Abstract
Sound creation and editing in hardware and software synthesizers presents usability problems and a challenge for HCI research. Synthesis parameters vary considerably in their degree of usability, and musical timbre itself is a complex and multidimensional attribute of sound. This chapter presents a user-driven search-based interaction style where the user engages directly with sound rather than with a mediating interface layer. Where the parameters of a given sound synthesis method do not readily map to perceptible sonic attributes, the search algorithm offers an alternative means of timbre specification and control. However, it is argued here that the method has wider relevance for interaction design in search domains which are generally well-ordered and understood, but whose parameters do not afford a useful or intuitive means of search.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ashley, R. (1986). A knowledge-based approach to assistance in timbral design. In Proceedings of the 1986 international computer music conference, The Hague, Netherlands.
Beauchamp, J. (1969). A computer system for time-variant harmonic analysis and synthesis of musical tones. In H. von Foerster & J. W. Beauchamp (Eds.), Music by computers. New York: Wiley.
Blumenthal, J., Grossmann, R., Golatowski, F., & Timmermann, D. (2007). Weighted centroid localization in Zigbee-based sensor networks. WISP 2007. In IEEE international symposium on intelligent signal processing, Madrid, Spain.
Butler, D. (1992). The musician’s guide to perception and cognition. New York: Schirmer Books.
Caclin, A., McAdams, S., Smith, B. K., & Winsberg, S. (2005). Acoustic correlates of timbre space dimensions: A confirmatory study using synthetic tones. Journal of the Acoustical Society of America, 118(1), 471–482.
Dahlstedt, P. (2001). Creating and exploring huge parameter spaces: Interactive evolution as a tool for sound generation proceedings of the 2001 international computer music conference. Havana: ICMA.
Ehresman, D., & Wessel, D. L. (1978). Perception of timbral analogies. Paris: IRCAM.
Ethington, R., & Punch, B. (1994). SeaWave: A system for musical timbre description. Computer Music Journal, 18(1), 30–39.
Faure, A., McAdams, S., & Nosulenko, V. (1996). Verbal correlates of perceptual dimensions of timbre. In Proceedings of the 4th International Conference on Music Perception and Cognition (ICMPC4), McGill University, Montreal, Canada.
Giannakis, K. (2006). A comparative evaluation of auditory-visual mappings for sound visualisation. Organised Sound, 11(3), 297–307.
Grey, J. M., & Gordon, J. W. (1978). Perceptual effects of spectral modifications on musical timbres. Journal of the Acoustical Society of America, 63(5), 1493–1500.
Hajda, J. M., Kendall, R. A., Carterette, E. C., & Harshberger, M. L. (1997). Methodological issues in timbre research. In I. Deliège & J. Sloboda (Eds.), The perception and cognition of music. London: Psychology Press.
Hourdin, C., Charbonneau, G., & Moussa, T. (1997a). A multidimensional scaling analysis of musical instruments’ time varying spectra. Computer Music Journal, 21(2), 40–55.
Hourdin, C., Charbonneau, G., & Moussa, T. (1997b). A sound synthesis technique based on multidimensional scaling of spectra. Computer Music Journal, 21(2), 40–55.
Hutchins, E. L., Hollan, J. D., & Norman, D. A. (1986). Direct manipulation interfaces. In D. A. Norman & S. W. Draper (Eds.), User centered system design: new perspectives on human-computer interaction. Hillsdale: Lawrence Erlbaum Associates.
Johnson, C.G. (1999). Exploring the sound-space of synthesis algorithms using interactive genetic algorithms. In AISB’99 symposium on musical creativity, Edinburgh.
Kendall, R. A., & Carterette, E. C. (1991). Perceptual scaling of simultaneous wind instrument timbres. Music Perception, 8(4), 369–404.
Kendall, R., & Carterette, E. C. (1993). Identification and blend of timbres as basis for orchestration. Contemporary Music Review, 9, 51–67.
Krumhansl, C. L. (1989). Why is musical timbre so hard to understand? In S. Nielzen & O. Olsson (Eds.), Structure and perception of electroacoustic sound and music. Amsterdam: Elsevier (Excerpta Medica 846).
Kruskal, J. B. (1964). Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika, 29(1), 1–27.
Kruskal, J. B., & Wish, M. (1978). Multidimensional scaling. Newbury Park: Sage Publications.
Mandelis, J. (2001). Genophone: An evolutionary approach to sound synthesis and performance. In E. Bilotta, E. R. Miranda, P. Pantano, & P. Todd (Eds.), Proceedings of ALMMA 2002: Workshop on artificial life models for musical applications. Cosenza: Editoriale Bios.
Mandelis, J., & Husbands, P. (2006). Genophone: Evolving sounds and integral performance parameter mappings. International Journal on Artificial Intelligence Tools, 20(10), 1–23.
Martins, J.M., Pereira, F.C., Miranda, E.R., & Cardoso, A. (2004) Enhancing sound design with conceptual blending of sound descriptors. In Proceedings of the workshop on computational creativity (CC’04), Madrid, Spain.
McAdams, S., & Cunible, J. C. (1992). Perception of timbral analogies. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 336(1278), 383–389.
McDermott, J. (2013). Evolutionary and generative music informs music HCI—and vice versa. In S. Holland, K. Wilkie, P. Mulholland, & A. Seago (Eds.), Music and human-computer interaction (pp. –). London: Springer. ISBN 978-1-4471-2989-9.
McDermott, J., Griffith, N. J. L., & O’Neill, M. (2007). Evolutionary GUIs for sound synthesis. In Applications of evolutionary computing. Berlin/Heidelberg: Springer.
Miranda, E. R. (1995). An artificial intelligence approach to sound design. Computer Music Journal, 19(2), 59–75.
Miranda, E. R. (1998). Striking the right note with ARTIST: An AI-based synthesiser. In M. Chemillier & F. Pachet (Eds.), Recherches et applications en informatique musicale. Paris: Editions Hermes.
Moorer, J. A. (1973). The heterodyne filter as a tool for analysis of transient waveforms. Stanford: Stanford Artificial Intelligence Laboratory.
Moravec, O., & Stepánek, J. (2003). Verbal description of musical sound timbre in Czech language. In Proceedings of the Stockholm Music Acoustics Conference (SMAC’03), Stockholm.
Nicol, C. A. (2005). Development and exploration of a timbre space representation of audio. PhD thesis, Department of Computing Science. Glasgow: University of Glasgow.
Plomp, R. (1976). Aspects of tone sensation. New York: Academic.
Pratt, R. L., & Doak, P. E. (1976). A subjective rating scale for timbre. Journal of Sound and Vibration, 45(3), 317–328.
Pressing, J. (1992). Synthesiser performance and real-time techniques. Madison: A-R Editions.
Risset, J. C., & Wessel, D. L. (1999). Exploration of timbre by analysis and synthesis. In D. Deutsch (Ed.), The psychology of music. San Diego: Academic.
Rolland, P.-Y., & Pachet, F. (1996). A framework for representing knowledge about synthesizer programming. Computer Music Journal, 20(3), 47–58.
Sandell, G., & Martens, W. (1995). Perceptual evaluation of principal components-based synthesis of musical timbres. Journal of the Audio Engineering Society, 43(12), 1013–1028.
Seago, A. (2009). A new user interface for musical timbre design. Ph.D thesis, Faculty of Mathematics, Computing and Technology, The Open University.
Seago, A., Holland, S., & Mulholland, P. (2004). A critical analysis of synthesizer user interfaces for timbre. HCI 2004: Design for Life, Leeds, British HCI Group.
Seago, A., Holland, S., & Mulholland, P. (2005). Towards a mapping of timbral space. In Conference on Interdisciplinary Musicology (CIM05), Montreal, Canada.
Takagi, H. (2001). Interactive evolutionary computation: Fusion of the capabilities of EC optimization and human evaluation. Proceedings of the IEEE, 89(9), 1275–1296.
Takala, T., Hahn, J., Gritz, L., Geigel, J., & Lee, J.W. (1993). Using physically-based models and genetic algorithms for functional composition of sound signals, synchronized to animated motion. In Proceedings of the International Computer Conference (ICMC’93), Tokyo, Japan.
Vertegaal, R., & Bonis, E. (1994). ISEE: An intuitive sound editing environment. Computer Music Journal, 18(2), 21–29.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this chapter
Cite this chapter
Seago, A. (2013). A New Interaction Strategy for Musical Timbre Design. In: Holland, S., Wilkie, K., Mulholland, P., Seago, A. (eds) Music and Human-Computer Interaction. Springer Series on Cultural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-2990-5_9
Download citation
DOI: https://doi.org/10.1007/978-1-4471-2990-5_9
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-2989-9
Online ISBN: 978-1-4471-2990-5
eBook Packages: Computer ScienceComputer Science (R0)