Abstract: A participant computing device connected to a teleconferencing session receives mixed audio data from a teleconference computing system orchestrating the session. The mixed audio data comprises a mix of audio captured by other devices connected to the session. The mixed audio and audio captured by the other devices prior to receipt of the mixed audio data are compared to determine that the participant computing device is co-located with at least one of the other devices. Information indicating that some of the other devices are featured devices that most actively contribute to the mixed audio is obtained. Co-location information for each of the featured devices is received. The co-location information is indicative of whether a featured device is co-located with the participant computing device. Based on the co-location information, a determination is made that one of the featured devices is co-located with the participant computing device.

Abstract: Techniques of introducing virtual objects into a physical environment of AR system include displacing vertices of a mesh representing the physical environment based on a live depth map. For example, an AR system generates a mesh template, i.e., an initial mesh with vertices that represents a physical environment and a depth map that indicates a geometry of real objects within the physical environment. The AR system is configured to represent the real objects in the physical environment by displacing the vertices of the mesh based on depth values of the depth map and parameter values of a pinhole camera model. The depth values may be taken from the perspective of an illumination source in the physical environment.

Abstract: Systems and methods for generating a bias lighting effect are provided. A computer-implemented method can include obtaining a video comprising a plurality of video frames. For each of one or more video frames of the plurality of video frames, the method can include sampling an edge portion of the video frame. The edge portion can include a portion of the video frame adjacent to an edge of the video frame. The method can further include generating a bias lighting effect for the video frame. Generating the bias lighting effect can include inverting the edge portion across the edge and blurring the edge portion. The method can further include displaying the video frame concurrently with the bias lighting effect for the video frame. The bias lighting effect can be displayed adjacent to the edge of the video frame.

Abstract: Implementations are directed to determining an audio delay, of a computing device, by causing an audio data stream to be transmitted to the computing device via a wireless communication channel. The computing device causes audio output generated using the audio data stream to be rendered via speaker(s). The rendered audio output is captured via microphone(s), and the audio delay determined by comparing the captured audio output with the audio data stream. A delay audio segment can be appended to an additional audio data stream transmitted to the computing device, where the length of the delay audio segment is determined using the audio delay. A noise reduction technique can additionally or alternatively be adapted based on the audio delay. Implementations are additionally or alternatively directed to determining if an audio data stream transmitted to a computing device for rendering through speaker(s) driven by the computing device—is actually being rendered.

Abstract: A computing system can include one or more machine-learned models configured to receive context data that describes one or more entities to be named. In response to receipt of the context data, the machine-learned model(s) can generate output data that describes one or more names for the entity or entities described by the context data. The computing system can be configured to perform operations including inputting the context data into the machine-learned model(s). The operations can include receiving, as an output of the machine-learned model(s), the output data that describes the name(s) for the entity or entities described by the context data. The operations can include storing at least one name described by the output data.

Abstract: The present disclosure provides methods, systems, and devices for projecting user-generated media content into three-dimensional immersive views. A system can obtain a three-dimensional representation of a location generated based on a plurality of images. The system can access user-generated media content associated with the location. The system can receive path information representing a path through the three-dimensional representation of the location. The system can select one or more pieces of user-generated media content based on the path information. The system can integrate the one or more pieces of user-generated media content into the three-dimensional representation of the location based on the path information and a portion of the three-dimensional representation to be displayed to a user, wherein the pieces of user-generated media content are presented within visual pop-outs in the three-dimensional representation.

Abstract: A computer-implemented method is described. The method includes a computing system receiving a first voice input from a user for generating a bookmark. Responsive to receiving the voice input, the computing system obtains a resource identifier associated with a resource page. The method includes the computing system storing the resource identifier as a bookmark in a bookmark index that is accessible in response to a request from a user device. The method further includes the computing system using the resource identifier, stored as the bookmark, to access the resource page. The computing system uses the resource identifier to access the resource page based on the request from the user device. The request is generated by the user device in response to the user device receiving a second voice input from the user.

Abstract: The technology makes wireless roaming decisions for a computing device. The device is configured to determine whether to consider roaming and to generate a roam reason. The device determines a quality score for at least one access point within a wireless communication range of the device based at least in part on the roam reason. A target access point with a highest quality score is selected. The device may then determine to roam to the target access point, if the target access point is not the current access point to which the device is connected.

Abstract: Embodiments are provided for receiving a request to output audio at a first speaker and a second speaker of an electronic device, determining that the electronic device is oriented in a portrait orientation or a landscape orientation, identifying, based on the determined orientation, a first equalization setting for the first speaker and a second equalization setting for the second speaker, providing, for output at the first speaker, a first audio signal with the first equalization setting, and providing, for output at the second speaker, a second audio signal with the second equalization setting.

Abstract: Example quantization-based approximate nearest neighbors (ANN) search methods and systems (e.g., search engines) are tuned to perform at the speed-recall pareto frontier. With a desired search cost or recall as input, embodiments employ Lagrangian-based methods to perform constrained optimization on theoretically-grounded search cost and recall models. The resulting tunings, when paired with the efficient quantization-based ANN implementation of the embodiments, exhibit excellent performance on standard benchmarks while requiring minimal tuning or configuration complexity.

Abstract: The disclosed embodiments include computerized methods, systems, and devices, including computer programs encoded on a computer storage medium, for integrating voice-based interaction and control into a native graphical user interface (GUI) of an executed application. For example, a communications device may obtaining component data identifying a plurality of components of a voice-user interface from a computing system maintained by a voice-service provider, and may execute an application linked to a corresponding one of the components of the voice-user interface. The communications device may generate the native GUI based on an output of the executed application, and may generate an interface element representative of the corresponding one of the components of the voice-user interface. The communications device may present the generated interface element within the native GUI, which may embed the corresponding component of the voice-user interface into the native GUI.

Abstract: Provided are methods, systems, and devices for generating semantic objects and an output based on the detection or recognition of the state of an environment that includes objects. State data, based in part on sensor output, can be received from one or more sensors that detect a state of an environment including objects. Based in part on the state data, semantic objects are generated. The semantic objects can correspond to the objects and include a set of attributes. Based in part on the set of attributes of the semantic objects, one or more operating modes, associated with the semantic objects can be determined. Based in part on the one or more operating modes, object outputs associated with the semantic objects can be generated. The object outputs can include one or more visual indications or one or more audio indications.

Abstract: A UE communicating in DC with an MN and an SN detects a master cell group (MCG) failure associated with the MN. In response to detecting the MCG failure, the UE performs an MCG recovery procedure by transmitting an MCG failure information message to the SN, receiving an MCG failure recovery message from the SN, and transmitting an MCG failure recovery complete message to the MN.

Abstract: The present disclosure relates to generating and adjusting translated audio from a video-based source. The method includes receiving video data and corresponding audio data in a first language; generating a translated preliminary transcript in a second language; aligning timing windows of portions of the translated preliminary transcript with corresponding segments of the audio data; determining portions of the translated aligned transcript in the second language that exceed a timing window range of the corresponding segments of the audio data in the first language to generate flagged transcript portions; transmitting the original transcript, the translated aligned transcript, and the first speech dub to a first device, the generated flagged transcript portions included in the original transcript and the translated aligned transcript; receiving, from the first device, a modified original transcript; and generating, based on the modified original transcript, a second speech dub in the second language.

Abstract: Methods, systems, devices, and tangible non-transitory computer readable media for saliency visualization are provided. The disclosed technology can include receiving a data input including a plurality of features. The data input can be segmented into regions. At least one of the regions can include two or more of the features. Attribution scores can be respectively generated for features of the data input. The attribution scores for each feature can be indicative of a respective saliency of such feature. A respective gain value for each region can be determined over one or more iterations based on the respective attribution scores associated with the features included in the region. Further, at each iteration one or more of the regions with the greatest gain values can be added to a saliency mask. Furthermore, at each iteration a saliency visualization can be produced based on the saliency mask.

Abstract: Implementations relate to training a model that can be used to process values for defined features, where the values are specific to a user account, to generate a predicted user measure that reflects both popularity and quality of the user account. The model is trained based on losses that are each generated as a function of both a corresponding generated popularity measure and a corresponding generated quality measure of a corresponding training instance. Accordingly, the model can be trained to generate, based on values for a given user account, a single measure that reflects both quality and popularity of the given user account. Implementations are additionally or alternatively directed to utilizing such predicted user measures to restrict provisioning of content items that are from user accounts having respective predicted user measures that fail to satisfy a threshold.

Abstract: A system for displaying a virtual image to a user includes a light engine to generate a display light representing the virtual image, a diffractive waveguide, and an incoupler and outcoupler that are each optically coupled to the diffractive waveguide. In operation, the incoupler receives the display light from the light engine and directs the received display light to the diffractive waveguide, and the outcoupler directs at least a portion of the display light from the diffractive waveguide to an eye of the user. The diffractive waveguide is configured to converge a first component light of the generated display light at a first focal distance from the eye of the user, and to converge one or more additional component lights of the generated display light at one or more distinct other focal distances from the eye of the user.

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.