Predicting the similarity between expressive performances of music from measurements of tempo and dynamics

Journal of the Acoustical Society of America

Volumn 117, Issue 1, 2005, Pages 391-399

  Timmers, Renee ^a,b  

^a AUSTRIAN RESEARCH INSTITUTE FOR ARTIFICIAL INTELLIGENCE   (Austria)

^b KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTICS; MATHEMATICAL MODELS; SENSORY PERCEPTION;

AUDIO FILES; CONVENTIONAL MODELS; DATA REPRESENTATION; TEMPO;

MUSICAL INSTRUMENTS;

ACOUSTICS; ARTICLE; CORRELATION ANALYSIS; DATA ANALYSIS; FREQUENCY ANALYZER; FREQUENCY MODULATION; LOUDNESS; MUSIC; PREDICTION; PRIORITY JOURNAL; RATING SCALE; SOUND INTENSITY; TASK PERFORMANCE; TEMPO; VALIDATION PROCESS;

ACOUSTICS; ADULT; AUDITORY PERCEPTION; FEMALE; FORECASTING; HUMANS; JUDGMENT; LOUDNESS PERCEPTION; MALE; MIDDLE AGED; MODELS, THEORETICAL; MUSIC; PERIODICITY;

EID: 12344271293     PISSN: 00014966     EISSN: None     Source Type: Journal    
DOI: 10.1121/1.1835504     Document Type: Article

References (33)

1. Bengtsson, I., and Gabrielsson, A. (1983). "Analysis and synthesis of musical rhythm," in Studies of Music Performance, edited by J. Sundberg (Royal Swedish Academy of Music, Stockholm), pp. 76-181.
2. Clarke, E. F. (1993). "Imitating and evaluating real and transformed musical performances," Music Percept. 10, 317-341.
3. Dixon, S. (2001). "Automatic extraction of tempo and beat from expressive performances," J. New Music Res. 30, 39-58.
4. Dixon, S., and Goebl, W. (2001). "Pinpointing the Beat: Tapping to Expressive Performances," in Proceedings of the 7th International Conference on Music Perception and Cognition (ICMPC7, Sydney, Australia), pp. 617-620.
5. Friberg, A., and Sundberg, J. (1999). "Does music performance allude to locomotion? A model of final ritardandi derived from measurements of stopping runners," J. Acoust. Soc. Am. 105, 1469-1484.
6. Friberg, A., Frydén, L., Bodin, L. G., and Sundberg, J. (1991). "Performance rules for computer-controlled contemporary keyboard music," Comput. Music J. 15, 49-55.
7. Gabrielsson, A. (1987). "Once again: The theme from Mozart's Piano Sonata in A major: A comparison of five performances," in Action and Perception in Rhythm and Music, edited by A. Gabrielsson (Royal Swedish Academy of Music, Stockholm), pp. 81-103.
8. Gabrielsson, A. (1988). "Timing in music performance and its relation to music experience," in Generative Processes in Music. The Psychology of Performance, Improvisation, and Composition, edited by J. Sloboda (Clarendon, Oxford), pp. 27-51.
9. Gjerdingen, R. O. (1988). "Shape and motion in the microstructure of song," Music Percept. 6, 35-64.
10. Hevner, K. (1937). "The affective value of pitch and tempo in music," Am. J. Psychol. 49, 621-630.
11. Honing, H. (1990). "POCO, An Environment for Analysing, Modifying and Generating Expression in Music," in Proceedings of the 1990 International Computer Music Association (CMA, San Francisco), pp. 364-368.
12. Kendall, R. A., and Carterette, E. C. (1990). "The communication of musical expression," Music Percept. 8, 129-164.
13. Kronman, U., and Sundberg, J. (1987). "Is the musical ritard an allusion to physical motion?" in Action and Perception in Rhythm and Music, edited by A. Gabrielsson (Royal Swedish Academy of Music, Stockholm).
14. Langner, J., and Goebl, W. (2003). "Visualizing expressive performance in tempo-loudness space," Comput. Music J. 27, 69-83.
15. Levitin, D. J., and Cook, P. R. (1996). "Memory for musical tempo: Additional evidence that auditory memory is absolute," Percept. Psychophys. 58, 927-935.
16. Nakajima, Y. (1987). "A model of empty duration perception," Percept. 16, 485-520.
17. Palmer, C. (1989). "Mapping musical thought to musical performance," J. Exp. Psychol. Hum. Percept. Perform. 15, 331-346.
18. Palmer, C. (1996). "On the assignment of structure in music performance," Music Percept. 14, 23-56.
19. Pampalk, E., Rauber, A., and Merkl, D. (2002). "Content-based organization and visualization of music archives," in Proceedings of the 10th ACM International Conference on Multimedia (MM'02, Juan-les-Pins, France), pp. 570-579.
20. Repp, B. H. (1990). "Patterns of expressive timing in performances of a Beethoven minuet by 19 famous pianists," J. Acoust. Soc. Am. 88, 622-641.
21. Repp, B. H. (1992a). "Diversity and commonality in music performance-An analysis of timing microstructure in Schumann's Traumerei," J. Acoust. Soc. Am. 92, 2546-2568.
22. Repp, B. H. (1992b). "Probing the cognitive representation of musical time: Structural constraints on the perception of timing perturbations," Cognition 44, 241-281.
23. Repp, B. H. (1994). "Relational invariance of expressive microstructure across global tempo changes in music performance: An exploratory study," Psychol. Res. 56, 269-284.
24. Repp, B. H. (1998). "Obligatory 'expectations' of expressive timing induced by perception of musical structure," Psychol. Res. 61, 33-43.
25. Repp, B. H. (2000). "Pattern typicality and dimensional interactions in pianists' imitation of expressive timing and dynamics," Music Percept. 18, 173-211.
26. Seashore, C. E. (1938). Psychology of Music (Dover, New York).
27. Sundberg, J., Friberg, A., and Frydén, L. (1989). "Rules for automated performances of ensemble music," Contemp. Music Rev. 3, 89-109.
28. Thompson, W. F., Sundberg, J., Friberg, A., and Frydén, L. (1989). "The use of rules for expression in the performance of melodies," Psychol. Music 17, 63-82.
29. Timmers, R. (2003). "On the contextual appropriateness of expression," Music Percept. 20, 225-240.
30. Timmers, R., and Honing, H. (2002). "On music performance, theories, measurement and diversity," Cognitive Processing (International Quarterly of Cognitive Sciences) 1-2, 1-19.
31. Timmers, R., Ashley, R., Desain, P., and Heijink, H. (2000). "The influence of musical context on tempo rubato," J. New Music Res. 29, 131-158.
32. Todd, N. P. (1992). "The dynamics of dynamics: A model of musical expression," J. Acoust. Soc. Am. 91, 3540-3550.
33. Zanon, P., and Widmer, G. (2003). "Learning to recognize famous pianists with machine learning techniques," in Proceedings of the Third Stockholm Music Acoustics Conference (SMAC03, Stockholm, Sweden).