Abstract
In this demonstration, we present an implementation of an emotion twenty questions (EMO20Q) questioner agent. The ubiquitous twenty questions game is a suitable format to study how people describe emotions and designing a computer agent to learn and reason about abstract emotion concepts can provide further theoretical insights. While natural language poses many challenges for the computer in human-computer interaction, the accessibility of natural language has made it possible to acquire data of many players reasoning about emotions in human-human games. These data are used to automate a computer questioner agent that asks the user questions and, based on that user’s answers, attempts to guess the emotion that the user has in mind.
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References
Kazemzadeh, A., Georgiou, P.G., Lee, S., Narayanan, S.: Emotion twenty questions: Toward a crowd-sourced theory of emotions. In: D´Mello, S., et al. (eds.) Proceedings of ACII 2011, Part II, vol. 6975, pp. 1–10. Springer, Heidelberg (2011)
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Kazemzadeh, A., Gibson, J., Georgiou, P.G., Lee, S., Narayanan, S.S. (2011). EMO20Q Questioner Agent. 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_38
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DOI: https://doi.org/10.1007/978-3-642-24571-8_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24570-1
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