IP Library Granted Patent US 11,367,029
Granted Patent B2
US 11,367,029 · App. 16/802,538 · Granted Jun 21, 2022

System and method for adaptive skill level assignments

Inventors: James Murison (Markham, CA); Johnson Tse (Markham, CA); Gaurav Mehrotra (Toronto, CA); Anthony Lam (Richmond Hill, CA)
G06Q10/063112G06N3/08G10L15/04G10L15/16G10L15/1815G10L15/22G10L2015/088G10L2015/223
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Quick Facts
Patent No.
US 11,367,029
App. No.
16/802,538
Granted
Jun 21, 2022
Kind
B2
Abstract

A system and method are presented for adaptive skill level assignments of agents in contact center environments. A client and a service collaborate to automatically determine the effectiveness of an agent handling an interaction that has been routed using skills-based routing. Evaluation operations may be performed including emotion detection, transcription of audio to text, keyword analysis, and sentiment analysis. The results of the evaluation are aggregated with other information such as the interaction's duration, agent skills and agent skill levels, and call requirement skills and skill levels, to update the agent's profile which is then used for subsequent routing operations.

Claims (44)

1. A method for automatically adjusting skill level assignments of agents in a contact center environment comprising the steps of:

obtaining a plurality of recordings corresponding to a plurality of interactions corresponding to an agent of the contact center environment from a recording system associated with the contact center environment;

invoking a client, by the recording system, and providing metadata describing each of the plurality of interactions to the client, the client comprising a software component that is deployed within the contact center environment;

invoking, by the client, a service for evaluation of handling of an interaction by the agent, wherein the client provides the metadata to the service;

performing, by the service, a number of evaluation operations on the audio of each of the plurality of recordings, wherein the number of evaluation operations comprise:

emotion detection;

segmentation of the audio into a plurality of segments;

speech recognition of each of the plurality of segments;

keyword recognition on each of the plurality of segments; and

sentiment analysis;

providing the results of the evaluation operations, the metadata, and an interaction duration to a neural network where the neural network determines effectiveness of the agent on handling each of the plurality of interactions; and

updating the skill level assignments of the agent based on the effectiveness determination.

2. The method of claim 1 , wherein the metadata comprises at least one of: an interaction identifier, the interaction duration, participants to the interaction, agent skills, skill level requirements, and interaction segments.

3. The method of claim 1 , wherein the audio comprises two channels.

4. The method of claim 3 , wherein the two channels are comprised of one channel containing a customer audio and one channel comprising an agent audio.

5. The method of claim 1 , wherein the emotion detection determines the emotion experienced by a customer and the emotion experienced by the agent during the progress of an interaction.

6. The method of claim 1 , wherein the segments are a defined interval of time in length.

7. The method of claim 1 , wherein the sentiment analysis analyzes the agent and a customer during interaction progression.

8. The method of claim 1 , wherein the effectiveness comprises comparing the agent against other interactions with similar skill requirements and other agents with similar skill levels and skills.

9. The method of claim 1 , wherein the updating comprises incrementing a skill level of the agent.

10. The method of claim 1 , wherein the updating comprises decrementing a skill level of the agent.

11. The method of claim 1 , wherein the updating comprises leaving a skill level at an existing value.

12. A system for automatically adjusting skill level assignments of agents in a contact center environment comprising:

a processor; and

a memory in communication with the processor, the memory storing instructions that, when executed by the processor, causes the processor to:

obtain a plurality of recordings corresponding to a plurality of interactions corresponding to an agent of the contact center environment from a recording system associated with the contact center environment;

invoke a client and providing metadata describing each of the plurality of interactions to the client, the client comprising a software component that is deployed within the contact center environment;

invoke a service for evaluation of handling of an interaction by the agent, wherein the client provides the metadata to the service;

perform a number of evaluation operations on the audio of each of the plurality of recordings, wherein the number of evaluation operations comprise:

emotion detection;

segmentation of the audio into a plurality of segments;

speech recognition of each of the plurality of segments;

keyword recognition on each of the plurality of segments; and

sentiment analysis;

provide the results of the evaluation operations, the metadata, and an interaction duration to a neural network where the neural network determines effectiveness of the agent on handling each of the plurality of interactions; and

update the skill level assignments of the agent based on the effectiveness determination.

13. The system of claim 12 , wherein the metadata comprises at least one of: an interaction identifier, the interaction duration, participants to the interaction, agent skills, skill level requirements, and interaction segments.

14. The system of claim 12 , wherein the audio comprises two channels, which are comprised of a customer audio channel and an agent audio channel.

15. The system of claim 12 , wherein the emotion detection determines the emotion experienced by a customer and the emotion experienced by the agent during the progress of an interaction.

16. The system of claim 12 , wherein the sentiment analysis analyzes the agent and a customer during interaction progression.

17. The system of claim 12 , wherein the effectiveness comprises comparing the agent against other interactions with similar skill requirements and other agents with similar skill levels and skills.

18. The system of claim 12 , wherein the updating comprises incrementing a skill level of the agent.

19. The system of claim 12 , wherein the updating comprises decrementing a skill level of the agent.

20. The system of claim 12 , wherein the updating comprises leaving a skill level at an existing value.

Assignments (3)
CHANGE OF NAME Recorded May 13, 2024
From: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.
To: GENESYS CLOUD SERVICES, INC.
Reel/Frame 067391/0081 →
SECURITY AGREEMENT Recorded May 6, 2020
From: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.
To: BANK OF AMERICA, N.A.
Reel/Frame 052585/0243 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 27, 2020
From: MURISON, JAMES; TSE, JOHNSON; MEHROTRA, GAURAV; LAM, ANTHONY
To: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.
Reel/Frame 052028/0213 →
Continuity (2)
Provisional Application 62811182 · Feb 27, 2019
Related Publication 20200272976A1 · Aug 27, 2020
Cited By (1)
US 12,675,761