Name
Title | ||
|---|---|---|
Large-scale music exploration in hierarchically organized landscapes using prototypicality information |
Abstract | ||
|---|---|---|
We present a novel user interface that offers a fun way to explore music collections in virtual landscapes in a game-like manner. Extending previous work, special attention is paid to scalability and user interaction. In this vein, the ever growing size of today's music collections is addressed in two ways that allow for visualizing and browsing nearly arbitrarily sized music repositories. First, the proposed user interface deepTune employs a hierarchical version of the Self-Organizing Map (SOM) to cluster similar pieces of music using multiple, hierarchically aligned layers. Second, to facilitate orientation in the landscape by presenting well-known anchor points to the user, a combination of Web-based and audio signal-based information extraction techniques to determine cluster prototypes (songs) is proposed. Selecting representative and well-known prototypes -- the former is ensured by using signal-based features, the latter by using Web-based data -- is crucial for browsing large music collections. We further report on results of an evaluation carried out to assess the quality of the proposed cluster prototype ranking. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1991996.1992004 | ICMR |
Keywords | Field | DocType |
large music collection,web-based data,novel user interface,large-scale music exploration,cluster similar piece,prototypicality information,music collection,proposed user interface deeptune,music repository,proposed cluster prototype ranking,user interaction,hierarchically organized landscape,cluster prototype,unsupervised learning,information extraction,human computer interaction,user interface | Audio signal,Ranking,Computer science,Unsupervised learning,Information extraction,Artificial intelligence,User interface,Machine learning,Scalability | Conference |
Citations | PageRank | References |
7 | 0.57 | 19 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Markus Schedl | 1 | 1431 | 117.09 |
| Christian Höglinger | 2 | 7 | 0.57 |
| Peter Knees | 3 | 594 | 51.71 |