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Harvard
Pavlov, S., Olsson, C., Anderling, V., Wikner, J., Andreasson, O. och Svensson, C. (2014) Generation of music through genetic algorithms. Göteborg : Chalmers University of Technology
BibTeX
@misc{
Pavlov2014,
author={Pavlov, Sean and Olsson, Christoffer and Anderling, Viktor and Wikner, Johannes and Andreasson, Olle and Svensson, Christian},
title={Generation of music through genetic algorithms},
abstract={The focus of this bachelor thesis is to generate appealing music segments algorithmically.
Since its creation, the art of music has constantly evolved, developing new
genres and styles over time. Computers have long been recognized for their potential
in discovering new music, but a computer has yet to produce a truly appealing piece
of music.
This thesis employs an evolutionary approach, generating large amounts of musical
segments and selecting the best ones. This selection is made by a group of
programmed raters with different specializations. This method aims to emulate the
process of natural selection.
While the generated results may not have been top hits in themselves, many
interesting segments were created. The created music was diverse, original and could
in many cases be considered to be appealing.
This project was able to produce decent results in short segments but there is
de nitely room for improvement. It is recommended to add more raters to make the
rating process as precise as possible.},
publisher={Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola},
place={Göteborg},
year={2014},
note={39},
}
RefWorks
RT Generic
SR Electronic
ID 203141
A1 Pavlov, Sean
A1 Olsson, Christoffer
A1 Anderling, Viktor
A1 Wikner, Johannes
A1 Andreasson, Olle
A1 Svensson, Christian
T1 Generation of music through genetic algorithms
YR 2014
AB The focus of this bachelor thesis is to generate appealing music segments algorithmically.
Since its creation, the art of music has constantly evolved, developing new
genres and styles over time. Computers have long been recognized for their potential
in discovering new music, but a computer has yet to produce a truly appealing piece
of music.
This thesis employs an evolutionary approach, generating large amounts of musical
segments and selecting the best ones. This selection is made by a group of
programmed raters with different specializations. This method aims to emulate the
process of natural selection.
While the generated results may not have been top hits in themselves, many
interesting segments were created. The created music was diverse, original and could
in many cases be considered to be appealing.
This project was able to produce decent results in short segments but there is
de nitely room for improvement. It is recommended to add more raters to make the
rating process as precise as possible.
PB Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola,PB Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola,PB Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola,PB Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola,PB Institutionen för data- och informationsteknik (GU), Göteborgs universitet,PB Institutionen för data- och informationsteknik (GU), Göteborgs universitet,
LA eng
LK http://publications.lib.chalmers.se/records/fulltext/203141/203141.pdf
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