Título:
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Classifying and generalizing successful parameter combinations for sound design
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Autor/a:
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Paz, Iván; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Romero Merino, Enrique
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Otros autores:
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Universitat Politècnica de Catalunya. Departament de Ciències de la Computació |
Abstract:
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Operating parametric systems in the context of sound design imposes cognitive and practical challenges. The present contribution applies rule extraction to analyze and to generalize a set of parameter combinations, which have been preselected by a user since they produce sound results within a desired perceptual category. Then, it is discussed how and under which conditions these generalizations can be used, for example, for the automation of specific tasks. |
Abstract:
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Peer Reviewed |
Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial -Computer composition (Music) -Musical analysis -- Data processing -Rule extraction -Sound design -Parametric systems -Generalizing data sets -Composició musical per ordinador -Anàlisi musical -- Processament de dades |
Derechos:
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Tipo de documento:
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Artículo - Versión presentada Capítulo o parte de libro |
Editor:
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IOS Press
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Compartir:
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