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Abstract

Described is a unified digital ink recognizer that recognizes various different types of digital ink data, such as handwritten character data and custom data, e.g., sketched shapes, handwritten gestures, and/or drawn pictures, without further participation by a user such as recognition mode selection or parameter input. For a custom item, the output may be a Unicode value from a private use area of Unicode. Building the unified digital ink recognizer may include defining the data set to be recognized, extracting features of training samples corresponding to the dataset items to build a recognizer model, evaluating the recognizer model using testing data, and modifying the recognizer model using tuning data. The extracted features may be processed into feature data for a multi-dimensional nearest neighbor recognizer approach; the extracted features for the samples of each class is calculated and combined into the feature set for this class in the resulting recognizer model.

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