Systems and methods for augmented-reality tutoring can utilize optical character recognition, natural language processing, and/or augmented-reality rendering for providing real-time notifications for completing a determined task. The systems and methods can include utilizing one or more machine-learned models trained for quantitative reasoning and can include providing a plurality of different user interface elements at different times.
G09B 7/04 - Dispositifs ou appareils d'enseignement à commande électrique procédant par questions et réponses du type où l'élève doit donner une réponse à la question posée, ou bien où la machine donne une réponse à la question posée par l'élève caractérisés par une modification du programme d'enseignement à la suite d'une réponse erronée, p.ex. en répétant la question, en fournissant des explications supplémentaires
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p.ex. glissement, rotation, agrandissement ou changement de couleur
G06T 11/60 - Edition de figures et de texte; Combinaison de figures ou de texte
G06V 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06V 20/70 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène Étiquetage du contenu de scène, p.ex. en tirant des représentations syntaxiques ou sémantiques
G06V 30/12 - Détection ou correction d’erreurs, p.ex. en effectuant une deuxième exploration du motif
G06V 30/19 - Reconnaissance utilisant des moyens électroniques
2.
Securely Provisioning Secrets in Authentication Devices
The present disclosure provides for increased security of root of trust (RoT) chips by preventing malicious provisioning. Unique device secrets (UDS) can only be provisioned securely by trustworthy hardware or trustworthy firmware. Entities other than the trustworthy hardware and trustworthy firmware do not have access to a composite device identifier (CDI) generated using the UDS and firmware measurements.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 21/44 - Authentification de programme ou de dispositif
3.
Virtual Channel Balancing In Ring-Based Topologies
Systems and method for routing data packets in ring network. A data packet being transmitted to a destination node may be received by a first structure at a first node. The first node may determine a number of hops the data packet will traverse as it is transmitted from the first node to the destination node and compare the determined number of hops to a threshold hop value to determine whether the number of hops is equal to or less than the threshold hop value. If the number of hops is greater than the threshold, the data packet may be transmitted to a dimension queuing structure for a first virtual channel within a second node, otherwise, the data packet may be transmitted to a dimension queuing structure for a second virtual channel or a turn queuing structure within the second node.
H04L 45/00 - Routage ou recherche de routes de paquets dans les réseaux de commutation de données
H04L 49/102 - TRANSMISSION D'INFORMATION NUMÉRIQUE, p.ex. COMMUNICATION TÉLÉGRAPHIQUE Éléments de commutation de paquets caractérisés par la construction de la matrice de commutation en utilisant un support partagé, p.ex. un bus ou un anneau
4.
Mechanism for Precise Time Synchronization in a Datacenter Network
Aspects of the disclosure are directed to supporting time synchronization across a datacenter network with greater accuracy. The time synchronization includes both software based and hardware based time synchronization mechanisms to provide more precise time synchronization across various nodes in the datacenter network. The software based mechanism can provide the initial coarse time synchronization while the hardware based mechanism can provide the subsequent finer time synchronization.
An example device (204) includes a wireless charging receive coil (222) configured to transduce, into an alternating current—AC—power signal, a magnetic field generated by a wireless charging transmit coil (218) of an external device (202); an active rectifier (224) configured to convert the AC signal into a direct current—DC—power signal; and circuitry (226) configured to: obtain a target level of the DC power signal; and control the active rectifier (224) to output the DC power signal with the target level.
H02J 50/10 - Circuits ou systèmes pour l'alimentation ou la distribution sans fil d'énergie électrique utilisant un couplage inductif
H02J 50/40 - Circuits ou systèmes pour l'alimentation ou la distribution sans fil d'énergie électrique utilisant plusieurs dispositifs de transmission ou de réception
H02M 7/219 - Transformation d'une puissance d'entrée en courant alternatif en une puissance de sortie en courant continu sans possibilité de réversibilité par convertisseurs statiques utilisant des tubes à décharge avec électrode de commande ou des dispositifs à semi-conducteurs avec électrode de commande utilisant des dispositifs du type triode ou transistor exigeant l'application continue d'un signal de commande utilisant uniquement des dispositifs à semi-conducteurs dans une configuration en pont
6.
Knowledge Distillation with Domain Mismatch For Speech Recognition
A method includes receiving distillation data including a plurality of out-of-domain training utterances. For each particular out-of-domain training utterance of the distillation data, the method includes generating a corresponding augmented out-of-domain training utterance, and generating, using a teacher ASR model trained on training data corresponding to a target domain, a pseudo-label corresponding to the corresponding augmented out-of-domain training utterance. The method also includes distilling a student ASR model from the teacher ASR model by training the student ASR model using the corresponding augmented out-of-domain training utterances paired with the corresponding pseudo-labels generated by the teacher ASR model.
G10L 15/06 - Création de gabarits de référence; Entraînement des systèmes de reconnaissance de la parole, p.ex. adaptation aux caractéristiques de la voix du locuteur
G10L 15/197 - Grammaires probabilistes, p.ex. n-grammes de mots
G10L 15/30 - Reconnaissance distribuée, p.ex. dans les systèmes client-serveur, pour les applications en téléphonie mobile ou réseaux
An optical links diagnostic system (LDS) and its operation within an optical circuit switch (OCS) for measurement and diagnosis of fiber-optic network fiber performance and quality is disclosed. The LDS can contain two photodetectors, a laser source, and be coupled to an OCS. Optical circulators can further be linked to the OCS. The LDS can be used both as an optical time domain reflectometer (OTDR) or as an optical return loss (ORL) meter and can automate the diagnosis of the fiber optical network fiber insertion loss and return loss.
H04Q 11/00 - Dispositifs de sélection pour systèmes multiplex
G02B 6/35 - Moyens de couplage optique comportant des moyens de commutation
G02B 26/08 - Dispositifs ou dispositions optiques pour la commande de la lumière utilisant des éléments optiques mobiles ou déformables pour commander la direction de la lumière
H04B 10/071 - Dispositions pour la surveillance ou le test de systèmes de transmission; Dispositions pour la mesure des défauts de systèmes de transmission utilisant un signal réfléchi, p.ex. utilisant des réflectomètres optiques temporels [OTDR]
H04B 10/079 - Dispositions pour la surveillance ou le test de systèmes de transmission; Dispositions pour la mesure des défauts de systèmes de transmission utilisant un signal en service utilisant des mesures du signal de données
8.
METHODS, SYSTEMS, AND MEDIA FOR ADAPTIVE PRESENTATION OF A VIDEO CONTENT ITEM BASED ON AN AREA OF INTEREST
A method for adaptive presentation of media content includes receiving a first version of a video content item, causing the first version of the video content item to be presented within a video viewport having first dimensions, receiving user input indicating a user request to change first dimensions of the video viewport to second dimensions, determining an area of interest in the video content item, wherein the area of interest is included in a frame of the video content item, generating, based on the second dimensions of the video viewport and the area of interest in a frame of the video content item, a second version of the video content item for presentation on a user device, and causing the second version of the video content item to be presented within the video viewport having the second dimensions on the user device, wherein the area of interest is placed differently within the frame in the second version of the video content item relative to the first version of the video content item.
G06V 20/40 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène dans le contenu vidéo
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport
Techniques and apparatuses are described for machine-learning architectures for broadcast and multicast communications. A network entity processes broadcast or multicast communications using a deep neural network (DNN) to direct the one or more broadcast or multicast communications to a targeted group of user equipments (UEs) using the wireless communication system. The network entity receives feedback from at least one user equipment (UE) of the targeted group of UEs. The network entity determines a modification to the DNN based on the feedback. The network entity transmits an indication of the modification to the targeted group of UEs. The network entity updates the DNN with the modification to form a modified DNN. The network entity processes the broadcast or multicast communications using the modified DNN to direct the broadcast or multicast communications to the targeted group of UEs using the wireless communication system.
This application is directed to a method for controlling user experience (UX) operations on an electronic device that executes an application. A touchless UX operation associated with the application has an initiation condition including at least detection of a presence and a gesture in a required proximity range with a required confidence level. The electronic device then determines from a first sensor signal the proximity of the presence with respect to the electronic device. In accordance with a determination that the determined proximity is in the required proximity range, the electronic device determines from a second sensor signal a gesture associated with the proximity of the presence and an associated confidence level of the determination of the gesture. In accordance with a determination that the determined gesture and associated confidence level satisfy the initiation condition, the electronic device initializes the touchless UX operation associated with the application.
Systems and methods provides for dialog management in real-time rather than turn taking. An example method included generating first candidate responses to triggering event. The triggering event may be receipt of a live stream chunk for the dialog or receipt of a backend response to a previous backend request for a dialog shema. The method also includes updating a list of candidate responses that are accepted or pending with at least on of the first candidate responses, and determining, for the triggering event, whether the list of candidate responses includes a candidate response that has a confidence score that meets a triggering threshold. The method also includes waiting for a next triggering event without providing a candidate response when the list does not include a candidate response that has a confidence score that meets the triggering threshold.
Disclosed is the technology for computer-based “Daily Brief” service, which includes methods and corresponding systems for proactively providing push notifications for users of chat information systems. The push notifications are dynamically generated and presented to the user based on identification of one or more triggering events, which may include predetermined time/date, current geographical location, activity of peers and friends in social media associated with the user, scheduled events, appointments, meetings, emails, instant messages, and many more. The described technology improves the interaction interface between the user and chat information system.
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p.ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p.ex. des réponses automatiques ou des messages générés par un agent conversationnel
13.
Automatic Generation of Training and Testing Data for Machine-Learning Models
Provided are computing systems, methods, and platforms for generating training and testing data for machine-learning models. The operations can include receiving signal extraction information that has instructions to query a data store. Additionally, the operations can include accessing, using Structured Query Language (SQL) code generated based on the signal extraction information, raw data from the data store. Moreover, the operations can include processing the raw data using signal configuration information to generate a plurality of signals. The signal configuration information can have instructions on how to generate the plurality of signals from the raw data. Furthermore, the operations can include joining, using SQL code, the plurality of signals with a first label source to generate training data and testing data. Subsequently, the operations can include processing the training data and the testing data to generate the input data. The input data being an ingestible for a machine-learning pipeline.
Implementations utilize deep reinforcement learning to train a policy neural network that parameterizes a policy for determining a robotic action based on a current state. Some of those implementations collect experience data from multiple robots that operate simultaneously. Each robot generates instances of experience data during iterative performance of episodes that are each explorations of performing a task, and that are each guided based on the policy network and the current policy parameters for the policy network during the episode. The collected experience data is generated during the episodes and is used to train the policy network by iteratively updating policy parameters of the policy network based on a batch of collected experience data. Further, prior to performance of each of a plurality of episodes performed by the robots, the current updated policy parameters can be provided (or retrieved) for utilization in performance of the episode.
G05B 13/02 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
G05B 19/042 - Commande à programme autre que la commande numérique, c.à d. dans des automatismes à séquence ou dans des automates à logique utilisant des processeurs numériques
G06N 3/008 - Vie artificielle, c. à d. agencements informatiques simulant la vie fondés sur des entités physiques commandées par une intelligence simulée de manière à reproduire des formes de vie intelligentes, p.ex. fondés sur des robots reproduisant les animaux ou les humains dans leur apparence ou leur comportement
Techniques described herein describe aspects of signal adjustments in user equipment-coordination set, UECS, joint transmissions. A base station analyzes a first joint transmission from multiple user equipments, UEs, participating in a UECS, where the multiple UEs include a coordinating UE of the UECS and at least one non-coordinating UE participating in the UECS. The base station determines that the first joint transmission fails to meet a performance metric and directs the multiple UEs participating in the UECS to add signal adjustments to a second joint transmission.
H04B 7/024 - Utilisation coopérative d’antennes sur plusieurs sites, p.ex. dans les systèmes à plusieurs points coordonnés ou dans les systèmes coopératifs à "plusieurs entrées plusieurs sorties" [MIMO]
H04B 7/06 - Systèmes de diversité; Systèmes à plusieurs antennes, c. à d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
16.
METHODS AND SYSTEMS FOR NON-DESTRUCTIVE STABILIZATION-BASED ENCODER OPTIMIZATION
A video item that is subject to one or more motion stabilization transformations applied to the video item is identified. The one or more motion stabilization transformations pertain to a motion between video frames of a video sequence associated with the video item. One or more operations to modify the one or more motion stabilization transformations applied to the video item are determined. The one or more operations to modify the motion stabilization transformations are performed. The video item is provided for playback via a client device. Playback of the video item depicts at least a portion of the motion between the video frames of the video sequence.
H04N 19/65 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant la tolérance aux erreurs
H04N 19/60 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant un codage par transformée
17.
Recalibrating Gamma Curves for Seamless Transitions in Multiple Display Refresh Rates
A method involves measuring, for an optical property of the display panel for an input gray level and at a first refresh rate, first and second values at respective first and second ambient brightness levels. The method also involves determining a compensation factor for the input gray level at the first refresh rate. The method further involves determining a modified gamma value at a second refresh rate, wherein the modified gamma value reduces a perceived optical defect of the display panel when operating at the second refresh rate by maintaining a consistent delta difference in values for the optical property between the first and second refresh rates at different ambient brightness levels. The method additionally involves storing the modified gamma value, where the device is configured to adjust input display data using the modified gamma value when transitioning from the first refresh rate to the second refresh rate.
G09G 3/20 - Dispositions ou circuits de commande présentant un intérêt uniquement pour l'affichage utilisant des moyens de visualisation autres que les tubes à rayons cathodiques pour la présentation d'un ensemble de plusieurs caractères, p.ex. d'une page, en composant l'ensemble par combinaison d'éléments individuels disposés en matrice
18.
CONVERSATION-AWARE PROACTIVE NOTIFICATIONS FOR A VOICE INTERFACE DEVICE
A method for proactive notifications in a voice interface device includes: receiving a first user voice request for an action with an future performance time; assigning the first user voice request to a voice assistant service for performance; subsequent to the receiving, receiving a second user voice request and in response to the second user voice request initiating a conversation with the user; and during the conversation: receiving a notification from the voice assistant service of performance of the action; triggering a first audible announcement to the user to indicate a transition from the conversation and interrupting the conversation; triggering a second audible announcement to the user to indicate performance of the action; and triggering a third audible announcement to the user to indicate a transition back to the conversation and rejoining the conversation.
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p.ex. dialogue homme-machine
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
H04L 12/28 - Réseaux de données à commutation caractérisés par la configuration des liaisons, p.ex. réseaux locaux [LAN Local Area Networks] ou réseaux étendus [WAN Wide Area Networks]
H04L 51/224 - Surveillance ou traitement des messages en fournissant une notification sur les messages entrants, p.ex. des poussées de notifications des messages reçus
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for post-hoc deferral for classification tasks. In particular, a system can perform either post-hoc threshold correction or post-hoc rejector training to account for the cost of deferring model inputs to an expert system for classification.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for handing off a user conversation between computer-implemented agents. One of the methods includes receiving, by a computer-implemented agent specific to a user device, a digital representation of speech encoding an utterance, determining, by the computer-implemented agent, that the utterance specifies a requirement to establish a communication with another computer-implemented agent, and establishing, by the computer-implemented agent, a communication between the other computer-implemented agent and the user device.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
G10L 13/00 - Synthèse de la parole; Systèmes de synthèse de la parole à partir de texte
G10L 13/033 - Procédés d'élaboration de parole synthétique; Synthétiseurs de parole Édition de voix, p.ex. transformation de la voix du synthétiseur
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p.ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
G10L 15/30 - Reconnaissance distribuée, p.ex. dans les systèmes client-serveur, pour les applications en téléphonie mobile ou réseaux
Systems and methods for automatically associating content characteristics to a third-party content are provided. A uniform resource locator identifying a resource is received from a content provider. The content is rendered to produce an object tree. A first node of the object tree is determined, where the first node represents a content slot. A second node of the object tree proximate to the first node is identified. The second node has a content characteristic, which is extracted. The extracted content characteristic is associated with the first node and stored.
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p.ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
The present disclosure relates to a streaming speech-to-speech conversion model, where an encoder runs in real time while a user is speaking, then after the speaking stops, a decoder generates output audio in real time. A streaming-based approach produces an acceptable delay with minimal loss in conversion quality when compared to other non-streaming server-based models. A hybrid model approach for combines look-ahead in the encoder and a non-causal stacker with non-causal self-attention.
G06F 40/58 - Utilisation de traduction automatisée, p.ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la parole; Sélection d'unités de reconnaissance
G10L 15/30 - Reconnaissance distribuée, p.ex. dans les systèmes client-serveur, pour les applications en téléphonie mobile ou réseaux
G10L 19/032 - Quantification ou dé-quantification de composantes spectrales
23.
Adaptive Public Land Mobile Network Management for Varying Network Conditions
The present disclosure describes apparatuses and techniques of adaptive PLMN management for varying network conditions. In some aspects, a PLMN manager of a user equipment (UE) searches, as part of a registration procedure, a data repository of PLMN information that includes a PLMN blocked from registration for a duration of time and determines that the PLMN is blocked due to a signal-related condition with a cell of the PLMN (e.g., weak signal). The PLMN manager then determines, during the duration of time, that the signal-related condition between the UE and the cell has improved. In response to the improvement, the PLMN manager unblocks the PLMN before expiration of the duration of time. By so doing, the UE may reattempt registration with the unblocked PLMN at least once before the duration of time expires, which may allow the UE to register more quickly and reestablish network services.
Provided are computing systems, methods, and platforms for a discrete-valued output classification. The operations can include obtaining a candidate threshold value for a first slice in a plurality of data slices. Additionally, the operations can include calculating, using a candidate machine-learned model and the candidate threshold value, a first performance value associated with a first risk tolerance value. Moreover, the operations can include determining, based on the first performance value, that a safeguard criterion for the first slice has not been satisfied. In response to the determination that the safeguard criterion for the first slice has not been satisfied, the operations can include performing a tradeoff logic operation to determine the final threshold value. Subsequently, the operations can include determining, using the candidate machine-learned model, whether input data is authentic based on the final threshold value.
An augmented-reality (AR) eyewear display utilizes an optical waveguide having multi-layered optical gratings in a repeating arrangement. The optical gratings include varying depths, slope angles, lengths, and/or widths in order to tune the gratings to provide an improved AR eyewear display. By using the different configurations of two-dimensional or three-dimensional gratings disclosed herein in a waveguide of an AR eyewear display, optical characteristics of the waveguide are optimized to provide, e.g., high resolution and/or contrast, high display uniformity, high input coupling efficiency, and/or high output coupling efficiency. Accordingly, in some embodiments, aspects of the present disclosure enable lower-power AR eyewear displays to produce the same quality of display of a higher-power conventional AR eyewear display waveguide.
The present disclosure describes techniques and apparatuses that are directed to using memory protection data within a computing device. Techniques include allocating regions of a memory for storing application data and protection data. Techniques also include creating a bitmap having bit values corresponding to memory blocks within the allocated regions. The one or more bit values can be indicative of whether application data and/or protection data are present in a memory block. The techniques and apparatuses can enable memory protection, such as memory security (e.g., encryption) and memory safety (e.g., error correction code (ECC) usage), to be efficiently used while permitting discontiguous memory allocations and without substantial operating system modification.
The present disclosure is directed to determining geographic orientation based at least in part on imagery. In particular, the methods and systems of the present disclosure can: receive data generated by a camera and representing imagery that includes at least a portion of a physical real-world environment comprising the camera and a travelway; and determine, based at least in part on the data and a machine-learning model, a geographic orientation of the camera with respect to the travelway.
G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
G01C 21/28 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier avec corrélation de données de plusieurs instruments de navigation
G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
G06T 7/80 - Analyse des images capturées pour déterminer les paramètres de caméra intrinsèques ou extrinsèques, c. à d. étalonnage de caméra
The present disclosure relates generally to the processing of machine-readable visual encodings in view of contextual information. One embodiment of aspects of the present disclosure comprises obtaining image data descriptive of a scene that includes a machine-readable visual encoding; processing the image data with a first recognition system configured to recognize the machine-readable visual encoding; processing the image data with a second, different recognition system configured to recognize a surrounding portion of the scene that surrounds the machine-readable visual encoding; identifying a stored reference associated with the machine-readable visual encoding based at least in part on one or more first outputs generated by the first recognition system based on the image data and based at least in part on one or more second outputs generated by the second recognition system based on the image data; and performing one or more actions responsive to identification of the stored reference.
G06K 7/14 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire utilisant la lumière sans sélection des longueurs d'onde, p.ex. lecture de la lumière blanche réfléchie
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p.ex. forme, nature, code
A method for identifying malicious software includes receiving and executing a software application, identifying a plurality of uniform resource identifiers the software application interacts with during execution of the software application, and generating a vector representation for the software application using a feed-forward neural network configured to receive the plurality of uniform resource identifiers as feature inputs. The method also includes determining similarity scores for a pool of training applications, each similarity score associated with a corresponding training application and indicating a level of similarity between the vector representation for the software application and a respective vector representation for the corresponding training application. The method also includes flagging the software application as belonging to a potentially harmful application category when one or more of the training applications have similarity scores that satisfy a similarity threshold and include a potentially harmful application label.
G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus
G06F 21/52 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p.ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données
A method comprising transmitting, via a first antenna array of a mobile communication device, a plurality of transmit beams, and receiving, via a second antenna array of the mobile communication device, a plurality of receive beams. Each beam pair of a plurality of beam pairs includes a respective transmit beam of the plurality of transmit beams and a respective receive beam of the plurality of receive beams. Then determining, based on a comparison between beam pairs of the plurality of beam pairs, whether an object is proximate to the mobile communication device. Then responsive to determining that the object is proximate to the mobile communication device, determining one or more transmission parameters. Then transmitting, with the one or more transmission parameters, a signal.
H04B 7/06 - Systèmes de diversité; Systèmes à plusieurs antennes, c. à d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station d'émission
H04B 7/08 - Systèmes de diversité; Systèmes à plusieurs antennes, c. à d. émission ou réception utilisant plusieurs antennes utilisant plusieurs antennes indépendantes espacées à la station de réception
H04W 16/28 - Structures des cellules utilisant l'orientation du faisceau
31.
PROCESSING CONTINUED CONVERSATIONS OVER MULTIPLE DEVICES
Implementations relate to facilitating continued conversations of a user with an automated assistant when the user changes locations relative to device(s) in an ecosystem of linked assistant devices. The user initially invokes a first device and provides a request, which is processed by the first device. The first device provides a notification to other device(s) in the ecosystem to indicate that the user is likely to issue a further assistant request. The first device processes subsequent audio data to determine whether the subsequent audio data includes a further assistant request. The other notified device(s) process device-specific sensor data to determine whether the user is co-present with the one of the other devices. If so, an indication is provided to the first device, causing the first device to cease processing subsequent audio data. Further, the co-present device starts to process subsequent audio data.
Methods, systems, and apparatus for solving quadratic optimization problems over orthogonal groups using quantum computing. In one aspect, a method includes receiving data representing a quadratic optimization problem, wherein decision variables of the quadratic optimization problem take values in an orthogonal group or a special orthogonal group; encoding the quadratic optimization problem as a quantum Hamiltonian, the encoding comprising using a Clifford algebra representation of the group to map orthogonal matrices or special orthogonal matrices in the group to respective quantum states in a Hilbert space; determining an approximate eigenstate of the quantum Hamiltonian; computing expectation values of Pauli operators with respect to the approximate eigenstate, wherein the Pauli operators comprise operators obtained by mapping multiplication operations of the Clifford algebra into the Hilbert space; and rounding the expectation values of the Pauli operators to elements of the orthogonal group to obtain a solution to the quadratic optimization problem.
Systems and methods for augmented-reality tutoring can utilize optical character recognition, natural language processing, and/or augmented-reality rendering for providing real-time notifications for completing a determined task. The systems and methods can include utilizing one or more machine-learned models trained for quantitative reasoning and can include providing a plurality of different user interface elements at different times.
G09B 3/02 - Matériel d'enseignement à commande manuelle ou mécanique procédant par questions et réponses du type où l'élève doit donner une réponse à la question posée, ou bien où la machine donne une réponse à la question posée par un élève
G06V 30/40 - Reconnaissance des formes à partir d’images axée sur les documents
G09B 3/10 - Matériel d'enseignement à commande manuelle ou mécanique procédant par questions et réponses du type à choix entre réponses multiples, c. à d. où pour une question donnée est fournie une série de réponses et où un choix doit être fait où un seul groupe de réponses est commun à plusieurs questions
G09B 5/06 - Matériel à but éducatif à commande électrique avec présentation à la fois visuelle et sonore du sujet à étudier
G09B 7/04 - Dispositifs ou appareils d'enseignement à commande électrique procédant par questions et réponses du type où l'élève doit donner une réponse à la question posée, ou bien où la machine donne une réponse à la question posée par l'élève caractérisés par une modification du programme d'enseignement à la suite d'une réponse erronée, p.ex. en répétant la question, en fournissant des explications supplémentaires
G09B 7/08 - Dispositifs ou appareils d'enseignement à commande électrique procédant par questions et réponses du type à choix entre réponses multiples, c. à d. où pour une question donnée est fournie une série de réponses entre lesquelles un choix doit être fait caractérisés par une modification du programme d'enseignement à la suite d'une réponse erronée, p.ex. en répétant la question, en fournissant une information supplémentaire
A method including generating a batch of calibration images including a ground-truth image, and an image captured by a backward facing camera of a head mounted AR device, predicting a first gaze direction based on the ground-truth image, training a neural network based on the predicted first gaze direction and the ground-truth image, predicting a second gaze direction based on the image and an indication displayed on a display of the head mounted AR device when the image was captured, and training the neural network based on the predicted second gaze direction and a position on the display of the head mounted AR device associated with the indication.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 40/18 - Caractéristiques de l’œil, p.ex. de l’iris
A method including receiving a time-domain audio signal, generating a blocked time-domain audio signal as a portion of the time-domain audio signal, transforming the blocked time-domain audio signal using a first non-windowed transform function to generate a first frequency-domain audio signal, transforming the first frequency-domain audio signal using a second non-windowed transform function to generate a second frequency-domain audio signal, and compressing the second frequency-domain audio signal to generate a compressed frequency-domain audio signal.
G10L 19/02 - Techniques d'analyse ou de synthèse de la parole ou des signaux audio pour la réduction de la redondance, p.ex. dans les vocodeurs; Codage ou décodage de la parole ou des signaux audio utilisant les modèles source-filtre ou l’analyse psychoacoustique utilisant l'analyse spectrale, p.ex. vocodeurs à transformée ou vocodeurs à sous-bandes
G10L 19/022 - Constitution de blocs, c. à d. regroupement d’échantillons temporels; Choix des fenêtres d’analyse; Facteur de recouvrement
G10L 19/032 - Quantification ou dé-quantification de composantes spectrales
36.
UPLINK ADAPTIVE FLOW CONTROL WITH PADDING MITIGATION
A first wireless device (102) employs an uplink (UL) pre-transmission process (122) to temporarily buffer data for processing prior to transmission of the resulting processed data to a second wireless device (110). To mitigate excessive delay of higher-priority data, higher-priority data is enqueued into the UL pre-transmission process (122) without restriction (subject to capacity limitations), while lower-priority data is selectively enqueued into the UL pre-transmission process (122) based on one or more criteria applied to a current volume of data in the input queue. Further, the first wireless device (102) monitors the current transmission efficiency based on, for example, the current usage of transmission padding, and operates to dynamically adjust one or more of the criteria based on the monitored current transmission efficiency.
A method (300) includes receiving distillation data (220) including a plurality of out-of-domain training utterances (222). For each particular out-of-domain training utterance of the distillation data, the method includes generating a corresponding augmented out-of-domain training utterance (232), and generating, using a teacher ASR model (170) trained on training data corresponding to a target domain, a pseudo-label (240) corresponding to the corresponding augmented out-of-domain training utterance. The method also includes distilling a student ASR model (210) from the teacher ASR model by training the student ASR model using the corresponding augmented out-of-domain training utterances paired with the corresponding pseudo-labels generated by the teacher ASR model.
G10L 15/06 - Création de gabarits de référence; Entraînement des systèmes de reconnaissance de la parole, p.ex. adaptation aux caractéristiques de la voix du locuteur
38.
CONVERSATIONAL INTERFACE FOR CONTENT CREATION AND EDITING USING LARGE LANGUAGE MODELS
Example embodiments of the present disclosure provide for an example method that includes obtaining via a conversational campaign assistant interface, by a custom language model, natural language input. The method includes generating, by the custom language model, an output comprising a predicted user intent. The method includes determining actions to perform and determining a natural language response. The method includes transmitting, to an action component, the action data structure comprising executable instructions that cause the action component to automatically perform operations associated with completing the action. The method includes transmitting to the conversation campaign assistant interface, the response data structure comprising the natural language response to be provided for display to a user via the conversational campaign assistant interface. The method includes obtaining user input indicative of a validation of the action data structure or the response data structure and updating the custom language model based on the user input.
Techniques of maintaining user comfort while using augmented reality smartglasses include performing an online calibration of frame deformation to correct display position in the lens. Such a calibration involves modeling the frame portion between the world-facing camera and the eye-tracking camera as a hinge that rotates about an axis on and normal to the frame portion. That is, the frame portion consists of two line segments that are joined at an axis at an unknown rotation (angle) to be determined. In this treatment, any translation induced will be neglected.
Methods, systems, and apparatus are described for immersive videoconferencing teleconferencing streams from multiple endpoints within shared scene environment. The method includes receiving a plurality of streams for presentation at a teleconference, wherein each of the plurality of streams represents a participant of a respective plurality of participants of the teleconference. The method includes, determining scene data descriptive of a scene environment, the scene data comprising at least one of lighting characteristics, acoustic characteristics, or perspective characteristics of the scene environment. The method includes, for each of the plurality of participants of the teleconference, determining a position of the participant within the scene environment and, based at least in part on the scene data and the position of the participant within the scene environment, modifying the stream that represents the participant.
Provided are computing systems, methods, and platforms that infer an object shape from an image using a neural radiance field (NeRF) model. A NeRF model can infer a 3D shape from a 2D image by performing a plurality of iterations to generate a plurality of sample 2D images of a 3D scene. For each iteration, an object code can be sampled from a posterior distribution of learned priors on NeRF models associated with the 3D scene, the object code can be processed with a hypernetwork to generate a set of NeRF weights from the object code, and a NeRF model with the set of NeRF weights predicted by the hypernetwork can generate a sample 2D image of the 3D scene. The sample 2D images generated during the iterations can be provided as an output.
Generating a location-specific three-dimensional model in response to a location query can provide users with a better understanding of a location through providing better interactivity, better perspective, and better understanding of dimensionality. Generation of the models can be enabled by leveraging a three-dimensional asset database and segmentation methods. The location-specific models can provide further utility by further including situation specific simulated effects, such as simulated weather or traffic.
The disclosure provides technology for enhancing the ability of a computing device to detect when a user has discontinued reading a text source. An example method includes receiving audio data comprising a spoken word associated with a text source, comparing the audio data with data of the text source, determining, based on the comparing, whether a segment of the audio data corresponds to a location of the text source, and responsive to determining that the segment of the audio data does not correspond to a location of the text source, transmitting a signal indicating that a user has discontinued reading the text source, the signal causing to cease the comparing of the audio data with the data of the text source.
G10L 25/87 - Détection de points discrets dans un signal de voix
G06F 3/0483 - Interaction avec des environnements structurés en pages, p.ex. métaphore livresque
G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la parole; Sélection d'unités de reconnaissance
G10L 15/04 - Segmentation; Détection des limites de mots
G10L 15/10 - Classement ou recherche de la parole utilisant des mesures de distance ou de distorsion entre la parole inconnue et les gabarits de référence
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
44.
METHODS AND SYSTEMS FOR ENCODER PARAMETER SETTING OPTIMIZATION
A media item to be provided to users of a platform is identified. The media item is associated with a media class of one or more media classes. An indication of the media item is provided as input to a machine learning model trained based on historical encoding data to predict, for a given media item, a set of encoder parameter settings that satisfy a performance criterion in view of a respective media class of the given media item. The historical encoding data includes a prior set of encoder parameter settings that satisfied the performance criterion with respect to a prior media item associated with the respective class. Encoder parameter settings that satisfy the performance criterion in view of the media class is determined based on an output of the model. The media item is caused to be encoded using the determined encoder parameter settings.
H04L 65/61 - Diffusion en flux de paquets multimédias pour la prise en charge des services de diffusion par flux unidirectionnel, p.ex. radio sur Internet
H04L 65/80 - Dispositions, protocoles ou services dans les réseaux de communication de paquets de données pour prendre en charge les applications en temps réel en répondant à la qualité des services [QoS]
H04N 21/25 - Opérations de gestion réalisées par le serveur pour faciliter la distribution de contenu ou administrer des données liées aux utilisateurs finaux ou aux dispositifs clients, p.ex. authentification des utilisateurs finaux ou des dispositifs clients ou
45.
RESIDUAL ADAPTERS FOR FEW-SHOT TEXT-TO-SPEECH SPEAKER ADAPTATION
A method for residual adapters for few-shot text-to-speech speaker adaptation includes obtaining a text-to-speech (TTS) model configured to convert text into representations of synthetic speech, the TTS model pre-trained on an initial training data set. The method further includes augmenting the TTS model with a stack of residual adapters. The method includes receiving an adaption training data set including one or more spoken utterances spoken by a target speaker, each spoken utterance in the adaptation training data set paired with corresponding input text associated with a transcription of the spoken utterance. The method also includes adapting, using the adaption training data set, the TTS model augmented with the stack of residual adapters to learn how to synthesize speech in a voice of the target speaker by optimizing the stack of residual adapters while parameters of the TTS model are frozen.
To determine whether two or more devices are at the same location, a first client device receives a first short-range communication from a second client device identifying the second client device. The first client device also receives a second short-range communication from the second client device identifying the second client device. The first client device provides the first and second short-range communications to a server device that analyzes the first and second short-range communications to verify that the first and second client devices are the same location. More specifically, the server device determines a likelihood that the first and second client devices are the same location based on the first and second short-range communications. Then the server devices determines a risk of fraud based on the likelihood.
H04W 4/40 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons
47.
Method for Training Large Language Models to Perform Query Intent Classification
Provided are computing systems, methods, and platforms that train query processing models, such as large language models, to perform query intent classification tasks by using retrieval augmentation and multi-stage distillation. Unlabeled training examples of queries may be obtained, and a set of the training examples may be augmented with additional feature annotations to generate augmented training examples. A first query processing model may annotate the retrieval augmented queries to generate inferred labels for the augmented training examples. A second query processing model may be trained on the inferred labels, distilling the query processing model that was trained with retrieval augmentation into a non-retrieval augmented query processing model. The second query processing model may annotate the entire set of unlabeled training examples. Another stage of distillation may train a third query processing model using the entire set of unlabeled training examples without retrieval augmentation.
A system and method for assigning a workload to one of a plurality of candidate host machines of a computing environment. The method may include receiving a request to schedule a workload, selecting a virtual machine type for executing the workload, for each candidate host machine of the plurality of candidate host machines, determining an expected waste score indicating a likelihood of resources at the candidate host machine remaining unused if the virtual machine type is assigned to the candidate host machine, selecting the candidate host machine for which the expected waste score is the lowest, and assigning the workload to the selected candidate host machine.
G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing an input image using a super-resolution neural network to generate an up-sampled image that is a higher resolution version of the input image. In one aspect, a method comprises: processing the input image using an encoder subnetwork of the super-resolution neural network to generate a feature map; generating an updated feature map, comprising, for each spatial position in the updated feature map: applying a convolutional filter to the feature map to generate a plurality of features corresponding to the spatial position in the updated feature map, wherein the convolutional filter is parametrized by a set of convolutional filter parameters that are generated by processing data representing the spatial position using a hyper neural network; and processing the updated feature map using a projection subnetwork of the super-resolution neural network to generate the up-sampled image.
G06T 3/40 - Changement d'échelle d'une image entière ou d'une partie d'image
G06T 5/20 - Amélioration ou restauration d'image en utilisant des opérateurs locaux
G06V 10/771 - Sélection de caractéristiques, p.ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques
50.
Immersive Teleconferencing within Shared Scene Environments
Methods, systems, and apparatus are described for immersive videoconferencing teleconferencing streams from multiple endpoints within shared scene environment. The method includes receiving a plurality of streams for presentation at a teleconference, wherein each of the plurality of streams represents a participant of a respective plurality of participants of the teleconference. The method includes, determining scene data descriptive of a scene environment, the scene data comprising at least one of lighting characteristics, acoustic characteristics, or perspective characteristics of the scene environment. The method includes, for each of the plurality of participants of the teleconference, determining a position of the participant within the scene environment and, based at least in part on the scene data and the position of the participant within the scene environment, modifying the stream that represents the participant.
G06V 10/26 - Segmentation de formes dans le champ d’image; Découpage ou fusion d’éléments d’image visant à établir la région de motif, p.ex. techniques de regroupement; Détection d’occlusion
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
A network node of a radio access network (RAN), communicating with a user equipment (UE) in dual connectivity (DC) with a master node (MN) and a secondary node (SN), can implement a method for managing deactivation of a secondary cell group (SCG). The method includes detecting (1802) that a condition for deactivating the SCG is satisfied. The method further includes determining (1804) whether the UE supports deactivating the SCG, and causing (1806) the SN to deactivate or to release the SCG at the SN based on the determining.
A method includes obtaining a multi-utterance training sample that includes audio data characterizing utterances spoken by two or more different speakers and obtaining ground-truth speaker change intervals indicating time intervals in the audio data where speaker changes among the two or more different speakers occur. The method also includes processing the audio data to generate a sequence of predicted speaker change tokens using a sequence transduction model. For each corresponding predicted speaker change token, the method includes labeling the corresponding predicted speaker change token as correct when the predicted speaker change token overlaps with one of the ground-truth speaker change intervals. The method also includes determining a precision metric of the sequence transduction model based on a number of the predicted speaker change tokens labeled as correct and a total number of the predicted speaker change tokens in the sequence of predicted speaker change tokens.
G10L 17/06 - Techniques de prise de décision; Stratégies d’alignement de motifs
G10L 17/02 - Opérations de prétraitement, p.ex. sélection de segment; Représentation ou modélisation de motifs, p.ex. fondée sur l’analyse linéaire discriminante [LDA] ou les composantes principales; Sélection ou extraction des caractéristiques
G10L 17/04 - Entraînement, enrôlement ou construction de modèle
A method can include receiving audio input of speech, receiving visual input while receiving the audio input, generating a semantic description based on the visual input, and presenting a transcription of the speech based on the audio input and the semantic description.
A method for fabricating a working stamp for forming surface gratings in a waveguide workpiece includes performing a series of step lithography processes using a series of master stamps so as to form a working stamp having a first surface having a plurality of surface gratings formed therein. Each step lithography process includes pressing a master stamp of the series of master stamps into a material layer of a working stamp workpiece at a corresponding region of the material layer, the master stamp having a plurality of surface grating patterns formed thereon. Each step lithography process further includes applying ultraviolet light to the corresponding region to locally cure the material layer at the corresponding region and detaching the master stamp from the material of the working stamp after applying the ultraviolet light.
G03F 7/00 - Production par voie photomécanique, p.ex. photolithographique, de surfaces texturées, p.ex. surfaces imprimées; Matériaux à cet effet, p.ex. comportant des photoréserves; Appareillages spécialement adaptés à cet effet
G02B 6/34 - Moyens de couplage optique utilisant des prismes ou des réseaux
Methods, systems and apparatus for producing quantum circuits with low T gate counts. In one aspect, a method for performing a temporary logical AND operation on two control qubits includes the actions of obtaining an ancilla qubit in an A-state; computing a logical-AND of the two control qubits and storing the computed logical-AND in the state of the ancilla qubit, comprising replacing the A-state of the ancilla qubit with the logical-AND of the two control qubits; maintaining the ancilla qubit storing the logical-AND of the two controls until a first condition is satisfied; and erasing the ancilla qubit when the first condition is satisfied.
G06N 10/70 - Correction, détection ou prévention d’erreur quantique, p.ex. codes de surface ou distillation d’état magique
H03K 19/195 - Circuits logiques, c. à d. ayant au moins deux entrées agissant sur une sortie; Circuits d'inversion utilisant des éléments spécifiés utilisant des dispositifs supraconducteurs
H03K 19/20 - Circuits logiques, c. à d. ayant au moins deux entrées agissant sur une sortie; Circuits d'inversion caractérisés par la fonction logique, p.ex. circuits ET, OU, NI, NON
56.
Universal Monolingual Output Layer for Multilingual Speech Recognition
A method includes receiving a sequence of acoustic frames as input to a multilingual automated speech recognition (ASR) model configured to recognize speech in a plurality of different supported languages and generating, by an audio encoder of the multilingual ASR, a higher order feature representation for a corresponding acoustic frame in the sequence of acoustic frames. The method also includes generating, by a language identification (LID) predictor of the multilingual ASR, a language prediction representation for a corresponding higher order feature representation. The method also includes generating, by a decoder of the multilingual ASR, a probability distribution over possible speech recognition results based on the corresponding higher order feature representation, a sequence of non-blank symbols, and a corresponding language prediction representation. The decoder includes monolingual output layer having a plurality of output nodes each sharing a plurality of language-specific wordpiece models.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an estimate for a number of users that accessed a digital resource within a time window. In one aspect, a method comprises: obtaining access data for a digital resource; generating a tree model based on the access data; selecting, for each node in the tree model, a respective private access value for the node that: (i) is an approximation of an access value for the node, and (ii) is selected from a finite set of possible private access values; and generating an estimate for the number of users that accessed the digital resource at least the predefined number of times within the time window based on private access values associated with one or more nodes in the tree model.
A method (400) includes receiving a sequence of acoustic frames (110) characterizing an input utterance and generating a higher order feature representation (212) for a corresponding acoustic frame by an audio encoder (210) of an automatic speech recognition (ASR) model (200). The method also includes generating a context embedding (305) corresponding to one or more previous transcriptions (120P) output by the ASR model by a context encoder (300) of the ASR model and generating, by a prediction network (230) of the ASR model, a dense representation (232) based on a sequence of non-blank symbols (121) output by a final Softmax layer (250). The method also includes generating, by a joint network (24) of the ASR model, a probability distribution (242) over possible speech recognition hypotheses based on the context embeddings, the higher order feature representation, and the dense representation.
Motion tracking accuracy is an important feature to an immersive augmented or virtual reality experience. Motion tracking may be computed based on data from an inertial measurement unit of a device. This data may include errors that can vary with temperature. The disclosure describes a calibration process to reduce or eliminate these errors. The calibration process does not require special equipment and can be performed while the device is in use (i.e., online).
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G01C 25/00 - Fabrication, étalonnage, nettoyage ou réparation des instruments ou des dispositifs mentionnés dans les autres groupes de la présente sous-classe
de minimisde minimis) audible spoken synthesized spoken output rendered by the computing system in guiding the user in selecting the subset of item(s).
Provided are systems and methods for general text-driven image editing, example implementations of which may be referred to as "UniTune". UniTune can receive as input an arbitrary image and a textual edit description, and can carry out the edit while maintaining high semantic and visual fidelity to the input image. UniTune does not require any additional inputs, like masks or sketches. According to an aspect of the present disclosure, with the right choice of parameters, example systems described herein can fine-tune a large diffusion model (e.g., Imagen) on a single image, encouraging the model to maintain fidelity to the input image, both visually and semantically, while still allowing expressive manipulations.
A computer-implemented method for enabling users to subscribe to people and other tagged entities is provided herein. Such a method includes maintaining subscription data specifying a plurality of entities subscribed to by a plurality of users, with each of the plurality of entities being a tagged entity associated with a tag. The method further includes identifying a media item associated with one or more tagged entities of the plurality of entities, determining, based on the subscription data, a user of the plurality of users that is subscribed to the tagged entities of the media item, and providing the media item to the user.
G06F 16/48 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/435 - Filtrage basé sur des données supplémentaires, p.ex. sur des profils d'utilisateurs ou de groupes
A system, method, and computer readable medium for asynchronous live migration of applications between two or more servers. The computer readable medium includes computer-executable instructions for execution by a processing system. Primary applications runs on primary hosts and one or more replicated instances of each primary application run on one or more backup hosts. Asynchronous live migration is provided through a combination of process replication, logging, barrier synchronization, checkpointing, reliable messaging and message playback. The live migration is transparent to the application and requires no modification to the application, operating system, networking stack or libraries.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p.ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
66.
Dynamic instream autoplay based on presence of watch while mini player
A method includes, responsive to user input, scrolling a plurality of elements visible on a user interface (UI) to scroll out of view, from the UI, one or more first elements of the plurality of elements that were visible in the UI prior to the user input, and to scroll into view, in the UI, one or more second elements that were not visible in the UI prior to the user input. A first media player and a second media player are concurrently visible in the UI responsive to the scrolling. The method further includes, responsive to first playback of a first media item via the first media player having priority over second playback of a second media item via the second media player, preventing the second playback of the second media item during the first playback of the first media item.
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p.ex. des menus
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
Various arrangements for performing wireless device-to-device communication are presented. An audio output device, such as an earbud or pair of earbuds, can establish a connection with an audio source via a first Bluetooth interface that communicates using a Bluetooth communication protocol on a 2.4 GHz Bluetooth frequency band. The audio output device can negotiate that Bluetooth frequency-shifted communication, such as on a 5 or 6 GHz frequency band, is available for use with the audio source. The audio output device may then perform Bluetooth frequency-shifted communication with the audio source such that the audio output device receives an audio stream from the audio source using Bluetooth frequency-shifted communication and the Bluetooth communication protocol.
Systems and methods for textual replacement can include the determination of a visual intent, which can trigger an interface for selecting an image to replace visual descriptors. The visually descriptive terms can be identified, and an indicator can be provided to indicate the text replacement option may be initiated. An image can then be selected by a user to replace the visually descriptive terms.
Implementations related to facilitating continued conversations of a user with an automated assistant when the user changes locations relative to one or more devices in an ecosystem of linked assistant devices. The user initially invokes a first device and provides a request, which is processed by the first device. The first device provides a notification to one or more other devices in the ecosystem to indicate that the user is likely to issue a further assistant request. The first device processes subsequent audio data to determine whether the subsequent audio data includes a further assistant request. The one or more other notified devices process device-specific sensor data to determine whether the user is co-present with the one of the other devices. If the user presence is detected, an indication is provided to the first device, causing the first device to cease processing subsequent audio data. Further, the co-present device starts to process subsequent audio data.
Mitigating latency in guiding a user, during an interaction between the user and a computing system, in selecting a subset of item(s), from a superset of candidate items, and causing performance of further action(s) based on the selected subset of item(s). In guiding a user in selecting the subset of items, various implementations enable the user to provide only spoken input(s) in selecting the subset of item(s), and provide visual output(s) that are responsive to the spoken input(s) and that guide the user in selecting the item(s). In some of those various implementations, there is not any (or there is only de minimis) audible spoken synthesized spoken output rendered by the computing system in guiding the user in selecting the subset of item(s).
The present disclosure is directed to selective gesture recognition for handheld device gestures. An example method includes receiving, by a handheld interactive object, movement information descriptive of a gesture performed with the handheld interactive object. The method includes selecting a local and/or remote machine-learned model for processing the movement information. The movement information can be processed to identify a gesture action corresponding to the movement information. The local and/or remote machine-learned model can be selected based on user input data and/or a complexity of the movement information. In response to selecting the local machine-learned model, the method includes processing the movement information according to the local machine-learned model and communicating a message to a remote device based on the result. In response to selecting the remote ma-chine-learned model, the method includes communicating the movement information to the remote device for processing in accordance with the remote machine-learned model.
G06F 3/038 - Dispositions de commande et d'interface à cet effet, p.ex. circuits d'attaque ou circuits de contrôle incorporés dans le dispositif
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G06F 3/0346 - Dispositifs de pointage déplacés ou positionnés par l'utilisateur; Leurs accessoires avec détection de l’orientation ou du mouvement libre du dispositif dans un espace en trois dimensions [3D], p.ex. souris 3D, dispositifs de pointage à six degrés de liberté [6-DOF] utilisant des capteurs gyroscopiques, accéléromètres ou d’inclinaiso
72.
Automatic Audio Playback of Displayed Textual Content
An audio playback system that provides intuitive audio playback of textual content responsive to user input actions, such as scrolling portions of textual content on a display. Playback of audio (e.g., text-to-speech audio) that includes textual content can begin based on a portion of textual content being positioned by a user input at a certain position on a device display. As one example, a user can simply scroll through a webpage or other content item to cause a text-to-speech system to perform audio playback of textual content displayed in one or more playback section(s) of the device's viewport (e.g., rather than requiring the user to perform additional tapping or gesturing to specifically select a certain portion of textual content).
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p.ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
G06F 3/0485 - Défilement ou défilement panoramique
G10L 13/02 - Procédés d'élaboration de parole synthétique; Synthétiseurs de parole
73.
LANGUAGE MODELS USING DOMAIN-SPECIFIC MODEL COMPONENTS
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for language models using domain-specific model components. In some implementations, context data for an utterance is obtained. A domain-specific model component is selected from among multiple domain-specific model components of a language model based on the non-linguistic context of the utterance. A score for a candidate transcription for the utterance is generated using the selected domain-specific model component and a baseline model component of the language model that is domain-independent. A transcription for the utterance is determined using the score the transcription is provided as output of an automated speech recognition system.
This document describes techniques and systems for providing trusted computing for digital devices. The techniques and systems may use cryptographic algorithms to provide trusted computing and processing. By doing so, the techniques help ensure authentic computation and prevent nefarious acts. For example, a method is described that receives a signature associated with a designee and validates the signature. The signature may be associated with a designee of a host computing device, and the signature may be generated according to firmware associated with an integrated circuit of the host computing device and a first private key of a first asymmetric key pair. Signature validation may be based on a second asymmetric key pair having a second private key and a second public key, the second private key stored in write-once memory of the host computing device.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p.ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
A waveguide includes an outcoupler with a dual reflective facet configuration. The dual reflective facet configuration includes a first set of reflective facets to receive light from a first direction and reflect the light incident thereon to an outcoupling direction. The dual reflective facet configuration also includes a second set of reflective facets to receive light from a second direction and reflect the light incident thereon to the outcoupling direction.
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for parameterization of physical dimensions of discrete circuit components for component definitions that define discrete circuit components. The component definitions may be selected for use in a device design. When a parametrization of a particular version of a discrete circuit component definition is changed, the version level of the device design is also changed and the circuit layout for the device design is physically verified for the new version level.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p.ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
G06N 3/084 - Rétropropagation, p.ex. suivant l’algorithme du gradient
G10L 13/04 - Procédés d'élaboration de parole synthétique; Synthétiseurs de parole - Détails des systèmes de synthèse de la parole, p.ex. structure du synthétiseur ou gestion de la mémoire
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
G10L 25/18 - Techniques d'analyses de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information spectrale de chaque sous-bande
G10L 25/30 - Techniques d'analyses de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse utilisant des réseaux neuronaux
78.
DISPLAY DEVICE WITH CONSISTENT LUMINANCE AT DIFFERENT REFRESH RATES
The subject matter described in this disclosure includes a pixel circuit with an LED and a driving transistor having a drain terminal that is connected to the LED to supply power to the LED. The pixel circuit also includes a second transistor that is connected between the LED and an initialization voltage line, the second transistor having a gate terminal connected to a scan line. The pixel circuit also includes a third transistor that is connected between the LED and the initialization voltage line in series with the second transistor, the third transistor having a gate terminal connected to a reset line. The pixel circuit is configured so that activating the scan line at a first frequency and activating the reset line at half the first frequency causes the LED to be initialized every other time the scan line is activated.
G09G 3/3233 - Dispositions ou circuits de commande présentant un intérêt uniquement pour l'affichage utilisant des moyens de visualisation autres que les tubes à rayons cathodiques pour la présentation d'un ensemble de plusieurs caractères, p.ex. d'une page, en composant l'ensemble par combinaison d'éléments individuels disposés en matrice utilisant des sources lumineuses commandées utilisant des panneaux électroluminescents semi-conducteurs, p.ex. utilisant des diodes électroluminescentes [LED] organiques, p.ex. utilisant des diodes électroluminescentes organiques [OLED] utilisant une matrice active avec un circuit de pixel pour commander le courant à travers l'élément électroluminescent
79.
MAGIC STATE FACTORY CONSTRUCTIONS FOR PRODUCING CCZ AND T STATES
Methods, systems, and apparatus for producing CCZ states and T states. In one aspect, a method for transforming a CCZ state into three T states includes obtaining a first target qubit, a second target qubit and a third target qubit in a CCZ state; performing a X−1/2 gate on the third target qubit; performing an X gate on the first target qubit and the second target qubit using the third target qubit as a control; performing a Z gate on the first target qubit and the second target qubit using the third qubit as a X axis control; performing a Z−1/4 gate on the third target qubit; and performing a Z gate on the first target qubit and the second target qubit using the third qubit as a X axis control to obtain the three T states.
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p.ex. couplage ou commande de qubit
H03K 19/003 - Modifications pour accroître la fiabilité
H03M 13/00 - Codage, décodage ou conversion de code pour détecter ou corriger des erreurs; Hypothèses de base sur la théorie du codage; Limites de codage; Méthodes d'évaluation de la probabilité d'erreur; Modèles de canaux; Simulation ou test des codes
H03M 13/03 - Détection d'erreurs ou correction d'erreurs transmises par redondance dans la représentation des données, c.à d. mots de code contenant plus de chiffres que les mots source
H03M 13/29 - Codage, décodage ou conversion de code pour détecter ou corriger des erreurs; Hypothèses de base sur la théorie du codage; Limites de codage; Méthodes d'évaluation de la probabilité d'erreur; Modèles de canaux; Simulation ou test des codes combinant plusieurs codes ou structures de codes, p.ex. codes de produits, codes de produits généralisés, codes concaténés, codes interne et externe
80.
PARAMETERIZED NOISE SYNTHESIS FOR GRAPHICAL ARTIFACT REMOVAL
Pre-encoding noise parameterization techniques mitigate or eliminate banding and other graphical artifacts in video frames for decoding and presentation by a client device. For one or more input video frames, a quantization parameter associated with the input video frames is identified. Noise synthesis parameters are determined based on the identified quantization parameter, and the input video frames are encoded for transmission. The encoded video frames are transmitted to the client device along with the determined noise synthesis parameters, for use by the client device in generating synthetic noise to add to resulting video frames decoded by the client device.
H04N 19/70 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par des aspects de syntaxe liés au codage vidéo, p.ex. liés aux standards de compression
81.
DETERMINING ATTRIBUTES FOR ELEMENTS OF DISPLAYABLE CONTENT AND ADDING THEM TO AN ACCESSIBILITY TREE
A method may receive an image representing displayable content for display by an application. A method may execute a layout extraction model using the image as input and generating a list of elements for the image as output, the list of elements including at least a bounding box defining a portion of the image and a role attribute. A method may add the role attribute to a node in an accessibility tree using the list of elements.
G06V 30/414 - Extraction de la structure géométrique, p.ex. arborescence; Découpage en blocs, p.ex. boîtes englobantes pour les éléments graphiques ou textuels
82.
PEOPLE SUGGESTION IN COLLABORATIVE ONLINE TEXT EDITORS
Techniques are described herein for providing people suggestions in collaborative online text editors. A method includes: receiving user interface input that corresponds to a document in a document editing application; automatically parsing the received user interface input to identify a name included in the user interface input; in response to identifying the name included in the user interface input, providing an option to create a link in the document between the name and a corresponding contact in a contact store; receiving additional user interface input that indicates acceptance of the option to create the link in the document; and in response to receiving the additional user interface input, automatically creating the link in the document between the name and the corresponding contact in the contact store.
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network using a priority queue. One of the methods includes maintaining data identifying a set of K output sequences that were previously generated; selecting at least one of the output sequences from the set of output sequences; for each selected output sequence, determining a respective score; determining, for each selected sequence, a respective first update to the current values of the controller parameters; generating a batch of new output sequences using the controller neural network; obtaining a respective reward for each of the new output sequences; determining, from the new output sequences and the output sequences in the maintained data, the K output sequences that have the highest rewards; and modifying the maintained data.
The wait time prediction technology determines expected wait times for businesses or other public services using a model generated based on at least historical wait times for the business. In response to a request from a user, an expected wait time for service at the business for at least one particular time period on a particular day of a week is determined using the model and provided for display. User feedback regarding the expected wait time may be requested, and used to refresh the model as new wait times and other information are collected.
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques
G06N 5/04 - Modèles d’inférence ou de raisonnement
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
G06Q 10/109 - Gestion du temps, p.ex. agendas, rappels, réunions ou décompte de temps
G06Q 30/0201 - Modélisation du marché; Analyse du marché; Collecte de données du marché
G06Q 30/0202 - Prédictions ou prévisions du marché pour les activités commerciales
85.
Secure Collaboration Between Processors And Processing Accelerators In Enclaves
Aspects of the disclosure relate to providing a secure collaboration between one or more PCIe accelerators and an enclave. An example system may include a PCIe accelerator apparatus. The PCIs accelerator apparatus may include the one or more PCIe accelerators and a microcontroller configured to provide a cryptographic identity to the PCIe accelerator apparatus. The PCIe accelerator apparatus may be configured to use the cryptographic identity to establish communication between the PCIe accelerator apparatus the enclave.
G06F 21/72 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du calcul ou du traitement de l’information dans les circuits de cryptographie
G06F 13/42 - Protocole de transfert pour bus, p.ex. liaison; Synchronisation
G06F 21/79 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du stockage de données dans les supports de stockage à semi-conducteurs, p.ex. les mémoires adressables directement
86.
AUTOMATED ASSISTANT THAT UTILIZES RADAR DATA TO DETERMINE USER PRESENCE AND VIRTUALLY SEGMENT AN ENVIRONMENT
Implementations relate to an automated assistant that can determine whether to respond to inputs in an environment according to whether radar data indicates a user is present. When user presence is detected, the automated assistant can virtually segment the environment and apply certain operational parameters to certain segments of the environment. For instance, the automated assistant can enable an input detection feature, such as warm word detection, for a segmented portion of the environment in which a user is detected. In this way, false positives can be mitigated for instances in which environmental and/or user sounds are detected by the automated assistant but do not originate from a particular segment of the environment. Other parameters, such as varying confidence thresholds and/or speech processing biasing, can be temporarily enforced for different segments of an environment in which a user is detected.
A waveguide includes a plurality of reflective facet sets. Each reflective facet set of the plurality of reflective facet sets includes a first reflective facet to reflect light having a first optical characteristic and a second reflective facet to reflect light having a second optical characteristic that is different from the first optical characteristic. A first reflective facet in a first reflective facet set of the plurality of reflective facet sets overlaps a first reflective facet of a second set of the plurality of reflective facet sets.
Various arrangements for performing wireless device-to-device communication are presented. An audio output device, such as an earbud or pair of earbuds, can establish a connection with an audio source via a first Bluetooth interface that communicates using a Bluetooth communication protocol on a 2.4 GHz Bluetooth frequency band. The audio output device can negotiate that Bluetooth frequency-shifted communication, such as on a 5 or 6 GHz frequency band, is available for use with the audio source. The audio output device may then perform Bluetooth frequency-shifted communication with the audio source such that the audio output device receives an audio stream from the audio source using Bluetooth frequency-shifted communication and the Bluetooth communication protocol.
H04W 4/80 - Services utilisant la communication de courte portée, p.ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
H04L 69/14 - Protocoles multicanaux ou multi-liaisons
A UE (102) receives (305), from a network entity (106a), a configuration for a TCI state list for a first serving cell that corresponds to a reference cell. The UE (102) further receives (309), from the network entity (106a), a first parameter and a second parameter that define an other TCI state list for a second serving cell. The first parameter indicates a type of the other TCI state list for the second serving cell and the second parameter indicates at least one of: a serving cell index for the first serving cell or one or more TCI state IDs in the TCI state list. The UE (102) communicates (377) with the network entity (106a) using the other TCI state list for the second serving cell. The other TCI state list is based on the second parameter and the TCI state list for the first serving cell.
Decoding a current block includes receiving a compressed bitstream. A transform block of transform coefficients is decoded from the compressed bitstream. The transform coefficients are in a transform domain. The transform block is input to a machine-learning model to obtain a residual block that is in a pixel domain. The residual block is used to reconstruct the current block. Encoding a current block includes receiving a current residual block. The current residual block and a specified rate-distortion parameter are input to a machine-learning model to obtain a quantized transform block. The quantized transform block is entropy encoded into a compressed bitstream.
H04N 19/107 - Sélection du mode de codage ou du mode de prédiction entre codage prédictif spatial et temporel, p.ex. rafraîchissement d’image
H04N 19/147 - Débit ou quantité de données codées à la sortie du codeur selon des critères de débit-distorsion
H04N 19/176 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p.ex. un objet la zone étant un bloc, p.ex. un macrobloc
H04N 19/18 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant un ensemble de coefficients de transformée
H04N 19/91 - Codage entropique, p.ex. codage à longueur variable ou codage arithmétique
Region-based cross-component prediction improves convolutional cross-component mode (CCCM) prediction by enabling filter coefficients for predicting chroma samples from luma samples to be derived for an entire region of a frame of a video stream, such as a coding tree unit (CTU), rather than requiring that such filter coefficients be derived for each individual coding unit (CU). Deriving the filter coefficients for an entire region instead of for each individual CU under processing significantly reduces the latency in video coding and thus enables CCCM prediction to be used in hardware coder implementations.
H04N 19/105 - Sélection de l’unité de référence pour la prédiction dans un mode de codage ou de prédiction choisi, p.ex. choix adaptatif de la position et du nombre de pixels utilisés pour la prédiction
H04N 19/157 - Mode de codage attribué, c. à d. le mode de codage étant prédéfini ou présélectionné pour être utilisé ultérieurement afin de sélectionner un autre élément ou paramètre
H04N 19/176 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p.ex. un objet la zone étant un bloc, p.ex. un macrobloc
H04N 19/186 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une couleur ou une composante de chrominance
H04N 19/593 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage prédictif mettant en œuvre des techniques de prédiction spatiale
H04N 19/70 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par des aspects de syntaxe liés au codage vidéo, p.ex. liés aux standards de compression
92.
FILTER COEFFICIENT DERIVATION SIMPLIFICATION FOR CROSS-COMPONENT PREDICTION
Filter coefficient derivation simplification for cross-component prediction reduces latencies typically introduced by convolutional cross-component model (CCCM) prediction and thus enables use of CCCM prediction by hardware coders. Various approaches for filter coefficient derivation simplification are disclosed, including limiting a dynamic range of filter coefficient derivation to a defined bit range, limiting filter coefficient derivation and thus use of CCCM prediction based on coding unit size, and/or enabling filter coefficient derivation directly from non-downsampled luma samples.
H04N 19/105 - Sélection de l’unité de référence pour la prédiction dans un mode de codage ou de prédiction choisi, p.ex. choix adaptatif de la position et du nombre de pixels utilisés pour la prédiction
H04N 19/157 - Mode de codage attribué, c. à d. le mode de codage étant prédéfini ou présélectionné pour être utilisé ultérieurement afin de sélectionner un autre élément ou paramètre
H04N 19/176 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une zone de l'image, p.ex. un objet la zone étant un bloc, p.ex. un macrobloc
H04N 19/186 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage adaptatif caractérisés par l’unité de codage, c. à d. la partie structurelle ou sémantique du signal vidéo étant l’objet ou le sujet du codage adaptatif l’unité étant une couleur ou une composante de chrominance
H04N 19/593 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques utilisant le codage prédictif mettant en œuvre des techniques de prédiction spatiale
H04N 19/70 - Procédés ou dispositions pour le codage, le décodage, la compression ou la décompression de signaux vidéo numériques caractérisés par des aspects de syntaxe liés au codage vidéo, p.ex. liés aux standards de compression
A computing device may drive a haptic device of the computing device to output a precursor haptic signal. The computing device may determine a motion signal associated with outputting the precursor haptic signal, lire computing device may determine, based at least in part on the motion signal associated with outputting the precursor haptic signal, that the computing device is in an adverse haptic environment. The computing device may, in response to determining that the computing device is in an adverse haptic environment, drive, by the one or more processors, the haptic device to output an alternative haptic signal instead of the haptic signal.
A method includes receiving feature vectors and, for each respective feature vector, a corresponding absolute positional encoding. The method also includes determining latent representations of entities represented by the feature vectors, and determining, for each respective latent representation, a corresponding relative positional encoding based on the corresponding absolute positional encoding of each feature vector and a corresponding position vector associated with the respective latent representation. The method additionally includes determining an attention matrix based on the feature vectors, the entity-centric latent representations, and the corresponding relative positional encoding of each latent representation. The method further includes updating, for each respective latent representation, the corresponding position vector based on a weighted mean of the corresponding absolute positional encoding of each feature vector weighted according to corresponding entries of the attention matrix, and outputting the latent representations and/or the position vectors associated therewith.
G06N 3/0442 - Réseaux récurrents, p.ex. réseaux de Hopfield caractérisés par la présence de mémoire ou de portes, p.ex. mémoire longue à court terme [LSTM] ou unités récurrentes à porte [GRU]
An enhanced matrix product state-based decoder is generated and employed to almost optimally detect and correct errors within a quantum computing and information processing system. The decoder takes as input a detector level error model that describes physical error channels and a set of error detections. This error model is improved using experimental data.
96.
AUTOMATED ASSISTANT THAT UTILIZES RADAR DATA TO DETERMINE USER PRESENCE AND VIRTUALLY SEGMENT AN ENVIRONMENT
Implementations relate to an automated assistant that can determine whether to respond to inputs in an environment according to whether radar data indicates a user is present. When user presence is detected, the automated assistant can virtually segment the environment and apply certain operational parameters to certain segments of the environment. For instance, the automated assistant can enable an input detection feature, such as warm word detection, for a segmented portion of the environment in which a user is detected. In this way, false positives can be mitigated for instances in which environmental and/or user sounds are detected by the automated assistant but do not originate from a particular segment of the environment. Other parameters, such as varying confidence thresholds and/or speech processing biasing, can be temporarily enforced for different segments of an environment in which a user is detected.
A method (400) for an aggregatable application programming interface (API) includes receiving, from a third party service (150), an aggregation request (20) requesting aggregation of client data (30) from a client (12) of the third party service. The method also includes receiving, from an API (14) executed by a client device (10) of the client, a first portion of the client data (30a). The method includes storing the first portion of the client data and receiving, from the API, a second portion of the client data (30b). The method includes determining that the second portion of the client data is a final portion of the client data. In response, the method includes aggregating the first portion of the client data with the second portion of the client data. The method also includes transmitting the aggregated client data (30A) to the third party service.
A method includes receiving a first facial framework and a first captured image of a face. The first facial framework corresponds to the face at a first frame and includes a first facial mesh of facial information. The method also includes projecting the first captured image onto the first facial framework and determining a facial texture corresponding to the face based on the projected first captured image. The method also includes receiving a second facial framework at a second frame that includes a second facial mesh of facial information and updating the facial texture based on the received second facial framework. The method also includes displaying the updated facial texture as a three-dimensional avatar. The three-dimensional avatar corresponds to a virtual representation of the face.
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
G06T 17/20 - Description filaire, p.ex. polygonalisation ou tessellation
G06T 19/20 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie Édition d'images tridimensionnelles [3D], p.ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
