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A Comparative Study on Polyphonic Musical Time Series Using MCMC Methods

  • Katrin Sommer
  • Claus Weihs
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

A general harmonic model for pitch tracking of polyphonic musical time series will be introduced. Based on a model of Davy and Godsill (2002) the fundamental frequencies of polyphonic sound are estimated simultaneously. For an improvement of these results a preprocessing step was be implemented to build an extended polyphonic model.

All methods are applied on real audio data from the McGill University Master Samples (Opolko and Wapnick (1987)).

Keywords

Fundamental Frequency Audio Signal MCMC Method MCMC Algorithm Correct Note 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. DAVY, M. and GODSILL, S. J. (2002): Bayesian Harmonic Models for Musical Pitch Estima-tion and Analysis. Technical Report 431, Cambridge University Engineering Department. GILKS, W. R., RICHARDSON, S. and SPIEGELHALTER D. J. (1996): Markov Chain Monte Carlo in Practice, Chapman & Hall.Google Scholar
  2. OPOLKO, F. and WAPNICK, J. (1987): McGill University Master Samples [Compact disc]: Montreal, Quebec: McGill University.Google Scholar
  3. SOMMER K. and WEIHS C. (2006): Using MCMC as a stochastic optimization procedure for music time series. In: V. Batagelj, H.H. Bock, A. Ferligoj, and A. Ziberna (Eds.): Data Science and Classifiction , Springer, Heidelberg, 307-314.CrossRefGoogle Scholar
  4. SOMMER K. and WEIHS C. (2007): Using MCMC as a stochastic optimization procedure for monophonic and polyphonic sound. In: R. Decker and H. Lenz (Eds.): Advances in Data Analysis, Springer, Heidelberg, 645-652.CrossRefGoogle Scholar
  5. WEIHS, C. and LIGGES, U. (2006): Parameter Optimization in Automatic Transcription of Music. In: Spiliopoulou, M., Kruse, R., Nürnberger, A., Borgelt, C. and Gaul, W. (eds.): From Data and Information Analysis to Knowledge Engineering. Springer, Berlin, 740 -747.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Katrin Sommer
    • 1
  • Claus Weihs
    • 1
  1. 1.Lehrstuhl für Computergestützte StatistikUniversität DortmundDortmundGermany

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