公开(公告)号：US12114134B1

公开(公告)日：2024-10-08

申请号：US17955355

申请日：2022-09-28

Applicant: Amazon Technologies, Inc.

Inventor： Shobha Devi Kuruba Buchannagari ,  Ludger Solbach ,  Madhuri Saraf ,  Andrew Jackson Stockton, X

IPC: H04R25/00

CPC classification number: H04R25/505

Abstract: An enhancement equalizer (EEQ) can be configured to compensate for hearing loss. An app or application can assist a user with measuring hearing loss at various frequencies (e.g., threshold sensitivity versus normal hearing). Using these measurements, the system may compute a set of filters for an EEQ that can boost different frequencies by different amounts corresponding to the user's sensitivity to that frequency. The measurement and resulting EEQ may be earphone specific (e.g., both the measurement and the filter computation may depend on the particular type/model of earphone used). In some implementations, the system may allow the user to select correction strength that controls an amount of correction applied (e.g., 25%, 50%, or 75% of full correction). In some implementations, the system may adjust the EEQ and/or correction strength according to the volume of playback (e.g., by applying less correction at higher playback volumes to avoid triggering earphone limiters).

公开(公告)号：US12113962B1

公开(公告)日：2024-10-08

申请号：US17886111

申请日：2022-08-11

Applicant: Amazon Technologies, Inc.

Inventor： Byeongdoo Choi ,  Christopher Andrew Segall ,  Kiran Mukesh Misra

IPC: H04N19/105 ,  H04N19/159 ,  H04N19/172 ,  H04N19/577

CPC classification number: H04N19/105 ,  H04N19/172 ,  H04N19/577 ,  H04N19/159

Abstract: Techniques for an efficient inter-prediction structure and signaling for low-delay streaming of live video are described. According to some examples, a computer-implemented method includes receiving a live video at a content delivery service, determining a subset of candidate reference frames from a plurality of frames received of the live video, generating an identification code, for the subset of candidate reference frames, having a multiple-bit format that includes a first bit value to indicate a corresponding candidate reference frame is a reference frame for an input frame from the live video and a second bit value to indicate the corresponding candidate reference frame is not the reference frame for the input frame from the live video, and, when a bit of the identification code for a first candidate reference frame is set to the first bit value to indicate the first candidate reference frame is one of a forward reference frame and a backward reference frame for the input frame from the live video, an immediately following bit of the identification code being set to the first bit value indicates the first candidate reference frame is also another of the one of the forward reference frame and the backward reference frame for the input frame from the live video, performing a real time encode of the input frame of the live video based at least in part on the identification code to generate an encoded frame by the content delivery service, and transmitting the encoded frame from the content delivery service to a viewer device.

公开(公告)号：US12112752B1

公开(公告)日：2024-10-08

申请号：US17688279

申请日：2022-03-07

Applicant: Amazon Technologies, Inc.

Inventor： Rahul Gupta ,  Jwala Dhamala ,  Apurv Verma ,  Qingwen Ye ,  Mayur Himmatbhai Dabhi ,  Srinivasan Rengarajan Veeravanallur ,  Spyridon Matsoukas ,  Melanie C B Gens ,  Seyed Omid Razavi ,  Avni Khatri ,  Premkumar Natarajan

IPC: G10L15/22 ,  G10L15/01 ,  G10L15/06 ,  G10L15/08

CPC classification number: G10L15/22 ,  G10L15/01 ,  G10L15/063 ,  G10L15/08 ,  G10L2015/0631 ,  G10L2015/223

Abstract: Devices and techniques are generally described for cohort determination in natural language processing. In various examples, a first natural language input to a natural language processing system may be determined. The first natural language input may be associated with a first account identifier. A first machine learning model may determine first data representing one or more words of the first natural language input. A second machine learning model may determine second data representing one or more acoustic characteristics of the first natural language input. Third data may be determined, the third data including a predicted performance for processing the first natural language input by the natural language processing system. The third data may be determined based on the first data representation and the second data representation.

公开(公告)号：US12111889B1

公开(公告)日：2024-10-08

申请号：US17350402

申请日：2021-06-17

Applicant: Amazon Technologies, Inc.

Inventor： Dilip Kumar ,  Jon Robert Ducrou ,  Joseph Xavier ,  Ramanathan Palaniappan ,  Michel Leonard Goldstein ,  Michael Lee Brundage

IPC: G06F18/24 ,  G06V10/75

CPC classification number: G06F18/24 ,  G06V10/751

Abstract: This disclosure describes a system for automatically updating item image information stored in an item images data store and used for processing captured images to identify items represented in those images. In one implementation, once an identity of an item has been verified, captured images of that item are associated with the item and stored in the item images data store. As a result, the item images data store is updated each time an image of the item is captured and the identity of the item is verified.

公开(公告)号：US12111739B1

公开(公告)日：2024-10-08

申请号：US17937361

申请日：2022-09-30

Applicant: Amazon Technologies, Inc.

Inventor： Ravi Mantrala ,  Peng Wu ,  Danny Wei ,  Shailesh Bhagwat ,  Sandeep Kumar

IPC: G06F11/20 ,  G06F9/50 ,  G06F11/07

CPC classification number: G06F11/2025 ,  G06F9/5044 ,  G06F9/5077 ,  G06F11/0772

Abstract: Systems and methods are described for use of reserved storage capacity at a cloud provider network extension, sometimes referred to as a provider substrate extension (“PSE”) or “outpost”, as a data cache, thereby improving performance of the PSE. The reserved storage capacity may be reserved for a primary purpose, such as data replication in the event of failure of an in-use portion of the PSE's storage capacity. During non-failover operation, the reserved storage capacity may be otherwise unused. Embodiments of the present disclosure enable the reserved storage capacity, when not used for its primary purpose, to be used as a data cache to store information potentially used at the PSE.

公开(公告)号：US20240331211A1

公开(公告)日：2024-10-03

申请号：US18194441

申请日：2023-03-31

Applicant: Amazon Technologies, Inc.

Inventor： Larry Davis ,  Nicolas Heron ,  Amit Kumar Agrawal ,  Nina Mitra Khosrowsalafi ,  Osama Makansi ,  Oleksandr Vorobiov

IPC: G06T11/00 ,  G06T7/12 ,  G06T7/70 ,  G06V10/764

CPC classification number: G06T11/00 ,  G06T7/12 ,  G06T7/70 ,  G06V10/764 ,  G06T2207/20081 ,  G06T2207/30196

Abstract: Systems and methods are described for generating images of synthesized bodies wearing a garment. For instance, a source image of a human or mannequin wearing a garment may be submitted to a synthesized human generation system. In response to receiving the source image, the synthesized human generation system may use a classifier to classify the image as depicting one or more body types or orientations. The synthesized human generation system may also apply segmentation to the source image to segment the garment pixels. The synthesized human generation system may then select one or more body generation machine learning models based on the classification of the source image. The synthesized human generation system may utilize the selected machine learning models to generate one or more output images of synthesized bodies that appear to be wearing the garment, using the segmented garment as input.

公开(公告)号：US20240331004A1

公开(公告)日：2024-10-03

申请号：US18128353

申请日：2023-03-30

Applicant: Amazon Technologies, Inc.

Inventor： Eilon Shitrit ,  Soomin Lee ,  Avihai Mejer

IPC: G06Q30/0601

CPC classification number: G06Q30/0631 ,  G06Q30/0625

Abstract: An automatic technique is disclosed to enrich presented answers by highlighting relevant shopping recommendations. The shopping recommendations can either be highlighted within the answer itself, or as an auxiliary list of suggestions. A model is described for selecting phrases from the answer text (sequences of consecutive terms called noun phrases) that refer to potential products that likely represent relevant shopping recommendation in context of the question-answer pair. The noun phrases are then ranked in order of importance. The top-ranked noun phrases are used to search products to be displayed in association with the noun phrases. Clicking or tapping on a highlighted noun phrase launches a shopping-related flow, such as presenting a widget with product recommendations or running a search in a search engine.

公开(公告)号：US20240330709A1

公开(公告)日：2024-10-03

申请号：US18193546

申请日：2023-03-30

Applicant: Amazon Technologies, Inc.

Inventor： Alexandre DAVID ,  Jeremiah M. DUNHAM ,  Amit GOEL ,  Dejan JOVANOVIC ,  Rami Gokhan KICI

IPC: G06N5/01 ,  G06N5/045

CPC classification number: G06N5/013 ,  G06N5/045

Abstract: Techniques are described for executing satisfiability modulo theories (SMT) solvers in a “shadow” system configuration where input queries are provided to a primary SMT solver system and additionally to one or more secondary SMT solver systems. SMT solver systems can be used by cloud providers and in other computing environments to analyze the implications of configured user account policies defining permissions with respect to users' computing resources and associated actions within a computing environment, to help ensure the security of computing resources and user data, etc. The results generated by a primary SMT solver system can be provided to one or more secondary SMT solver systems, where each of the secondary SMT systems can comprise different system components or different versions of system components, to assess the correctness of the primary SMT solver system, to compare performance metrics, among other possible types of analyses.

公开(公告)号：US20240330270A1

公开(公告)日：2024-10-03

申请号：US18740434

申请日：2024-06-11

Applicant: Amazon Technologies, Inc.

Inventor： Anurag Windlass Gupta ,  Neal Fachan ,  Samuel James McKelvie ,  Laurion Darrell Burchall ,  Christopher Richard Newcombe ,  Pradeep Jnana Madhavarapu ,  Benjamin Tobler ,  James McClellan Corey

IPC: G06F16/23 ,  G06F11/14 ,  G06F11/20

CPC classification number: G06F16/2365 ,  G06F11/1451 ,  G06F11/1471 ,  G06F16/23 ,  G06F11/2094 ,  G06F2201/80

Abstract: A database system may include a database service and a separate distributed storage service. The database service (or a database engine head node thereof) may be responsible for query parsing, optimization, and execution, transactionality, and consistency, while the storage service may be responsible for generating data pages from redo log records and for durability of those data pages. For example, in response to a write request directed to a particular data page, the database engine head node may generate a redo log record and send it, but not the data page, to a storage service node. The storage service node may store the redo log record and return a write acknowledgement to the database service prior to applying the redo log record. The server node may apply the redo log record and other redo log records to a previously stored version of the data page to create a current version.

公开(公告)号：US20240329964A1

公开(公告)日：2024-10-03

申请号：US18194370

申请日：2023-03-31

Applicant: Amazon Technologies, Inc.

Inventor： Roland Mesde ,  Alex Bessonov ,  Brian Ewanchuk ,  George Sherif Kamal Hanna ,  Paolo Gruenberg Hilario

IPC: G06F8/65

CPC classification number: G06F8/65

Abstract: Systems and methods of determining and providing optimized deployment plans for deploying software to vehicles are disclosed. In some embodiments, a vehicle software deployment system evaluates one or more cost functions to determine relative costs of different deployment configuration options for deploying software to a vehicle, such as resource costs (e.g., bandwidth, compute, memory, etc.), isolation costs (e.g., limited access to input information, limited connectivity to other ECUs, etc.), performance costs, etc. Based on the evaluation of the one or more cost functions, the vehicle software deployment system determines an optimized deployment plan. Also, the vehicle software deployment system receives telemetry data from the vehicle and automatically determines updated optimized deployment plans in response to changes in configuration of the vehicle indicated in the telemetry data.