Melodic modeling: A comparison of scale degree and interval

International Computer Music Conference, ICMC 2006

Volumn , Issue , 2006, Pages 495-498

  Li, Yipeng ^a   Huron, David ^b  

^a The Ohio State University   (United States)

^b OHIO STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATES; COMPUTER MUSIC;

INTERVAL MEASUREMENT; INTERVAL MODELS; MARKOV MODEL; SUCCESSION MODEL;

MARKOV PROCESSES;

EID: 84923555921     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Coons, E. and D. Kraehenbuehl (1958). Information as a measure of structure in music. Journal of Music Theory 2, 127-161.
2. Desain, P., H. Honing, and M. Sadakata (2003). Predicting rhythm perception from rhythm production and score counts: The Bayesian approach. Paper presented at the Society for Music Perception and Cognition 2003 Conference.
3. Eerola, T. (2004). Data-driven influences on melodic expectancy: continuation in north Sami Yoiks rated by South African traditional healers. In S. D. Lipscomb, R. Ashley, R. O. Gjerdingen, and P. Webster (Eds.), Proceedings of the 8th International Conference of Music Perception and Cognition, pp. 83-87. Evanston, Ill.: Casual Productions.
4. Eerola, T. and P. Toiviainen (2004). Suomen Kansan eSävelmät. Finnish Folk Song Database. Available: http://www.jyu.fi/musica/sks/.
5. Goldstone, J. A. (1979). A general mathematical theory of expectation models of music. Ph. D. thesis, University of Southern California.
6. Huron, D. (1995). The Humdrum Toolkit: Reference Manual. Stanford, California: Center for Computer Assisted Research in the Humanities.
7. Huron, D. (2006). Sweet Anticipation: Music and the Psychology of Expectation. Cambridge, Massachusetts: MIT Press.
8. Krumhansl, C. L., J. Louhivuori, P. Toiviainen, T. Järvine, and T. Eerola (1999). Melodic expectancy in Finnish folk hymns: Convergence of statistical, behavioral, and computational approaches. Music Perception 17(2), 151-195.
9. Margulis, E. H. (2005). A model of melodic expectation. Music Perception 21(4), 663-714.
10. Margulis, E. H. andW. H. Levine (2004). Melodic expectation: A priming study. In S. D. Lipscomb, R. Ashley, R. O. Gjerdingen, and P. Webster (Eds.), Proceedings of the 8th International Conference of Music Perception and Cognition, pp. 364-366. Evanston, Ill.: Casual Productions.
11. Narmour, E. (1990). The Analysis and Cognition of Basic Melodic Structures: The Implication-Realization Model. Chicago: University of Chicago Press.
12. Narmour, E. (1992). TThe Analysis and Cognition of Melodic Complexity: The Implication-Realization Model. Chicago: University of Chicago Press.
13. Saffran, J. R., E. K. Johnson, R. N. Aslin, and E. Newport (1999). Statistical learning of tone sequences by human infants and adults. Cognition 70, 27-52.
14. Schaffrath, H. (1995). The Essen Folksong Collection. In D. Huron (Ed.). Stanford, California: Center for Computer Assisted Research in the Humanities.
15. Schellenberg, E. G. (1996). Expectancy in melody: Tests of the implication-realization model. Cognition 58, 75-125.
16. Schellenberg, E. G. (1997). Simplifying the implicationrealization model. Music Perception 14(3), 295-318.
17. Schellenberg, E. G., M. Adachi, K. T. Purdy, and M. C. McKinnon (2002). Expectancy in melody: Tests of children and adults. Journal of Experimental Psychology: General 131(4), 511-537.
18. Schmuckler, M. A. (1989). Expectation in music: Investigation of melodic and harmonic processes. Music Perception 7(2), 109-150.
19. Schmuckler, M. A. (1990). The performance of global expectation. Psychomusicology 9, 122-147.
20. Schmuckler, M. A. (1997). Expectancy effects in memory for melodies. Canadian Journal of Experimental Psychology 51(4), 292-305.
21. Wu, M., D. L.Wang, and G. J. Brown (2003). A multipitch tracking algorithm for noisy speech. IEEE Trans. Speech Audio Processing 11, 229-241.