Visual Mining in Music Collections

We describe the MusicMiner system for organizing large collections of music with databionic mining techniques. Visualization based on perceptually motivated audio features and Emergent Self-Organizing Maps enables the unsupervised discovery of timbrally consistent clusters that may or may not correspond to musical genres and artists. We demonstrate the visualization capabilities of the U-Map. An intuitive browsing of large music collections is offered based on the paradigm of topographic maps. The user can navigate the sound space and interact with the maps to play music or show the context of a song.

• Type: Conference
• Year: 2005
• Where: GFKL
• Authors: Fabian Mörchen, Alfred Ultsch, Mario Nöcker, Christian Stamm
• Keywords: Databionic Mining Techniques, Emergent Self-Organizing Maps, GFKL 2005, Large Music Collections