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Music viewed by its entropy content: A novel window for comparative analysis
Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description, which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: (a) a method to adjust a textual description from its original scale of o...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5645004/ https://www.ncbi.nlm.nih.gov/pubmed/29040288 http://dx.doi.org/10.1371/journal.pone.0185757 |
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author | Febres, Gerardo Jaffe, Klaus |
author_facet | Febres, Gerardo Jaffe, Klaus |
author_sort | Febres, Gerardo |
collection | PubMed |
description | Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description, which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: (a) a method to adjust a textual description from its original scale of observation to an arbitrarily selected scale, (b) a method to model the structure of any textual description based on the shape of the symbol frequency profiles, and (c) the concept of higher order entropy as the entropy associated with the deviations of a frequency-ranked symbol profile from a perfect Zipfian profile. We call this diversity index the ‘2nd Order Entropy’. Applying these methods to a variety of musical pieces showed how the space of ‘symbolic specific diversity-entropy’ and that of ‘2nd order entropy’ captures characteristics that are unique to each music type, style, composer and genre. Some clustering of these properties around each musical category is shown. These methods allow us to visualize a historic trajectory of academic music across this space, from medieval to contemporary academic music. We show that the description of musical structures using entropy, symbol frequency profiles and specific symbolic diversity allows us to characterize traditional and popular expressions of music. These classification techniques promise to be useful in other disciplines for pattern recognition and machine learning. |
format | Online Article Text |
id | pubmed-5645004 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56450042017-10-30 Music viewed by its entropy content: A novel window for comparative analysis Febres, Gerardo Jaffe, Klaus PLoS One Research Article Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description, which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: (a) a method to adjust a textual description from its original scale of observation to an arbitrarily selected scale, (b) a method to model the structure of any textual description based on the shape of the symbol frequency profiles, and (c) the concept of higher order entropy as the entropy associated with the deviations of a frequency-ranked symbol profile from a perfect Zipfian profile. We call this diversity index the ‘2nd Order Entropy’. Applying these methods to a variety of musical pieces showed how the space of ‘symbolic specific diversity-entropy’ and that of ‘2nd order entropy’ captures characteristics that are unique to each music type, style, composer and genre. Some clustering of these properties around each musical category is shown. These methods allow us to visualize a historic trajectory of academic music across this space, from medieval to contemporary academic music. We show that the description of musical structures using entropy, symbol frequency profiles and specific symbolic diversity allows us to characterize traditional and popular expressions of music. These classification techniques promise to be useful in other disciplines for pattern recognition and machine learning. Public Library of Science 2017-10-17 /pmc/articles/PMC5645004/ /pubmed/29040288 http://dx.doi.org/10.1371/journal.pone.0185757 Text en © 2017 Febres, Jaffe 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 Febres, Gerardo Jaffe, Klaus Music viewed by its entropy content: A novel window for comparative analysis |
title | Music viewed by its entropy content: A novel window for comparative analysis |
title_full | Music viewed by its entropy content: A novel window for comparative analysis |
title_fullStr | Music viewed by its entropy content: A novel window for comparative analysis |
title_full_unstemmed | Music viewed by its entropy content: A novel window for comparative analysis |
title_short | Music viewed by its entropy content: A novel window for comparative analysis |
title_sort | music viewed by its entropy content: a novel window for comparative analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5645004/ https://www.ncbi.nlm.nih.gov/pubmed/29040288 http://dx.doi.org/10.1371/journal.pone.0185757 |
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