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Dynamic Time Warping (DTW) for Single Word and Sentence ...

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<strong>DTW</strong> <strong>for</strong> <strong>Single</strong> <strong>Word</strong> <strong>and</strong> <strong>Sentence</strong> Recognizers<br />

Classifier Design in Practice<br />

• Need a priori probability P ( ) i (not too bad)<br />

• Need class conditional PDF p<br />

• Problems:<br />

– limited training data<br />

– limited computation<br />

– class-labeling potentially costly <strong>and</strong> prone to error<br />

– classes may not be known<br />

– good features not known<br />

• Parametric Solution:<br />

– Assume that p (x / )<br />

has a particular parametric <strong>for</strong>m<br />

i<br />

– Most common representative: multivariate normal density<br />

12<br />

(x / i )

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