Generative model based polyphonic music transcription
Ali Taylan Cemgil, Bert Kappen, David Barber · 2004
We present a model for simultaneous tempo and polyphonic pitch tracking. Our model, a form of dynamic Bayesian network (Murphy, K.P., 2002), embodies a transparent and computationally tractable approach to this acoustic analysis problem. An advantage of our approach is that it places emphasis on modeling the sound generation procedure. It provides a clear framework in which both high level (cognitive) prior information on music structure can be coupled with low level (acoustic physical) information in a principled manner to perform the analysis. The model is readily extensible to more complex sound generation processes.