Source Separation and Beat Tracking: A System Approach to the Development of a Robust Audio-to-Score System

  • Mario Malcangi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3310)

Abstract

A set of tools for pitch, metric and rhythm information matching on musical audio streams are under development. The goal is a robust automatic system capable to track musical audio data for information retrieval and access purpose. Several problems have been identified and approached to be solved separately, such as metric computation, rhythm recognition and pitch tracking. This approach has been chosen to synthesize a whole processing model robust enough to be applied virtually to any kind of music. A source separation modeling has been investigated starting from ICA model. An ICA modified unmixing model has been proposed as preprocessing subsystem. This subsystem demonstrated to be very helpful for efficient applying of processing algorithms to rhythm and pitch tracking.

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References

  1. 1.
    Malcangi, M.: A mixed methodology speech-to-text recognition system. In: Proceedings of the twelfth Turkish symposium on Artificial Intelligence and Neural Networks (TAINN 2003), Canakkale, Turkey, July 02-04 (2003)Google Scholar
  2. 2.
    Moorer, J.A.: On the segmentation and analysis of continuous musical sound by digital computer, PhD thesis, Dept. of Computer Science, Standford University (May 1975) (report number STAN-M-3)Google Scholar
  3. 3.
    Bregman, A.S.: Auditory Scene Analysis. MIT Press, Cambridge (1994)Google Scholar
  4. 4.
    Brown, G., Cooke, M.: Computational Auditory Scene Analysis. Computer, Speech and Language 8 (1994)Google Scholar
  5. 5.
    García, L., Casajús-Quirós, J.: Separation of musical instruments based on perceptual and statistical priciples. In: 2nd COST-G6 Workshop on Digital Audio Effects (DAFx 1999), Trondheim, Norway (December 1999)Google Scholar
  6. 6.
    Lee, T.-W., Bell, A.J., Orglmeister, R.: Blind source separation of real world signals. In: Proceedings of IEEE International Conference Neural Networks, Houston, pp. 2129–2135 (June 1997)Google Scholar
  7. 7.
    Hyvärinen, A.: Fast and Robust fixed point algorithm for independent component analysis. IEEE Trans. on Neural Networks 10(3), 626–634 (1999)CrossRefGoogle Scholar
  8. 8.
    Roweis, S.T.: Factorial models and refiltering for speech separation and denoising. In: Proceedings of Eurospeech 2003, Geneva, pp. 1009–1012 (2003)Google Scholar
  9. 9.
    Cauwenberghs, G.: Monaural separation of independent acoustical components. In: IEEE Symposium Circuit & Systems (ISCAS 1999) (1999)Google Scholar
  10. 10.
    Scheirer, E.: Tempo and Beat analysis of acoustic musical signals. J. Acoust. Soc. Am. 103(1), 588–601 (1998)CrossRefGoogle Scholar
  11. 11.
    Sepännen, J.: Computational models of musical meter recognition. Master’s thesis, Tampere Univ. of Tech., Tampere, Finland (2001)Google Scholar
  12. 12.
    Malcangi, M., Nivuori, A.: Beat and rhythm tracking of audio musical signal for dance synchronization of a virtual puppet. In: Proceedings of the XIV Colloquium on Musical Informatics (XIV CIM 2003), Firenze, May 8-10 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Mario Malcangi
    • 1
  1. 1.LIM – Laboratorio di Informatica Musicale, DICo – Dipartimento di Informatica e ComunicazioneUniversità degli Studi di MilanoMilanoItaly

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