Abstract
We describe a method using animated agents to investigate how humans recognize conversational moods. Conversational moods are usually generated by conversation participants through verbal cues as well as nonverbal cues, such as facial expressions, eye movements, and nods. Identifying specific rules of conversational moods would enable us to construct conversational robots and agents that are not only able to converse naturally, but pleasantly and excitedly. Additionally, these robots and agents would be able to assist us with proper action to generate improved conversational moods in different situations. We propose methods for developing agents that can help improve the quality of our conversations and facilitate greater enjoyment of life.
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Yuasa, M. (2014). Can Animated Agents Help Us Create Better Conversational Moods? An Experiment on the Nature of Optimal Conversations. In: Stephanidis, C., Antona, M. (eds) Universal Access in Human-Computer Interaction. Design for All and Accessibility Practice. UAHCI 2014. Lecture Notes in Computer Science, vol 8516. Springer, Cham. https://doi.org/10.1007/978-3-319-07509-9_60
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DOI: https://doi.org/10.1007/978-3-319-07509-9_60
Publisher Name: Springer, Cham
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