mlsanityData to 7 Oct 2026

Multi-Dataset Co-Training with Sharpness-Aware Optimization for Audio Anti-spoofing

arXiv 2305.19953 ↗First posted 31 May 2023cs.SD cs.LG eess.AScited by 9

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Abstract (arXiv)

Audio anti-spoofing for automatic speaker verification aims to safeguard users' identities from spoofing attacks. Although state-of-the-art spoofing countermeasure(CM) models perform well on specific datasets, they lack generalization when evaluated with different datasets. To address this limitation, previous studies have explored large pre-trained models, which require significant resources and time. We aim to develop a compact but well-generalizing CM model that can compete with large pre-trained models. Our approach involves multi-dataset co-training and sharpness-aware minimization, which has not been investigated in this domain. Extensive experiments reveal that proposed method yield competitive results across various datasets while utilizing 4,000 times less parameters than the large pre-trained models.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 33 of its 47 references that are in the map. First posted on arXiv 31 May 2023.

Builds on

33 of 47 references.

References · 33

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21 more
  1. 2022Improving Generalization in Federated Learning by Seeking Flat Minimacited by 98
  2. 2021WaveFake: A Data Set to Facilitate Audio Deepfake Detectioncited by 78
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  6. 2021RawBoost: A Raw Data Boosting and Augmentation Method applied to Automatic Speaker Verification Anti-Spoofingcited by 64
  7. 2020One-class Learning Towards Synthetic Voice Spoofing Detectioncited by 59
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  13. 2018Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentationcited by 18
  14. 2021A Study On Data Augmentation In Voice Anti-Spoofingcited by 16
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  21. 2022Model Generalization: A Sharpness Aware Optimization Perspectivecited by 2

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Cited by year

Citing papers per year: 2024: 6; 2025: 3.

9 papers.

  1. 2024The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audiocited by 31
  2. 2024Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapescited by 10
  3. 2024Prompt Tuning for Audio Deepfake Detection: Computationally Efficient Test-time Domain Adaptation with Limited Target Datasetcited by 7
  4. 2024SZU-AFS Antispoofing System for the ASVspoof 5 Challengecited by 4
  5. 2024Passive Deepfake Detection Across Multi-modalities: A Comprehensive Surveycited by 4
  6. 2025Bona fide Cross Testing Reveals Weak Spot in Audio Deepfake Detection Systemscited by 3
  7. 2024Beyond Silence: Bias Analysis through Loss and Asymmetric Approach in Audio Anti-Spoofingcited by 2
  8. 2025AMA-SAM: Adversarial Multi-Domain Alignment of Segment Anything Model for High-Fidelity Histology Nuclei Segmentationcited by 1
  9. 2025FADEL: Uncertainty-aware Fake Audio Detection with Evidential Deep Learningcited by 1