Several inference problems are associated with hidden Markov models, as outlined below.

However, it is also possible to create hidden Markov models with other types of prior distributions.

The algorithm is analogous to that used by hidden Markov models.

In a Markov model, these probabilities are approximated as products.

For simplicity, we describe the algorithm on hidden Markov models.

Jelinek took individual words as the states in his Markov model for speech recognition.

One common use of hidden Markov models is for voice recognition.

Markov models have also been used to analyze web navigation behavior of users.

Speech can be thought of as a Markov model for many stochastic purposes.

This Markov model is used as an approximation of the true underlying language.