Spelling Correction using Noisy Channel Models
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Updated
Mar 20, 2018 - Python
Spelling Correction using Noisy Channel Models
A simple python simulator to compare efficiency of different kinds of hamming coding in noisy channels
Implementation of unigram/bigram language models, noisy channel and pointwise mutual information for natural language processing.
The project uses the symmetric delete spelling correction algorithm, noisy channel model and python's natural language toolkit to develop a spell-checking application.
This is a project that uses Information Retrieval concepts to develop a Search-as-a-Service Platform
Python program that generates the best suggestion for a given misspelled word using the Noisy Channel Model.
A web based application for Bengali spelling correction using Noisy Channel method
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