A Content Dependent Visualization System for Symbolic Representation of Piano Stream

  • Alexander Adli
  • Zensho Nakao
  • Yasunori Nagata
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4693)


This paper provides an overview on the advances of music information retrieval in symbolic representation of music. Such musical aspects as key, tonality, bass, melody, dynamics, rhythm and patterns are considered as foundation for visualizing systems for the piano stream in classical music. The paper then describes the proposed visualizing system and Malinowski’s music animation machine. It lays light on the challenges facing creating contemporary visualizing systems. It is supplied with a related references list for further study on the issue.


Music content analysis Visualization MIDI piano stream MIR 


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  1. 1.
    Isaacson, E.: What You See Is What You Get: On Visualizing Music. In: Proceedings of International Symposium in Music Information Retrieval, London (2005)Google Scholar
  2. 2.
    Ozcan, G., Isikhan, C., Alpkocak, A.: Melody Extraction on MIDI music Files. In: Proceedings of the seventh IEEE International Symposium on Multimedia (2005)Google Scholar
  3. 3.
    Li, T., Ogihara, M.: Detecting Emotions in Music. In: Proceedings of International Symposium in Music Information Retrieval (2003)Google Scholar
  4. 4.
    Malinowski, S.: Music Animation Machine (2005),
  5. 5.
  6. 6.
    Adli, A., Nakao, Z., Nagata, Y.: Calculating the expected sound intensity level for solo piano sound in MIDI files. In: Proceedings of the SCIS & ISIS, Tokyo Institute of Technology, Tokyo (September 2006)Google Scholar
  7. 7.
    Langner, J., Goebl, W.: Visualizing Expressive Performance in Tempo-Loudness Space. Computer Music Journal 27(4), 69–83 (2003)CrossRefGoogle Scholar
  8. 8.
    Adli, A., Nakao, Z., Yokoda, T., Nagata, Y.: Piano Sound Characteristics: A Study On Some Factors Affecting Loudnes. In: Digital And Acoustic Pianos, ICICIC, Japan (2007) (in print)Google Scholar
  9. 9.
    Adli, A., Nakao, Z., Nagata, Y.: A Score Based Algorithm for Tonality Recognition in Monophonic Piano Streams (submitted)Google Scholar
  10. 10.
    MIDI Manufacturers Association:
  11. 11.
    Martin, K.D., Scheirer, E.D., Vercoe, B.L.: Music Content Analysis Through Models of Audition. In: Proceedings of the ACM Multimedia Workshop on Content Processing of Music for Multimedia Applications, Bristol, UK, ACM Press, New York (1998)Google Scholar
  12. 12.
    Rizo, D., de Le’on, P.P., P’erez-Sancho, C., Pertusa, A., Inesta, J.M.: A Pattern Recognition Approach for Melody Track Selection in MIDI Files. In: Proceedings of International Symposium in Music Information Retrieval (2006)Google Scholar
  13. 13.
    Levitin, D.J.: This is your brain on Music, Dutton (2006)Google Scholar
  14. 14.
    Uitdenbogerd, A., Zobel, J.: Manipulation of Music for Melody Matching. In: Proceedings of ACM Internaional Multimedia Conference, ACM Press, New York (1998)Google Scholar
  15. 15.
    Chai, W.: Melody Retrieval on the web, MS Thesis, Massachusetts Institute of Technology, Boston (2000)Google Scholar
  16. 16.
    Fastl, H., Zwicker, E.: Psychoacoustics: Facts and Models, Springer, 3rd edn. Springer, Heidelberg (2006)Google Scholar
  17. 17.
    Parncutt, R.: Revision of Terhardt ‘s psychoacoustical model for the roots of a musical chord. Music perception 6, 65–94 (1988)CrossRefGoogle Scholar
  18. 18.
    Rowe, R.: Machine Musicianship. The Mit Press, Cambridge (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Alexander Adli
    • 1
  • Zensho Nakao
    • 2
  • Yasunori Nagata
    • 2
  1. 1.Graduate School of Engineering & Science, University of the Ryukyus, Okinawa, 903-0213Japan
  2. 2.Department of Electrical & Electronics Engineering, University of the Ryukyus, Okinawa 903-0213Japan

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