ML training

If we use the gradient techniques with ML, then the procedure would be as follows.

(1)

Initialize the each HMM with values generated randomly or using an initialization algorithm like segmental K means .

(2)

Take an observation sequence of a sentence and,

• Form the corresponding sentence model using the HMMs of the speech units contained in the sentence.
• Calculate the forward and backward probabilities for the sentence model, using the recursions 1.5 and 1.2.
• Using the equation 1.21 calculate the likelihood of the observations in the sentence model.
• Using the equations 1.26 and 1.29 calculate the gradients wrt all parameters in the sentence model.
• Update parameters in each of the HMMs in the sentence model using the eqn.1.19.

(3)

Go to step (2), unless all the observation sequences are considered.

(4)

Repeat step(2) to (3) until a convergence criterion is satisfied.

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