TRAINING APPROACH FOR HIDDEN MARKOV-MODELS

The authors propose a new training approach based on maximum model dis tance (MMD) for HMMs. MMD uses the entire training set to estimate the parameters of each HMM, while the traditional maximum likelihood (ML) only uses those data labelled for the model. Experimental results sho wed that significant error reduction can be achieved through the propo sed approach. In addition, the relationship between MMD and corrective training [3] was discussed, and we have proved that the corrective tr aining is a special case of MMD approach.