Patterns generated by a hidden process
Section 1 - Page 1
1
2
When a Markov process may not be powerful enough
In some cases the patterns that we wish to find are not
described sufficiently by a Markov process. Returning to the
weather example, a hermit may perhaps not have access to direct
weather observations, but does have a piece of seaweed. Folklore
tells us that the state of the seaweed is probabalistically
related to the state of the weather - the weather and seaweed
states are closely linked. In this case we have two sets of
states, the observable states (the state of the seaweed) and the
hidden states (the state of the weather). We wish to devise an
algorithm for the hermit to forecast weather from the seaweed
and the Markov assumption without actually ever seeing the
weather.
A more realistic problem is that of recognising speech; the
sound that we hear is the product of the vocal chords, size of
throat, position of tongue and several other things. Each of
these factors interact to produce the sound of a word, and the
sounds that a speech recognition system detects are the changing
sound generated from the internal physical changes in the person
speaking.
|
