[Show abstract][Hide abstract] ABSTRACT: In recent years, the role of percussion instrument in music has become important. Especially, the drum is used in various genres such as brass band, jazz, and the pop music. The drum is one of the musical instruments, and becomes essential to music. In this work, we suggested automated creation of drum's fill-in pattern using Interactive Genetic Algorithm (IGA). The proposed system created the drum's fill-in patterns as individuals in GA, and the user evaluates them subjectively. Based on the fitness value, the proposed system performs GA calculation. As results of experiment 1 and 2, the average gradually increased in accordance with progress of generation. Especially, the significant increase of the fitness value was observed in the experiment 1. However, significant difference was not observed in the experiment 2.
[Show abstract][Hide abstract] ABSTRACT: The chord development is one of musical elements and plays a role to create atmosphere of a musical piece. Chord development is successive musical chord. Since there are in-numerably connections, it is hard for general users to create a music development, which suits for user's favorite taste. A previous study has proposed a method to create a chord development by combining Genetic Algorithm and experience data storage system, however, the method did not reflect user's favorite taste. This study proposes a method to create a chord development that suits the user's favorite taste by using Inter-active Genetic Algorithm. In the proposed method, the user evaluates and scores created chord development in 7-point scale. Chord development optimization is performed based on the scores. Furthermore, we fundamentally evaluate the pro-posed method through a listening experiment.
[Show abstract][Hide abstract] ABSTRACT: Interactive Evolutionary Computation (IEC) is known as an effective method to create media contents suited to each user. To reduce the user's fatigue, which remains as a serious problem in IEC, an extended IEC that utilizes physiological information as fitness value have been proposed. As a new extended IEC, this study proposed an extended IEC using heart rate variability (HRV), which reflects autonomic nervous activity. High frequency component of HRV was used as a fitness value. Through two listening experiments, the efficacy of the proposed method was investigated. In the experiment 1, with a concrete system of the proposed method creating music chord progression, change in the fitness value was observed. In the experiment 2, representative created music chord progressions were evaluated subjectively. The change in the fitness value did not show gradual increase, however, lowest fitness value was observed in the initial generation in subjective evaluation. These results of subjective evaluation showed a possibility of the proposed method.