Hostname: page-component-8448b6f56d-gtxcr Total loading time: 0 Render date: 2024-04-23T07:24:37.471Z Has data issue: false hasContentIssue false

Artificial Intelligence in Organised Sound

Published online by Cambridge University Press:  05 March 2015

Eduardo R. Miranda*
Affiliation:
Interdisciplinary Centre for Computer Music Research (ICCMR), Faculty of Arts and Humanities, Plymouth University, Plymouth PL4 8AA, UK
Duncan Williams*
Affiliation:
Interdisciplinary Centre for Computer Music Research (ICCMR), Faculty of Arts and Humanities, Plymouth University, Plymouth PL4 8AA, UK

Abstract

Artificial Intelligence is a rich and still-developing field with a number of musical applications. This paper surveys the use of Artificial Intelligence in music in the pages of Organised Sound, from the first issue to the latest, at the time of writing. Traditionally, Artificial Intelligence systems for music have been designed with note-based composition in mind, but the research we present here finds that Artificial Intelligence has also had a significant impact in electroacoustic music, with contributions in the fields of sound analysis, real-time sonic interaction and interactive performance-driven composition, to cite but three. Two distinct categories emerged in the Organised Sound papers: on the one hand, philosophically and/or psychologically inspired, symbolic approaches and, on the other hand, biologically inspired approaches, also referred to as Artificial Life approaches. The two approaches are not mutually exclusive in their use, and in some cases are combined to achieve ‘best of both’ solutions. That said, as Organised Sound is uniquely positioned in the electroacoustic music community, it is somewhat surprising that work addressing important compositional issues such as musical form and structure, which Artificial Intelligence can be readily applied to, is not more present in these pages.

Type
Articles
Copyright
© Cambridge University Press 2015 

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

Blackwell, T. and Young, M. 2004. Self-Organised Music. Organised Sound 9(2): 123136.Google Scholar
Bosma, H. 2003. Bodies of Evidence, Singing Cyborgs and Other Gender Issues in Electrovocal Music. Organised Sound 8(1): 517, doi:10.1017/S135577180300102X.CrossRefGoogle Scholar
Bourotte, R. and Delhaye, C. 2013. Learn to Think for Yourself: Impelled by UPIC to Open New Ways of Composing. Organised Sound 18(2): 134145, doi:10.1017/S1355771813000058.Google Scholar
Brown, A. R. 2004. An Aesthetic Comparison of Rule-Based and Genetic Algorithms for Generating Melodies. Organised Sound 9(2): 191197, doi:10.1017/S1355771804000275.Google Scholar
Casey, M. 2001. General Sound Classification and Similarity in MPEG-7. Organised Sound 6(2): 153164.CrossRefGoogle Scholar
Collins, N. 2002. Experiments with a New Customisable Interactive Evolution Framework. Organised Sound 7(3): 267273.Google Scholar
Collins, N. 2008. The Analysis of Generative Music Programs. Organised Sound 13(3): 237248, doi:10.1017/S1355771808000332.CrossRefGoogle Scholar
Cunha, U. S. and Ramalho, G. 1999. An Intelligent Hybrid Model for Chord Prediction. Organised Sound 4(2): 115119.Google Scholar
Dahlstedt, P. 2001. A MutaSynth in Parameter Space: Interactive Composition Through Evolution. Organised Sound 6(2): 121124.Google Scholar
Eigenfeldt, A. 2011. Real-time Composition as Performance Ecosystem. Organised Sound 16(2): 145153, doi:10.1017/S1355771811000094.CrossRefGoogle Scholar
Eigenfeldt, A. and Pasquier, P. 2010. Real-Time Timbral Organisation: Selecting Samples Based upon Similarity. Organised Sound 15(2): 159166, doi:10.1017/S1355771810000154.Google Scholar
Godøy, R. I. 2006. Gestural-Sonorous Objects: Embodied Extensions of Schaeffer’s Conceptual Apparatus. Organised Sound 11(2): 149157, doi:10.1017/S1355771806001439.Google Scholar
Impett, J. 2000. Situating the Invention in Interactive Music. Organised Sound 5(1): 2734.CrossRefGoogle Scholar
Jacob, B. L. 1996. Algorithmic Composition as a Model of Creativity. Organised Sound 1(3): 157165, doi:10.1017/S1355771896000222.CrossRefGoogle Scholar
Manzolli, J., Moroni, A., Von Zuben, F. and Gudwin, R. 1999. An Evolutionary Approach to Algorithmic Composition. Organised Sound 4(2): 121125.Google Scholar
Miranda, E. R. 2010. Organised Sound, Mental Imageries and the Future of Music Technology: A Neuroscience Outlook. Organised Sound 15(1): 1325.CrossRefGoogle Scholar
Nelson, P. 1997. The UPIC System as an Instrument of Learning. Organised Sound 2(1): 3542.Google Scholar
Orton, R. 2000. Review of David Cope: The Algorithmic Composer. Organised Sound 5(2): 111116.CrossRefGoogle Scholar
Visell, Y. 2004. Spontaneous Organisation, Pattern Models, and Music. Organised Sound 9(2): 151165.Google Scholar
Whalley, I. 2004. PIWeCS: Enhancing Human/Machine Agency in an Interactive Composition System. Organised Sound 9(2): 167174.CrossRefGoogle Scholar
Whalley, I. 2009. Software Agents in Music and Sound Art Research/Creative Work: Current State and a Possible Direction. Organised Sound 14(2): 156167, doi:10.1017/S1355771809000260.Google Scholar
Xenakis, I. 1996. Tutorial Article: Determinacy and Indeterminacy. Organised Sound 1(3): 143155.CrossRefGoogle Scholar