Microsoft Technology Licensing, LLC

Keri Talbot

Christopher D Edwards

Jason F Morrill

Igor B Peev

Elizabeth Ann Holz

Renee Yang

Christopher Doan

L Tucker Hatfield

Kathleen R Thompson

Tyler Robert Adams

March Rogers

Gary Caldwell

Karen Xiaoxu Cheng

Sarah Faulkner

Nathan James Fish

Sam Franklin Williams, Iii

Nathaniel Eric Breskin Auer

Amanda A Alvarado

C Joe Coplen

David Landis

Erez Kikin Gil

Clinton Dee Covington

Chad B Rothschiller

Hiroshi Tsukahara

Christopher Michael Maloney

Daniel Yancy Parish

Jonathan D Esterly

Ajitesh Kishore

Krista Bendig

Melissa Susan Kerr

Amnon Itamar Govrin

Alexander A Babanov

Jimmy Y Sun

Tracy ThuyDuyen Tran

Dmitri Viktorovich Kotchetov

Marian Kimberley Chua

James Patrick Spotanski

Robert Earl Stout

Kiruthika Selvamani

Megan Moriko Langley

Aleta Bashaw

Harley Adams

Joe C Coplen

In a device including a processor and a memory, the memory includes executable instructions that cause the processor to control the device to perform functions of receiving a user input to initiate a conversation session for generating an outline for a writing; generating a voice output asking a question regarding the writing; receiving a voice input from the user responding to the voice output; identifying, based on the received voice input, content of the voice input responding to the voice output; repeating, until a predetermined condition is met, the steps of generating the voice output, receiving the voice input, and identifying the content of the voice input, wherein the question asked via each voice output is generated in response to the content of the voice input responding to the preceding voice output; and generating, based on the content of the voice inputs, the outline for the writing.

Freeform conversation writing assistant

Real-time interactions made by a client on a whiteboard are shown on remote client(s) currently viewing the whiteboard. The real-time interactions that are shown on the remote clients can include a variety of different interactions. For example, the location(s) of where a remote client is touching the whiteboard or interacting with the whiteboard using a stylus may be viewed. A current inking stroke of a remote user may also be viewed as it is occurring. Interactions on the whiteboard may be shown differently depending on the remote user performing the interaction. The whiteboard may also show a location on the whiteboard where each of the remote users are currently viewing. A user may also track the actions of another user. When a change is committed to the whiteboard, the remote clients update the display to reflect the committed state.

Showing interactions as they occur on a whiteboard

Disclosed are methods, systems, and machine readable mediums which provide for an automatic image scaling that may be utilized in a variety of contexts, including for scaling images inserted into documents. The image may be scaled based upon one or more scaling features that may be utilized alone or in combination. Scaling features may be described by scaling feature categories, although as will be appreciated, the scaling features may be placed in one or more categories. Example feature categories may include image characteristics; image content; content of the document and context of the image within the document; past user behavior and preferences; and the like.

Automated image scale adjustment based upon document and image context

Non-limiting examples herein relate to generation and presentation of data analytics that provide managers of digital content with audience and content insights in real-time. A representation of data analytics is generated and automatically surfaced for a user through a user interface of an application/service. One set of examples of the present disclosure relates to processing by one or more computing devices for a service that manages client data of the application/service. The service that manages the client data may interface with an exemplary service such as a digital presentation service to obtain the client data, aggregate the client data, analyze the client data and generate exemplary read ratio data analytics, among other executed processing operations. Further sets of examples relate to processing that occurs by a specific front-end application/service that may be configured to automatically surface a representation of the read ratio data analytics for one or more user accounts.

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Seattle, WA, United States of America

Keri Talbot