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A Comparison of Differential Performance Metrics for the Evaluation of Automatic Speaker Verification Fairness
- Publication Year :
- 2024
-
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.<br />Comment: 8 pages, 7 figures
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2404.17810
- Document Type :
- Working Paper