Part of Advances in Neural Information Processing Systems 17 (NIPS 2004)
Dustin Lang, Nando Freitas
We present a graphical model for beat tracking in recorded music. Using a probabilistic graphical model allows us to incorporate local information and global smoothness constraints in a principled manner. We evaluate our model on a set of varied and difficult examples, and achieve impres- sive results. By using a fast dual-tree algorithm for graphical model in- ference, our system runs in less time than the duration of the music being processed.