Speaker recognition using features derived from fractional Fourier transform

As the generalization of the classical Fourier transform, fractional Fourier transform(FRFT) is introduced into the field of speaker recognition in this paper. The individual feature sets derived from fractional Fourier transform achieve the excellent recognition success rate which goes up to the extent a little higher than the counterparts of the classical MFCC parameters when applied in the GMM classifiers. In addition, the computation efficiency of the feature extraction process arrives at the acceptable level which completely matches the one of MFCC parameter acquirement.