Multi-objective evaluation of music classification

Studies in Classification, Data Analysis, and Knowledge Organization

Volumn , Issue , 2012, Pages 401-410

  Vatolkin, Igor ^a  

^a TU DORTMUND UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; PROCESSING;

ALGORITHM EVALUATION; APPLICATION SCENARIO; CLASSIFICATION ALGORITHM; CLASSIFICATION MODELS; COMPLETE CLASSIFICATION; MULTI-OBJECTIVE EVALUATIONS; MUSIC CLASSIFICATION; PERSONAL MUSIC COLLECTION;

COMPUTER MUSIC;

EID: 84890016602     PISSN: 14318814     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-642-24466-7_41     Document Type: Conference Paper

References (17)

1. AllMusicGuide (2010) Webpage. URL http://www.allmusic.com, cited Feb 2011
2. Bischl B, Vatolkin I, Preuss M (2010) Selecting small audio feature sets in music classification by means of asymmetric mutation. In: Proceedings of the 11th International Conference on Parallel Problem Solving From Nature (PPSN), Krakow, pp 314-323
3. Deb K (2001) Multiobjective optimization using evolutionary algorithms. Wiley-Interscience, Chichester, UK
4. Downie JS (2008) The music information retrieval evaluation exchange (2005-2007): A window into music information retrieval research. Acoust Sci Technol 29(4):247-255
5. Duda RO, Hart PE, Stork DG (2001) Pattern classification. Wiley, New York
6. Hogg RV, Craig AT (1995) Introduction to mathematical statistics. Macmillan, New York
7. Lartillot O, Toiviainen P, Eerola T (2008) A Matlab toolbox for music information retrieval. In: Preisach C, Burkhardt H, Schmidt-Thieme L, Decker R (eds) Data analysis, machine learning and applications, studies in classification, data analysis, and knowledge organization. Springer, Berlin, pp 261-268
8. Lidy T, Rauber A (2005) Evaluation of feature extractors and psycho-acoustic transformations for music genre classification. In: Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR), London, UK, pp 34-41
9. Martin R, Nagathil A (2009) Cepstral modulation ratio regression (CMRARE) parameters for audio signal analysis and classification. In: Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), Taipei, Taiwan, pp 321-324
10. Music test database of the CI research group (2010) http://ls11-www.cs. tu-dortmund.de/rudolph/ mi#music test database, cited Feb 2011
11. Paulus J, Klapuri A (2008) Music structure analysis using a probabilistic fitness measure and an integrated musicological model. In: Bello JP, Chew E, Turnbull D (eds) Proc. of the 9th International Conference on Music Information Retrieval, pp 369-374
12. Ras ZW, Wieczorkowska A (2010) Advances in music information retrieval. Springer, Berlin
13. Sokolova M, Japkowicz N, Szpakowicz S (2006) Beyond accuracy, F-score and ROC: A family of discriminant measures for performance evaluation. In: Sattar A, Kang BH (eds) Proceedings of the AAAI'06 workshop on Evaluation Methods for Machine Learning, Springer, Berlin, pp 1015-1021
14. TheimerW, Vatolkin I, Eronen A (2008) Definitions of Audio Features for Music Content Description, Algorithm Engineering Report TR08-2-001. Technische Universität Dortmund, Germany
15. Tzanetakis G, Cook P (2002) Musical genre classification of audio signals. IEEE Trans Speech Audio Process 10:293-302
16. Vatolkin I, Theimer W, Rudolph G (2009) Design and comparison of different evolution strategies for feature selection and consolidation in music classification. In: Proceedings of the 2009 IEEE Congress on Evolutionary Computation (CEC 2009), IEEE Press, Piscataway, NJ, pp 174-181
17. Witten IH, Frank E (2005) Data mining. Elsevier, Amsterdam