Analysis and Visualization of Musical Structure using Networks

Fuente: arXiv
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Main Authors: Alcalá-Alvarez, Alberto, Padilla-Longoria, Pablo
Format: Preprint
Published: 2024
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author Alcalá-Alvarez, Alberto
Padilla-Longoria, Pablo
author_facet Alcalá-Alvarez, Alberto
Padilla-Longoria, Pablo
contents In this article, a framework for defining and analysing a family of graphs or networks from symbolic music information is discussed. Such graphs concern different types of elements, such as pitches, chords and rhythms, and the relations among them, and are built from quantitative or categorical data contained in digital music scores. They are helpful in visualizing musical features at once, thus leading to a computational tool for understanding the general structural elements of a music fragment. Data obtained from a digital score undergoes different analytical procedures from graph and network theory, such as computing their centrality measures and entropy, and detecting their communities. We analyze pieces of music coming from different styles, and compare some of our results with conclusions from traditional music analysis techniques.
format Preprint
id arxiv_https___arxiv_org_abs_2404_15208
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Analysis and Visualization of Musical Structure using Networks
Alcalá-Alvarez, Alberto
Padilla-Longoria, Pablo
Social and Information Networks
Sound
Audio and Speech Processing
Physics and Society
In this article, a framework for defining and analysing a family of graphs or networks from symbolic music information is discussed. Such graphs concern different types of elements, such as pitches, chords and rhythms, and the relations among them, and are built from quantitative or categorical data contained in digital music scores. They are helpful in visualizing musical features at once, thus leading to a computational tool for understanding the general structural elements of a music fragment. Data obtained from a digital score undergoes different analytical procedures from graph and network theory, such as computing their centrality measures and entropy, and detecting their communities. We analyze pieces of music coming from different styles, and compare some of our results with conclusions from traditional music analysis techniques.
title Analysis and Visualization of Musical Structure using Networks
topic Social and Information Networks
Sound
Audio and Speech Processing
Physics and Society
url https://arxiv.org/abs/2404.15208