Artificial immune systems for text-dependent speaker recognition

Abstract

This paper shows the potential accomplishments of artificial immune systems (in particular, the negative selection algorithm) application to the problem of speaker recognition. Both the use of binary representation of original signal and that of its Fast Fourier Transform in a real-number representation are analysed. A number of experiments are performed on different datasets to examine the performance evolution with respect to the different system parameters. It is found that substantial enhancements of the system capabilities are possible by means of the exploitation of the Fast Fourier Transform.