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Published in:
2011 | OriginalPaper | Chapter
5. Active Interaction and Learning in Handwritten Text Transcription
Authors : Dr. Alejandro Héctor Toselli, Dr. Enrique Vidal, Prof. Francisco Casacuberta
Published in: Multimodal Interactive Pattern Recognition and Applications
Publisher: Springer London
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Abstract
Computer-assisted systems are being increasingly used in a variety of real-world tasks, though their application to handwritten text transcription in old manuscripts remains largely unexplored. The basic idea explored in this chapter is to follow a sequential, line-by-line transcription of the whole manuscript in which a continuously retrained system interacts with the user to efficiently transcribe each new line. User interaction is expensive in terms of time and cost. Our top priority is to take advantage of these interactions, while trying to reduce them as most as possible.
To this end, we study three different frameworks: (a) improve a recognition system from newly recognized transcriptions via adaptation techniques, using semi-supervised learning techniques; (b) study how to best adapt from limited user supervisions, which is related to active learning; and (c) develop a simple error estimate, which is used to let the user adjust the error in a computer-assisted transcription task. In addition, we test these approaches in the sequential transcription of two old text documents.