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In this paper we propose a new method for correcting garbled words based on Levenshtein distance and weighted Levenshtein distance. We can correct not only substitution errors, but also insertion errors and deletion errors by this method. According to the results of simulation on nearly 1000 high occurrence English words, higher error correcting rates can be achieved by this method than any other method tried to date. Hardware realization of the method is possible, though it is rather complicated.
Okuda et al. (Sun,) studied this question.