Participatory Research as a Path to Community-Informed, Gender-Fair Machine Translation

• URL: http://arxiv.org/abs/2306.08906v1
• Date: Thu, 15 Jun 2023 07:20:14 GMT
• Title: Participatory Research as a Path to Community-Informed, Gender-Fair Machine Translation
• Authors: Dagmar Gromann, Manuel Lardelli, Katta Spiel, Sabrina Burtscher, Lukas Daniel Klausner, Arthur Mettinger, Igor Miladinovic, Sigrid Schefer-Wenzl, Daniela Duh, Katharina B\"uhn
• Abstract summary: We propose a method and case study building on participatory action research to include queer and non-binary people, translators, and MT experts. The case study focuses on German, where central findings are the importance of context dependency to avoid identity invalidation.
• Score: 19.098548371499678
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent years have seen a strongly increased visibility of non-binary people in public discourse. Accordingly, considerations of gender-fair language go beyond a binary conception of male/female. However, language technology, especially machine translation (MT), still suffers from binary gender bias. Proposing a solution for gender-fair MT beyond the binary from a purely technological perspective might fall short to accommodate different target user groups and in the worst case might lead to misgendering. To address this challenge, we propose a method and case study building on participatory action research to include experiential experts, i.e., queer and non-binary people, translators, and MT experts, in the MT design process. The case study focuses on German, where central findings are the importance of context dependency to avoid identity invalidation and a desire for customizable MT solutions.

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