Abstract: The present disclosure is directed to a computer-implemented method for enabling private communications during a videoconference. The method includes receiving interface data associated with input from a first participant to a first participant device associated with the first participant and participating in the videoconference. The interface data includes requesting limiting transmission of communication data to a second participant device associated with a second participant and participating in the videoconference while excluding transmission of the communication data to third participant device(s) participating in the videoconference. The method includes obtaining the communication data associated with the first participant including audio data associated with the first participant.

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: A compact electronic device has a touch sensor and/or a microphone that are concealed within a housing at least partially wrapped by an acoustically porous cover. In some implementations, the touch sensor includes a sensing portion and a contact portion extending from the sensing portion. While the sensing portion is placed in proximity to an interior surface of the housing to detect a touch on the housing, the contact portion is bent to electrically couple the sensing portion to a circuit board via two distinct electrical paths. In some implementations, an exterior surface of the housing includes a sealing area surrounding an aperture on the housing, and the acoustically porous cover is affixed to the sealing area via an adhesive. The adhesive covers the sealing area and permeates a thickness of the acoustically porous cover, thereby enabling formation of a controlled sound path to access the microphone via the aperture.

Abstract: A solution arranged to build or train a machine learning model (ML model) that can be uploaded to a server arranged to deploy the ML model to communicating devices. The ML model builder can build the ML model and a ML production pipeline. The ML production pipeline can train the ML model, convert the ML model to a web browser compatible format, and upload the converted ML model to the server. The ML model can receive as input a sequence of prior activities on one communicating device in the communicating devices, analyze the sequence of prior activities on the communicating device, predict a next activity on the communicating device based on the analysis of the sequence of prior activities, preemptively search a computer network based on the predicted next activity to find a computer asset, and preload the found computer asset to a storage in the communicating device.

Abstract: Implementations are directed to updating a trained voice bot that is deployed for conducting conversations on behalf of a third-party. A third-party developer can interact with a voice bot development system that enables the third-party developer to train, update, validate, and monitor performance of the trained voice bot. In various implementations, the trained voice bot can be updated by updating a corpus of training instances that was initially utilized to train the voice bot, and updating the trained voice bot based on the updated corpus. In some implementations, the corpus of training instances may be updated in response to identifying occurrence(s) of behavioral error(s) of the trained voice bot while the conversations are being conducted on behalf of the third-party. In additional or alternative implementations, the corpus of training instances may be updated in response to determining the trained voice bot does not include a desired behavior.

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 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: 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 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: 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: 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: A media application selects, from a collection of images associated with a user account, candidate pairs of images, where each pair includes a first static image and a second static image from the user account. The media application applies a filter to select a particular pair of images from the candidate pairs of images. The media application generates, using an image interpolator, one or more intermediate images based on the particular pair of images. The media application generates a video that includes three or more frames arranged in a sequence, where a first frame of the sequence is the first static image, a last frame of the sequence is the second static image, and each of the one or more intermediate images is a corresponding intermediate frame of the sequence between the first frame and the last frame.

Abstract: Methods and systems for determining an individual gaze value are disclosed herein. An exemplary method involves: (a) receiving gaze data for a first wearable computing device, wherein the gaze data is indicative of a wearer-view associated with the first wearable computing device, and wherein the first wearable computing device is associated with a first user-account; (b) analyzing the gaze data from the first wearable computing device to detect one or more occurrences of one or more advertisement spaces in the gaze data; (c) based at least in part on the one or more detected advertisement-space occurrences, determining an individual gaze value for the first user-account; and (d) sending a gaze-value indication, wherein the gaze-value indication indicates the individual gaze value for the first user-account.

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: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting a continued conversation are disclosed. In one aspect, a method includes the actions of receiving first audio data of a first utterance. The actions further include obtaining a first transcription of the first utterance. The actions further include receiving second audio data of a second utterance. The actions further include obtaining a second transcription of the second utterance. The actions further include determining whether the second utterance includes a query directed to a query processing system based on analysis of the second transcription and the first transcription or a response to the first query. The actions further include configuring the data routing component to provide the second transcription of the second utterance to the query processing system as a second query or bypass routing the second transcription.