Music information retrieval using social tags and audio

IEEE Transactions on Multimedia

Volumn 11, Issue 3, 2009, Pages 383-395

  Levy, Mark ^a   Sandler, Mark ^b  

^a Lastfm   (United Kingdom)

^b QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

Audio; information retrieval; music; social tags

Indexed keywords

ELECTRONIC MUSICAL INSTRUMENTS; INFORMATION RETRIEVAL; INFORMATION SERVICES;

ASPECT MODELS; AUDIO; MUSIC; MUSIC COLLECTIONS; MUSIC INFORMATION RETRIEVALS; REGIONS OF INTERESTS; RETRIEVAL PERFORMANCE; SOCIAL TAGS; TEXT-BASED INFORMATIONS; VECTOR SPACES;

AUDIO ACOUSTICS;

EID: 63049114780     PISSN: 15209210     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMM.2009.2012913     Document Type: Article

References (45)

1. J. Haitsma and T. Kalker, "A highly robust audio fingerprinting system," in Proc. ISMIR, 2002.
2. A. Wang, "The shazam music recognition service," Commun. ACM, vol. 49, no. 8, pp. 44-48, 2006.
3. D. Turnbull, L. Barrington, D. Torres, and G. Lanckriet, "Semantic annotation and retrieval of music and sound effects," IEEE Trans. Audio, Speech, Lang. Process., vol. 16, no. 2, pp. 467-476, Feb. 2008.
4. B. Whitman, "Learning the meaning of music." Ph.D. dissertation, MIT, Cambridge, MA, 2005.
5. D. Eck, P. Lamere, T. Bertin-Mahieux, and S. Green, "Automatic generation of social tags for music recommendation," in Proc. Neural Information Processing Systems Conf. (NIPS) 20, 2007.
6. E. Pampalk, "Computational models of music similarity and their application to music information retrieval," Ph.D. dissertation, Vienna Univ. Technol., Vienna, Austria, 2006.
7. M. Levy and M. Sandler, "A semantic space for music derived from social tags." in Proc. ISMIR, 2007.
8. M. Levy and M. B. Sandler, "Learning latent semantic models for music from social tags," J. New Music Res., submitted for publication.
9. X. Wu, L. Zhang, and Y. Yu, "Exploring social annotations for the semantic web," in Proc. World Wide Web Conf., 2006.
10. S. Golder and B. Huberman, "Usage patterns of collaborative tagging systems," J. Inf. Sci., vol. 32, pp. 198-208, 2006.
11. CD. Manning, P. Raghavan, and H. Schutze, Introduction to Infoimation Retrieval. Cambridge, U.K.: Cambridge Univ. Press, 2008.
12. B. Marlin,R. Zemel, S. Roweis, andM. Slaney, "Collaborative filtering and the missing at random assumption," in Proc. 23rd Conf. Uncertainty in Artificial Intelligence, 2007.
13. F. Vignoli and S. Pauws, "A music retrieval system based on user-driven similarity and its evaluation," in Proc. ISMIR, 2005.
14. M. Levy and M. Sandler, "Lightweight measures for timbral similarity of musical audio," in Proc. ACM Multimedia, 2006.
15. J.-J. Aucouturier, B. Defreville, and F. Pachet, "The bag-of-frame approach to audio pattern recognition: A sufficient model for urban soundscapes but not for polyphonic music," J. Acoust. Soc. Amer., vol. 122, no. 2, pp. 881-891, 2007.
16. J.-J. Aucouturier, "Ten experiments on the modelling of polyphonic timbre," Ph.D. dissertation, Univ. Paris 6, Paris, France, 2006.
17. L. Barrington, A. Chan, D. Turnbull, and G. Lanckriet, "Audio information retrieval using semantic similarity," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP), 2007.
18. N. Maddage, X. Changsheng, M. Kankanhalli, and X. Shao, "Content-based music structure analysis with applications to music semantics understanding," in Proc. 6th ACM SIGMM Int. Workshop Multimedia Information Retrieval, Oct. 2004.
19. L. Lu, M. Wang, and H. Zhang, "Repeating pattern discovery and structure analysis from acoustic music data," in Proc. 6th ACM SIGMM Int. Workshop Multimedia Information Retrieval, Oct. 2004.
20. M. Goto, "A chorus-section detecting method for musical audio signals," in Proc. ICASSP, 2003, vol. V, pp. 437-440.
21. W. Chai and B. Vercoe, "Music thumbnailing via structural analysis," in Proc. ACM Multimedia, 2003, pp. 223-226.
22. J. Paulus and A. Klapuri, "Music structure analysis by rinding repeated parts," in Proc. 1st ACM Audio and Music Computing Multimedia Workshop, 2006.
23. Y. Shiu, H. Jeong, and C. J. Kuo, "Similarity matrix processing for music structure analysis," in Proc. 1st ACM Audio and Music Computing Multimedia Workshop, 2006.
24. M. Levy, M. Sandler, and M. Casey, "Extraction of high-level musical structure from audio data and its application to thumbnail generation," in Proc. ICASSP, 2006.
25. M. Levy and M. Sandler, "New methods in structural segmentation of musical audio," in Proc. Eur. Signal Processing Conf., 2006.
26. M. Levy and M. Sandler, "Structural segmentation of musical audio by constrained clustering," IEEE Trans. Audio, Speech, Lang. Process., vol. 16, no. 2, pp. 318-326, Feb. 2008.
27. M. Davies and M. Plumbley, "Exploring the effect of rhythmic style classification on automatic tempo estimation," in Proc. EUSIPCO, 2008, submitted for publication.
28. J. P. Bello, C Duxbury, M. E. Davies, and M. B. Sandler, "On the use of phase and energy for musical onset detection in the complex domain," IEEE Signal Process. Lett., vol. 11, no. 6, pp. 553-556, Jun. 2004.
29. G. Salton, A. Wong, and C. S. Yang, "A vector space model for automatic indexing," Commun. ACM, vol. 18, no. 11, pp. 613-620, 1975.
30. T. Hofmann, "Probabilistic latent semantic analysis," in Pwc. Uncertainty in Artificial Intelligence, UAI '99, Stockholm, Sweden, 1999.
31. T. Hofmann, "Unsupervised learning by probabilistic latent unsupervised learning by probabilistic latent semantic analysis," Mach. Learn., vol. 42, pp. 177-196, 2001.
32. F. Monay and D. Gatica-Perez, "Modeling semantic aspects for cross- media image indexing," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 10, pp. 1802-1817, Oct. 2007.
33. P. Knees, E. Pampalk, and G. Widmer, "Artist classification with web- based data," in Proc. ISMIR, 2004.
34. P. Knees, "Automatische klassifikation von musikktinstlern basierend auf web-daten," Master's thesis, Vienna Univ. Technol., Vienna, Austria, Nov. 2004.
35. M. Mandel and D. Ellis, "Song-level features and S VMs for music classification," in Proc. ISMIR, 2005.
36. Y. Mori, H. Takahashi, and R. Oka, "Image-to-word transformation based on dividing and vector quantizing images with words." in Proc. Int. Workshop Multimedia Intelligent Storage and Retrieval Management, 1999.
37. K. Barnard and D. Forsyth, "Learning the semantics of words and pictures," in Proc. IEEE Int. Conf. Computer Vision, 2001.
38. I. Jeon, V. Lavrenko, and R. Manmatha, "Automatic image annotation and retrieval using cross-media relevance models," in Proc. ACMSIGIR Conf., 2003.
39. D. Blei and M. lordan, "Modeling annotated data," in Proc. ACM SIGIR Conf., 2003.
40. P. Quelhas, F. Monay, J.-M. Odobez, D. Gatica-Perez, and T. Tuyte- laars, "A thousand words in a scene," IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 9, pp. 1575-1589, Sep. 2007.
41. O. Gillet and G. Richard, "Comparing audio and video segmentations for music videos indexing," in Proc. ICASSP, 2006.
42. D. Turnbull, G. Lanckriet, E. Pampalk, and M. Goto, "A supervised approach for detecting boundaries in music using difference features and boosting," in Proc. Int. Conf. Music Information Retrieval (ISMIR), Sep. 2007.
43. P. Knees, T. Pohle, M. Schedl, and G. Widmer, "A music search engine built upon audio-based and web-based similarity measures," in Proc. 30th Annu. Int. ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR'07), Amsterdam, The Netherlands, Jul. 23-27, 2007.
44. K. Yoshii, M. Goto, K. Komatani, T. Ogata, and H. G. Okuno, "An efficient hybrid music recommender system using an incrementally trainable probabilistic generative model," IEEE Trans. Audio, Speech, Lang. Process., vol. 16, no. 2, pp. 435-447, Feb. 2008.
45. G. G. An, M. Schedl, and P. Knees, "The quest for groundtruth in musical artist tagging in the social web era," in Proc. ISMIR, 2007.