Amazon Technologies, Inc.

Brett E Lounsbury

Scott Southwood

Christo Frank Devaraj

Lakshya Bhagat

Katelyn Doran

Neil Christopher Fritz

Daniel Bruce Lloyd

Samuel A Minter

Nick Ciubotariu

Stephen Brent Ivie

Jeffrey B Slosberg

Tri M Cao

Joseph Steven Mate

Vishal M Shanbhag

Chih-Jen Huang

Michal Maciej Bryc

Canku Alp Calargun

Shadie Hijazi

Prajwal Yadapadithaya

Michal M Brye

Fnu Arun Kumar Agarwal

Ankit Garg

Stacie Lauren Buckingham

Vivek Chaganti

Audio data, corresponding to an utterance spoken by a person within a detection range of a voice communications device, can include an audio message portion. The audio data can be captured and analyzed to determine the intent to send a message. Based at least in part upon that intent, a remaining portion of the audio data can be analyzed to determine the intended message target or recipient, as well as the portion corresponding to the actual message payload. Once determined, the audio file can be trimmed to the message payload, and the message payload of the audio data can be delivered as an audio message to the target recipient.

Audio message extraction

Various embodiments provide processes for identification of embedded unauthorized data within document data. Such processes may include evaluating document data properties for indications of closing headers, comparing document data sizes against reference sizes, and comparing document data sizes against other document data sizes. Certain embodiments evaluating image data may evaluate image properties, such as histograms or gradient images, to determine random or otherwise unauthorized data. Upon detection of unauthorized data, the document data may be flagged for later processing, such as removal from a storage server.

System and method for evaluating data files

Described herein are systems and techniques for an event handling system capable of distinguishing between application or user-specific events and system-wide events. The described system may be further capable of suppressing event notifications associated with application or user specific events and escalating system-wide events. In some embodiments, the system may identify an origination source for a number of event trigger. The system may determine whether a number of trigger events associated with any particular origination source are over a threshold number of trigger events. Upon determining that the event is an application or user specific event, then the system may suppress a potential escalation of the event.

Event handling system with escalation suppression

Systems and methods are provided for selecting components to include in portions of a displayable file. Selecting the components may include determining an order of the components for each portion of the displayable file. The components' order for a given portion may be based on a score for each component, where a component's score is based on an estimated value and standard error associated with the component. The component to include in each portion of the displayable file may be selected based at least in part on the determined component order for each portion and a predetermined priority of each portion.

Systems and methods for selecting components for inclusion in portions of a displayable file

Systems are provided for the streamlining authentication of encrypted data. In streaming authentication, the authentication and decryption of a data file is performed in a streaming manner. The data file can be stored as a collection of discrete encrypted portions. When the data file is to be accessed, it can be authenticated in a streaming manner, as discrete portions of the large file are loaded from storage or transmitted to other systems.

Streaming authenticated encryption

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Edmonds, WA, United States of America

Brett E Lounsbury