Systematically Adapting Machine Translation for Grammatical Error Correction
TL
TL;DR
This work adapts machine translation to grammatical error correction, identifying how components of the statistical MT pipeline can be modified for this task and analyzing how each modification impacts system performance.
Abstract
n this work we adapt machine translation (MT) to grammatical error correction, identifying how components of the statistical MT pipeline can be modified for this task and analyzing how each modification impacts system performance. We evaluate the contribution of each of these components with standard evaluation metrics and automatically characterize the morphological and lexical transformations made in system output. Our model rivals the current state of the art using a fraction of the training data.
References36 items
1
Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction
2
JFLEG: A Fluency Corpus and Benchmark for Grammatical Error Correction
3
Adapting Grammatical Error Correction Based on the Native Language of Writers with Neural Network Joint Models
4
Optimizing Statistical Machine Translation for Text Simplification
5