The Viterbi algorithm is a dynamic programming algorithm for finding the most likely sequence of hidden states – called the Viterbi path – that results in a sequence of observed events, especially in the context of Markov information sources and hidden Markov models . The terms Viterbi path and Viterbi algorithm are also applied to related dynamic programming algorithms that discover the single most likely explanation for an observation. For example, in statistical parsing a dynamic programming algorithm can be used to discover the single most likely context-free derivation (parse) of a string, which is sometimes called the Viterbi parse .
"The Viterbi algorithm is a dynamic programming algorithm for finding the most likely sequence of hidden states", like hidden markov. by Jun 7
A hidden Markov model ( HMM ) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved ( hidden ) states. An HMM can be considered as the simplest dynamic Bayesian network . The mathematics behind the HMM was developed by L. E.
In markov model, state is visible. In Hidden markov model, only result is visible. By looking at the sequence of results, the change in state and therefore hidden model can be inferred.
From the link: "Each state has a probability distribution over the possible output tokens. Therefore the sequence of tokens generated by an HMM gives some information about the sequence of states." by Jun 7