Classifying and generalizing successful parameter combinations for sound design
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 desir...
| Autores: | , , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/127703 |
| Acceso en línea: | https://hdl.handle.net/2117/127703 https://dx.doi.org/10.3233/978-1-61499-918-8-256 |
| Access Level: | acceso abierto |
| Palabra clave: | 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 Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
| Sumario: | 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. |
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