Gender-Fair (Machine) Translation
- Autor(en)
- Manuel Lardelli, Dagmar Gromann
- Abstrakt
Recent years have seen an increased visibility of non-binary people in public discourse. Accordingly, gender-fair language strategies that go beyond a binary conception of gender have been proposed. Such strategies pose a challenge for both translators and machine translation (MT), and gender-fair (machine) translation represents a relatively novel research field. With this survey and discussion, we hope to provide a starting point for this field and contribute a detailed overview of (machine) translation strategies to counteract the misrepresentation of an individual’s gender. The results show that gender-fair translation studies (TS) approaches largely focus on media translation, such as subtitles or news articles, and the MT results show
that the need to include non-binary debiasing methods is increasingly acknowledged, however, hardly ever implemented. Ideas on a closer mutually beneficial interaction between MT and translation studies are presented to advance multilingual gender-fair language use.- Organisation(en)
- Institut für Translationswissenschaft
- Externe Organisation(en)
- Karl-Franzens-Universität Graz
- Publikationsdatum
- 2023
- Peer-reviewed
- Ja
- ÖFOS 2012
- 602051 Translationswissenschaft, 504014 Gender Studies
- Link zum Portal
- https://ucrisportal.univie.ac.at/de/publications/bdb12971-a045-4989-a28b-862390597246