Abstract
This paper addresses the problem of multi-label classification of emotions in musical recordings. The testing data set contains 875 samples (30 seconds each). The samples were manually labelled into 13 classes, without limits regarding the number of labels for each sample. The experiments and test results are presented.
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References
1. Bernstein., L. (1959) The Joy of Music, New York, Simon and Schuster.
2. Boutell, M., Shen, X., Luo, J., Brown, C. (2003) Multi-label Semantic Scene Classification. Technical Report, Dept. of Computer Science, U. Rochester
3. Clare, A., King, R.D. (2001) Knowledge Discovery in Multi-label Phenotype Data. Lecture Notes in Computer Science 2168 42–53.
4. Dellaert, F., Polzin, T., Waibel, A. (1996) Recognizing Emotion in Speech. Proc. ICSLP 96 3 1970–1973.
5. Fujinaga, L, McMillan, K. (2000) Realtime recognition of orchestral instruments. Proceedings of the International Computer Music Conference, 141–143.
6. Guarino, N. (Ed.) (1998) Formal Ontology in Information Systems, IOS Press, Amsterdam.
7. Li, T., Ogihara, M. (2003) Detecting emotion in music. 4th International Conference on Music Information Retrieval ISMIR, Washington, D.C., and Baltimore, MD. Available at http://ismir2003.ismir.net/papers/Li.pdf
8. Logan, B. and Salomon, A. (2001) A Music Similarity Function Based on Signal Analysis, IEEE International Conference on Multimedia and EXPO (ICME 2001).
9. McCallum, A. (1999) Multi-label Text Classification with a Mixture Model Trained by EM. AAAI'99 Workshop on Text Learning.
10. Peeters, G. Rodet, X. (2002) Automatically selecting signal descriptors for Sound Classification. ICMC 2002 Goteborg, Sweden
11. Pollard, H. F., Jansson, E. V. (1982) A Tristimulus Method for the Specification of Musical Timbre. Acustica 51 162–171
12. Synak, P. and Wieczorkowska, A. (s2005). Some Issues on Detecting Emotions in Music, in: D. Slezak, J. Yao, J. F. Peters, W. Ziarko, X. Hu (Eds.), Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. 10th International Conference, RSFDGrC 2005, Regina, Canada, August/September 2005, Proceedings, Part II. LNAI 3642, Springer, 314–322
13. Tato, R., Santos, R., Kompe, R., Pardo, J. M. (2002) Emotional Space Improves Emotion Recognition. 7th International Conference on Spoken Language Processing ICSLP 2002, Denver, Colorado
14. Tzanetakis, G., Cook, P. (2000) Marsyas: A framework for audio analysis. Organized Sound 4(3) 169–175. Available at http://www-2.cs.cmu.edu/~gtzan/ work/pubs/organisedOOgtzan.pdf
15. Tzanetakis, G., Essl, G. and Cook, P. (2001) Automatic Musical Genre Classification of Audio Signals, 2nd International Conference on Music Information Retrieval (ISMIR 2001)
16. Wieczorkowska, A. A. (2005) Towards Extracting Emotions from Music, in: L. Bole, Z. Michalewicz, T. Nishida (Eds), Intelligent Media Technology for Communicative Intelligence, Second International Workshop, IMTCI 2004, Warsaw, Poland, September 2004, Revised Selected Papers. LNAI 3490, Springer, 228–238.
17. Wieczorkowska, A. A., Ras, Z.W., Tsay, L.-S. (2003) Representing audio data by FS-trees and Adaptable TV-trees, in Foundations of Intelligent Systems, Proceedings of ISMIS Symposium, Maebashi City, Japan, LNAI, Springer-Verlag, No. 2871, 2003, 135–142
18. Wieczorkowska, A. A., Ras, Z.W. (Eds.) (2003) Music Information Retrieval, Special Issue, Journal of Intelligent Information Systems, Kluwer, Vol. 21, No. 1, 2003
19. Wieczorkowska, A., Synak, P., Lewis, R., Ras, Z. W. (2005) Extracting Emotions from Music Data, in: M.-S. Hacid, N. V. Murray, Z. W. Ras, S. Tsumoto (Eds.), Foundations of Intelligent Systems. 15th International Symposium, ISMIS 2005, Saratoga Springs, NY, USA, May 25–28, 2005, Proceedings. LNAI 3488, Springer, 456–465.
20. Wieczorkowska, A., Synak, P., Lewis, R., Ras, Z. W. (2005) Creating Reliable Database for Experiments on Extracting Emotions from Music, in: M. A. Kłopotek, S. Wierzchon, K. Trojanowski (Eds.), Intelligent Information Processing and Web Mining. Proceedings of the International IIS: IIPWM'05 Conference held in Gdansk, Poland, June 13–16, 2005. Advances in Soft Computing, Springer, 395–402.
21. Yang, C. (2001) Music Database Retrieval Based on Spectral Similarity, 2nd International Conference on Music Information Retrieval (ISMIR 2001), Poster.
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Wieczorkowska, A., Synak, P., Raś, Z.W. (2006). Multi-Label Classification of Emotions in Music. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33521-8_30
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DOI: https://doi.org/10.1007/3-540-33521-8_30
Publisher Name: Springer, Berlin, Heidelberg
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