Google LLC patent applications on September 12th, 2024
Patent Applications by Google LLC on September 12th, 2024
Google LLC: 37 patent applications
Google LLC has applied for patents in the areas of G10L15/06 (4), G10L15/22 (4), G06N3/04 (3), G06N3/08 (2), G10L15/20 (2) G06Q40/04 (2), G10L15/20 (2), G10L15/197 (2), G10L15/063 (2), G06F1/1683 (1)
With keywords such as: data, based, user, content, device, input, network, token, example, and computing in patent application abstracts.
Patent Applications by Google LLC
20240302872. INTEGRATION OF A HINGE ON A FOLDABLE DEVICE_simplified_abstract_(google llc)
Inventor(s): Michael J. Lombardi of South Barrington IL (US) for google llc, Joseph Allore of Mundelein IL (US) for google llc, Sangsoo Park of San Jose CA (US) for google llc
IPC Code(s): G06F1/16, H01Q1/22
CPC Code(s): G06F1/1683
Abstract: an example folding device () includes a hinge assembly (), a first assembly (), and a second assembly (). the hinge assembly () defines a first axis () and a second axis (). the first assembly () includes a first arm (), formed from a first material and rotatably connected to the hinge assembly about the first axis, a first main housing component (), and a first divider () disposed between the first arm () and the first main housing component (). the first main housing component () is formed from a second material that is different than the first material. the second assembly () includes a second arm (), formed from the first material and rotatably connected to the hinge assembly about the second axis, a second main housing component (), and a second divider () disposed between the second arm () and the second main housing component (). the second main housing component () is formed from a second material that is different than the first material. folding device () may include housing components formed from different materials with different properties (e.g. strength, weight, thermal conductivity, galvanic isolation, etc.) to address one or more of the disadvantages (e.g. thickness, weight, thermal performance, wireless transmission performance, reliability, complexity, cost, etc.) while achieving a continuous color appearance.
20240302935. Multiple Views of a Geographic Area on a Mobile Device_simplified_abstract_(google llc)
Inventor(s): Adam Bliss of Drain OR (US) for google llc, Mark Crady of Palo Alto CA (US) for google llc, Michael Chu of Los Gatos CA (US) for google llc, Scott Jenson of Palo Alto CA (US) for google llc, Sanjay Mavinkurve of East Palo Alto CA (US) for google llc, Joshua J. Sacks of Woodside CA (US) for google llc, Jerry Morrison of Mountain View CA (US) for google llc
IPC Code(s): G06F3/04817, G01C21/36, G06F3/048, G06F3/0482, G06F16/29, G06F16/951, G06F16/9535, G06F16/9537, G06F16/9538, G06F16/954, G09B29/10, H04M1/02, H04M1/724, H04M1/72457
CPC Code(s): G06F3/04817
Abstract: a computer-implemented method is disclosed that includes receiving on a mobile device a search query associated with a geographic location, providing one or more search results in response to the search query, the search results each being associated with a geographic location, and presenting on a graphical display of the computing device icons corresponding to each search result and also corresponding to a key on the computing device.
Inventor(s): Derek James Basehore of Menlo Park CA (US) for google llc, Nicholas Jordan Sanders of Saratoga CA (US) for google llc
IPC Code(s): G06F9/30, G06F9/38
CPC Code(s): G06F9/30149
Abstract: this disclosure describes apparatuses, methods, and techniques for supporting a parallel decode instruction set computer architecture with variable-length instructions. in various aspects, a processor receives an instruction for execution. a decoder identifies multiple fixed-length prefixes in the instruction and identifies multiple variable-length suffixes in the instruction. each of the multiple fixed-length prefixes is associated with one of the variable-length suffixes. the instruction is then executed based on the plurality of variable-length suffixes. by so doing, the described systems and methods may be implemented in a manner that reduces program size and reduces the required area on the silicon chip.
20240303243. Retrieval and Composition of Modular Spaces_simplified_abstract_(google llc)
Inventor(s): Cliff Shan Kuang of San Francisco CA (US) for google llc, Joshua Lance Leviste Principe of Los Angeles CA (US) for google llc, Kevin Gaunt of San Francisco CA (US) for google llc, Ricardo Bruno Augusto Enriques of Lagos (PT) for google llc
IPC Code(s): G06F16/2457, G06F16/22
CPC Code(s): G06F16/24578
Abstract: example embodiments of the present disclosure provide for an example method including obtaining component data associated with a plurality of components. the example method includes generating an index of the component data and obtaining user input data indicative of a request. the example method includes processing the user input data to determine an intent associated with the request and obtaining, based on the intent, data indicative of one or more components from the index. the example method includes determining a rank for at least one respective component of the one or more components. the example method includes updating a user interface to display the one or more components, wherein the components are displayed based at least in part on the rank of the respective component. the example method can include generating modular spaces composed of a plurality of components to generate composite application interfaces which can include cross-application functionalities.
20240303267. Contextual Querying of Content Rendering Activity_simplified_abstract_(google llc)
Inventor(s): Ramprasad Sedouram of Bangalore (IN) for google llc, Patlavath Bharathi Dharma Teja Naik of Bangalore (IN) for google llc
IPC Code(s): G06F16/438, G06F3/16, G06F16/432, G06F16/532
CPC Code(s): G06F16/438
Abstract: in an example aspect, the present disclosure provides for an example method for processing queries over content rendering activity. the example method includes receiving, by a computing system comprising one or more processors, a first input signal of a first modality, the first input signal being obtained using one or more sensors of a client device and providing local context signals associated with a content rendering event on an output device. the example method includes receiving, by the computing system, a second input signal of a second modality different from the first modality. the example method includes generating, by the computing system and based on the first input signal and the second input signal, a content query. the example method includes retrieving, by the computing system and based on the content query, a content item associated with the content rendering event.
20240303297. LOW LATENCY MATRIX MULTIPLY UNIT_simplified_abstract_(google llc)
Inventor(s): Andrew Everett Phelps of Middleton WI (US) for google llc, Norman Paul Jouppi of Palo Alto CA (US) for google llc
IPC Code(s): G06F17/16, G06F5/01, G06F9/30, G06F15/80, G06N3/04, G06N3/08
CPC Code(s): G06F17/16
Abstract: methods, systems, and apparatus for a matrix multiply unit implemented as a systolic array of cells are disclosed. each cell of the matrix multiply includes: a weight matrix register configured to receive a weight input from either a transposed or a non-transposed weight shift register; a transposed weight shift register configured to receive a weight input from a horizontal direction to be stored in the weight matrix register; a non-transposed weight shift register configured to receive a weight input from a vertical direction to be stored in the weight matrix register; and a multiply unit that is coupled to the weight matrix register and configured to multiply the weight input of the weight matrix register with a vector data input in order to obtain a multiplication result.
20240303417. STORAGE OF CONTENT ASSOCIATED WITH A RESOURCE LOCATOR_simplified_abstract_(google llc)
Inventor(s): Mark Chang of Seattle WA (US) for google llc, Sébastien Séguin-Gagnon of Montreal (CA) for google llc, David Bokan of Toronto (CA) for google llc, Grant Wang of Mountain View CA (US) for google llc, Nasim Sedaghat of Montreal (CA) for google llc, Jason Edward Dishlip of Seattle WA (US) for google llc, Joel Roger Beukelman of Franklin TN (US) for google llc, Evelyn Tio of San Francisco CA (US) for google llc, Arielle Baio of Pacifica CA (US) for google llc, Shuangshuang Li of Los Angeles CA (US) for google llc
IPC Code(s): G06F40/169, G06F3/0483, G06F3/04842, G06F3/0485, G06F16/954, G06F16/958
CPC Code(s): G06F40/169
Abstract: a method can be performed by a browser. the method can include presenting at least a portion of a resource address; presenting a rendered webpage in a browser content window, the rendered webpage being associated with the resource address; presenting an annotation area, the annotation area being outside the browser content window; receiving, in association with a user account, an annotation in the annotation area; and storing the annotation in association with the user account and the resource address.
Inventor(s): Nan Du of San Jose CA (US) for google llc, Tao Wang of Sunnyvale CA (US) for google llc, Yanqi Zhou of Hillsborough CA (US) for google llc, Tao Lei of Sunnyvale CA (US) for google llc, Yuanzhong Xu of Mountain View CA (US) for google llc, Andrew Mingbo Dai of San Francisco CA (US) for google llc, Zhifeng Chen of Sunnyvale CA (US) for google llc, Dewen Zeng of Mishawaka IN (US) for google llc, Yingwei Cui of Palo Alto CA (US) for google llc
IPC Code(s): G06N3/04, G06N3/084
CPC Code(s): G06N3/04
Abstract: a method includes providing a first set of data objects to a first skip router of a neural network (nn). the nn includes a first nn layer and a second nn layer. the first set of data objects is subdivided into a first set of skip objects and a first set of non-skip objects based on a first skip logic implemented by the first skip router and a first context of each data object in the first set of data objects. a first set of processed objects is generated based on the first set of non-skip objects and a first layer logic implemented by the first nn layer. predictions are generated based on a second set of data objects and a second layer logic implemented by the second nn layer. the second set of data objects includes the first set of processed objects and the first set of skip objects.
Inventor(s): Jibing Wang of San Jose CA (US) for google llc, Erik Richard Stauffer of Sunnyvale CA (US) for google llc
IPC Code(s): G06N3/08, G06N3/04, H04B7/026
CPC Code(s): G06N3/08
Abstract: techniques and apparatuses are described for deep neural network (dnn) processing for a user equipment-coordination set (uecs). a network entity selects () an end-to-end (e2e) machine-learning (ml) configuration that forms an e2e dnn for processing uecs communications. the network entity directs () each device of multiple devices participating in an uecs to form, using at least a portion of the e2e ml configuration, a respective sub-dnn of the e2e dnn that transfers the uecs communications through the e2e communication, where the multiple devices include at least one base station, a coordinating user equipment (ue), and at least one additional ue. the network entity receives () feedback associated with the uecs communications and identifies () an adjustment to the e2e ml configuration. the network entity then directs at least some of the multiple devices participating in an uecs to update the respective sub-dnn of the e2e dnn based on the adjustment.
Inventor(s): Yuezhen Niu of El Segundo CA (US) for google llc, Hartmut Neven of Malibu CA (US) for google llc, Vadim Smelyanskiy of Mountain View CA (US) for google llc, Sergio Boixo Castrillo of Rancho Palos Verdes CA (US) for google llc
IPC Code(s): G06N3/094, G06N10/60
CPC Code(s): G06N3/094
Abstract: methods and apparatus for learning a target quantum state. in one aspect, a method for training a quantum generative adversarial network (qgan) to learn a target quantum state includes iteratively adjusting parameters of the qgan until a value of a qgan loss function converges, wherein each iteration comprises: performing an entangling operation on a discriminator network input of a discriminator network in the qgan to measure a fidelity of the discriminator network input, wherein the discriminator network input comprises the target quantum state and a first quantum state output from a generator network in the qgan, wherein the first quantum state approximates the target quantum state; and performing a minimax optimization of the qgan loss function to update the qgan parameters, wherein the qgan loss function is dependent on the measured fidelity of the discriminator network input.
Inventor(s): Laura Marie Eidem of Mountain View CA (US) for google llc, Alex Daniel Jacobson of Los Altos CA (US) for google llc
IPC Code(s): G06Q30/0241
CPC Code(s): G06Q30/0241
Abstract: systems, methods, and computer-readable storage media utilized to determine product response for analysis systems. one method includes receiving a product response for a first product, the product response including interaction data indicating a user interaction with a content item of a second product, wherein the content item is associated with a content provider, and identifying a relatedness graph of a plurality of products. the method further includes aggregating weights of measures of degrees of relatedness in the relatedness graph of a first node of the first product to a second node of the second product, and generating a relatedness index based on normalizing the aggregation of the weights of the measures of degrees. the method further includes, in response to the relatedness index exceeding a threshold, calculating an attribution credit assigned to the product response based on the relatedness index, and providing the attribution credit to the content provider.
20240303692. System And Method For Personalized Banner Placement_simplified_abstract_(google llc)
Inventor(s): Dongeek Shin of San Jose CA (US) for google llc
IPC Code(s): G06Q30/0251, G06F40/106, G06Q30/0241
CPC Code(s): G06Q30/0255
Abstract: the present disclosure provides for determining personalized banner placement in relation to content based on probabilistic spatial user engagement. the probabilistic spatial user engagement can be determined based on user input signals, types of content, or a combination of user input signals and types of content. such determination may be used to identify regions of a page displaying the content where banners may be rendered for maximum user engagement and minimal disruption of the content.
Inventor(s): Daniel Patt of Saratoga CA (US) for google llc, Ibrahim Badr of New York NY (US) for google llc
IPC Code(s): G06Q40/04, G06F16/22
CPC Code(s): G06Q40/04
Abstract: systems and methods for non-fungible token data indexing can include processing blockchain data and/or web page data to identify token data associated with a non-fungible token. the identified token data can then be utilized to generate index data associated with the non-fungible token. the index data can be utilized to generate an index database. the index database can then be utilized for non-fungible token search and/or for generating derivative data associated with the non-fungible tokens. the surfaced non-fungible token search results can be provided in a specific search result panel and/or adjacent to general search results.
20240303734. Deduplication of Non-Fungible Tokens in Search Index_simplified_abstract_(google llc)
Inventor(s): Daniel Patt of Saratoga CA (US) for google llc, Ibrahim Badr of New York NY (US) for google llc
IPC Code(s): G06Q40/04, G06Q30/018
CPC Code(s): G06Q40/04
Abstract: systems and methods for non-fungible token indexing can include obtaining and identifying token data associated with a plurality of non-fungible tokens. in generating an index database, the systems and methods may index a token multiple times and/or may index tokens with same or similar payloads. the systems and methods can identify the duplicate token indexing and can adjust the index database based on the identification of duplicate token index data. the adjustment can affect the determination of which search results to surface in response to a search query.
Inventor(s): Noritsugu KANAZAWA of Campbell CA (US) for google llc, Yael PRITCH KNAAN of Tel Aviv (IL) for google llc
IPC Code(s): G06T5/77, G06T7/194, G06T7/50, G06V10/44
CPC Code(s): G06T5/77
Abstract: a method includes receiving an image from an image capture device, determining a mask for the image, and determining a depth representation including a pixelwise depth estimation for a scene represented by the image. a respective inpainting region in the mask includes pixels that represent two or more features of the scene. the two or more features have different depth estimates in the depth representation, and a respective feature of the two or more features overlaps with the non-inpainting region. the method includes refining the respective inpainting region based on (i) the two or more features having different depth estimates, and (ii) the respective feature of the two or more features overlapping with the non-inpainting region, and inpainting the image in accordance with refining the respective inpainting region such that the portion of the respective feature that overlaps with the non-inpainting region is not inpainted.
Inventor(s): Matthew Alun Brown of Vancouver (CA) for google llc, Ricardo Martin-Brualla of Seattle WA (US) for google llc, Keunhong Park of Seattle WA (US) for google llc, Christopher Derming Xie of London (GB) for google llc
IPC Code(s): G06T7/194, G06T17/00
CPC Code(s): G06T7/194
Abstract: systems and methods for three-dimensional object category modeling can utilize figure-ground neural radiance fields for unsupervised training and inference. for example, the systems and methods can include a foreground model and a background model that can generate an object output based at least in part on one or more learned embeddings. the foreground model and background model may process position data and view direction data in order to output color data and volume density data for a respective position and view direction. moreover, the object category model may be trained to generate an object output, which may include an instance interpolation, a view synthesis, or a segmentation.
20240303876. Augmented Reality Based Geolocalization of Images_simplified_abstract_(google llc)
Inventor(s): Juan David Hincapie Ramos of Palo Alto CA (US) for google llc, Justin Paul Quimby of Oakland CA (US) for google llc, Marek Lech Gorecki of Los Gatos CA (US) for google llc
IPC Code(s): G06T11/00, G06V20/20, G06V20/62, G06V30/10
CPC Code(s): G06T11/00
Abstract: a method for determining a location at which an unobstructed view of a target location is obtained, includes capturing an image of an environment which includes a target location; accessing target location data, wherein the target location data comprises information associated with the environment and the target location; determining, based on the target location data and a spatial relationship between the target location and one or more objects in the image which obstruct a view of the target location, at least one suitable location of a user device from which an unobstructed view of the target location is within a field of view of the user device and satisfies one or more criteria; and providing a guided human-machine interaction process to assist a user associated with the user device in re-locating the user device to the at least one suitable location.
Inventor(s): Yinda Zhang of Daly City CA (US) for google llc, Danhang Tang of West Hollywood CA (US) for google llc, Ruofei Du of San Francisco CA (US) for google llc, Zhang Chen of Beijing (CN) for google llc, Kyle Genova of San Mateo CA (US) for google llc, Sofien Bouaziz of Los Gatos CA (US) for google llc, Thomas Allen Funkhouser of Menlo Park CA (US) for google llc, Sean Ryan Francesco Fanello of San Francisco CA (US) for google llc, Christian Haene of Berkeley CA (US) for google llc
IPC Code(s): G06T15/08, G06T3/40, G06T9/00, G06T19/20
CPC Code(s): G06T15/08
Abstract: a method including generating a first vector based on a first grid and a three-dimensional (3d) position associated with a first implicit representation (ir) of a 3d object, generating at least one second vector based on at least one second grid and an upsampled first grid, decoding the first vector to generate a second ir of the 3d object, decoding the at least one second vector to generate at least one third ir of the 3d object, generating a composite ir of the 3d object based on the second ir of the 3d object and the at least one third ir of the 3d object, and generating a reconstructed volume representing the 3d object based on the composite ir of the 3d object.
20240303918. GENERATING REPRESENTATION OF USER BASED ON DEPTH MAP_simplified_abstract_(google llc)
Inventor(s): Ruofei Du of San Francisco CA (US) for google llc, Xun Qian of Mountain View CA (US) for google llc, Yinda Zhang of Palo Alto CA (US) for google llc, Alex Olwal of Santa Cruz CA (US) for google llc
IPC Code(s): G06T17/00, G06T7/55, G06T7/73
CPC Code(s): G06T17/00
Abstract: a method can include receiving, via a camera, a first video stream of a face of a user; determining a location of the face of the user based on the first video stream and a facial landmark detection model; receiving, via the camera, a second video stream of the face of the user; generating a depth map based on the second video stream, the location of the face of the user, and a depth prediction model; and generating a representation of the user based on the depth map and the second video stream.
20240304173. Systems and Methods for a Text-To-Speech Interface_simplified_abstract_(google llc)
Inventor(s): Benedict Davies of London (GB) for google llc, Guillaume Boniface of London (GB) for google llc, Jack Whyte of London (GB) for google llc, Jakub Adamek of St. Albans, Hertfordshire (GB) for google llc, Simon Tokumine of London (GB) for google llc, Alessio Macri of London (GB) for google llc, Matthias Quasthoff of London (GB) for google llc
IPC Code(s): G10L13/00, G06F3/16, G06F40/30
CPC Code(s): G10L13/00
Abstract: a computing system and related techniques for selecting content to be automatically converted to speech and provided as an audio signal are provided. a text-to-speech request associated with a first document can be received that includes data associated with a playback position of a selector associated with a text-to-speech interface overlaid on the first document. first content associated with the first document can be determined based at least in part on the playback position, the first content including content that is displayed in the user interface at the playback position. the first document can be analyzed to identify one or more structural features associated with the first content. speech data can be generated based on the first content and the one or more structural features.
Inventor(s): Andrew M Rosenberg of Brooklyn NY (US) for google llc, Yacob Yochai Blau of Mountain View CA (US) for google llc, Bhuvana Ramabhadran of Mt. Kisco NY (US) for google llc, Genady Beryozkin of Mountain View CA (US) for google llc, Gary Wang of Mountain View CA (US) for google llc, Zhehuai Chen of Edgewater NJ (US) for google llc, Rohan Agrawal of Mountain View CA (US) for google llc, Parisa Haghani of Mountain View CA (US) for google llc
IPC Code(s): G10L15/06, G10L15/22, G10L15/26
CPC Code(s): G10L15/063
Abstract: a method includes receiving training data including transcribed speech utterances spoken in a general domain, modified speech utterances in a target domain, and unspoken textual utterances corresponding to the transcriptions of the modified speech utterances in the target domain. the modified speech utterances include utterances spoken in the target domain that have been modified to obfuscate one or more classes of sensitive information recited in the utterances. the method also includes generating a corresponding alignment output for each unspoken textual utterance of the received training data using an alignment model. the method also includes training a speech recognition model on the alignment outputs generated for the corresponding to the unspoken textual utterances, the un-transcribed speech utterances, and the transcribed speech utterances to teach the speech recognition model to learn to recognize speech in the target domain and phrases within the one or more classes of sensitive information.
Inventor(s): Guru Prakash Arumugam of Sunnyvale CA (US) for google llc, Shuo-yiin Chang of Sunnyvale CA (US) for google llc, Shaan Jagdeep Patrick Bijwadia of San Francisco CA (US) for google llc, Weiran Wang of San Jose CA (US) for google llc, Quan Wang of Hoboken NJ (US) for google llc, Rohit Prakash Prabhavalkar of Palo Alto CA (US) for google llc, Tara N. Sainath of Jersey City NJ (US) for google llc
IPC Code(s): G10L15/06
CPC Code(s): G10L15/063
Abstract: a method includes receiving a plurality of training samples spanning multiple different domains. each corresponding training sample includes audio data characterizing an utterance paired with a corresponding transcription of the utterance. the method also includes re-labeling each corresponding training sample of the plurality of training samples by annotating the corresponding transcription of the utterance with one or more speaker tags. each speaker tag indicates a respective segment of the transcription for speech that was spoken by a particular type of speaker. the method also includes training a multi-domain speech recognition model on the re-labeled training samples to teach the multi-domain speech recognition model to learn to share parameters for recognizing speech across each of the different multiple different domains.
Inventor(s): Roberto Pieraccini of New York NY (US) for google llc, Wangqing Yuan of Wilmington MA (US) for google llc, Martin Baeuml of Zurich (CH) for google llc
IPC Code(s): G10L15/197, G06F40/35, G10L15/06, G10L15/18, G10L15/22, G10L15/30
CPC Code(s): G10L15/197
Abstract: as part of an ongoing dialog between a user and an automated assistant, processor(s) can receive a natural language (nl) based input from the user during a turn of the ongoing dialog, obtain style signal(s) for the turn, and determine, based on the style signal(s), a nl based response style that is not specified in the nl based input. further, the processor(s) can process, using a large language model (llm), the nl based input and a nl based response style tag for the nl based response style to generate llm output, determine, based on the llm output, a nl based response in the nl based response style, and cause the nl based response to be rendered. in some implementations, a llm behavior controller is utilized to determine the nl based response style, whereas in other implementations, the llm is fine-tuned to determine the nl based response style.
Inventor(s): Ke Hu of Stony Brook NY (US) for google llc, Bo Li of Santa Clara CA (US) for google llc, Tara N. Sainath of Jersey City NJ (US) for google llc, Yu Zhang of Mountain View CA (US) for google llc, Francoise Beaufays of Mountain View CA (US) for google llc
IPC Code(s): G10L15/197, G10L15/02, G10L15/06
CPC Code(s): G10L15/197
Abstract: a method of a multilingual asr model includes receiving a sequence of acoustic frames characterizing an utterance of speech. at a plurality of output steps, the method further includes generating a first higher order feature representation for an acoustic frame by a first encoder that includes a first plurality of multi-head attention layers; generating a second higher order feature representation for a corresponding first higher order feature representation by a second encoder that includes a second plurality of multi-head attention layers; and generating, by a first decoder, a first probability distribution over possible speech recognition hypotheses based on the second higher order feature representation and a sequence of n previous non-blank symbols. a gating layer of each respective moe layer configured to dynamically route an output from a previous multi-head attention layer at each of the plurality of output steps to a respective pair of feed-forward expert networks.
20240304186. AUDIO SIGNAL SYNTHESIS FROM A NETWORK OF DEVICES_simplified_abstract_(google llc)
Inventor(s): Dongeek Shin of San Jose CA (US) for google llc
IPC Code(s): G10L15/20, G10L15/16, G10L15/30
CPC Code(s): G10L15/20
Abstract: merging first and second audio data to generate merged audio data, where the first audio data captures a spoken utterance of a user and is collected by a first computing device within an environment, and the second audio data captures the spoken utterance and is collected by a distinct second computing device that is within the environment. in some implementations, the merging includes merging the first audio data using a first weight value and merging the second audio data using a second weight value. the first and second weight values can be based on predicted signal-to-noise ratios (snrs) for respective of the first audio data and the second audio data, such as a first snr predicted by processing the first audio data using a neural network model and a second snr predicted by processing the second audio data using the neural network model.
Inventor(s): Christopher Hughes of Redwood City CA (US) for google llc, Yiteng Huang of Basking Ridge NJ (US) for google llc, Turaj Zakizadeh Shabestary of San Francisco CA (US) for google llc, Taylor Applebaum of Mountain View CA (US) for google llc
IPC Code(s): G10L15/20, G10L15/02, G10L15/08, G10L15/22, G10L21/0216, G10L21/0232, G10L25/84
CPC Code(s): G10L15/20
Abstract: techniques are described for selectively adapting and/or selectively utilizing a noise reduction technique in detection of one or more features of a stream of audio data frames. for example, various techniques are directed to selectively adapting and/or utilizing a noise reduction technique in detection of an invocation phrase in a stream of audio data frames, detection of voice characteristics in a stream of audio data frames (e.g., for speaker identification), etc. utilization of described techniques can result in more robust and/or more accurate detections of features of a stream of audio data frames in various situations, such as in environments with strong background noise. in various implementations, described techniques are implemented in combination with an automated assistant, and feature(s) detected utilizing techniques described herein are utilized to adapt the functionality of the automated assistant.
Inventor(s): Daniel Sank of Goleta CA (US) for google llc
IPC Code(s): H02J50/12, G06N10/20
CPC Code(s): H02J50/12
Abstract: a quantum computing system includes a qubit, a coupler, and a resonator. the qubit has quantum states associated with discretized frequencies. the coupler has a tunable coupler frequency. when the coupler frequency is tuned to a first frequency value in accordance with a frequency of the qubit, a first energy-transfer operation is enabled that transfers a first quantized amount of energy from the first qubit to the coupler such that the qubit is prepared in a first quantum state. the resonator has a resonant frequency. the resonator is enabled to store input energy that is in accordance with its resonant frequency. when the coupler frequency is tuned to a second frequency value in accordance with its resonant frequency, a second energy-transfer operation is initiated that transfers the first quantized amount of energy from the coupler to the resonator. the resonator may dissipate the energy transferred to it.
Inventor(s): Syed Shakir Iqbal of Bangalore (IN) for google llc
IPC Code(s): H03K19/23, H03K19/003
CPC Code(s): H03K19/23
Abstract: the present disclosure describes various aspects of complementary 2(n)-bit redundancy for single event upset (seu) prevention. in some aspects, an integrated circuit includes a data storage element to store a data value, another data storage element to store a complementary data value, a multi-bit data storage element (e.g., a 2-bit storage element) to store both the data value and the complementary data value, and voting logic that may enable a complementary data storage scheme with inter-circuit redundancy to prevent seu. additionally, the voting logic of the integrated circuit may enable detection and correction of data value errors and/or enable programming of voting logic criteria, which may be implemented dynamically based on a type of seu failures that are detected or corrected.
20240305482. Extracting Data from a Blockchain_simplified_abstract_(google llc)
Inventor(s): Daniel Patt of Saratoga CA (US) for google llc, Ibrahim Badr of New York NY (US) for google llc
IPC Code(s): H04L9/00, G06Q20/36
CPC Code(s): H04L9/50
Abstract: systems and methods for extracting data from blockchain transactions can include obtaining blockchain data, processing the blockchain data to determine token data, segmenting the token data from the blockchain data, and storing the segmented token data. the systems and methods can be utilized to extract descriptive data (e.g., non-fungible token titles, non-fungible token descriptions, and/or non-fungible token labels), content data (e.g., a preview of a digital resource associated with the non-fungible token), and/or transaction data (e.g., data descriptive of the transaction history of the non-fungible token). the extracted data can be indexed and can then be provided in a search results page based on a search query.
20240305534. Scalable Mixed-Effect Modeling and Control_simplified_abstract_(google llc)
Inventor(s): Ali Nasiri Amini of Redwood City CA (US) for google llc, Zheng Zhao of San Jose CA (US) for google llc, Di-Fa Chang of Cupertino CA (US) for google llc
IPC Code(s): H04L41/14
CPC Code(s): H04L41/145
Abstract: in an example aspect, the present disclosure provides for an example method including obtaining session data descriptive of one or more user sessions in the networked environment; initializing a mixed effects model configured to describe a first effect and a second effect on a distribution of the session data; optimizing a weighted objective over a plurality of subsets of the session data, the weighted objective comprising a weighting parameter configured to adjust, respectively for the plurality of subsets of the session data, a contribution of the second effect with respect to the first effect; and updating the mixed effects model based on the optimized weighted objective.
20240305558. Virtual Channel Balancing In Ring-Based Topologies_simplified_abstract_(google llc)
Inventor(s): Brian Patrick Towles of Chapel Hill NC (US) for google llc, Hojat Parta of Los Angeles CA (US) for google llc
IPC Code(s): H04L45/00, H04L49/102
CPC Code(s): H04L45/20
Abstract: 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.
20240305584. Spectrum-Aware Cross-Layer Optimization_simplified_abstract_(google llc)
Inventor(s): Rodolfo Enrique Alvizu Gomez of San Jose CA (US) for google llc, Anurag Sharma of Cupertino CA (US) for google llc, Christina Vlachou of San Francisco CA (US) for google llc, Rene Marcel Schmogrow of Santa Clara CA (US) for google llc
IPC Code(s): H04L47/80, H04B10/079, H04L69/321
CPC Code(s): H04L47/805
Abstract: allocating network resources to one or more signals that are to be conveyed over the network by calculating a transport capacity for a sublink of the network based on a spectral efficiency of at least one subpath included in the sublink, and allocating the sublink to at least one signal based on the calculated transport capacity.
Inventor(s): Cheng Chen of Milpitas CA (US) for google llc, Jingning Han of Santa Clara CA (US) for google llc, Hui Su of Sunnyvale CA (US) for google llc, Yaowu Xu of Saratoga CA (US) for google llc
IPC Code(s): H04N19/44, H04N19/14, H04N19/176, H04N19/186
CPC Code(s): H04N19/44
Abstract: syntax elements are written to a bitstream to designate bit depth precision for palette mode coding of video blocks. during encoding, a bit depth to use for palette mode coding a current block may be based on an input video signal including the current block or based on some change in bit depth precision. a prediction residual for the current block is encoded to a bitstream along with syntax elements indicative of the bit depth used for the palette mode coding of the current block. in particular, the syntax elements include a first element indicating the palette mode coding bit depth used and a second element indicating whether to apply a bit offset to the palette mode coding bit depth. during decoding, values of the syntax elements are read from the bitstream and used to determine a bit depth for palette mode coding the encoded block.
Inventor(s): Kurt Wilms of Mountain View CA (US) for google llc, Anish Kattukaran of Mountain View CA (US) for google llc, Lingxian Ding of Mountain View CA (US) for google llc, Amit Ghorawat of Mountain View CA (US) for google llc
IPC Code(s): H04N21/478, H04N21/41, H04N21/433, H04N21/81
CPC Code(s): H04N21/478
Abstract: techniques for initiating download of content are provided, including receiving, by one or more processors of the mobile computing device, an indication of a selection, made by a user of the mobile computing device, associated with third-party content provided by a proximate media player device; identifying, by the one or more processors of the mobile computing device, an indication of downloadable content associated with the third-party content displayed by the media player device; and downloading, by the one or more processors of the mobile computing device, in response to receiving the indication that the user selected the icon and without further input from the user, the downloadable content to a memory of the mobile computing device.
20240305963. ROUTING QUERIES BASED ON CARRIER PHRASE REGISTRATION_simplified_abstract_(google llc)
Inventor(s): Michael J. Lebeau of New York NY (US) for google llc, John Nicholas Jitkoff of Palo Alto CA (US) for google llc, William J. Byrne of Davis CA (US) for google llc
IPC Code(s): H04W4/50, G10L15/08, G10L15/18, G10L15/22, G10L15/26, H04L67/02, H04L67/53, H04M1/27, H04W4/60
CPC Code(s): H04W4/50
Abstract: in general, the subject matter described in this specification can be embodied in methods, systems, and program products for receiving a voice query at a mobile computing device and generating data that represents content of the voice query. the data is provided to a server system. a textual query that has been determined by a speech recognizer at the server system to be a textual form of at least part of the data is received at the mobile computing device. the textual query is determined to include a carrier phrase of one or more words that is reserved by a first third-party application program installed on the computing device. the first third-party application is selected, from a group of one or more third-party applications, to receive all or a part of the textual query. all or a part of the textual query is provided to the selected first application program.
Inventor(s): Chih-Hsiang Wu of Taoyuan City (TW) for google llc
IPC Code(s): H04W36/00, H04W36/36
CPC Code(s): H04W36/0072
Abstract: a radio access network (ran) for configuring a user equipment (ue) generates (i) a conditional configuration, and (ii) a condition to be satisfied before the ue applies the conditional configuration (), receives, from a core network (cn), an interface message indicating to configure the ue (), determines that the interface message affects the conditional configuration (), generates a message related to the conditional configuration in view of the received interface message (), and transmits the message to the ue ().
20240306248. MANAGING AN EARLY DATA COMMUNICATION CONFIGURATION_simplified_abstract_(google llc)
Inventor(s): Chih-Hsiang Wu of Taoyuan City (TW) for google llc
IPC Code(s): H04W76/30, H04W76/27, H04W88/08
CPC Code(s): H04W76/30
Abstract: a central unit (cu) of a distributed base station, the distributed base station including the cu and a distributed unit (du), can implement a method for managing early data communication with a user equipment (ue). the method may include: determining () whether the du supports early data communication with a ue; determining () whether to include a configuration for performing early data communication in a message to the ue based at least in part on whether the du supports early data communication; and transmitting () the message to the ue.
- Google LLC
- G06F1/16
- H01Q1/22
- CPC G06F1/1683
- Google llc
- G06F3/04817
- G01C21/36
- G06F3/048
- G06F3/0482
- G06F16/29
- G06F16/951
- G06F16/9535
- G06F16/9537
- G06F16/9538
- G06F16/954
- G09B29/10
- H04M1/02
- H04M1/724
- H04M1/72457
- CPC G06F3/04817
- G06F9/30
- G06F9/38
- CPC G06F9/30149
- G06F16/2457
- G06F16/22
- CPC G06F16/24578
- G06F16/438
- G06F3/16
- G06F16/432
- G06F16/532
- CPC G06F16/438
- G06F17/16
- G06F5/01
- G06F15/80
- G06N3/04
- G06N3/08
- CPC G06F17/16
- G06F40/169
- G06F3/0483
- G06F3/04842
- G06F3/0485
- G06F16/958
- CPC G06F40/169
- G06N3/084
- CPC G06N3/04
- H04B7/026
- CPC G06N3/08
- G06N3/094
- G06N10/60
- CPC G06N3/094
- G06Q30/0241
- CPC G06Q30/0241
- G06Q30/0251
- G06F40/106
- CPC G06Q30/0255
- G06Q40/04
- CPC G06Q40/04
- G06Q30/018
- G06T5/77
- G06T7/194
- G06T7/50
- G06V10/44
- CPC G06T5/77
- G06T17/00
- CPC G06T7/194
- G06T11/00
- G06V20/20
- G06V20/62
- G06V30/10
- CPC G06T11/00
- G06T15/08
- G06T3/40
- G06T9/00
- G06T19/20
- CPC G06T15/08
- G06T7/55
- G06T7/73
- CPC G06T17/00
- G10L13/00
- G06F40/30
- CPC G10L13/00
- G10L15/06
- G10L15/22
- G10L15/26
- CPC G10L15/063
- G10L15/197
- G06F40/35
- G10L15/18
- G10L15/30
- CPC G10L15/197
- G10L15/02
- G10L15/20
- G10L15/16
- CPC G10L15/20
- G10L15/08
- G10L21/0216
- G10L21/0232
- G10L25/84
- H02J50/12
- G06N10/20
- CPC H02J50/12
- H03K19/23
- H03K19/003
- CPC H03K19/23
- H04L9/00
- G06Q20/36
- CPC H04L9/50
- H04L41/14
- CPC H04L41/145
- H04L45/00
- H04L49/102
- CPC H04L45/20
- H04L47/80
- H04B10/079
- H04L69/321
- CPC H04L47/805
- H04N19/44
- H04N19/14
- H04N19/176
- H04N19/186
- CPC H04N19/44
- H04N21/478
- H04N21/41
- H04N21/433
- H04N21/81
- CPC H04N21/478
- H04W4/50
- H04L67/02
- H04L67/53
- H04M1/27
- H04W4/60
- CPC H04W4/50
- H04W36/00
- H04W36/36
- CPC H04W36/0072
- H04W76/30
- H04W76/27
- H04W88/08
- CPC H04W76/30
