Music genre visualization and classification exploiting a small set of high-level semantic features

Proceedings of the International Conference on Digital Audio Effects, DAFx

Volumn , Issue , 2009, Pages 510-516

  Prandi, Giorgio ^a   Sarti, Augusto ^a   Tubaro, Stefano ^a  

^a POLITECNICO DI MILANO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); MUSIC; SEMANTICS;

% REDUCTIONS; CLASSIFICATION TASKS; CONTINUOUS ANALYSIS; GAUSSIAN MIXTURE MODEL; HIGH-LEVEL FEATURES; HIGH-LEVEL SEMANTIC FEATURES; LOW-LEVEL FEATURE VECTORS; MUSIC GENRE; PRIMARY COLORS; SUPPORT VECTORS MACHINE;

VISUALIZATION;

EID: 84869831396     PISSN: 24136700     EISSN: 24136689     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. C. Cortes and V. Vapnik, "Support-vector networks," Machine learning, vol. 20, no. 3, pp. 273-297, 1995.
2. G. Tzanetakis and P. Cook, "Musical genre classification of audio signals," IEEE Transactions on speech and audio processing, vol. 10, no. 5, pp. 293-302, 2002.
3. C. Xu, NC Maddage, X. Shao, F. Cao, and Q. Tian, "Musical genre classification using support vector machines," in 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP'03), 2003, vol. 5.
4. N. Scaringella and D. Mlynek, "A mixture of support vector machines for audio classification," 1 st Music Information Retrieval Evaluation Exchange (MIREX), 2005.
5. J.G.A. Barbedo and A. Lopes, "Automatic genre classification of musical signals," EURASIP Journal on Applied Signal Processing, vol. 2007, no. 1, pp. 157-157, 2007.
6. C. McKay and I. Fujinaga, "Automatic genre classification using large high-level musical feature sets," in Proceedings of the International Conference on Music Information Retrieval, 2004, vol. 525, p. 30.
7. E. Pampalk, S. Dixon, and G. Widmer, "Exploring music collections by browsing different views," Computer Music Journal, vol. 28, no. 2, pp. 49-62, 2004.
8. F. Morchen, A. Ultsch, M. Nocker, and C. Stamm, "Databionic visualization of music collections according to perceptual distance," in Proc. of the 6th International Conference on Music Information Retrieval (ISMIR05), London, UK, 2005.
9. C. Laurier and P. Herrera, "Mood Cloud: A Real-Time Music Mood Visualization Tool," Computer Music Modeling and Retrieval, 2008.
10. K. West, J.S. Downie, X. Hu, and M.C. Jones, "Dynamic visualization of music classification systems," in Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval. ACM New York, NY, USA, 2008, pp. 888-888.
11. M.A.T. Figueiredo and A.K. Jain, "Unsupervised learning of finite mixture models," IEEE Transactions on pattern analysis and machine intelligence, pp. 381-396, 2002.
12. R. Bresin, "What is the color of that music performance," in proceedings of the International Computer Music Conference-ICMC, 2005, pp. 367-370.