mlsanityData to 7 Oct 2026

Adversarial Speaker Distillation for Countermeasure Model on Automatic Speaker Verification

arXiv 2203.17031 ↗First posted 31 Mar 2022cs.SD cs.LG eess.AScited by 2

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Abstract (arXiv)

The countermeasure (CM) model is developed to protect ASV systems from spoof attacks and prevent resulting personal information leakage in Automatic Speaker Verification (ASV) system. Based on practicality and security considerations, the CM model is usually deployed on edge devices, which have more limited computing resources and storage space than cloud-based systems, confining the model size under a limitation. To better trade off the CM model sizes and performance, we proposed an adversarial speaker distillation method, which is an improved version of knowledge distillation method combined with generalized end-to-end (GE2E) pre-training and adversarial fine-tuning. In the evaluation phase of the ASVspoof 2021 Logical Access task, our proposed adversarial speaker distillation ResNetSE (ASD-ResNetSE) model reaches 0.2695 min t-DCF and 3.54% EER. ASD-ResNetSE only used 22.5% of parameters and 19.4% of multiply and accumulate operands of ResNetSE model.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 31 of its 46 references that are in the map. First posted on arXiv 31 Mar 2022.

Builds on

31 of 46 references.

References · 31

  1. 2015Distilling the Knowledge in a Neural Networkcited by 10,076
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  3. 2018The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networkscited by 2,250
  4. 2016Adversarial Machine Learning at Scalecited by 934
  5. 2015MUSAN: A Music, Speech, and Noise Corpuscited by 400
  6. 2017Generalized End-to-End Loss for Speaker Verificationcited by 290
  7. 2019ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detectioncited by 173
  8. 2021AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networkscited by 173
  9. 2020End-to-end anti-spoofing with RawNet2cited by 160
  10. 2021ASVspoof 2021: accelerating progress in spoofed and deepfake speech detectioncited by 157
  11. 2020In defence of metric learning for speaker recognitioncited by 123
  12. 2022Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentationcited by 110
19 more
  1. 2020Self-training and Pre-training are Complementary for Speech Recognitioncited by 98
  2. 2019STC Antispoofing Systems for the ASVspoof2019 Challengecited by 51
  3. 2015End-to-End Text-Dependent Speaker Verificationcited by 49
  4. 2022LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERTcited by 45
  5. 2022MFA-Conformer: Multi-scale Feature Aggregation Conformer for Automatic Speaker Verificationcited by 44
  6. 2018Fooling End-to-end Speaker Verification by Adversarial Examplescited by 39
  7. 2020Clova Baseline System for the VoxCeleb Speaker Recognition Challenge 2020cited by 36
  8. 2020Improving on-device speaker verification using federated learning with privacycited by 29
  9. 2019ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworkscited by 23
  10. 2019Adversarial Attacks on Spoofing Countermeasures of automatic speaker verificationcited by 23
  11. 2020Tandem Assessment of Spoofing Countermeasures and Automatic Speaker Verification: Fundamentalscited by 22
  12. 2020Defense against adversarial attacks on spoofing countermeasures of ASVcited by 20
  13. 2021Adversarial defense for automatic speaker verification by cascaded self-supervised learning modelscited by 16
  14. 2021Improving the Adversarial Robustness for Speaker Verification by Self-Supervised Learningcited by 16
  15. 2022Partially Fake Audio Detection by Self-attention-based Fake Span Discoverycited by 14
  16. 2020Defense for Black-box Attacks on Anti-spoofing Models by Self-Supervised Learningcited by 12
  17. 2021Voting for the right answer: Adversarial defense for speaker verificationcited by 12
  18. 2021UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021cited by 8
  19. 2019Detecting Spoofing Attacks Using VGG and SincNet: BUT-Omilia Submission to ASVspoof 2019 Challengecited by 6

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Citing papers per year: 2022: 1; 2023: 0; 2024: 1.

2 papers.

  1. 2024DFADD: The Diffusion and Flow-Matching Based Audio Deepfake Datasetcited by 20
  2. 2022Multimodal Transformer Distillation for Audio-Visual Synchronizationcited by 2