Toward Empathic Communication: Emotion Differentiation via Face-to-Face Interaction in Generative Model of Emotion - Hieida, Chie; Horii, Takato; Nagai, Takayuki (IEEE International Conference on Development and Learning (Print), 2018)
In this paper, a model of emotions is proposed based on various neurological and psychological findings. The proposed model consists of three layers: the external/internal appraisal layer, the prediction/decision-making layer, and the emotional memory layer. We implement the proposed model by integrating some deep learning modules such as recurrent attention model, convolutional long short-term memory, and deep deterministic policy gradient. We set a "facial expression" task simulating mother-child interactions and verified emotion differentiation during the task. We also examine the trained model in the "still face" experiment. A claim in this study is that it is a very important step for the constructive approach to compare the proposed model with real human subjects in the same experiment that was carried out in the psychological studies.