Speech/speaker recognition using a HMM/GMM hybrid model

In this paper, a speaker recognition voice based system is presented [5]. We have implemented it in a Sun platform. We train (and test) the system using a Database recorded in several sessions in order to repair the huge effects that the speech variability with time has in the recognition rate system. Several experiments have been made iri order to achieve the best configuration in the system set up. This is an important point to take into account in a real world system in which users train,the system once and the models generated in the training process are not updated for strategic reasons. The recognition rate obtained for the proposed system is around 93% if the speech came from a microphone is around 90% when the speech came from a phone line.