Auto-Transcription for Citizen Science

We propose to implement a system for automatic transcription of tables from handwritten or typed document images. In phase I we developed an end-to-end system design and showed the feasibility of our approach with a working prototype to take document images as inputs and extract a digital, tabular output. In phase II we will fully implement the end to-end system. Our work will focus on three tasks. The first is the implementation of the front-end user interface, which will allow users to create “templates” for transcription jobs, provide guidance, and correct the output. The second task focuses on implementing the back end, which employs highly accurate models that can incorporate user knowledge about the tables to be transcribed. Finally, in addition to the implementation work, we will evaluate the system’s ultimate accuracy, deploy the system, conduct user testing, and refine the implementation in response to feedback. This man-machine combination of user input, and models capable of using the input, will allow transcription to be efficiently and accurately accomplished, even in cases where the system does not initially produce a perfect result. Our system will empower citizen scientists to accomplish transcription tasks quickly, intuitively, and easily.