Google Inc.

Roblox Corporation

Effie Goenawan

Austin Chang

David Robert Black

Abraham Lee

Arvind Sivaram Sharma

James Stephen Higgins

Shyna Khurana

Brandon Kang

Eliza Jacobs

Alexey Goloshubin

Sophie Finck

Yiming Hu

Alex Trimm

Hitesh Chhabra

A metaverse application generates a first abuse score for the audio stream associated with a first user based on rules that analyze user signals, wherein the user signals include one or more selected from the group of one or more second users muting the first user, a history of past moderation actions associated with the first user, one or more third users blocking the first user, and combinations thereof. The metaverse application includes an audio-classifier model that obtains a second abuse score for an audio stream associated with the first user, wherein the audio stream is provided as input to the audio-classifier model. The metaverse application determines that the first user is committing abuse based on one or more selected from the group of the first abuse score, the second abuse score, and combinations thereof exceeding a threshold score value. Responsive to determining that the first user is committing abuse, the metaverse application performs a remedial action.

Using moderation by proxy to identify abuse in audio streams

Methods and apparatus for detecting hazardous vehicle events and encouraging usage of driving optimized application features to mitigate occurrence of the hazardous vehicle events. The driving optimized application features can address unsafe driving events that are determined to be correlated with certain distracting application features. For example, an application of a computing device can determine that a user is occupying a vehicle and is driving toward a destination. While driving, data available to the application can indicate that an unsafe driving event, such as a hard braking event, has occurred while the user was interacting with another application. Thereafter, and based on this data, the application can render an output characterizing the correlation between the hard braking event and the other application, and/or provide the user with an option to interact with the other application via driving optimized feature(s).

Adaptation(s) based on correlating hazardous vehicle events with application feature(s)

Implementations set forth herein relate to interactions, between vehicle computing devices and mobile computing devices, that reduce duplicative processes from occurring at either device. Reduction of such processes can be performed, in some instances, via communications between a vehicle computing device and a mobile computing device in order to determine, for example, how to uniquely render content at an interface of each respective computing device while the user is driving the vehicle. These communications can occur before a user has entered a vehicle, while the user is in the vehicle, and/or after a user has left the vehicle. For instance, just before a user enters a vehicle, a vehicle computing device can be primed for certain automated assistant interactions between the user and their mobile computing device. Alternatively, or additionally, the user can authorize the vehicle computing device to perform certain processes immediately after leaving the vehicle.

Automated assistant that detects and supplements various vehicle computing device capabilities

Growing community of inventors

San Francisco, CA, United States of America

Effie Goenawan