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We introduce a new approach to spellchecking for languages with extreme phonetic irregularities. The spelling for such languages can be significantly improved if knowledge about pronunciation and sound becomes the central part of the spelling algorithm. However, given a weak phoneme-grapheme-correspondence the standard spelling algorithms, which are rule-based or edit-distance-based, are severely limited in their phonetic capabilities.
A production approach to spelling can overcome the limitations—but suffers from its search space size. We describe in this paper the main building blocks to tackle this problem with heuristic search. Our ideas have been operationalized in the SMARTSPELL algorithm, with impressive results related to spelling correction and runtime.
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