Change search
ReferencesLink to record
Permanent link

Direct link
Evolutionary Music Composition: A Quantitative Approach
Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, Department of Computer and Information Science.
2011 (English)MasteroppgaveStudent thesis
Abstract [en]

Artificial Evolution has shown great potential in the musical domain. One task in which Evolutionary techniques have shown special promise is in the automatic creation or composition of music. However, a major challenge faced when constructing evolutionary music composition systems is finding a suitable fitness function. Several approaches to fitness have been tried. The most common is interactive evaluation. However, major efficiency challenges with such an approach have inspired the search for <i>automatic</i> alternatives. In this thesis, a music composition system is presented for the evolution of novel melodies. Motivated by the repetitive nature of music, a <i>quantitative</i> approach to automatic fitness is pursued. Two techniques are explored that both operate on frequency distributions of musical events. The first builds on <i>Zipf's Law</i>, which captures the scaling properties of music. Statistical <i>similarity</i> governs the second fitness function and incorporates additional domain knowledge learned from existing music pieces. Promising results show that pleasant melodies can emerge through the application of these techniques. The melodies are found to exhibit several favourable musical properties, including rhythm, melodic locality and motifs.

Place, publisher, year, edition, pages
Institutt for datateknikk og informasjonsvitenskap , 2011. , 115 p.
Keyword [no]
ntnudaim:6314, MTDT datateknikk, Intelligente systemer
URN: urn:nbn:no:ntnu:diva-14036Local ID: ntnudaim:6314OAI: diva2:445806
Available from: 2011-10-05 Created: 2011-10-05

Open Access in DiVA

fulltext(3323 kB)1196 downloads
File information
File name FULLTEXT01.pdfFile size 3323 kBChecksum SHA-512
Type fulltextMimetype application/pdf
cover(226 kB)40 downloads
File information
File name COVER01.pdfFile size 226 kBChecksum SHA-512
Type coverMimetype application/pdf
attachment(39884 kB)1625 downloads
File information
File name ATTACHMENT01.zipFile size 39884 kBChecksum SHA-512
Type attachmentMimetype application/zip

By organisation
Department of Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 1196 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 88 hits
ReferencesLink to record
Permanent link

Direct link