Gender bias in machine translation: an analysis of Google Translate in English and Spanish

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/116954
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Title: Gender bias in machine translation: an analysis of Google Translate in English and Spanish
Authors: Lopez-Medel, Maria
Center, Department or Service: Universidad de Alicante. Departamento de Traducción e Interpretación
Keywords: Translation | Sexism | Automatic translation | Google Translate
Knowledge Area: Traducción e Interpretación
Issue Date: Jul-2021
Publisher: Academia.edu
Citation: Academia Letters. 2021, Article 2288. https://doi.org/10.20935/AL2288
Abstract: Although Google has attempted on several occasions to remove gender bias from its free online translation service, it still tends to exhibit predominantly masculine options and shows a tendency towards perpetuating or exaggerating sexist stereotypes, which adds to other flaws like a failure to notice text formality, typos and nuances. We analyse the gender bias of Google Translate between English and Spanish by entering a number of gender-invariable Spanish nouns whose referent’s gender was unknown due to the omission of pronouns and other particles. The results show a strong gender bias which needs to be removed by training machine translation software to infer semantic gender from pronouns and word terminations, and applying gender-tagging in multilingual corpora.
URI: http://hdl.handle.net/10045/116954
DOI: 10.20935/AL2288
Language: eng
Type: info:eu-repo/semantics/article
Rights: ©2021 by the author — Open Access — Distributed under CC BY 4.0
Peer Review: si
Publisher version: https://doi.org/10.20935/AL2288
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