Abstract
In this paper, we present and evaluate a new innovative method for quantitative estimation of the musical instrument categories which compose a music piece. The method uses a wavelet-based music source (i.e., musical instrument) separation algorithm and consists of two steps. In the first step, a source separation technique based on wavelet packets is applied to separate the musical instruments which compose a music piece. In the second step, a classification algorithm based on support vector machines is applied to estimate the musical category of each of the musical instruments identified in the first step. The method is evaluated on the publically available Iowa Musical Instrument Database and found to perform quite successfully.
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Lampropoulou, P.S., Lampropoulos, A.S., Tsihrintzis, G.A. (2008). Musical Instrument Category Discrimination Using Wavelet-Based Source Separation. In: Tsihrintzis, G.A., Virvou, M., Howlett, R.J., Jain, L.C. (eds) New Directions in Intelligent Interactive Multimedia. Studies in Computational Intelligence, vol 142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68127-4_13
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DOI: https://doi.org/10.1007/978-3-540-68127-4_13
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