Affective computing
Integrating models of personality and emotions into lifelike characters
Affective interactions
Analysis of emotion recognition using facial expressions, speech and multimodal information
Proceedings of the 6th international conference on Multimodal interfaces
ALMA: a layered model of affect
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
A conversational agent as museum guide: design and evaluation of a real-world application
Lecture Notes in Computer Science
Computer Speech and Language
Multimodal emotion classification in naturalistic user behavior
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: towards mobile and intelligent interaction environments - Volume Part III
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The detection of user emotions plays an important role in Human-Machine-Interaction. By considering emotions, applications such as monitoring agents or digital companions are able to adapt their reaction towards users' needs and claims. Besides emotions, personality and moods are eminent as well. Standard emotion recognizers do not consider them adequately and therefore neglect a crucial part of user modeling. The challenge is to gather reliable predictions about the actual mood of the user and, beyond that, represent changes in users' mood during interaction. In this paper we present a model that incorporates both the tracking of mood changes based on recognized emotions and different personality traits. Furthermore we present a first evaluation on realistic data.