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Evaluating the Efficacy of Length-Controllable Machine Translation

arXiv 2305.02300 ↗First posted 3 May 2023cs.CL cs.AIcited by 0

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Abstract (arXiv)

Length-controllable machine translation is a type of constrained translation. It aims to contain the original meaning as much as possible while controlling the length of the translation. We can use automatic summarization or machine translation evaluation metrics for length-controllable machine translation, but this is not necessarily suitable and accurate. This work is the first attempt to evaluate the automatic metrics for length-controllable machine translation tasks systematically. We conduct a rigorous human evaluation on two translation directions and evaluate 18 summarization or translation evaluation metrics. We find that BLEURT and COMET have the highest correlation with human evaluation and are most suitable as evaluation metrics for length-controllable machine translation.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 31 of its 47 references that are in the map. First posted on arXiv 3 May 2023.

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References · 31

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19 more
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  2. 2020Rethinking embedding coupling in pre-trained language modelscited by 103
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  19. 2021Unifying Cross-lingual Summarization and Machine Translation with Compression Ratecited by 5

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