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Who makes what sound?: supporting real-time musical improvisations of electroacoustic ensembles

Published:22 November 2010Publication History

ABSTRACT

Coordination between ensembles of improvising electroacoustic musicians is a special case of the larger HCI problem of coordinating joint, real-time activity; one that involves some interesting additional and different challenges. This paper reports on research that has identified two specific real-time coordination problems for ensembles of electroacoustic musicians: "who makes what sound?" and "how is the sound being altered?" Real-time sound visualization is explored as a possible solution to assist musicians in overcoming some of these challenges. The main contribution of this paper is that, counterintuitively, for certain kinds of joint, real-time, coordination activities, temporal representations are important in helping to determine "who did what?"

References

  1. Blaine, T. and Fels, S. Contexts of collaborative musical experiences. In Proc. NIME 2003, (2003), 129--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Callaghan, J., Thorpe, W., and van Doorn, J. The science of singing and seeing. In Proc. of the Conference of Interdisciplinary Musicology, (2004).Google ScholarGoogle Scholar
  3. Emmerson, S. 'live' versus 'real-time'. Contemporary Music Review, 10, 2 (1994), 95--101.Google ScholarGoogle ScholarCross RefCross Ref
  4. Gergle, D., Kraut, R. E., and Fussell, S. R. The impact of delayed visual feedback on collaborative performance. In Proc. of CHI 2006, ACM Press (2006), 1303--1312. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Ginsborg, J., Chaffin, R., and Nicholson, G. Shared performance cues in singing and conducting: a content analysis of talk during practice. Psychology of Music, 34, 2 (2006), 167--194.Google ScholarGoogle ScholarCross RefCross Ref
  6. Kinns, N. B., Healey, P. G. T., and Leach, J. Exploring mutual engagement in creative collaborations. In Proc. C&C 2007, ACM Press (2007), 223--232. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Luck, G. and Toiviainen, P. Ensemble musicians' synchronization with conductors' gestures: An automated feature-extraction analysis. Music Perception, 24, 2 (2006), 189--200.Google ScholarGoogle ScholarCross RefCross Ref
  8. Ng, K. and Nesi, P. i-maestro: Technology-enhanced learning and teaching for music. In Proc. NIME 2008, (2008), 4--8.Google ScholarGoogle Scholar
  9. Ng, K. C., Weyde, T., Larkin, O., Neubarth, K., Koerselman, T., and Ong, B. 3d augmented mirror: a multimodal interface for string instrument learning and teaching with gesture support. In Proc. ICMI 2007, ACM Press (2007), 339--345. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Percival, G., Wang, Y., and Tzanetakis, G. Effective use of multimedia for computer-assisted musical instrument tutoring. In Proc. EMME 2007, ACM Press (2007), 67--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Rasch, R. Timing and synchronization in ensemble performance. In Sloboda, J., editor, Generative Processes in Music: The Psychology of Performance, Improvisation, and Composition. Oxford University Press, USA (2001).Google ScholarGoogle Scholar
  12. Sadakata, M., Hoppe, D., Brandmeyer, A., Timmers, R., and Desain, P. Real-time visual feedback for learning to perform short rhythms with expressive variations in timing and loudness. Journal of New Music Research, 37, 3 (2008), 207--220.Google ScholarGoogle ScholarCross RefCross Ref
  13. Shaw, R., Laplante, P. A., Salinas, J., and Riccone, R. A multimedia speech learning system for the hearing impaired. Multimedia Tools and Applications, 3, 1 (1996), 55--70.Google ScholarGoogle ScholarCross RefCross Ref
  14. Smallwood, S., Trueman, D., Cook, P. R., and Wang, G. Composing for laptop orchestra. Computer Music Journal, 32, 1 (2008), 9--25. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Trueman, D. Why a laptop orchestra? Organised Sound, 12, 02 (2007), 171--179. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Welch, G. F., Howard, D. M., and Rush, C. Real-time visual feedback in the development of vocal pitch accuracy in singing. Psychology of Music, 17, 2 (1989), 146--157.Google ScholarGoogle ScholarCross RefCross Ref
  17. Wilson, P. H., Thorpe, C. W., and Callaghan, J. Looking at singing: Does real-time visual feedback improve the way we learn to sing? In Proc. APSCOM 2005, (2005)Google ScholarGoogle Scholar
  18. Wyse, L. and Mitani, N. Bridges for networked musical ensembles. In Proc. ICMC 2009, (2009).Google ScholarGoogle Scholar

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              cover image ACM Other conferences
              OZCHI '10: Proceedings of the 22nd Conference of the Computer-Human Interaction Special Interest Group of Australia on Computer-Human Interaction
              November 2010
              462 pages
              ISBN:9781450305020
              DOI:10.1145/1952222

              Copyright © 2010 ACM

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              New York, NY, United States

              Publication History

              • Published: 22 November 2010

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