mlsanityData to 7 Oct 2026

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

arXiv 2109.00535 ↗First posted 1 Sep 2021eess.AS cs.CR cs.LGcited by 18

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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.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 1 Sep 2021.

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5 of 11 references.

References · 5

  1. 2020End-to-end anti-spoofing with RawNet2cited by 160
  2. 2021A Comparative Study on Recent Neural Spoofing Countermeasures for Synthetic Speech Detectioncited by 56
  3. 2020Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification: Fundamentalscited by 22
  4. 2018t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verificationcited by 19
  5. 2020Spoofing Attack Detection using the Non-linear Fusion of Sub-band Classifierscited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 4; 2024: 0; 2025: 4; 2026: 7.

18 papers.

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  1. 2022AudioLM: a Language Modeling Approach to Audio Generationcited by 611
  2. 2023FSD: An Initial Chinese Dataset for Fake Song Detectioncited by 12
  3. 2023An Efficient Temporary Deepfake Location Approach Based Embeddings for Partially Spoofed Audio Detectioncited by 10
  4. 2022Deepfake: Definitions, Performance Metrics and Standards, Datasets and Benchmarks, and a Meta-Reviewcited by 6
  5. 2023t-EER: Parameter-Free Tandem Evaluation of Countermeasures and Biometric Comparatorscited by 3
  6. 2025A Survey of Threats Against Voice Authentication and Anti-Spoofing Systemscited by 2
  7. 2025Reliable Audio Deepfake Detection in Variable Conditions via Quantum-Kernel SVMscited by 2
  8. 2025SONAR: Spectral-Contrastive Audio Residuals for Generalizable Deepfake Detectioncited by 1
  9. 2021Impact of Channel Variation on One-Class Learning for Spoof Detectioncited by 0
  10. 2023An End-to-End Multi-Module Audio Deepfake Generation System for ADD Challenge 2023cited by 0
  11. 2025RoVo: Robust Voice Protection Against Unauthorized Speech Synthesis with Embedding-Level Perturbationscited by 0
  12. 2026Listening Deepfake Detection: A New Perspective Beyond Speaking-Centric Forgery Analysiscited by 0
6 more
  1. 2026Phoneme-Level Deepfake Detection Across Emotional Conditions Using Self-Supervised Embeddingscited by 0
  2. 2026Deepfake Audio Detection Using Self-supervised Fusion Representationscited by 0
  3. 2026From AI-Generated Content to Agentic Action: Security and Safety Threats in Generative AIcited by 0
  4. 2026SynSFX: Multi-Model Sound Effects Synthesis Dataset for Deepfake Detection and Evaluationcited by 0
  5. 2026Probing Speaker Identity Sensitivity in Audio Deepfake Detectorscited by 0
  6. 2026On Evaluating Quantum Kernel Robustness for Low-Resource Cross-Corpus Audio Deepfake Detectioncited by 0