Phase-plane Representation and Visualization of Gestural Structure in Expressive Timing

Journal of New Music Research

Volumn 38, Issue 2, 2009, Pages 183-195

  Grachten, Maarten ^a   Goebl, Werner ^a   Flossmann, Sebastian ^a   Widmer, Gerhard ^a,b  

^a JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

^b AUSTRIAN RESEARCH INSTITUTE FOR ARTIFICIAL INTELLIGENCE   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 77956614467     PISSN: 09298215     EISSN: 17445027     Source Type: Journal    
DOI: 10.1080/09298210903171160     Document Type: Article

References (26)

1. Boon, J. and Decroly, O. 1995. Dynamical systems theory for music dynamics. Chaos, 5 (3): 501–508.
2. Canazza, S., De Poli, G., Rodá, A. and Vidolin, A. 2003. An abstract control space for communication of sensory expressive intentions in music performance. Journal of New Music Research, 32 (3): 281–294.
3. Clarke, E. F. 1988. “ Generative principles in music ”. In Generative Processes in Music: The Psychology of Performance, Improvisation, and Composition, Edited by: J., Sloboda. Oxford University Press.
4. Desain, P. and Honing, H. 1993. Time in Contemporary Musical Thought. Contemporary Music Review, 7 (2): 123–138. Tempo curves considered harmful. J.D. Kramer
5. Desain, P. and Honing, H. Physical motion as a metaphor for timing in music: The final ritard. Proceedings of the 1996 International Computer Music Conference. pp. 458–460. San Francisco: ICMA.
6. Dixon, S., Goebl, W. and Cambouropoulos, E. 2006. Perceptual smoothness of tempo in expressively performed music. Music Perception, 23 (3): 195–214.
7. Friberg, A. and Sundberg, J. 1999. Does music performance allude to locomotion? A model of final ritardandi derived from measurements of stopping runners. Journal of the Acoustical Society of America, 105 (3): 1469–1484.
8. Gabrielsson, A. 2003. Music performance research at the millennium. The Psychology of Music, 31 (3): 221–272.
9. Goodall, C. 1991. Procrustes methods in the statistical analysis of shape. Journal of the Royal Statistical Society. Series B (Methodological), 53 (2): 285–339.
10. Grachten, M., Goebl, W., Flossmann, S. and and Widmer, G. Intuitive visualization of gestures in expressive timing: A case study on the final ritard. Proceedings of the International Conference on Music Perception and Cognition.
11. Honing, H. When a good fit is not good enough: a case study on the final ritard. Proceedings of the 8th ICMPC. Evanston, IL. Edited by: Lipscomb, S. D., Ashley, R., Gjerdingen, R. O. and Webster, P. pp. 510–513. Adelaide: Causal Productions.
12. Honing, H. 2005. Is there a perception-based alternative to kinematic models of tempo rubato?. Music Perception, 23 (1): 79–85.
13. JuslinP. SlobodaJ. 2001 Music and Emotion: Theory and Research Oxford University Press
14. Langner, J. and Goebl, W. 2003. Visualizing expressive performance in tempo-loudness space. Computer Music Journal, 27 (4): 69–83.
15. Métois, E. Musical sound information: Musical gestures and embedding synthesis. (PhD thesis). Massachusetts Institute of Technology.
16. Palmer, C. 1997. Music performance. Annual Review of Psychology, 48: 115–138.
17. Ramsay, J. and Silverman, B. 2005. Functional Data Analysis, 2nd ed, New York: Springer.
18. Repp, B. H. 1992. Diversity and commonality in music performance—an analysis of timing microstructure in Schumann's ‘Träumerei’. Journal of the Acoustical Society of America, 92 (5): 2546–2568.
19. Repp, B. H. 1998. A microcosm of musical expression: I. Quantitative analysis of pianists' timing in the initial measures of Chopin's etude in E major. Journal of the Acoustical Society of America, 104 (2): 1085–1100.
20. Schoner, B. State reconstruction for determining predictability in driven nonlinear acoustical systems. (Master's thesis). Rheinisch-Westphalische Technische Hochschule Aachen.
21. Sundberg, J., Friberg, A. and Frydén, L. 1991. “ Common secrets of musicians and listeners: An analysis-by-synthesis study of musical performance ”. In Representing Musical Structure, Edited by: Howell, P., West, R. and Cross, I. 161–197. Academic Press Ltd. Cognitive Science series. London
22. Todd, N. P. 1985. A model of expressive timing in tonal music. Music Perception, 3: 33–58.
23. Todd, N. P. 1992. The dynamics of dynamics: A model of musical expression. Journal of the Acoustical Society of America, 91: 3540–3550.
24. Truslit, A. 1938. Gestaltung und Bewegung in der Musik, Berlin-Lichterfelde: Chr. Friedrich Vieweg.
25. Widmer, G. 2003. Discovering simple rules in complex data: A meta-learning algorithm and some surprising musical discoveries. Artificial Intelligence, 146 (2): 129–148.
26. Widmer, G., Dixon, S., Goebl, W., Pampalk, E. and Tobudic, A. 2003. In search of the Horowitz factor. AI Magazine, 24 (3): 111–130.