Automatic Correction of Human Translations

1 code implementation • NAACL 2022 • Jessy Lin, Geza Kovacs, Aditya Shastry, Joern Wuebker, John DeNero

We show that human errors in TEC exhibit a more diverse range of errors and far fewer translation fluency errors than the MT errors in automatic post-editing datasets, suggesting the need for dedicated TEC models that are specialized to correct human errors.

Automatic Post-Editing Translation