Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Algorithmic Composition of Popular Music
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Music Acoustics.ORCID iD: 0000-0003-2926-6518
2012 (English)In: Proceedings of the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music / [ed] Emilios Cambouropoulos, Costas Tsourgas, Panayotis Mavromatis, Costas Pastiadis, 2012, 276-285 p.Conference paper, Published paper (Refereed)
Abstract [en]

Human  composers  have  used  formal  rules  for  centuries  to  compose music, and an algorithmic composer – composing without the aid of human intervention – can be seen as an extension of this technique. An algorithmic  composer  of  popular  music  (a  computer  program)  has been  created  with  the  aim  to  get  a  better  understanding  of  how  the composition process can be formalized and at the same time to get a better  understanding  of  popular  music  in  general.  With  the  aid  of statistical  findings  a  theoretical  framework  for  relevant  methods  are presented.  The concept of Global Joint Accent Structure is introduced, as a way of understanding how melody and rhythm interact to help the listener   form   expectations  about   future   events. Methods  of  the program   are   presented   with   references   to   supporting   statistical findings. The  algorithmic  composer  creates a  rhythmic  foundation (drums), a chord progression, a phrase structure and at last the melody. The main focus has been the composition of the melody. The melodic generation  is  based  on  ten  different  musical  aspects  which  are described. The resulting output was evaluated in a formal listening test where 14  computer  compositions  were  compared  with  21  human compositions. Results indicate a slightly lower score for the computer compositions but the differences were statistically insignificant.

Place, publisher, year, edition, pages
2012. 276-285 p.
National Category
Computer Science Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-109400OAI: oai:DiVA.org:kth-109400DiVA: diva2:581688
Conference
the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music
Note

tmh_import_13_01_02, tmh_id_3822 QC 20130523

Available from: 2013-01-02 Created: 2013-01-02 Last updated: 2016-12-13Bibliographically approved

Open Access in DiVA

No full text

Authority records BETA

Friberg, Anders

Search in DiVA

By author/editor
Elowsson, AndersFriberg, Anders
By organisation
Music Acoustics
Computer ScienceLanguage Technology (Computational Linguistics)

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 273 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf