{"id":57141,"date":"2018-03-09T22:44:54","date_gmt":"2018-03-09T22:44:54","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/music-complexity-a-multi-faceted-description-of-audio-content\/"},"modified":"2018-03-09T22:44:54","modified_gmt":"2018-03-09T22:44:54","slug":"music-complexity-a-multi-faceted-description-of-audio-content","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/inteligencia-artificial\/music-complexity-a-multi-faceted-description-of-audio-content\/","title":{"rendered":"Music complexity: a multi-faceted description of audio content"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Sebastian Streich <\/strong><\/h2>\n<p>Esta tesis propone un juego de algoritmos que puede emplearse para computar estimaciones de las distintas facetas de complejidad que ofrecen se\u00f1ales musicales auditivas. Est\u00e1n enfocados en los aspectos de ac\u00fastica, ritmo, timbre y tonalidad. As\u00ed pues, la complejidad musical se entiende aqu\u00ed en el nivel m\u00e1s basto del com\u00fan acuerdo entre oyentes humanos. El objetivo es obtener juicios de complejidad mediante computaci\u00f3n autom\u00e1tica que resulten similares al punto de vista de un oyente ingenuo. La motivaci\u00f3n de la presente investigaci\u00f3n es la de mejorar la interacci\u00f3n humana con colecciones de m\u00fasica digital. Seg\u00fan se discute en la tesis, hay toda una serie de tareas a considerar, como la visualizaci\u00f3n de una colecci\u00f3n, la generaci\u00f3n de listas de reproducci\u00f3n o la recomendaci\u00f3n autom\u00e1tica de m\u00fasica. A trav\u00e9s de las estimaciones de complejidad musical provistas por los algoritmos descritos, podemos obtener acceso a un nivel de descripci\u00f3n sem\u00e1ntica de la m\u00fasica que ofrecer\u00e1 novedosas e interesantes soluciones para estas tareas.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Music complexity: a multi-faceted description of audio content<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Music complexity: a multi-faceted description of audio content <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Sebastian Streich <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Pompeu fabra<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 21\/02\/2007<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Xavier Serra Casals<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: rafael Ramirez melendez <\/li>\n<li>frans Wiering (vocal)<\/li>\n<li>ichiro Fujinaga (vocal)<\/li>\n<li>emilia G\u00f3mez guti\u00e9rrez (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Sebastian Streich Esta tesis propone un juego de algoritmos que puede emplearse para computar estimaciones de las 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