Abstract: Techniques are described herein for assembling/evaluating automated assistant responses for privacy concerns. In various implementations, a free-form natural language input may be received from a first user and may include a request for information pertaining to a second user. Multiple data sources may be identified that are accessible by an automated assistant to retrieve data associated with the second user. The multiple data sources may collectively include sufficient data to formulate a natural language response to the request. Respective privacy scores associated with the multiple data sources may be used to determine an aggregate privacy score associated with responding to the request. The natural language response may then be output at a client device operated by the first user in response to a determination that the aggregate privacy score associated with the natural language response satisfies a privacy criterion established for the second user with respect to the first user.

Abstract: Automated assistant responses may be assembled and/or evaluated to address privacy concerns. In various implementations, a free-form natural language input may be received from a first user and may include a request for information pertaining to a second user. Multiple data sources may be identified that are accessible by an automated assistant to retrieve data associated with the second user. The multiple data sources may collectively include sufficient data to formulate a natural language response to the request. Respective privacy scores associated with the multiple data sources may be used to determine an aggregate privacy score associated with responding to the request. The natural language response may then be output at a client device operated by the first user in response to a determination that the aggregate privacy score associated with the natural language response satisfies a privacy criterion established for the second user with respect to the first user.

Abstract: When an online system creates a video exchange session where video content is presented to users participating in the video exchange session, the online system detects an error in video content received from a user, such as lag in the video content received from the user. In response to detecting the error in the video content from the user, the online system generates synthetic media from video content previously received from the user. The synthetic media synchronizes with audio included in the video content from the user and replaces at least a portion of the video content received from the user with the synthetic media. Other users participating in the video exchange receive the video content from the user replaced with the synthetic media to prevent the other users from noticing the error in the video content from the user.

Abstract: In one embodiment, an AR/VR system includes a social-networking application installed on the AR/VR system, which allows a user to access on online social network, including communicating with the user's social connections and interacting with content objects on the online social network. The AR/VR system also includes an AR/VR application, which allows the user to interact with an AR/VR platform by providing user input to the AR/VR application via various modalities. Based on the user input, the AR/VR platform generates responses and sends the generated responses to the AR/VR application, which then presents the responses to the user at the AR/VR system via various modalities.

Abstract: To provide context-aware audio navigation instructions, a server device obtains sets of audio navigation instructions previously provided to users along with sensor data descriptive of a context in which the audio navigation instructions were provided and an indication of whether a driver correctly responded to the audio navigation instructions. The server device trains a machine learning model using this data, where the machine learning model identifies audio navigation instruction parameters for a particular context. In response to a request for navigation directions, the server device receives sensor data from the client computing device generating the request that is indicative of the environment surrounding the client computing device. The server device then applies the sensor data and navigation instructions to the machine learning model to generate a set of audio navigation instructions responsive to the request.

Abstract: Techniques are described herein for assembling/evaluating automated assistant responses for privacy concerns. In various implementations, a free-form natural language input may be received from a first user and may include a request for information pertaining to a second user. Multiple data sources may be identified that are accessible by an automated assistant to retrieve data associated with the second user. The multiple data sources may collectively include sufficient data to formulate a natural language response to the request. Respective privacy scores associated with the multiple data sources may be used to determine an aggregate privacy score associated with responding to the request. The natural language response may then be output at a client device operated by the first user in response to a determination that the aggregate privacy score associated with the natural language response satisfies a privacy criterion established for the second user with respect to the first user.

Abstract: An automated messaging reply-to system can automatically select which message a potential reply message is replying to. The automated messaging reply-to system can obtain a message thread, a potential reply message, and a context. The automated messaging reply-to system can filter the message thread and generate model inputs based on the remaining messages, the potential reply message, and the context. The automated messaging reply-to system can apply the model input to a machine learning model, which can generate reply scores for the remaining messages. After generating reply scores, the automated messaging reply-to system can determine whether the remaining message with the highest reply score qualifies as an originating message being replied to. The automated messaging reply-to system can cause display of the potential reply message as a reply-to for the determined originating message.

Abstract: Systems, methods, and non-transitory computer-readable media can be configured to determine first audio associated with a first user and second audio associated with a second user, the first user and the second user associated with a communication session. The second audio can be muted based on a determination that the first audio and the second audio overlap. The second audio can be provided based on completion of the first audio.

Abstract: To provide context-aware audio navigation instructions, a server device obtains sets of audio navigation instructions previously provided to users along with sensor data descriptive of a context in which the audio navigation instructions were provided and an indication of whether a driver correctly responded to the audio navigation instructions. The server device trains a machine learning model using this data, where the machine learning model identifies audio navigation instruction parameters for a particular context. In response to a request for navigation directions, the server device receives sensor data from the client computing device generating the request that is indicative of the environment surrounding the client computing device. The server device then applies the sensor data and navigation instructions to the machine learning model to generate a set of audio navigation instructions responsive to the request.

Abstract: Techniques are described herein for assembling/evaluating automated assistant responses for privacy concerns. In various implementations, a free-form natural language input may be received from a first user and may include a request for information pertaining to a second user. Multiple data sources may be identified that are accessible by an automated assistant to retrieve data associated with the second user. The multiple data sources may collectively include sufficient data to formulate a natural language response to the request. Respective privacy scores associated with the multiple data sources may be used to determine an aggregate privacy score associated with responding to the request. The natural language response may then be output at a client device operated by the first user in response to a determination that the aggregate privacy score associated with the natural language response satisfies a privacy criterion established for the second user with respect to the first user.

Abstract: An online system receives, from a client device of a user participating an online meeting, a request to share content with another user participating the online meeting. The online system identifies content items from applications running on the client device. For each identified content item, the online system determines, e.g., by using a trained model or instructing the client device to use the trained model, a sharing score that indicates a likelihood that the user would select the content item to share with the other user. Candidate content items are selected form the identified content items based on the sharing scores. The candidate content items are provided for display to the user in a user interface running on the client device. The user interface allows the user to select one of the candidate content items to share with the other user.

Abstract: Automated assistant responses may be assembled and/or evaluated to address privacy concerns. In various implementations, a free-form natural language input may be received from a first user and may include a request for information pertaining to a second user. Multiple data sources may be identified that are accessible by an automated assistant to retrieve data associated with the second user. The multiple data sources may collectively include sufficient data to formulate a natural language response to the request. Respective privacy scores associated with the multiple data sources may be used to determine an aggregate privacy score associated with responding to the request. The natural language response may then be output at a client device operated by the first user in response to a determination that the aggregate privacy score associated with the natural language response satisfies a privacy criterion established for the second user with respect to the first user.

Abstract: Aspects of the disclosed technology can determine when a user has made a gesture mapped to an effect and can display the effect on the video. Additional aspects of the disclosed technology can automatically match movements between a source video and a live feed of a user. Yet further aspects of the disclosed technology can customize a video based on a determined focus of the video creator.

Abstract: Systems, methods, and non-transitory computer-readable media can be configured to determine an issue associated with a media broadcast during the media broadcast. A copy of a portion of the media broadcast associated with the issue can be stored. A stored media broadcast associated with the media broadcast can be repaired based on the copy of the portion of the media broadcast.

Abstract: In one embodiment, a method includes initiating a real-time multimedia communication session with one or more other communication devices, detecting that an audio input level for an audio sample is lower than a threshold level based on sensor data from an audio sensor associated with the communication device, triggering a silence-detection timer, and entering, upon an expiration of the silence-detection timer, into a silence mode. Another method includes displaying one or more applications to a user, determining a context in which the user is interacting with the one or more applications and determining, based on the context, that the user intends to retrieve at least one message of the plurality of messages while the user is interacting with the one or more applications, generating a confidence score for each of the plurality of messages based on the user intent to retrieve the at least one message.

Abstract: Automated assistant responses may be assembled and/or evaluated to address privacy concerns. A free-form natural language input may be received from a first user and may include a request for information pertaining to a second user. Multiple data sources may be identified that are accessible by an automated assistant to retrieve data associated with the second user. The multiple data sources may collectively include sufficient data to formulate a natural language response to the request. Respective privacy scores associated with the multiple data sources may be used to determine an aggregate privacy score associated with responding to the request. The natural language response may then be output at a client device operated by the first user in response to a determination that the aggregate privacy score associated with the natural language response satisfies a privacy criterion established for the second user with respect to the first user.

Abstract: Systems, methods, and non-transitory computer-readable media can determine context information associated with a media content item accessible to a user. One or more segments of the media content item can be determined. At least one segment of the media content item to be provided for presentation and a playback speed for the at least one segment can be determined based at least in part on a machine learning model that evaluates the context information and the one or more segments.

Abstract: Systems, apparatuses and methods may provide technology that identifies categories that are related to subject matter content of a plurality of videos and associated with different categorization signals. The technology categorizes a first video among the plurality of videos as being within a first category of the categories based on the different categorization signals, segments the first video into segments based on the categorization of the first video as being within the first category, and identifies engagement signals associated with the first video, where the engagement signals are associated with actions of viewers that viewed the first video. The technology further conducts an analysis of the segments based on the engagement signals and automatically generates a final video that includes one or more of the segments and omits at least one segment of the segments based on the analysis.

Abstract: Systems, methods, and non-transitory computer-readable media can be configured to obtain source audio based on recorded audio. A tuned audio transform can be generated based on a source audio transform corresponding to the source audio and a recorded audio transform corresponding to the recorded audio. Tuned audio can be generated based on the tuned audio transform.

Abstract: An automated messaging reply-to system can automatically select which message a potential reply message is replying to. The automated messaging reply-to system can obtain a message thread, a potential reply message, and a context. The automated messaging reply-to system can filter the message thread and generate model inputs based on the remaining messages, the potential reply message, and the context. The automated messaging reply-to system can apply the model input to a machine learning model, which can generate reply scores for the remaining messages. After generating reply scores, the automated messaging reply-to system can determine whether the remaining message with the highest reply score qualifies as an originating message being replied to. The automated messaging reply-to system can cause display of the potential reply message as a reply-to for the determined originating message.