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Gender Neutralization for an Inclusive Machine Translation: from Theoretical Foundations to Open Challenges

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arxiv 2301.10075 v3 pith:34HDIGBP submitted 2023-01-24 cs.CL

classification cs.CL
keywords gendertranslationinclusivitylanguagechallengesmachineachievedadvancements
verification ladder T0 review T1 audit T2 compute T3 formal
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Gender inclusivity in language technologies has become a prominent research topic. In this study, we explore gender-neutral translation (GNT) as a form of gender inclusivity and a goal to be achieved by machine translation (MT) models, which have been found to perpetuate gender bias and discrimination. Specifically, we focus on translation from English into Italian, a language pair representative of salient gender-related linguistic transfer problems. To define GNT, we review a selection of relevant institutional guidelines for gender-inclusive language, discuss its scenarios of use, and examine the technical challenges of performing GNT in MT, concluding with a discussion of potential solutions to encourage advancements toward greater inclusivity in MT.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. GeNRe: A French Gender-Neutral Rewriting System Using Collective Nouns

    cs.CL 2025-05 conditional novelty 6.0 of 10

    GeNRe is the first French gender-neutral rewriting system to replace masculine plural member nouns with collective nouns, reaching 3.81% WER with its rule-based version.

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