@inproceedings{bawden-etal-2020-parbleu,
title = "{P}ar{BLEU}: Augmenting Metrics with Automatic Paraphrases for the {WMT}{'}20 Metrics Shared Task",
author = {Bawden, Rachel and
Zhang, Biao and
T{\"a}ttar, Andre and
Post, Matt},
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.98",
pages = "887--894",
abstract = "We describe parBLEU, parCHRF++, and parESIM, which augment baseline metrics with automatically generated paraphrases produced by PRISM (Thompson and Post, 2020a), a multilingual neural machine translation system. We build on recent work studying how to improve BLEU by using diverse automatically paraphrased references (Bawden et al., 2020), extending experiments to the multilingual setting for the WMT2020 metrics shared task and for three base metrics. We compare their capacity to exploit up to 100 additional synthetic references. We find that gains are possible when using additional, automatically paraphrased references, although they are not systematic. However, segment-level correlations, particularly into English, are improved for all three metrics and even with higher numbers of paraphrased references.",
}
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%0 Conference Proceedings
%T ParBLEU: Augmenting Metrics with Automatic Paraphrases for the WMT’20 Metrics Shared Task
%A Bawden, Rachel
%A Zhang, Biao
%A Tättar, Andre
%A Post, Matt
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F bawden-etal-2020-parbleu
%X We describe parBLEU, parCHRF++, and parESIM, which augment baseline metrics with automatically generated paraphrases produced by PRISM (Thompson and Post, 2020a), a multilingual neural machine translation system. We build on recent work studying how to improve BLEU by using diverse automatically paraphrased references (Bawden et al., 2020), extending experiments to the multilingual setting for the WMT2020 metrics shared task and for three base metrics. We compare their capacity to exploit up to 100 additional synthetic references. We find that gains are possible when using additional, automatically paraphrased references, although they are not systematic. However, segment-level correlations, particularly into English, are improved for all three metrics and even with higher numbers of paraphrased references.
%U https://aclanthology.org/2020.wmt-1.98
%P 887-894
Markdown (Informal)
[ParBLEU: Augmenting Metrics with Automatic Paraphrases for the WMT’20 Metrics Shared Task](https://aclanthology.org/2020.wmt-1.98) (Bawden et al., WMT 2020)
ACL