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

Andrea Piergentili, Dennis Fucci, Beatrice Savoldi, Luisa Bentivogli, Matteo Negri
1/24/2023
cs.CL

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Abstract

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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Cite this paper

@article{piergentili2023gender,
  title  = {Gender Neutralization for an Inclusive Machine Translation: from Theoretical Foundations to Open Challenges},
  author = {Andrea Piergentili and Dennis Fucci and Beatrice Savoldi and Luisa Bentivogli and Matteo Negri},
  year   = {2023},
  eprint = {2301.10075},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2301.10075v3}
}

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