TY  - CONF
T1  - Tracking Rests and Tempo Changes: Improved Score Following with Particle Filters
T2  - Proceedings of the International Computer Music Conference (ICMC)
Y1  - 2013
A1  - Korzeniowski, Filip
A1  - Krebs, Florian
A1  - Andreas Arzt
A1  - Widmer, Gerhard
AB  - <p>In this paper we present a score following system based on a Dynamic Bayesian Network, using particle filtering as inference method. The proposed model sets itself apart from existing approaches by including two new extensions: A multi-level tempo model to improve alignment quality of performances with challenging tempo changes, and an extension to reflect different expressive characteristics of notated rests. Both extensions are evaluated against a dataset of classical piano music. As the results show, the extensions improve both the accuracy and the robustness of the algorithm.</p>
JF  - Proceedings of the International Computer Music Conference (ICMC)
CY  - Perth, Australia
ER  -