A Neural-Network Approach for Speech Features Classification Based on Paraconsistent Logic

In this paper, two independent Support Vector Machines were connected to a paraconsistent logic unit in order to establish a new classification scheme which takes into account the degrees of faith and uncertainty of a certain statement. By using this approach, one can classify an input signal as matching one of two independent classes or both of them. In our experiments, speech data constitute the classification elements which were adopted, and the results demonstrate the efficacy of the proposed approach.