The generalized viterbialgorithm, a direct extension of the viterbialgorithm for hidden Markov models (HMMs), has been used to find the most likely state sequence for hierarchical HMMs. However, the generalized Vite...
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The generalized viterbialgorithm, a direct extension of the viterbialgorithm for hidden Markov models (HMMs), has been used to find the most likely state sequence for hierarchical HMMs. However, the generalized viterbialgorithm finds the most likely whole level state sequence rather than the most likely upper level state sequence. In this paper, we propose a marginalized viterbi algorithm, which finds the most likely upper level state sequence by marginalizing lower level state sequences. We show experimentally that the marginalized viterbi algorithm is more accurate than the generalized viterbialgorithm in terms of upper level state sequence estimation. (C) 2013 Published by Elsevier Ltd.
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