A NIME Reader pp 299-315 | Cite as

2007: Expression and Its Discontents: Toward an Ecology of Musical Creation

Chapter
Part of the Current Research in Systematic Musicology book series (CRSM, volume 3)

Abstract

We describe the prevailing model of musical expression, which assumes a binary formulation of “the text” and “the act,” along with its implied roles of composer and performer. We argue that this model not only excludes some contemporary aesthetic values but also limits the communicative ability of new music interfaces. As an alternative, an ecology of musical creation accounts for both a diversity of aesthetic goals and the complex interrelation of human and non-human agents. An ecological perspective on several approaches to musical creation with interactive technologies reveals an expanded, more inclusive view of artistic interaction that facilitates novel, compelling ways to use technology for music. This paper is fundamentally a call to consider the role of aesthetic values in the analysis of artistic processes and technologies.

Keywords

Ecological Approach Musical Style Instrumental Music Musical Expression Expressive Content 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Arfib, D., Couturier, J.-M., & Kessous, L. (2005). Expressiveness and digital musical instrument design. Journal of New Music Research, 34(1), 125–136.CrossRefGoogle Scholar
  2. Brown, H. M., Hiley, D., Page, C., Kreitner, K., Walls, P., Page, J. K., et al. (2001). Performing practice. In: Grove Music Online. Oxford Music Online. Oxford University Press.Google Scholar
  3. Cage, J. (1961). Silence. Middletown, CT: Wesleyan University Press.Google Scholar
  4. Camurri, A., Mazzarino, B., Ricchetti, M., Timmers, R., & Volpe, G. (2004). Gesture-based communication in human-computer interaction, chapter Multimodal Analysis of Expressive Gesture in Music and Dance Performances (pp. 20–39). Springer, New York.Google Scholar
  5. Cascone, K. (2000). The aesthetics of failure: “Post-digital” tendencies in contemporary computer music. Computer Music Journal, 24(4), 12–18.CrossRefGoogle Scholar
  6. Clarke, E. F. (2005). Ways of listening: An ecological approach to the perception of musical meaning. Oxford University Press.Google Scholar
  7. Cooke, D. (1959). The language of music. London: Oxford University Press.Google Scholar
  8. Cope, D. (1996). Experiments in musical intelligence. Madison, WI: A-R Editions.Google Scholar
  9. Davies, S. (1994). Musical meaning and expression. Cornell University Press.Google Scholar
  10. Davies, S. (2001). Music and emotion, chapter Philosophical Perspectives on Musics Expressiveness. Oxford: Oxford University Press.Google Scholar
  11. DeMarinis, P. (2004). Firebirds. Exhibition notes for show at “Singuhr” Berlin.Google Scholar
  12. Derno, M., & Washburne, C., (Eds.) (2004). Bad music: The music we love to hate, chapter III. Noise, Malfunction, and Discourses of (In)Authenticity (pp. 235–333). New York, Routledge.Google Scholar
  13. Dobrian, C., & Koppelman, D. (2006). The E in NIME: Musical expression with new computer interfaces. In Proceedings of the International Conference on New Interfaces for Musical Expression, Paris, France.Google Scholar
  14. Eco, U. (2004). Audio culture: Readings in modern music, chapter The Poetics of the Open Work (pp. 167–175). Continuum Press.Google Scholar
  15. Fels, S., Gadd, A., & Mulder, A. (2002). Mapping transparency through metaphor: Towards more expressive musical instruments. Organised Sound, 7(2), 109–126.CrossRefGoogle Scholar
  16. Flynt, H. (2007). http://www.henryflynt.org.
  17. Friedman, B. H. (Ed.). (2000). Give my regards to Eighth Street: Collected writings of Morton Feldman. Cambridge: Exact Change Press.Google Scholar
  18. Harrison, S., Tatar, D., & Sengers, P. (2007). The three paradigms of HCI. In: Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI), New York.Google Scholar
  19. Hindley, G. (2002). Music and technology in the twentieth century, chapter Keyboards, Crankshafts and Communication: The Musical Mindset of Western Technology (pp. 33–42). Johns Hopkins University Press.Google Scholar
  20. Huang, F., Gillespie, R. B., & Kuo, A. D. (2007). Visual and haptic feedback contribute to tuning and online control during object manipulation. J. Mot. Behav., 39(3), 179–193.CrossRefGoogle Scholar
  21. Johnston, A. (2016). Opportunities for practice-based research in musical instrument design. Leonardo, 49(1).Google Scholar
  22. Jordà, S. (2005). Digital Lutherie: Crafting Musical Computers for New Musics’ Performance and Improvisation. PhD thesis, Universitat Pompeu Fabra, Barcelona.Google Scholar
  23. Juslin, P. N. (2007). Emotional communication in music performance: A functionalist perspective and some data. Music Perception, 14(4), 383–418.CrossRefGoogle Scholar
  24. Kawato, M. (1997). Bidirectional theory approach to consciousness. In M. Ito, Y. Miyashita, & E. T. Rolls (Eds.), Cognition, Computation and Consciousness. Oxford University Press.Google Scholar
  25. Kline, R. R. (2015). The cybernetics moment, or, why we call our age the information age. Baltimore: Johns Hopkins University Press.Google Scholar
  26. Lansky, P. (1990). A view from the bus: When machines make music. Perspectives of New Music, 28(2), 102–110.CrossRefGoogle Scholar
  27. Marrin, T. (2000). Inside the Conductors Jacket: Analysis, Interpretation and Musical Synthesis of Expressive Gesture. PhD thesis, Massachussets Institute of Technology, Cambridge, MA.Google Scholar
  28. Meyer, F., & Zimmermann, H. (Eds.). (2006). Edgard Varese: Composer, sound sculptor, visionary. Woodbridge: The Boydell Press.Google Scholar
  29. Müller, S., & Mazzola, G. (2003). The extraction of expressive shaping in performance. Computer Music Journal, 27(1), 47–58.CrossRefGoogle Scholar
  30. Norman, D. A. (2004). Emotional design. New York: Basic Books.Google Scholar
  31. Paradiso, J. (1997b). New ways to play: Electronic music interfaces. IEEE Spectr., 34(12), 18–30.CrossRefGoogle Scholar
  32. Peretz, I. (2001). Listen to the brain: A biological perspective on musical emotions. In P. N. Juslin & J. A. Sloboda (Eds.), Music and emotion. Oxford University Press.Google Scholar
  33. Petrie, H. G. (1976). Do you see what I see? The epistemology of interdisciplinary inquiry. Journal of Aesthetic Education, 10(1), 29–43.CrossRefGoogle Scholar
  34. Poepel, C. (2005). On interface expressivity: A player-based study. In: Proceedings of the International Conference on New Interfaces for Musical Expression (pp. 228–231). Canada: Vancouver.Google Scholar
  35. Rowe, R. (2001). Machine musicianship. Cambridge, MA: The MIT Press.Google Scholar
  36. Sarris, A. (1963). Notes on the auteur theory in 1962. Film Culture, 27(1–18),Google Scholar
  37. Scherer, K. R., & Zentner, M. R. (2001). Emotional effects of music: Production rules. In P. N. Juslin & J. A. Sloboda (Eds.), Music and emotion. Oxford University Press.Google Scholar
  38. Sloboda, J. A. (1992). Empirical studies of emotional response to music. In M. R. Jones & S. Holleran (Eds.), Cognitive bases of musical communication. Washington, DC: American Psychological Association.Google Scholar
  39. Sontag, S. (2001). Against interpretation and other essays, chapter Against Interpretation and Other Essays (p. 5). New York: Picador Press.Google Scholar
  40. Sundberg, J. (1988). Computer synthesis of music performance. In J. Sloboda (Ed.), Generative Processes in Music (pp. 52–69). Oxford: Clarendon Press.Google Scholar
  41. Tanaka, A., Tokui, N., & Momeni, A. (2005). Facilitating collective musical creativity. In: Proceedings of ACM Multimedia. Singapore.Google Scholar
  42. Taruskin, R. (1995). Text and Act. Oxford: Oxford University Press.Google Scholar
  43. Taylor, T. D. (2001). Strange Sounds: Music, Technology and Culture. Routledge, New York.Google Scholar
  44. Thompson, E. (2002). The soundscape of modernity. Cambridge, MA: MIT Press.Google Scholar
  45. Wanderley, M. M., Depalle, P., & Warusfel, O. (1999). Improving instrument sound synthesis by modeling the effects of performer gesture. In Proceedings of the 1999 International Computer Music Conference (pp. 418–421). San Francisco.Google Scholar
  46. Wolpert, D. M., Miall, R. C., & Kawato, M. (1998). Internal models in the cerebellum. Trends in Cognitive Sciences, 2(9), 338–347.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Music, Theatre and DanceUniversity of MichiganAnn ArborUSA
  2. 2.Music and Performing Arts DepartmentCalifornia State University, Monterey BaySeasideUSA

Personalised recommendations