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This workshop discusses how interactive, multimodal technology, such as virtual agents, can measure and train social-affective interactions. Sensing technology now enables analyzing users’ behaviors and physiological signals. Various signal processing and machine learning methods can be used for prediction tasks. Such social signal processing and tools can be applied to measure and reduce social stress in everyday situations, including public speaking at schools and workplaces.
Tanaka et al. (Sat,) studied this question.
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