Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus

Andrea Piergentili, Beatrice Savoldi, Dennis Fucci, Matteo Negri, Luisa Bentivogli


Abstract
Gender inequality is embedded in our communication practices and perpetuated in translation technologies. This becomes particularly apparent when translating into grammatical gender languages, where machine translation (MT) often defaults to masculine and stereotypical representations by making undue binary gender assumptions. Our work addresses the rising demand for inclusive language by focusing head-on on gender-neutral translation from English to Italian. We start from the essentials: proposing a dedicated benchmark and exploring automated evaluation methods. First, we introduce GeNTE, a natural, bilingual test set for gender-neutral translation, whose creation was informed by a survey on the perception and use of neutral language. Based on GeNTE, we then overview existing reference-based evaluation approaches, highlight their limits, and propose a reference-free method more suitable to assess gender-neutral translation.
Anthology ID:
2023.emnlp-main.873
Original:
2023.emnlp-main.873v1
Version 2:
2023.emnlp-main.873v2
Volume:
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2023
Address:
Singapore
Editors:
Houda Bouamor, Juan Pino, Kalika Bali
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
14124–14140
Language:
URL:
https://aclanthology.org/2023.emnlp-main.873
DOI:
10.18653/v1/2023.emnlp-main.873
Bibkey:
Cite (ACL):
Andrea Piergentili, Beatrice Savoldi, Dennis Fucci, Matteo Negri, and Luisa Bentivogli. 2023. Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 14124–14140, Singapore. Association for Computational Linguistics.
Cite (Informal):
Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus (Piergentili et al., EMNLP 2023)
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PDF:
https://preview.aclanthology.org/nschneid-patch-5/2023.emnlp-main.873.pdf
Video:
 https://preview.aclanthology.org/nschneid-patch-5/2023.emnlp-main.873.mp4