Abstract: This application is directed to a display assistant device that acts as a voice-activated user interface device. The display assistant device includes a base, a screen and a rear speaker. The base is configured for sitting on a surface. The screen has a rear surface and is supported by the base at the rear surface. A bottom edge of the screen is configured to be held above the surface by a predefined height, and the base is substantially hidden behind the screen from a front view of the display assistant device. The rear speaker is concealed inside the base and oriented to project sound towards the rear side of the base.

Abstract: This document describes techniques and systems for authentication management through IMU and radar. The techniques and systems use inertial sensor data from an inertial measurement unit (IMU) and/or radar data to manage authentication for a computing device. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for computing-device authentication.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.

Abstract: Techniques for controlling a remotely controllable device are described. In an example, a mobile device detects a remotely controllable device, measures a distance and direction from the mobile device to the remotely controllable device, and determines from the distance and direction that the mobile device is pointing at the remotely controllable device. In response to determining that the mobile device is in a handheld position, is pointing at the remotely controllable device, or both, the mobile device monitors for a movement of the mobile device according to a prescribed gesture. In response to detecting that the mobile device was moved according to the prescribed gesture, the mobile device presents a collection of selectable actions control operations of the remotely controllable device.

Abstract: Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, a leader is selected from among candidate computing clusters. To make this selection, an activity monitor predicts or monitors the workload of one or more clients. Different activities of the workload are given corresponding weights. The delay in performing requested activities, modified by these weights is found, and the candidate leader with the lowest weighted delay is selected as the leader.

Abstract: A computer-implemented input-method editor process includes receiving a request from a user for an application-independent input method editor having written and spoken input capabilities, identifying that the user is about to provide spoken input to the application-independent input method editor, and receiving a spoken input from the user. The spoken input corresponds to input to an application and is converted to text that represents the spoken input. The text is provided as input to the application.

Abstract: A method using multi-assistant warm words includes, for each digital assistant in a group of digital assistants enabled on a multi-assistant device, receiving a respective active set of warm words that each specify a respective action to perform. Based on the respective active set of warm words, the method also includes executing a warm word arbitration routine to enable a final set of warm words for detection, each warm word in the final set of warm words selected from the respective active set of warm words for at least one digital assistant. While the final set of warm words are enabled for detection, the method includes receiving audio data corresponding to an utterance, detecting a warm word from the final set of warm words, and instructing the digital assistant associated with the detected warm word to perform the respective action specified by the detected warm word.

Abstract: Methods, systems, apparatus, including computer programs encoded on computer storage media, for reclaiming storage space in a storage environment. In one aspect, the method includes actions of aggregating data that is indicative of access to one or more data objects, determining a future storage cost associated with each of a plurality of data objects, determining an access window for each of the plurality of data objects, identifying a data object based on (i) the future storage cost that satisfies a predetermined threshold and (ii) a data object access window, providing a notification to a user device that requests feedback from a user indicating whether the data object can be deleted, and in response to receiving data that indicates that the data object can be deleted, generating an instruction to cause deletion of the data object upon the expiration of the access window.

Abstract: A method for augmenting handling of logs generated in platform as a system (PaaS) environments includes transmitting, to an external cloud computing environment, an application programming interface (API) request. The API request includes a trace identification (ID), a concealment indicator, and a policy ID. The method also includes updating the first entry in the first log corresponding to the API request based on the trace ID and the concealment indicator. The method also includes storing the first entry in the first log corresponding to the API request based on the storage criteria of the policy ID.

Abstract: A method for training a non-autoregressive TTS model includes receiving training data that includes a reference audio signal and a corresponding input text sequence. The method also includes encoding the reference audio signal into a variational embedding that disentangles the style/prosody information from the reference audio signal and encoding the input text sequence into an encoded text sequence. The method also includes predicting a phoneme duration for each phoneme in the input text sequence and determining a phoneme duration loss based on the predicted phoneme durations and a reference phoneme duration. The method also includes generating one or more predicted mel-frequency spectrogram sequences for the input text sequence and determining a final spectrogram loss based on the predicted mel-frequency spectrogram sequences and a reference mel-frequency spectrogram sequence. The method also includes training the TTS model based on the final spectrogram loss and the corresponding phoneme duration loss.

Abstract: An electronic device is configured with a notification throttling system. The notification throttling system obtains a set of priorities for multiple applications that are installed on the electronic device and are enabled for alerting the user via notifications. The set of priorities specifies a relative importance of each particular application among the multiple applications. The notification throttling system throttles application alerts presented by the user device for notifications generated by the applications based on the relative importance of each particular application as specified by the set of priorities.

Abstract: A first electronic device, electronically coupled to a second device for supplying a charge to the second electronic device, tracks the voltage requirements of the second device and dynamically adjusts its output voltage upwards or downwards to match such requirements. The second electronic device may provide feedback to the first electronic device through a feedback loop. The feedback may include an indication of the voltage requirements and/or instructions for adjusting the voltage output of the first electronic device. The second device may be, for example, a wearable audio device, while the first device is a case for the wearable audio device.

Abstract: Methods, systems, and media for associating multiple users with a media presentation device are provided. In some embodiments, the method comprises: receiving first user preferences; receiving second user preferences; receiving requests to associate the first user preferences and the second user preferences, respectively, with a media presentation device; causing the first user preferences and the second user preferences to be associated with identifying information of the media presentation device; receiving, from the media presentation device, a request to present a slideshow of images based on user preferences and identifying information of the first user device and a third user device; determining that the first user preferences are associated with the media presentation device; determining that user preferences of the third user device are not associated with the media presentation device; and causing content based on the first user preferences to be presented by the media presentation device.

Abstract: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium for delivering content. A method includes: identifying an application that is installed on a user device; accepting a bid from a sponsor associated with the application for presenting customized content on the user device after installation of the application on the user device; identifying an opportunity to present content on the user device including receiving a request for content that identifies the user device; conducting an auction including evaluating the accepted bid along with other bids; determining that the accepted bid is the winning bid in the auction and providing, in response to the determining, a shell for the customized content; enabling the shell to be populated with data stored on the user device to produce the customized content; and providing the customized content for presentation on the user device in response to the identified opportunity.

Abstract: A new segment of electronic handwriting is provided to a handwriting recognition module to obtain a plurality of textual interpretations of the new segment. The textual interpretations obtained from the handwriting recognition module are scored based on how each respective electronic handwriting representation would change a display of existing electronic content when the respective electronic handwriting representation is displayed substantially at the user designated position within or adjacent to the existing electronic content. Based on the scoring, an electronic handwriting representation corresponding to a respective textual interpretation of the plurality of textual interpretations is selected, and the existing electronic content is modified to include the selected electronic handwriting representation located substantially at the user designated position.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using self-attention based neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more self-attention neural network layers.

Abstract: This technology relates to rasterizing and compositing vector graphics in parallel on a data-parallel computing device. For example, vector data of the vector graphics, may be loaded into local memory accessible by the one or more parallel processors. The vector data may include one or more paths comprised of one or more path segments of the vector graphics. The one or more parallel processors may rasterize the one or more path segments into respective rasters and assign each of the rasters into groups based on pixel coordinates of the respective rasters. Each group may have an associated key and the rasters within each group represent a portion of the same vector graphic. The rasters may be placed onto subpixels according to their respective pixel coordinates and rendered onto a display by the one or more parallel processors.

Abstract: Methods, systems, and computer programs encoded on a computer storage medium, for training and using machine learning models are disclosed. Methods include creating a model that represents relationships between user attributes, content exposures, and performance levels for a target action using organic exposure data specifying one or more organic exposures experienced by a particular user over a specified time prior to performance of a target action by the particular user and third party exposure data specifying third party exposures of a specified type of digital component to the particular user over the specified time period. Using the model, an incremental performance level attributable to each of the third party exposures at an action time when the target action was performed by the particular user is determined. Transmission criteria for at least some digital components to which the particular user was exposed are modified based on the incremental performance.

Abstract: A system and method for repartitioning data in a distributed network. The method may include executing, by one or more processors, a first pass of a data set from a plurality of first sources to a plurality of first sinks, each first sink collecting data from one or more of the first sources, and executing, by the one or more processors, a second pass of the data set from a plurality of second sources to a plurality of second sinks, each one of the plurality of first sinks corresponding to one of the plurality of second sources, and each second sink collecting data from one or more of the second sources. Executing the first and second passes causes the data set to be repartitioned such that one or more second sinks collect data that originated from two or more of the first sources.

Abstract: A method is provided for processing medical text and associated medical images. A natural language processor configured as a deep conventional neural network is trained on a first corpus of curated free-text, medical reports each of which having one or more structured labels assigned by an medical expert. The network is trained to learn to read additional free-text medical reports and produce predicted structured labels. The natural language processor is applied to a second corpus of free-text medical reports that are associated with medical images. The natural language processor generates structured labels for the associated medical images. A computer vision model is trained using the medical images and the structured labels generated. The computer vision model can thereafter assign a structured label to a further input medical image. In one example, the medical images are chest X-rays.