Unifying low-level and high-level music similarity measures

IEEE Transactions on Multimedia

Volumn 13, Issue 4, 2011, Pages 687-701

  Bogdanov, Dmitry ^a   Serrà, Joan ^a   Wack, Nicolas ^a   Herrera, Perfecto ^a   Serra, Xavier ^a  

^a UNIVERSITAT POMPEU FABRA   (Spain)

Author keywords

Distance measurement; information retrieval; knowledge acquisition; multimedia computing; multimedia databases; music

Indexed keywords

AUDIO CONTENT; DESCRIPTORS; DISTANCE MEASURE; DISTANCE-BASED; EUCLIDEAN DISTANCE; FEATURE SPACE; GAUSSIANS; HIGH LEVEL SEMANTICS; MEL-FREQUENCY CEPSTRAL COEFFICIENTS; MULTIMEDIA COMPUTING; MULTIMEDIA DATABASE; MULTIMEDIA RETRIEVAL; MUSIC; MUSIC COLLECTION; MUSIC SIMILARITY;

INFORMATION RETRIEVAL; KNOWLEDGE ACQUISITION; SEMANTICS; SPEECH RECOGNITION;

PRINCIPAL COMPONENT ANALYSIS;

EID: 79960657136     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2011.2125784     Document Type: Article

References (76)

1. G. Lu, "Techniques and data structures for efficient multimedia retrieval based on similarity," IEEE Trans. Multimedia, vol. 4, no. 3, pp. 372-384, 2002. (Pubitemid 35312152)
2. M. A. Casey, R. Veltkamp, M. Goto, M. Leman, C. Rhodes, and M. Slaney, "Content-based music information retrieval: Current directions and future challenges," Proc. IEEE, vol. 96, no. 4, pp. 668-696, 2008.
3. M. Slaney and W. White, "Similarity based on rating data," in Proc. Int. Symp. Music Information Retrieval (ISMIR'07), 2007.
4. M. Levy and M. Sandler, "Music information retrieval using social tags and audio," IEEE Trans. Multimedia, vol. 11, no. 3, pp. 383-395, 2009.
5. O. Celma, "Music recommendation and discovery in the long tail," Ph.D. dissertation, Univ. Pompeu Fabra, Barcelona, Spain, 2008.
6. L. Barrington, R. Oda, and G. Lanckriet, "Smarter than genius? human evaluation of music recommender systems," in Proc. International Society for Music Information Retrieval Conf. (ISMIR'09), 2009, pp. 357-362.
7. D. Bogdanov, J. Serrà, N. Wack, and P. Herrera, "From low-level to high-level: Comparative study of music similarity measures," in Proc. IEEE Int. Symp. Multimedia (ISM'09). Int. Workshop Advances in Music Information Research (AdMIRe'09), 2009, pp. 453-458.
8. L. Barrington, D. Turnbull, D. Torres, and G. Lanckriet, "Semantic similarity for music retrieval," in Proc. Music Information Retrieval Evaluation Exchange (MIREX'07) , 2007. [Online]. Available: http://www.music-ir. org/mirex/abstracts/2007/AS-barrington.pdf.
9. A. Berenzweig, D. P. W. Ellis, and S. Lawrence, "Anchor space for classification and similarity measurement of music," in Proc. Int. Conf. Multimedia and Expo (ICME'03), 2003, vol. 1, pp. 29-32.
10. K. West and P. Lamere, "A model-based approach to constructing music similarity functions," EURASIP J. Adv. Signal Process., vol. 2007, p. 149, 2007.
11. G. C. Cupchik, M. Rickert, and J. Mendelson, "Similarity and preference judgments of musical stimuli," Scandinavian J. Psychol., vol. 23, no. 4, pp. 273-282, 1982.
12. E. Pampalk, A. Flexer, and G.Widmer, "Improvements of audio-based music similarity and genre classification," in Proc. Int. Conf. Music Information Retrieval (ISMIR'05), 2005, pp. 628-633.
13. E. Pampalk, "Computational models of music similarity and their application in music information retrieval," Ph.D. dissertation, Vienna Univ. Technol., Vienna, Austria, 2006.
14. T. Pohle and D. Schnitzer, "Striving for an improved audio similarity measure," in Proc. Music Information Retrieval Evaluation Exchange (MIREX'07) , 2007. [Online]. Available: http://www.music-ir.org/mirex/ 2007/abs/AS-pohle.pdf.
15. T. Pohle and D. Schnitzer, "Submission to MIREX 2009 audio similarity task," in Proc. Music Information Retrieval Evaluation Exchange (MIREX'09) , 2009. [Online]. Available: http://music-ir.org/ mirex/2009/results/abs/PS.pdf.
16. T. Pohle, D. Schnitzer, M. Schedl, P. Knees, and G. Widmer, "On rhythm and general music similarity," in Proc. International Society for Music Information Retrieval Conf. (ISMIR'09), 2009, pp. 525-530.
17. Y. Song and C. Zhang, "Content-based information fusion for semisupervised music genre classification," IEEE Trans. Multimedia, vol. 10, no. 1, pp. 145-152, 2008. (Pubitemid 350281203)
18. B. McFee and G. Lanckriet, "Heterogeneous embedding for subjective artist similarity," in Proc. Int. Conf. Music Information Retrieval (ISMIR'09), 2009.
19. P. Cano, M. Koppenberger, and N.Wack, "Content-based music audio recommendation," in Proc. ACMInt. Conf. Multimedia (ACMMM'05), 2005, pp. 211-212.
20. M. Slaney, K. Weinberger, and W. White, "Learning a metric for music similarity," in Proc. Int. Symp. Music Information Retrieval (ISMIR'08), 2008, pp. 313-318.
21. N. Shental, T. Hertz, D.Weinshall, and M. Pavel, "Adjustment learning and relevant component analysis," Lecture Notes In Computer Science, pp. 776-792, 2002.
22. K. Q. Weinberger and L. K. Saul, "Distance metric learning for large margin nearest neighbor classification," J. Mach. Learn. Res., vol. 10, pp. 207-244, 2009.
23. B. Logan and A. Salomon, "A music similarity function based on signal analysis," in Proc. IEEE Int. Conf. Multimedia and Expo (ICME'01), 2001, p. 190.
24. M. I. Mandel and D. P. Ellis, "Song-level features and support vector machines for music classification," in Proc. Int. Conf. Music Information Retrieval (ISMIR'05), 2005, pp. 594-599.
25. J. J. Aucouturier and F. Pachet, "Music similarity measures: What's the use," in Proc. ISMIR, 2002, pp. 157-163.
26. J. J. Aucouturier, F. Pachet, and M. Sandler, "The way it sounds: Timbre models for analysis and retrieval of music signals," IEEE Trans. Multimedia, vol. 7, no. 6, pp. 1028-1035, 2005. (Pubitemid 41789115)
27. A. Flexer, D. Schnitzer, M. Gasser, and G. Widmer, "Playlist generation using start and end songs," in Proc. Int. Symp. Music Information Retrieval (ISMIR'08), 2008, pp. 173-178.
28. J. H. Jensen, M. G. Christensen, D. P. W. Ellis, and S. H. Jensen, "Quantitative analysis of a common audio similarity measure," IEEE Trans. Audio, Speech, Lang. Process., vol. 17, pp. 693-703, 2009.
29. T. Li and M. Ogihara, "Toward intelligent music information retrieval," IEEE Trans. Multimedia, vol. 8, no. 3, pp. 564-574, 2006.
30. D. P. Ellis and G. E. Poliner, "Identifying 'cover songs' with chroma features and dynamic programming beat tracking," in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP'07), 2007, pp. 1429-1432.
31. M. Marolt, "A Mid-level representation for melody-based retrieval in audio collections," IEEE Trans. Multimedia, vol. 10, no. 8, pp. 1617-1625, 2008.
32. J. Serrà, X. Serra, and R. G. Andrzejak, "Cross recurrence quantification for cover song identification," New J. Phys., vol. 11, no. 9, p. 093017, 2009.
33. O. Celma, P. Herrera, and X. Serra, "Bridging the music semantic gap," in Proc. ESWC 2006 Workshop Mastering the Gap: From Information Extraction to Semantic Representation, 2006. [Online]. Available: http://mtg.upf.edu/node/874.
34. G. Tzanetakis and P. Cook, "Musical genre classification of audio signals," IEEE Trans. Speech Audio Process., vol. 10, no. 5, pp. 293-302, 2002. (Pubitemid 34950067)
35. C. Laurier, O. Meyers, J. Serrà, M. Blech, P. Herrera, and X. Serra, "Indexing music by mood: Design and integration of an automatic content- based annotator," Multimedia Tools and Applications, vol. 48, no. 1, pp. 161-184, 2010.
36. C. Laurier, O. Meyers, J. Serrà, M. Blech, and P. Herrera, "Music mood annotator design and integration," in Proc. Int. Workshop Content- Based Multimedia Indexing (CBMI'2009), 2009.
37. G. Peeters, A Large Set of Audio Features for Sound Description (Similarity and Classification) in the CUIDADO Project CUIDADO Project Report, 2004. [Online]. Available: http://recherche.ircam.fr/ equipes/analyse-synthese/ peeters/ARTICLES/.
38. B. Logan, "Mel frequency cepstral coefficients for music modeling," in Proc. Int. Symp. Music Information Retrieval (ISMIR'00), 2000.
39. P. M. Brossier, "Automatic annotation of musical audio for interactive applications," Ph.D. dissertation, Queen Mary, Univ. London, London, U.K., 2007.
40. E. Gómez, P. Herrera, P. Cano, J. Janer, J. Serrà, J. Bonada, S. El-Hajj, T. Aussenac, and G. Holmberg, "Music Similarity Systems and Methods Using descriptors," WO 2009/001202, Dec. 31, 2008.
41. F. Gouyon, "A computational approach to rhythm description: Audio features for the computation of rhythm periodicity functions and their use in tempo induction and music content processing," Ph.D. dissertation, Univ. Pompeu Fabra, Barcelona, Spain, 2005.
42. E. Gómez, "Tonal description of music audio signals," Ph.D. dissertation, Univ. Pompeu Fabra, Barcelona, Spain, 2006.
43. W. A. Sethares, Tuning, Timbre, Spectrum, Scale. New York: Springer Verlag, 2005.
44. I. H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and Techniques. San Francisco, CA: Morgan Kaufmann, 2005.
45. K. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft, "When is "nearest neighbor" meaningful?," in Proc. Database Theory-ICDT'99, 1999, pp. 217-235.
46. F. Korn, B. Pagel, and C. Faloutsos, "On the 'dimensionality curse' and the 'self-similarity blessing," IEEE Trans. Knowl. Data Eng., vol. 13, no. 1, pp. 96-111, 2001.
47. C. C. Aggarwal, "On k-anonymity and the curse of dimensionality," in Proc. Int. Conf. Very Large Data Bases (VLDB'05), VLDB Endowment, Trondheim, Norway, 2005, pp. 901-909. (Pubitemid 43991062)
48. N. Wack, P. Cano, B. de Jong, and R. Marxer, A Comparative Study of Dimensionality Reduction Methods: The Case of Music Similarity, Music Technology Group, 2006, Tech. Rep. [Online]. Available: http://mtg.upf.edu/files/ publications/NWack-2006.pdf.
49. T. Pohle, P. Knees, M. Schedl, and G. Widmer, "Automatically adapting the structure of audio similarity spaces," in Proc. Workshop Learning the Semantics of Audio Signals (LSAS'06), 2006, pp. 66-75.
50. E. Pampalk, S. Dixon, and G.Widmer, "On the evaluation of perceptual similarity measures for music," in Proc. 6th Int. Conf. Digital Audio Effects (DAFx'03), London, U.K., 2003, pp. 7-12.
51. S. Sigurdsson, K. B. Petersen, and T. Lehn-Schiøler, "Mel frequency cepstral coefficients: An evaluation of robustness of mp3 encoded music," in Proc. Int. Conf. Music Information Retrieval (ISMIR'07), 2006, pp. 286-289.
52. M. F. McKinney and D. Moelants, "Ambiguity in tempo perception: What draws listeners to different metrical levels?," Music Percept., vol. 24, no. 2, pp. 155-166, 2006.
53. F. Gouyon, A. Klapuri, S. Dixon, M. Alonso, G. Tzanetakis, C. Uhle, and P. Cano, "An experimental comparison of audio tempo induction algorithms," IEEE Trans. Speech Audio Process., vol. 14, no. 5, pp. 1832-1844, 2006. (Pubitemid 46547602)
54. L. M. Smith, "Beat critic: Beat tracking octave error identification by metrical profile analysis," in Proc. International Society for Music Information Retrieval Conf. (ISMIR'10), 2010.
55. E. Gómez and P. Herrera, "Comparative analysis of music recordings from western and non-western traditions by automatic tonal feature extraction," Empiric. Musicol. Rev., vol. 3, no. 3, pp. 140-156, 2008.
56. C. Xu, N. C. Maddage, X. Shao, F. Cao, and Q. Tian, "Musical genre classification using support vector machines," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP'03), 2003, pp. 429-432.
57. B. Sarwar, G. Karypis, J. Konstan, and J. Reidl, "Item-based collaborative filtering recommendation algorithms," in Proc. Int. Conf. World Wide Web (WWW'01), 2001, pp. 285-295.
58. J. L. Herlocker, J. A. Konstan, L. G. Terveen, and J. T. Riedl, "Evaluating collaborative filtering recommender systems," ACM Trans. Inf. Syst., vol. 22, no. 1, pp. 5-53, 2004.
59. A. Cripps, C. Pettey, and N. Nguyen, "Improving the performance of FLN by using similarity measures and evolutionary algorithms," in Proc. IEEE Int. Conf. Fuzzy Systems, 2006, pp. 323-330. (Pubitemid 46948776)
60. M. B. Abdullah, "On a robust correlation coefficient," J. R. Statist. Soc. Series D (The Statistician), vol. 39, no. 4, pp. 455-460, 1990.
61. A. Novello, M. F. McKinney, and A. Kohlrausch, "Perceptual evaluation of music similarity," in Proc. Int. Conf. Music Information Retrieval (ISMIR'06), 2006.
62. H. Homburg, I. Mierswa, B. Möller, K. Morik, and M. Wurst, "A benchmark dataset for audio classification and clustering," in Proc. Int. Conf. Music Information Retrieval (ISMIR'05), 2005, pp. 528-531.
63. P. J. Rentfrow and S. D. Gosling, "The do re mi's of everyday life: The structure and personality correlates of music preferences," J. Personal. Social Psychol., vol. 84, pp. 1236-1256, 2003. (Pubitemid 37189381)
64. P. Cano, E. Gómez, F. Gouyon, P. Herrera, M. Koppenberger, B. Ong, X. Serra, S. Streich, and N.Wack, ISMIR 2004 Audio Description Contest, 2006. [Online]. Available: http://mtg.upf.edu/node/461.
65. C. D. Manning, P. Raghavan, and H. Schẗze, Introduction to Information Retrieval. Cambridge, U.K.: Cambridge Univ. Press, 2008.
66. W. E. Saris and I. N. Gallhofer, Design, Evaluation and Analysis of Questionnaires for Survey Research. New York: Wiley-Interscience, 2007.
67. F. Maillet, D. Eck, G. Desjardins, and P. Lamere, "Steerable playlist generation by learning song similarity from radio station playlists," in Proc. Int. Conf. Music Information Retrieval (ISMIR'09), 2009.
68. R. Sinha and K. Swearingen, "The role of transparency in recommender systems," in Proc. CHI'02 Extended Abstracts on Human Factors in Computing Systems, 2002, p. 831.
69. M. Fernández, D. Vallet, and P. Castells, "Probabilistic score normalization for rank aggregation," in Proc. Advances in Information Retrieval, 2006, pp. 553-556. (Pubitemid 44029509)
70. M. Arevalillo-Herráez, J. Domingo, and F. J. Ferri, "Combining similarity measures in content-based image retrieval," Pattern Recognit. Lett., vol. 29, no. 16, pp. 2174-2181, Dec. 2008.
71. A. Turpin and F. Scholer, "User performance versus precision measures for simple search tasks," in Proc. Int. ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR'06), 2006, pp. 11-18.
72. W. B. Croft, D. Metzler, and T. Strohman, Search Engines: Information Retrieval in Practice. Reading, MA: Addison-Wesley, 2010.
73. F. Radlinski and N. Craswell, "Comparing the sensitivity of information retrieval metrics," in Proc. 33rd Int. ACM SIGIR Conf. Research and Development in Information Retrieval, 2010, pp. 667-674.
74. J. S. Downie, "The music information retrieval evaluation exchange (2005-2007): a window into music information retrieval research," Acoust. Sci. Technol., vol. 29, no. 4, pp. 247-255, 2008.
75. J. Downie, A. Ehmann, M. Bay, and M. Jones, "The music information retrieval evaluation eXchange: some observations and insights," in Proc. Advances in Music Information Retrieval, 2010, pp. 93-115.
76. A. A. Gruzd, J. S. Downie, M. C. Jones, and J. H. Lee, "Evalutron 6000: Collecting music relevance judgments," in Proc. ACM/IEEE-CS Joint Conf. Digital Libraries (JCDL'07), 2007, p. 507. (Pubitemid 350158059)