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arXiv · 2305.13740

TeCS: A Dataset and Benchmark for Tense Consistency of Machine Translation

Yiming Ai·Zhiwei He·Kai Yu·Rui Wang
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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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Yiming Ai, Zhiwei He, Kai Yu, Rui Wang. 2023-05-23. TeCS: A Dataset and Benchmark for Tense Consistency of Machine Translation. https://arxiv.org/abs/2305.13740

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