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The Viterbi algorithm works by calculating the probability of observing state sequences,
and then reports back with the most probable sequence that has occurred.
One of the side-effects of the Viterbi algorithm is this calculation of these
probabilities, and these can be used to evaluate the likelihood that a sequence
occurred1. By using the data from which that the models were learnt, the general
trends of how the probability behaves throughout the course of the action can
be recorded. A deviation from these general trends is indicative of failure.
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