Looking through the "Glass ceiling": A conceptual framework for the problems of spectral similarity

Proceedings of the 11th International Society for Music Information Retrieval Conference, ISMIR 2010

Volumn , Issue , 2010, Pages 267-272

  Karydis, Ioannis ^a   Radovanović, Milos ^b   Nanopoulos, Alexandros ^c   Ivanović, Mirjana ^b  

^a Ionian University   (Greece)

^b UNIVERSITY OF NOVI SAD   (Serbia)

^c UNIVERSITY OF HILDESHEIM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CONCENTRATION EFFECTS; CONCENTRATION PROPERTIES; CONCEPTUAL FRAMEWORKS; DATA SPACE; EARTH MOVER'S DISTANCE; GAUSSIAN MIXTURE MODEL (GMMS); GLASS CEILING; GROUPS OF FRAMES; HIGH DIMENSIONALITY; HIGH-DIMENSIONAL DATA SPACE; KULLBACK-LEIBLER DIVERGENCE; MONTE CARLO; MUSIC INFORMATION RETRIEVAL; NEAREST NEIGHBORS; ROBUST METHODS; SIMILARITY MEASURE; SPECTRAL SIMILARITY;

INFORMATION RETRIEVAL;

EID: 78649416079     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. C. C. Aggarwal, A. Hinneburg, and D. A. Keim. On the surprising behavior of distance metrics in high dimensional spaces. In Proc. 8th Int. Conf. on Database Theory (ICDT), pages 420-434, 2001.
2. J.-J. Aucouturier and F. Pachet. Improving timbre similarity: How high's the sky? Journal of Negative Results in Speech and Audio Sciences, 1(1), 2004.
3. J.-J. Aucouturier and F. Pachet. A scale-free distribution of false positives for a large class of audio similarity measures. Pattern Recognition, 41(1):272-284, 2008.
4. A. Berenzweig. Anchors and Hubs in Audio-basedMusic Similarity. PhD thesis, Columbia University, New York, USA, 2007.
5. K. S. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft. When is "nearest neighbor" meaningful? In Proc. 7th Int. Conf. on Database Theory (ICDT), pages 217-235, 1999.
6. M. Casey, C. Rhodes, and M. Slaney. Analysis of minimum distances in high-dimensional musical spaces. IEEE Transactions on Audio, Speech and Language Processing, 16(5):1015-1028, 2008.
7. P. Demartines. Analyse de Données Par Réseaux de Neurones Auto-Organisés. PhD thesis, Institut Nat'l Polytechnique de Grenoble, Grenoble, France, 1994.
8. D. François, V. Wertz, and M. Verleysen. The concentration of fractional distances. IEEE Transactions on Knowledge and Data Engineering, 19(7):873-886, 2007.
9. M. Hoffman, D. M. Blei, and P. R. Cook. Contentbased musical similarity computation using the hierarchical dirichlet process. In Proc. 9th Int. Conf. on Music Information Retrieval (ISMIR), pages 349-354, 2008.
10. B. Logan and A. Salomon. A music similarity function based on signal analysis. In Proc. IEEE Int. Conf. on Multimedia and Expo (ICME), pages 952-955, 2001.
11. E. Pampalk. Speeding up music similarity. In 1st Annual Music Information Retrieval Evaluation eXchange (MIREX), 2005.
12. E. Pampalk. Computational Models of Music Similarity and their Application in Music Information Retrieval. PhD thesis, Vienna University of Technology, Vienna, Austria, 2006.
13. E. Pampalk, A. Flexer, and G. Widmer. Improvements of audio-based music similarity and genre classification. In Proc. 6th Int. Conf. on Music Information Retrieval (ISMIR), pages 628-633, 2005.
14. T. Pohle. Post processing music similarity computations. In 2nd AnnualMusic Information Retrieval Evaluation eXchange (MIREX), 2006.
15. T. Pohle, M. Schedl, P. Knees, and G. Widmer. Automatically adapting the structure of audio similarity spaces. In Proc. 1st Workshop on Learning the Semantics of Audio Signals (LSAS), pages 76-86, 2006.
16. M. Radovanović, A. Nanopoulos, and M. Ivanović. Nearest neighbors in high-dimensional data: The emergence and influence of hubs. In Proc. 26th Int. Conf. on Machine Learning (IMCL), pages 865-872, 2009.
17. K. Seyerlehner, G. Widmer, and P. Knees. Frame level audio similarity - a codebook approach. In Proc. 11th Int. Conf. on Digital Audio Effects (DAFx), pages 349- 356, 2008.
18. Z. Wang, W. Dong, W. Josephson, Q. Lv, M. Charikar, and K. Li. Sizing sketches: A rank-based analysis for similarity search. In Proc. ACM SIGMETRICS Int. Conf. on Measurement andModeling of Computer Systems, pages 157-168, 2007.
19. K. West, S. Cox, and P. Lamere. Incorporating machine-learning into music similarity estimation. In Proc. 1st ACM Workshop on Audio and Music Computing Multimedia, pages 89-96, 2006.