Amazon Technologies, Inc.

Richard Christopher Green

Jonathan Alan Leblang

Collin Charles Davis

Milo Oostergo

Aakarsh Nair

Kevin Crews

Yu-Hsiang Cheng

Gary Zhong

Justin Jon Derby

Faizal S Kassamali

Andrew Kenneth Milton

Massimo Ramella-Pezza

Adib Roumani

Cassity Barrows Queen

Systems and methods are disclosed related to determining and providing contextual information associated with a meeting based in part by parsing text from a meeting invitation or calendar entry. A voice-capturing device may receive audio data before or during a meeting that includes an invocation phrase used to invoke a voice-based functionality. A response may be generated by the voice-capturing device or an associated service provider system based on the contextual information determined from the parsed meeting invitation and/or related sources.

Contextual parsing of meeting information

Techniques for selecting a meeting to join in response to a voice command from a user are described herein. A user may utter a voice command to 'join my meeting' and, in response, the techniques may access a calendar associated with the user to identify the call-in information used to join the meeting. If the calendar indicates that the user is listed as an invitee for multiple meetings at the current time, then the techniques may analyze an array of criteria to determine which meeting the user most likely would like to join.

Selecting meetings based on input requests

Systems and methods are disclosed related to determining device settings for a meeting based in part by parsing text from a meeting invitation or calendar entry, and controlling one or more remotely controllable devices during the meeting according to the determined settings. Based on contextual information determined from a parsed meeting invitation and/or related sources, controllable devices such as remote-controllable window shades, lighting equipment, camera equipment, display screens and/or other in-room equipment may be automatically assigned to determined settings before or during an in-person meeting, conference call or videoconference.

Device control based on parsed meeting information

Systems and methods are provided for increasing the overall network performance experienced by a group of devices by forming a dynamic and collaborative cluster of computing devices. In particular, the computing devices within the cluster collectively may identify and leverage the current capabilities of each of the individual members of the cluster to respond efficiently to network resource requests from computing devices inside or outside the cluster. As such, various embodiments provide for a dynamic cluster of computing devices that tailor the responsibilities of the members of the cluster to the current capabilities, capacities, and state of these computing devices. In particular, devices in the cluster may participate dynamically in the cluster to ensure that a device in the cluster that is currently most suited to performing a task is the device selected to perform that task.

Cache based on dynamic device clustering

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Bothell, WA, United States of America

Richard Christopher Green