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​Spell​ ​checker that​ ​handles​ ​both​ ​non-word​ ​and​ ​real-word errors​ given in a ​context

Python 79.33% Jupyter Notebook 20.67%
natural-language-processing nlp machine-learning-algorithms

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Probabilistic-Spell-Checker-The-Noisy-Channel

Spell checker that handles both non-word and real-word errors given in a context

The purpose of this assignment is to build probabilistic language models by implementing the full algorithmic pipeline.

Specifics:

  • Use the noisy channel model to correct the errors:
    • A correction of a misspelled word depends on both the most probable correction on the error type-character level and the word prior
    • A correction of a word in a sentence depends on the error type-character level and on the language model -- the correction should maximize the likelihood of getting the full corrected sentence.
  • Use the language model when correcting words in a context.

References:

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