Algoritmisk komposition av popmusik - utformad med markovkedjor, bayesiskt nätverk samt strukturmodellering
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Typ
Examensarbete för kandidatexamen
Bachelor Thesis
Bachelor Thesis
Program
Engineering Physics (300 hp)
Publicerad
2015
Författare
Lorentzon, Albin
Grönvall, Joahn
Brötjefors, Karin
Olzon, Per
Andersson, Oscar
Wänderlöv, Viktor
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
This 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.
Beskrivning
Ämne/nyckelord
Data- och informationsvetenskap , Computer and Information Science