Hierarchical hidden Markov model
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The hierarchical hidden Markov model (HHMM) is a statistical model derived from the hidden Markov model (HMM). In an HHMM, each state is considered to be a self-contained probabilistic model. More precisely, each state of the HHMM is itself an HHMM.
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HHMMs and HMMs are useful in many fields, including pattern recognition.[1][2]