Modifying avatars in user interfaces based on wearable device data using machine learning
Some examples described herein relate to modifying avatars in user interfaces based on wearable device data using machine learning. For example, a system can receive, from a wearable device, a set of biological data with respect to a user wearing the wearable device. The user can be associated with an avatar of the user on a user interface. The system can provide the avatar of the user and the set of biological data as input to a trained machine-learning model. The trained machine-learning model can generate a modified avatar based on the input. The system can then receive the modified avatar as output from the trained machine-learning model. The system can modify the user interface to include the modified avatar. The modified avatar can be outputted for display on a client device.
1. A system comprising:
a processor; and
a memory including instructions that are executable by the processor for causing the processor to:
receive a set of biological data for a user from a wearable device worn by the user, the user being associated with an avatar of the user on a user interface;
provide the avatar of the user and the set of biological data as input to a trained machine-learning model, the trained machine-learning model being configured to generate a modified avatar based on the input by:
determining an emotional state of the user based on the set of biological data;
determining a color indicator that indicates the emotional state of the user based on the set of biological data; and
modifying the avatar to display the emotional state of the user;
receive the modified avatar and the color indicator as output from the trained machine-learning model;
modify the user interface to include the modified avatar and the color indicator; and
output the modified user interface for display on a client device.
2. The system of claim 1 , wherein the user interface is a digital communication user interface, and wherein the memory further comprises instructions that are executable by the processor for causing the processor to:
receive, from the user interacting with the digital communication user interface on the client device, a digital communication to be transmitted to another client device;
determine, based on the digital communication and the color indicator, a suggested modification to the digital communication; and
output the suggested modification for display on the digital communication user interface.
3. The system of claim 1 , wherein the set of biological data is a first set of biological data with respect to a first user wearing a first wearable device, wherein the avatar is a first avatar on a first user interface, and wherein the memory further comprises instructions that are executable by the processor for causing the processor to:
receive a second set of biological data for a second user from a second wearable device worn by the user, the second user being associated with a second avatar on a second user interface;
provide the first set of biological data, the first avatar, the second set of biological data, and the second avatar as input to the trained machine-learning model, the trained machine-learning model being configured to generate a composite avatar based on the input;
receive the composite avatar as output from the trained machine-learning model; and
modify the user interface to include the composite avatar.
4. The system of claim 3 , wherein the modified user interface is a video conference user interface, and wherein the composite avatar indicates a composite emotional state of the first user and the second user.
5. The system of claim 1 , wherein the memory further comprises instructions that are executable by the processor for causing the processor to:
generate the trained machine-learning model by training a machine-learning model using historical data, the historical data indicating emotional states of historical sets of biological data.
6. A method comprising:
receiving, by a processor, a set of biological data for a user from a wearable device worn by the user, the user being associated with an avatar of the user on a user interface;
providing, by the processor, the avatar of the user and the set of biological data as input to a trained machine-learning model, the trained machine-learning model being configured to generate a modified avatar based on the input by:
determining an emotional state of the user based on the set of biological data;
determining a color indicator that indicates the emotional state of the user based on the set of biological data; and
modifying the avatar to display the emotional state of the user;
receiving, by the processor, the modified avatar and the color indicator as output from the trained machine-learning model;
modifying, by the processor, the user interface to include the modified avatar and the color indicator; and
outputting, by the processor, the modified user interface for display on a client device.
7. The method of claim 6 , wherein the user interface is a digital communication user interface, and wherein the method further comprises:
receiving, from the user interacting with the digital communication user interface on the client device, a digital communication to be transmitted to another client device;
determining, based on the digital communication and the color indicator, a suggested modification to the digital communication; and
outputting the suggested modification for display on the digital communication user interface.
8. The method of claim 6 , wherein the set of biological data is a first set of biological data for a first user wearing a first wearable device, wherein the avatar is a first avatar on a first user interface, and wherein the method further comprises:
receiving a second set of biological data for a second user from a second wearable device worn by the user, the second user being associated with a second avatar on a second user interface;
providing the first set of biological data, the first avatar, the second set of biological data, and the second avatar as input to the trained machine-learning model, the trained machine-learning model being configured to generate a composite avatar based on the input;
receiving the composite avatar as output from the trained machine-learning model; and
modifying the user interface to include the composite avatar.
9. The method of claim 8 , wherein the modified user interface is a video conference user interface, and wherein the composite avatar indicates a composite emotional state of the first user and the second user.
10. The method of claim 6 , further comprising:
generating the trained machine-learning model by training a machine-learning model using historical data, the historical data indicating emotional states of historical sets of biological data.
11. A non-transitory computer-readable medium comprising program code that is executable by a processor for causing the processor to:
receive a set of biological data for a user from a wearable device worn by the user, the user being associated with an avatar of the user on a user interface;
provide the avatar of the user and the set of biological data as input to a trained machine-learning model, the trained machine-learning model being configured to generate a modified avatar based on the input by:
determining an emotional state of the user based on the set of biological data;
determining a color indicator that indicates the emotional state of the user based on the set of biological data; and
modifying the avatar to display the emotional state of the user;
receive the modified avatar and the color indicator as output from the trained machine-learning model;
modify the user interface to include the modified avatar and the color indicator; and
output the modified user interface for display on a client device.
12. The non-transitory computer-readable medium of claim 11 , wherein the user interface is a digital communication user interface, and wherein the program code is further executable by the processor for causing the processor to:
receive, from the user interacting with the digital communication user interface on the client device, a digital communication to be transmitted to another client device;
determine, based on the digital communication and the color indicator, a suggested modification to the digital communication; and
output the suggested modification for display on the digital communication user interface.
13. The non-transitory computer-readable medium of claim 11 , wherein the set of biological data is a first set of biological data with respect to a first user wearing a first wearable device, wherein the avatar is a first avatar on a first user interface, and wherein the program code is further executable by the processor for causing the processor to:
receive a second set of biological data for a second user from a second wearable device worn by the user, the second user being associated with a second avatar on a second user interface;
provide the first set of biological data, the first avatar, the second set of biological data, and the second avatar as input to the trained machine-learning model, the trained machine-learning model being configured to generate a composite avatar based on the input;
receive the composite avatar as output from the trained machine-learning model; and
modify the user interface to include the composite avatar.
14. The non-transitory computer-readable medium of claim 13 , wherein the modified user interface is a video conference user interface, and wherein the composite avatar indicates a composite emotional state of the first user and the second user.