ExpressMatch: A System for Creating Ground-Truthed Datasets of Online Mathematical Expressions

In recognition domains, publicly available ground-truthed datasets are essential to perform effective performance evaluation and comparison of existing methods and systems. However, in the field of online handwritten mathematical expression recognition, datasets are quite scarce and their creation is one of the current challenging issues. In this paper, we present Express Match, a system designed to help creation and management of online mathematical expression datasets with ground-truth data. In this system, handwritten model expressions can be input and manually annotated with ground-truth data, transcriptions of these expressions can be automatically annotated by matching them to the respective models. Additional metadata can also be attached to each sample expression. To test the system, a dataset consisting of 56 model expressions and 910 sample expressions with a total of 20,010 symbols, written by 25 different writers, has been created. This dataset, as well as Express Match, will be made publicly available.