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@inproceedings{1790577,
author = {Štefánik, Michal and Novotný, Vít and Sojka, Petr},
address = {Online and Punta Cana, Dominican Republi},
booktitle = {Proceedings of EMNLP 2021 Sixth Conference on Machine Translation (WMT 21)},
editor = {Loïc Barrault et al.},
keywords = {machine translation; translation quality metrics; regressive ensemble for machine translation quality evaluation},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Online and Punta Cana, Dominican Republi},
isbn = {978-1-954085-94-7},
pages = {1041-1048},
publisher = {ACL},
title = {Regressive Ensemble for Machine Translation Quality Evaluation},
url = {https://arxiv.org/abs/2109.07242v1},
year = {2021}
}
TY - JOUR
ID - 1790577
AU - Štefánik, Michal - Novotný, Vít - Sojka, Petr
PY - 2021
TI - Regressive Ensemble for Machine Translation Quality Evaluation
PB - ACL
CY - Online and Punta Cana, Dominican Republi
SN - 9781954085947
KW - machine translation
KW - translation quality metrics
KW - regressive ensemble for machine translation quality evaluation
UR - https://arxiv.org/abs/2109.07242v1
N2 - This work introduces a simple regressive ensemble for evaluating machine translation quality based on a set of novel and established metrics. We evaluate the ensemble using a correlation to expert-based MQM scores of the WMT 2021 Metrics workshop. In both monolingual and zero-shot cross-lingual settings, we show a significant performance improvements over single systems. In the cross-lingual settings, we also demonstrate that an ensemble approach is well-applicable to unseen languages. Furthermore, we identify a strong reference-free baseline that consistently outperforms the commonly-used BLEU and METEOR measures and significantly improves our ensemble's performance.
ER -
ŠTEFÁNIK, Michal, Vít NOVOTNÝ a Petr SOJKA. Regressive Ensemble for Machine Translation Quality Evaluation. In Loïc Barrault et al. \textit{Proceedings of EMNLP 2021 Sixth Conference on Machine Translation (WMT 21)}. Online and Punta Cana, Dominican Republi: ACL. s.~1041-1048. ISBN~978-1-954085-94-7. 2021.
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