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Audio Deepfake Detection

Nowadays, deepfake is now generically used by the media or people to refer to any audio or video in which important attributes have been either digitally altered or swapped, with the help of artificial intelligence (AI). Audio deepfake detection is a task that aims to distinguish genuine utterances from fake ones via machine learning techniques.

Papers

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Showing 1–10 of 74 papers

TitleStatusHype
Audio Deepfake Detection with Self-Supervised XLS-R and SLS ClassifierCode2
SafeEar: Content Privacy-Preserving Audio Deepfake DetectionCode2
Temporal-Channel Modeling in Multi-head Self-Attention for Synthetic Speech DetectionCode2
The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake AudioCode2
End-to-end Audio Deepfake Detection from RAW Waveforms: a RawNet-Based Approach with Cross-Dataset EvaluationCode1
Detect All-Type Deepfake Audio: Wavelet Prompt Tuning for Enhanced Auditory PerceptionCode1
Comprehensive Layer-wise Analysis of SSL Models for Audio Deepfake DetectionCode1
Region-Based Optimization in Continual Learning for Audio Deepfake DetectionCode1
XLSR-Mamba: A Dual-Column Bidirectional State Space Model for Spoofing Attack DetectionCode1
Prompt Tuning for Audio Deepfake Detection: Computationally Efficient Test-time Domain Adaptation with Limited Target DatasetCode1
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