Automatic speaker recognition using circular DFT sectors

Abstract

In this paper, we propose automatic speaker recognition using circular DFT (Discrete Fourier Transform) sectors. In the first method, the feature vectors are extracted by dividing the complex DFT spectrum into circular sectors and then taking the weighted density count of the number of points in each of these sectors. In the second and third method, the circular sectors are further divided and then weighted density count of the number of samples is used as feature vector. The results show that this approach gives fairly good speaker recognition (70 % -80%)Also the results improve as the circular sectors are further divided.