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

We present Hover Widgets, a new technique for increasing the capabilities of pen-based interfaces. Hover Widgets are implemented by using the pen movements above the display surface, in the tracking state. Short gestures while hovering, followed by a pen down, access the Hover Widgets, which can be used to activate localized interface widgets. By using the tracking state movements, Hover Widgets create a new command layer which is clearly distinct from the input layer of a pen interface. In a formal experiment Hover Widgets were found to be faster than a more traditional command activation technique, and also reduced errors due to divided attention.

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Hover widgets: using the tracking state to extend the capabilities of pen-operated devices

Example embodiments provide for (i) suggesting proper gesture sequences based on a user's initial gesture input; and/or (ii) providing visual or other gesture example(s), which may alternatively be compared with the user's mimic thereof For example, a user may input a gesture into a touch/display surface. Based on the user's movement, recognized or proper application gesture commands are suggested. In other embodiments, a tutorial session may be presented to the user for teaching or educating the user on numerous types of gestures. As such, a visual representation of a gesture example may be presented to the user, and feedback provided based on the user's mimicking thereof

Gesture recognition interactive feedback

A user interface that accepts input data through both speech and the use of a pen or stylus. With the interface, a user can employ voice recognition to enter a large volume of data, and subsequently employ a stylus input to modify the input data. A user can also employ stylus input, such as data from a handwriting or character recognition operation, to control how subsequently spoken words are recognized by a voice recognition operation. Further, a user may input data using a stylus, and then modify the input data using a voice recognition operation. A user may also employ a voice recognition operation to control how handwriting or character data input through a stylus is recognized by a handwriting recognition operation or a character recognition operation. In addition to a user interface, a technique is disclosed for inputting data into a computer where information is shared between a speech input operation and a handwriting input operation.

Integration of speech and stylus input to provide an efficient natural input experience

In accordance with one aspect of the present invention, disclosed is an image analysis and conversion method and system, where digital ink images are converted to structured object representations of the digital ink images, capable of being edited by a structured text/graphics editor.

Method and apparatus to convert bitmapped images for use in a structured text/graphics editor

The present invention concerns a graphical handwriting user interface for a handheld device. As each handwritten word is entered (142) at a handwriting input area, the handwritten entry is checked for completeness (144) by selecting a designated key or by gesturing a writing instrument. When the handwritten entry is complete, a handwriting recognition engine matches (146) the handwritten input against words in a system dictionary as supplemented by a user dictionary. A confidence score is then attached (148) to the top scoring word. If the confidence level is high enough (154), then it is inserted in the input buffers as primary word choice for that handwritten word and the user may decide (156) whether the primary word is correct. If the confidence level is not high enough, then the user is prompted (158) with an indication that the recognition result is less reliable.

Giovanni Seni

Papers

Handwriting user interface for personal digital assistants and the like