Hidden Markov model

Summary

A hidden Markov model is a pair of processes: a Markov chain of hidden states and a sequence of observations. Each observation depends only on the hidden state at the same time. Only the observations are seen, and the task is to infer the hidden states or the parameters of the model. Hidden Markov models are used in speech recognition, bioinformatics and signal processing, with efficient algorithms such as the forward algorithm and the Viterbi algorithm.