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Statistical characteristics of tonal harmony: A corpus study of Beethoven’s string quartets

Tonal harmony is one of the central organization systems of Western music. This article characterizes the statistical foundations of tonal harmony based on the computational analysis of expert annotations in a large corpus. Using resampling methods, this study shows that 1) the rank-frequency distri...

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Detalles Bibliográficos
Autores principales: Moss, Fabian C., Neuwirth, Markus, Harasim, Daniel, Rohrmeier, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6553690/
https://www.ncbi.nlm.nih.gov/pubmed/31170188
http://dx.doi.org/10.1371/journal.pone.0217242
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author Moss, Fabian C.
Neuwirth, Markus
Harasim, Daniel
Rohrmeier, Martin
author_facet Moss, Fabian C.
Neuwirth, Markus
Harasim, Daniel
Rohrmeier, Martin
author_sort Moss, Fabian C.
collection PubMed
description Tonal harmony is one of the central organization systems of Western music. This article characterizes the statistical foundations of tonal harmony based on the computational analysis of expert annotations in a large corpus. Using resampling methods, this study shows that 1) the rank-frequency distribution of chords resembles a power law, i.e. few chords govern a large proportion of the data; 2) chord transitions are referential and chord predictability is significantly affected by distinguished chord features; 3) tonal harmony conveys directedness in time; and 4) tonal harmony operates differently at the hierarchical levels of chords and keys. These results serve to characterize tonal harmony on empirical grounds and advance the methodological state-of-the-art in digital musicology.
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spelling pubmed-65536902019-06-17 Statistical characteristics of tonal harmony: A corpus study of Beethoven’s string quartets Moss, Fabian C. Neuwirth, Markus Harasim, Daniel Rohrmeier, Martin PLoS One Research Article Tonal harmony is one of the central organization systems of Western music. This article characterizes the statistical foundations of tonal harmony based on the computational analysis of expert annotations in a large corpus. Using resampling methods, this study shows that 1) the rank-frequency distribution of chords resembles a power law, i.e. few chords govern a large proportion of the data; 2) chord transitions are referential and chord predictability is significantly affected by distinguished chord features; 3) tonal harmony conveys directedness in time; and 4) tonal harmony operates differently at the hierarchical levels of chords and keys. These results serve to characterize tonal harmony on empirical grounds and advance the methodological state-of-the-art in digital musicology. Public Library of Science 2019-06-06 /pmc/articles/PMC6553690/ /pubmed/31170188 http://dx.doi.org/10.1371/journal.pone.0217242 Text en © 2019 Moss et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Moss, Fabian C.
Neuwirth, Markus
Harasim, Daniel
Rohrmeier, Martin
Statistical characteristics of tonal harmony: A corpus study of Beethoven’s string quartets
title Statistical characteristics of tonal harmony: A corpus study of Beethoven’s string quartets
title_full Statistical characteristics of tonal harmony: A corpus study of Beethoven’s string quartets
title_fullStr Statistical characteristics of tonal harmony: A corpus study of Beethoven’s string quartets
title_full_unstemmed Statistical characteristics of tonal harmony: A corpus study of Beethoven’s string quartets
title_short Statistical characteristics of tonal harmony: A corpus study of Beethoven’s string quartets
title_sort statistical characteristics of tonal harmony: a corpus study of beethoven’s string quartets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6553690/
https://www.ncbi.nlm.nih.gov/pubmed/31170188
http://dx.doi.org/10.1371/journal.pone.0217242
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