mlsanityData to 7 Oct 2026

Beyond ROC-AUC: Operating-Point Performance Reporting for Biometric Verification

arXiv 2606.20680 ↗First posted 13 Jun 2026cs.CV eess.AScited by 0

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Abstract (arXiv)

A biometric verifier is often deployed with a strict false match budget, so only a narrow, low false match rate (FMR) slice of the score range is used. A reporting standard for this setting already exists. ISO/IEC 19795-1 asks for error rates at stated operating points, for the detection error tradeoff (DET) curve as the view of the trade-off between FMR and the false non-match rate (FNMR), and for an interval of uncertainty on every value. In practice, a single area under the receiver operating characteristic curve (ROC-AUC), the equal error rate (EER), or a verification accuracy is still reported as the resolution, which is a threshold-independent summary that the standard does not endorse. The full ROC-AUC averages the true match rate (TMR) with equal weight over the whole FMR range from 0 to 1, so almost all of its weight is placed where the system is never operated; low-FMR behavior can then be hidden, and the order of two systems can even be reversed. The guideline is revisited in this paper and tested against seven pretrained matchers across four modalities, face, voice, iris, and fingerprint, each reported with bootstrap confidence intervals and paired bootstrap tests. A system that looks stronger on full ROC-AUC is shown to be significantly worse at FMR = 10^-3. For face, a higher full AUC was obtained by FaceNet, whereas a higher TMR at FMR = 10^-3 was obtained by ArcFace, and both gaps were significant with non-overlapping intervals. Hence, the DET curve and the FNMR at a fixed FMR are re-iterated in this paper as the primary report, with ROC-AUC and EER retained as supplementary context.

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References · 9

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  5. 2017VoxCeleb: a large-scale speaker identification datasetcited by 714
  6. 2020ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verificationcited by 606
  7. 2021SpeechBrain: A General-Purpose Speech Toolkitcited by 404
  8. 2025Descriptor:: Extended-Length Audio Dataset for Synthetic Voice Detection and Speaker Recognition (ELAD-SVDSR)cited by 1
  9. 2026Classical Machine Learning Baselines for Deepfake Audio Detection on the Fake-or-Real Datasetcited by 1

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