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(2015) Mathematics and computation in music, Dordrecht, Springer.
Symbolic music similarity using neuronal periodicity and dynamic programming
Rafael Valle, Adrian Freed
pp. 199-204
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
DOI: 10.1007/978-3-319-20603-5_21
Full citation:
Valle, R. , Freed, A. (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, pp. 199-204.
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