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Part of a semester project this grammarchecker uses a n-gram language model to detect grammatical errors and a bert model is used to generate suggestions.

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al-becker/StatisticalGrammarChecker

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statistical_grammar_checker

This small project is part of a semester project. The goal is to build a statistical grammarchecker. The error detection was done using ngram counts from the google ngram corpus. As a proof of concept of the statistical model german was added as a second language. For a little bit more detailed explanation of the implemented concepts see "NLP - GrammarChecker.pdf".

To start it run the docker-compose.yml or if you want to install all the necessary python modules install them according to requirements.txt and run the app.py file.

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Part of a semester project this grammarchecker uses a n-gram language model to detect grammatical errors and a bert model is used to generate suggestions.

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