Data-based melody generation through multi-objective evolutionary computation
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http://hdl.handle.net/10045/65707
Título: | Data-based melody generation through multi-objective evolutionary computation |
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Autor/es: | Ponce de León Amador, Pedro José | Iñesta, José M. | Calvo-Zaragoza, Jorge | Rizo, David |
Grupo/s de investigación o GITE: | Reconocimiento de Formas e Inteligencia Artificial |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos |
Palabras clave: | Machine learning | Evolutionary algorithms | Composition | Melody | Tree representation | Multi-objective optimization |
Área/s de conocimiento: | Lenguajes y Sistemas Informáticos |
Fecha de publicación: | 3-ago-2016 |
Editor: | Taylor & Francis |
Cita bibliográfica: | Journal of Mathematics and Music. 2016, 10(2): 173-192. doi:10.1080/17459737.2016.1188171 |
Resumen: | Genetic-based composition algorithms are able to explore an immense space of possibilities, but the main difficulty has always been the implementation of the selection process. In this work, sets of melodies are utilized for training a machine learning approach to compute fitness, based on different metrics. The fitness of a candidate is provided by combining the metrics, but their values can range through different orders of magnitude and evolve in different ways, which makes it hard to combine these criteria. In order to solve this problem, a multi-objective fitness approach is proposed, in which the best individuals are those in the Pareto front of the multi-dimensional fitness space. Melodic trees are also proposed as a data structure for chromosomic representation of melodies and genetic operators are adapted to them. Some experiments have been carried out using a graphical interface prototype that allows one to explore the creative capabilities of the proposed system. An Online Supplement is provided and can be accessed at http://dx.doi.org/10.1080/17459737.2016.1188171, where the reader can find some technical details, information about the data used, generated melodies, and additional information about the developed prototype and its performance. |
Patrocinador/es: | This work was supported by the Spanish Ministerio de Educación, Cultura y Deporte [FPU fellowship AP2012-0939]; and the Spanish Ministerio de Economía y Competitividad project TIMuL supported by UE FEDER funds [No. TIN2013–48152–C2–1–R]. |
URI: | http://hdl.handle.net/10045/65707 |
ISSN: | 1745-9737 (Print) | 1745-9745 (Online) |
DOI: | 10.1080/17459737.2016.1188171 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2016 Informa UK Limited, trading as Taylor & Francis Group |
Revisión científica: | si |
Versión del editor: | http://dx.doi.org/10.1080/17459737.2016.1188171 |
Aparece en las colecciones: | INV - BAES - Artículos de Revistas INV - GRFIA - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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2016_Ponce-de-Leon_etal_JMathMusic_final.pdf | Versión final (acceso restringido) | 1,56 MB | Adobe PDF | Abrir Solicitar una copia |
2016_Ponce-de-Leon_etal_JMathMusic_rev.pdf | Versión revisada (acceso abierto) | 569,68 kB | Adobe PDF | Abrir Vista previa |
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