Findings of the WMT 2022 Shared Task on Automatic Post-Editing

27599

Authors

nan

Abstract

AbstractWe present the results from the 8th round of the WMT shared task on MT Automatic PostEditing, which consists in automatically correcting the output of a “black-box” machine translation system by learning from human corrections. This year, the task focused on a new language pair (English→Marathi) and on data coming from multiple domains (healthcare, tourism, and general/news). Although according to several indicators this round was of medium-high difficulty compared to the past,the best submission from the three participating teams managed to significantly improve (with an error reduction of 3.49 TER points) the original translations produced by a generic neural MT system.

Keywords

nan

Full Content

nan

Labeled Text

AbstractWe present the results from the 8th round of the WMT shared task on MT Automatic PostEditing, which consists in automatically correcting the output of a “black-box” machine translation system by learning from human corrections. This year, the task focused on a new language pair (English→Marathi) and on data coming from multiple domains (healthcare, tourism, and general/news). Although according to several indicators this round was of medium-high difficulty compared to the past,the best submission from the three participating teams managed to significantly improve (with an error reduction of 3.49 TER points) the original translations produced by a generic neural MT system.

Publication Details

Paper ID:
27599
Year:
2022
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan