February 2018
Intermediate to advanced
378 pages
10h 14m
English
Content preview from Machine Learning with Swift
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DTW
Despite its Sci-Fi name, DTW has little to do with time travel, except for the fact that this technique was popular for speech recognition back in the 1980s. Imagine two signals as two springs oriented along the time axis. We place them next to each other on the table, and want to measure how similar (or how different... what's the same?) they are. One of them will serve as a template. And we start stretching and compressing another one, piece by piece, until it looks exactly as the first one (or the most similar). Then we account for how much effort we put into align two springs—we sum up all tensions and stretches together, and get the DTW distance.
DTW distance between two sound signals tells us how similar to each other they are. ...
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