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Unformatted text preview: Evaluation of Techniques for Visualizing Mathematical Expression Recognition Results Joseph J. LaViola Jr. * University of Central Florida School of EECS Orlando, FL 32816 USA Anamary Leal † University of Central Florida School of EECS Orlando, FL 32816 USA Timothy S. Miller ‡ Brown University Dept. of Computer Science Providence, RI 02912 USA Robert C. Zeleznik § Brown University Dept. of Computer Science Providence, RI 02912 USA ABSTRACT We present an experimental study that evaluates four different tech- niques for visualizing the machine interpretation of handwritten mathematics. Typeset in Place puts a printed form of the recog- nized expression in the same location as the handwritten mathe- matics. Adjusted Ink replaces what was written with scaled-to-fit, cleaned up handwritten characters using an ink font. The Large Offset technique scales a recognized printed form to be just as wide as the handwritten input, and places it below the handwritten math- ematical expression. The Small Offset technique is similar to Large Offset but the printed form is set to be a fixed size which is gener- ally small compared to the written expression. Our experiment explores how effective each technique is with assisting users in identifying and correcting recognition mistakes with different types and quantities of mathematical expressions. Our evaluation is based on task completion time and a comprehen- sive post-questionnaire used to solicit reactions on each technique. The results of our study indicate that, although each technique has advantages and disadvantages depending on the complexity of the handwritten mathematics, subjects took significantly longer to com- plete the recognition task with Typeset in Place and generally pre- ferred Adjusted Ink or Small Offset. Keywords: pen-based user interfaces, mathematical expression recognition results, usability evaluation, typeset, adjusted ink Index Terms: H.5.2 [Information Interfaces and Presentation]: User Interfaces—Interaction Styles, Evaluation/Methodology; 1 INTRODUCTION Computer recognition of handwritten mathematics is an old  and important  field, and many advances have been made in the decades of research on it. However, we posit that, since some handwritten math is ambiguous even to another human, even the best achievable recognition techniques will at times misinterpret the writer’s intent. Thus, identifying and correcting recognition errors can be viewed as a fundamental problem. Nonetheless, compared to the core algorithmic problem of recognizing handwritten math- ematics, very little attention has focused on UI techniques which allow users to cope with recognition errors. In particular, we have identified two UI tasks which merit investigation: visualization techniques for depicting the machine interpretation of handwritten mathematics and thus identifying recognition errors, and interaction techniques for correcting the machine interpretation....
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This note was uploaded on 06/12/2011 for the course CAP 6105 taught by Professor Lavoila during the Spring '09 term at University of Central Florida.
- Spring '09