Abstract
Affect interpretation from story/dialogue context and metaphorical expressions is challenging but essential for the development of emotion inspired intelligent user interfaces. In order to achieve this research goal, we previously developed an AI actor with the integration of an affect detection component on detecting 25 emotions from literal text-based improvisational input. In this paper, we report updated development on metaphorical affect interpretation especially for sensory & cooking metaphors. Contextual affect detection with the integration of emotion modeling is also explored. Evaluation results for the new developments are provided. Our work benefits systems with intention to employ emotions embedded in the scenarios/characters and open-ended input for visual representation without detracting users from learning situations.
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Zhang, L., Barnden, J. (2011). Context-Sensitive Affect Sensing and Metaphor Identification in Virtual Drama. In: D’Mello, S., Graesser, A., Schuller, B., Martin, JC. (eds) Affective Computing and Intelligent Interaction. ACII 2011. Lecture Notes in Computer Science, vol 6975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24571-8_18
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DOI: https://doi.org/10.1007/978-3-642-24571-8_18
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