Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10427128" target="_blank" >RIV/00216208:11320/19:10427128 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/P19-1161" target="_blank" >https://www.aclweb.org/anthology/P19-1161</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology
Original language description
Gender stereotypes are manifest in most of the world's languages and are consequently propagated or amplified by NLP systems. Although research has focused on mitigating gender stereotypes in English, the approaches that are commonly employed produce ungrammatical sentences in morphologically rich languages. We present a novel approach for converting between masculine-inflected and feminine-inflected sentences in such languages. For Spanish and Hebrew, our approach achieves F1 scores of 82% and 73% at the level of tags and accuracies of 90% and 87% at the level of forms. By evaluating our approach using four different languages, we show that, on average, it reduces gender stereotyping by a factor of 2.5 without any sacrifice to grammaticality.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů