ML training
ML training
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If we use the gradient techniques with ML, then the procedure would be
as follows.
- (1)
- Initialize the each HMM
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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.
Narada Warakagoda
Fri May 10 20:35:10 MET DST 1996