Investigating the Impact of Different Pivot Languages on Translation Quality

Longhui Zou, Ali Saeedi, Michael Carl


Abstract
Translating via an intermediate pivot language is a common practice, but the impact of the pivot language on the quality of the final translation has not often been investigated. In order to compare the effect of different pivots, we back-translate 41 English source segments via vari- ous intermediate channels (Arabic, Chinese and monolingual paraphrasing) into English. We compare the 912 English back-translations of the 41 original English segments using manual evaluation, as well as COMET and various incarnations of BLEU. We compare human from- scratch back-translations with MT back-translations and monolingual paraphrasing. A varia- tion of BLEU (Cum-2) seems to better correlate with our manual evaluation than COMET and the conventional BLEU Cum-4, but a fine-grained qualitative analysis reveals that differences between different pivot languages (Arabic and Chinese) are not captured by the automatized TQA measures.
Anthology ID:
2022.amta-wetpr.3
Volume:
Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Workshop 1: Empirical Translation Process Research)
Month:
September
Year:
2022
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Venue:
AMTA
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Publisher:
Association for Machine Translation in the Americas
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Pages:
15–28
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URL:
https://aclanthology.org/2022.amta-wetpr.3
DOI:
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Cite (ACL):
Longhui Zou, Ali Saeedi, and Michael Carl. 2022. Investigating the Impact of Different Pivot Languages on Translation Quality. In Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Workshop 1: Empirical Translation Process Research), pages 15–28, None. Association for Machine Translation in the Americas.
Cite (Informal):
Investigating the Impact of Different Pivot Languages on Translation Quality (Zou et al., AMTA 2022)
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https://preview.aclanthology.org/auto-file-uploads/2022.amta-wetpr.3.pdf