Abstract: Context-based word prediction is provided. A software application utilizes words contained in an application document to provide context-based word prediction in the same or a related document. The software application creates an application defined data source and populates the data source with words occurring in a document. When the same or a related document is being edited via an input method, for example, typing, speech recognition, electronic handwriting, etc., a prediction engine presents candidate words from the application defined data source that match current text input, and the user may choose from the presented candidate words for automatic population into the document being edited. Information from the application defined data source may be transferred between computing devices, for example, between a mobile computing device and a desktop (non-mobile) computing device.

Abstract: Embodiments are provided to predict and suggest one or more candidates. Words, acronyms, compound words, phrases, and other textual and symbolic representations can be predicted and suggested to a user as part of an input process or other user operation. In an embodiment, a number of textual candidates can be predicted based in part on user input and data stored in a store component. The number of predicted textual candidates can be suggested to a user as a number of suggested textual candidates. Embodiments enable a user to select an appropriate textual candidate from the number of suggested textual candidates, while reducing a number of associated user operations.

Abstract: Embodiments are provided to predict and suggest one or more candidates. Words, acronyms, compound words, phrases, and other textual and symbolic representations can be predicted and suggested to a user as part of an input process or other user operation. In an embodiment, a number of textual candidates can be predicted based in part on user input and data stored in a store component. The number of predicted textual candidates can be suggested to a user as a number of suggested textual candidates. Embodiments enable a user to select an appropriate textual candidate from the number of suggested textual candidates, while reducing a number of associated user operations.

Abstract: Context-based word prediction is provided. A software application utilizes words contained in an application document to provide context-based word prediction in the same or a related document. The software application creates an application defined data source and populates the data source with words occurring in a document. When the same or a related document is being edited via an input method, for example, typing, speech recognition, electronic handwriting, etc., a prediction engine presents candidate words from the application defined data source that match current text input, and the user may choose from the presented candidate words for automatic population into the document being edited. Information from the application defined data source may be transferred between computing devices, for example, between a mobile computing device and a desktop (non-mobile) computing device.

Abstract: A software multi-tap input method requires only two taps to input most characters. This is especially beneficial for languages where existing multi-tap methods require on average more than two strokes per character, and where handwriting recognition is currently an unacceptable alternative. The described system employs a touch-screen input that contains a selection of displayed “buttons” substantially fewer in number than the number of potential characters in the language of interest. An input area contains an array of symbols, each symbol being associated with a group of candidate characters. A candidate area contains an array of characters associated with a most recently selected group symbol in the input area. To select a particular character, a user pushes a group symbol in the input area and then selects the desired character in the candidate area.

Abstract: A software multi-tap input method requires only two taps to input most characters. This is especially beneficial for languages where existing multi-tap methods require on average more than two strokes per character, and where handwriting recognition is currently an unacceptable alternative. The described system employs a touch-screen input that contains a selection of displayed “buttons” substantially fewer in number than the number of potential characters in the language of interest. An input area contains an array of symbols, each symbol being associated with a group of candidate characters. A candidate area contains an array of characters associated with a most recently selected group symbol in the input area. To select a particular character, a user pushes a group symbol in the input area and then selects the desired character in the candidate area.