Automatic characterization and generation of music loops and instrument samples for electronic music production

dc.contributor
Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions
dc.contributor.author
Ramires, António
dc.date.accessioned
2023-02-15T11:11:12Z
dc.date.available
2023-02-15T11:11:12Z
dc.date.issued
2023-02-08
dc.identifier.uri
http://hdl.handle.net/10803/687697
dc.description.abstract
Repurposing audio material to create new music - also known as sampling - was a foundation of electronic music and is a fundamental component of this practice. Currently, large-scale databases of audio offer vast collections of audio material for users to work with. The navigation on these databases is heavily focused on hierarchical tree directories. Consequently, sound retrieval is tiresome and often identified as an undesired interruption in the creative process. We address two fundamental methods for navigating sounds: characterization and generation. Characterizing loops and one-shots in terms of instruments or instrumentation allows for organizing unstructured collections and a faster retrieval for music-making. The generation of loops and one-shot sounds enables the creation of new sounds not present in an audio collection through interpolation or modification of the existing material. To achieve this, we employ deep-learning-based data-driven methodologies for classification and generation.
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dc.description.abstract
Repurposing audio material to create new music - also known as sampling - was a foundation of electronic music and is a fundamental component of this practice. Currently, large-scale databases of audio offer vast collections of audio material for users to work with. The navigation on these databases is heavily focused on hierarchical tree directories. Consequently, sound retrieval is tiresome and often identified as an undesired interruption in the creative process. We address two fundamental methods for navigating sounds: characterization and generation. Characterizing loops and one-shots in terms of instruments or instrumentation allows for organizing unstructured collections and a faster retrieval for music-making. The generation of loops and one-shot sounds enables the creation of new sounds not present in an audio collection through interpolation or modification of the existing material. To achieve this, we employ deep-learning-based data-driven methodologies for classification and generation.
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dc.format.extent
182 p.
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dc.language.iso
eng
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dc.publisher
Universitat Pompeu Fabra
dc.rights.license
L'accés als continguts d'aquesta tesi queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
*
dc.source
TDX (Tesis Doctorals en Xarxa)
dc.subject
Electronic music production
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dc.subject
Instrument classification
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dc.subject
Percussive sound generation
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dc.subject
Music information retrieval
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dc.subject
Deep learning
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dc.subject
Deep generative models
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dc.subject
Producción de música electrónica
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dc.subject
Clasificación de instrumentos
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dc.subject
Generación de sonidos percusivos
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dc.subject
Recuperación de la información musical
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dc.subject
Aprendizaje profundo
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dc.subject
Modelos generativos profundos
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dc.title
Automatic characterization and generation of music loops and instrument samples for electronic music production
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dc.type
info:eu-repo/semantics/doctoralThesis
dc.type
info:eu-repo/semantics/publishedVersion
dc.subject.udc
62
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dc.contributor.authoremail
aframires@gmail.com
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dc.contributor.director
Serra, Xavier
dc.contributor.director
Font Corbera, Frederic
dc.embargo.terms
cap
ca
dc.rights.accessLevel
info:eu-repo/semantics/openAccess
dc.description.degree
Programa de doctorat en Tecnologies de la Informació i les Comunicacions


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