@inproceedings{ding-etal-2021-jhu,
title = "The {JHU}-{M}icrosoft Submission for {WMT}21 Quality Estimation Shared Task",
author = "Ding, Shuoyang and
Junczys-Dowmunt, Marcin and
Post, Matt and
Federmann, Christian and
Koehn, Philipp",
booktitle = "Proceedings of the Sixth Conference on Machine Translation",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wmt-1.94",
pages = "904--910",
abstract = "This paper presents the JHU-Microsoft joint submission for WMT 2021 quality estimation shared task. We only participate in Task 2 (post-editing effort estimation) of the shared task, focusing on the target-side word-level quality estimation. The techniques we experimented with include Levenshtein Transformer training and data augmentation with a combination of forward, backward, round-trip translation, and pseudo post-editing of the MT output. We demonstrate the competitiveness of our system compared to the widely adopted OpenKiwi-XLM baseline. Our system is also the top-ranking system on the MT MCC metric for the English-German language pair.",
}
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%0 Conference Proceedings
%T The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task
%A Ding, Shuoyang
%A Junczys-Dowmunt, Marcin
%A Post, Matt
%A Federmann, Christian
%A Koehn, Philipp
%S Proceedings of the Sixth Conference on Machine Translation
%D 2021
%8 nov
%I Association for Computational Linguistics
%C Online
%F ding-etal-2021-jhu
%X This paper presents the JHU-Microsoft joint submission for WMT 2021 quality estimation shared task. We only participate in Task 2 (post-editing effort estimation) of the shared task, focusing on the target-side word-level quality estimation. The techniques we experimented with include Levenshtein Transformer training and data augmentation with a combination of forward, backward, round-trip translation, and pseudo post-editing of the MT output. We demonstrate the competitiveness of our system compared to the widely adopted OpenKiwi-XLM baseline. Our system is also the top-ranking system on the MT MCC metric for the English-German language pair.
%U https://aclanthology.org/2021.wmt-1.94
%P 904-910
Markdown (Informal)
[The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task](https://aclanthology.org/2021.wmt-1.94) (Ding et al., WMT 2021)
ACL