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Exploring the Importance of Source Text in Automatic Post-Editing for Context-Aware Machine Translation

Wang, Chaojun; Hardmeier, Christian; Sennrich, Rico (2021). Exploring the Importance of Source Text in Automatic Post-Editing for Context-Aware Machine Translation. In: Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), Reykjavik, Iceland (Online), 31 May 2021 - 2 June 2021. ACL Anthology, 326-335.

Abstract

Accurate translation requires document-level information, which is ignored by sentence-level machine translation. Recent work has demonstrated that document-level consistency can be improved with automatic post-editing (APE) using only target-language (TL) information. We study an extended APE model that additionally integrates source context. A human evaluation of fluency and adequacy in English–Russian translation reveals that the model with access to source context significantly outperforms monolingual APE in terms of adequacy, an effect largely ignored by automatic evaluation metrics. Our results show that TL-only modelling increases fluency without improving adequacy, demonstrating the need for conditioning on source text for automatic post-editing. They also highlight blind spots in automatic methods for targeted evaluation and demonstrate the need for human assessment to evaluate document-level translation quality reliably.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:2 June 2021
Deposited On:08 Nov 2021 16:06
Last Modified:08 Nov 2021 16:06
Publisher:ACL Anthology
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:https://www.aclweb.org/anthology/2021.nodalida-main.34
Project Information:
  • Funder: H2020
  • Grant ID: 825460
  • Project Title: European Live Translator
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  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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