Title :
Model for memory-based music transcription and its Variational Bayes solution
Author :
Albrecht, Stepan ; Smidl, Vaclav
Author_Institution :
Univ. of West Bohemia, Plzeñ, Czech Republic
fDate :
Aug. 29 2011-Sept. 2 2011
Abstract :
The problem of memory based music transcription is considered and a probabilistic model for polyphonic music is proposed. Parameters of the model correspond to labels of the pre-recorded sounds and their amplitudes. Since exact estimation of the parameters is computationally prohibitive, we develop an approximate estimation algorithm using the Variational Bayes approximation. Results of the proposed algorithm are compared to alternative algorithms on piano recordings.
Keywords :
Bayes methods; approximation theory; audio recording; audio signal processing; music; variational techniques; approximate estimation algorithm; memory-based music transcription; piano recordings; polyphonic music; prerecorded sounds amplitudes; probabilistic model; variational Bayes approximation; variational Bayes solution; Computational modeling; Estimation; Libraries; Mathematical model; Multiple signal classification; Music; Signal processing algorithms;
Conference_Titel :
Signal Processing Conference, 2011 19th European
Conference_Location :
Barcelona