Abstract
The availability of large music collections calls for ways to efficiently access and explore them. We present a new approach which combines descriptors derived from audio analysis with meta-information to create different views of a collection. Such views can have a focus on timbre, rhythm, artist, style or other aspects of music. For each view the pieces of music are organized on a map in such a way that similar pieces are located close to each other. The maps are visualized using an Islands of Music metaphor where islands represent groups of similar pieces. The maps are linked to each other using a new technique to align self-organizing maps. The user is able to browse the collection and explore different aspects by gradually changing focus from one view to another. We demonstrate our approach on a small collection using a meta-information-based view and two views generated from audio analysis, namely, beat periodicity as an aspect of rhythm and spectral information as an aspect of timbre.
Highlights
Music similarity as such might appear to be a rather simple concept
We use smoothed data histograms to visualize the cluster structure and to create an ‘‘islands of music’’ metaphor where groups of similar pieces are visualized as islands (Pampalk et al 2002a)
The user is able to browse the collection and interactively explore different aspects by gradually changing focus from one view to another. This is similar to the idea presented by Aucouturier and Pachet (2002b) who use an ‘‘Aha-Slider’’ to control the combination of meta-information with information derived from audio analysis
Summary
Technological advances with respect to Internet bandwidth and storage media have made large music collections prevalent. We integrate a third type of organization that is not derived from audio analysis This could be based on meta-data such as artist or genre information, or it could be any arbitrary userde ned organization. The user is able to browse the collection and interactively explore different aspects by gradually changing focus from one view to another This is similar to the idea presented by Aucouturier and Pachet (2002b) who use an ‘‘Aha-Slider’’ to control the combination of meta-information with information derived from audio analysis. We rst present the spectrum and periodicity histograms used to calculate similarities from the respective viewpoints This is followed by a review of the SOM and Aligned SOMs. we demonstrate our approach and discuss various shortcomings and more recent work
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