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Hi in this lesson we are going to look at hidden Markov models or hmms first let's look at some speech recognition basics speech recognition can be accomplished using the popular template based pattern recognition approach one key idea here is to derive typical speech sequences as patterns example word patterns and calculate local spectral distances to compare the patterns even though statistical techniques are widely used in clustering to create reference patterns in image based techniques it is often inadequate for switch classification and recognition consider for example the use of LPC linear predictive coding of speech segments as a distortion measure for the local distance of the template matching the Euclidean distance form of the LPC coefficients suggest that the reference vector can be lived as the mean of some assumed distribution this simple form of sufficient statistics neglects the time dependency of speech signals which is often very useful in recognition speech utterance

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