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Context-Aware Switching of Input Systems

IP.com Disclosure Number: IPCOM000252361D
Publication Date: 2018-Jan-05

Publishing Venue

The IP.com Prior Art Database

Abstract

Generally, the present disclosure is directed to switching between one or more input systems based on a context of a user. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict one or more input systems to provide to a user based on context data relating to a context in which the one or more input systems are used.

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Context-Aware Switching of Input Systems

Overview

Generally, the present disclosure is directed to switching between one or more input

systems based on a context of a user. In particular, in some implementations, the systems and

methods of the present disclosure can include or otherwise leverage one or more machine-

learned models to predict one or more input systems to provide to a user based on context data

relating to a context in which the one or more input systems are used.

Example Figures

Introduction

Many users configure a computing system such as a mobile phone, tablet, etc. to receive

input from one or more input systems. For example, a computing system may have a keyboard

(e.g. a physical and/or touch screen keyboard), microphone, input correcting system, handwriting

recognition system, etc. Additionally or alternatively, the input systems may be configured for

one or more languages. For example, a user may communicate in one language for family, close

friends, etc. and may communicate in another language for social media, workers, colleagues,

etc. Unfortunately, many computing systems may only receive input from a small plurality of the

one or more input systems. For example, due to limited space on a touch screen, it may not be

possible to provide more than one language of keyboard at a time. While it is typically possible

for the user to manually switch between the one or more input systems, this process can be

cumbersome if the user has configured a sizable plurality of input systems and/or if the user

requires frequent switching. Thus, what is needed is a method to predict which of one or more

input systems to provide to the user to best suit the user’s context at a time.

Summary

Generally, the present disclosure is directed to switching between one or more input

systems based on a context of a user. In particular, in some implementations, the systems and

methods of the present disclosure can include or otherwise leverage one or more machine-

learned models to predict one or more input systems to provide to a user based on context data

relating to a context in which the one or more input systems are used.

A computing system can predict one or more input systems to provide to a user based on

a context of a user. The computing system can be, for example, a device, mobile phone, tablet,

laptop computer, desktop computer, application-specific computer, personal digital assistant,

server, application, or other suitable computing system. The one or more input systems can

include, for example, a physical keyboard, touch-screen or “soft” keyboard, a keyboard

configured for a language, country, alphabet, user, etc., an input correcting system (e.g. text input

correcting system), an input correcting system configured for a language, country, dialect, user,

etc., a voice input system, handwriting recognition system, translation system, or other suitable

input system, or combination thereof. The one or more input systems may be pre-configu...