Modeling and control of expressiveness in music performance

Proceedings of the IEEE

Volumn 92, Issue 4, 2004, Pages 686-701

  Canazza, Sergio ^a,b   De Poli, Giovanni ^b   Drioli, Carlo ^c   Rodà, Antonio ^a   Vidolin, Alvise ^b  

^a UNIVERSITY OF UDINE   (Italy)

^b UNIVERSITY OF PADOVA   (Italy)

^c INSTITUTE OF COGNITIVE SCIENCES AND TECHNOLOGIES   (Italy)

Author keywords

Audio; Expression communication; Multimedia; Music; Signal processing

Indexed keywords

DATA REDUCTION; GRAPHIC METHODS; INFORMATION TECHNOLOGY; MATHEMATICAL MODELS; MULTIMEDIA SYSTEMS; SIGNAL PROCESSING; SPEECH COMMUNICATION;

CONTENT COMMUNICATION; EXPRESSION COMMUNICATION; FACTOR ANALYSIS; NEUTRAL PERFORMANCE;

COMPUTER MUSIC;

EID: 14844361706     PISSN: 00189219     EISSN: None     Source Type: Journal    
DOI: 10.1109/JPROC.2004.825889     Document Type: Article

References (49)

1. A. Gabrielsson, "Expressive intentions and performance," in Music and the Mind Machine, R. Steinberg, Ed. Berlin, Germany: Springer-Verlag, 1995, pp. 35-17.
2. R. Cowie, E. Douglas-Cowie, N. Tsapatsoulis, G. Votsis, S. Kollias, W. Felenz, and J. Taylor, "Emotion recognition in human-computer interaction," IEEE Signal Processing Mag., vol. 18, pp. 32-80, Jan. 2001.
3. C. Palmer, "Music performance," Annu. Rev. Psychol., vol. 48, pp. 115-138, 1997.
4. B. H. Repp, "Diversity and commonality in music performance: an analysis of timing microstructure in Schumann's 'Träumerei'," J. Acoust. Soc. Amer., vol. 92, pp. 2546-2568, 1992.
5. M. Clynes, "Microstructural musical linguistics: composer's pulses are liked best by the best musicians," Cognition: Int. J. Cogn. Sci., vol. 55, pp. 269-310, 1995.
6. B. H. Repp, "Patterns of expressive timing in performances of a Bcethoven minuet by nineteen famous pianists," J. Acoust. Soc. Amer., vol. 88, pp. 622-641, 1990.
7. A. Gabrielsson, "Music performance, the psychology of music," in The Psychology of Music, 2nd ed. D. Deutsch, Ed. New York: Academic, 1997, pp. 35-47.
8. N. P. Todd, "A model of expressive timing in tonal music," Music Perception, vol. 3, no. 1, pp. 33-58, 1985.
9. _, "The dynamics of dynamics: a model of musical expression," J. Acoust. Soc. Amer., vol. 91, no. 6, pp. 3540-3550, 1992.
10. _, "The kinematics of musical expression," J. Acoust. Soc. Amer., vol. 97, no. 3, pp. 1940-1949, 1995.
11. G. De Poli, A. Rodá, and A. Vidolin, "Note-by-note analysis of the influence of expressive intentions and musical structure in violin performance," J. New Music Res., vol. 27, no. 3, pp. 293-321, 1998.
12. M. Clynes, "Some guidelines for the synthesis and testing of pulse microstructure in relation to musical meaning," Music Perception, vol. 7, no. 4, pp. 403-122, 1990.
13. A. Friberg, L. Frydén, L. G. Bodin, and J. Sundberg, "Performance rules for computer-control led contemporary keyboard music," Comput. Music J., vol. 15, no. 2, pp. 49-55, 1991.
14. J. Sundberg, "How can music be expressive?," Speech Commun., vol. 13, pp. 239-253, 1993.
15. A. Friberg, V. Colombo, L. Frydén, and J. Sundberg, "Generating musical performances with director musices," Cumput. Music J., vol. 24, no. 3, pp. 23-29, 2000.
16. G. De Poli, L. Irone, and A. Vidolin, "Music score interpretation using a multilevel knowledge base," Interface (J. New Music Res.), vol. 19, pp. 137-146, 1990.
17. G. Widmer, "Learning expressive performance: the structure-level approach," J. New Music Res., vol. 25, no. 2, pp. 179-205, 1996.
18. _, "Large-scale induction of expressive performance rules: first qualitative results," in Proc. 2000 Int. Comp. Music Conf., Berlin, Germany, 2000, pp. 344-347.
19. H. Katayose and S. Inokuchi, "Learning performance rules in a music interpretation system," Comput. Humanities, vol- 27, pp. 31-40, 1993.
20. J. L. Arcos and R. L. de Màntaras, "An interactive case-based reasoning approach for generating expressive music," Appl. Intell., vol. 14, no. 1, pp. 115-129, 2001.
21. T. Suzuki, T. Tokunaga, and H. Tanaka, "A case based approach to the generation of musical expression," in Proc. 1999 IJCAI, pp. 642-648.
22. R. Bresin, "Artificial neural networks based models for automatic performance of musical scores," J. New Music Res., vol. 27, no. 3, pp. 239-270, 1998.
23. R. Bresin, G. D. Poli, and R. Ghetta, "A fuzzy approach to performance rules," in Proc. XI Colloquium on Musical Informatics (CIM-95), pp. 163-168.
24. _, "Fuzzy performance rules," in Proc. KTH Symp. Grammars for Music Performance, Stockholm, Sweden, 1995, pp. 15-36.
25. O. Ishikawa, Y. Aono, H. Katayose, and S. Inokuchi, "Extraction of musical performance rule using a modified algorithm of multiple regression analysis," in Proc. KTH Symp. Grammars for Music Performance", 2000, pp. 348-351.
26. J. L. Arcos, R. L. de Màntaras, and X. Serra, "Saxex: a case-based reasoning system for generating expressive musical performances," J. New Music Res., pp. 194-210, Sept. 1998.
27. R. Bresin and A. Friberg, "Emotional coloring of computer controlled music performance," Comput. Music J., vol. 24, no. 4, pp. 44-62, 2000.
28. P. Juslin and J. Sloboda, Eds., Music and Emotion: Theory and Research. Oxford, U.K.: Oxford Univ. Press, 2001.
29. S. Canazza, G. De Poli, and A. Vidolin, "Perceptual analysis of the musical expressive intention in a clarinet performance," in Music, Gestalt, and Computing, M. Leman, Ed. Berlin. Germany: Springer-Verlag. 1997, pp. 441-450.
30. S. Canazza, A. Rodà, and N. Orio, "A parametric model of expressiveness in musical performance based on perceptual and acoustic analyses," in Proc. ICMC99 Conf., 1999, pp. 379-382.
31. C. Roads, The Computer Music Tutorial, Cambridge, MA: MIT Press, 1996.
32. B. Vercoe, W. Gardner, and E. Scheirer, "Structured audio: creation, transmission, and rendering of parametric sound representation," Proc. IEEE, vol. 86, pp. 922-940, May 1998.
33. W. J. Pielemeier, G. H. Wakefield, and M. H. Simoni, "Time-frequency analysis of musical signals," Proc. IEEE, vol. 84, pp. 1216-1230, Sept. 1996.
34. R. J. McAulay and T. F. Quatieri, "Speech analysis/synthesis based on a sinusoidal representation," IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-34, pp. 744-754, Aug. 1986.
35. X. Serra, "Musical sound modeling with sinusoids plus noise," in Musical Signal Processing. Lisse, The Netherlands: Swets & Zeitlinger, 1997, pp. 497-510.
36. Spectral modeling synthesis software [Online]. Available: http://www.iua.upf.es/sms/
37. J. M. Grey and J. W. Gordon, "Perceptual effects of spectral modification on musical timbres," J. Acoust. Soc. Am., vol. 65, no. 5. pp. 1493-1500, 1978.
38. S. Canazza, G. De Poli, C. Drioli, A. Rodà, and A. Vidolin, "Audio morphing different expressive intentions for multimedia systems," IEEE Multimedia, vol. 7, pp. 79-84, July-Sept. 2000.
39. S. Canazza and N. Orio, "The communication of emotions in jazz music: a study on piano and saxophone performances," Gen. Psychol. (Special Issue on Musical Behavior and Cognition), vol. 3/4, pp. 261-276, Mar. 1999.
40. S. Canazza, G. De Poli, and A. Vidolin, "Perceptual analysis of the musical expressive intention in a clarinet performance," in Proc. IV Int. Symp. Systematic and Comparative Musicology, 1996, pp. 31-37.
41. E. Zwicker and E. Terhardt, "Analytical expressions for critical-band rate and critical bandwidth as a function of frequency," J. Acoust. Soc. Amer., vol. 68, no. 5, pp. 1523-1525, November 1980.
42. O. Cappé, J. Laroche, and E. Moulines, "Regularized estimation of cepstrum envelope from discrete frequency points," in Proc. IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics, 1995, pp. 213-216.
43. C. Drioli, "Radial basis function networks for conversion of sound spectra," J. Appl. Signal Process., vol. 2001. no. 1, pp. 36-44, 2001.
44. S. Haykin, Neural Networks, A Comprehensive Foundation, New York: Macmillan, 1994.
45. N. Iwahashi and Y. Sagisaka, "Speech spectrum conversion based on speaker interpolation and multi-functional representation with weighting by radial basis function networks," Speech Commun., vol. 16, no. 2, pp. 139-151, 1995.
46. S. Chen, C. F. N. Cowan, and P. M. Grant, "Orthogonal least squares learning algorithm for radial basis functions networks," IEEE Trans. Neural Networks, vol. 2, pp. 302-309, Mar. 1991.
47. Algorithms and models for sound synthesis: Audio examples [Online]. Available: http://www.dei.unipd.it/ricerca/csc/research_groups/ expressive_performance_examples.html
48. P. Juslin, "Can results from studies of perceived expression in musical performances be generalized across response formats?," Psychomusicology, vol. 16, no. 3, pp. 77-101, 1997.
49. D. Cirotteau, S. Canazza, G. De Poli, and A. Rodà, "Analysis of expressive contents in synthesized music: categorical and dimensional approach," presented at the 5th International Workshop Gesture and Sign Language Based Human-Computer Interaction, Genova, Italy, 2003.