Abstract
Studies of breakdowns in music performance can provide rich information about the planning activities required for music performance, as well as offer significant advantages over studies of skilled performance in other domains (Palmer & van de Sande, 1993). Yet despite the potential benefits, documented evidence of errors in music performance is scarce, primarily because of methodological limitations. One important practical problem that arises is how to find a correspondence between the actual performance and the score, or intended performance. When performances are long and complex, with potentially many errors, matching a performance to a musical score becomes a nontrivial task. This paper describes an algorithm for this task, developed in the context of a study of music production errors. The solution to the problem utilizes dynamic programming techniques and runs in polynomial time.
Article PDF
Similar content being viewed by others
References
Brassard, G., &Bratley, P. (1988).Algorithmics: Theory and practice. Englewood Cliffs, NJ: Prentice-Hall.
Cormen, T. H., Leiserson, C. E., &Rivest, R. L. (1990).Introduction to Algorithms. Cambridge, MA: MIT Press.
Dell, G. S. (1986). A spreading-activation theory of retrieval in sentence production.Psychological Review,93, 283–321.
Garrett, M. F. (1975). The analysis of sentence production. In G. H. Bower (Ed),The psychology of learning and motivation (pp. 133–177). San Diego: Academic Press.
Palmer, C. (1989). Computer graphics in music performance research.Behavior Research Methods, Instruments, & Computers,21, 265–270.
Palmer, C. (1992). The role of interpretive preferences in music performance. In M. R. Jones & S. Holleran (Eds.),Cognitive bases of musical communication (pp. 249–262). Washington, DC: American Psychological Association.
Palmer, C., &van de Sande, C. (1993). Units of knowledge in music performance.Journal of Experimental Psychology: Learning, Memory, & Cognition,19, 457–470.
Author information
Authors and Affiliations
Additional information
This research was supported by NIMH Grant 1R29-MH45764 to Caroline Palmer. I thank John Kolen and Caroline Palmer for comments on an earlier version of this paper.
Rights and permissions
About this article
Cite this article
Large, E.W. Dynamic programming for the analysis of serial behaviors. Behavior Research Methods, Instruments, & Computers 25, 238–241 (1993). https://doi.org/10.3758/BF03204504
Issue Date:
DOI: https://doi.org/10.3758/BF03204504