Skip to main content

Interval Distinction on Melody Perception for Music Information Retrieval

  • Conference paper
Computer Music Modeling and Retrieval. Genesis of Meaning in Sound and Music (CMMR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5493))

Included in the following conference series:

  • 1262 Accesses

Abstract

The problem of musical query processing can be envisioned as a substring- matching problem when the melody is represented as a sequence of notes associated with a set of attributes. In comparison of two musical sequences, one of the important problems is to determine the weights of each operation. This paper presents an alternate weighting-scheme which is based on diatonic distinctions on melody perception. To achieve this, we run a cognitive experimentation applying Probe-Tone method. The results showed that perceptional hierarchy of pitches changes according to the interval distinction on melody, whether it has more disjunt interval than conjunct intervals, vice versa. Consequently, if the new weighting-scheme created in this study are used in sequenced- based melody comparison, melodies retrieved to user would have a more credible ranking. The details of experimentations and the results we reach are also presented in detail.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Garay, A.: Evaluating text-based similarity measures for musical content. In: Second International Conference on WEB Delivering of Music, p. 2. Darmstadt, Germany (2002)

    Google Scholar 

  2. Grachten, M., Arcos, J.L., M´antaras, R.L.: Melodic Similarity: Looking for a Good Abstraction Level. In: 5th International Conference on Music Information Retrieval (ISMIR), Barcelona, Spain (2004)

    Google Scholar 

  3. Mongeau, M., Sankoff, D.: Comparison of Musical Sequences. Computers and the Humanities 24, 161–175 (1990)

    Article  Google Scholar 

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

    Google Scholar 

  5. Deutsch, D.: The Processing of Pitch Combinations. In: The Psychology of Music. Academic Press, New York (1990)

    Google Scholar 

  6. Lerdahl, F., Jackendoff, R.: A Generative Theory of Tonal Music. MIT Press, Cambridge (1983)

    Google Scholar 

  7. Meyer, L.B.: Emotion and Meaning in Music. University of Chicago Press, Chicago (1956)

    Google Scholar 

  8. Schenker, H.: Neue Musikalische Theorien und Phantasien: Der Freie Satz, Universal Edition, Vienna (1956)

    Google Scholar 

  9. Narmour, E.: The Analysis and Cognition of Basic Melodic Structures. University of Chicago Press, Chicago (1990)

    Google Scholar 

  10. McNab, R.J., Smith, L.A., Bainbridge, D., Witten, I.H.: The New Zealand Digital Library MELody inDEX. D-Lib Magazine 3(5) (1997)

    Google Scholar 

  11. Hoos, H.H., Hamel, K.: GUIDO music notation: Specification Part I, Basic GUIDO. Technical Report TI 20/97, Technische Universität Darmstadt (1997)

    Google Scholar 

  12. Ghias, A., Logan, J., Chamberlin, D., Smith, B.C.: Query by humming: Musical information retrieval in an audio database. In: Proceedings of the ACM International Multimedia Conference & Exhibition, pp. 231–236 (1995)

    Google Scholar 

  13. Uitdenbogerd, A.L., Zobel, J.: Matching techniques for large music databases. In: Proceedings of the 7th ACM International Multimedia Conference, pp. 57–66 (1999)

    Google Scholar 

  14. Droettboom, M., Fujianga, I., MacMillan, K., Patton, M., Warner, J., Choudhury, G.S.: Expressive and efficient retrieval of symbolic music data. In: Proceedings of the 2nd Annual International Symposium on Music Information Retrieval, pp. 173–178 (2001)

    Google Scholar 

  15. Sapp, C.S., Liu, Y.-W., Field, E.S.: Search Effectiveness Measures for Symbolic Music Queries in Very Large Databases. In: International Symposium on Music Information Retrieval, p. 11 (2004); Hoos, H.H., Hamel, K.: GUIDO music notation: Specification Part I, Basic GUIDO. Technical Report TI 20/97, Technische Universität Darmstadt (1997)

    Google Scholar 

  16. Downie, S., Nelson, M.: Evaluation of a simple and effective music information retrieval method. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 73–80 (2000)

    Google Scholar 

  17. Lemstrom, K.: String Matching Techniques for Music Retrieval. Ph.D thesis, University of Helsinki, Department of Computer Science (2000)

    Google Scholar 

  18. Lemstrom, K., Tarhio, J.: Transposition invariant pattern matching for multi-track strings. Nordic Journal of Computing 10, 185–205 (2003)

    MathSciNet  MATH  Google Scholar 

  19. Vurma, A., Ross, J.: Production and Perception of Musical Intervals. Music Perception 23(4), 331–345 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Isikhan, C., Alpkocak, A., Ozer, Y. (2009). Interval Distinction on Melody Perception for Music Information Retrieval. In: Ystad, S., Kronland-Martinet, R., Jensen, K. (eds) Computer Music Modeling and Retrieval. Genesis of Meaning in Sound and Music. CMMR 2008. Lecture Notes in Computer Science, vol 5493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02518-1_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02518-1_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02517-4

  • Online ISBN: 978-3-642-02518-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics