Skip to main content

Determining Key Boundaries

  • Chapter
  • First Online:
Mathematical and Computational Modeling of Tonality

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 204))

  • 1366 Accesses

Abstract

Computer models for determining key boundaries are important tools for computer analysis of music, computational modeling of music cognition, content-based categorization and retrieval of music information and automatic generating of expressive performance. This chapter describes a Boundary Search Algorithm (BSA) for determining points of modulation in a piece of music using a geometric model for tonality called the Spiral Array. For a given number of key changes, the computational complexity of the algorithm is polynomial in the number of pitch events. We present and discuss computational results for two selections from J.S. Bach’s A Little Notebook for Anna Magdalena. Comparisons between the choices of an expert listener and the algorithm indicates that in human cognition, a dynamic interplay exists between memory and present knowledge, thus maximizing the opportunity for the information to coalesce into meaningful patterns.

This chapter is a minor revision of the work, “The Spiral Array: An Algorithm for Determining Key Boundaries” by E. Chew, published in Anagnostopoulou, C., Ferrand, M., Smaill, A. (eds.): Music and Artificial Intelligence, LNCS/LNAI 2445, pp. 18–31. Springer-Verlag, Heidelberg (2002)

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Auhagen, W., Vos, P.G.: Experimental methods in tonality induction research: a review. Music Percept. 17(4), 417–436 (2000)

    Article  Google Scholar 

  2. Bamberger, J.S.: Developing Musical Intuition. Oxford University Press, New York (2000)

    Google Scholar 

  3. Brown, R.: Tonal implications of the diatonic set. In Theory Only 5, 3–21 (1981)

    Google Scholar 

  4. Chew, E.: Towards a mathematical model of tonality. Ph.D. Dissertation, MIT (2000)

    Google Scholar 

  5. Chew, E.: Modeling tonality: applications to music cognition. In: Proceedings of the 23rd Annual Meeting of the Cognitive Science Society (2001)

    Google Scholar 

  6. Cohn, R.: Neo-Riemannian operations, parsimonious trichords, and their tonnetz representations. J. Music Theory 41(1), 1–66 (1997)

    Article  Google Scholar 

  7. Cohn, R.: Introduction to Neo-Riemannian theory: a survey and a historical perspective. J. Music Theory 42(2), 167–180 (1998)

    Article  Google Scholar 

  8. Gjerdingen, R. (ed.): Music Percept. 17, 4 (2000) Note: Special issue on tonality induction.

    Google Scholar 

  9. Krumhansl, C.L.: Cognitive Foundations of Musical Pitch. Oxford University Press, New York (1990)

    Google Scholar 

  10. Lewin, D.: Generalized Musical Intervals and Transformations. Yale University Press, CT (1987)

    Google Scholar 

  11. Longuet-Higgins, H. C., Steedman, M. J.: On interpreting Bach. B. Meltzer and D. Michie (eds.). Machine Intelligence, vol. 6, p. 221. Edinburgh U Press, Edinburgh (1971)

    Google Scholar 

  12. Longuet-Higgins, H.C.: Mental Processes. MIT Press, MA (1987)

    Google Scholar 

  13. Rowe, R.: Key induction in the context of interactive performance. Music Percept. 17(4), 511–530 (2000)

    Article  Google Scholar 

  14. Shmulevich, I., Yli-Harja, O.: Localized key-finding: algorithms and applications. Music Percept. 17(4), 531–544 (2000)

    Article  Google Scholar 

  15. Steedman, M.: The well-tempered computer. Phil. Trans. R. Soc. Lond. 349, 115–131 (1994)

    Article  Google Scholar 

  16. Temperley, D.: The perception of harmony and tonality: an algorithmic approach. Ph.D. Dissertation, Columbia University (1996)

    Google Scholar 

  17. Temperley, D.: What’s key for key? The Krumhansl-Schmuckler key-finding algorithm reconsidered. Music Percept. 17(1), 65–100 (1999)

    Article  Google Scholar 

  18. Vos, P.G., Van Geenen, E.W.: A parallel-processing key-finding model. Music Percept. 14(2), 185–223 (1996)

    Article  Google Scholar 

Download references

Acknowledgments

I thank Jeanne Bamberger for her guidance and cogent advice that made this research possible; and Martin Brody for his insightful comments on interpreting the results in an early version of this document.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Elaine Chew .

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this chapter

Cite this chapter

Chew, E. (2014). Determining Key Boundaries. In: Mathematical and Computational Modeling of Tonality. International Series in Operations Research & Management Science, vol 204. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-9475-1_6

Download citation

Publish with us

Policies and ethics