PERSONALITY-BASED CHATBOT AND METHODS INCLUDING NON-TEXT INPUT

• US 20180108353A1
• Filed: 12/18/2017
• Published: 04/19/2018
• Est. Priority Date: 06/19/2014
• Status: Active Grant

• Current Assignee: Mattersight Corporation (Nice Ltd)
• Original Assignee: Mattersight Corporation (Nice Ltd)
• Inventors: GUSTAFSON, David, DANSON, Christopher
• Granted Patent: US 10,748,534 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 3/167 Audio in a user interface, e.g. using voice commands for navigating, audio feedback
• CPC Class Codes: G06F 40/20 Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G10L 13/00 Speech synthesis; Text to speech systems
• CPC Class Codes: G10L 15/19 Grammatical context, e.g. disambiguation of the recognition hypotheses based on word sequence rules
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 15/30 Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
• CPC Class Codes: G10L 2015/088 Word spotting
• CPC Class Codes: G10L 25/51 for comparison or discrimination
• CPC Class Codes: G10L 25/63 for estimating an emotional state
• CPC Class Codes: G10L 25/66 for extracting parameters related to health condition detecting or measuring for diagnostic purposes A61B5/00
• CPC Class Codes: H04M 3/493 Interactive information services, e.g. directory enquiries ; Arrangements therefor, e.g. interactive voice response [IVR] systems or voice portals

Abstract

The methods, apparatus, and systems described herein assist a user with a request. The methods in part receive input from a user that includes a voice input, a gesture input, a text input, biometric information, or a combination thereof; retrieve or determine a personality type of the user based on the input; determine a distress level or an engagement level of the user; determine a set of outputs responsive to the received input; rank the outputs in the set based on the retrieved or determined personality type and the determined distress level or engagement level; deliver a ranked output to the input in a modality based on the retrieved or determined personality type and a type of device configured to deliver the ranked output to the user, wherein the device comprises a navigation system, a car, a robot, or a combination thereof; and weigh the ranked output for future interactions.

Claims

1. A system adapted to communicate with a user, 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 instruction stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises;

instructions that, when executed, receive input from a user, wherein the input comprises;

a voice input, a gesture input, a text input, biometric information, or a combination thereof;

instructions that, when executed, retrieve or determine a personality type of the user based on the input from the user;

instructions that, when executed, determine a distress level or an engagement level of the user;

instructions that, when executed, determine a set of outputs responsive to the received input;

instructions that, when executed, rank the outputs in the set based on the retrieved or determined personality type of the user and the determined distress level or engagement level of the user;

instructions that, when executed, deliver a ranked output to the input in a modality based on the retrieved or determined personality type of the user and a type of device configured to deliver the ranked output to the user, wherein the device comprises a navigation system, a car, a robot, or a combination thereof; and

instructions that, when executed, weigh the ranked output for future interactions with the user.

2. The system of claim 1, wherein the instructions that retrieve or determine a personality type of the user comprises instructions, that when executed, apply a linguistic-based algorithm to the input.

3. The system of claim 1, wherein the plurality of instructions further comprise instructions, that when executed, determine a mental state of the user based on the received input.

4. The system of claim 1, wherein the input further comprises context information.

5. The system of claim 4, wherein the context information comprises a user location, a local time, a positional orientation, a motion, a light level, a sound level, or a combination thereof.

6. The system of claim 4, wherein the plurality of instructions further comprise instructions, that when executed, predict input based on the context information.

7. The system of claim 6, wherein the plurality of instructions further comprise instructions that, when executed, rank the predicted input to prioritize predicted inputs for the user.

8. The system of claim 1, wherein the outputs comprise an email, a chat, a video, an actuator output to control physical actions of a device, an actuator output to control physical actions of a device attached or controlled by another device, or a combination thereof.

9. The system of claim 1, wherein the plurality of instructions further comprise:

instructions, that when executed, receive a user response to the ranked output;

instructions, that when executed, evaluate success of the ranked output in addressing the input based on the user response; and

instructions, that when executed, refine a future output based on the evaluation of the success.

10. The system of claim 9, wherein the instructions that evaluate success of the ranked output comprise instructions, that when executed, determine whether the ranked output results in a decrease in the distress level of the user or an increase in the engagement level of the user.

11. The system of claim 10, wherein the plurality of instructions further comprise instructions, that when executed, store the evaluation of the success of the ranked output and update the stored evaluation with outputs that result in a decrease in the distress level of the user or an increase in the engagement level of the user.

12. The system of claim 1, wherein the plurality of instructions further comprise instructions, that when executed, determine that the received input comprises input from a group of users.

13. The system of claim 12, wherein the plurality of instructions further comprise instructions, that when executed, adjust the outputs based on a determination of which of the group of users is providing the received input.

14. A method for communicating with a user, which comprises:

receiving input from a client device, wherein the input comprise a voice input, a gesture input, a text input, biometric information, or a combination thereof;

retrieving or determining a personality type of the user from three or more personality types based on input from the user;

determining a distress level of the user, an engagement level of the user, or both;

determining a set of outputs responsive to the received input;

ranking outputs based on the retrieved or determined personality type of the user and the determined distress level of the user, the engagement level of the user, or both;

delivering a ranked output to the input in a modality based on the retrieved or determined personality type of the user and a type of device configured to deliver the ranked output to the user, wherein the device comprises a navigation system, a self-driving car, a robot, or a combination thereof; and

weighing the ranked output for future interactions with the user.

15. The method of claim 14, wherein the retrieving or determining personality type of the user comprises applying a linguistic-based algorithm to the input.

16. The method of claim 14, which further comprises determining a mental state of the user based on the received input.

17. The method of claim 14, wherein the input further comprises context information.

18. The method of claim 17, wherein the context information comprises a user location, a local time, a positional orientation, a motion, a light level, a sound level, or a combination thereof.

19. The method of claim 14, which further comprises predicting input based on the context information.

20. The method of claim 19, which further comprises ranking the predicted input to prioritize predicted inputs for the user.

21. The method of claim 14, wherein the outputs comprise an email, a chat, a video, an actuator output to control physical actions of a device, an actuator output to control physical actions of a device attached or controlled by another device, or a combination thereof.

22. The method of claim 14, which further comprises extracting one or more communication attributes from the input.

23. The method of claim 22, wherein each communication attribute is selected to comprise tone, tempo, pattern of speech, syntax, grammar, or any combination thereof.

24. A method for assisting a user, which comprises:

receiving, by one or more processors, at least one input from the user, wherein the at least one input comprise a voice input, a gesture input, a text input, biometric information, or a combination thereof;

determining, by one or more processors, a personality type of the user from three or more personality types based on the at least one input;

determining a distress level of the user or an engagement level of the user;

determining, by one or more processors, a set of outputs based on the at least one input from the user and the determined personality type of the user;

ranking, by one or more processors, the outputs based on the determined personality type of the user and the determined distress level or engagement level of the user;

delivering, by one or more processors, a ranked output to the input in a modality based on the determined personality type of the user and a type of device configured to deliver the ranked output to the user, wherein the device comprises a navigation system, a self-driving car, a robot, or a combination thereof; and

weighing the ranked output for future interactions with the user.

25. The method of claim 24, wherein the determining a personality type comprises entering, by the one or more processors, the at least one input into an algorithm trained to output a personality type of the user.

26. The method of claim 24, wherein the at least one input further comprises a user location, a local time, a positional orientation, a motion, a light level, a sound level, or a combination thereof.

27. The method of claim 24, wherein the outputs comprise an email, a chat, a video, an actuator output to control physical actions of a device, an actuator output to control physical actions of a device attached or controlled by another device, or a combination thereof.

28. A non-transitory computer readable medium comprising a plurality of instructions comprising:

instructions that, when executed, receive input from a client device of a user, wherein the input comprise a voice input, a gesture input, a text input, biometric information, or a combination thereof, and the client device comprises a wearable computer health monitoring device;

instructions that, when executed, identify a personality type of the user based on the input;

instructions that, when executed, determine a distress level or an engagement level of the user;

instructions that, when executed, determine a set of outputs responsive to the received input;

instructions that, when executed, rank the outputs in the set based on the identified personality type of the user and the determined distress level or engagement level of the user;

instructions that, when executed, deliver a ranked output to the input in a modality based on the identified personality type of the user and a type of device configured to deliver the ranked output to the user, wherein the device comprises a navigation system, a self-driving car, a robot, or a combination thereof; and

instructions that, when executed, weigh the ranked output for future interactions with the user.