Finding or composing suitable media music often poses a serious challenge to media producers: Low-budget video productions, video game producers etc. often lack know-how or resources to have adequate media music composed for the application in question. To avoid the use of royalty-free music libraries, this book suggests the use of generative algorithms for music production. First, functions, impacts and possible taxonomies of media music are investigated, along with its emotional and semantic content. Moreover, a model for the musical representation of emotional or affective states is introduced using Russell's Circumplex Model of Affects and based on state-of-the-art research on this topic. Eventually, algorithms suitable for automated composition of music are evaluated, with a special focus on the ability to map the musical parameters derived from the above-mentioned emotional model onto the algorithms' input parameters. In addition, using the most applicable methods for automated composition, a prototypical music-generating application is developed. This book addresses media producers, computer musicians and audio engineers engaged in sound and music computing.
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Julian Rubisch studied Telecommunications and Media at the University of Applied Sciences St. Pölten in Austria, and received his Master's degree in April 2009. He has been working as a junior researcher there since 2007; his primary fields of interest are sound & music computing, sonic interaction design and multimodal information retrieval.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : moluna, Greven, Allemagne
Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rubisch JulianJulian Rubisch studied Telecommunications and Media at the University of Applied Sciences St. Poelten in Austria, and received his Master s degree in April 2009. He has been working as a junior researcher there since 20. N° de réf. du vendeur 4957509
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Finding or composing suitable media music often poses a serious challenge to media producers: Low-budget video productions, video game producers etc. often lack know-how or resources to have adequate media music composed for the application in question. To avoid the use of royalty-free music libraries, this book suggests the use of generative algorithms for music production. First, functions, impacts and possible taxonomies of media music are investigated, along with its emotional and semantic content. Moreover, a model for the musical representation of emotional or affective states is introduced using Russell's Circumplex Model of Affects and based on state-of-the-art research on this topic. Eventually, algorithms suitable for automated composition of music are evaluated, with a special focus on the ability to map the musical parameters derived from the above-mentioned emotional model onto the algorithms' input parameters. In addition, using the most applicable methods for automated composition, a prototypical music-generating application is developed. This book addresses media producers, computer musicians and audio engineers engaged in sound and music computing. N° de réf. du vendeur 9783639101287
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Generative Music for Media Applications | An Evaluation of Algorithmic Composition Strategies to Enhance the Media Production Process | Julian Rubisch | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639101287 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101453093
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. This item is printed on demand. N° de réf. du vendeur 3639101286
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