Please use this identifier to cite or link to this item: http://monografias.ufrn.br/handle/123456789/7714
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dc.contributor.advisorCosta-Abreu, Márjory da-
dc.contributor.authorSantos, Luísa Rocha de Azevedo-
dc.date.accessioned2018-12-11T13:55:12Z-
dc.date.available2018-12-11T13:55:12Z-
dc.date.issued2018-11-28-
dc.identifier20180008263pt_BR
dc.identifier.citationSANTOS, Luísa Rocha de Azevedo. An analysis of procedural piano music composition with mood templates using genetic algorithms. 2018. 69 f. Trabalho de Conclusão de Curso (Bacharelado em Ciência da Computação) - Departamento de Informática e Matemática Aplicada, Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Natal, 2018.pt_BR
dc.identifier.urihttp://monografias.ufrn.br/jspui/handle/123456789/7714-
dc.languageenpt_BR
dc.publisherUniversidade Federal do Rio Grande do Nortept_BR
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Brazil*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/br/*
dc.subjectMusic Compositionpt_BR
dc.subjectMusic Emotionpt_BR
dc.subjectMusic Moodpt_BR
dc.subjectGenetic Algorithmpt_BR
dc.subjectProcedural Content Generationpt_BR
dc.titleAn analysis of procedural piano music composition with mood templates using genetic algorithmspt_BR
dc.typebachelorThesispt_BR
dc.contributor.referees1Maia, Sílvia Maria Diniz Monteiro-
dc.contributor.referees2Silla Jr, Carlos Nascimento-
dc.description.resumoCreating music in an automatic way has been studied since the beginning of artificial intelligence. One of the biggest obstacles of music generation is the vagueness and subjectivity of the mood or emotion transmitted by a music piece. In this work, we experiment with the generation of piano music using template pieces, represented in MIDI format, as a mood directive. We generated a population of random pieces for templates of two opposing moods - happy and sad - and evolved them with a genetic algorithm until their intended mood was close enough to their respective templates. The fitness function that we implemented uses MIDI statistical features to calculate the distance between the given piece and the template. A questionnaire applied to human listeners showed that the generated pieces could overall meet the objective, which was to express the same mood as the template. However, they still sounded computer-generated, probably due to the lack of rhythm regularity and synchronicity. We believe that the weights in the fitness function still need to be balanced, and that new rhythm features could make the pieces sound more natural.pt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentCiência da Computaçãopt_BR
dc.publisher.initialsUFRNpt_BR
Appears in Collections:Ciência da Computação

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