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This tutorial gives a gentle introduction to Markov models and Hidden Markov models as mathematical abstractions, and relates them to their use in automatic speech recognition. This material was developed for the Fall 1995 semester of CS188: Introduction to Artificial Intelligence at the University of California, Berkeley. It is targeted for introductory AI courses basic knowledge of probability theory (eg Bayes' Rule) is assumed. This version is slightly updated from the original, including a few minor error corrections, a short\Further Reading" section, and exercises that were given as a homework in the Fall 1995 class.