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In order to study aspects of music performance, one has to find correspondences between the performance data and a score. Locating the corresponding score note for every performance note, called matching, is therefore a common task. An algorithm that automates this procedure is called a matcher. Automated matching is difficult because performers make errors, performers use expressive timing, and scores are frequently underspecified. To find the best match, most matchers use information about pitch, temporal order, and the number of matched notes. We show that adding information about the musical structure of the score gives better results. However, we found that even this information was insufficient to identify some types of performance errors and that a definition of best match based only on the number of matched notes is sometimes problematic. We provide some suggestions about how to achieve greater improvements.

Data processing in music performance research: Using structural information to improve score-performance matching