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Baum-Welch algorithm

For the evaluation problem, the probability of an observation sequence O = oi, 02,..., ot is determined, given the model A, P(0 A). This probability can be found using the forward part of the inductive forward-backward algorithm (Baum-Welch algorithm [13]), which is initialized by... [Pg.143]

In the state estimation problem, the aim is to find a state sequence that best explains the real observations. For this, a new variable 7 is defined in terms of the forward (a) and backward (/ ) variables of the Baum-Welch algorithm ... [Pg.145]

All of the information needed to perform HMM parameter re-estimation using the Baum-Welch algorithm is now in place. The steps in this algorithm may be summarised as follows... [Pg.463]

In the off-line phase, the training data is classified into M different groups and then, each constituent HMM model is trained individually with the data in the corresponding group. At this step, the well-known Baum-Welch algorithm can be used without any modifications. In the next step, the number of data in each group is used to assign the a priori probabilities for each model (equation (2)). Finally, a trained MB-HMM model is obtained. [Pg.1199]

After having determined the number of states, each model is trained thanks to the Baum-Welch algorithm. The next step is to assign the a priori probability for each branch (equation (2)) and the result are = 0.41 and = 0.59. [Pg.1202]

Equations 15.19 and 15.20 are the Baum-Welch re-estimation formulae for the means and co-variances of a HMM. A similar but slightly more complex formula can be derived for the transition probabilities. Of course, to apply equations 15.19 and 15.20, the probability of state occupation Lj t) must be calculated. This is done efficiently using the forward-backward algorithm. Let the forward probability tty(t) for some modelMwith A states be defined as... [Pg.462]


See other pages where Baum-Welch algorithm is mentioned: [Pg.144]    [Pg.222]    [Pg.461]    [Pg.105]    [Pg.221]    [Pg.448]    [Pg.87]    [Pg.144]    [Pg.222]    [Pg.461]    [Pg.105]    [Pg.221]    [Pg.448]    [Pg.87]    [Pg.220]    [Pg.219]   
See also in sourсe #XX -- [ Pg.449 ]

See also in sourсe #XX -- [ Pg.449 ]




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