Globally Optimal Short-Time Dynamic Time Warping, Application to Score to Audio Alignment

Dynamic time warping (DTW) finds the best global match or alignment between two sequences by ´time´ warping them optimally. Since the algorithm uses the whole sequences, it can be very demanding in calculation cost and memory. In particular, this limits the size of the sequences which can be aligned. In this paper a novel algorithm is presented, short-time dynamic time warping (STDTW), which requires much less memory because optimization is done iteratively on portions of the sequences. The very remarkable property of the algorithm is that under some weak hypothesis, it produces the same globally optimal solution as the classical DTW. As an example, STDTW is applied to score to audio alignment which links events in a musical score and points on the audio performance time axis