mlsanityData to 7 Oct 2026

Exploring WavLM Back-ends for Speech Spoofing and Deepfake Detection

arXiv 2409.05032 ↗First posted 8 Sep 2024eess.AS cs.LG cs.SDcited by 10

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Abstract (arXiv)

This paper describes our submitted systems to the ASVspoof 5 Challenge Track 1: Speech Deepfake Detection - Open Condition, which consists of a stand-alone speech deepfake (bonafide vs spoof) detection task. Recently, large-scale self-supervised models become a standard in Automatic Speech Recognition (ASR) and other speech processing tasks. Thus, we leverage a pre-trained WavLM as a front-end model and pool its representations with different back-end techniques. The complete framework is fine-tuned using only the trained dataset of the challenge, similar to the close condition. Besides, we adopt data-augmentation by adding noise and reverberation using MUSAN noise and RIR datasets. We also experiment with codec augmentations to increase the performance of our method. Ultimately, we use the Bosaris toolkit for score calibration and system fusion to get better Cllr scores. Our fused system achieves 0.0937 minDCF, 3.42% EER, 0.1927 Cllr, and 0.1375 actDCF.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 20 of its 25 references that are in the map. First posted on arXiv 8 Sep 2024.

Builds on

20 of 25 references.

References · 20

  1. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  2. 2021HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitscited by 2,301
  3. 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,609
  4. 2016On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minimacited by 1,337
  5. 2021XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scalecited by 589
  6. 2019How to Fine-Tune BERT for Text Classification?cited by 409
  7. 2015MUSAN: A Music, Speech, and Noise Corpuscited by 400
  8. 2021YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyonecited by 277
  9. 2021AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networkscited by 173
  10. 2020End-to-end anti-spoofing with RawNet2cited by 160
  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
8 more
  1. 2021RawBoost: A Raw Data Boosting and Augmentation Method applied to Automatic Speaker Verification Anti-Spoofingcited by 64
  2. 2021Investigating self-supervised front ends for speech spoofing countermeasurescited by 43
  3. 2021A Study On Data Augmentation In Voice Anti-Spoofingcited by 16
  4. 2022An attention-based backend allowing efficient fine-tuning of transformer models for speaker verificationcited by 14
  5. 2013The BOSARIS Toolkit: Theory, Algorithms and Code for Surviving the New DCFcited by 12
  6. 2024Adapting WavLM for Speech Emotion Recognitioncited by 4
  7. 2024Towards Supervised Performance on Speaker Verification with Self-Supervised Learning by Leveraging Large-Scale ASR Modelscited by 4
  8. 2023Spoofing attack augmentation: can differently-trained attack models improve generalisation?cited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 9.

10 papers.

  1. 2026Assessing the Impact of Speaker Identity in Speech Spoofing Detectioncited by 5
  2. 2026Evolutionary Multi-Objective Fusion of Deepfake Speech Detectorscited by 3
  3. 2026Enhancing Multi-Corpus Training in SSL-Based Anti-Spoofing Models: Domain-Invariant Feature Extractioncited by 1
  4. 2025Multilingual Dataset Integration Strategies for Robust Audio Deepfake Detection: A SAFE Challenge Systemcited by 0
  5. 2026A SUPERB-Style Benchmark of Self-Supervised Speech Models for Audio Deepfake Detectioncited by 0
  6. 2026A Comparison of SSL-Based Feature Extractors and Back-End Classifiers for Spoofing Detection: A Multi-Corpus Training and Cross-Linguistic Analysiscited by 0
  7. 2026Speaker-Invariant Representation Learning for Spoofing Detection via Gradient Reversal and A Variational Information Bottleneckcited by 0
  8. 2026RAT: Reference-Augmented Training for ASV Anti-Spoofingcited by 0
  9. 2026What Do Deepfake Speech Detectors Actually Hear?cited by 0
  10. 2026Linguistic Bias Mitigation for Spoofing Detection via Gradient Reversal and A Variational Information Bottleneckcited by 0