GOOGLE LLC patent applications on January 25th, 2024
Patent Applications by GOOGLE LLC on January 25th, 2024
GOOGLE LLC: 39 patent applications
GOOGLE LLC has applied for patents in the areas of G10L15/22 (12), G10L15/08 (7), G06F16/9538 (6), G10L15/063 (4), G10L15/06 (4)
With keywords such as: device, data, user, audio, speech, based, utterance, textual, recognition, and sequence in patent application abstracts.
Patent Applications by GOOGLE LLC
Inventor(s): Haroon Baig of Mountain View CA (US) for google llc, Ankit Gupta of Mountain View CA (US) for google llc
IPC Code(s): G01C21/36
Abstract: to provide personalized data for display on a map, a server device obtains location data for a user and identifies locations that are familiar to the user based on the frequency and recency in which the user visits the locations. the server device then provides the familiar locations in search results/suggestions and annotates the familiar locations with a description of a relationship between the familiar location and the user. the server device also includes the familiar locations as landmarks for performing maneuvers in a set of navigation instructions. furthermore, the server device provides a familiar location as a frame of reference on a map display when a user selects another location nearby the familiar location. moreover, the server device includes a familiar location as an intermediate destination when the user request navigation directions to a final destination.
Inventor(s): Muhammad Muneeb Saleem of Mountain View CA (US) for google llc
IPC Code(s): G01S13/58, G01S13/34, G01S7/41
Abstract: techniques and apparatuses are described that implement a smart-device-based radar system capable of performing angular position estimation. a machine-learned module analyzes complex range data generated to estimate angular positions of objects. the machine-learned module is implemented using a multi-stage architecture. in a local stage, the machine-learned module splits the complex range data into different range intervals and separately processes subsets of the complex range data using individual branch modules. in a global stage, the machine-learned module merges the feature data generated from the individual branch modules using a symmetric function and generates angular position data. by using machine-learning techniques and processing the complex range data directly, the radar system can achieve higher angular resolutions compared to other radar systems that utilize other techniques, such as analog or digital beamforming.
Inventor(s): Tuan Nguyen of San Jose CA (US) for google llc, Kenneth Mixter of Los Altos Hills CA (US) for google llc, Yuan Yuan of Redwood City CA (US) for google llc
IPC Code(s): G06F3/01, G06T7/73, G06F9/451, G06F3/03, G06F3/16, G06F3/0482, G06V40/20, G06F18/22
Abstract: methods, apparatus, systems, and computer-readable media are provided for generating and/or adapting automated assistant content according to a distance of a user relative to an automated assistant interface that renders the automated assistant content. for instance, the automated assistant can provide data for a client device to render. the client device can request additional data when the user relocates closer to, or further from, the client device. in some implementations, a request for additional data can identify a distance between the user and the client device. in this way, the additional data can be generated or selected according to the distance in the request. other implementations can allow an automated assistant to determine an active user from a group of users in an environment, and determine a distance between the active user and the client device in order that any rendered content can be tailored for the active user.
Inventor(s): Peter Krogh of Nevada City CA (US) for google llc, Shikha Kapoor of Sunnyvale CA (US) for google llc, Shen-En Shih of Mountain View CA (US) for google llc, Max Loh of Mountain View CA (US) for google llc
IPC Code(s): G06F16/2457, G06F16/242, G06F16/9035, H04M3/493, G10L15/22
Abstract: generation and/or utilization of particular data structure(s) in more efficiently storing, retrieving, and/or presenting personal entry(s) is described herein. implementations can utilize the data structure(s) in more efficiently responding to a vague user request that specifies a particular type of personal entry, but lacks any additional features of the personal entry(s) sought. utilization of the data structure(s) can enable responsive personal entry(s) to be efficiently identified (e.g., processor and/or memory efficiency and/or with reduced latency). for example, some implementations can enable selection of a subgroup of personal entries to provide responsive to the vague request, without necessitating any processing of personal entries, that are not included in the selected subgroup, be performed responsive to the request. as another example, some implementations can additionally or alternatively obviate the need to perform any ranking of the available personal entries of the subgroup on the fly responsive to the request.
Inventor(s): Jian Wei Leong of San Francisco CA (US) for google llc, Nicu Cornea of San Jose CA (US) for google llc, Maya Tekke Anant of Sunnyvale CA (US) for google llc
IPC Code(s): G06F16/432, G06F16/242, G06F16/23, G06F16/25, G06F9/38
Abstract: the present disclosure is generally related to a data processing system to coordinate parallel processing of audio queries across multiple devices. a data processing system can receive an audio input signal detected the display device and parse the audio input signal to identify an entity. the data processing system can transmit a query command to the display device to cause a multimedia content application to perform a search for the entity. the data processing system can access at least one of an address database and a multimedia content provider to identify a reference address for the entity. the data processing system can provide the reference address for the entity to cause the display device to present a content selection interface. the content selection interface can include an element for the reference address, prior to completion of the search for the entity performed by the multimedia content application.
Inventor(s): Benedict Junjie Liang of Singapore (SG) for google llc, Ahmad Nizam Anuar of Johor (MY) for google llc, Sumeet Kale of Singapore (SG) for google llc, Ching-Fei Yang of Singapore (SG) for google llc, Dian Zhang of Beijing (CN) for google llc, Kiat Chuan Tan of Singapore (SG) for google llc
IPC Code(s): G06F16/435, G06F16/48, H04N21/2187
Abstract: the present disclosure provides computer-implemented methods, systems, and devices for generating media content pages for live events at scale. a computing system accesses media data associated with a live event. the computing system customizes media data for one or more user groups. the computing system selects one or more page templates from a plurality of page templates based, at least in part on the customized media data. the computing system generates one or more content pages based on the customized media data and the one or more page templates. the computing system provides the one or more content pages to one or more user computing devices.
Inventor(s): Balint Miklos of Zürich (CH) for google llc, Rajan Sharad Patel of Los Altos CA (US) for google llc, Severin Heiniger of Zürich (CH) for google llc
IPC Code(s): G06F16/532, G06F9/451, G06F16/538
Abstract: systems and methods of the present disclosure are directed to a computer-implemented method for multimodal search refinement. the method includes obtaining a visual search query from a user comprising one or more query images. the method includes providing a search interface for display to the user, the search interface comprising one or more result images responsive to the one or more query images and an interface element indicative of a request to the user to refine the visual search query. the method includes obtaining, from the user, textual data comprising a refinement to the visual search query. the method includes appending, by the computing system, the textual data to the visual search query to obtain a multimodal search query.
20240028656.DISCOVERING ALTERNATE ONLINE SERVICE PROVIDERS_simplified_abstract_(google llc)
Inventor(s): Jared Zimmerman of Mountain View CA (US) for google llc, Heather Campbell of San Francisco CA (US) for google llc
IPC Code(s): G06F16/9535, G06F16/954, G06F16/9538
Abstract: systems and methods are described that include determining an intent from an intent library that matches a received query, identifying, based on the intent, at least one mini-app from a first provider and at least one mini-app from a second provider, ranking the identified mini-apps, and triggering rendering of search results, the search results including at least a first ranked mini-app in an expanded state and the remaining ranked mini-apps in a collapsed state.
Inventor(s): Andrew Jason Lavery of Austin TX (US) for google llc, Michael Vernon Lee of Cedar Park TX (US) for google llc
IPC Code(s): G06F16/957, G06F16/9538, G06F16/958, G06F16/906
Abstract: techniques of modifying user interfaces associated with a browser application includes enabling a user to modify a web page as displayed by the web browser in a way not anticipated by the creators of the web page elements and without needing to understand the internal structure of the web page. for example, improved techniques implemented as part of the technical solution would allow a participant in a web meeting to emphasize the names of other participants having the same manager without knowing anything about the architecture or programming code associated with the web meeting application.
Inventor(s): Keun Soo Yim of San Jose CA (US) for google llc, Bogdan Caprita of Mountain View CA (US) for google llc
IPC Code(s): G06F16/957, G06Q30/06
Abstract: implementations relate to triggering suggestion(s) for a document that is at least partially displayed by a content access application at a user interface of a client computing device. the suggestions(s) can be triggered when one or more triggering conditions that provide when to trigger the suggestion(s) are satisfied. the one or more triggering conditions can include, for example, a coordinate condition, a dom node condition, and/or a temporal condition.
20240028822.CONTEXTUAL ANSWER GENERATION IN SPREADSHEETS_simplified_abstract_(google llc)
Inventor(s): Gökhan Bakir of Zurich (CH) for google llc
IPC Code(s): G06F40/18, G06F16/9538
Abstract: a method includes receiving, via a user interface of a client device, a request to populate one or more cells of a plurality of cells of a document having a tabular structure, wherein the one or more cells correspond to a first attribute pertaining to a first column header and a first object pertaining to a first row header; analyzing the request and one or more additional cells corresponding to one or more additional attributes and one or more additional objects of the document to obtain contextual information for the request; generating a query based at least in part on the contextual information; initiating an execution of the query to obtain a response using one or more data sources; and causing the user interface to be modified to populate the response in the one or more cells corresponding to the first attribute and the first object.
20240028829.Joint Speech and Text Streaming Model for ASR_simplified_abstract_(google llc)
Inventor(s): Tara N. Sainath of Jersey City NJ (US) for google llc, Zhouyuan Huo of Mountain View CA (US) for google llc, Zhehuai Chen of Edgewater NJ (US) for google llc, Yu Zhang of Mountain View CA (US) for google llc, Weiran Wang of Palo Alto CA (US) for google llc, Trevor Strohman of Mountain View CA (US) for google llc, Rohit Prakash Prabhavalkar of Palo Alto CA (US) for google llc, Bo Li of Fremont CA (US) for google llc, Ankur Bapna of Sunnyvale CA (US) for google llc
IPC Code(s): G06F40/284, G06F40/40
Abstract: a method includes receiving training data that includes a set of unspoken textual utterances. for each respective unspoken textual utterance, the method includes, tokenizing the respective textual utterance into a sequence of sub-word units, generating a first higher order textual feature representation for a corresponding sub-word unit tokenized from the respective unspoken textual utterance, receiving the first higher order textual feature representation generated by a text encoder, and generating a first probability distribution over possible text units. the method also includes training an encoder based on the first probability distribution over possible text units generated by a first-pass decoder for each respective unspoken textual utterance in the set of unspoken textual utterances.
Inventor(s): William Chan of Toronto (CA) for google llc, Mitchell Thomas Stern of Berkeley CA (US) for google llc, Nikita Kitaev of Berkeley CA (US) for google llc, Kelvin Gu of Mountain View CA (US) for google llc, Jakob D. Uszkoreit of Berlin (DE) for google llc
IPC Code(s): G06N3/08, G06F40/237, G06N3/04, G06N3/084
Abstract: methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing sequence modeling tasks using insertions. one of the methods includes receiving a system input that includes one or more source elements from a source sequence and zero or more target elements from a target sequence, wherein each source element is selected from a vocabulary of source elements and wherein each target element is selected from a vocabulary of target elements; generating a partial concatenated sequence that includes the one or more source elements from the source sequence and the zero or more target elements from the target sequence, wherein the source and target elements arranged in the partial concatenated sequence according to a combined order; and generating a final concatenated sequence that includes a finalized source sequence and a finalized target sequence, wherein the finalized target sequence includes one or more target elements.
20240029296.Orientation Determination for Mobile Computing Devices_simplified_abstract_(google llc)
Inventor(s): Daniel Joseph Filip of San Jose CA (US) for google llc
IPC Code(s): G06T7/73, G06V10/12, G06V10/60, G06V10/24, G06V10/82, G06V20/50
Abstract: methods, systems, devices, and tangible non-transitory computer readable media for determining orientation are provided. the disclosed technology can include capturing images of an environment visible in a field of view of the mobile computing device. location data associated with a location of the mobile computing device can be received. image data including information associated with the images can be generated. based on the image data and one or more machine-learned models, features of one or more objects in the environment can be determined. based on the location data and the features of the objects, respective orientations of the objects relative to the location of the mobile computing device can be determined. furthermore, orientation data that includes a geographic orientation of the mobile computing device can be generated based on the respective (geographic) orientations of the objects.
Inventor(s): Abhimitra Meka of San Francisco CA (US) for google llc, Thabo Beeler of Egg (CH) for google llc, Franziska Müller of Zurich (CH) for google llc, Gengyan Li of Volketswil (CH) for google llc, Marcel Bühler of Truttikon (CH) for google llc, Otmar Hilliges of Zurich (CH) for google llc
IPC Code(s): G06T13/40, G06T17/20, G06T15/50
Abstract: a method including selecting a first point from a 3d model representing an avatar, the first point being associated with an eye, selecting a second point from the 3d model, the second point being associated with a periocular region associated with the eye, generating an albedo and spherical harmonics (sh) coefficients based on the first point and the second point, and generating an image point based on the albedo, and the sh coefficients.
20240029413.Dynamic training of Models_simplified_abstract_(google llc)
Inventor(s): Anthony Jacob Piergiovanni of Mountain View CA (US) for google llc, Weiching Kuo of Mountain View CA (US) for google llc, Wei Li of Mountain View CA (US) for google llc, Anelia Angelova of Mountain View CA (US) for google llc
IPC Code(s): G06V10/774, G06V10/25
Abstract: a method involves the training of a model by dynamically adjusting the number of examples within each training batch. the dynamic adjustment is accomplished by adjusting the number of examples per task within each training batch according to the performance of the model on the tasks that the model is being trained on. in some embodiments, this method is applied to cross-modal vision-language tasks. this model may also be applied to the pre-training of a model that can be later fine-tuned for a more specific task(s).
20240029640.BACKPLANE CONFIGURATIONS AND OPERATIONS_simplified_abstract_(google llc)
Inventor(s): Gang He of Cupertino CA (US) for google llc
IPC Code(s): G09G3/32
Abstract: the disclosure describes various aspects of backplanes, including unit cells, architectures, and operations. in an aspect, a backplane unit cell is described that includes first and second switches, a storage element, a comparator, a source (e.g., a current or voltage source), where the source generates a drive signal to control light emission of a selected one of the light emitting elements in a display, and where the drive signal is based on a power signal selected by the second switch. in another aspect, a device is described that includes a backplane configured in an active matrix topology including multiple data columns and multiple row selects; and a set of electrical contacts associated with the active matrix topology and configured to electrically couple the backplane with the display, the display having multiple light emitting elements configured in a passive matrix topology. methods of operation of the backplane are also described.
20240029706.DEVICES AND METHODS FOR A SPEECH-BASED USER INTERFACE_simplified_abstract_(google llc)
Inventor(s): Ioannis Agiomyrgiannakis of London (GB) for google llc, Fergus James Henderson of Twickenham (GB) for google llc
IPC Code(s): G10L13/033, G06F3/16, G10L13/10
Abstract: a device may identify a plurality of sources for outputs that the device is configured to provide. the plurality of sources may include at least one of a particular application in the device, an operating system of the device, a particular area within a display of the device, or a particular graphical user interface object. the device may also assign a set of distinct voices to respective sources of the plurality of sources. the device may also receive a request for speech output. the device may also select a particular source that is associated with the requested speech output. the device may also generate speech having particular voice characteristics of a particular voice assigned to the particular source.
Inventor(s): Françoise Beaufays of Mountain View CA (US) for google llc, Johan Schalkwyk of Scarsdale NY (US) for google llc, Giovanni Motta of San Jose CA (US) for google llc
IPC Code(s): G10L15/00, G06F3/04842, G06F3/04883, G10L25/51
Abstract: processor(s) of a client device can: receive audio data that captures a spoken utterance of a user of the client device; process, using an on-device speech recognition model, the audio data to generate a predicted textual segment that is a prediction of the spoken utterance; cause at least part of the predicted textual segment to be rendered (e.g., visually and/or audibly); receive further user interface input that is a correction of the predicted textual segment to an alternate textual segment; and generate a gradient based on comparing at least part of the predicted output to ground truth output that corresponds to the alternate textual segment. the gradient is used, by processor(s) of the client device, to update weights of the on-device speech recognition model and/or is transmitted to a remote system for use in remote updating of global weights of a global speech recognition model.
Inventor(s): Andrew Rosenberg of Brooklyn NY (US) for google llc, Zhehuai Chen of Edgewater NJ (US) for google llc, Ankur Bapna of Sunnyvale CA (US) for google llc, Yu Zhang of Mountain View CA (US) for google llc, Bhuvana Ramabhadran of Mt. Kisco NY (US) for google llc
IPC Code(s): G10L15/06
Abstract: a method includes receiving training data that includes unspoken textual utterances in a target language. each unspoken textual utterance not paired with any corresponding spoken utterance of non-synthetic speech. the method also includes generating a corresponding alignment output for each unspoken textual utterance using an alignment model trained on transcribed speech utterance in one or more training languages each different than the target language. the method also includes generating a corresponding encoded textual representation for each alignment output using a text encoder and training a speech recognition model on the encoded textual representations generated for the alignment outputs. training the speech recognition model teaches the speech recognition model to learn how to recognize speech in the target language.
Inventor(s): Thibault Doutre of Mountain View CA (US) for google llc, Wei Han of Mountain View CA (US) for google llc, Min Ma of Mountain View CA (US) for google llc, Zhiyun Lu of Mountain View CA (US) for google llc, Chung-Cheng Chiu of Sunnyvale CA (US) for google llc, Ruoming Pang of New York NY (US) for google llc, Arun Narayanan of Santa Clara CA (US) for google llc, Ananya Misra of Mountain View CA (US) for google llc, Yu Zhang of Mountain View CA (US) for google llc, Liangliang Cao of Mountain View CA (US) for google llc
IPC Code(s): G10L15/06, G10L15/08, G10L15/18, G06N3/045
Abstract: a method for training a streaming automatic speech recognition student model includes receiving a plurality of unlabeled student training utterances. the method also includes, for each unlabeled student training utterance, generating a transcription corresponding to the respective unlabeled student training utterance using a plurality of non-streaming automated speech recognition (asr) teacher models. the method further includes distilling a streaming asr student model from the plurality of non-streaming asr teacher models by training the streaming asr student model using the plurality of unlabeled student training utterances paired with the corresponding transcriptions generated by the plurality of non-streaming asr teacher models.
Inventor(s): Antoine Jean Bruguier of Milpitas CA (US) for google llc, David Qiu of Fremont CA (US) for google llc, Yangzhang He of Mountain View CA (US) for google llc, Trevor Strohman of Mountain View CA (US) for google llc
IPC Code(s): G10L15/10, G10L15/26
Abstract: a method includes processing, using a speech recognizer, a first portion of audio data to generate a first lattice, and generating a first partial transcription for an utterance based on the first lattice. the method includes processing, using the recognizer, a second portion of the data to generate, based on the first lattice, a second lattice representing a plurality of partial speech recognition hypotheses for the utterance and a plurality of corresponding speech recognition scores. for each particular partial speech recognition hypothesis, the method includes generating a corresponding re-ranked score based on the corresponding speech recognition score and whether the particular partial speech recognition hypothesis shares a prefix with the first partial transcription. the method includes generating a second partial transcription for the utterance by selecting the partial speech recognition hypothesis of the second plurality of partial speech recognition hypotheses having the highest corresponding re-ranked score.
Inventor(s): Shaan Jagdeep Patrick Bijwadia of San Francisco CA (US) for google llc, Shuo-yiin Chang of Sunnyvale CA (US) for google llc, Bo Li of Fremont CA (US) for google llc, Yanzhang He of Palo Alto CA (US) for google llc, Tara N. Sainath of Jersey City NJ (US) for google llc, Chao Zhang of Mountain View CA (US) for google llc
IPC Code(s): G10L15/16, G10L15/06, G10L25/93
Abstract: a single e2e multitask model includes a speech recognition model and an endpointer model. the speech recognition model includes an audio encoder configured to encode a sequence of audio frames into corresponding higher-order feature representations, and a decoder configured to generate probability distributions over possible speech recognition hypotheses for the sequence of audio frames based on the higher-order feature representations. the endpointer model is configured to operate between a vad mode and an eoq detection mode. during the vad mode, the endpointer model receives input audio frames, and determines, for each input audio frame, whether the input audio frame includes speech. during the eoq detection mode, the endpointer model receives latent representations for the sequence of audio frames output from the audio encoder, and determines, for each of the latent representation, whether the latent representation includes final silence.
Inventor(s): David Qiu of Fremont CA (US) for google llc, Tsendsuren Munkhdalai of Mountain View CA (US) for google llc, Yangzhang He of Mountain View CA (US) for google llc, Khe Chai Sim of Dublin CA (US) for google llc
IPC Code(s): G10L15/16, G10L15/02, G10L15/22, G10L15/06, G10L15/19
Abstract: an automatic speech recognition (asr) system that includes an asr model, a neural associative memory (nam) biasing model, and a confidence estimation model (cem). the asr model includes an audio encoder configured to encode a sequence of audio frames characterizing a spoken utterance into a sequence of higher-order feature representations, and a decoder configured to receive the sequence of higher-order feature representations and output a final speech recognition result. the nam biasing model is configured to receive biasing contextual information and modify the sequence of higher-order feature representations based on the biasing contextual information to generate, as output, biasing context vectors. the cem is configured to compute a confidence of the final speech recognition result output by the decoder. the cem is connected to the biasing context vectors generated by the nam biasing model.
Inventor(s): Nicolo D'Ercole of Oberrieden (CH) for google llc, Shumin Zhai of Zurich (CH) for google llc, Swante Scholz of Zurich (CH) for google llc, Mehek Sharma of Thalwil (CH) for google llc, Adrien Olczak of Irvine CA (US) for google llc, Akshay Kannan of Fremont CA (US) for google llc, Alvin Abdagic of Zurich (CH) for google llc, Julia Proskurnia of Zurich (CH) for google llc, Viesturs Zarins of Zurich (CH) for google llc
IPC Code(s): G10L15/22, G10L15/08, G06F16/683
Abstract: implementations described herein generally relate to generating a modification selectable element that may be provided for presentation to a user in a smart dictation session with an automated assistant. the modification selectable element may, when selected, cause a transcription, that includes textual data generated based on processing audio data that captures a spoken utterance and that is automatically arranged, to be modified. the transcription may be automatically arranged to include spacing, punctuation, capitalization, indentations, paragraph breaks, and/or other arrangement operations that are not specified by the user in providing the spoken utterance. accordingly, a subsequent selection of the modification selectable element may cause these automatic arrangement operation(s), and/or the textual data locationally proximate to these automatic arrangement operation(s), to be modified. implementations described herein also relate to generating the transcription and/or the modification selectable element on behalf of a third-party software application.
20240029735.MULTI-USER VIRTUAL ASSISTANT FOR VERBAL DEVICE CONTROL_simplified_abstract_(google llc)
Inventor(s): Yuzhao Ni of Sunnyvale CA (US) for google llc, David Roy Schairer of San Jose CA (US) for google llc
IPC Code(s): G10L15/22, G10L15/08, G10L17/22, G06F21/32, H04L9/40
Abstract: in one example, a method includes receiving audio data generated by one or more microphones of a computing device, the audio data representing a spoken utterance; identifying, based on the audio data, a user that provided the spoken utterance; identifying, based on the audio data, an automation action associated with one or more automation devices, the automation action corresponding to the spoken utterance; determining whether the identified user is authorized to cause performance of the identified automation action; and responsive to determining that the identified user is authorized to cause performance of the identified automation action, causing the one or more automation devices to perform the identified automation action.
Inventor(s): Matthew Sharifi of Kilchberg (CH) for google llc, Aleksandar Kracun of New York NY (US) for google llc
IPC Code(s): G10L15/30, G06F16/63, G10L15/08, G10L15/22, H04L67/568
Abstract: a method includes receiving an automated speech recognition (asr) request from a user device that includes a speech input captured by the user device and content metadata associated with the speech input. the content metadata is generated by the user device. the method also includes determining a priority score for the asr request based on the content metadata associated with the speech input and caching the asr request in a pre-processing backlog of pending asr requests each having a corresponding priority score. the pending asr requests in the pre-processing backlog are ranked in order of the priority scores. the method also includes providing, from the pre-processing backlog, one or more of the pending asr requests to a backend-side asr module, wherein pending asr requests associated with higher priority scores are processed before pending asr requests associated with lower priority scores.
20240029742.ATTENTIVE SCORING FUNCTION FOR SPEAKER IDENTIFICATION_simplified_abstract_(google llc)
Inventor(s): Ignacio Lopez Moreno of New York NY (US) for google llc, Quan Wang of Hoboken NJ (US) for google llc, Jason Pelecanos of Mountain View CA (US) for google llc, Yiling Huang of Mountain View CA (US) for google llc, Mert Saglam of Mountain View CA (US) for google llc
IPC Code(s): G10L17/06, G06F16/245, G06N3/08, G10L17/04, G10L17/18
Abstract: a speaker verification method includes receiving audio data corresponding to an utterance, processing the audio data to generate a reference attentive d-vector representing voice characteristics of the utterance, the evaluation ad-vector includes nstyle classes each including a respective value vector concatenated with a corresponding routing vector. the method also includes generating using a self-attention mechanism, at least one multi-condition attention score that indicates a likelihood that the evaluation ad-vector matches a respective reference ad-vector associated with a respective user. the method also includes identifying the speaker of the utterance as the respective user associated with the respective reference ad-vector based on the multi-condition attention score.
20240030380.LIGHT EMITTING DEVICES WITH REDUCED STRAIN_simplified_abstract_(google llc)
Inventor(s): Melvin Barker McLaurin of Oakland CA (US) for google llc, Aurelien Jean Francois David of San Francisco CA (US) for google llc
IPC Code(s): H01L33/12, H01L33/00, H01L33/02
Abstract: in a general aspect, a method for producing an optoelectronic device includes forming a mechanically-compliant layer on a substrate, and forming a second layer, the mechanically-compliant layer being disposed between the second layer and the substrate. the method also includes performing a relaxation operation to facilitate a release of strain energy in the second layer by the mechanically-compliant layer. the mechanically-compliant layer, the second layer and the relaxation operation are configured such that a surface of the second layer has an extended defect density below a predetermined value. the method also includes forming a light-emitting region, the second layer being disposed between the light-emitting region and the substrate. the extended defect density being below the predetermined value results in a leakage resistance in an active region of the light-emitting region that is higher than 10 milliohms per centimeter-squared (mohm/cm2).
Inventor(s): Jeffrey Brown of Mountain View CA (US) for google llc, Kristopher Giesing of Palo Alto CA (US) for google llc, Steffen Meschkat of Menlo Park CA (US) for google llc, Alhaad Gokhale of Sunnyvale CA (US) for google llc
IPC Code(s): H04L7/00, H04L69/329, G06F8/61, G06F16/178, H04L67/01
Abstract: a system and method are provided that permits different devices with different applications to respond to the occurrence of a condition in a similar manner. by way of example, trigger data may be synchronized across multiple devices, wherein trigger data identifies information to be provided to a program in response to the occurrence of a condition. if a program is not installed or running on a particular device when the trigger occurs, the device automatically installs and executes the application.
20240031261.STANDARDIZING ANALYSIS METRICS ACROSS MULTIPLE DEVICES_simplified_abstract_(google llc)
Inventor(s): Prithwish Mukherjee of Mountain View CA (US) for google llc, Sujee Rajayogam of San Diego CA (US) for google llc
IPC Code(s): H04L43/065, G10L15/22, G10L15/30, H04L41/02
Abstract: implementations relate to generating standardized metrics from device specific metrics that are generated during an interaction between a user and an automated assistant. the metrics indicate events that occurred while processing an interaction of a user with the automated assistant and are specific to the particular configuration of the device with which the user is interacting. conversion mappings are determined based on device characteristics that can be utilized to convert the device metrics into standardized metrics. analysis metrics are generated based on the standardized metrics that are incapable of being generated from the device metrics. some implementations include visually rendering the analysis metrics such that one or more of the analysis metrics are rendered more prominently than other metrics.
Inventor(s): Akshay Goel of Seattle WA (US) for google llc, Jonathan Eccles of San Francisco CA (US) for google llc, Nitin Khandelwal of Sunnyvale CA (US) for google llc, Sarvjeet Singh of Palo Alto CA (US) for google llc, David Sanchez of Burlingame CA (US) for google llc, Ashwin Ram of Los Altos CA (US) for google llc
IPC Code(s): H04L9/40
Abstract: implementations described herein utilize an independent server for facilitating secure exchange of data between multiple disparate parties. the independent server receives client data, via an automated assistant application executing at least in part at a client device, that is to be transmitted to a given third-party application. the independent server processes the client data, using a first encoder-decoder model, to generate opaque client data, and transmits the opaque client data to the given third-party application and without transmitting any of the client data. further, the independent server receives response data, via the given third-party application, that is generated based on the opaque client data and that is to be transmitted back to the client device. the independent server processes the response data, using a second encoder-decoder model, to generate opaque response data, and transmits the opaque response data to the client device and without transmitting any of the response data.
20240031364.RECONFIGURABLE ROBOTIC MANUFACTURING CELLS_simplified_abstract_(google llc)
Inventor(s): Nivedita Ravi of Redmond WA (US) for google llc, John William Zevenbergen, IV of Woodway WA (US) for google llc, Joseph Neil Reichenbach of Snoqualmie WA (US) for google llc, Toby Ge Xu of Seattle WA (US) for google llc
IPC Code(s): H04L9/40
Abstract: a manufacturing process adopting the reconfigurable robotic manufacturing cells that can work conjointly and yet have the capabilities to be reconfigured to disconnect from other cells and handle multiple tasks. the reconfigurable robotic cell is not dependent on any other robotic cells to complete work in progress.
20240031482.Synchronous Communication Using Voice and Text_simplified_abstract_(google llc)
Inventor(s): Shavit Matias of Tel Aviv (IL) for google llc, Noam Etzion-Rosenberg of Tel Aviv (IL) for google llc, Rebecca Chiou of San Mateo CA (US) for google llc, Benjamin Schlesinger of Tel Aviv (IL) for google llc, Brandon Charles Barbello of San Jose CA (US) for google llc, Ori Kabeli of Yehud (IL) for google llc, Usman Abdullah of Sunnyvale CA (US) for google llc, Eric Erfanian of Bellevue WA (US) for google llc, Michelle Tadmor of Tel Aviv (IL) for google llc, Aditi Bhargava of Cortlandt NY (US) for google llc, Jan Piotr Jedrzejowicz of San Francisco CA (US) for google llc, Alex Agranovich of Herzliya (IL) for google llc, Nir Shemy of Tel Aviv (IL) for google llc, Paul Dunlop of London (GB) for google llc, Yossi Matias of Tel Aviv (IL) for google llc, Kyungmin Youn of Thalwil (CH) for google llc, Nadav Bar of Tel Aviv (IL) for google llc
IPC Code(s): H04M3/436, H04M3/42
Abstract: a computing device is described that accepts, a telephone call, from another device, initiated by a caller. prior to establishing a telephone user interface that receives spoken input from the user and outputs spoken audio from the caller, the computing device executes a call screening service that outputs an audio user interface, to the other device and as part of the telephone call. the audio user interface interrogates the caller for additional information including a purpose of the telephone call, which allows the user to have more context of the telephone call before deciding whether to accept the call or hang up. the computing device outputs a graphical user interface associated with telephone call. the graphical user interface includes an indication of the additional information obtained via the audio user interface that interrogates the caller.
Inventor(s): Yuval Baror of Mountain View CA (US) for google llc, Michael Andrew Goodman of Oakland CA (US) for google llc, Yoav Tzur of TelAviv (IL) for google llc
IPC Code(s): H04M3/493, G06F16/901, H04M3/51
Abstract: implementations are directed to utilizing an assistant to automatically navigate an interactive voice response (ivr) tree to arrive at a target state during an assisted telephone call. the assistant can receive input to initiate the assisted telephone call, identify an entity to engage with, on behalf of the user, and during the assisted telephone call, based on the input, and identify an ivr tree stored in association with the entity. in various implementations, navigation of the ivr tree can be modified based on interaction(s) detected at a client device subsequent to initiating the assisted telephone call. in various implementations, the assisted telephone call can be initiated from a search interface, and the target state can be associated with a given search result. in various implementations, the ivr tree can be dynamic in that only a subset of candidate state(s) of the ivr tree may be available as the target state.
Inventor(s): Henrik Fahlberg Lundin of Sollentuna (SE) for google llc, Alessio Bazzica of Stockholm (SE) for google llc, Esbjörn Dominique of Stockholm (SE) for google llc, Per Erik Daniel Johansson of Stockholm (SE) for google llc, Tomas Gunnarsson of Stockholm (SE) for google llc, Markus Lindroth of Uppsala (SE) for google llc, Karl Allan Tore Rudberg of Stockholm (SE) for google llc
IPC Code(s): H04M3/56, G10L21/0364, G10L25/51, G10L25/84, G10L21/028, G10L21/034, G10L17/06
Abstract: methods, systems, and apparatus for normalizing audio transmissions from multiple endpoints within a teleconference. a first audio transmission from a first participant of a teleconference can be received for presentation at the teleconference. the first audio transmission can be analyzed to classify one or more audio signatures of the first audio transmission as speech. a difference can be determined between the audio level of the one or more audio signatures and an audio level of second transmissions. based on the difference, the first audio transmission can be normalized to adjust a gain of the first transmission. the transmission can be output to the teleconference.
20240031773.SHARING STATE BASED ON DIRECTIONAL PROFILES_simplified_abstract_(google llc)
Inventor(s): Dongeek Shin of Santa Clara CA (US) for google llc
IPC Code(s): H04W4/029, H04W4/02
Abstract: a method can include determining, by a correlation device, that a correlation event has occurred based on at least a first device and a second device having corresponding directional profiles, and responsive to occurrence of the correlation event, causing the first device to transfer a state of the first device by sending a state information message to the second device.
Inventor(s): Marci Meingast of San Francisco CA (US) for google llc, Andrew Axley of Mountain View CA (US) for google llc, Daniele Midi of San Francisco CA (US) for google llc
IPC Code(s): H04W24/08, G06N20/00
Abstract: systems and techniques are provided for determination of user presence and absence using wifi connections. reports may be received from wifi access points in an environment. the reports may include an identifier of a wifi device, an indication of a connection to or disconnection from a wifi access point, a time of the connection or disconnection, and an identifier of the wifi access point. a connection sequence for the wifi device may be generated from the reports. whether the wifi device is present in or absent from the environment as of a specified time may be determined based on the connection sequence. an indication of presence for a user associated with the wifi device may generated if the wifi device is present in the environment. an indication of absence for the user associated with the wifi device may be generated if the wifi device is absent from the environment.
20240031893.MANAGING UE CONNECTIONS AFTER NETWORK TOPOLOGY CHANGE_simplified_abstract_(google llc)
Inventor(s): Chih-Hsiang Wu of Mountain View CA (US) for google llc
IPC Code(s): H04W36/08, H04W36/00
Abstract: a source donor, for managing a connection between a user equipment (ue) and a radio access network (ran) via an integrated access backhaul (iab)-node, (i) determines (), when the iab-node communicates with the ran via the source donor, that the iab-node is to migrate from the source donor to establish a new radio connection with the ran, and (ii) subsequently to the determining and prior to the ue and the iab-node establishing respective new connections with the ran, facilitates () exchange of data between the ue and a core network (cn) via the source donor and the target donor.
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