Recently, I’ve been working on a new handwriting recognition engine for Tegaki based on Dynamic Time Warping and I figured it would be interesting to make a short, informal introduction to it.
Dynamic Time Warping (DTW) is a well-known algorithm which aims at comparing and aligning two sequences of data points (a.k.a time series). Although it was originally developed for speech recognition (see [1]), it has also been applied to many other fields like bioinformatics, econometrics and, of course, handwriting recognition.
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