A Kansei Expression Method Based on the Simultaneous GM with the Kansei Map

Abstract

We propose the K-Model using Multi-Agent Systems (MAS) and dynamic system as a Kansei information processing model. A dynamic system has been realized by Grey Model (GM) in grey system theory. However, the output system in the conventional model was one-dimensional function. And, it was specifically insufficient to show current human emotion. In the emotion analysis system from human voice, the discrimination accuracy remains at around 60%. This paper presents a new proposal for a multi-dimensional Kansei expression method. This method is constructed from the Kansei map and the simultaneous GM. The Kansei map is a map that includes Kansei elements on a two-dimensional plane. This method is introduced into the emotion analysis system from human voice and its evaluation experiment is carried out. Moreover, a data-preprocessing method to establish the GM newly proposed. As a result of the experiment, it is possible that the discrimination accuracy is improved about 20% compared with the conventional method.