Towards an Intelligent Score Following System: Handling of Mistakes and Jumps Encountered During Piano Practicing

  • Mevlut Evren Tekin
  • Christina Anagnostopoulou
  • Yo Tomita
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3310)

Abstract

Score following has been an important area of research in AI and music since the mid 80’s. Various systems were developed, but they were predominantly for providing automated accompaniment to live concert performances, dealing mostly with issues relating to pitch detection and identification of embellished melodies. They have a big potential in the area of education where student performers benefit in practice situations. Current accompaniment systems are not designed to deal with errors that may occur during practising. In this paper we present a system developed to provide accompaniment for students practising at home. First a survey of score following will be given. Then the capabilities of the system will be explained, and the results from the first experiments of the monophonic score following system will be presented.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bloch, J.J., Dannenberg, R.: Real-Time Computer Accompaniment of Keyboard Performances. In: Proceedings of the 1985 International Computer Music Conference, International Computer Music Association, pp. 279–289 (1985)Google Scholar
  2. 2.
    Bora, U., Tufan, S., Bilgen, S.: A tool for comparison of piano performances. Journal of New Music Research 29(1), 85–99 (2000)CrossRefGoogle Scholar
  3. 3.
    Cano, P., Loscos, A., Bonada, J.: Score-Performance Matching Using HMMs. In: Proceedings of the 1999 International Computer Music Conference, International Computer Music Association, pp. 441–444 (1999)Google Scholar
  4. 4.
    Dannenberg, R.: An Online Algorithm for Real-Time Accompaniment. In: Proceedings of the 1984 International Computer Music Conference, International Computer Music Association, pp. 193–198 (1984)Google Scholar
  5. 5.
    Dannenberg, R., Mukaino, H.: New techniques for Enhanced Quality of Computer Accompaniment. In: Proceedings of the 1988 International Computer Music Conference, International Computer Music Association, pp. 243–249 (1988)Google Scholar
  6. 6.
    Dannenberg, R.: Recent Work in Real-Time Music Understanding by Computer. In: Sundberg, Nord, Carlson (eds.) Music, Language, Speech and Brain, Wenner-Gren International Symposium Series, pp. 194–202. Macmillan, Basingstoke (1991)Google Scholar
  7. 7.
    Dannenberg, R., et al.: Results from the Piano Tutor Project. In: Proceedings of the Fourth Biennial Arts and Technology Symposium, March 1993, pp. 143–150 (1993)Google Scholar
  8. 8.
    Loy, G., Abbott, C.: Programming Languages for Computer Music Synthesis, Performance, and Composition. Computing Surveys 17(2) (June 1985)Google Scholar
  9. 9.
    Orio, N., Lemouton, S., Schwarz, D.: Score Following: State of the Art and New Developments. In: Proceedings of the Conference of New Interfaces for Musical Expression, NIME, Montreal, pp. 36–41 (2003)Google Scholar
  10. 10.
    Puckette, M., Lippe, C.: Score Following in Practice. In: Proceedings of the 1992 International Computer Music Conference, International Computer Music Association, pp. 182–185 (1992)Google Scholar
  11. 11.
    Puckette, M.: Score Following Using the Sung Voice. In: Proceedings of the 1995 International Computer Music Conference, International Computer Music Association, pp. 175–178 (1995)Google Scholar
  12. 12.
    Raphael, C.: Automatic Segmentation of Acoustic Musical Signals Using Hidden Markov Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(4), 360–370 (1999)CrossRefMathSciNetGoogle Scholar
  13. 13.
    Raphael, C.: A Probabilistic Expert system for Automatic Musical Accompaniment. Journal of Computer and Graphic Stats 10(3), 487–512 (2001)CrossRefMathSciNetGoogle Scholar
  14. 14.
    Roads, C.: Research in Music and Artificial Intelligence. Computing Surveys 17(2) (June 1985)Google Scholar
  15. 15.
    Vercoe, B.: The Synthetic Performer in the Context of Live Performance. In: Proceedings of the 1984 International Computed Music Conference, International Computer Music Association, pp. 199–200 (1984)Google Scholar
  16. 16.
    AMuseTec website: http://www.musebook.com

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Mevlut Evren Tekin
    • 1
  • Christina Anagnostopoulou
    • 1
  • Yo Tomita
    • 1
  1. 1.Sonic Arts Research CentreQueen’s University of BelfastBelfastUnited Kingdom

Personalised recommendations