Abstract
The rationale of this research work was to find appropriate sound parameters on the basis of which it is possible to discern musical instrument sounds. A review of parameters used in musical acoustics was carried out focusing on the frequency-domain. Some of parameters were extracted from sound representations. Then, the quality of calculated parameters was tested statistically. Additionally, some discretization methods were applied in order to create so-called feature vectors that are to be used for feeding inputs of decision algorithms. Experimental results and conclusions are showed in the paper.References
[1] S. ANDO and K. YAMAGUCHI, Statistical study of spectral parameters in musical instrument ones, J. Acoust. Soc. of America, 94, 1, 37-45 (1993).
[2] J.C. BROWN, Musical fundamental frequency tracking using a pattern recognition method, J. Acoust Soc. Am., 92, 3, 1394-1402 (1992).
[3] T. CHEN, Construction and Frequency Characteristics of Chinese Bowed String Instrument, Proc. 15th Intern. Congress on Acoustics, Trondheim, Norway 1995.
[4] M.R. CHMIELEWSKI and J.W. GRZYMAŁA-BUSSE, Global Discretization of Continuous Attributes as Preprocessing for Machine Learning, 3rd Intern. Workshop on Rough Sets and Soft Computing, Conf. Proc., San Jose, CA, USA, 294-301 (1994).
[2] J.C. BROWN, Musical fundamental frequency tracking using a pattern recognition method, J. Acoust Soc. Am., 92, 3, 1394-1402 (1992).
[3] T. CHEN, Construction and Frequency Characteristics of Chinese Bowed String Instrument, Proc. 15th Intern. Congress on Acoustics, Trondheim, Norway 1995.
[4] M.R. CHMIELEWSKI and J.W. GRZYMAŁA-BUSSE, Global Discretization of Continuous Attributes as Preprocessing for Machine Learning, 3rd Intern. Workshop on Rough Sets and Soft Computing, Conf. Proc., San Jose, CA, USA, 294-301 (1994).
