Abstract: An electronic ink object is preprocessed for improving handwriting recognition results. An electronic ink object, possibly having multiple lines of non-horizontal ink, is preprocessed by segmenting or separating the electronic ink object into one or more lines, computing a writing angle of each line, and rotating each line so that it is horizontal.

Abstract: A technique for reducing a prototype database for use with handwriting recognizers. The prototype database is divided into multiple spaces and the effect on the error rate for removing each prototype is identified. All prototypes that contribute to the error rate are removed. If further prototype database reduction is desired, the technique identifies and removes one or more prototypes that have the least adverse effect on the error rate across all spaces. The technique continues removing prototypes in this manner until a desired prototype database size has been achieved.

Abstract: Ink strokes of cursive writing are segmented to make the cursive writing more like print writing, particularly with respect to the number of strokes of a character. A stroke-segmentation module first finds the local extrema points on a stroke of input ink. Then the local extrema points are stepped through, two (or three) at a time. The stroke-segmentation module may compare the three (or four) ink segments that are adjacent to the two (or three) local extrema points to a set of predefined stroke-segmentation patterns to find a closest matching pattern. Strokes are then segmented based on a stroke-segmentation rule that corresponds to the closest matching pattern. Additional stroke segmentation may be performed based on the change of curvature of the segmented ink strokes. Then, a character-recognition module performs character recognition processing by comparing the segmented ink strokes to prototype samples at least some of which have been similarly segmented.

Abstract: Input handwritten characters are classified as print or cursive based upon numerical feature values calculated from the shape of an input character. The feature values are applied to inputs of an artificial neural network which outputs a probability of the input character being print or cursive. If a character is classified as print, it is analyzed by a print character recognizer. If a character is classified as cursive, it is analyzed using a cursive character recognizer. The cursive character recognizer compares the input character to multiple prototype characters using a Dynamic Time Warping (DTW) algorithm.

Abstract: The present invention comprises an interactive learning apparatus employing a closed educational loop that encompasses obtaining written and spoken responses characteristic to the user. The user's characteristic response is recognized via handwriting and speech recognition techniques and educational feedback is communicated to the user. The invention also comprises means for allowing an observer or instructor to monitor or influence the interactivity between the disclosed learning apparatus and the user in retrospect or directly via employing memory means and various networking schemes.

Abstract: A technique for reducing a prototype database for use with handwriting recognizers. The prototype database is divided into multiple spaces and the effect on the error rate for removing each prototype is identified. All prototypes that contribute to the error rate are removed. If further prototype database reduction is desired, the technique identifies and removes one or more prototypes that have the least adverse effect on the error rate across all spaces. The technique continues removing prototypes in this manner until a desired prototype database size has been achieved.

Abstract: An electronic ink object is preprocessed for improving handwriting recognition results. An electronic ink object, possibly having multiple lines of non-horizontal ink, is preprocessed by segmenting or separating the electronic ink object into one or more lines, computing a writing angle of each line, and rotating each line so that it is horizontal.

Abstract: A system and method for organizing and prioritizing recognized text. More particularly, a method and system for categorizing recognized text according to confidence levels in the correctness of the recognized text. The system and method may categorize recognized text into two or more different confidence levels. A user interface can display recognized text based upon the confidence level assigned to that text, thereby drawing a user's attention to that text for which the recognition process has a low confidence in its correctness estimate. The user interface may also allow a user to correct erroneously recognized text with different techniques, according to the level of confidence that the recognition process has in the correctness of the text.

Abstract: The present invention comprises an interactive learning apparatus employing a closed educational loop that encompasses obtaining written and spoken responses characteristic to the user. The user's characteristic response is recognized via handwriting and speech recognition techniques and educational feedback is communicated to the user. The invention also comprises means for allowing an observer or instructor to monitor or influence the interactivity between the disclosed learning apparatus and the user in retrospect or directly via employing memory means and various networking schemes.