In this paper we successfully apply the MCE/GPD method to train speaker cluster HMM. The essential concept of our approach is to adjust all the parameters of the speaker cluster HMM simultaneously using each utterance of the whole training set. In other words, the parameters of each cluster-dependent HMM are no longer independently estimated by using only the training data of the speakers who belong to its corresponding cluster. To achieve this purpose, the discriminant function used in the

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... GPD method need to be defined by the parameter set of the entire speaker cluster HMM. In our implementation, we define it as a function of the log-likelihood scores given the cluster-dependent HMMs. The proposed discriminative training procedure would increase the cluster separability and then improve the recognition rate.