Speaker identification system based in verification techniques with Bayesian discrimination

In this work an automatic speaker identification system of good performance is presented, which is based in state-of-the-art verification systems. The problem of speaker verification can be extended to the task of identifying an individual between a group, called speaker identification. In this paper a modification to the final Bayesian discrimination between different speakers is proposed, including classification within the theoretical setting of the final statistical model. The system is able to display the usual good verification systems results, even for restricted data conditions.