The SOM-enhanced JukeBox: Organization and Visualization of Music Collections Based on Perceptual Models

The availability of large music repositories calls for new ways of automatically organizing and accessing them. While artist-based listings or title indexes may help in locating a specific piece of music, a more intuitive, genre-based organization is required to allow users to browse an archive and explore its contents. So far, however, these organizations following musical styles have to be designed manually. With the SOM-enhanced JukeBox (SOMeJB) we propose an approach to automatically create an organization of music archives following their perceived sound similarity. More specifically, characteristics of frequency spectra are extracted and transformed according to psychoacoustic models. The resulting psychoacoustic Rhythm Patterns are further organized using the Growing Hierarchical Self-Organizing Map, an unsupervised neural network. On top of this advanced visualizations including Islands of Music (IoM) and Weather Charts offer an interface for interactive exploration of large music repositories.