AI generated visual accompaniment for music: Machine learning techniques for composing visual accompaniment for music shows

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dc.contributor.advisorGrootjen, F.A.
dc.contributor.advisorDesain, P.W.M.
dc.contributor.authorBiondina, M.
dc.date.issued2017-08-29
dc.description.abstractIn this study a method for artificially composing visual accompaniment for music pieces is proposed. We analyze whether the proposed method composes visual accompaniments that are comparable in quality to visual accompaniments made by a human artist. It was found that visual accompaniments composed by the proposed methods are judged significantly lower in quality than their human-made counterparts. Additionally, it was found that the performance of the proposed method did not differ significantly from a pseudo-random approach to composing visual accompaniments. Despite these results, this method might provide a framework for future research on this topic.en_US
dc.identifier.urihttp://theses.ubn.ru.nl/handle/123456789/5210
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationBachelor Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeBacheloren_US
dc.titleAI generated visual accompaniment for music: Machine learning techniques for composing visual accompaniment for music showsen_US
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