This project focuses specifically on using a probabilistic language model combined with techniques like the n-gram model and edit distance, particularly for the English language. The bigram language model and Damerau-Levenshtein distance algorithm are employed to develop a spelling checker. This system uses edit distance and word probabilities from a medical and Covid-19 related corpus. A user-friendly Graphical User Interface (GUI) is created with Tkinter. While the system shows promising results, it has limitations such as handling contextual ambiguity, homophones, and plural words. It is also limited to the English language and does not address misspellings in other languages.
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A probabilistic language model combined with techniques like the n-gram model and edit distance, particularly for the English language.
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yanshenp/nlp-spell-checker
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A probabilistic language model combined with techniques like the n-gram model and edit distance, particularly for the English language.
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