Usefulness of the LPC-residue in text-independent speaker verification
Speech Communication
Discrete Time Processing of Speech Signals
Discrete Time Processing of Speech Signals
Speaker Identification Using Harmonic Structure of LP-residual Spectrum
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Signal modeling for speaker identification
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
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This paper compares the identification rates of a speaker recognition system using several parameterizations, with special emphasis on the residual signal obtained from linear and nonlinear predictive analysis. It is found that the residual signal is still useful even when using a high dimensional linear predictive analysis. On the other hand, it is shown that the residual signal of a nonlinear analysis contains less useful information, even for a prediction order of 10, than the linear residual signal. This shows the inability of the linear models to cope with nonlinear dependences present in speech signals, which are useful for recognition purposes.