Gender-Fair Post-Editing: A Case Study Beyond the Binary

Manuel Lardelli, Dagmar Gromann

Abstract
Machine Translation (MT) models are well-known to suffer from gender bias, especially for gender beyond a binary conception. Due to the multiplicity of language-specific strategies for gender representation beyond the binary, debiasing MT is extremely challenging. As an alternative, we propose a case study on gender-fair post-editing. In this study, six professional translators each post-edited three English to German machine translations. For each translation, participants were instructed to use a different gender-fair language strategy, that is, gender-neutral rewording, gender-inclusive characters, and a neosystem. The focus of this study is not on translation quality but rather on the ease of integrating gender-fair language into the post-editing process. Findings from non-participant observation and interviews show clear differences in temporal and cognitive effort between participants and strategy as well as in the success of using gender-fair language.
Anthology ID:
2023.eamt-1.24
Volume:
Proceedings of the 24th Annual Conference of the European Association for Machine Translation
Month:
June
Year:
2023
Address:
Tampere, Finland
Editors:
Mary Nurminen, Judith Brenner, Maarit Koponen, Sirkku Latomaa, Mikhail Mikhailov, Frederike Schierl, Tharindu Ranasinghe, Eva Vanmassenhove, Sergi Alvarez Vidal, Nora Aranberri, Mara Nunziatini, Carla Parra Escartín, Mikel Forcada, Maja Popovic, Carolina Scarton, Helena Moniz
Venue:
EAMT
SIG:
Publisher:
European Association for Machine Translation
Note:
Pages:
251–260
Language:
URL:
https://aclanthology.org/2023.eamt-1.24
DOI:
Bibkey:
Cite (ACL):
Manuel Lardelli and Dagmar Gromann. 2023. Gender-Fair Post-Editing: A Case Study Beyond the Binary. In Proceedings of the 24th Annual Conference of the European Association for Machine Translation, pages 251–260, Tampere, Finland. European Association for Machine Translation.
Cite (Informal):
Gender-Fair Post-Editing: A Case Study Beyond the Binary (Lardelli & Gromann, EAMT 2023)
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PDF:
https://preview.aclanthology.org/nschneid-patch-3/2023.eamt-1.24.pdf
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