Toward Empathic Communication: Emotion Differentiation via Face-to-Face Interaction in Generative Model of Emotion

• Published in: IEEE International Conference on Development and Learning (Print) pp. 66 - 71
• Main Authors: Hieida, Chie, Horii, Takato, Nagai, Takayuki
• Format: Conference Proceeding
• Language: English; Japanese
• Published: IEEE 01.09.2018
• Subjects: decision-making; Model of Emotion; still face experiment
• ISSN: 2161-9484
• DOI: 10.1109/DEVLRN.2018.8761026

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.