Computer Science|