Text Induced Spelling Correction

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Abstract

    We present TISC, a language-independent and context-sensitive spelling checking and correction system designed to facilitate the automatic removal of non-word spelling errors in large corpora. Its lexicon is derived from a very large corpus of raw text, without supervision, and contains word unigrams and word bigrams. It is stored in a novel representation based on a purpose-built hashing function, which provides a fast and computationally tractable way of checking whether a particular word form likely constitutes a spelling error and of retrieving correction candidates. The system employs input context and lexicon evidence to automatically propose a limited number of ranked correction candidates when insufficient information for an unambiguous decision on a single correction is available. We describe the implemented prototype and evaluate it on English and Dutch text, containing real-world errors in more or less limited contexts. The results are compared with those of the isolated word spelling checking programs Ispell and the Microsoft Proofing Tools MPT.
    Original languageEnglish
    Title of host publicationProceedings of the 20th International Conference on Computational Linguistics (COLING 2004)
    Place of PublicationGeneva
    PublisherUnknown Publisher
    Pages834-840
    Number of pages7
    ISBN (Print)1932432485
    Publication statusPublished - 2004

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