Microsoft Technology Licensing, LLC

Gregg Robert Wygonik

Christian Klein

Raymond Quan

Sophors Khut

Jan-Kristian Markiewicz

Matthew Hartman

Sergio Paolantonio

Aaron Burns

Christian Michael Sadak

Kenneth Liam Kiemele

Jeffrey Sipko

John Benjamin Hesketh

Michael Robert Thomas

Matt Peltier

Roger Sebastian Sylvan

Charlene Mary Jeune

Ken M Sadahiro

Ricardo A Espinoza Reyes

Ricardo Arturo Espinoza Reyes

Andrew David Wilson

Ryen William White

Robert Disano

Gabriel Takacs

Jeroen Vanturennout

David Maxwell Gedye

Eric Sanderson

Gavin Dean Lazarow

Nirupama Chandrasekaran

Tushar Cyril Bhatnagar

Michael D McCormack

Zach Johnson

Jonathan David Hildebrandt

Alain Philippe Maillot

Matt Pinski

Jason Randall Wadsworth

Roy Henry Berger, Jr

Evan Lincoln Tice

Robert David Steen

Michael David Mccormack

Roy H Berger

Matthew Fleming

Hayden William McAfee

Rob Disano

Sam Webber

Sean Edward Andrist

Erik Manfred Schulz

Richard Renchi Ma

Systems and methods related to engaging with a virtual assistant via ancillary input are provided. Ancillary input may refer to non-verbal, non-tactile input based on eye-gaze data and/or eye-gaze attributes, including but not limited to, facial recognition data, motion or gesture detection, eye-contact data, head-pose or head-position data, and the like. Thus, to initiate and/or maintain interaction with a virtual assistant, a user need not articulate an attention word or words. Rather the user may initiate and/or maintain interaction with a virtual assistant more naturally and may even include the virtual assistant in a human conversation with multiple speakers. The virtual assistant engagement system may utilize at least one machine-learning algorithm to more accurately determine whether a user desires to engage with and/or maintain interaction with a virtual assistant. Various hardware configurations associated with a virtual assistant device may allow for both near-field and/or far-field engagement.

Non-verbal engagement of a virtual assistant

In a multi-user, collaborative environment, an operating system state change can occur by passing a stylus pen from one user to another. Upon detecting a change of the active user, a state machine transition can result in a change in a user experience. In one example, a change in the user experience includes a change in user interface (UI) functionality. Some examples include changing color of the digital ink being displayed, changing a handwriting pattern, and automatically switching a view displayed on the user interface. The switched view can be switching from a single-user model to a multi-user model. In another example, a state machine transition can result in establishing connections between devices (e.g., phones or laptops) associated with the users that used the pen.

Change of active user of a stylus pen with a multi user-interactive display

In one example, a method for detecting input can include detecting a capacitive pattern from a physical object and detecting that the physical object is a passive physical object. The method can also include determining a plurality of characteristics corresponding to the passive physical object based on the capacitive pattern, wherein the plurality of characteristics comprise a type of the physical object and a capability of the physical object. Additionally, the method can include modifying an application manager to detect input from the passive physical object based on the plurality of characteristics and modifying a user interface setting detected from the capacitive pattern.

Detecting input based on a capacitive pattern

A digital inking device can automatically adapt its interaction modality to provide contextually relevant status information and contextually relevant user interface control elements based on a user's activity. An interaction model of a digital inking device can automatically adapt the display of particular control user interface control elements and particular status indicators based on one or more factors. For example, a digital inking device can select an interaction model from a number of interaction models based on a way a digital inking device is held by a user, a fingerprint of a user, an angle and/or distance of a digital inking device with respect to a paired computer, a particular grip a user has on a digital inking device, an amount of pressure that is used to hold a digital inking device, a contact pressure between a digital inking device and a paired computer, and/or one more gestures performed by a user.

Dynamic interaction adaptation of a digital inking device

A gesture language for a device with multiple touch surfaces is described. Generally, a series of new touch input models is described that includes touch input interactions on two disjoint touch-sensitive surfaces. For example, a mobile device can include a primary display on a 'front' side of the device, and a secondary display or touch-sensitive surface on the 'back' side of the device, such as a surface that is opposite the primary display. Accordingly, the gesture language can include a series of &#x201c;back touch&#x201d; interactions with the touch-sensitive surface on the backside of the device. Example interactions include direct and indirect touch input on the back side, as well as simultaneous touch input on both sides of the device.

Gesture language for a device with multiple touch surfaces

Techniques for navigational aid for a hinged device via semantic abstraction are described. Generally, the techniques described herein improve a user experience when the user is navigating through content, such as user-generated content in an electronic document. For example, the techniques described herein semantically abstract authored content in an electronic document to provide abstracted content. In implementations, abstracted content includes abstracted pages that each represent a different section of the authored content. When a user scans through an electronic document, rather than scanning page by page, techniques described herein instead navigate through displays of the abstracted pages. In addition, a hinge between different displays can be used as an input mechanism to control a speed of navigating through the abstracted pages to allow a user to more easily locate specific sections of the authored content.

Navigational aid for a hinged device via semantic abstraction

Techniques are described herein that are capable of making a state-based determination of information to be displayed on a screen region of a hinge that is coupled to other screen regions. For instance, a state of a hinge that is coupled between a first screen region and a second screen region may be determined. Information that is to be displayed on a third screen region that is provided on the hinge may be determine based at least in part on the state of the hinge.

Device having a screen region on a hinge coupled between other screen regions

A computing device and method are provided for accelerating the coarse relocalization process of the computing device by generating a current fingerprint using signal data detected by sensors, statistically analyzing the current fingerprint for proximity to candidate fingerprints in fingerprint data to generate a ranked list, and subsequently retrieving map data corresponding to the closest matching fingerprints in the ranked list. The computing device may comprise a processor, a memory operatively coupled to the processor, and a fingerprint program stored in the memory and executed by the processor.

Coarse relocalization using signal fingerprints

A system for detecting input described herein can include a processor to augment a user interface to display a magnified input panel proximate a keyboard. The processor can also load a plurality of gesture functions associated with the magnified input panel and detect an input character corresponding to a source text field based on at least one keyboard selection from the keyboard. Additionally, the processor can display the input character in the magnified input panel and the source text field and generate a modified input character to be displayed in the magnified input panel and the source text field based on the input character and at least one gesture corresponding to the plurality of gesture functions.

Magnified input panels

Techniques for input based on interactions with a physical hinge are described. Generally, a new class of interactions involves user manipulation of a physical hinge in order to provide input to a computing device. These hinge-based interactions provide input to a computing system that can be leveraged to initiate one or more system-level commands or operations, initiate transitions between discrete views of content, interact with content displayed via one or more display devices, and so on. In an example, a sequence of two or more consecutive hinge angle changes is recognized as a hinge gesture to perform a particular operation, such as a transition between a single-tasking state and a multitasking state.

Input based on interactions with a physical hinge

A contextual state of a graphical user interface presented via a display of the computing system is identified. A voice command is selected from a set of voice commands based on the contextual state of the graphical user interface. A context-specific voice-command suggestion corresponding to the selected voice command is identified. A graphical user interface including the context-specific voice-command suggestion is presented via a display.

Voice-command suggestions based on computer context

A computing system is configured to listen to user speech and translate the user speech into voice commands that control operation of the computing system. The identity of a user interacting with the computing system is determined, and a voice command is selected from a set of voice commands based on the user identity. A voice-command suggestion corresponding to the voice command is selected and presented via a display. If the user speaks the voice-command suggestion, the computing system executes the voice command corresponding to the voice-command suggestion.

Voice-command suggestions based on user identity

Display screen with animated graphical user interface

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Duvall, WA, United States of America

Gregg Robert Wygonik