Patent US10181333

Intelligent truthfulness indicator association
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US10181333

1. A method comprising: (12) (3)

obtaining speech based message data and biometric data of a speaker user of a messaging system, the speech based message data being input into a computer device by the speaker user and the biometric data indicating one or more aspect of a physical condition of the speaker user during the input of the speech based message data into the computer device;

processing data to determine a truthfulness parameter of the speech based message data, the processing data to determine a truthfulness parameter including processing the biometric data, the truthfulness parameter indicating a probability that the speech based message data is knowingly untruthful; and

associating the truthfulness parameter to the speech based message data, wherein the associating includes tagging the speech based message data with the truthfulness parameter, wherein the processing includes performing a preliminary truthfulness determining process, the preliminary truthfulness determining process based on examining of biometric data, and wherein the processing includes performing a fact check process to determine factual correctness of content of the message data conditionally on the condition that the preliminary truthfulness determining process satisfies a criteria.

2. The method of claim 1, wherein the method includes activating a speech Natural Language Processing (NLP) process to determine a sentiment parameter of the speech based message data, and wherein the method includes tagging the speech based message data with the sentiment parameter. (0)

3. The method of claim 1, wherein the processing includes determining the truthfulness parameter based on one or more of the following selected from the group consisting of: (a) a fact check process output, wherein the fact check process checks factual correctness of statements of the speech based message data, and (c) an NLP process output, wherein the NLP process is performed using the speech based message data. (0)

4. The method of claim 1, wherein the processing includes determining the truthfulness parameter based on each of (a) a fact check process output, wherein the fact check process checks factual correctness of statements of the speech based message data, and (c) an NLP process output, wherein the NLP process is performed using the speech based message data. (0)

5. The method of claim 1, wherein the biometric data includes one or more of the following selected from the group consisting of (a) received image data, (b) received blood pressure data, (d) received pulse data, (e) received skin conductivity data, and (f) received breathing data. (0)

6. The method of claim 1, wherein the processing includes determining the truthfulness parameter based on received biometric data provided by breathing data, the breathing data being provided by activating a speech NLP process to process the speech based message data. (0)

7. The method of claim 1, wherein the method includes responsively to the processing initiating one or more of the following selected from the group consisting of: (a) a change in digital rights defining access to a security protected electronic asset, (b) an alert, and (c) a change in access to a physical asset. (0)

8. The method of claim 1, wherein the processing includes performing a preliminary truthfulness determining process, the preliminary truthfulness determining process based on examining of biometric data and on an output of a first fact check process, and wherein the processing includes performing a second fact check process to determine factual correctness of content of the message data conditionally on the condition that the preliminary truthfulness determining process satisfies a criteria, the second fact check process consuming processing resources in excess of processing resources consumed by the first fact check process. (0)

9. The method of claim 1, wherein the method includes performing a machine learning process for identifying signature behavior patterns for the user, the signature behavior patterns identified by the performing a machine learning process including signature biometric patterns identified as being exhibited by the user on input of message data that satisfies a criteria, and wherein the processing includes examining the biometric data for the speech based message data to determine whether a signature biometric pattern of the signature biometric patterns is included in the biometric data. (0)

10. The method of claim 1, wherein the method includes performing a machine learning process for identifying signature behavior patterns for the user, the signature behavior patterns identified by the performing a machine learning process including signature behavior patterns identified as being exhibited by the user on input of message data that satisfies a criteria, and wherein the processing includes examining NLP output data for the speech based message data to determine whether a signature NLP pattern of the signature NLP patterns is included in the NLP output data. (0)

11. The method of claim 1, wherein the processing includes performing processing based on user defined configuration data entered into a user interface, the user interface including on or more of the following selected from the group consisting of (a) a user interface for use by an administrator user, and (b) a user interface for use by a user of a messaging system. (0)

12. The method of claim 1, wherein the method includes converting speech of the speech based message data into text, activating a text based Natural Language Processing (NLP) process to determine a sentiment parameter of the speech based message data, and wherein the method includes tagging the speech based message data with the sentiment parameter, wherein the processing includes determining the truthfulness parameter based on received biometric data for the message data, the received biometric data provided by one or more of the following selected form the group consisting of (a) received image data, (b) received blood pressure data, (d) received pulse data, (e) received skin conductivity data, and (f) received breathing data, wherein the processing includes performing a preliminary truthfulness determining process, the preliminary truthfulness determining process based on examining of biometric data, and wherein the processing includes performing a fact check process to determine factual correctness of content of the message data conditionally on the condition that the preliminary truthfulness determining process satisfies a criteria, wherein the method includes responsively to the processing initiating one or more of the following selected from the group consisting of: (i) a change in digital rights defining access to a security protected electronic asset, (ii) an alert, and (iii) a change in access to a physical asset, and wherein the processing includes performing processing based on user defined configuration data entered into a user interface, the user interface including on or more of the following selected from the group consisting of (A) a user interface for use by an administrator user, and (B) a user interface for use by a user of a messaging system. (0)

13. The method of claim 1, wherein the processing and associating are performed by one or more computing node remote and external from the computer device. (0)

14. A computer program product comprising: (4) (4)

a computer readable storage medium readable by one or more processing unit and storing instructions for execution by one or more processor for performing a method comprising:

15. The computer program product of claim 14, wherein the method includes activating a speech Natural Language Processing (NLP) process to determine a sentiment parameter of the message data, and wherein the method includes tagging the message data with the sentiment parameter. (0)

16. The computer program product of claim 14, wherein the processing includes determining the truthfulness parameter based each of the following (a) a biometric output for the message data, (b) a fact check process output, wherein the fact check process checks factual correctness of statements of the message data, and (c) an NLP process output, wherein the NLP process is performed on the message data. (0)

17. The computer program product of claim 14, wherein the method includes performing a machine learning process for identifying signature behavior patterns for the user, the signature behavior patterns identified by the performing a machine learning process including signature behavior patterns identified as being exhibited by the user on input of message data that satisfies a criteria, and wherein the processing includes examining NLP output data for the speech based message data to determine whether a signature NLP pattern of the signature NLP patterns is included in the NLP output data. (0)

18. The method of claim 14, wherein the processing includes determining the truthfulness parameter based on each of the following (a) received image data, (b) received blood pressure data, (d) received pulse data, (e) received skin conductivity data, and (f) received breathing data. (0)

19. A system comprising: (0) (5)

a memory;

at least one processor in communication with the memory; and program instructions executable by one or more processor via the memory to perform a method comprising:

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Patent US10181333

Intelligent truthfulness indicator association

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