The ‘chunk’ phenomenon has attracted some attention lately. In the auditory domain a chunk is seen as a segment of sound. This work first investigates theories of chunks from cognitive science and musicology. We define the chunk as a closed entity of a certain size and with a dynamic structure containing a peak. The perceptual analysis of three songs leads to a collection of chunks, classified according to their internal structure. Common signal processing methods are then used to extract loudness, pitch and brightness of the chunks. The features are modeled in a simple chunk model, consisting of height, slope, peak and peak position, and the values of the model are furthermore estimated for each chunk. Histogram plots are used to give values for the probability of each chunk type. The model parameters from the features are finally compared to the parameters found by listening and determining the shape of each chunk.


Music retrieval cognition chunking feature extraction temporal perception 


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  1. 1.
    “Phrase”. In: Kennedy, M. (ed.) The Oxford Dictionary of Music, 2nd ed. rev. Oxford Music Online, (accessed October 5, 2008)
  2. 2.
    Chew, G.: “Articulation and phrasing”. In Grove Music Online. Oxford Music Online, (accessed October 5, 2008)
  3. 3.
    Jensen, K., Kühl, O.: Retrieving Musical Chunks. In: Proceedings of ICMC 2008. Re:New, Copenhagen (2008)Google Scholar
  4. 4.
    Wertheimer, M.: ‘Gestalt Theory’. Social Research 11 (1944)Google Scholar
  5. 5.
    Jackendoff, R.: Semantics and Cognition Cambridge. The MIT Press, Mass (1983)Google Scholar
  6. 6.
    Gärdenfors, P.: Conceptual Spaces. The MIT Press, Cambridge (2000)zbMATHGoogle Scholar
  7. 7.
    Miller, G.: The Magical Number Seven, Plus or Minus Two. Psychological Review 63, 81–97 (1956)CrossRefGoogle Scholar
  8. 8.
    Lerdahl, F., Jackendoff, R.: A Generative Theory of Tonal Music. The MIT Press, Cambridge (1983)Google Scholar
  9. 9.
    Kühl, O.: Musical Semantics. Peter Lang, Bern (2007)CrossRefGoogle Scholar
  10. 10.
    Pöppel, E.: A hierarchical model of temporal perception. Trends in Cognitive Science 1/2, 56–61 (1997)CrossRefGoogle Scholar
  11. 11.
    Snyder, B.: Music and Memory. The MIT Press, Cambridge (2000)Google Scholar
  12. 12.
    McNeill, D.: Gesture and Thought. The University of Chicago Press, Chicago (2005)CrossRefGoogle Scholar
  13. 13.
    Clarke, E.: Empirical Methods in the Study of Performance. In: Clarke, E., Cook, N. (eds.) Empirical Musicology, pp. 77–102. Oxford University Press, Oxford (2004)CrossRefGoogle Scholar
  14. 14.
    Getz, S.: People Time, Mercury (1992)Google Scholar
  15. 15.
    Walters, J.: Jamie Walters, Atlantic (1994)Google Scholar
  16. 16.
    Barenboim, D.: Mozart: Complete Piano Sonatas and Variations, EMI Classics (1991)Google Scholar
  17. 17.
    Zwicker, E., Fastl, H.: Psychoacoustics: Facts and Models. Springer, Heidelberg (1990)Google Scholar
  18. 18.
    Bartsch, M.A., Wakefield, G.H.: To catch a chorus: Using chroma-based representations for audio thumbnailing. In: Proceedings of the Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 15–18 (2001)Google Scholar
  19. 19.
    Rabiner, L.R.: On the use of autocorrelation analysis for pitch detection. IEEE Trans. ASSP ASSP-25(1) (February 1977)Google Scholar
  20. 20.
    Beauchamp, J.: Synthesis by spectral amplitude and “Brightness” matching of analyzed musical instrument tones. J. Acoust. Eng. Soc. 30(6) (1982)Google Scholar
  21. 21.
    Moré, J.J.: The Levenberg-Marquardt algorithm: Implementation and theory. In: Watson, G.A. (ed.). Lecture notes in mathematics. Springer, Heidelberg (1977)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Kristoffer Jensen
    • 1
  • Ole Kühl
    • 1
  1. 1.Aalborg University EsbjergEsbjergDenmark

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