1. A system for generating a biometric voice print, comprising: a voice processor for: receiving a spoken utterance and at least one repetition of the spoken utterance from a user; segmenting the spoken utterance into one or more vocalized frames; generating one or more feature vectors from the one or more vocalized frames, wherein the one or more feature vectors include identification parameters that minimize an intra-speaker variability and that maximize an inter-speaker variability; calculating a feature matrix from the one or more feature vectors; and normalizing the feature matrix over the one or more vocalized frames; wherein the voice processor generates the one or more feature vectors by: segmenting the spoken utterance into one or more vocalized frames; performing a perceptual filter bank analysis on the one or more vocalized frames; calculating Linear Prediction Coefficients (LPC) from the perceptual filter bank analysis; converting the LPC's to Line Spectral Pair coefficients (LSP's); calculating formants and anti-formants from the LSP's; and creating the feature vectors from the formants and anti-formants; and a biometric voice analyzer for: calculating one or more vocal tract shapes from the spoken utterance and the at least one repetition; and calculating a vocal tract configuration difference between the one or more vocal tract shapes based on a varying pronunciation of the spoken utterance and the at least one repetition.
1. A system for generating a biometric voice print, comprising: a voice processor for: receiving a spoken utterance and at least one repetition of the spoken utterance from a user; segmenting the spoken utterance into one or more vocalized frames; generating one or more feature vectors from the one or more vocalized frames, wherein the one or more feature vectors include identification parameters that minimize an intra-speaker variability and that maximize an inter-speaker variability; calculating a feature matrix from the one or more feature vectors; and normalizing the feature matrix over the one or more vocalized frames; wherein the voice processor generates the one or more feature vectors by: segmenting the spoken utterance into one or more vocalized frames; performing a perceptual filter bank analysis on the one or more vocalized frames; calculating Linear Prediction Coefficients (LPC) from the perceptual filter bank analysis; converting the LPC's to Line Spectral Pair coefficients (LSP's); calculating formants and anti-formants from the LSP's; and creating the feature vectors from the formants and anti-formants; and a biometric voice analyzer for: calculating one or more vocal tract shapes from the spoken utterance and the at least one repetition; and calculating a vocal tract configuration difference between the one or more vocal tract shapes based on a varying pronunciation of the spoken utterance and the at least one repetition. 6. The system of claim 1 , wherein the voice processor: calculates a feature matrix from the feature vectors for multiple sections of the spoken utterance corresponding to the one or more vocalized frames, wherein the feature matrix is a concatenation of feature vectors of the one or more vocalized frames; and normalizes the feature matrix by removing vocalized frames shorter that a predetermined length and removing vocalized frames corresponding to vocal tract configurations that exceed an average vocal tract configuration.