Correcting Different Types of Errors in Texts

This paper proposes an unsupervised approach that automatically detects and corrects a text containing multiple errors of both syntactic and semantic nature. The number of errors that can be corrected is equal to the number of correct words in the text. Error types include, but are not limited to: spelling errors, real-word spelling errors, typographical errors, unwanted words, missing words, prepositional errors, punctuation errors, and many of the grammatical errors (e.g., errors in agreement and verb formation).