Name
Title | ||
|---|---|---|
A fast algorithm for music search by similarity in large databases based on modified Symetrized Kullback Leibler Divergence |
Abstract | ||
|---|---|---|
State of the art on music similarity search is based on the pairwise comparison of statistical models representing audio features. The comparison is often obtained by the Symetrized Kullback-Leibler Divergence (SKLD). When dealing with very large databases (over one million items), usual search by similarity algorithms - sequential or exhaustive search - cannot be used. In these cases, optimized search strategies such as the M-tree reduces the search time but requires the dissimilarity measure to be a metric. Unfortunately, this is not the case of the SKLD. In this paper, we propose and successfully test on a large-scale a modification of the Symetrized Kullback-Leibler Divergence which allows to use it as a metric. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/CBMI.2010.5529917 | CBMI |
Keywords | Field | DocType |
music similarity search,very large database,dissimilarity measure,statistical analysis,tree data structures,music,audio features representation,optimized search strategies,statistical model pairwise comparison,modified symmetrized kullback leibler divergence,computational complexity,fast algorithm,very large databases,audio signal processing,m-tree strategy,query formulation,kullback leibler divergence,mel frequency cepstral coefficient,indexing,time measurement,exhaustive search,statistical model,testing,covariance matrix,multiple signal classification,signal analysis | Data mining,Computer science,Search engine indexing,Artificial intelligence,Nearest neighbor search,Pairwise comparison,Pattern recognition,Brute-force search,Tree (data structure),Very large database,Algorithm,Statistical model,Database,Kullback–Leibler divergence | Conference |
ISSN | ISBN | Citations |
1949-3983 E-ISBN : 978-1-4244-8027-2 | 978-1-4244-8027-2 | 3 |
PageRank | References | Authors |
0.42 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christophe Charbuillet | 1 | 34 | 4.44 |
| Geoffroy Peeters | 2 | 523 | 62.99 |
| Stanislav Barton | 3 | 33 | 3.56 |
| Valérie Gouet-brunet | 4 | 69 | 9.90 |