Abstract: A method for disaggregated cache memory for efficiency in distributed databases includes receiving, from a user device, a first query requesting first data be written to a distributed database. The distributed database includes a plurality of nodes each controlling writes to a respective portion of the distributed database and a distributed cache pool caching a subset of the distributed database independently from the plurality of nodes. The method includes writing, using one of the plurality of nodes, the first data to the distributed database. The method also includes receiving, from the user device, a second query requesting second data be read from the distributed database. The method further includes retrieving, from the distributed cache pool, the second data. The method includes providing, to the user device, the second data retrieved from the distributed cache pool.

Abstract: A method includes receiving a source data set and a target data set and identifying a loss function for a deep learning model based on the source data set and the target data set. The loss function includes encoder weights, source classifier layer weights, target classifier layer weights, coefficients, and a policy weight. During a first phase of each of a plurality of learning iterations for a learning to transfer learn (L2TL) architecture, the method also includes: applying gradient decent-based optimization to learn the encoder weights, the source classifier layer weights, and the target classifier weights that minimize the loss function; and determining the coefficients by sampling actions of a policy model. During a second phase of each of the plurality of learning iterations, determining the policy weight that maximizes an evaluation metric.

Abstract: Features described herein generally relate to systems and methods for assembling an electronic device. Particularly, the electronic device can be assembled by holding a portion of the first component arranged in a first plane in a holding position with a stream of air output from a nozzle of an assembly system and aligning the portion of the first component with an opening in a portion of the second component arranged in a second plane parallel to the first plane while the portion of the first component is held in the holding position.

Abstract: A method includes receiving a scan request requesting to scan a set of network-connected assets designated for a network scan. For each respective network-connected asset, the method includes scanning, at a network security scanner using a first scanning privilege level, the respective network-connected asset. The method includes determining, based on the scan using the first scanning privilege level, whether the respective network-connected asset has a vulnerability. In response, the method includes scanning, at the network security scanner using a second scanning privilege level, the respective network-connected asset. The second scanning privilege level defines a lower level of access the network security scanner has than the first scanning privilege level. The method includes determining, based on the scans, an exposure level of the vulnerability. The method includes reporting the exposure level of the vulnerability to a user of the respective network-connected asset.

Abstract: This document generally describes systems and methods for dynamically adapting speech recognition for individual voice queries of a user using class-based language models. The method may include receiving a voice query from a user that includes audio data corresponding to an utterance of the user, and context data associated with the user. One or more class models are then generated that collectively identify a first set of terms determined based on the context data, and a respective class to which the respective term is assigned for each respective term in the first set of terms. A language model that includes a residual unigram may then be accessed and processed for each respective class to insert a respective class symbol at each instance of the residual unigram that occurs within the language model. A transcription of the utterance of the user is then generated using the modified language model.

Abstract: This document describes techniques and devices for a radar recognition-aided search. Through use of a radar-based recognition system, gestures made by, and physiological information about, persons can be determined. In the case of physiological information, the techniques can use this information to refine a search. For example, if a person requests a search for a coffee shop, the techniques may refine the search to coffee shops in the direction that the person is walking. In the case of a gesture, the techniques may refine or base a search solely on the gesture. Thus, a search for information about a store, car, or tree can be made responsive to a gesture pointing at the store, car, or tree with or without explicit entry of a search query.

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: 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: 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: 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 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: 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: The various implementations described herein include methods, devices, and systems for monitoring activity in a home environment. In one aspect, a method performed at a voice-assistant device includes: detecting a sound; obtaining a determination as to whether the sound meets one or more monitoring criteria; and in accordance with a determination that the sound meets the one or more monitoring criteria, generating a notification.

Abstract: An electronic device receives a first plurality of images of a scene captured by an image sensor of an electronic device, receives an ambient light level proximate to the electronic device, and determines whether the ambient light level is less than a first threshold value. In accordance with a determination that the ambient light level is less than the first threshold value, the electronic device detects motion in the scene based on one or more of the first plurality of images. In accordance with detecting motion in the scene, the electronic device receives a second plurality of images of the scene captured by the image sensor of the electronic device, forms a composite image from two or more of the second plurality of images, and causes the composite image to be presented for display on a user device.

Abstract: A method for representing an intended prosody in synthesized speech includes receiving a text utterance having at least one word, and selecting an utterance embedding for the text utterance. Each word in the text utterance has at least one syllable and each syllable has at least one phoneme. The utterance embedding represents an intended prosody. For each syllable, using the selected utterance embedding, the method also includes: predicting a duration of the syllable by decoding a prosodic syllable embedding for the syllable based on attention by an attention mechanism to linguistic features of each phoneme of the syllable and generating a plurality of fixed-length predicted frames based on the predicted duration for the syllable.

Abstract: Techniques and apparatuses are described for integrated access backhaul with an adaptive phase-changing device (APD) are described. In aspects, a donor base station determines to include an APD in a communication path for the wireless backhaul link with a node base station and apportions APD access to the APD for the node base station. The donor base station then communicates with the node base station using the surface of the APD and based on the apportioned APD-access by using the surface to exchange wireless signals with the donor base station.

Abstract: A method of storing semi-structured data includes receiving user data from a user of a query system where the user data includes semi-structured user data. The method also includes receiving an indication that the semi-structured user data fails to include a fixed schema. In response to the indication that the semi-structured user data fails to include the fixed schema, the method further includes parsing the semi-structured user data into a plurality of data paths and extracting a data type associated with each respective data path of the plurality of data paths. The method additionally includes storing the semi-structured user data as a row entry in a table of a database in communication with the query system wherein each column value associated with the row entry corresponds to a respective one of the plurality of data paths and the data type associated with the respective data path.

Abstract: A pin fin placement assembly utilized to form pin fins in a thermal dissipating feature is provided. The pin fin placement assembly may place the pin fins on an IC die disposed in the IC package. The pin fin placement assembly may assist massively placing the pin fins with desired profiles and numbers on desired locations of the IC die. The plurality of pin fins is formed in a first plurality of apertures in the pin fin placement assembly. A thermal process is then performed to solder the plurality of pin fins on the IC die.

Abstract: This document describes methods implemented by and systems utilizing an alternating-current (AC) power-switching device. The AC power-switching device includes first and second current input/output (I/O) nodes, a current-limiting resistor, and a bypass switch connected between the first and second current I/O nodes. The bypass switch includes a first light-emitting-diode-input normally closed solid-state relay. Further, the AC power-switching device includes a rectifier, a voltage regulator, and a controller. The controller includes a programmable controller chip and is configured to detect a voltage level at the output of the rectifier, activate the bypass switch in response to the voltage level exceeding a first voltage level threshold, set a first lockout timer in response to activating the bypass switch, and deactivate the bypass switch in response to the voltage level dropping below a second voltage level threshold.

Abstract: This document generally describes systems, methods, devices, and other techniques related to speaker verification, including (i) training a neural network for a speaker verification model, (ii) enrolling users at a client device, and (iii) verifying identities of users based on characteristics of the users' voices. Some implementations include a computer-implemented method. The method can include receiving, at a computing device, data that characterizes an utterance of a user of the computing device. A speaker representation can be generated, at the computing device, for the utterance using a neural network on the computing device. The neural network can be trained based on a plurality of training samples that each: (i) include data that characterizes a first utterance and data that characterizes one or more second utterances, and (ii) are labeled as a matching speakers sample or a non-matching speakers sample.

Abstract: A method for training a streaming automatic speech recognition student model includes receiving a plurality of unlabeled student training utterances. The method also includes, for each unlabeled student training utterance, generating a transcription corresponding to the respective unlabeled student training utterance using a plurality of non-streaming automated speech recognition (ASR) teacher models. The method further includes distilling a streaming ASR student model from the plurality of non-streaming ASR teacher models by training the streaming ASR student model using the plurality of unlabeled student training utterances paired with the corresponding transcriptions generated by the plurality of non-streaming ASR teacher models.

Abstract: A method includes processing, using a speech recognizer, a first portion of audio data to generate a first lattice, and generating a first partial transcription for an utterance based on the first lattice. The method includes processing, using the recognizer, a second portion of the data to generate, based on the first lattice, a second lattice representing a plurality of partial speech recognition hypotheses for the utterance and a plurality of corresponding speech recognition scores. For each particular partial speech recognition hypothesis, the method includes generating a corresponding re-ranked score based on the corresponding speech recognition score and whether the particular partial speech recognition hypothesis shares a prefix with the first partial transcription.

Abstract: A device may identify a plurality of sources for outputs that the device is configured to provide. The plurality of sources may include at least one of a particular application in the device, an operating system of the device, a particular area within a display of the device, or a particular graphical user interface object. The device may also assign a set of distinct voices to respective sources of the plurality of sources. The device may also receive a request for speech output. The device may also select a particular source that is associated with the requested speech output. The device may also generate speech having particular voice characteristics of a particular voice assigned to the particular source.

Abstract: A method includes receiving an automated speech recognition (ASR) request from a user device that includes a speech input captured by the user device and content metadata associated with the speech input. The content metadata is generated by the user device. The method also includes determining a priority score for the ASR request based on the content metadata associated with the speech input and caching the ASR request in a pre-processing backlog of pending ASR requests each having a corresponding priority score. The pending ASR requests in the pre-processing backlog are ranked in order of the priority scores. The method also includes providing, from the pre-processing backlog, one or more of the pending ASR requests to a backend-side ASR module, wherein pending ASR requests associated with higher priority scores are processed before pending ASR requests associated with lower priority scores.

Abstract: Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing angular position estimation. A machine-learned module analyzes complex range data generated to estimate angular positions of objects. The machine-learned module is implemented using a multi-stage architecture. In a local stage, the machine-learned module splits the complex range data into different range intervals and separately processes subsets of the complex range data using individual branch modules. In a global stage, the machine-learned module merges the feature data generated from the individual branch modules using a symmetric function and generates angular position data. By using machine-learning techniques and processing the complex range data directly, the radar system can achieve higher angular resolutions compared to other radar systems that utilize other techniques, such as analog or digital beamforming.

Abstract: A single E2E multitask model includes a speech recognition model and an endpointer model. The speech recognition model includes an audio encoder configured to encode a sequence of audio frames into corresponding higher-order feature representations, and a decoder configured to generate probability distributions over possible speech recognition hypotheses for the sequence of audio frames based on the higher-order feature representations. The endpointer model is configured to operate between a VAD mode and an EOQ detection mode. During the VAD mode, the endpointer model receives input audio frames, and determines, for each input audio frame, whether the input audio frame includes speech. During the EOQ detection mode, the endpointer model receives latent representations for the sequence of audio frames output from the audio encoder, and determines, for each of the latent representation, whether the latent representation includes final silence.

Abstract: A method includes receiving training data that includes a set of unspoken textual utterances. For each respective unspoken textual utterance, the method includes, tokenizing the respective textual utterance into a sequence of sub-word units, generating a first higher order textual feature representation for a corresponding sub-word unit tokenized from the respective unspoken textual utterance, receiving the first higher order textual feature representation generated by a text encoder, and generating a first probability distribution over possible text units. The method also includes training an encoder based on the first probability distribution over possible text units generated by a first-pass decoder for each respective unspoken textual utterance in the set of unspoken textual utterances.

Abstract: A method includes receiving training data that includes unspoken textual utterances in a target language. Each unspoken textual utterance not paired with any corresponding spoken utterance of non-synthetic speech. The method also includes generating a corresponding alignment output for each unspoken textual utterance using an alignment model trained on transcribed speech utterance in one or more training languages each different than the target language. The method also includes generating a corresponding encoded textual representation for each alignment output using a text encoder and training a speech recognition model on the encoded textual representations generated for the alignment outputs. Training the speech recognition model teaches the speech recognition model to learn how to recognize speech in the target language.

Abstract: Systems and techniques are provided for determination of user presence and absence using WiFi connections. Reports may be received from WiFi access points in an environment. The reports may include an identifier of a WiFi device, an indication of a connection to or disconnection from a WiFi access point, a time of the connection or disconnection, and an identifier of the WiFi access point. A connection sequence for the WiFi device may be generated from the reports. Whether the WiFi device is present in or absent from the environment as of a specified time may be determined based on the connection sequence. An indication of presence for a user associated with the WiFi device may generated if the WiFi device is present in the environment. An indication of absence for the user associated with the WiFi device may be generated if the WiFi device is absent from the environment.

Abstract: A speaker verification method includes receiving audio data corresponding to an utterance, processing the audio data to generate a reference attentive d-vector representing voice characteristics of the utterance, the evaluation ad-vector includes ne style classes each including a respective value vector concatenated with a corresponding routing vector. The method also includes generating using a self-attention mechanism, at least one multi-condition attention score that indicates a likelihood that the evaluation ad-vector matches a respective reference ad-vector associated with a respective user. The method also includes identifying the speaker of the utterance as the respective user associated with the respective reference ad-vector based on the multi-condition attention score.

Abstract: A method includes generating a first asset token that represents control, by a first entity, of a portion of a physical communication asset. The method includes publishing, to a distributed ledger, ownership of the first asset token and receiving, from a second entity, a request to control the portion of the physical communication asset represented by the first asset token. In response to receiving the request, the method includes removing the first asset token from circulation on the distributed ledger and generating a second asset token representing control, by the second entity, of the portion of the physical communication asset. The method also includes publishing, to the distributed ledger, ownership of the second asset token and transferring, using the distributed ledger, ownership of the second asset token to the second entity.

Abstract: A method includes obtaining a dataset that includes health data in a Fast Healthcare Interoperability Resources (FHIR) standard. The health data includes a plurality of healthcare events. The method includes generating, using the dataset, an events table that includes the plurality of healthcare events and is indexed by time and a unique identifier per patient encounter. The method also includes generating, using the dataset, a traits table that includes static data and is indexed by the unique identifier per patient encounter. The method includes training a machine learning model using the events table and the traits table and predicting, using the trained machine learning model and one or more additional healthcare events associated with a patient, a health outcome for the patient.

Abstract: A method for arbitrarily grouping computer system resources includes receiving a resource policy to be applied to a group of resources associated with a user. The resource policy includes a unique user-defined label assigned to each resource of the group of resources. The method also includes identifying the group of resources among a plurality of resources using the user-defined label. Here, the plurality of resources is associated with the user and distributed across a plurality of different computing environments. For each identified resource of the group of resources, the method also includes applying the resource policy to a corresponding identified resource by accessing the respective computing environment where the corresponding identified resource resides.

Abstract: Methods, systems, and apparatus for data analysis in a distributed computing system by accessing data stored at a first processing zone associated with a distributed data processing job, detecting information identifying a particular child job associated with the distributed data processing job, comparing the identifying information to data stored at a second processing zone, and identifying an additional child job as associated with the distributed data processing job based on a result of the comparison. The methods, systems and apparatus are further for correlating particular output data associated with the particular child job and additional output data associated with the additional child job for the distributed data processing job, determining performance data for the distributed data processing job based on the output data associated with each of the particular child job and the additional child job, and providing for display the performance data for the distributed data processing job.

Abstract: A method for training a sub-model for contextual biasing for speech recognition includes obtaining a base speech recognition model trained on non-biased data. The method includes obtaining a set of training utterances representative of a particular domain, each training utterance in the set of training utterances including audio data characterizing the training utterances and a ground truth transcription of the training utterance. The method further includes, for each corresponding training utterance in the set of training utterances, determining, using an embedding encoder, a corresponding document embedding from the ground truth transcription of the corresponding training utterance. The method includes training, using the corresponding document embeddings determined from the ground truth transcriptions of the set of training utterances, a sub-model to bias the base speech recognition model to recognize speech in the particular domain.

Abstract: The subject matter of the present disclosure can be implemented by, among other things, a remote control device configured to receive an identifier, present a plurality of controllable devices for selection on a display of the remote control device, and receive a selection of two or more controllable devices via the user interface. Using the identifier, a session with the two or more controllable devices is generated and performances of a same task by the two or more controllable devices are controlled by the remote control device by transmitting a message containing control information and the identifier to a network service.

Abstract: Techniques and apparatuses are described for resource block-level index modulation. In aspects, a wireless transmitter modulates a first portion of data for a wireless receiver to provide modulation symbols that correspond to the first portion of the data. The wireless transmitter also selects, based on a value of a second portion of the data, respective index locations for one or more resource blocks by which to transmit the modulation symbols. The wireless transmitter then transmits the modulation symbols to the wireless receiver using the one or more resource blocks having the respective index locations to convey the first portion of the data and the second portion of the data to the wireless receiver. By so doing, the wireless transmitter conveys the second portion of the data without using additional time-frequency resources of a communication channel, which can be useful when concurrently transmitting small amounts of data to many wireless receivers.

Abstract: This document describes systems and techniques directed at an external wide-angle lens for imagers in electronic devices. An imager is disclosed that includes an image sensor and a lens stack, the lens stack including an external wide-angle lens, an internal lens, and four or more intermediate lenses. The imager has a first ratio of a projection at a vertex of the external wide-angle lens divided by a maximum focused dimension of the focal area being less than or equal to 0.15, a second ratio of a total length of the lens stack divided by the maximum focused dimension being less than or equal to 7.0, or a third ratio of a total transmission length of the imager divided by an entrance pupil diameter of the external wide-angle lens being between 1.2 and 2.6.

Abstract: The described techniques and apparatuses enable memory-request priority up-leveling. A memory request is received over a virtual channel, VC, and is then added to a memory-request buffer with an original priority-level for the memory request and an indication that the memory request is associated with a virtual channel identification, VCID, of the VC. Related memory requests within the memory-request buffer are also indicated as being associated with the VCID. Responsive to determining that an up-level indication for the VCID is asserted over a side channel, the original priority-levels of the memory request, and other memory-requests in the memory-request buffer having an indication of the VCID, are increased to respective up-leveled priority levels. Responsive to determining that the up-level indication is no longer asserted, the up-leveled priority levels are returned to respective original priority-levels.

Abstract: This document describes techniques for flexible frequency band pairing for satellite communications. In aspects, a non-terrestrial communication system uses multiple frequency bands for a wireless link between a user equipment, UE, and a satellite of the non-terrestrial communication system. The non-terrestrial communication system determines to utilize two different frequency bands the wireless link between the satellite and the UE, the two different frequency bands being defined by a governing entity. In response, the non-terrestrial based communication system selects a first defined frequency band for downlink communications from the satellite to the UE and a second defined frequency band for uplink communications from the UE to the satellite. The non-terrestrial communication system then directs the satellite and the UE to communicate via the wireless link by using the first defined frequency band for the downlink communications and the second defined frequency band for the uplink communications.

Abstract: A method includes receiving a build request containing build step instructions from a user. The build step instructions specify a usage of containers within memory hardware for building an output container. The containers include at least one private container having private contents and/or at least one public container having public contents. The method also includes authenticating the user initiating the build request and determining whether the user is authorized to access the private containers. When the user is authenticated and authorized to access the private containers, the method includes obtaining the containers specified by the build step instructions from the memory hardware, executing the build step instructions to build the output container while using the received containers, and outputting the built output container.

Abstract: A method includes receiving follow-on audio data captured by an assistant-enabled device, the follow-on audio data corresponding to a follow-on query spoken by a user of the assistant-enabled device to a digital assistant subsequent to the user submitting a previous query to the digital assistant. The method also includes processing, using a speech recognizer, the follow-on audio data to generate multiple candidate hypotheses, each candidate hypothesis corresponding to a candidate transcription for the follow-on query and represented by a respective sequence of hypothesized terms. For each corresponding candidate hypothesis among the multiple candidate hypotheses, the method also includes determining a corresponding similarity metric between the previous query and the corresponding candidate hypothesis and determining a transcription of the follow-on query spoken by the user based on the similarity metrics determined for the multiple candidate hypotheses.

Abstract: This disclosure describes methods, devices, systems, and procedures in a computing system for capturing a configuration state of an operating system executing on a central processing unit (CPU), and offloading resource-related tasks, based on the configuration state, to a resource management unit such as a system-on-chip (SoC). The resource management unit identifies a status of each resource based on the captured configuration state of the operating system. The resource management unit then processes tasks associated with the status of the resources, such as modifying a clock rate of a clocked component in the computing system. This can alleviate the CPU from processing those tasks thereby improving overall computing system performance and dynamics.

Abstract: A method for multi-channel voice activity detection includes receiving a sequence of input frames characterizing streaming multi-channel audio captured by an array of microphones. Each channel of the streaming multi-channel audio includes respective audio features captured by a separate dedicated microphone. The method also includes determining, using a location fingerprint model, a location fingerprint indicating a location of a source of the multi-channel audio relative to the user device based on the respective audio features of each channel of the multi-channel audio. The method also includes generating an output from an application-specific classifier. The first score indicates a likelihood that the multi-channel audio corresponds to a particular audio type that the particular application is configured to process.

Abstract: This application is directed to a method for correct temperature measurement. An electronic device includes a temperature sensor that measures an ambient temperature of an environment and a display that is driven by a display driver. The electronic device determines a brightness setting of the display, estimates a display driver current based on the brightness setting, estimates a driver efficiency of the display driver based on the display driver current, and combines a predetermined display driver voltage, the display driver current, and the driver efficiency to determine a power consumption of the display driver. An ambient temperature correction is determined in accordance with the determined power consumption of the display driver, and the measured ambient temperature is thereby corrected using the ambient temperature correction. In some implementations, a power consumption of a distinct heat-generating electronic component is also monitored for adjusting the ambient temperature correction.

Abstract: Techniques and apparatuses are described for intra-user equipment-coordination set (intra-UECS) communication via an adaptive phase-changing device (APD) are described. In aspects, a base station selects an APD for use by a first user equipment-coordination set, UECS), in an intra-UECS communication path. The base station communicates APD information about the APD to a first coordinating user equipment, UE, of the first UECS. In aspects, the base station the apportions APD-access to the APD for the first UECS and indicates the apportioned APD-access to the first coordinating UE of the first UECS.

Abstract: In aspects, a non-terrestrial communication system communicates with a user equipment, UE, using repetitive communications. The non-terrestrial communication system determines (905, 940) a repetition configuration for repetitive communications with the UE and indicates (910, 915) the repetition configuration to the UE. The non-terrestrial communication system communicates (920) with the UE using the repetitive communications in accordance with the repetition configuration.

Abstract: A method includes obtaining a corpus of unlabeled training data including a plurality of spoken utterances, each corresponding spoken utterance of the plurality of spoken utterances includes audio data characterizing the corresponding spoken utterance. The method also includes receiving a target domain. The method also includes selecting, using a contrastive data selection model, a subset of the utterances from the corpus of unlabeled training data that correspond to the target domain. The method includes training an automatic speech recognition (ASR) model on the subset of utterances.

Abstract: This document describes systems and techniques for modulating credit allocations in memory subsystems. The described systems and techniques can provide a feedback mechanism to a credit controller to improve the bandwidth at a memory interface. The memory controller monitors statistics associated with transaction requests served to one or more random access memories (RAMs) of the memory subsystem. The memory controller can then provide suggestions to the credit controller or to the one or more clients to modulate the number of credits allocated to one or more clients. In this way, the described systems and techniques can improve the efficiency of the memory controller in managing the transaction requests and the bandwidth at the memory interface.