IP Library Granted Patent US 11,443,120
Granted Patent B2
US 11,443,120 · App. 17/006,377 · Granted Sep 13, 2022

Multimodal entity and coreference resolution for assistant systems

Inventors: Shivani Poddar (Mountain View, CA); Seungwhan Moon (Seattle, WA); Paul Anthony Crook (Newcastle, WA); Rajen Subba (San Carlos, CA)
Assignee: Meta Platforms, Inc.
G06F40/30G06F3/011G06F3/013G06F9/485G06F9/4881G06F9/547G06F16/90332G06F16/9536G06F40/205G06F40/242G06F40/253G06N3/0454G06N3/0472G06N3/08G06N20/00G06Q50/01G06V10/255G06V20/20G06V20/30G06V20/41G06V40/174G10L15/08G10L15/1815G10L15/1822G10L15/22G10L15/30G10L15/32H04L51/12H04L51/32H04L67/306H04L67/36H04N7/147G06F3/017G06F3/167G06V2201/10G10L2015/088G10L2015/223G10L2015/227
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Quick Facts
Patent No.
US 11,443,120
App. No.
17/006,377
Granted
Sep 13, 2022
Kind
B2
Abstract

In one embodiment, a method includes accessing visual data from a client system associated with a user, wherein the visual data comprises images portraying one or more objects, receiving, from the client system, a user request, wherein the user request comprises a coreference to a target object, resolving the coreference to the target object from among the one or more objects, resolving the target object to a specific entity, and sending, to the client system, instructions for providing a response to the user request, wherein the response comprises attribute information about the specific entity.

Claims (61)

1. A method comprising:

accessing visual data from a client system associated with a user, wherein the visual data comprises images portraying one or more objects;

receiving, from the client system, a user request, wherein the user request comprises a coreference to a target object;

resolving the coreference to the target object from among the one or more objects;

resolving the target object to a specific entity; and

sending, to the client system, instructions for providing a response to the user request, wherein the response comprises attribute information about the specific entity.

2. The method of claim 1 , further comprising:

analyzing, by a computer vision module, the visual data to identify the one or more objects portrayed in the images;

parsing, by a natural-language understanding (NLU) module, the user request to identify an intent of the user request and references to one or more of the objects; and

updating a dialog state to include the identified objects and the identified references.

3. The method of claim 2 , further comprising:

receiving gesture or gaze information from the user; and

updating the dialog state to include the received gesture or gaze information.

4. The method of claim 2 , wherein resolving the coreference to the target object from among the one or more objects comprises combining additional information with the dialog state.

5. The method of claim 4 , wherein the additional information comprises a level of interestingness of one or more of the objects.

6. The method of claim 4 , wherein the additional information comprises information of a user profile of the user.

7. The method of claim 4 , wherein the additional information comprises a model of past interactions with one or more of the objects by other users.

8. The method of claim 1 , further comprising:

analyzing the visual data to identify the one or more objects portrayed in the images;

assigning respective object identifiers to one or more of the identified objects; and

storing one or more of the object identifiers as entities in a dialog state tracker.

9. The method of claim 8 , wherein resolving the coreference to the target object from among the one or more objects comprises:

analyzing the dialog state tracker to identify one or more of the entities; and

identifying a result set of one or more of the identified entities based on a context of the user.

10. The method of claim 9 , wherein resolving the target object to a specific entity comprises:

selecting the specific entity from among the identified entities of the result set.

11. The method of claim 8 , further comprising:

in response to receiving the user request, generating, by a scene understanding engine, relational information between identified objects.

12. The method of claim 1 , further comprising:

accessing a knowledge graph; and

retrieving the attribute information about the specific entity from the knowledge graph.

13. The method of claim 1 , wherein one or more of the objects of the visual data are virtual objects in a virtual reality environment displayed to the user via the client system.

14. The method of claim 1 , further comprising:

receiving, from the client system, a second user request to perform a task with respect to the specific entity;

executing the task; and

sending, the client system, instructions for providing a second response to the user comprising results of the executed task.

15. The method of claim 1 , wherein resolving the coreference to the target object from among the one or more objects comprises:

analyzing, by a scene understanding engine, the visual data to identify the one or more objects portrayed in the images; and

identifying the target object from among the identified objects based on its position within a field of view of the visual data.

16. The method of claim 1 , wherein resolving the coreference to the target object from among the one or more objects comprises:

sending, to the client system, a prompt for the user to confirm the target object; and

receiving, from the client system, a user response to the prompt identifying the target object.

17. The method of claim 1 , further comprising:

accessing a set of images from the visual data; and

selecting one or more images from among the set of images based on a timing of the user request, wherein the selected images portray the target object.

18. The method of claim 1 , further comprising:

accessing a memory graph associated with the user to retrieve context data associated with the user; and

comparing the attribute information about the specific entity with the context data,

wherein the response further comprises a result of the comparison.

19. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

access visual data from a client system associated with a user, wherein the visual data comprises images portraying one or more objects;

receive, from the client system, a user request, wherein the user request comprises a coreference to a target object;

resolve the coreference to the target object from among the one or more objects;

resolve the target object to a specific entity; and

send, to the client system, instructions for providing a response to the user request, wherein the response comprises attribute information about the specific entity.

20. A system comprising: one or more processors; and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to:

access visual data from a client system associated with a user, wherein the visual data comprises images portraying one or more objects;

receive, from the client system, a user request, wherein the user request comprises a coreference to a target object;

resolve the coreference to the target object from among the one or more objects;

resolve the target object to a specific entity; and

send, to the client system, instructions for providing a response to the user request, wherein the response comprises attribute information about the specific entity.

Assignments (2)
CHANGE OF NAME Recorded Dec 20, 2021
From: FACEBOOK, INC.
To: META PLATFORMS, INC.
Reel/Frame 058553/0802 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 29, 2020
From: PODDAR, SHIVANI; MOON, SEUNGWHAN; CROOK, PAUL ANTHONY; SUBBA, RAJEN
To: FACEBOOK, INC.
Reel/Frame 054210/0451 →