Touchtype Limited

Microsoft Technology Licensing, LLC

Jonathan Paul Reynolds

Benjamin William Medlock

The present invention provides a system comprising a user interface configured to receive text input by a user, a text prediction engine comprising a plurality of language models and configured to receive the input text from the user interface and to generate concurrently text predictions using the plurality of language models, and wherein the text prediction engine is further configured to provide text predictions to the user interface for display and user selection. An analogous method and an interface for use with the system and method are also provided.

System and method for inputting text into electronic devices

An embodiment is directed to an interface for a small screen device, such as a watch, that enables a user to enter text on the small screen device by touching in the vicinity of characters, rather than aiming for a particular button or the exact location of a character. Embodiments further enable the design of interfaces without the use of buttons for controlling the entry of text on the small screen device.

System and method for inputting text into small screen devices

The present invention relates generally to a system and method for the reordering of text predictions. More particularly, the system and method reorders the text predictions based on modified probability values, wherein the probability values are modified according to the likelihood that a given text prediction will occur in the text inputted by a user.

The present invention relates generally to a system and method for text prediction and, in particular, a system and method for the adaptive weighting of text predictions. The present invention provides a modular language model-based text prediction system for the adaptive weighting of text prediction components and a method for doing so. The system uses category predictions, generated by a timed aggregated perceptron classifier, to weight, using a weighting module, text predictions generated by a text prediction engine comprising at least one predictor.

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London, United Kingdom

Jonathan Paul Reynolds