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arXiv · 2404.17810

A Comparison of Differential Performance Metrics for the Evaluation of Automatic Speaker Verification Fairness

Oubaida Chouchane·Christoph Busch·Chiara Galdi·Nicholas Evans·Massimiliano Todisco
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Abstract

When decisions are made and when personal data is treated by automated processes, there is an expectation of fairness -- that members of different demographic groups receive equitable treatment. This expectation applies to biometric systems such as automatic speaker verification (ASV). We present a comparison of three candidate fairness metrics and extend previous work performed for face recognition, by examining differential performance across a range of different ASV operating points. Results show that the Gini Aggregation Rate for Biometric Equitability (GARBE) is the only one which meets three functional fairness measure criteria. Furthermore, a comprehensive evaluation of the fairness and verification performance of five state-of-the-art ASV systems is also presented. Our findings reveal a nuanced trade-off between fairness and verification accuracy underscoring the complex interplay between system design, demographic inclusiveness, and verification reliability.

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Oubaida Chouchane, Christoph Busch, Chiara Galdi, Nicholas Evans, Massimiliano Todisco. 2024-04-27. A Comparison of Differential Performance Metrics for the Evaluation of Automatic Speaker Verification Fairness. https://arxiv.org/abs/2404.17810

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