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        <title>Group Fairness in Multilingual Speech Recognition Models</title>
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            <namePart type="given">Kevin</namePart>
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            <namePart type="given">Helena</namePart>
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    <abstract>We evaluate the performance disparity of the Whisper and MMS families of ASR models across the VoxPopuli and Common Voice multilingual datasets, with an eye toward intersectionality. Our two most important findings are that model size, surprisingly, correlates logarithmically with worst-case performance disparities, meaning that larger (and better) models are less fair. We also observe the importance of intersectionality. In particular, models often exhibit significant performance disparity across binary gender for adolescents.</abstract>
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%0 Conference Proceedings
%T Group Fairness in Multilingual Speech Recognition Models
%A Zee, Anna
%A Zee, Marc
%A Søgaard, Anders
%Y Duh, Kevin
%Y Gomez, Helena
%Y Bethard, Steven
%S Findings of the Association for Computational Linguistics: NAACL 2024
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F zee-etal-2024-group
%X We evaluate the performance disparity of the Whisper and MMS families of ASR models across the VoxPopuli and Common Voice multilingual datasets, with an eye toward intersectionality. Our two most important findings are that model size, surprisingly, correlates logarithmically with worst-case performance disparities, meaning that larger (and better) models are less fair. We also observe the importance of intersectionality. In particular, models often exhibit significant performance disparity across binary gender for adolescents.
%U https://aclanthology.org/2024.findings-naacl.143
%P 2213-2226

Markdown (Informal)

[Group Fairness in Multilingual Speech Recognition Models](https://aclanthology.org/2024.findings-naacl.143) (Zee et al., Findings 2024)

• Group Fairness in Multilingual Speech Recognition Models (Zee et al., Findings 2024)

ACL

• Anna Zee, Marc Zee, and Anders Søgaard. 2024. Group Fairness in Multilingual Speech Recognition Models. In Findings of the Association for Computational Linguistics: NAACL 2024, pages 2213–2226, Mexico City, Mexico. Association for Computational Linguistics.