This paper deals with an artificial emotion model for 'Active Human Interface' that generates emotions and facial expressions from desire state by neural network application. The harmony theory, a type of Boltzmann machine, is employed in this paper, and for this network system, the authors show a method of learning six basic emotions (joy, anger, sadness, fear, disgust and surprise). They also formulate schemata connecting a desire state and facial expression consisting of three facial components (eye, eyebrow and mouth). Some simulation results show the successful emotion generation, demonstrating the effectiveness of the learning.
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