Abstract
We present a novel approach to clustering and classification of music, based on the concept of interval categories. Six interval categories exist, each with its own musical character. A piece of music can be represented by six numbers, reflecting the percentages of occurrences of each interval category. A piece of music can, in this way, be visualized as a point in a six dimensional space. The three most significant dimensions are chosen from these six. Using this approach, a successful visual clustering of music is possible for 1) composers through various musical time periods, and 2) the three periods of Beethoven, which illustrates the use of our approach on both a general and a specific level. Furthermore, we will see that automatic classification between tonal and atonal music can be achieved.
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© 2011 Springer-Verlag Berlin Heidelberg
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Honingh, A., Bod, R. (2011). Clustering and Classification of Music by Interval Categories. In: Agon, C., Andreatta, M., Assayag, G., Amiot, E., Bresson, J., Mandereau, J. (eds) Mathematics and Computation in Music. MCM 2011. Lecture Notes in Computer Science(), vol 6726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21590-2_30
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DOI: https://doi.org/10.1007/978-3-642-21590-2_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21589-6
Online ISBN: 978-3-642-21590-2
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