This tutorial gives a gentle introduction to Markov models and hiddenMarkov models (HMMs) and relates them to their use in automatic speech recognition.

This introduction to the expectation–maximization (EM) algorithm provides an intuitive and mathematically rigorous understanding of EM. Two of the most popular applications of EM are described in detail: estimating Gaussian mixture models (GMMs),