Predictive neural networks in text independent speaker verification: an evaluation on the SIVA database

The authors propose a system which combines the use of predictive neural networks and the statistical approach in the task of text-independent speaker verification through a telephone line. The system is composed of a predictive neural network for every reference speaker, which is trained with the backpropagation algorithm and the maximum likelihood criterion, in order to obtain the highest probability that the input to the network belongs to the reference speaker. They also consider a global network trained on the whole training set whose likelihood gives a measure of the predictability of a given input with the aim of eliminating the strong dependence of the score from the particular input considered. The evaluation of the system is carried out on a subset of the Italian telephonic database SIVA, purposely collected for the considered task