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Let us calculate the number of parameters for bi-gram hMM given as

Let be the total number of states and be the vocabulary size and be the length of the sequence

- Before directly estimating the number of parameters, let us first try to see what are the different probabilities or rather probability matrix we have.
- Once we know the probability matrix, we can estimate the parameters by its size.
- If you’re thinking how does a probability matrix appear, notice that we have conditional probabilities here, and or probability expression involving 2 variables and such as , hence we should have the probability matrix.
- So for we have a probability matrix where each row is a state and each column is an output variable . Hence this matrix is of size leading to these many parameters.
- Similarly for , we have x matrix and hence same number of parameters.
- From (d) and (e), we have at least parameters.
- Now think carefully if we there is anything which we missed in our calculation.
- We also have start tokens and initial state . In State Probability matrix explained in (e), we have one more row but columns are still N. Therefore number of parameters due to initial state becomes
- Once you’re convinced, you’ll get to know that total number of parameters in the above hMM model are
- Give a try for a general for n-gram hMM!

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