Algorithmic Composition of Popular Music
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 (Refereed)
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.
Computer Science Language Technology (Computational Linguistics)
IdentifiersURN: urn:nbn:se:kth:diva-109400OAI: oai:DiVA.org:kth-109400DiVA: diva2:581688
the 12th International Conference on Music Perception and Cognition and the 8th Triennial Conference of the European Society for the Cognitive Sciences of Music
tmh_import_13_01_02, tmh_id_3822 QC 201305232013-01-022013-01-022013-05-23Bibliographically approved