Improved score-performance alignment algorithms on polyphonic music

Automated symbolic music alignment is a challenging task due to the variation of performance by different performers. It becomes more complicated when dealing with polyphonic music because note events could occur at the same time. The goal of this study is to find an efficient algorithm for aligning two polyphonic symbolic representations (MIDI files, for instance) of the same music. To this end, we design two methods for such score-performance alignment that matches the performance with its corresponding score. The first method applies a string matching algorithm based on dynamic programming. The second method is based on the principle of "divide and conquer" that performs efficient alignment recursively. To evaluate the algorithms, we have collected a set of 21 MIDI pairs of classic piano performance with human corrected note-level mapping as ground truth. We have released the dataset as a public resource. Both the proposed algorithms achieved a precision and recall higher than 96% in our experiment, outperforming the most recently proposed method [7] in the literature. Besides, the execution time of proposed methods is much faster the method of [7].