A Global Network with KANSEI-based filtering

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We propose a method to locate relations and constraints between a music score and its impressions, by which we show that machine learning techniques may provide a powerful tool for composing music and analyzing human feelings. We examine, its generality by modifying some arrangements to provide the subjects with a specified impression. This project introduces some user interfaces, which are capable of predicting feelings and creating new objects based on seed structures, such as spectra and their transition for sounds that have been extracted and are perceived as favorable by the test subject.