# Audio Deepfake Detection: A Survey

arXiv: https://arxiv.org/abs/2308.14970 · HTML: https://mlsanity.com/paper/2308.14970/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2023.

## Built on by (most cited first, 30 of 50)

- [Speech DF Arena: A Leaderboard for Speech DeepFake Detection Models](https://mlsanity.com/paper/2509.02859/) (2025)
- [Mixture of Experts Fusion for Fake Audio Detection Using Frozen wav2vec 2.0](https://mlsanity.com/paper/2409.11909/) (2024)
- [ALLM4ADD: Unlocking the Capabilities of Audio Large Language Models for Audio Deepfake Detection](https://mlsanity.com/paper/2505.11079/) (2025)
- [A Timely Survey on Vision Transformer for Deepfake Detection](https://mlsanity.com/paper/2405.08463/) (2024)
- [Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook](https://mlsanity.com/paper/2411.19537/) (2024)
- [BiCrossMamba-ST: Speech Deepfake Detection with Bidirectional Mamba Spectro-Temporal Cross-Attention](https://mlsanity.com/paper/2505.13930/) (2025)
- [Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities](https://mlsanity.com/paper/2405.00711/) (2024)
- [SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection](https://mlsanity.com/paper/2407.18517/) (2024)
- [Learn from Real: Reality Defender's Submission to ASVspoof5 Challenge](https://mlsanity.com/paper/2410.07379/) (2024)
- [CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation](https://mlsanity.com/paper/2505.15233/) (2025)
- [Deepfake Audio Detection Using Spectrogram-based Feature and Ensemble of Deep Learning Models](https://mlsanity.com/paper/2407.01777/) (2024)
- [SZU-AFS Antispoofing System for the ASVspoof 5 Challenge](https://mlsanity.com/paper/2408.09933/) (2024)
- [Easy, Interpretable, Effective: openSMILE for voice deepfake detection](https://mlsanity.com/paper/2408.15775/) (2024)
- [VoiceWukong: Benchmarking Deepfake Voice Detection](https://mlsanity.com/paper/2409.06348/) (2024)
- [Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap](https://mlsanity.com/paper/2410.07436/) (2024)
- [Passive Deepfake Detection Across Multi-modalities: A Comprehensive Survey](https://mlsanity.com/paper/2411.17911/) (2024)
- [The last Dance : Robust backdoor attack via diffusion models and bayesian approach](https://mlsanity.com/paper/2402.05967/) (2024)
- [Watermarking for AI Content Detection: A Review on Text, Visual, and Audio Modalities](https://mlsanity.com/paper/2504.03765/) (2025)
- [Reliable Audio Deepfake Detection in Variable Conditions via Quantum-Kernel SVMs](https://mlsanity.com/paper/2512.18797/) (2025)
- [Gender Fairness in Audio Deepfake Detection: Performance and Disparity Analysis](https://mlsanity.com/paper/2603.09007/) (2026)
- [AFSS: Artifact-Focused Self-Synthesis for Mitigating Bias in Audio Deepfake Detection](https://mlsanity.com/paper/2603.26856/) (2026)
- [A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems](https://mlsanity.com/paper/2508.16843/) (2025)
- [AUDDT: A Unified Benchmark Toolkit for Audio and Speech Deepfake Detectors](https://mlsanity.com/paper/2509.21597/) (2025)
- [Can Generative Models Actually Forge Realistic Identity Documents?](https://mlsanity.com/paper/2601.00829/) (2025)
- [SpMis: An Investigation of Synthetic Spoken Misinformation Detection](https://mlsanity.com/paper/2409.11308/) (2024)
- [A Practical Synthesis of Detecting AI-Generated Textual, Visual, and Audio Content](https://mlsanity.com/paper/2504.02898/) (2025)
- [FADEL: Uncertainty-aware Fake Audio Detection with Evidential Deep Learning](https://mlsanity.com/paper/2504.15663/) (2025)
- [End-to-end Audio Deepfake Detection from RAW Waveforms: a RawNet-Based Approach with Cross-Dataset Evaluation](https://mlsanity.com/paper/2504.20923/) (2025)
- [Few-Shot Speech Deepfake Detection Adaptation with Gaussian Processes](https://mlsanity.com/paper/2505.23619/) (2025)
- [Segment Transformer: AI-Generated Music Detection via Music Structural Analysis](https://mlsanity.com/paper/2509.08283/) (2025)

## Abstract (arXiv)

Audio deepfake detection is an emerging active topic. A growing number of literatures have aimed to study deepfake detection algorithms and achieved effective performance, the problem of which is far from being solved. Although there are some review literatures, there has been no comprehensive survey that provides researchers with a systematic overview of these developments with a unified evaluation. Accordingly, in this survey paper, we first highlight the key differences across various types of deepfake audio, then outline and analyse competitions, datasets, features, classifications, and evaluation of state-of-the-art approaches. For each aspect, the basic techniques, advanced developments and major challenges are discussed. In addition, we perform a unified comparison of representative features and classifiers on ASVspoof 2021, ADD 2023 and In-the-Wild datasets for audio deepfake detection, respectively. The survey shows that future research should address the lack of large scale datasets in the wild, poor generalization of existing detection methods to unknown fake attacks, as well as interpretability of detection results.