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: 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: 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: The present disclosure provides systems and methods that generate query templates that are expressed in a generic schema-agnostic language. The query templates can be generated “from scratch” or can be automatically generated from existing queries, a process which may be referred to as “templatizing” the existing queries. As one example, generation of query templates can be performed through an iterative process that iteratively generates candidate templates over time to optimize a coverage over a set of existing queries. After generation of the schema-agnostic query templates, the systems and methods described herein can automatically translate/map the templatized queries into “concrete,” schema-specific queries that can be evaluated over specific customer schemas/datasets. In this manner, a query template for a given semantic query (e.g., “return the names of all employees”), is required to be written only once.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatically determining parameter values that control or affect provision of content by a content platform. In one aspect, evaluation points are identified for a parameter. Each evaluation point includes an evaluated parameter value of the parameter and a metric value of a metric corresponding to the provision of digital components by the content platform. A first model is generated using the set of evaluation points. A second model is generated based on the first model and an acquisition function that is based on mean values and confidence intervals of the first model and a configurable exploration weight that controls a priority of exploration for evaluating the parameter. A next parameter value to evaluate is determined from the second model and the content platform is configured to use the next parameter value to provide digital components.

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: 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: Methods and systems of determining competition for search queries on a video hosting system on a computer network are provided. Search records associated with search queries directed to the video hosting system are received. Each search record identifies videos available on the video hosting system that are search results for a corresponding search query and indicates associated view durations that the videos were viewed responsive to the search query. Search queries directed to a first and second videos and associated view durations that the first video was watched in response to the queries are identified from the received search records. A competition score indicating an amount of competition between the first and second videos for views of users of the video hosting system is calculated based on the identified search queries and associated view durations.

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: 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: Techniques are described for selectively adapting and/or selectively utilizing a noise reduction technique in detection of one or more features of a stream of audio data frames. For example, various techniques are directed to selectively adapting and/or utilizing a noise reduction technique in detection of an invocation phrase in a stream of audio data frames, detection of voice characteristics in a stream of audio data frames (e.g., for speaker identification), etc. Utilization of described techniques can result in more robust and/or more accurate detections of features of a stream of audio data frames in various situations, such as in environments with strong background noise. In various implementations, described techniques are implemented in combination with an automated assistant, and feature(s) detected utilizing techniques described herein are utilized to adapt the functionality of the automated assistant.

Abstract: Location modeling may be generated for candidate locations based on validated location data. The location models for candidate locations may be based on validated location data associated with wireless access points that is validated using transaction data. Such validation may include comparing an identifier associated with candidate location data received from a client device to an identifier for a transaction account associated with a transaction from transaction data at a candidate location. Matching transaction data and candidate location data may generate validated location data to be used in generating location models for candidate locations.

Abstract: Methods and apparatus related to ranking modifications of a previous query. For example, modifications of a previous query may be generated based on a current query issued subsequent to the previous query by substituting one or more n-grams of the previous query with one or more n-grams of the current query. One or more measures of each of the modifications may be identified and, based on such measures, a ranking of each of the modifications may be determined. One of the modifications may be selected as a submission query based on the rankings of the modifications. The submission query may be selected for submission in lieu of, or in addition to, the current query.

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 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: Example embodiments of the present disclosure provide for an example method. The example method includes generating an initial user interface including a content assistant component. The example method include obtaining user input data. The example method includes processing, by a machine learned model interfacing with the content assistant component, the data indicative of the input received from the user. The method includes obtaining output data, from the machine learned model interfacing with the content assistant component, indicative of one or more content item components. The method includes transmitting data which causes the content item components to be provided for display via an updated user interface. The method includes obtaining data indicative of user selection of approval of the content item components. The method includes generating, in response to obtaining the data indicative of the user selection of the approval of the content item components, content items.

Abstract: Implementations are provided for providing responsive audio recordings to user queries that are prerecorded by human beings, rather than generated automatically using speech synthesis processing. In various implementations, a query provided by a user at an input component of a computing device may be used to search a corpus of voice recordings From the searching, a plurality of candidate responsive voice recordings may be identified and ranked based on measures of credibility associated with speakers that created the candidate responsive voice recordings. Based on the ranking, one or more of the plurality of candidate responsive voice recordings may be provided for presentation to the user at an output component of the same computing device or a different computing device.

Abstract: A method for example-driven machine learning is disclosed herein. The method comprises maintaining a plurality of dialog system rules and a knowledge database including a plurality of intent objects and a plurality of entity objects. The plurality of intent objects and the plurality of entity objects are associated with at least one dialog system rule. An exemplary phrase is received and one or more linguistic elements are retrieved from the exemplary phrase. It is determined that at least one of the linguistic elements is directed to at least one of the plurality of intent objects of the plurality of entity objects and the at least one of the linguistic elements in association with the at least one dialog system rule is added to the knowledge database.

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.

Abstract: A method for determining playback behavior of a media item including a video component and an audio component includes determining a current event that causes a playing of the video component of the media item on a screen of a user device to be suspended. The method further includes predicting user playback preferences for the media item using a behavioral model trained on previous events corresponding to the current event, and determining, based on the predicted user playback preferences, whether to continue playing the audio component of the media item.

Abstract: The present disclosure provides systems and methods for on-device machine learning. In particular, the present disclosure is directed to an on-device machine learning platform and associated techniques that enable on-device prediction, training, example collection, and/or other machine learning tasks or functionality. The on-device machine learning platform can include a mode controller that allows a user to provide data input indicating whether to operate one or more applications on the device in a first collection mode (e.g., permission mode) for storing training examples or a second collection mode for (e.g., incognito mode) for not storing training examples. The training examples can be generated based on user interaction with the one or more applications and used to personalize one or more machine-learned models used by the application(s) by retraining the models using the user-specific training examples.

Abstract: In some embodiments, a method for controlling access to media is provided, the method comprising: receiving an encrypted media content stream from a media content source that includes first media content corresponding to at least a portion of a media content item; requesting a second media content stream that includes second media content having a playback position adjacent to the first media content, wherein the second media content stream includes key information for decrypting the encrypted media content stream; decrypting the encrypted media content stream using the key information included in the second media content stream; and causing the decrypted media content stream to be presented.

Abstract: Implementations relate to automatic generation of speaker features for each of one or more particular text-dependent speaker verifications (TD-SVs) for a user. Implementations can generate speaker features for a particular TD-SV using instances of audio data that each capture a corresponding spoken utterance of the user during normal non-enrollment interactions with an automated assistant via one or more respective assistant devices. For example, a portion of an instance of audio data can be used in response to: (a) determining that recognized term(s) for the spoken utterance captured by that the portion correspond to the particular TD-SV; and (b) determining that an authentication measure, for the user and for the spoken utterance, satisfies a threshold. Implementations additionally or alternatively relate to utilization of speaker features, for each of one or more particular TD-SVs for a user, in determining whether to authenticate a spoken utterance for the user.

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: 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: In aspects, a base station establishes a wireless connection with a user equipment, UE. The base station determines to include at least a first adaptive phase-changing device, APD, and a second APD in a wireless communication path with the UE. In response to determining to include multiple APDs in the communication path, the base station determines a first surface configuration for a first surface of the first APD and a second surface configuration for a second surface of the second APD. The base station directs the first APD to apply the first surface configuration to the first surface and directs the second APD to apply the second surface configuration to the second surface. The base station and the UE communicate with the UE using wireless transmissions that travel along a wireless communication path that includes the first surface of the first APD and the second surface of the second APD.

Abstract: Various arrangements are presented for increasing a link margin of a wireless audio link. A short-range wireless communication link having a first physical layer (PHY) symbol rate is established between an audio source device and an audio output device. An audio stream is transmitted using the communication link, which includes a connected isochronous stream (CIS) link. A number of packet retransmissions are detected on the CIS. Based on the detected number of packet retransmissions on the CIS, the first PHY symbol rate of the CIS can be altered to a second PHY symbol rate for transmitting the audio stream.

Abstract: The various implementations described herein include methods and systems for synchronous audio playback. An electronic device can receive an identification of a first device as a common clock device that has a first internal clock being designated as a master clock. The electronic device receives a synchronized audio playback command that includes audio data to be output and a future playback time. In response to receiving the audio data, the device determines a synchronized audio playback time for audio to be output. An optimal time for output can be calculated and transmitted to the server system for future playback time calculations.

Abstract: The present disclosure describes thermal mitigation for an electronic speaker device and associated systems and methods. The thermal mitigation includes monitoring several thermal zones to determine or estimate thermal conditions in corresponding parts of the electronic speaker device. The thermal zones may include a System-on-Chip (SoC) integrated circuit (IC) component, audio components including power-dissipating IC components, and a temperature of an exterior surface of a housing component of the electronic speaker device. To mitigate thermal runaway, different throttling schemes may be triggered based on the thermal zones exceeding certain thermal limits. The throttling schemes may include reducing the amount of power supplied to the SoC, reducing audio power of the audio components to a lower wattage, or manipulating SoC cores such as by disabling one or more of the cores or adjusting utilization of the SoC cores.

Abstract: A method includes receiving training data that includes a plurality of sets of text-to-speech (TTS) spoken utterances each associated with a respective language and including TTS utterances of synthetic speech spoken that includes a corresponding reference speech representation paired with a corresponding input text sequence. For each TTS utterance in each set of the TTS spoken training utterances of the received training data, the method includes generating a corresponding TTS encoded textual representation for the corresponding input text sequence, generating a corresponding speech encoding for the corresponding TTS utterance of synthetic speech, generating a shared encoder output, generating a predicted speech representation for the corresponding TTS utterance of synthetic speech, and determining a reconstruction loss. The method also includes training a TTS model based on the reconstruction losses determined for the TTS utterances in each set of the TTS spoken training utterances.

Abstract: A method includes a hierarchical dataset that includes a root-data object and data collections nested under the root-data object. Each data collection includes one or more data objects, each data object associated with one or more other data collections. The method also includes displaying a hierarchical user interface on a screen. The hierarchical user interface includes column. The columns include data-object columns and data-collection columns, wherein the columns alternate between data-object columns and data-collection columns. Each data-object column displays a list of the one or more data objects of a respective data collection. Each data-collection column displays a list of the one or more data collections of a respective data object, the data-collection columns includes a root-data-collection column displaying a list of the one or more data collections associated with the root-data object.

Abstract: A method includes receiving context biasing data that includes a set of unspoken textual utterances corresponding to a particular context. The method also includes obtaining a list of carrier phrases associated with the particular context. For each respective unspoken textual utterance, the method includes generating a corresponding training data pair that includes the respective unspoken textual utterance and a carrier phrase. For each respective training data pair, the method includes tokenizing the respective training data pair into a sequence of sub-word units, generating a first higher order textual feature representation for a corresponding sub-word unit, receiving the first higher order textual feature representation, and generating a first probability distribution over possible text units. The method also includes training a speech recognition model based on the first probability distribution over possible text units.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for hotword detection on multiple devices are disclosed. In one aspect, a method includes the actions of receiving audio data that corresponds to an utterance. The actions further include determining that the utterance likely includes a particular, predefined hotword. The actions further include transmitting (i) data indicating that the computing device likely received the particular, predefined hotword, (ii) data identifying the computing device, and (iii) data identifying a group of nearby computing devices that includes the computing device. The actions further include receiving an instruction to commence speech recognition processing on the audio data. The actions further include in response to receiving the instruction to commence speech recognition processing on the audio data, processing at least a portion of the audio data using an automated speech recognizer on the computing device.

Abstract: This document describes techniques and apparatuses that enable determining expected hash-values in functions with control flow. A computing device receives a function comprising function instructions within at least three basic blocks connected via multiple execution paths. Hash-input instructions are inserted within a plurality of the basic blocks that indirectly force hash values at the respective insertion points. Hash values at ends of the plurality of the basic blocks are set to a canonical value and an expected hash-value and hash input-values are calculated using a hash function. By using the canonical value and the hash input-values, the expected hash-value is the same regardless of which execution path is executed.

Abstract: A method includes receiving a training dataset that includes one or more spoken training utterances for training an automatic speech recognition (ASR) model. Each spoken training utterance in the training dataset paired with a corresponding transcription and a corresponding target sequence of auxiliary tokens. For each spoken training utterance, the method includes generating a speech recognition hypothesis for a corresponding spoken training utterance, determining a speech recognition loss based on the speech recognition hypothesis and the corresponding transcription, generating a predicted auxiliary token for the corresponding spoken training utterance, and determining an auxiliary task loss based on the predicted auxiliary token and the corresponding target sequence of auxiliary tokens. The method also includes the ASR model jointly on the speech recognition loss and the auxiliary task loss determined for each spoken training utterance.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a packet from a client, the packet having header information including a destination Internet Protocol (IP) address, a destination port, a source IP address, and a source port, and wherein the source IP address and source port are associated with the client; selecting a destination virtual machine based on the destination port; modifying the packet by replacing the destination IP address in the header information with an IP address of the selected destination virtual machine; and sending the modified packet to the destination virtual machine.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing a machine learning model that is trained to perform a machine learning task. In one aspect, a method comprises receiving a request to train a machine learning model on a set of training examples; determining a set of one or more meta-data values characterizing the set of training examples; using a mapping function to map the set of meta-data values characterizing the set of training examples to data identifying a particular machine learning model architecture; selecting, using the particular machine learning model architecture, a final machine learning model architecture for performing the machine learning task; and training a machine learning model having the final machine learning model architecture on the set of training examples.

Abstract: An indexed sequence of bits in a buffer is allocated for tracking a battery charging state. The indexed sequence of bits has a first number of bits. A battery voltage of a rechargeable battery is sampled at a sampling rate. For each sampled battery voltage, the battery voltage is compared with a voltage threshold. A next bit position in the indexed sequence of bits is identified. In accordance with a determination that a comparison result is true, a predefined first value is added to the next bit position. A second number of bits that are filled with the predefined first value is determined. A ratio between the second number and the first number is also determined. In accordance with a determination that the ratio exceeds a threshold step-down ratio, a battery charge voltage is stepped down. The rechargeable battery is charged to a step-down voltage.

Abstract: A method for extracting entities comprises obtaining a document that includes a series of textual fields that includes a plurality of entities. Each entity represents information associated with a predefined category. The method includes generating, using the document, a series of tokens representing the series of textual fields. The method includes generating an entity prompt that includes the series of tokens and one of the plurality of entities and generating a schema prompt that includes a schema associated with the document. The method includes generating a model query that includes the entity prompt and the schema prompt and determining, using an entity extraction model and the model query, a location of the one of the plurality of entities among the series of tokens. The method includes extracting, from the document, the one of the plurality of entities using the location of the one of the plurality of entities.

Abstract: The present disclosure provides systems and methods for adjusting the playback speed of accessories based on the buffer level of the received content. The accessories may receive content from a host device at a certain speed. The incoming speed of the content may be different than the playback speed of the content. Therefore, a buffer level of the received content may be determined using a linear least square (“LLS”) fit of the buffer level, the average of the buffer level, or a phased locked loop (“PLL”) approach. Based on a difference between the buffer level and the playback speed, a speed adjustment may be determined. Instructions may be transmitted from a primary accessory to a secondary accessory to adjust the playback speed by a certain amount at a certain time. This may ensure that the accessories remain in sync. The accessories may then adjust their respective playback speeds.

Abstract: A cloud implementation of a persisted storage device, such as a disk, is provided. The implementation supports a variety of features and protocols, in full analogy with a physical storage device such as a disk drive. The present disclosure provides for implementing standard eDrive protocols in the cloud by designing internal disk storage, referred to as a “system area,” in a virtual disk instance that the virtual disk can potentially utilize for a multitude of disk features. This internal storage can be used to implement eDrive protocols, which use the system area to maintain the necessary internal virtual disk state.

Abstract: In an implementation, a method includes causing a source application data object to be embedded in a host application file and recording information associated with the source application data object in a common data store. It further includes identifying a modification made to the embedded source application data object, sending a notification to the source application to update a corresponding source copy of the source application data object based on the modification made to the embedded source application data object, and recording the modification in the common data store. The method also includes identifying a change made to the source copy of the source application data object, and causing the host application to update the embedded source application data object in the host application data store according to access permissions of the host application file, and recording the change in the common data store.

Abstract: Generally disclosed herein is a hardware/software interface for asynchronous data movement between an off-core memory and a core-local memory, referred to as “stream transfers”, and a stream ordering model. The stream transfers allow software to more efficiently express common data-movement patterns, specifically ones seen in sparse workloads. Direct stream instructions that belong to a stream are processed in-order. For indirect stream instructions, offset elements in an offset list are processed in order. A sync flag is updated to indicate monotonic incremental progress for the stream.

Abstract: The disclosed technology provides techniques, systems, and apparatus for proactively detecting, containing, and recovering from uncorrectable memory errors in distributed computing environment. An aspect of the disclosed technology includes scanning, by a scanner of a host machine, memory of the host machine for errors. After the scanner detects an error, the scanner may generate an error notification. The scanner may transmit the error notification to one or more processors of the host machine to implement mitigation techniques.

Abstract: A system includes a first processor configured to analyze packets received over a communication protocol system and determine one or more congestion indicators from the analysis of the data packets, the one or more congestion indicators being indicative of network congestion for data packets transmitted over a reliable transport protocol layer of the communication protocol system. The system also includes a rate update engine separate from the packet datapath and configured to operate a second processor to receive the determined one or more congestion indicators, determine one or more congestion control parameters for controlling transmission of data packets based on the received one or more congestion indicators, and output a congestion control result based on the determined one or more congestion control parameters.

Abstract: Identity systems, methods, and media for auditing and notifying users concerning verifiable claims are provided.