European Society
for Phenomenology

Repository | Series | Book | Chapter

226953

Symbolic music similarity using neuronal periodicity and dynamic programming

Rafael ValleAdrian Freed

pp. 199-204

Abstract

We introduce NP-MUS, a symbolic music similarity algorithm tailored for polyphonic music with continuous representations of pitch and duration. The algorithm uses dynamic programming and a cost function that relies on a mathematical model of tonal fusion based on neuronal periodicity detection mechanisms. This paper reviews the general requirements of melodic similarity and offers a similarity method that better addresses contemporary and non-traditional music. We provide experiments based on monophonic and polyphonic excerpts inspired by spectral music and Iannis Xenakis.

Publication details

Published in:

Collins Tom, Meredith David, Volk Anja (2015) Mathematics and computation in music: 5th international conference, MCM 2015, London, UK, June 22-25, 2015. Dordrecht, Springer.

Pages: 199-204


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DOI: 10.1007/978-3-319-20603-5_21

Full citation:

Valle Rafael, Freed Adrian (2015) „Symbolic music similarity using neuronal periodicity and dynamic programming“, In: T. Collins, D. Meredith & A. Volk (eds.), Mathematics and computation in music, Dordrecht, Springer, 199–204.