Algoritmisk komposition av popmusik - utformad med markovkedjor, bayesiskt nätverk samt strukturmodellering

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dc.contributor.authorLorentzon, Albin
dc.contributor.authorGrönvall, Joahn
dc.contributor.authorBrötjefors, Karin
dc.contributor.authorOlzon, Per
dc.contributor.authorAndersson, Oscar
dc.contributor.authorWänderlöv, Viktor
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineering (Chalmers)en
dc.date.accessioned2019-07-03T13:42:25Z
dc.date.available2019-07-03T13:42:25Z
dc.date.issued2015
dc.description.abstractThis study proposes and explains the development of a method for algorithmically composing modern pop music. The method uses machine learning in a top-down strategy to generate a chord progression and a tting melody. In an attempt to capture the structure and self similarity present in pop music the method generates a structure in the form of partial repetitions. A test to see if a listener can tell a genererated song from a human composed song showed that most listeners had trouble telling the di erence. However, the songs still lacked some important properties resulting in some listeners being able to tell the di erence.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/219030
dc.language.isoswe
dc.setspec.uppsokTechnology
dc.subjectData- och informationsvetenskap
dc.subjectComputer and Information Science
dc.titleAlgoritmisk komposition av popmusik - utformad med markovkedjor, bayesiskt nätverk samt strukturmodellering
dc.type.degreeExamensarbete för kandidatexamensv
dc.type.degreeBachelor Thesisen
dc.type.uppsokM2
local.programmeEngineering Physics (300 hp)
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