Exploring Music Collections by Browsing Different Views

Technological advances with respect to Internet bandwidth and storage media have made large music collections prevalent. Exploration of such collections is usually either limited to listings returned from, for example, artist-based queries, or it requires additional information not readily available to the public, such as customer pro � les from electronic-music distributors. In particular, content-based browsing of music according to overall sound similarity has remained an unsolved problem, although recent work seems very promising (e.g., Tzanetakis and Cook 2001; Aucouturier and Pachet 2002b; Cano et al. 2002; Pampalk et al. 2002a). The main dif � culty lies in estimating perceived similarity given solely an audio signal. Music similarity as such might appear to be a rather simple concept. For example, it is easy to distinguish classical music from heavy metal. However, there are several aspects of similarity to consider. Some aspects have a very high level of detail, such as the difference between Vladimir Horowitz’s and Daniel Barenboim’s interpretation of a Mozart piano sonata. Other aspects are more apparent, such as the noise level. It is questionable whether it will ever be possible to automatically analyze all aspects of similarity directly from audio. But within limits, it is possible to analyze similarity in terms of, for example, rhythm (Foote et al. 2002; Paulus and Klapuri 2002; Dixon et al. 2003) or timbre (Logan and Salomon 2001; Aucouturier