Efficient text independent speaker recognition with wavelet feature selection based multilayered neural network using supervised learning algorithm

A wavelet packet feature selection derived by using multilayered neural network for speaker identification is described. The concept of a multilayered neural network is without using a gradient method. First, the outputs of each hidden unit are algebraically determined by an error backpropagation method. Then, the weight parameters are determined by using an exponentially weighted least squares method. Our results have shown that this feature selection introduced better performance than the other methods with respect to the percentages of recognition.