presents some experiments on discriminative training for GMM/UBM speaker
recognition. We propose two MMIE adaptation methods for GMM component weights
suitable for speaker recognition. The impact on performance of this training
methods is compared to the standard weight estimation/adaptation criterion, MLE
and MAP on standard GMM systems and on SVM systems. The results enforce the
difficulty to introduce discriminative behaviour in GMM where as it is inherent
in SVM systems.