GATE: A Challenge Set for Gender-Ambiguous Translation Examples

Although recent years have brought significant progress in improving translation of unambiguously gendered sentences, translation of ambiguously gendered input remains relatively unexplored. When source gender is ambiguous, machine translation models typically default to stereotypical gender roles,...

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Bibliographic Details
Published inarXiv.org
Main Authors Spencer Rarrick, Naik, Ranjita, Mathur, Varun, Poudel, Sundar, Chowdhary, Vishal
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 07.03.2023
Subjects
Machine translation
Sentences
Systems analysis
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Summary:Although recent years have brought significant progress in improving translation of unambiguously gendered sentences, translation of ambiguously gendered input remains relatively unexplored. When source gender is ambiguous, machine translation models typically default to stereotypical gender roles, perpetuating harmful bias. Recent work has led to the development of "gender rewriters" that generate alternative gender translations on such ambiguous inputs, but such systems are plagued by poor linguistic coverage. To encourage better performance on this task we present and release GATE, a linguistically diverse corpus of gender-ambiguous source sentences along with multiple alternative target language translations. We also provide tools for evaluation and system analysis when using GATE and use them to evaluate our translation rewriter system.
ISSN:2331-8422