System and method for digital voice data processing and authentication

1 . A system for digital voice data processing and authentication, the system comprising:

at least one non-transitory storage device; and

at least one processing device coupled to the at least one non-transitory storage device, wherein the at least one processing device is configured to:

receive a user interaction comprising a digital audio signal;

capture a first audio segment and a second audio segment of the digital audio signal continuously, in real time, from a singular audio source, wherein the second audio segment is subsequent the first audio segment, wherein the first audio segment corresponds to a first instance of a word and the second audio segment corresponds to a second instance of the word, wherein a natural language processing engine identifies the first audio segment and the second audio segment as two instances of the same word from text of the first audio segment and the second audio segment, and wherein the natural language processing engine identifies word boundaries of the first audio segment and the second audio segment by tagging timestamps of the digital audio signal corresponding to the beginning and end of each word;

plot the first audio segment and the second audio segment into corresponding first and second plots, wherein the first plot comprises a first curve comprising a first plurality of points, wherein the second plot comprises a second curve comprising a second plurality of points, and wherein a plot type of the first and second plots is a spectrogram;

compare the first and second plots, wherein comparing comprises subtracting each point of the first plurality of points of the first curve from a corresponding point of the second plurality of points of the second curve at corresponding horizontal axis locations to form a difference plot;

determine a quantity of outlier peaks, wherein the outlier peaks comprise peaks of the difference plot above an upper predetermined threshold or below a lower predetermined threshold;

assign an artificial user probability to the user interaction, wherein the artificial user probability is low if the quantity of outlier peaks is greater than a predetermined outlier peak threshold; and

display the artificial user probability on a user interface of an endpoint device.

2 . The system of claim 1 , wherein the first audio segment is received subsequent a first word prompt provided to a user, wherein the second audio segment is provided in response to a second word prompt provided to a user, and wherein the first word prompt and the second word prompts are identical.

3 . The system of claim 1 , wherein the first audio segment and the second audio segment are captures of space between words, wherein the space between words is related to auditory cadence captured in the first and second audio segments.

4 . The system of claim 1 , wherein if the artificial user probability is high, at least one of a spectrogram of the first audio segment and a spectrogram of the second audio segment is transmitted to a machine learning subsystem as training data.

5 . The system of claim 4 , wherein the at least one processing device is further configured to:

query the machine learning subsystem, prior to comparing the first and second plots, to determine if the spectrogram is identical to a known spectrogram; and

terminate the user interaction if the spectrogram is identical.

6 . A computer program product for digital voice data processing and authentication, the computer program product comprising a non-transitory computer-readable medium comprising code causing a first apparatus to:

receive a user interaction comprising a digital audio signal;

capture a first audio segment and a second audio segment of the digital audio signal continuously, in real time, from a singular audio source, wherein the second audio segment is subsequent the first audio segment, wherein the first audio segment corresponds to a first instance of a word and the second audio segment corresponds to a second instance of the word, wherein a natural language processing engine identifies the first audio segment and the second audio segment as two instances of the same word from text of the first audio segment and the second audio segment, and wherein the natural language processing engine identifies word boundaries of the first audio segment and the second audio segment by tagging timestamps of the digital audio signal corresponding to the beginning and end of each word;

plot the first audio segment and the second audio segment into corresponding first and second plots, wherein the first plot comprises a first curve comprising a first plurality of points, wherein the second plot comprises a second curve comprising a second plurality of points, and wherein a plot type of the first and second plots is a spectrogram;

compare the first and second plots, wherein comparing comprises subtracting each point of the first plurality of points of the first curve from a corresponding point of the second plurality of points of the second curve at corresponding horizontal axis locations to form a difference plot;

determine a quantity of outlier peaks, wherein the outlier peaks comprise peaks of the difference plot above an upper predetermined threshold or below a lower predetermined threshold;

assign an artificial user probability to the user interaction, wherein the artificial user probability is low if the quantity of outlier peaks is greater than a predetermined outlier peak threshold; and

display the artificial user probability on a user interface of an endpoint device.

7 . The computer program product of claim 6 , wherein the first audio segment is received subsequent a first word prompt provided to a user, wherein the second audio segment is provided in response to a second word prompt provided to a user, and wherein the first word prompt and the second word prompts are identical.

8 . The computer program product of claim 6 , wherein the first audio segment and the second audio segment are captures of space between words, wherein the space between words is related to auditory cadence captured in the first and second audio segments.

9 . The computer program product of claim 6 , wherein if the artificial user probability is high, at least one of a spectrogram of the first audio segment and a spectrogram of the second audio segment is transmitted to a machine learning subsystem as training data.

10 . The computer program product of claim 9 , wherein the code further causes a first apparatus to:

query the machine learning subsystem, prior to comparing the first and second plots, to determine if the spectrogram is identical to a known spectrogram; and

terminate the user interaction if the spectrogram is identical.

11 . A method for digital voice data processing and authentication, the method comprising:

receiving a user interaction comprising a digital audio signal;

capturing a first audio segment and a second audio segment of the digital audio signal continuously, in real time, from a singular audio source, wherein the second audio segment is subsequent the first audio segment, wherein the first audio segment corresponds to a first instance of a word and the second audio segment corresponds to a second instance of the word, wherein a natural language processing engine identifies the first audio segment and the second audio segment as two instances of the same word from text of the first audio segment and the second audio segment, and wherein the natural language processing engine identifies word boundaries of the first audio segment and the second audio segment by tagging timestamps of the digital audio signal corresponding to the beginning and end of each word;

plotting the first audio segment and the second audio segment into corresponding first and second plots, wherein the first plot comprises a first curve comprising a first plurality of points, wherein the second plot comprises a second curve comprising a second plurality of points, and wherein a plot type of the first and second plots is a spectrogram;

comparing the first and second plots, wherein comparing comprises subtracting each point of the first plurality of points of the first curve from a corresponding point of the second plurality of points of the second curve at corresponding horizontal axis locations to form a difference plot;

determining a quantity of outlier peaks, wherein the outlier peaks comprise peaks of the difference plot above an upper predetermined threshold or below a lower predetermined threshold;

assigning an artificial user probability to the user interaction, wherein the artificial user probability is low if the quantity of outlier peaks is greater than a predetermined outlier peak threshold; and

displaying the artificial user probability on a user interface of an endpoint device.

12 . The method of claim 11 , wherein the first audio segment is received subsequent a first word prompt provided to a user, wherein the second audio segment is provided in response to a second word prompt provided to a user, and wherein the first word prompt and the second word prompts are identical.

13 . The method of claim 11 , wherein the first audio segment and the second audio segment are captures of space between words, wherein the space between words is related to auditory cadence captured in the first and second audio segments.

14 . The method of claim 11 , wherein if the artificial user probability is high, at least one of a spectrogram of the first audio segment and a spectrogram of the second audio segment is transmitted to a machine learning subsystem as training data.

15 . The method of claim 14 , wherein the method further comprises:

querying a machine learning subsystem, prior to comparing the first and second plots, to determine if the spectrogram is identical to a known spectrogram; and

terminating the user interaction if the spectrogram is identical.