In HMM’s, what are the possible values of the variable?

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‘Possible States of the World’ is the possible values of the variable in HMM’s.

In Hidden Markov Models (HMMs), there are typically three main types of variables:

  1. Observation Variables (O): These are the observable variables or emissions associated with each state in the model. They represent the data that can be directly observed. For example, in speech recognition, observation variables could be the acoustic features of the speech signal.
  2. Hidden State Variables (S): These are the unobservable or hidden variables that represent the underlying states of the system. Each state emits observations according to a probability distribution. The transitions between hidden states are governed by transition probabilities. In speech recognition, hidden state variables could represent phonemes or words.
  3. Transition Variables (T): These are the variables representing the transition probabilities between different hidden states. They define the probabilities of transitioning from one hidden state to another.

So, the correct answer to the question “In HMM’s, what are the possible values of the variable?” would be:

  • Observation Variables (O)
  • Hidden State Variables (S)
  • Transition Variables (T)