Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-05T13:53:22.919Z Has data issue: false hasContentIssue false
  • English
  • Français

Scoring with Code: Composing with algorithmic notation

Published online by Cambridge University Press:  13 November 2014

Thor Magnusson
Thor Magnusson*
Affiliation:
Department of Music, School of Media, Film and Music, Silverstone 214, University of Sussex, Brighton, BN1 9RH, UK
*
Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Computer code is a form of notational language. It prescribes actions to be carried out by the computer, often by systems called interpreters. When code is used to write music, we are therefore operating with programming language as a relatively new form of musical notation. Music is a time-based art form and the traditional musical score is a linear chronograph with instructions for an interpreter. Here code and traditional notation are somewhat at odds, since code is written as text, without any representational timeline. This can pose problems, for example for a composer who is working on a section in the middle of a long piece, but has to repeatedly run the code from the beginning or make temporary arrangements to solve this difficulty in the compositional process. In short: code does not come with a timeline but is rather the material used for building timelines. This article explores the context of creating linear ‘code scores’ in the area of musical notation. It presents the Threnoscope as an example of a system that implements both representational notation and a prescriptive code score.

Type
Articles
Information
Organised Sound , Volume 19 , Special Issue 3: Mediation: Notation and Communication in Electroacoustic Music Performance , December 2014 , pp. 268 - 275
Copyright
© Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bate, D. 2009. Photography: The Key Concepts. Oxford: Berg.Google Scholar
Bowker, G. C. and Star, S. L. 2000. Sorting Things Out: Classification and its Consequences. Cambridge, MA: MIT Press.Google Scholar
Boyd Davis, S. 2012. History on the Line: Time as Dimension. Design Issues 28(4): 4–17.Google Scholar
Clark, A. and Chalmers, D. J. 1998. The Extended Mind. ANALYSIS 58(1): 7–19.Google Scholar
Collins, N., McLean, A., Rohrhuber, J. and Ward, A. 2003. Live Coding in Laptop Performance. Organised Sound 8(3): 321–330.Google Scholar
Eco, U. 1989. The Poetics of the Open Work. The Open Work . Cambridge, MA: Harvard University Press.Google Scholar
Goehr, L. 1992. The Imaginary Museum of Musical Works: An Essay in the Philosophy of Music. Oxford: Oxford University Press.Google Scholar
Good, M. 2001. MusicXML for Notation and Analysis. In W. B. Hewlett and E. Selfridge-Field (eds), The Virtual Score: Representation, Retrieval, Restoration. Cambridge, MA: MIT Press.Google Scholar
Green, T. R. G. and Petre, M. 1996. Usability Analysis of Visual Programming Environments: A ‘Cognitive Dimensions’ Framework. Journal of Visual Languages and Computing 10(2): 131–174.Google Scholar
Haynes, B. 2007. The End of Early Music: A Period Performer’s History of Music for the Twenty-First Century. Oxford: Oxford University Press.Google Scholar
Hugill, A. 2012. The Digital Musician. 2nd edn. Abingdon: Routledge.Google Scholar
Kanno, M. 2007. Prescriptive Notation: Limits and Challenges. Contemporary Music Review 26(2): 231–254.Google Scholar
Kotz, L. 2007. Words to Be Looked At: Language in 1960s Art. Cambridge, MA: MIT Press.Google Scholar
McCartney, J. 2002. Rethinking the Computer Music Language: SuperCollider. Computer Music Journal 26(4): 61–68.Google Scholar
McLean, A. 2008. Live Coding for Free. In A. Mansoux and M. de Valk (eds), Floss+Art. London: Mute Publishing.Google Scholar
Nettl, B. 2005. The Study of Ethnomusicology: Thirty-One Issues and Concepts. Champaign, IL: The University of Illinois Press.Google Scholar
Seeger, C. 1958. Prescriptive and Descriptive Music-Writing. The Musical Quarterly 44(2): 184–195.Google Scholar
Sorensen, A. and Brown, A. 2007. aa-cell in Practice: An Approach to Musical Live Coding. Proceedings of the International Computer Music Conference, Copenhagen/San Francisco: ICMA. 292–9.Google Scholar
Wright, M. 2005. Open Sound Control: An Enabling Technology for Musical Networking. Organised Sound 10(3): 193–200.Google Scholar
Xenakis, I. 1992. Formalized Music: Thought and Mathematics in Composition. Hillsdale, NY: Pendragon Press.Google Scholar