Processing of Musical Data Employing Rough Sets and Artificial Neural Networks

1. Bazan, J.G., Szczuka, M.S.: RSES and RSESlib - A Collection of Tools for Rough Set Computations. In: Ziarko, W.P., Yao, Y. (eds.) RSCTC 2000. LNCS (LNAI), vol. 2005, p. 106. Springer, Heidelberg (2001)

   Chapter  Google Scholar 

2. Bazan, J.G., Szczuka, M.S., Wróblewski, J.: A New Version of Rough Set Exploration System. In: Alpigini, J.J., Peters, J.F., Skowron, A., Zhong, N. (eds.) RSCTC 2002. LNCS (LNAI), vol. 2475, pp. 397–404. Springer, Heidelberg (2002)

   Chapter  Google Scholar 

3. Brown, J.C.: Computer identification of musical instruments using pattern recognition with cepstral coefficients as features. J. Acoust. Soc. of America 105, 1933–1941 (1999)

   Article  Google Scholar 

4. Czyzewski, A., Szczerba, M., Kostek, B.: Musical Phrase Representation and Recognition by Means of Neural Networks and Rough Sets. Transactions on Rough Sets, 259–284 (2004)

   Google Scholar 

5. Eronen, A., Klapuri, A.: Musical instrument recognition using cepstral coefficients and temporal features. In: Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2000, vol. 2, p. 753–756 (2000)

   Google Scholar 

6. Eronen, A.: Comparison of Features for Musical instrument recognition. In: Proc. IEEE Workshop on the Applicationis of Signal Processing to Audio and Acoustics, pp. 19–22 (2001)

   Google Scholar 

7. Herrera, P., Peeters, G., Dubnov, S.: Automatic classification of musical instrument sounds. J. of New Music Research 32(19), 3–21 (2003)

   Article  Google Scholar 

8. http://logic.mimuw.edu.pl/~rses/ (RSES homepage)

9. http://www.meta-labs.com/mpeg-7-aud

10. http://www.gracenote.com

11. http://www.ismir.net

12. Hunter, J.: An overview of the MPEG-7 Description Definition Language (DDL). IEEE Transactions on Circuits and Systems for Video Technology 11(6), 765–772 (2001)

    Article  Google Scholar 

13. Kaminskyj, I.: Automatic Musical Vibrato Detection System. In: Proc. ACMA Conference, pp. 9–15 (1998)

    Google Scholar 

14. Komorowski, J., Pawlak, Z., Polkowski, L., Skowron, A.: Rough Sets: A Tutorial. In: Pal, S.K., Skowron, A. (eds.) Rough Fuzzy Hybridization: A New Trend in Decision-Making, pp. 3–98. Springer, Heidelberg (1998)

    Google Scholar 

15. Kostek, B.: Soft Computing in Acoustics, Applications of Neural Networks. In: Fuzzy Logic and Rough Sets to Musical Acoustics, Physica Verlag, Heidelberg (1999)

    Google Scholar 

16. Kostek, B., Czyzewski, A.: Representing Musical Instrument Sounds for their Automatic Classification. J. Audio Eng. Soc. 49(9), 768–785 (2001)

    Google Scholar 

17. Kostek, B., Zwan, P.: Wavelet-based automatic recognition of musical instruments. In: Proc. 142nd Meeting of the Acoustical Soc. of America, Fort Lauderdale, Florida, USA, December 3–7, p. 2754 (2001)

    Google Scholar 

18. Kostek, B., Szczuko, P., Zwan, P.: Processing of Musical Data Employing Rough Sets and Artificial Neural Networks. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 539–548. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

19. Kostek, B., Czyzewski, A.: Processing of Musical Metadata Employing Pawlak’s Flow Graphs. In: Peters, J.F., Skowron, A., Grzymała-Busse, J.W., Kostek, B.z., Świniarski, R.W., Szczuka, M.S. (eds.) Transactions on Rough Sets I. LNCS, vol. 3100, pp. 285–305. Springer, Heidelberg (2004)

    Google Scholar 

20. Kostek, B.: Musical Instrument Classification and Duet Analysis Employing Music Information Retrieval Techniques. Proc. of the IEEE 92(4), 712–729 (2004)

    Article  Google Scholar 

21. Lindsay, A.T., Herre, J.: MPEG-7 and MPEG-7 Audio – An Overview. J. Audio Eng. Soc. 49(7/8), 589–594 (2001)

    Google Scholar 

22. Martin, K.D., Kim, Y.E.: Musical instrument identification: A pattern-recognition approach. In: Proc. 136th Meeting, J. Acoust. Soc. of America 103, 1768 (1998)

    Google Scholar 

23. Opolko, F., Wapnick, J.: MUMS – McGill University Master Samples. CD’s (1987)

    Google Scholar 

24. Pal, S.K., Polkowski, L., Skowron, A.: Rough-Neural Computing. Techniques for Computing with Words, Springer, Heidelberg (2004)

    Google Scholar 

25. Pawlak, Z.: Rough Sets. International J. Computer and Information Sciences 11(5) (1982)

    Google Scholar 

26. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer, Boston (1991)

    MATH  Google Scholar 

27. Pawlak, Z.: Probability, Truth and Flow Graph. Electronic Notes in Theoretical Computer Science 82(4) (2003)

    Google Scholar 

28. Pawlak, Z.: Elementary Rough Set Granules: Towards a Rough Set Processor. In: Pal, S.K., Polkowski, L., Skowron, A. (eds.) Rough-Neural Computing. Techniques for Computing with Words, pp. 5–13. Springer, Heidelberg (2004)

    Google Scholar 

29. Peters, J.F., Skowron, A., Grzymala-Busse, J.W., Kostek, B.z., Świniarski, R.W., Szczuka, M.S. (eds.): Transactions on Rough Sets I. LNCS, vol. 3100. Springer, Heidelberg (2004)

    Google Scholar 

30. Polkowski, L., Skowron, A.: Rough sets: A perspective. In: Polkowski, L., Skowron, A. (eds.) Rough Sets in Knowledge Discovery 1: Methodology and Applications, pp. 31–56. Physica-Verlag, Heidelberg (1998)

    Google Scholar 

31. Szczuko, P., Dalka, P., Dabrowski, M., Kostek, B.: MPEG-7-based Low-Level Descriptor Effectiveness in the Automatic Musical Sound Classification. In: 116 Audio Eng. Convention, Preprint No. 6105, Berlin (2004)

    Google Scholar 

32. Wieczorkowska, A., Wróblewski, J., Synak, P., Ślęzak, D.: Application of temporal descriptors to musical instrument sound recognition. J. of Intelligent Information Systems 21(1), 71–93 (2003)

    Article  Google Scholar 

Download references