Abstract

In this tutorial we present an overview of (i) what are HMMs, (ii) what are the different problems associated with HMMs, (iii) the Viterbi algorithm for determining the optimal state sequence, (iv) algorithms associated with training HMMs, and (v) distance between HMMs. 1 Introduction [1] Suppose a person has say three coins and is sitting inside a room tossing them in some sequence-- this room is closed and what you are shown (on a display outside the room) is only the outcomes of his tossing TTHTHHTT. . . this will be called the observation sequence . You do not know the sequence in which he is tossing the different coins, nor do you know the bias of the various coins. To appreciate how much the outcome depends on the individual biasing and the order of tossing the coins, suppose you are given that the third coin is highly biased to produce heads and all coins are tossed with equal probability. Then, we naturally expect there to be far greater number of heads than tails in the o...