Melodic segmentation: structure, cognition, algorithms

Title: Melodic segmentation: structure, cognition, algorithms
Source document: Musicologica Brunensia. 2017, vol. 52, iss. 1, pp. 53-61
  • ISSN
    1212-0391 (print)
    2336-436X (online)
Type: Article
License: Not specified license
Segmentation of melodies into smaller units (phrases, themes, motifs, etc.) is an important process in both music analysis and music cognition. Also, segmentation is a necessary preprocessing step for various tasks in music information retrieval. Several algorithms for automatic segmentation have been proposed, based on different music-theoretical backgrounds and computing approaches. Rule-based models operate on a given set of logical conditions. Learning-based models, originating in linguistics, compute segmentation criteria on the basis of statistical parameters of a training corpus and/or of the given composition. The aim of this preliminary study is to propose and describe a new segmentation algorithm that is rule-based, parsimonious, and unambiguous.
[1] ALTMANN, Gabriel – SCHWIBBE, Michael. Das Menzerathsche Gesetz in informationsverarbeitenden Systemen. Hildesheim/Zürich/New York: Olms, 1989.

[2] BELLINGHAM, Jane. Phrase. The Oxford Companion to Music. Ed. Alison Latham. Oxford Music Online. Oxford University Press. Web. 20. 12. 2016.

[3] BOD, Rens. Memory-based models of melodic analysis: Challenging the Gestalt principles. Journal of New Music Research, 2001, 30(3), pp. 27–36.

[4] BORODA, Moisej. Zur Bestimmung einer phrasenänlichen melodischen Informationseinheit in der Musik. In: Orlov, J.K., Boroda, M.G., Nadarejšvili, I.Š. (Eds.): Sprache, Text, Kunst. Quantitative Analysen (pp. 222–230). Bochum: Brockmeyer, 1982.

[5] BRENT, Michael. An efficient, probabilistically sound algorithm for segmentation and word discovery. Machine Learning, 1999a, 34(1–3), pp. 71–105. | DOI 10.1023/A:1007541817488

[6] BRENT, Michael. Speech segmentation and word discovery: A computational perspective. Trends in Cognitive Sciences, 1999b, 3(8), pp. 294–301. | DOI 10.1016/S1364-6613(99)01350-9

[7] CAMBOUROPOULOS, Emilios. Musical parallelism and melodic segmentation: A computational approach. Music Perception: An Interdisciplinary Journal, 2006, 23(3), pp. 249–268. | DOI 10.1525/mp.2006.23.3.249

[8] CAMBOUROPOULOS, Emilios. The local boundary detection model (LBDM) and its application in the study of expressive timing. In: Proceedings of the International Computer Music Conference (pp. 17–22). San Francisco: ICMA, 2001.

[9] DELIÈGE, Irène. Grouping conditions in listening to music: An approach to Lerdahl & Jackendoff's grouping preference rules. Music Perception: An Interdisciplinary Journal, 1987, 4(4), pp. 325–359. | DOI 10.2307/40285378

[10] DOWLING, William. Rhythmic groups and subjective chunks in memory for melodies. Perception and Psychophysics, 1973, 14(1), pp. 37–40. | DOI 10.3758/BF03198614

[11] DRABKIN, William. Motif. Grove Music Online. Oxford Music Online. Oxford University Press. Web. 20. 12. 2016.

[12] FRANKLAND, Bradley – COHEN, Annabel. Parsing of melody: Quantification and testing of the local grouping rules of Lerdahl and Jackendoff's A Generative Theory of Tonal Music. Music Perception: An Interdisciplinary Journal, 2004, 21(4), pp. 499–543. | DOI 10.1525/mp.2004.21.4.499

[13] LERDAHL, Fred – JACKENDOFF, Ray. A Generative Grammar of Tonal Music. Cambridge, Mass.: The MIT Press, 1983.

[14] NARMOUR, Eugene. The Analysis and Cognition of Basic Melodic Structures: The Implication-Realization model. Chicago: University of Chicago Press, 1990.

[15] NARMOUR, Eugene. The Analysis and Cognition of Melodic Complexity: The Implication-Realization Model. Chicago: University of Chicago Press, 1992.

[16] PALMER, Caroline. Music performance. Annual Review of Psychology, 1997, 48(1), pp. 115–138. | DOI 10.1146/annurev.psych.48.1.115

[17] PATEL, Aniruddh – DANIELE, Joseph. An empirical comparison of rhythm in language and music. Cognition, 2003, 87(1), pp. B35-B45. | DOI 10.1016/S0010-0277(02)00187-7

[18] PEARCE, Marcus – MÜLLENSIEFEN, Daniel – WIGGINS, Geraint. Melodic grouping in music information retrieval: New methods and applications. In: Advances in music information retrieval. Springer, Berlin Heidelberg, 2010, pp. 364–388.

[19] REPP, Bruno H. Diversity and commonality in music performance: An analysis of timing micro-structure in Schumann's "Träumerei". The Journal of the Acoustical Society of America, 1992, 92(5), pp. 2546–2568. | DOI 10.1121/1.404425

[20] SCHENKER, Heinrich. Harmony. Chicago: University of Chicago Press, 1980.

[21] SLOBODA, John. The effect of item position on the likelihood of identification by inference in prose reading and music reading. Canadian Journal of Psychology, 1976, 30(4), pp. 228–237. | DOI 10.1037/h0082064

[22] TEMPERLEY, David. The Cognition of Basic Musical Structures. Cambridge, Mass., The MIT Press, 2001.

[23] WERTHEIMER, Max: Untersuchungen zur Lehre von der Gestalt II. Psychologische Forschung, 1923, 4(1), pp. 301–350. | DOI 10.1007/BF00410640