@inproceedings{ai-etal-2023-tecs,
title = "{T}e{CS}: A Dataset and Benchmark for Tense Consistency of Machine Translation",
author = "Ai, Yiming and
He, Zhiwei and
Yu, Kai and
Wang, Rui",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-short.164",
doi = "10.18653/v1/2023.acl-short.164",
pages = "1930--1941",
abstract = "Tense inconsistency frequently occurs in machine translation. However, there are few criteria to assess the model{'}s mastery of tense prediction from a linguistic perspective. In this paper, we present a parallel tense test set, containing French-English 552 utterances. We also introduce a corresponding benchmark, tense prediction accuracy. With the tense test set and the benchmark, researchers are able to measure the tense consistency performance of machine translation systems for the first time.",
}
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%0 Conference Proceedings
%T TeCS: A Dataset and Benchmark for Tense Consistency of Machine Translation
%A Ai, Yiming
%A He, Zhiwei
%A Yu, Kai
%A Wang, Rui
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F ai-etal-2023-tecs
%X Tense inconsistency frequently occurs in machine translation. However, there are few criteria to assess the model’s mastery of tense prediction from a linguistic perspective. In this paper, we present a parallel tense test set, containing French-English 552 utterances. We also introduce a corresponding benchmark, tense prediction accuracy. With the tense test set and the benchmark, researchers are able to measure the tense consistency performance of machine translation systems for the first time.
%R 10.18653/v1/2023.acl-short.164
%U https://aclanthology.org/2023.acl-short.164
%U https://doi.org/10.18653/v1/2023.acl-short.164
%P 1930-1941
Markdown (Informal)
[TeCS: A Dataset and Benchmark for Tense Consistency of Machine Translation](https://aclanthology.org/2023.acl-short.164) (Ai et al., ACL 2023)
ACL