IP Library Granted Patent US 11,238,226
Granted Patent B2
US 11,238,226 · App. 16/192,245 · Granted Feb 1, 2022

System and method for accelerating user agent chats

Inventors: Paul Joseph Vozila (Arlington, MA); Peter Stubley (Beaconsfield, CA); Jean-Francois Beaumont (Verdun, CA); Ding Liu (Lexington, MA); William F. Ganong, III (Brookline, MA)
Assignee: NUANCE COMMUNICATIONS, INC.
G06F40/289G06F40/35H04L51/04
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Quick Facts
Patent No.
US 11,238,226
App. No.
16/192,245
Granted
Feb 1, 2022
Kind
B2
Abstract

A method, computer program product, and computer system for identifying, by a computing device, a model for predicting conversational phrases for a communication between at least a first user and a second user. The model may be trained based upon, at least in part, an attribute associated with the second user. At least one conversational phrase may be predicted for the communication between the first user and the second user. The at least one conversational phrase may be provided to the second user as an optional phrase to be sent to the first user.

Claims (35)

1. A computer-implemented method comprising:

identifying, by a computing device, a model for predicting conversational phrases for a communication between at least a first user and a second user;

training the model using long-short term memories (LSTMs) based upon, at least in part, an attribute associated with the second user;

predicting at least one conversational phrase for the communication between the first user and the second user based upon, at least in part, the model and the attribute associated with the second user, wherein the attribute includes a modification, by the second user, with a previously predicted conversational phrase provided to the second user, wherein the modification includes a deletion of one or more elements of the predicted at least one conversational phrase;

providing the at least one conversational phrase to both the first user based upon the LSTMs being updated with the modification and the modification being stored in a memory and the second user as an optional phrase before the second user has sent the at least one conversational phrase to the first user; and

sending at least one of the at least one conversational phrase and another conversational phrase to the first user based upon, at least in part, providing the at least one conversational phrase to both the first user and the second user as the optional phrase.

2. The computer-implemented method of claim 1 wherein the communication between the first user and the second user includes a real-time instant message.

3. The computer-implemented method of claim 1 wherein the attribute includes an enterprise associated with the second user.

4. The computer-implemented method of claim 1 wherein the attribute includes one or more characteristics associated with the second user.

5. The computer-implemented method of claim 1 wherein the attribute includes communication logs of one or more prior communications of the second user.

6. The computer-implemented method of claim 1 wherein predicting the at least one conversational phrase includes predicting at least one conversational phrase of the first user before the first user has sent the at least one conversational phrase to the second user.

7. The computer-implemented method of claim 1 wherein the attribute includes seniority of the second user.

8. A computer program product residing on a non-transitory computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising:

identifying, by a computing device, a model for predicting conversational phrases for a communication between at least a first user and a second user;

training the model using long-short term memories (LSTMs) based upon, at least in part, an attribute associated with the second user;

predicting at least one conversational phrase for the communication between the first user and the second user based upon, at least in part, the model and the attribute associated with the second user, wherein the attribute includes a modification, by the second user, with a previously predicted conversational phrase provided to the second user, wherein the modification includes a deletion of one or more elements of the predicted at least one conversational phrase;

providing the at least one conversational phrase to both the first user based upon the LSTMs being updated with the modification and the modification being stored in a memory and the second user as an optional phrase before the second user has sent the at least one conversational phrase to the first user; and

sending at least one of the at least one conversational phrase and another conversational phrase to the first user based upon, at least in part, providing the at least one conversational phrase to both the first user and the second user as the optional phrase.

9. The computer program product of claim 8 wherein the communication between the first user and the second user includes a real-time instant message.

10. The computer program product of claim 8 wherein the attribute includes an enterprise associated with the second user.

11. The computer program product of claim 8 wherein the attribute includes one or more characteristics associated with the second user.

12. The computer program product of claim 8 wherein the attribute includes communication logs of one or more prior communications of the second user.

13. The computer program product of claim 8 wherein predicting the at least one conversational phrase includes predicting at least one conversational phrase of the first user before the first user has sent the at least one conversational phrase to the second user.

14. The computer program product of claim 8 wherein the attribute includes seniority of the second user.

15. A computing system including one or more processors and one or more memories configured to perform operations comprising:

identifying, by a computing device, a model for predicting conversational phrases for a communication between at least a first user and a second user;

training the model using long-short term memories (LSTMs) based upon, at least in part, an attribute associated with the second user;

predicting at least one conversational phrase for the communication between the first user and the second user based upon, at least in part, the model and the attribute associated with the second user, wherein the attribute includes a modification, by the second user, with a previously predicted conversational phrase provided to the second user, wherein the modification includes a deletion of one or more elements of the predicted at least one conversational phrase;

providing the at least one conversational phrase to both the first user based upon the LSTMs being updated with the modification and the modification being stored in a memory and the second user as an optional phrase before the second user has sent the at least one conversational phrase to the first user; and

sending at least one of the at least one conversational phrase and another conversational phrase to the first user based upon, at least in part, providing the at least one conversational phrase to both the first user and the second user as the optional phrase.

16. The computing system of claim 15 wherein the communication between the first user and the second user includes a real-time instant message.

17. The computing system of claim 15 wherein the attribute includes an enterprise associated with the second user.

18. The computing system of claim 15 wherein the attribute includes at least one of one or more characteristics associated with the second user and communication logs of one or more prior communications of the second user.

19. The computing system of claim 15 wherein predicting the at least one conversational phrase includes predicting at least one conversational phrase of the first user before the first user has sent the at least one conversational phrase to the second user.

20. The computing system of claim 15 wherein the attribute includes seniority of the second user.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 9, 2023
From: NUANCE COMMUNICATIONS, INC.
To: MICROSOFT TECHNOLOGY LICENSING, LLC
Reel/Frame 065531/0665 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 15, 2018
From: VOZILA, PAUL JOSEPH; STUBLEY, PETER; BEAUMONT, JEAN-FRANCOIS; LIU, DING; GANONG, WILLIAM F., III
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 047517/0224 →