Auto-completion for gesture-input in assistant systems

Patent metadata

Field	Value
Publication number	US-10795703-B2
Application number	US-201916389708-A
Country	US
Kind code	B2
Filing date	Apr 19, 2019
Priority date	Apr 20, 2018
Publication date	Oct 6, 2020
Grant date	Oct 6, 2020

Abstract

In one embodiment, a method includes receiving a user input from a client system associated with a first user, wherein the user input comprises an incomplete gesture performed by the first user, calculating one or more confidence scores by an intent-understanding module for one or more intents corresponding to the incomplete gesture, determining the calculated confidence scores associated with each of the intents are below a threshold score, selecting candidate gestures from a plurality of pre-defined gestures based on a personalized gesture-recognition model responsive to determining that the calculated confidence scores for each of the intents are below the threshold score, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate gestures to the client system.

First claim

The invention claimed is:

1. A method comprising, by one or more computing systems:
receiving, from a client system associated with a first user, a user input detected by one or more cameras of the client system, wherein the user input comprises an incomplete gesture performed by one or more hands of the first user;
calculating, by an intent-understanding module, one or more confidence scores for one or more intents corresponding to the incomplete gesture;
determining that the calculated confidence scores associated with each of the intents are below a threshold score;
selecting, based on a personalized gesture-recognition model, one or more candidate gestures from a plurality of pre-defined gestures responsive to determining that the calculated confidence scores for each of the intents are below the threshold score, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture; and
sending, to the client system, instructions for presenting one or more suggested inputs corresponding to one or more of the candidate gestures.

2. The method of claim 1 , wherein the threshold score is based on a wake-up gesture performed by the first user.

3. The method of claim 1 , wherein calculating the one or more confidence scores for the one or more intents corresponding to the incomplete gesture is based on a velocity associated with the incomplete gesture.

4. The method of claim 1 , wherein calculating the one or more confidence scores for the one or more intents corresponding to the incomplete gesture is based on temporal information associated with the incomplete gesture, and wherein the temporal information comprises a pause in the user input.

5. The method of claim 1 , further comprising:
receiving, from the client system, a user-selected input from the first user, wherein the user-selected input comprises one of the suggested inputs; and
executing one or more tasks based on the user-selected input.

6. The method of claim 1 , wherein selecting the one or more candidate gestures is further based on the one or more intents.

7. The method of claim 1 , wherein each pre-defined gesture comprises one or more of pointing, poking, tapping, waving, or swiping.

8. The method of claim 1 , further comprising:
receiving, from the client system, a first user-selected input from the first user, wherein the first user-selected input comprises one of the suggested inputs, and wherein the first user-selected input is associated with a first intent;
generating, based on the first user-selected input, one or more additional candidate gestures, wherein each of the one or more additional candidate gestures is associated with the first intent;
sending, to the client system, instructions for presenting one or more additional suggested inputs corresponding to one or more of the additional candidate gestures;
receiving, from the client system, a second user-selected input from the first user, wherein the second user-selected input comprises one of the additional suggested inputs; and
executing one or more tasks based on the second user-selected input.

9. The method of claim 1 , further comprising:
calculating, for each of the one or more candidate gestures, a similarity level of the candidate gesture with respect to the incomplete gesture.

10. The method of claim 9 , wherein the similarly level of each candidate gesture with respect to the incomplete gesture is based on a trajectory of the incomplete gesture with respect to the client system.

11. The method of claim 9 , wherein the similarly level of each candidate gesture with respect to the incomplete gesture is based on an orientation of the incomplete gesture with respect to the client system.

12. The method of claim 9 , wherein the similarly level of each candidate gesture with respect to the incomplete gesture is based on an object associated with the incomplete gesture.

13. The method of claim 9 , wherein the similarly level of each candidate gesture with respect to the incomplete gesture is based on contextual information associated with the incomplete gesture.

14. The method of claim 9 , wherein the similarly level of each candidate gesture with respect to the incomplete gesture is based on a position of the incomplete gesture with respect to the client system.

15. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:
receive from a client system associated with a first user, a user input detected by one or more cameras of the client system, wherein the user input comprises an incomplete gesture performed by one or more hands of the first user;
calculate, by an intent-understanding module, one or more confidence scores for one or more intents corresponding to the incomplete gesture;
determine that the calculated confidence scores associated with each of the intents are below a threshold score;
select, based on a personalized gesture-recognition model, one or more candidate gestures from a plurality of pre-defined gestures responsive to determining that the calculated confidence scores for each of the intents are below the threshold score, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture; and
send, to the client system, instructions for presenting one or more suggested inputs corresponding to one or more of the candidate gestures.

16. The media of claim 15 , wherein the software is further operable when executed to:
calculate, for each of the one or more candidate gestures, a similarity level of the candidate gesture with respect to the incomplete gesture.

17. The media of claim 15 , wherein the similarly level of each candidate gesture with respect to the incomplete gesture is based on a trajectory of the incomplete gesture with respect to the client system.

18. The media of claim 15 , wherein the similarly level of each candidate gesture with respect to the incomplete gesture is based on an orientation of the incomplete gesture with respect to the client system.

19. The media of claim 15 , wherein the similarly level of each candidate gesture with respect to the incomplete gesture is based on an object associated with the incomplete gesture.

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:
receive from a client system associated with a first user, a user input detected by one or more cameras of the client system, wherein the user input comprises an incomplete gesture performed by one or more hands of the first user;
calculate, by an intent-understanding module, one or more confidence scores for one or more intents corresponding to the incomplete gesture;
determine that the calculated confidence scores associated with each of the intents are below a threshold score;
select, based on a personalized gesture-recognition model, one or more candidate gestures from a plurality of pre-defined gestures responsive to determining that the calculated confidence scores for each of the intents are below the threshold score, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture; and
send, to the client system, instructions f

Assignees

• Facebook Tech Llc

Inventors

• Presant William Crosby
• Penov Francislav P
• Kumar Anuj

Classifications

• G06F16/3329

  Natural language query formulation · CPC title

• G06F3/017

  Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883) · CPC title

• G06F3/011

  Arrangements for interaction with the human body, e.g. for user immersion in virtual reality (blind teaching G09B21/00) · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title