a-DCF: an architecture agnostic metric with application to spoofing-robust speaker verification
Open accessAbstract
Spoofing detection is today a mainstream research topic. Standard metrics can be applied to evaluate the performance of isolated spoofing detection solutions and others have been proposed to support their evaluation when they are combined with speaker detection. These either have well-known deficiencies or restrict the architectural approach to combine speaker and spoof detectors. In this paper, we propose an architecture-agnostic detection cost function (a-DCF). A generalisation of the original DCF used widely for the assessment of automatic speaker verification (ASV), the a-DCF is designed for the evaluation of spoofing-robust ASV. Like the DCF, the a-DCF reflects the cost of decisions in a Bayes risk sense, with explicitly defined class priors and detection cost model. We demonstrate the merit of the a-DCF through the benchmarking evaluation of architecturally-heterogeneous spoofing-robust ASV solutions.
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The architecture-agnostic DCF is used as the primary metric for Track 2.
“The recently proposed architecture-agnostic DCF (a-DCF) [9] is used as the primary metric for Track 2”
From ASVspoof 5: crowdsourced speech data, deepfakes, and adversarial attacks at scale (2024) · cites this paper as [9]
In ASVspoof 5, t-DCF is used concurrently with t-EER and a-DCF.
“In ASVspoof 5, it is used concurrently with the recently proposed t-EER [94] and a-DCF [95]”
From Audio Deepfake Detection: What Has Been Achieved and What Lies Ahead (2025) · cites this paper as [95]
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Self-citation
- Authors
- Shim, H.-J., Jung, J.-W., Kinnunen, T., Evans, N., Bonastre, J.-F., & Lapidot, I.
- Affiliations
- EURECOM (FR)
- Venue
- The Speaker and Language Recognition Workshop (Odyssey 2024)
- Publisher
- ISCA
- Published
- 2024-06-18
- Pages
- 158-164
- OpenAlex
- W4392487686
- Cited by
- 14
- References
- 0
- Citations by year
- 2026: 5 · 2025: 9
- FWCI
- 4.04
- Type
- conference paper
- Language
- en
- Open access
- green
- hal.science
- Locations
- The Speaker and Language Recognition Workshop (Odyssey) (publishedVersion)
- HAL (submittedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (2137603, 2138259, 2138296, 2138307, Bridges2, 2138286)
- National Centre for Supercomputing Applications (2138296, #2138307, #2138286, CIS210014, #2138259, #2137603)
- Agence Nationale de la Recherche (ANR-22-CE39-0009)
- Office of Advanced Cyberinfrastructure (#2138286, #2138296, 2138259, #2138307, 2137603)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Keywords
- anti-spoofing, speaker verification, spoofing attacks
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