0363591 20240103195449.920110913235959.9 4 s. www cav_un_epca*03729162076-14651-4BarcelonaEURASIP2011 music transcription Variational Bayes blind source separation cav_un_auth*0254098 Albrecht Š. CZ cav_un_auth*0101207 Šmídl Václav Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2011/AS/smidl-model%20for%20memory-based%20music%20transcription%20and%20its%20variational%20bayes%20solution.pdf CEZ:AV0Z10750506 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. cav_un_auth*0274046 19th European Signal Processing Conference Barcelona 29.08.2011-02.09.2011 ES 2012 BD http://hdl.handle.net/11104/0199350 2011 cav_un_epca*0372916 EUSIPCO 2011: 19th European Signal Processing Conference 2076-1465 1 4 Barcelona EURASIP 2011