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Aesthetics, Interaction and Machine Improvisation

Published online by Cambridge University Press:  04 March 2020

Henrik Frisk
Henrik Frisk*
Affiliation:
Royal College of Music in Stockholm, Sweden
*
Email: [email protected]
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Abstract

Departing from the artistic research project Goodbye Intuition (GI) hosted by the Norwegian Academy of Music in Oslo, this article discusses the aesthetics of improvising with machines. Playing with a system such as the one described in this article, with limited intelligence and no real cognitive skills, will obviously reveal the weaknesses of the system, but it will also convey part of the preconditions and aesthetic frameworks that the human improviser brings to the table. If we want the autonomous system to have the same kind of freedom we commonly value in human players’ improvisational practice, are we prepared to accept that it may develop in a direction that departs from our original aesthetical ambitions? The analyses is based on some of the documented interplay between the musicians in a group in workshops and laboratories. The question of what constitutes an ethical relationship in this kind of improvisation is briefly discussed. The aspect of embodiment emerges as a central obstacle in the development of musical improvisation with machines.

Type
Articles
Information
Organised Sound , Volume 25 , Issue 1: Computation in the Sonic Arts , April 2020 , pp. 33 - 40
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Copyright
© Cambridge University Press, 2020

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References

REFERENCES

Aucouturier, J.-J. and Pachet, F. 2003. Representing Musical Genre: A State of the Art. Journal of New Music Research 32(1): 83–93.10.1076/jnmr.32.1.83.16801CrossRefGoogle Scholar
Belgum, E., Roads, R., Chadabe, J., Tobenfeld, E. T. and Spiegel, L. 1988. A Turing Test for ‘Musical Intelligence’? Computer Music Journal 12(4): 7–9.CrossRefGoogle Scholar
Benson, B. E. 2003. The Improvisation of Musical Dialogue: A Phenomenology of Music. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Blackwell, T. and Young, M. 2004. Self-Organised Music. Organised Sound 9(2): 123–36.10.1017/S1355771804000214CrossRefGoogle Scholar
Bowers, J. and Archer, P. 2005. Not Hyper, Not Meta, Not Cyber but Infra-Instruments. Proceedings of the 2005 Conference on New Interfaces for Musical Expression. Vancouver, Canada: University of British Columbia, 5–10.Google Scholar
Cobussen, M. 2005. Noise and Ethics: On Evan Parker and Alain Badiou. Culture, Theory and Critique 46(1): 29–42.CrossRefGoogle Scholar
Cobussen, M. and Nielsen, N. 2016. Music and Ethics. New York: Taylor & Francis.CrossRefGoogle Scholar
Cook, N. 2017. Scripting Social Interaction: Improvisation, Performance and ‘Art’ Music. In Born, G., Lewis, E. and Straw, W. (eds.) Improvisation, Community, and Social Practice. Durham: Duke University Press, 59–77.Google Scholar
Endresen, S. 2018. Improvising with Humans and Improvising with Machines: Reflection Text #1. www.researchcatalogue.net/view/411228/432839 (accessed on 15 August, 2019).Google Scholar
Evens, A. 2005. Sound Ideas: Music, Machines, and Experience. Theory Out of Bounds, vol. 27. Minneapolis: University of Minnesota Press.Google Scholar
Fiebrink, R. 2011. Real-Time Human Interaction with Supervised Learning Algorithms for Music Composition and Performance. PhD thesis, Princeton University.CrossRefGoogle Scholar
Frisk, H. 2008. Improvisation, Computers, and Interaction: Rethinking Human-Computer Interaction Through Music. PhD thesis, Lund University.Google Scholar
Frisk, H. 2014. Improvisation and the Self: To Listen to the Other. In Schroeder, F. and hAodha, M. Ó (eds.) Soundweaving: Writings on Improvisation. Cambridge: Cambridge Scholars Publishing, 153–69.Google Scholar
Frisk, H. and Östersjö, S. 2006a. Negotiating the Musical Work. An Empirical Study. Proceedings of the International Computer Music Conference 2006. New Orleans/San Francisco: ICMA, 242–9.Google Scholar
Frisk, H. and Östersjö, S. 2006b. Negotiating the Musical Work. An Empirical Study on the Inter-Relation between Composition, Interpretation and Performance. Proceedings of Ems -06, Beijing. Terminology and Translation. Beijing: EMS.Google Scholar
Godøy, R. I. 2006. Gestural-Sonorous Objects: Embodied Extensions of Schaeffer’s Conceptual Apparatus. Organised Sound 11(2): 149–57.CrossRefGoogle Scholar
Grydeland, I. and Qvenild, M. 2019. Goodbye Intuition. www.researchcatalogue.net/view/411228/424771 (accessed on 15 August 2019)Google Scholar
Harris, C. 1999. Art and Innovation: The Xerox Parc Artist-in-Residence Program. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Heidegger, M. 1954. The Question Concerning Technology. In Krell, D. F. (ed.) Basic Writings, 2nd edn. San Francisco: Harper, 311–41.Google Scholar
Hiraga, R., Bresin, R., Hirata, K. and Katayose, H. 2004. Rencon 2004: Turing Test for Musical Expression. Proceedings of the 2004 Conference on New Interfaces for Musical Expression. Hamamatsu, Shizuoka, Japan, 120–3.Google Scholar
Lanier, J. 1996. My Problem with Agents. Wired 4. www.wired.com/1996/11/myprob/ (accessed 20 November 2019).Google Scholar
Lanier, J. 2018. Ten Arguments for Deleting Your Social Media Accounts Right Now. New York: Henry Holt.Google Scholar
Leman, M. and Maes, P.-J. 2015. The Role of Embodiment in the Perception of Music. Empirical Musicology Review 9 (3–4): 236–46.CrossRefGoogle Scholar
LeWitt, S. 1967. Paragraphs on Conceptual Art. Artforum 5(10): 79–83.Google Scholar
Lippe, C. 2002. Real-Time Interaction Among Composers, Performers, and Computer Systems. Information Processing Society of Japan SIG Notes 2002(123): 1–6.Google Scholar
Lopes, D. 2009. A Philosophy of Computer Art. Abingdon: Routledge.CrossRefGoogle Scholar
Machover, T. 1989. Hyperinstrument: Musically Intelligent and Interactive Performance and Creativity Systems. Proceedings of the International Computer Music Conference. San Francisco: ICMA, 186–90.Google Scholar
Monson, I. 1998. Oh Freedom: George Russel, John Coltrane, and Modal Jazz. In Nettl, B. and Russel, M. (ed.) In the Course of Performance: Studies in the World of Musical Improvisation. Chicago: University of Chicago Press, 149–68.Google Scholar
Nancy, J.-L. and Mandell, C. 2007. Listening. New York: Fordham University Press.Google Scholar
Neumann, A., Qvenild, M., Grydeland, I. and Endresen, S. 2019. Lab #5, Part 2. www.researchcatalogue.net/view/411228/431482 (accessed 15 August, 2019).Google Scholar
Nilsson, P.-A. 2011. A Field of Possibilities: Designing and Playing Digital Musical Instruments. PhD thesis, University of Gothenburg.Google Scholar
Nowak, K. L. and Biocca, F. 2003. The Effect of the Agency and Anthropomorphism on Users’ Sense of Telepresence, Copresence, and Social Presence in Virtual Environments. Presence: Teleoperators and Virtual Environments 12(5): 481–94.CrossRefGoogle Scholar
Pachet, F. 2003. The Continuator: Musical Interaction with Style. Journal of New Music Research 32(3): 333–41.CrossRefGoogle Scholar
Pachet, F. 2012. Musical Turing Test with the Continuator on Vpro Channel (Amsterdam). YouTube. www.youtube.com/watch?v=ynPWOMzossI (accessed 10 August, 2019).Google Scholar
Patton, M. Q. 2002. Qualitative Research & Evaluation Methods. Thousand Oaks, CA: Sage.Google Scholar
Qvenild, M. 2019. Playing with Kim Auto – Reflections on Improvising with Ka. www.researchcatalogue.net/view/411228/557934 (accessed 13 August, 2019).Google Scholar
Rodà, A., Schubert, E., De Poli, G. and Canazza, S. 2015. Toward a Musical Turing Test for Automatic Music Performance. International Symposium on Computer Music Multidisciplinary Research.Google Scholar
Sandell, S. 2013. På Insidan Av Tystnaden. En Undersökning. ArtMonitor 36. Konstnärliga fakulteten, Göteborgs Universitet.Google Scholar
Schneider, S., Häßler, A., Habermeyer, T., Beege, M. and Rey, G. D. 2019. The More Human, the Higher the Performance? Examining the Effects of Anthropomorphism on Learning with Media. Journal of Educational Psychology 111(1): 57–72.CrossRefGoogle Scholar
Schnell, N. and Battier, M. 2002. Introducing Composed Instruments, Technical and Musicological Implications. Proceedings of the 2002 Conference on New Interfaces for Musical Expression, Dublin, Ireland, 138–142.Google Scholar
Snow, J. 2018. Amazon’s Face Recognition Falsely Matched 28 Members of Congress with Mugshots. www.aclu.org/blog/privacy-technology/surveillance-technologies/amazons-face-recognition-falsely-matched-28 (accessed 1 June, 2019).Google Scholar
Turing, A. 1950. Computing Machinery and Intelligence. Mind 59(236): 433.CrossRefGoogle Scholar
Young, M. W. 2009. Creative Computers, Improvisation and Intimacy. Dagstuhl Seminar Proceedings (no. 09291). Dagstuhl, Germany: Schloss Dagstuhl – Leibniz-Zentrum fuer Informatik, 1–7. http://research.gold.ac.uk/4686/ (accessed 20 July, 2019).Google Scholar