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The paper describes two different methods for using context to correct garbled English text. The first makes use of a dictionary of English words containing their probability of occurrence. The second uses letter digram frequencies to roughly approximate English word probabilities. Probabilities of various letter substitutions are obtained from a confusion matrix of the simulated character recognizer whose operation produced the garbling. This information is combined using a maximum likelihood scheme to obtain word recognition or, if only digram information is available, the recognition of word approximations.
Vossler et al. (Wed,) studied this question.