Automatic speaker recognition system using the discrete Hartley transform and an artificial neural network

A system is presented which will identify speakers that it was trained to recognize with 100% accuracy. This system will also classify inputs that it has not been trained to recognize as unknown. The high degree of confidence offered by this system is attributed to careful processing of the input data sets. Only easily distinguishable segments of the speech samples are passed as inputs to the artificial neural network (ANN). Additionally, sufficient input information is provided with the training inputs to enable the ANN to rapidly train and subsequently classify speakers. This system may be readily implemented in hardware using existing technology. Hardware implementation will render near real-time performance. Applications that would be enhanced by the use of this system include electronic surveillance and computer security. The speaker identification system was successfully tested