IP Library Granted Patent US 11,356,558
Granted Patent B2
US 11,356,558 · App. 17/559,098 · Granted Jun 7, 2022

Systems and methods for dynamically controlling conversations and workflows based on multi-modal conversation monitoring

Inventors: Howard A. Brown (Los Angeles, CA); Jeffrey K. Shelton (Los Angeles, CA); Jason Ouellette (San Francisco, CA); Kanwar Saluja (Los Angeles, CA)
Assignee: Revenue, Inc.
H04M3/5175G06Q30/0281H04M3/5183G06N20/00
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,356,558
App. No.
17/559,098
Granted
Jun 7, 2022
Kind
B2
Abstract

A conversation system may dynamically control a conversation or workflow by performing multi-modal conversation monitoring, generating actions that control the conversation based on the multi-modal monitoring producing conversation elements that deviate from patterns of a selected plan for that conversation, and/or by dynamically generating and/or updating the plan for future conversations based on the pattern recognition. For instance, the conversation system may detect a pattern within completed conversations that resulted in a common outcome, may monitor an active conversation between at least an agent and a participant, may extract different sets of conversation elements from different points in the active conversation, may determine that a particular set of conversation elements deviates from the pattern, and may modify the active conversation by performing one or more actions based on the particular set of conversation elements that deviate from the pattern.

Claims (74)

1. A method comprising:

tracking, with a conversation system, a plurality of elements from each of a plurality of conferences;

classifying, with the conversation system, outcomes of the plurality of conferences based on the plurality of elements tracked for each conference of the plurality of conferences, wherein said classifying comprises classifying a first set of the plurality of conferences with a first outcome and a second set of the plurality of conferences with a second outcome;

generating, by the conversation system, an outcome model based on a set of elements that are present in the plurality of elements of at least a first threshold number of the first set of conferences and that are not present in the plurality of elements of at least a second threshold number of the second set of conferences; and

controlling, by the conversation system, a conference between two or more participants based on the outcome model.

2. The method of claim 1 further comprising:

defining a plan comprising one or more actions based on the outcome model; and

wherein controlling the conference comprises presenting different actions from the plan to at least one of the two or more participants at different times during the conference.

3. The method of claim 1 further comprising:

determining a first set of attributes for a first set of participants involved in the first set of conferences, and a second set of attributes for a second set of participants involved in the first set of conferences;

determining a first set of actions performed in the first set of conferences involving the first set of participants that resulted in the set of elements, and a second set of actions performed in the first set of conference involving the second set of participants that resulted in the set of elements;

matching attributes of the two or more participants in the conference to the second set of attributes; and

wherein controlling the conference comprises implementing the second set of actions instead of the first set of actions at different times during the conference in response to said matching.

4. The method of claim 1 , wherein controlling the conference comprises:

extracting elements from different points in the conference; and

performing an action that modifies an audio or video interface of at least one of the two or more participants in response to one or more elements extracted from the conference deviating from the set of elements of the outcome model.

5. The method of claim 1 further comprising:

extracting elements from different points in the conference;

tracking state of the conference based on a comparison of the elements from the different points in the conference to the set of elements from the outcome model; and

wherein controlling the conference comprises implementing an action based on one or more elements at a specific point in the conference differing from one or more elements of the set of elements.

6. The method of claim 1 , wherein generating the outcome model comprises:

calculating a probability that the set of elements affected the first outcome for the first set of conferences; and

determining that the probability is greater than a threshold probability.

7. The method of claim 1 , wherein controlling the conference comprises:

generating a plan to control actions of at least one of the two or more participants during the conference; and

modifying the plan at different times during the conference based on states of the conference deviating from the plan at the different times.

8. The method of claim 1 further comprising:

monitoring elements of the conference;

comparing the elements of the conference to the set of elements from the outcome model; and

predicting an outcome classification for the conference based on said comparing.

9. The method of claim 8 , wherein controlling the conference comprises:

inducing a change in the conference in response to the outcome classification for the conference differing from the first outcome.

10. The method of claim 1 , wherein generating the outcome model comprises:

modeling different probabilities of the set of elements producing each of the outcomes based on a presence or absence of the set of elements in the plurality of elements from the plurality of conferences.

11. The method of claim 1 , wherein generating the outcome model comprises:

performing pattern recognition across the plurality of elements of the plurality of conferences; and

detecting the set of elements as common elements for a conference of the first outcome.

12. The method of claim 1 , wherein generating the outcome model comprises:

modeling probabilities for an association between different sets of the plurality of elements and each outcome of a plurality of outcomes;

determining that the probabilities associated with the set of elements and the first outcome is greater than the probabilities associated with other sets of elements and the first outcome; and

determining a sequence of actions that caused the set of elements in the first set of conferences.

13. The method of claim 12 , wherein determining the sequence of actions comprises:

analyzing the first set of conferences; and

identifying each action of the sequence of actions that precede one or more elements of the set of elements.

14. The method of claim 12 , wherein determining the sequence of actions comprises:

identifying one or more elements occurring in the first set of conferences before each element of the set of elements; and

defining a plan for at least one participant of the two or more participants to repeat each of the one or more elements during the conference.

15. The method of claim 1 further comprising:

determining a first set of attributes associated with one or more participants engaged in the first set of conferences;

linking the outcome model to the first set of attributes; and

selecting the outcome model, from a plurality of different outcome models, for the conference based on a second set of attributes associated with the two or more participants of the conference matching the first set of attributes linked to the outcome model.

16. The method of claim 1 , wherein generating the outcome model comprises:

determining attributes associated with participants engaged in the first set of conferences; and

adjusting the set of elements of the outcome model based on the attributes associated with the participants engaged in the first set of conferences, wherein adjusting the set of elements comprises modifying a weight attributed to one or more of the set of elements based on the attributes associated with the participants.

17. The method of claim 1 , wherein generating the outcome model comprises:

generating a different behavioral model for each of a plurality of different agents involved in one or more of the first set of conferences based on an effectiveness of each agent reaching a desired outcome with respect to a particular topic in the first set of conferences; and

assigning a particular agent from the plurality of different agents as one of the two or more participants of the conference based on the conference being associated with the particular topic and the behavioral model of the particular agent indicating a greater effectiveness in reaching the desired outcome with respect to the particular topic than the behavioral model of other agents from the plurality of agents.

18. The method of claim 1 ,

wherein generating the outcome model comprises:

generating a different behavioral model for each participant involved in one or more of the first set of conferences based on reactions of each participant to different subsets of elements from the first set of conferences; and

selecting a particular behavioral model for the conference based on the particular behavioral model being generated for a particular participant in one or more of the first set of conferences and the two or more participants of the conference having attributes in common with the particular participant; and

wherein controlling the conference comprises:

providing subject matter for discussion at different times during the conference based on the particular behavioral model.

19. A conversation system comprising:

one or more processors configured to:

track a plurality of elements from each of a plurality of conferences monitored by the conversation system;

classify outcomes of the plurality of conferences based on the plurality of elements tracked for each conference of the plurality of conferences, wherein said classifying comprises classifying a first set of the plurality of conferences with a first outcome and a second set of the plurality of conferences with a second outcome;

generate an outcome model based on a set of elements that are present in the plurality of elements of at least a first threshold number of the first set of conferences and that are not present in the plurality of elements of at least a second threshold number of the second set of conferences; and

control a conference between two or more participants based on the outcome model via a connection between the conversation system and the conference.

20. A non-transitory computer-readable medium of a conversation system, storing a plurality of processor-executable instructions to:

track, with the conversation system, a plurality of elements from each of a plurality of conferences;

classify, with the conversation system, outcomes of the plurality of conferences based on the plurality of elements tracked for each conference of the plurality of conferences, wherein said classifying comprises classifying a first set of the plurality of conferences with a first outcome and a second set of the plurality of conferences with a second outcome;

generate, by the conversation system, an outcome model based on a set of elements that are present in the plurality of elements of at least a first threshold number of the first set of conferences and that are not present in the plurality of elements of at least a second threshold number of the second set of conferences; and

control, by the conversation system, a conference between two or more participants based on the outcome model.

Assignments (3)
SECURITY INTEREST Recorded Feb 6, 2024
From: REVENUE, INC.
To: STIFEL BANK
Reel/Frame 066397/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 22, 2021
From: BROWN, HOWARD A.; SHELTON, JEFFREY K.; OUELLETTE, JASON; SALUJA, KANWAR
To: RINGDNA, INC.
Reel/Frame 058459/0580 →
CHANGE OF NAME Recorded Dec 22, 2021
From: RINGDNA, INC.
To: REVENUE, INC.
Reel/Frame 058564/0407 →
Continuity (5)
Continuation 17313635 · May 6, 2021
Continuation In Part 16998316 · Aug 20, 2020
Continuation 16587680 · Sep 30, 2019
Continuation 16429321 · Jun 3, 2019
Related Publication 20220116500A1 · Apr 14, 2022