Measuring the Performance of Beat Tracking Algorithms Using a Beat Error Histogram

We present a new evaluation method for measuring the performance of musical audio beat tracking systems. Central to our method is a novel visualization, the beat error histogram, which illustrates the metrical relationship between two qausi-periodic sequences of time instants: the output of beat tracking system and a set of ground truth annotations. To quantify beat tracking performance we derive an information theoretic statistic from the histogram. Results indicate that our method is able to measure performance with greater precision than existing evaluation methods and implicitly cater for metrical ambiguity in tapping sequences.