Dynamic Bayesian Networks for Symbolic Polyphonic Pitch Modeling

Symbolic pitch modeling is a way of incorporating knowledge about relations between pitches into the process of analyzing musical information or signals. In this paper, we propose a family of probabilistic symbolic polyphonic pitch models, which account for both the "horizontal" and the &q...

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Veröffentlicht in:	IEEE transactions on audio, speech, and language processing Jg. 21; H. 9; S. 1830 - 1840
Hauptverfasser:	Raczyński, Stanisław A., Vincent, Emmanuel, Sagayama, Shigeki
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway, NJ IEEE 01.09.2013 Institute of Electrical and Electronics Engineers
Schlagworte:	Accuracy Acoustics Applied sciences Audio signals Bayes methods Computer Science Context modeling Data models Detection, estimation, filtering, equalization, prediction Dynamic Bayesian Networks Engineering Sciences Estimation Exact sciences and technology Hidden Markov models Horizontal Information theory Information, signal and communications theory Interpolation Mathematical models multipitch analysis Music Pitch estimation Signal and communications theory Signal and Image Processing Signal, noise symbolic pitch modeling Telecommunications and information theory Training Transaction processing Performance evaluation Linear interpolation Dynamic Bayesian Networks Probabilistic approach Acoustic signal Signal estimation Entropy Matrix factorization Modeling Information analysis Accuracy Non negative matrix Audio signal Linear combination symbolic pitch modeling multipitch analysis Bayes network Musical sound Pitch(acoustics)
ISSN:	1558-7916, 1558-7924
Online-Zugang:	Volltext
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