Applications
One of the major applications of the HMM is in the field of speech recognition. In this section, we will briefly describe the process of speech recognition.
In speech recognition, our job is to compute the most probable word corresponding to a speech signal or acoustic observation. Our aim is to compute the following:
Here, O corresponds to the acoustic observation and W is the set of all possible words. The likelihood 
is determined by an acoustic model, and the prior P(W) is determined by a language model.
Fig 7.14 shows the architecture of an HMM-based speech recognition system. There are three major components:
Acoustic model
Language model
Pronunciation dictionary
Fig 7.14: Architecture of an HMM-based speech recognition system
The acoustic model
The basic units of sound represented by the acoustic model are the phonetics. For example, the word "bat" is composed of three phonetics, /b/ /ae/ /t/. About 40 such phonetics are required for English. Each spoken letter W can be decomposed...
