Stochastic error-correcting parsing for OCR post-processing

In this paper, stochastic error-correcting parsing is proposed as a powerful and flexible method to post-process the results of an optical character recognizer (OCR). Deterministic and nondeterministic approaches are possible under the proposed setting. The basic units of the model can be words or complete sentences, and the lexicons or the language databases can be simple enumerations or may convey probabilistic information from the application domain.