Applying Machine Translation Methods in the Problem of Automatic Text Correction
Wojciech Jarmosz
DOI: http://dx.doi.org/10.15439/2021F142
Citation: Position and Communication Papers of the 16th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 26, pages 227–228 (2021)
Abstract. This document describes the problem of automatic text corrections. The author presents a classification of errors, a process of correcting texts and a proof of concept as a containerized version of machine translation system - MSuedin
References
- D. Naber, A rule-based style and grammar checker, GRIN Verlag 2003.
- K. Kukich, Techniques for automatically correcting words in text, ACM Computing Surveys 1992
- https://marian-nmt.github.io
- https://github.com/grammatical/pretraining-bea2019
- R. Grundkiewicz, M. Junczys-Dowmunt, K. Heafield, Neural Grammatical Error Correction Systems with Unsupervised Pre-training on Synthetic Data, BEA 2019