# a-DCF: an architecture agnostic metric with application to spoofing-robust speaker verification

arXiv: https://arxiv.org/abs/2403.01355 · HTML: https://mlsanity.com/paper/2403.01355/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 32 references that are in the map.
- First posted on arXiv 3 Mar 2024.

## Builds on (most cited first, 11 of 11)

- [AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks](https://mlsanity.com/paper/2110.01200/) (2021)
- [ASVspoof 2021: Towards Spoofed and Deepfake Speech Detection in the Wild](https://mlsanity.com/paper/2210.02437/) (2022)
- [Pushing the limits of raw waveform speaker recognition](https://mlsanity.com/paper/2203.08488/) (2022)
- [MFA-Conformer: Multi-scale Feature Aggregation Conformer for Automatic Speaker Verification](https://mlsanity.com/paper/2203.15249/) (2022)
- [The BOSARIS Toolkit: Theory, Algorithms and Code for Surviving the New DCF](https://mlsanity.com/paper/1304.2865/) (2013)
- [Towards single integrated spoofing-aware speaker verification embeddings](https://mlsanity.com/paper/2305.19051/) (2023)
- [Baseline Systems for the First Spoofing-Aware Speaker Verification Challenge: Score and Embedding Fusion](https://mlsanity.com/paper/2204.09976/) (2022)
- [The DKU-OPPO System for the 2022 Spoofing-Aware Speaker Verification Challenge](https://mlsanity.com/paper/2207.07510/) (2022)
- [t-EER: Parameter-Free Tandem Evaluation of Countermeasures and Biometric Comparators](https://mlsanity.com/paper/2309.12237/) (2023)
- [Generalizing Speaker Verification for Spoof Awareness in the Embedding Space](https://mlsanity.com/paper/2401.11156/) (2024)
- [Two Methods for Spoofing-Aware Speaker Verification: Multi-Layer Perceptron Score Fusion Model and Integrated Embedding Projector](https://mlsanity.com/paper/2206.13807/) (2022)

## Built on by (most cited first, 6 of 6)

- [ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale](https://mlsanity.com/paper/2408.08739/) (2024)
- [SpoofCeleb: Speech Deepfake Detection and SASV In The Wild](https://mlsanity.com/paper/2409.17285/) (2024)
- [SZU-AFS Antispoofing System for the ASVspoof 5 Challenge](https://mlsanity.com/paper/2408.09933/) (2024)
- [To what extent can ASV systems naturally defend against spoofing attacks?](https://mlsanity.com/paper/2406.05339/) (2024)
- [WildSpoof Challenge Evaluation Plan](https://mlsanity.com/paper/2508.16858/) (2025)
- [Large Audio Language Models for Spoofing-Aware Speaker Verification](https://mlsanity.com/paper/2607.14753/) (2026)

## Abstract (arXiv)

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.