Investigation of an automatic speaker identification system using a neural network

摘要

This paper investigated a simple speaker identification system based on a backpropagation neural network. The network was trained to distinguish between a small base of speakers using parameters extracted from human speech which are typically speaker dependent. Different network configurations were tested and observations were made regarding training time, testing errors and the ability to generalize. The results showed that an experimentally determined optimum network configuration produced no errors during testing and that the parameters used to represent each speaker are sufficient for generalization.