Abstract
The research purpose of interactive sound is to achieve the sound generation with complexity and variety which exceeds the forecast of human. By using the chaotic theory, it is expected that a new sound which affects human's sensitivity is generated. In our laboratory, the sound generation system has been developed using Globally Coupled Map (GCM) which many chaotic elements are put in order and the state is made to transit the whole interaction by passing through the averaging process. GCM, both chaotic asynchronism and whole synchronism are controllable, is able to generate various sounds. By adding some music elements in this system, we are able to generate the sound which does not give displeasure to human. However, there is a problem which payloads to human also become large in case parameters controlled by human operator increase. Therefore, in this research, we introduce the interactive genetic algorithm (IGA) which makes evolution guide to the direction corresponding to human's Kansei and aim for constructing a method to make sound generation easy. IGA is an optimization methodology united the human evaluation and optimization ability of genetic algorithm. ICAS is able to control the complexity of output sounds by only two parameters of synchronism and asynchronism, therefore, it was easy to apply IGA to ICAS. We constructed the simulator ICAS-IGA1 which adjusts only parameters of GCM automatically and ICAS-IGA2 including also parameters of musical elements, and conducted the experiment of sound generation. As a result, we confirmed that the sound generated by ICAS-IGA1 and ICAS-IGA2 coincide with human's Kansei in general. Furthermore, the comparison experiment of performance and operativeness between the conventional method (ICAS) and the proposed method (ICAS-IGA1) was executed to confirm the efficiency of this system.
