Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/22629 
Year of Publication: 
2005
Series/Report no.: 
Technical Report No. 2005,39
Publisher: 
Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, Dortmund
Abstract: 
Based on former work on automatic transcription of musical time series into sheet music (Ligges et al. (2002), Weihs and Ligges (2003, 2005)) in this paper parameters of the transcription algorithm are optimized for various real singers. Moreover, the parameters of various artificial singer models derived from the models of Rossignol et al. (1999) and Davy and Godsill (2002) are estimated. In both cases, optimization is carried out by the Nelder-Mead (1965) search algorithm. In the modelling case a hierarchical Bayes extension is estimated by WinBUGS (Spiegelhalter et al. (2004)) as well. In all cases, optimal parameters are compared to heuristic estimates from our former standard method.
Document Type: 
Working Paper

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