Computational modeling of music cognition: Problem or solution?

Music Perception

Volumn 16, Issue 1, 1998, Pages 151-166

  Desain, Peter ^a   Honing, Henkjan ^a   Vanthienen, Huub ^a   Windsor, Luke ^a  

^a RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0347379635     PISSN: 07307829     EISSN: None     Source Type: Journal    
DOI: 10.2307/40285783     Document Type: Article

References (46)

1. Abelson, H., & Sussman, G. J. (1985). Structure and interpretation of computer programs. Cambridge, MA: MIT Press.
2. Anderson, J. R. (1983). The architecture of cognition. Cambridge, MA: Harvard University Press.
3. Besson, M., & Faïta, F. (1995). An event-related potential (ERP) study of musical expectancy: Comparisons of musicians with nonmusicians. Journal of Experimental Psychology: Human Perception and Performance, 21(6), 1278-1296.
4. Bharucha, J. J. (1987). Music cognition and perceptual facilitation: A connectionist framework. Music Perception, 5(1), 1-30.
5. Bharucha, J. J. (1991). Pitch, harmony, and neural nets: A psychological perspective. In P. M. Todd & D. G. Loy (Eds.), Music and connectionism. Cambridge, MA: MIT Press.
6. Brachman, R. J., & Smith, B. C. (1980). Special issues on knowledge representation. SIGART Newsletter, 70, 103-104.
7. Desain, P. (1991). Parsing the parser: A case study in programming style. Computers in Music Research, 1(2), 39-90.
8. Desain, P. (1993). A connectionist and a traditional AI quantizer, symbolic versus sub-symbolic models of rhythm perception. Contemporary Music Review, 9, 239-254.
9. Desain, P., & Honing, H. (1992). Music, mind and machine: Studies in computer music, music cognition and artificial intelligence. Amsterdam: Thesis Publishers.
10. Desain, P., & Honing, H. (1994). Foot-tapping: A brief introduction to beat induction. In Proceedings of the 1994 International Computer Music Conference (pp. 78-79). San Francisco: International Computer Music Association.
11. Desain, P., & Honing, H. (1996). Physical motion as a metaphor for timing in music: The final ritard. In Proceedings of the 1996 International Computer Music Conference (pp. 458-460). San Francisco: International Computer Music Association.
12. Desain, P., & Honing, H. (in press). Computational models of beat induction: The rule-based approach. Journal of New Music Research.
13. Deutsch, D. (Ed.) (1982). The psychology of music. New York: Academic Press.
14. Dowling, W. J., & Harwood, D. (1986). Music cognition. New York: Academic Press.
15. Fraisse, P. (1982). Rhythm and tempo. In D. Deutsch (Ed.), The psychology of music (pp. 149-180). New York: Academic Press.
16. Friedman, D. P., Wand, M., & Haynes, C. T. (1992). Essentials of programming languages. Cambridge, MA: MIT Press.
17. Gjerdingen, R. O. (1994). Apparent motion in music? Music Perception, 11(4), 225-370.
18. Honing, H. (1995). The vibrato problem: Comparing two solutions. Computer Music Journal, 19(3), 32-49.
19. Jacobs, A. M., & Grainger, J. (1994). Models of visual word recognition: Sampling the state of the art. Journal of Experimental Psychology: Human Perception and Performance, 20(6), 1311-1334.
20. Janata, P. (1995). ERP measures assay the degree of expectancy violation of harmonic contexts in music. Journal of Cognitive Neuroscience, 7(2), 153-167.
21. Jones, M. R., & Boltz, M. (1989). Dynamic attending and responses to time. Psychological Review, 96, 459-491.
22. Kiczales, G., des Rivières, J., & Bobrow, D. G. (1991). The art of the Metaobject Protocol. Cambridge, MA: MIT Press.
23. Kosslyn, S. M. (1994). Image and brain: The resolution of the imagery debate. Cambridge, MA: MIT Press.
24. Krumhansl, C. L. (1990). Cognitive foundations of musical pitch. New York: Oxford University Press.
25. Krumhansl, C. L., & Kessler, E. J. (1982). Tracing the dynamic changes in perceived tonal organisation in a spatial representation of musical keys. Psychological Review, 89(4), 334-368.
26. Large, E. W., & Jones, M. R. (in press). The dynamics of attending: How we track time varying events. Psychological Review.
27. Large, E. W., & Kolen, J. F. (1994). Resonance and the perception of musical meter. Connection Science, 6(1), 177-208.
28. Laird, J., Newell, A., & Rosenbloom, P. (1987). SOAR: An architecture for general intelligence. Artificial Intelligence, 33,1-64.
29. Lerdahl, F., & Jackendoff, R. (1983). A generative theory of tonal music. Cambridge, MA: MIT Press.
30. Longuet-Higgins, H. C. (1987). Mental processes. Cambridge, MA: MIT Press.
31. Lewin, D. (1987). Generalized musical intervals and transformations. London: Yale University Press.
32. Neely, J. H. (1991). Semantic priming effects in visual word recognition: A selective review of current findings and theories. In D. Besner & G. W. Humphreys (Eds.), Basic processes in reading: Visual word recognition (pp. 264-336), Hillsdale, NJ: Erlbaum.
33. Newell, A. (1990). Unified theories of cognition. Cambridge, MA: Harvard University Press.
34. Partridge, T., & Wilks, Y. (Eds.) (1990). The foundations of artificial intelligence, a sourcebook. Cambridge, England: Cambridge University Press.
35. Partsch, H. A. (1990). Specification and transformation of programs: A formal approach to software development. Berlin: Springer.
36. Povel, D. J., & Essens, P. (1985). Perception of temporal patterns. Music Perception, 2(4), 411-440.
37. Pinker, S. (1995). The language instinct. London: Penguin Books.
38. Pylyshyn, Z. (1979). Complexity and the study of human artificial intelligence. In M. Ringle (Ed.), Philosophical perspectives in artificial intelligence (pp. 23-56). Atlantic Highlands, NJ: Humanities Press.
39. Pylyshyn, Z. W. (1984). Computation and cognition: Toward a foundation for cognitive science. Cambridge, MA: MIT Press.
40. Rich, C., & Waters, R. (1986). Readings in artificial intelligence and software engineering. Los Altos, CA: Morgan Kaufman.
41. Ringle, M. (1983). Psychological studies and artificial intelligence. The AI Magazine, Winter/Spring, 37-43.
42. Sloboda, J. (1985). The musical mind: The cognitive psychology of music. Oxford: Clarendon Press.
43. Smith, J. O. (1992). Physical modeling using digital waveguides. Computer Music Journal, 16(4), 74-91.
44. Stoy, J. E. (1977). Denotational semantics: The Scott-Strachey approach to programming language theory. Cambridge, MA: MIT Press.
45. Todd, N. P. M. (1993). Vestibular feedback in musical performance: Response to Somatosensory Feedback in Musical Performance (edited by Sundberg and Verrillo). Music Perception, 10(3), 379-382.
46. Wilks, Y. A. (1990). One small head: Models and theories. In D. Partridge & Y. A. Wilks (Eds.). The foundations of artificial intelligence (pp. 121-134). Cambridge, England: Cambridge University Press.