# ASVspoof 2021: Automatic Speaker Verification Spoofing and Countermeasures Challenge Evaluation Plan

arXiv: https://arxiv.org/abs/2109.00535 · HTML: https://mlsanity.com/paper/2109.00535/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 11 references that are in the map.
- First posted on arXiv 1 Sep 2021.

## Builds on (most cited first, 5 of 5)

- [End-to-end anti-spoofing with RawNet2](https://mlsanity.com/paper/2011.01108/) (2020)
- [A Comparative Study on Recent Neural Spoofing Countermeasures for Synthetic Speech Detection](https://mlsanity.com/paper/2103.11326/) (2021)
- [Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification: Fundamentals](https://mlsanity.com/paper/2007.05979/) (2020)
- [t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification](https://mlsanity.com/paper/1804.09618/) (2018)
- [Spoofing Attack Detection using the Non-linear Fusion of Sub-band Classifiers](https://mlsanity.com/paper/2005.10393/) (2020)

## Built on by (most cited first, 20 of 20)

- [AudioLM: a Language Modeling Approach to Audio Generation](https://mlsanity.com/paper/2209.03143/) (2022)
- [FSD: An Initial Chinese Dataset for Fake Song Detection](https://mlsanity.com/paper/2309.02232/) (2023)
- [An Efficient Temporary Deepfake Location Approach Based Embeddings for Partially Spoofed Audio Detection](https://mlsanity.com/paper/2309.03036/) (2023)
- [Deepfake: Definitions, Performance Metrics and Standards, Datasets and Benchmarks, and a Meta-Review](https://mlsanity.com/paper/2208.10913/) (2022)
- [t-EER: Parameter-Free Tandem Evaluation of Countermeasures and Biometric Comparators](https://mlsanity.com/paper/2309.12237/) (2023)
- [Reliable Audio Deepfake Detection in Variable Conditions via Quantum-Kernel SVMs](https://mlsanity.com/paper/2512.18797/) (2025)
- [A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems](https://mlsanity.com/paper/2508.16843/) (2025)
- [SONAR: Spectral-Contrastive Audio Residuals for Generalizable Deepfake Detection](https://mlsanity.com/paper/2511.21325/) (2025)
- [Impact of Channel Variation on One-Class Learning for Spoof Detection](https://mlsanity.com/paper/2109.14900/) (2021)
- [An End-to-End Multi-Module Audio Deepfake Generation System for ADD Challenge 2023](https://mlsanity.com/paper/2307.00729/) (2023)
- [Frequency-mix Knowledge Distillation for Fake Speech Detection](https://mlsanity.com/paper/2406.09664/) (2024)
- [RoVo: Robust Voice Protection Against Unauthorized Speech Synthesis with Embedding-Level Perturbations](https://mlsanity.com/paper/2505.12686/) (2025)
- [Efficient Speech Watermarking for Speech Synthesis via Progressive Knowledge Distillation](https://mlsanity.com/paper/2509.19812/) (2025)
- [Listening Deepfake Detection: A New Perspective Beyond Speaking-Centric Forgery Analysis](https://mlsanity.com/paper/2604.12650/) (2026)
- [Phoneme-Level Deepfake Detection Across Emotional Conditions Using Self-Supervised Embeddings](https://mlsanity.com/paper/2605.03079/) (2026)
- [Deepfake Audio Detection Using Self-supervised Fusion Representations](https://mlsanity.com/paper/2605.03420/) (2026)
- [From AI-Generated Content to Agentic Action: Security and Safety Threats in Generative AI](https://mlsanity.com/paper/2605.16471/) (2026)
- [SynSFX: Multi-Model Sound Effects Synthesis Dataset for Deepfake Detection and Evaluation](https://mlsanity.com/paper/2607.04848/) (2026)
- [Probing Speaker Identity Sensitivity in Audio Deepfake Detectors](https://mlsanity.com/paper/2607.21820/) (2026)
- [On Evaluating Quantum Kernel Robustness for Low-Resource Cross-Corpus Audio Deepfake Detection](https://mlsanity.com/paper/2610.00649/) (2026)

## Abstract (arXiv)

The automatic speaker verification spoofing and countermeasures (ASVspoof) challenge series is a community-led initiative which aims to promote the consideration of spoofing and the development of countermeasures. ASVspoof 2021 is the 4th in a series of bi-annual, competitive challenges where the goal is to develop countermeasures capable of discriminating between bona fide and spoofed or deepfake speech. This document provides a technical description of the ASVspoof 2021 challenge, including details of training, development and evaluation data, metrics, baselines, evaluation rules, submission procedures and the schedule.