Symbolic music similarity using neuronal periodicity and dynamic programming

Rafael Valle

Adrián Freed

pp. 199-204

in: Tom Collins, David Mérédith, Anja Volk (eds), Mathematics and computation in music, Berlin, Springer, 2015

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.