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.
CITATION STYLE
Valle, R., & Freed, A. (2015). Symbolic music similarity using neuronal periodicity and dynamic programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9110, pp. 199–204). Springer Verlag. https://doi.org/10.1007/978-3-319-20603-5_21
Mendeley helps you to discover research relevant for your work.