FMF(Fast Melody Finder): A Web-Based Music Retrieval System

  • Seung-Min Rho
  • Een-Jun Hwang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2771)

Abstract

As the use of digital music is getting popular, there is an increasing demand for efficient retrieval of music. To do that, an effective music indexing and natural way of querying a music should be incorporated. This paper describes the FMF system that designed to retrieve tunes from a database on the basis of a few notes which are drawn into a musical sheet applet or sung into a microphone. FMF system accepts both acoustic and visual input from the user, transcribes all the acoustic and common music notational inputs into specific strings such as UDR and LSR. Then, It searches an index for tunes that contain the sung pattern, or patterns similar to it. We implemented a web-based retrieval system and report on its performance through various experiments.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison Wesley, Reading (1999)Google Scholar
  2. 2.
    Blackburn, S., DeRoure, D., et al.: A Tool for Content Based Navigation of Music. In: Proceedings of ACM multimedia 1998 - Electronic Proceedings, pp. 361–368 (1998)Google Scholar
  3. 3.
    Foote, J.T.: Content-Based Retrieval of Music and Audio. In: Multimedia Storage and Archiving Systems II - Proceedings of SPIE, pp. 138–147 (1997)Google Scholar
  4. 4.
    Foote, J.T.: An Overview of Audio Information Retrieval. ACM-Springer Multimedia Systems, 2–10 (1998)Google Scholar
  5. 5.
    Ghias, A., et al.: Query by humming - musical information retrieval in an audio database. In: Proceedings of ACM Multimedia 1995 - Electronic Proceedings, pp. 231–236 (1995)Google Scholar
  6. 6.
    Lu, G.: Indexing and Retrieval of Audio: A Survey. Journal of Multimedia Tools and Applications, 269–290 (2001)Google Scholar
  7. 7.
    Hawley, M.J. : Structure out of Sound PhD thesis, MIT (1993) Google Scholar
  8. 8.
    Hwang, E., Park, D.: Popularity-Adaptive Index Scheme for Fast Music Retrieval. In: Proceedings of IEEE Multimedia and Expo. (2002)Google Scholar
  9. 9.
    Hwang, E., Rho, S.: Fast Melody Finding Based on Memorable Tunes. In: 1st International Symposium on Computer Music Modeling and Retrieval, Montpellier, France, pp. 227–239 (2003)Google Scholar
  10. 10.
    Huron, D., Sapp, C.S., et al.: Themefinder (2000), http://www.themefinder.org
  11. 11.
    jMusic, Java library, http://jmusic.ci.qut.edu.au/
  12. 12.
    Kornstadt, A.: Themefinder: A Web-Based Melodic Search Tool. Computing in Musicology, vol. 11. MIT Press, Cambridge (1998)Google Scholar
  13. 13.
    Kosugi, N., et al.: A Practical Query-By-Humming System for a Large Music Database. In: Proceedings of the 8th ACM International Conference, pp. 333–342 (2000)Google Scholar
  14. 14.
    Lemstorm, K., et al.: Retrieving Music - To Index or not to Index. In: ACM International Multimedia Conference, pp. 64–65 (1998)Google Scholar
  15. 15.
    Lemstorm, K., et al.: SEMEX - An efficient Music Retrieval Prototype. In: Proceeding of Symposium on Music Information RetrievalGoogle Scholar
  16. 16.
    McNab, R.J., et al.: Toward the digital music library: tune retrieval from acoustic input. In: Proceedings of the first ACM Conference on Digital Libraries, pp. 11–18 (1996)Google Scholar
  17. 17.
    McNab, R.J., et al.: The New Zealand digital library MELody index. Digital Libraries Magazine, 11–18 (1997)Google Scholar
  18. 18.
    Melucci, M., et al.: Musical Information Retrieval using Melodic Surface. In: Proceedings of the ACM Digital Libraries Conference, pp. 152–160 (1999)Google Scholar
  19. 19.
    Michael, G.: Representing Music Using XML. International Symposium on Music Information Retrieval Google Scholar
  20. 20.
    MiDiLiB project: Content-based indexing, retrieval, and compression of data in digital music libraries, http://www-mmdb.iai.uni-bonn.de/forschungprojekte/midilib/english/
  21. 21.
    Rolland, P.Y., et al.: Musical Content-Based Retrieval: an Overview of the Melodiscov Approach and System. In: Proceedings of ACM multimedia 1998 – Electronic Proceedings, pp. 81–84 (1998)Google Scholar
  22. 22.
    Rolland, P.Y., et al.: usic Information Retrieval: a brief Overview of Current and Forthcoming Research. In: Proceeding of Human Supervision and Control in Engineering and MusicGoogle Scholar
  23. 23.
    Salosaari, P., et al.: MUSIR-A Retrieval Model for Music. Technical Report RN-1998-1, University of Tampere (1998) Google Scholar
  24. 24.
    Subramanya, S.R., et al. : Transforms - Based Indexing of Audio Data for Multimedia Databases. In: IEEE International Conference on Multimedia Systems (1997) Google Scholar
  25. 25.
    Subramanya, S.R., et al. : Use of Transforms for Indexing in Audio Databases. International Conference on Computational Intelligence and Multimedia Applications (1999) Google Scholar
  26. 26.
    Tseng, Y.H. : Content-Based Retrieval for Music Collections. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 176–182 (1999) Google Scholar
  27. 27.
    Typke, R., Prechelt, L.: An Interface for melody input. ACM Transactions on Computer-Human Interaction, 133–149 (2001)Google Scholar
  28. 28.
    Uitdenbogerd, A., Zobel, J.: Manipulation of music for melody matching. In: Proceedings of ACM Multimedia Conference, pp. 235–240 (1998)Google Scholar
  29. 29.
    Uitdenbogerd, A., Zobel, J.: Melodic matching techniques for large music databases. In: Proceedings of ACM Multimedia Conference, pp. 57–66 (1999)Google Scholar
  30. 30.
    Wold, E., et al.: Content-based Classification, Search and Retrieval of Audio. IEEE Multimedia 3(3), 27–36Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Seung-Min Rho
    • 1
  • Een-Jun Hwang
    • 1
  1. 1.The Graduate School of Information and CommunicationAjou UniversitySuwonKorea

Personalised recommendations