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Music Ranking Techniques Evaluated
Uitdenbogerd, A.L. and Zobel, J.
In a music retrieval system, a user presents a piece of music as a query and the system must identify from a corpus of performances other pieces with a similar melody. Several techniques have been proposed for matching such queries to stored music. In previous work, we found that local alignment, a technique derived from bioinformatics, was more effective than the n-gram methods derived from information retrieval; other researchers have reported success with n-grams, but have not compared against local alignment. In this paper we explore a broader range of n-gram techniques, and test them with both manual queries and queries automatically extracted from MIDI files. Our experiments show that n-gram matching techniques can be as effective as local alignment; one highly effective technique is to simply count the number of n-grams in common between the query and the stored piece of music. N-grams are particularly effective for short queries and manual queries, while local alignment is superior for automatic queries. |
Cite as: Uitdenbogerd, A.L. and Zobel, J. (2002). Music Ranking Techniques Evaluated. In Proc. Twenty-Fifth Australasian Computer Science Conference (ACSC2002), Melbourne, Australia. CRPIT, 4. Oudshoorn, M. J., Ed. ACS. 275-283. |
(from crpit.com)
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