Abstract
Based on a model of Davy and Godsill (2002) we describe a general model for time series from monophonic musical sound to estimate the pitch. The model is a hierarchical Bayes Model which will be estimated with MCMC methods. All the parameters and their prior distributions are motivated individually. For parameter estimation an MCMC based stochastic optimization is introduced. In a simulation study it will be looked for the best implementation of the optimization procedure.
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References
DAVY, M. and GODSILL, S.J. (2002): Bayesian Harmonic Models for Musical Pitch Estimation and Analysis. Technical Report 431, Cambridge University Engineering Department.
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Sommer, K., Weihs, C. (2006). Using MCMC as a Stochastic Optimization Procedure for Musical Time Series. In: Batagelj, V., Bock, HH., Ferligoj, A., Žiberna, A. (eds) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-34416-0_33
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DOI: https://doi.org/10.1007/3-540-34416-0_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34415-5
Online ISBN: 978-3-540-34416-2
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