7. A system for reducing a security vulnerability of a speech-based user authentication process, the system comprising: a memory configured to store executable instructions; a network interface communicatively coupled to the memory, the network interface configured to receive over a communication network from a client device:  a request to authenticate a user, and a speech signal having one or more discriminating features; and a processor configured to execute the instructions stored in the memory and thereby: extract the one or more discriminating features from the received speech signal, wherein extracting the one or more discriminating features includes: segmenting the received speech signal into at least one of one or more utterances, one or more words, or one or more phonemes, computing one or more pitch patterns of the received speech signal, segmenting the pitch pattern to form a pitch pattern image, the pitch pattern image displaying a plurality of discrete data regions each forming a shape, and performing an image analysis of the pitch pattern image, wherein performing the image analysis includes: determining for each of at least a portion of the regions an upper line value associated with an upper edge of the shape displayed in the pitch pattern image and a lower line value associated a lower edge of the shape displayed in the pitch pattern image, and calculating one or more discriminating features based on the upper line value and the lower line value determined from the pitch pattern image to form a set of feature vectors; classify the received speech signal based on the extracted features as a synthetic speech signal configured to imitate a sequence of human vocal sounds, and decline the request to authenticate the user based on the classification of the received speech signal as the synthetic speech signal.
7. A system for reducing a security vulnerability of a speech-based user authentication process, the system comprising: a memory configured to store executable instructions; a network interface communicatively coupled to the memory, the network interface configured to receive over a communication network from a client device:  a request to authenticate a user, and a speech signal having one or more discriminating features; and a processor configured to execute the instructions stored in the memory and thereby: extract the one or more discriminating features from the received speech signal, wherein extracting the one or more discriminating features includes: segmenting the received speech signal into at least one of one or more utterances, one or more words, or one or more phonemes, computing one or more pitch patterns of the received speech signal, segmenting the pitch pattern to form a pitch pattern image, the pitch pattern image displaying a plurality of discrete data regions each forming a shape, and performing an image analysis of the pitch pattern image, wherein performing the image analysis includes: determining for each of at least a portion of the regions an upper line value associated with an upper edge of the shape displayed in the pitch pattern image and a lower line value associated a lower edge of the shape displayed in the pitch pattern image, and calculating one or more discriminating features based on the upper line value and the lower line value determined from the pitch pattern image to form a set of feature vectors; classify the received speech signal based on the extracted features as a synthetic speech signal configured to imitate a sequence of human vocal sounds, and decline the request to authenticate the user based on the classification of the received speech signal as the synthetic speech signal. 9. The system of claim 7 , wherein the classification comprises: prompting a user to speak a predetermined utterance, the predetermined utterance having one or more words that are discriminatory in distinguishing a human speech signal comprising a sequence of human vocal sounds from a synthetic speech signal configured to imitate the sequence of human vocal sounds; storing a table of unique words and corresponding distance measures for human word models and synthetic word models in memory; measuring a weighted distance between a human word utterance and a corresponding synthetic word utterance; and classifying the received speech as synthetic rather than human based on the measured distance as compared to the distance measures stored in the table.