Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a distilled machine learning model. One of the methods includes training a cumbersome machine learning model, wherein the cumbersome machine learning model is configured to receive an input and generate a respective score for each of a plurality of classes; and training a distilled machine learning model on a plurality of training inputs, wherein the distilled machine learning model is also configured to receive inputs and generate scores for the plurality of classes, comprising: processing each training input using the cumbersome machine learning model to generate a cumbersome target soft output for the training input; and training the distilled machine learning model to, for each of the training inputs, generate a soft output that matches the cumbersome target soft output for the training input.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting a neural network with additional operations.

Abstract: A method for predicting parametric vocoder parameter includes receiving a text utterance having one or more words, each word having one or more syllables, and each syllable having one or more phonemes. The method also includes receiving, as input to a vocoder model, prosodic features that represent an intended prosody for the text utterance and a linguistic specification. The prosodic features include a duration, pitch contour, and energy contour for the text utterance, while the linguistic specification includes sentence-level linguistic features, word-level linguistic features for each word, syllable-level linguistic features for each syllable, and phoneme-level linguistic features for each phoneme. The method also includes predicting vocoder parameters based on the prosodic features and the linguistic specification.

Abstract: A method for document extraction includes receiving, from a user device associated with a user, an annotated document that includes one or more fields. Each respective field of the one or more fields of the annotated document is labeled by a respective annotation. The method includes clustering, using a template matching algorithm, the annotated document into a cluster and inducing, using the annotated document, a document template for the cluster. The method includes receiving, from the user device, an unannotated document including the one or more fields. The method includes clustering, using the template matching algorithm, the unannotated document into the cluster and, in response to clustering the unannotated document into the cluster, extracting, using the document template, the one or more fields.

Abstract: An apparatus includes a processing device coupled to a memory storing instructions. The instructions cause the processing device to receive photoplethysmography (PPG) data derived from signals associated with at least one PPG sensor; receive acoustic data derived from signals associated with at least one audio sensor oriented to sense a heart rate of a human subject; and combine the PPG data and the acoustic data to generate a heart rate estimate.

Abstract: This document describes systems and techniques directed at compensating for voltage losses in organic light-emitting diode (OLED) displays. In aspects, a computing device having an OLED display and a luminance manager is configured to receive an indication of a luminance that is, or is intended to be, displayed by pixels of the OLED display. Responsive to and based on the received indication of luminance and a voltage loss, the luminance manager determines a luminance modification for the pixels of the OLED display. Based on the determined luminance modification, the luminance manager modifies the luminance that is displayed or modifies the luminance that is intended to be displayed by the pixels of the OLED display effective to compensate for the voltage loss.

Abstract: A computer-implemented method for transcribing an utterance includes receiving, at a computing system, speech data that characterizes an utterance of a user. A first set of candidate transcriptions of the utterance can be generated using a static class-based language model that includes a plurality of classes that are each populated with class-based terms selected independently of the utterance or the user. The computing system can then determine whether the first set of candidate transcriptions includes class-based terms. Based on whether the first set of candidate transcriptions includes class-based terms, the computing system can determine whether to generate a dynamic class-based language model that includes at least one class that is populated with class-based terms selected based on a context associated with at least one of the utterance and the user.

Abstract: A method for unstructured data analytics in data warehouses includes receiving an unstructured data query from a user, the unstructured data query requesting the data processing hardware determine one or more unstructured data files stored at a data repository that match query parameters. The method includes determining, using an object table, a set of unstructured data files stored at the data repository that matches the query parameters. The object table includes a plurality of rows, each row of the plurality of rows associated with a respective unstructured data file stored at the data repository, and a plurality of columns, each column of the plurality of columns comprising metadata associated with the respective unstructured data file of each row of the plurality of rows. The method includes returning, to the user, a structured data table including the determined set of unstructured data files.

Abstract: The various embodiments of a rotationally-locking magnetic alignment system and components thereof are described herein, which enable position locking and self-alignment along stepwise rotational increments. In aspects, a rotationally-locking magnetic alignment system can include magnetic alignment components, where each magnetic alignment component can include an array of magnetic field-inducing components that possess a particular magnetic polarity such that a first magnetic alignment component can attract, magnetically couple, and positionally lock a complementary second magnetic alignment component. In implementations, the array of magnetic field-inducing components can be arranged in one or more patterns, within the first magnetic alignment component and/or the second magnetic alignment component, allowing for the first magnetic alignment component to be positionally locked at any number of stepwise rotational increments.

Abstract: A device (100) includes a display (110) itself including pixel groups. A bottom and sides of each of the pixel groups are covered with non-reflective material. The pixel groups are electrically coupled together with transparent conductive interconnections. A camera (122) is located beneath the display and the camera is configured to sense light that passes through the display.

Abstract: Implementations relate to determination and visual display of spoken menus for calls. In some implementations, a computer-implemented method includes receiving audio data output in a call between a call device and a device associated with a target entity. The audio data includes speech indicating one or more selection options for a user of the call device to navigate through a call menu provided by the target entity in the call. Text is determined by programmatically analyzing the audio data, the text representing the speech. The selection options are determined based on programmatically analyzing at least one of the text or the audio data. At least a portion of the text is displayed by the call device during the call, as one or more visual options that correspond to the selection options. The visual options are each selectable via user input to cause corresponding navigation through the call menu.

Abstract: Methods, systems, and media for selecting video formats for adaptive video streaming are provided.

Abstract: Systems and methods for generating phonetic spelling variations of a given word based on locale-specific pronunciations. A phoneme-letter density model may be configured to identify a phoneme sequence corresponding to an input word, and to identify all character sequences that may correspond to an input phoneme sequence and their respective probabilities. The phoneme-phoneme error model may be configured to identify locale-specific alternative phoneme sequences that may correspond to a given phoneme sequence, and their respective probabilities. Using these two models, a processing system may be configured to generate, for a given input word, a list of alternative character sequences that may correspond to the input word based on locale-specific pronunciations, and/or a probability distribution representing how likely each alternative character sequence is to correspond to the input word.

Abstract: A data rack system includes a data center rack frame, a shelf positioned within the data center rack frame; and a modular battery unit disposed on the shelf. The modular battery unit further includes a housing having an outer surface, a plurality of strips of phase change material (“PCM”) attached to the outer surface and spaced apart from one another; and air flow channels. The air flow channels are formed in spaces between two adjacent strips of the plurality of strips and defined by a shape and size of the spaces between the two adjacent strips.

Abstract: Methods, systems and apparatus for correcting a result of a quantum computation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a fundus image processing machine learning models that is configured to process one or more fundus images captured by a fundus camera to generate a predicted label. One of the methods includes generating training data, comprising: receiving sets of one or more training fundus images captured by a fundus camera; receiving, for each of the sets, a ground truth label assigned to a different image of the eye of the patient corresponding to the set that has been captured using a different imaging modality; and generating, for each set of training fundus images, a training example that includes the set of training fundus images in association with the ground truth label assigned to the different image of the patients eye; and training the machine learning model on the training examples in the training data.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. In one aspect, one of the systems includes an encoder neural network configured to receive the input sequence and generate encoded representations of the network inputs, the encoder neural network comprising a sequence of one or more encoder subnetworks, each encoder subnetwork configured to receive a respective encoder subnetwork input for each of the input positions and to generate a respective subnetwork output for each of the input positions, and each encoder subnetwork comprising: an encoder self-attention sub-layer that is configured to receive the subnetwork input for each of the input positions and, for each particular input position in the input order: apply an attention mechanism over the encoder subnetwork inputs using one or more queries derived from the encoder subnetwork input at the particular input position.

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: An electronic device comprises an image sensor, one or more processors, and memory storing instructions for receiving an event recording profile based on configuration data of the electronic device, the configuration data including a location type or a power type; receiving a plurality of images of a scene captured by the image sensor; detecting a trigger event based on one or more of the plurality of images of the scene; in response to detecting the trigger event, identifying an object of interest in one or more of the plurality of images of the scene; creating an event clip from the stored images that include the object of interest, wherein creating the event clip includes configuring a clip length based on the event recording profile; and providing the event clip for display.

Abstract: Methods, systems, and computer programs are presented for implementing a multi-function control element in a Graphical User Interface (GUI). The method includes responsive to a cursor being away from a control element, present the control element in a compact state in the Graphical User Interface (GUI) within a display. The method also includes responsive to the cursor being over the control element, present the control element in an expanded state. The method includes responsive to receiving the selection of the option and determining the cursor is away from the control element, return the control element to the compact state from the expanded state.