IP Library Granted Patent US 11,283,928
Granted Patent B1
US 11,283,928 · App. 17/386,604 · Granted Mar 22, 2022

Real-time agent assistance using real-time automatic speech recognition and behavioral metrics

Inventors: Gordon Scott Edwards (Roswell, GA); Jon A. Arrowood (Atlanta, GA); Mark Finlay (Atlanta, GA)
Assignee: NICE LTD.
H04M3/5175G06N5/025G10L15/08G10L25/63G10L2015/088H04M2201/42H04M2203/402
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Quick Facts
Patent No.
US 11,283,928
App. No.
17/386,604
Granted
Mar 22, 2022
Kind
B1
Abstract

A method of assisting an agent in real-time includes includes receiving a call interaction between a customer and an agent; identifying words spoken in the call interaction; providing the words to a behavioral models module; computing a score for a plurality of behavioral metrics; providing a phrase formed by the words to a knowledge article selection module; providing each score for the plurality of behavioral metrics to the knowledge article selection module; providing a plurality of knowledge selection rules to the knowledge article selection module; evaluating a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules; matching a knowledge selection rule to the combination; selecting a knowledge article associated with the matched knowledge selection rule; generating a visual representation of the selected knowledge article; and presenting in real-time the visual representation on a graphical user interface.

Claims (69)

1. A real-time agent assistance system comprising:

a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform operations which comprise:

receiving a call interaction between a customer and an agent;

identifying, by a word spotting module, words spoken in the call interaction;

providing, by the word spotting module, the words to a behavioral models module;

computing, by the behavioral models module, a score for each of a plurality of behavioral metrics based at least in part on the words provided by the word spotting module;

providing, by the word spotting module, a phrase formed by the words to a knowledge article selection module;

providing, by the behavioral models module, each score for the plurality of behavioral metrics to the knowledge article selection module;

providing a plurality of knowledge selection rules to the knowledge article selection module, wherein each knowledge selection rule is associated with a knowledge article;

evaluating, by the knowledge article selection module, a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules;

matching, by the knowledge article selection module, a knowledge selection rule to the combination based on the evaluation;

selecting, by the knowledge article selection module, a knowledge article associated with the matched knowledge selection rule;

generating, by a knowledge article presentation module, a visual representation of the selected knowledge article; and

presenting in real-time, by the knowledge article presentation module to the agent or an agent supervisor, the visual representation on a graphical user interface.

2. The real-time agent assistance system of claim 1 , wherein the plurality of behavioral metrics comprises two or more of sentiment, active listening, empathy, demonstration of ownership, building rapport, setting expectations, effective questioning, promotion of self-service, speech velocity, or interruption.

3. The real-time agent assistance system of claim 1 , wherein the operations further comprise identifying time locations in the call interaction at which a spoken instance of a word occurred.

4. The real-time agent assistance system of claim 3 , wherein the operations further comprise determining whether the agent or the customer spoke the word.

5. The real-time agent assistance system of claim 1 , wherein the operations further comprise receiving the plurality of knowledge selection rules from a user.

6. The real-time agent assistance system of claim 5 , wherein the operations further comprise:

receiving an updated plurality of knowledge selection rules from the user;

re-evaluating, by the knowledge article selection module, the combination of the phrase and the scores of the plurality of behavioral metrics against each of the updated plurality of knowledge selection rules;

re-matching, by the knowledge article selection module, an updated knowledge selection rule to the combination based on the evaluation; and

re-selecting, by the knowledge article selection module, a knowledge article associated with the updated matched knowledge selection rule.

7. The real-time agent assistance system of claim 1 , wherein computing the score for each of the plurality of behavioral metrics comprises:

processing a first word to generate an initial score for each of the plurality of behavioral metrics; and

processing one or more additional words to iteratively update the initial scores.

8. The real-time agent assistance system of claim 1 , wherein the selected knowledge article comprises content associated with promotions, incentives, products, product accessories, services, service enhancements, or agent-assisting content.

9. The real-time agent assistance system of claim 1 , wherein the visual representation comprises an alert, a message, a score, or a combination thereof.

10. A method of assisting an agent in real-time, which comprises:

receiving a call interaction between a customer and an agent;

identifying, by a word spotting module, words spoken in the call interaction;

providing, by the word spotting module, the words to a behavioral models module;

computing, by the behavioral models module, a score for each of a plurality of behavioral metrics based at least in part on the words provided by the word spotting module;

providing, by the word spotting module, a phrase formed by the words to a knowledge article selection module;

providing, by the behavioral models module, each score for the plurality of behavioral metrics to the knowledge article selection module;

providing a plurality of knowledge selection rules to the knowledge article selection module, wherein each knowledge selection rule is associated with a knowledge article;

evaluating, by the knowledge article selection module, a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules;

matching, by the knowledge article selection module, a knowledge selection rule to the combination based on the evaluation;

selecting, by the knowledge article selection module, a knowledge article associated with the matched knowledge selection rule;

generating, by a knowledge article presentation module, a visual representation of the selected knowledge article; and

presenting in real-time, by the knowledge article presentation module to the agent or an agent supervisor, the visual representation on a graphical user interface.

11. The method of claim 10 , wherein the plurality of behavioral metrics comprise two or more of sentiment, active listening, empathy, demonstration of ownership, building rapport, setting expectations, effective questioning, promotion of self-service, speech velocity, or interruption.

12. The method of claim 10 , further comprising identifying time locations in the call interaction at which a spoken instance of a word occurred.

13. The method of claim 12 , further comprising determining whether the agent or the customer spoke the word.

14. The method of claim 10 , further comprising receiving the plurality of knowledge selection rules from a user.

15. The method of claim 10 , wherein computing the score for each of the plurality of behavioral metrics comprises:

processing a first word to generate an initial score for each of the plurality of behavioral metrics; and

processing one or more additional words to iteratively update the initial scores.

16. A non-transitory computer-readable medium having stored thereon computer-readable instructions executable by a processor to perform operations which comprise:

receiving a call interaction between a customer and an agent;

identifying, by a word spotting module, words spoken in the call interaction;

providing, by the word spotting module, the words to a behavioral models module;

computing, by the behavioral models module, a score for each of a plurality of behavioral metrics based at least in part on the words provided by the word spotting module;

providing, by the word spotting module, a phrase formed by the words to a knowledge article selection module;

providing, by the behavioral models module, each score for the plurality of behavioral metrics to the knowledge article selection module;

providing a plurality of knowledge selection rules to the knowledge article selection module, wherein each knowledge selection rule is associated with a knowledge article;

evaluating, by the knowledge article selection module, a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules;

matching, by the knowledge article selection module, a knowledge selection rule to the combination based on the evaluation;

selecting, by the knowledge article selection module, a knowledge article associated with the matched knowledge selection rule;

generating, by a knowledge article presentation module, a visual representation of the selected knowledge article; and

presenting in real-time, by the knowledge article presentation module to the agent or an agent supervisor, the visual representation on a graphical user interface.

17. The non-transitory computer-readable medium of claim 16 , wherein the plurality of behavioral metrics comprise two or more of sentiment, active listening, empathy, demonstration of ownership, building rapport, setting expectations, effective questioning, promotion of self-service, speech velocity, or interruption.

18. The non-transitory computer-readable medium of claim 16 , wherein the operations further comprise identifying time locations in the call interaction at which a spoken instance of a word occurred, and determining whether the agent or the customer spoke the word.

19. The non-transitory computer-readable medium of claim 16 , wherein the operations further comprise receiving the plurality of knowledge selection rules from a user.

20. The non-transitory computer-readable medium of claim 19 , wherein the operations further comprise:

receiving an updated plurality of knowledge selection rules from the user;

re-evaluating, by the knowledge article selection module, the combination of the phrase and the scores of the plurality of behavioral metrics against each of the updated plurality of knowledge selection rules;

re-matching, by the knowledge article selection module, an updated knowledge selection rule to the combination based on the evaluation; and

re-selecting, by the knowledge article selection module, a knowledge article associated with the updated matched knowledge selection rule.

Assignments (2)
SECURITY INTEREST Recorded Feb 26, 2026
From: NICE LTD; NICE SYSTEMS INC.; NICE SYSTEMS TECHNOLOGIES INC.; INCONTACT, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 074986/0208 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 28, 2021
From: EDWARDS, GORDON SCOTT; ARROWOOD, JON A.; FINLAY, MARK
To: NICE LTD.
Reel/Frame 056999/0249 →