Microsoft Technology Licensing, LLC

Drew Elliot Linerud

Eric Norman Badger

Timothy S Paek

Asela J Gunawardana

Dmytro Rudchenko

Itai Almog

Takanobu Murayama

Parthasarathy Sundararajan

Kenichi Morimoto

Kenneth R Walters

Chongming Ho

An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

User-centric soft keyboard predictive technologies

A local or remote server is configured to receive requests for text and other suggestions from a plurality of client applications. The local or remote server can format requests for delivery to one or more suggestion sources along with client contexts that specify client delivery, format, or other requests associated with the suggestion request. The local or remote server selects suggestion sources based on the client requests and the client contexts, and can combine suggestions returned from multiple sources as directed by client contexts. Requests associated with different clients can be directed to different suggestion sources, and user or client accepted suggestion histories can be stored for use in providing suggestions.

Text suggestion framework with client and server model

Growing community of inventors

Duvall, WA, United States of America

Drew Elliot Linerud