Abstract: A system comprising: one or more processors; and program instructions for providing a user interface. Execution of the program instructions by the one or more processors causes the one or more processors to display a user interface comprising: an entry mechanism for entering an input comprising at least one character, symbol, numeral or punctuation mark; a typing pane configured to display the input entered via the entry mechanism; wherein, in response to selection of a prediction based on the input entered via the entry mechanism, the typing pane is configured to replace the input entered via the entry mechanism by the prediction; and an undo button, wherein in response to user selection of the undo button, the typing pane is configured to replace the selected prediction by the input entered via the entry mechanism.

Abstract: 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.

Abstract: A system for inputting text into an electronic device. The system comprises a candidate generator (2) configured to generate one or more candidates from an input sequence (20). The input sequence (20) comprises a contiguous sequence of characters. Each candidate comprises two or more terms separated by one or more term boundaries. The candidate generator (2) is configured to assign a first probability estimate to each candidate by: searching for one or more terms of that candidate in a context language model, wherein the context language model comprises sequences of terms, each sequence of terms having a corresponding probability of occurring; and assigning the probability corresponding to the one or more terms of that candidate from the context language model to the candidate. The candidate generator (2) is configured to discard one or more candidates on the basis of the corresponding first probability estimates. There is provided a corresponding method of inferring term boundaries in a user input sequence.

Abstract: 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.

Abstract: Systems comprising a user interface configured to receive text input by a user and a text prediction engine configured to receive the input text and generate text predictions. The text prediction engine may comprise a general language model and a context-specific language model. The text prediction engine is configured to generate text predictions from the general language model and the context-specific language model and combine the text predictions. The text prediction engine may comprise first and second language models and a first context-specific weighting factor associated with the first language model.

Abstract: 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.

Abstract: 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.

Abstract: 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.