Microsoft Technology Licensing, LLC

Drew Elliott Linerud

Eric Norman Badger

Timothy S Paek

Itai Almog

Parthasarathy Sundararajan

Shawna Julie Davis

Tirthankar Sengupta

Kenneth R Walters

Andrew Douglas Peterson

Asela J Gunawardana

Dmytro Rudchenko

Hugh A Teegan

Daryn Elliot Robbins

Jason Michael Bower

Jason Anthony Grieves

Xin Gong

Daniel Chang

Sameer Garde

Hector Barbera

Apparatus and methods are disclosed for providing feedback and guidance to touch screen device users to improve the text entry user experience and performance. According to one embodiment, a method comprises receiving a text entry, receiving input on a touch screen in the form of a first single touch input located over a word of previously entered text, and presenting the user with one or more suggestion candidates indicated possible replacement words related to the selected word. The user can then select one of the suggestion candidates using a second single touch input to replace the selected word with a word associated with the selected suggestion candidate.

Typing assistance for editing

Quick tasks for on-screen keyboards are described in which an on-screen keyboard supports a plurality of quick tasks configured to edit selected text in defined ways. Quick task functions may be assigned to keys of the on-screen keyboard in addition to the default actions or 'normal' character entry functions of the keys. During text input, the keys operate normally to perform a function related to character entry, such as to cause input of corresponding text character. When text is selected or in other designated interaction scenarios, operation of a key associated with a quick task may automatically trigger the quick task to modify selected text in a corresponding way. Thus, the same key of an on-screen keyboard may be employed to initiate a function related to character entry or apply of a quick task to text depending upon the interaction scenario.

Quick tasks for on-screen keyboards

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 facility for processing textual input generated with a user input device described. In one example facility, the facility stores the textual input in a first data structure contained in the address space of a first process. The facility synchronizes contents of the first data structure to a second data structure contained in the address space of a second process distinct from the first process, an application executing in the second process being configured to consume textual input synchronized to the second data structure.

Externalized execution of input method editor

A personality-based theme may be provided. A prompt and an input indicating a personality may be received. Next, a voice font corresponding to the personality may be determined. The voice font may then be applied to the received prompt by augmenting the voice font applied prompt with recorded phrases of the personality.

Personality-based device

A personality-based theme may be provided to a device. An application program may query a personality resource file for a prompt corresponding to a personality. Then the prompt may be received at a text to speech synthesis engine. Next, the speech synthesis engine may query a personality voice font and recorded phrases database for a voice font corresponding to the personality and may alter the prompt text to conform with the grammatical style of the personality. Then the speech synthesis engine may apply the voice font to the prompt, which is then produced at an output device.

Embodiments are configured to provide one or more candidates based in part on an input identifier associated with an input interface. In an embodiment, a system includes an input method editor (IME) that can be configured to provide one or more candidates based in part on a prediction model and one or more input scope values associated with an input interface. The IME can also operate to store an entered string including one or more associated input scope values to a storage component. The stored information can be used when suggesting candidates.

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Duvall, WA, United States of America

Drew Elliott Linerud