Title :
Classification of EGC output and Mental State Transition Network using Self Organizing Map
Author :
Mera, Kazuya ; Ichimura, Takumi
Author_Institution :
Fac. of Inf. Sci., Hiroshima City Univ., Hiroshima, Japan
Abstract :
Mental State Transition Network which consists of mental states connected one another is a basic concept of approximating to human psychological and mental responses. It can represent transition from an emotional state to other one with stimulus by calculating Emotion Generating Calculations method. However, this method ignores most of emotions except for an emotion which has the strongest effect although EGC can calculate the degree of 20 emotions in parallel. In this paper, we investigate the discrepancy between the group of emotions by EGC and the clustering results of the relation of sentences and their emotions by Self Organizing Map. Mental state transits based on the group of emotions on the map. For example, a set of emotions in a group transits the mental state “happy,” and negative mental state is enfeebled.
Keywords :
emotion recognition; pattern classification; pattern clustering; psychology; self-organising feature maps; clustering result; emotion generating calculation output classification; emotion generating calculations method; emotional state; human psychological response approximation; mental response approximation; mental state transition network; self organizing map; Computers; Humans; Organizing; Physiology; Psychology; Support vector machine classification; Vectors; Emotion Generating Calculations; Emotion Oriented Interface; Mental State Transition Network; Self Organizing Map;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4577-0652-3
DOI :
10.1109/ICSMC.2011.6084145