Abstract
In this investigation we propose a novel approach for classifying polyphonic melodies. Our main idea comes from Probability Stochastic Processes using Markov models where the characteristic features of polyphonic melodies are extracted from each bar. The similarity among harmonies can be considered by means of the features. We show the effectiveness and the usefulness of the approach by experimental results.
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© 2006 Springer-Verlag Berlin Heidelberg
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Yoshihara, Y., Miura, T. (2006). Classifying Polyphony Music Based on Markov Model. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_84
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DOI: https://doi.org/10.1007/11875581_84
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45485-4
Online ISBN: 978-3-540-45487-8
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