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Graph-Based Rhythm Interpretation

We present a system that interprets the notated rhythm obtained from optical music recognition (OMR). Our approach represents the notes and rests in a system measure as the vertices of a graph. We connect the graph by adding voice edges and coincidence edges between pairs of vertices, while the rhythmic interpretation follows simply from the connected graph. The graph identification problem is cast as an optimization where each potential edge is scored according to its plausibility. We seek the optimally scoring graph where the score is represented as a sum of edge scores. Experiments were performed on about 60 score pages showing that our system can handle difficult rhythmic situations including multiple voices, voices that merge and split, voices spanning two staves, and missing tuplets.