This paper 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.