Error repair in human handwriting: an intelligent user interface for automatic online handwriting recognition

Since both users and recognition algorithms make mistakes, it is desirable for the user interface of a handwriting recognition system to have mechanisms recovering from errors. We address the problem of error repair in online handwriting recognition. First, we perform a user study on error occurrences and corresponding repair patterns in human handwriting. Based on a data analysis, we have identified typical types of errors and repair patterns. We then propose methods to deal with error repair in an online handwriting system. We have developed a prototype system to demonstrate and evaluate the proposed error handling mechanisms. The system extends NPen⁺⁺, an online handwriting recognition system developed in our lab, by providing error repair abilities to users in addition to its high recognition rate. The experimental results indicate that the error handling mechanisms can significantly improve the system performance in case of the data containing error repair