Predictive video analytics system and methods
First Claim
1. A video analytics system adapted to predict user behavior based on analysis of a video communication, which comprises:
- a node comprising a processor and a non-transitory computer readable medium operably coupled thereto, the non-transitory computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises;
instructions, that when executed, receive a video communication from a user, wherein the video communication comprises an audio component and a video component;
instructions, that when executed, analyze the video component to provide time-coded video behavioral data from the user;
instructions, that when executed, analyze the audio component to provide time-coded spoken words from the user;
instructions, that when executed, associate the time-coded spoken words with the video behavioral data to determine an emotional state of the user,instructions, that when executed, aggregate the spoken words and the video behavioral data to build a predictive model;
instructions, that when executed, determine a personality type of the user by applying a linguistic-based algorithm to the spoken words, searching a density of keywords in the spoken words, applying contextual weighting to the keywords, and comparing the weighted keywords to keywords stored in a library separated by different personality types; and
instructions, that when executed, enter the emotional state and the personality type into the predictive model, wherein the predictive model generates an indication of a likelihood of an outcome of the video communication.
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Abstract
The methods and systems described herein predict user behavior based on analysis of a user video communication. The methods include receiving a user video communication, extracting video facial analysis data from the video communication, extracting voice analysis data from the video communication, associating the video facial analysis data with the voice analysis data to determine an emotional state of a user, applying a linguistic-based psychological behavioral model to the voice analysis data to determine personality type of the user, and inputting the emotional state and personality type into a predictive model to determine a likelihood of an outcome of the video communication.
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Citations
30 Claims
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1. A video analytics system adapted to predict user behavior based on analysis of a video communication, which comprises:
a node comprising a processor and a non-transitory computer readable medium operably coupled thereto, the non-transitory computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises; instructions, that when executed, receive a video communication from a user, wherein the video communication comprises an audio component and a video component; instructions, that when executed, analyze the video component to provide time-coded video behavioral data from the user; instructions, that when executed, analyze the audio component to provide time-coded spoken words from the user; instructions, that when executed, associate the time-coded spoken words with the video behavioral data to determine an emotional state of the user, instructions, that when executed, aggregate the spoken words and the video behavioral data to build a predictive model; instructions, that when executed, determine a personality type of the user by applying a linguistic-based algorithm to the spoken words, searching a density of keywords in the spoken words, applying contextual weighting to the keywords, and comparing the weighted keywords to keywords stored in a library separated by different personality types; and instructions, that when executed, enter the emotional state and the personality type into the predictive model, wherein the predictive model generates an indication of a likelihood of an outcome of the video communication. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A method to predict user behavior based on analysis of a video communication, which comprises:
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receiving, by one or more processors, a user video communication; extracting, by the one or more processors, video facial analysis data for the user from the video communication; extracting, by the one or more processors, voice analysis data from the user video communication; associating, by the one or more processors, the video facial analysis data with the voice analysis data to determine an emotional state of the user; aggregating, by the one or more processors, the voice analysis data and the video facial analysis data to build a predictive model; applying, by the one or more processors, a linguistic-based psychological behavioral model to the voice analysis data, searching a density of keywords in the voice analysis data, applying contextual weighting to the keywords, and comparing the weighted keywords to keywords stored in a library separated by different personality types to determine personality type of the user; and inputting, by the one or more processors, the emotional state and the personality type into the predictive model, wherein the predictive model generates an indication of a likelihood of an outcome of the video communication. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23)
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24. A non-transitory machine-readable medium comprising instructions which, in response to a computer system, cause the computer system to perform a method which comprises:
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receiving a user video communication; separating an audio component from a video component of the video communication; analyzing facial expressions of the user in the video component; transcribing words spoken of the user in the audio component; associating the facial expressions and spoken words to determine an emotional state of the user; aggregating the spoken words and the facial expressions to build a predictive model; determining a personality type of the user by applying a linguistic-based algorithm, searching a density of keywords in the spoken words, applying contextual weighting to the keywords, and comparing the weighted keywords to keywords stored in a library separated by different personality types; and inputting the emotional state and the personality type into the predictive model to predict a likelihood of an outcome of the video communication. - View Dependent Claims (25, 26, 27, 28, 29, 30)
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Specification