The course begins with an overview of the speech recognition problem, and a review of some common speech analysis models. The dynamic time warping algorithm and the hidden Markov model are then introduced in turn, with the basic principles behind these methods discussed both through theory and practice. Programming examples are provided at the end of each section to help reconcile theory with actual application.

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