mlsanityData to 7 Oct 2026

An Initial Investigation for Detecting Vocoder Fingerprints of Fake Audio

arXiv 2208.09646 ↗First posted 20 Aug 2022cs.SD cs.AI eess.AScited by 12

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Abstract (arXiv)

Many effective attempts have been made for fake audio detection. However, they can only provide detection results but no countermeasures to curb this harm. For many related practical applications, what model or algorithm generated the fake audio also is needed. Therefore, We propose a new problem for detecting vocoder fingerprints of fake audio. Experiments are conducted on the datasets synthesized by eight state-of-the-art vocoders. We have preliminarily explored the features and model architectures. The t-SNE visualization shows that different vocoders generate distinct vocoder fingerprints.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 20 of its 40 references that are in the map. First posted on arXiv 20 Aug 2022.

Builds on

20 of 40 references.

References · 20

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  2. 2017Squeeze-and-Excitation Networkscited by 4,763
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  4. 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,139
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  8. 2019ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detectioncited by 173
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8 more
  1. 2020Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speechcited by 63
  2. 2019STC Antispoofing Systems for the ASVspoof2019 Challengecited by 51
  3. 2021Half-Truth: A Partially Fake Audio Detection Datasetcited by 44
  4. 2021Investigating self-supervised front ends for speech spoofing countermeasurescited by 43
  5. 2021Continual Learning for Fake Audio Detectioncited by 27
  6. 2020StyleMelGAN: An Efficient High-Fidelity Adversarial Vocoder with Temporal Adaptive Normalizationcited by 26
  7. 2016LCNN: Lookup-based Convolutional Neural Networkcited by 11
  8. 2018EMPHASIS: An Emotional Phoneme-based Acoustic Model for Speech Synthesis Systemcited by 4

Built on by

Cited by year (2026 to 7 Oct)

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

12 papers.

  1. 2023Do You Remember? Overcoming Catastrophic Forgetting for Fake Audio Detectioncited by 11
  2. 2023Single and Multi-Speaker Cloned Voice Detection: From Perceptual to Learned Featurescited by 10
  3. 2025STOPA: A Database of Systematic VariaTion Of DeePfake Audio for Open-Set Source Tracing and Attributioncited by 6
  4. 2024Generalized Source Tracing: Detecting Novel Audio Deepfake Algorithm with Real Emphasis and Fake Dispersion Strategycited by 5
  5. 2024Passive Deepfake Detection Across Multi-modalities: A Comprehensive Surveycited by 4
  6. 2025Synthetic Speech Source Tracing using Metric Learningcited by 4
  7. 2024Lightweight Model Attribution and Detection of Synthetic Speech via Audio Residual Fingerprintscited by 3
  8. 2025Signals of Provenance: Practices & Challenges of Navigating Indicators in AI-Generated Media for Sighted and Blind Individualscited by 2
  9. 2022Audio Deepfake Attribution: An Initial Dataset and Investigationcited by 1
  10. 2024Reject Threshold Adaptation for Open-Set Model Attribution of Deepfake Audiocited by 1
  11. 2025Towards Generalized Source Tracing for Codec-Based Deepfake Speechcited by 0
  12. 2026SNAP: Speaker Nulling for Artifact Projection in Speech Deepfake Detectioncited by 0