Dan Ellis : Research :

[artist space image] Music Similarity: Raw Data and Statistics

As part of our research into music similarity and music recommendation systems, we have been looking at the problem of ground-truth information and how to collect subjective opinions about music similarity. We are committed to sharing this information with other interested researchers, and these pages provide access to the data we have collected and processed. Where practical, we provide data in its most neutral and most useful form i.e. after regularization and tokenization, but before distillation to specific forms we use.

Currently, we have descriptions for the following data sources:

There are also some ancilliary resources:


Here are some of our publications that relate to this data:

M. Mandel, D. Ellis (2005). Song-Level Features and Support Vector Machines for Music Classification
Proc. Int. Conf. on Music Info. Retrieval ISMIR-05, London, September 2005. (6pp)
A. Berenzweig, B. Logan, D. Ellis, B. Whitman (2004). A large-scale evaluation of acoustic and subjective music-similarity measures
Computer Music Journal, 28(2), pp. 63-76, June 2004. (14pp)
B. Logan, D. Ellis, A. Berenzweig (2003). Towards Evaluation Techniques for Music Similarity
White paper (keynote!) at the Workshop on the Evaluation of Music Information Retrieval (MIR) Systems at SIGIR-03, Toronto, August 2003. (5pp)
A. Berenzweig, B. Logan, D. Ellis, B. Whitman (2003). A large-scale investigation of acoustic and subjective music similarity measures
Submitted to ISMIR-03, Baltimore, October 2003. (8pp)
A. Berenzweig, D.P.W. Ellis & S. Lawrence (2003). Anchor Space for Classification and Similarity Measurement of Music
Proc. ICME-03, Baltimore, July 2003. (4pp)
D. Ellis, B. Whitman, A. Berenzweig, S. Lawrence (2002). The Quest for Ground Truth in Musical Artist Similarity
Proc. ISMIR-02, Paris, October 2002. (8pp)


This material is based in part upon work supported by the National Science Foundation under Grant No. IIS-0238301. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

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Dan Ellis <[email protected]>