On the use of perceptual Line Spectral pairs Frequencies and higher-order residual moments for Speaker Identification

Abstract: Conventional Speaker Identification (SI) systems utilise spectral features like Mel-Frequency Cepstral Coefficients (MFCC) or Perceptual Linear Prediction (PLP) as a frontend module. Line Spectral pairs Frequencies (LSF) are popular alternative representation of Linear Prediction Coefficients (LPC). In this paper, an investigation is carried out to extract LSF from perceptually modified speech. A new feature set extracted from the residual signal is also proposed. SI system based on this residual feature containing complementary information to spectral characteristics, when fused with the conventional spectral feature based system as well as the proposed perceptually modified LSF, shows improved performance