Statistics-based music generation approach considering both rhythm and melody coherence

This paper presents a music generation method which is an extension of a previously presented method that generates coherent melodies using a melodic coherence structure extracted from a template piece. This extension, which has been applied for generating bertso melodies, adds the generation of the...

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Detalhes bibliográficos
Autores: Goienetxea Urkizu, Izaro, Mendialdua Beitia, Iñigo, Rodríguez Rodríguez, Igor, Sierra Araujo, Basilio
Formato: artículo
Fecha de publicación:2019
País:España
Recursos:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/70712
Acesso em linha:http://hdl.handle.net/10810/70712
Access Level:acceso abierto
Palavra-chave:coherence
rhythm generation
computer generated music
statistical models
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spelling Statistics-based music generation approach considering both rhythm and melody coherenceGoienetxea Urkizu, IzaroMendialdua Beitia, IñigoRodríguez Rodríguez, IgorSierra Araujo, Basiliocoherencerhythm generationcomputer generated musicstatistical modelsThis paper presents a music generation method which is an extension of a previously presented method that generates coherent melodies using a melodic coherence structure extracted from a template piece. This extension, which has been applied for generating bertso melodies, adds the generation of the rhythmic content of the melodies, for which a rhythmic coherence structure of the template piece is also created. To do so, a pattern discovery and ranking method is used to discover the rhythmically repeated segments that are interesting, and create a rhythmic coherence structure which can have several levels of nesting. Independent sampling processes have been developed for melodic and rhythmic content, using an adapted optimization method for sampling the rhythmic content of the new pieces. An evaluation process has been carried out to evaluate some of the generated pieces, considering on one hand how the listeners perceive them and on the other hand whether they share the features with bertso melodies. It has been concluded from this evaluation that the method is capable of generating good coherent bertso melodieshis work was supported in part by the Basque Government Research Teams under Grant IT900-16, in part by the Spanish Ministry of Economy and Competitiveness under Grant RTI2018-093337-B-I00, and in part by the Provincial Council of Gipuzkoa under Grant DGE19/04.IEEE202420242019info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/70712reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoIngléshttps://ieeexplore.ieee.org/document/8932479info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/oai:addi.ehu.eus:10810/707122026-06-18T09:23:17Z
dc.title.none.fl_str_mv Statistics-based music generation approach considering both rhythm and melody coherence
title Statistics-based music generation approach considering both rhythm and melody coherence
spellingShingle Statistics-based music generation approach considering both rhythm and melody coherence
Goienetxea Urkizu, Izaro
coherence
rhythm generation
computer generated music
statistical models
title_short Statistics-based music generation approach considering both rhythm and melody coherence
title_full Statistics-based music generation approach considering both rhythm and melody coherence
title_fullStr Statistics-based music generation approach considering both rhythm and melody coherence
title_full_unstemmed Statistics-based music generation approach considering both rhythm and melody coherence
title_sort Statistics-based music generation approach considering both rhythm and melody coherence
dc.creator.none.fl_str_mv Goienetxea Urkizu, Izaro
Mendialdua Beitia, Iñigo
Rodríguez Rodríguez, Igor
Sierra Araujo, Basilio
author Goienetxea Urkizu, Izaro
author_facet Goienetxea Urkizu, Izaro
Mendialdua Beitia, Iñigo
Rodríguez Rodríguez, Igor
Sierra Araujo, Basilio
author_role author
author2 Mendialdua Beitia, Iñigo
Rodríguez Rodríguez, Igor
Sierra Araujo, Basilio
author2_role author
author
author
dc.subject.none.fl_str_mv coherence
rhythm generation
computer generated music
statistical models
topic coherence
rhythm generation
computer generated music
statistical models
description This paper presents a music generation method which is an extension of a previously presented method that generates coherent melodies using a melodic coherence structure extracted from a template piece. This extension, which has been applied for generating bertso melodies, adds the generation of the rhythmic content of the melodies, for which a rhythmic coherence structure of the template piece is also created. To do so, a pattern discovery and ranking method is used to discover the rhythmically repeated segments that are interesting, and create a rhythmic coherence structure which can have several levels of nesting. Independent sampling processes have been developed for melodic and rhythmic content, using an adapted optimization method for sampling the rhythmic content of the new pieces. An evaluation process has been carried out to evaluate some of the generated pieces, considering on one hand how the listeners perceive them and on the other hand whether they share the features with bertso melodies. It has been concluded from this evaluation that the method is capable of generating good coherent bertso melodies
publishDate 2019
dc.date.none.fl_str_mv 2019
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/70712
url http://hdl.handle.net/10810/70712
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://ieeexplore.ieee.org/document/8932479
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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