Speaker Recognition Based on the Use of Vocal Tract and Residue Signal LPC Parameters

The problem of text-independent speaker recognition based on the use of vocal tract and residue signal LPC parameters is investigated. Pseudostationary segments of voiced sounds are used for feature selection. Parameters of the linear prediction model (LPC) of vocal tract and residue signal or LPC derived cepstral parameters are used as features for speaker recognition. Speaker identification is performed by applying nearest neighbour rule to average distance between speakers. Comparison of distributions of intraindividual and interindividual distortions is used for speaker verification. Speaker recognition performance is investigated. Results of experiments demonstrate speaker recognition performance.