top of page
  • Writer's pictureCihan Işıkhan

Interval Distinction on Melody Perception for Music Information Retrieval

Updated: Jan 17, 2021

Book Chapter/Kitapiçi Bölüm, 2009



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.



https://blog.flat.io/


"We have an experiment, applying PT method, containing a melody which will be singing by user as a condition instead of western music theory and we try to be contented with having pitch hierarchy on perception to be a realistic dimension by horizontal relation of pitches on melody line."

REFERENCES

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

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

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

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

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

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

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

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

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

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

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

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

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

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

15. Sapp, Craig Stuart, Yi-Wen Liu, and Eleanor Selfridge- Field: Search Effectiveness Measures for Symbolic Music Queries in Very Large Databases, International Symposium on Music Information Retrieval, (2004)

16. S. Downie and M. Nelson: 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, pages 73–80, (2000)

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

18. K. Lemstrom and J. Tarhio. Transposition invariant pattern matching for multi-track strings. Nordic Journal of Computing, 10.185–205, (2003)

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


6 views0 comments

Comments


bottom of page