# WavMark: Watermarking for Audio Generation

arXiv: https://arxiv.org/abs/2308.12770 · HTML: https://mlsanity.com/paper/2308.12770/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 50 references that are in the map.
- First posted on arXiv 24 Aug 2023.

## Builds on (most cited first, 22 of 22)

- [Density estimation using Real NVP](https://mlsanity.com/paper/1605.08803/) (2016)
- [Glow: Generative Flow with Invertible 1x1 Convolutions](https://mlsanity.com/paper/1807.03039/) (2018)
- [Common Voice: A Massively-Multilingual Speech Corpus](https://mlsanity.com/paper/1912.06670/) (2019)
- [ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks](https://mlsanity.com/paper/1809.00219/) (2018)
- [NICE: Non-linear Independent Components Estimation](https://mlsanity.com/paper/1410.8516/) (2014)
- [Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers](https://mlsanity.com/paper/2301.02111/) (2023)
- [Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech](https://mlsanity.com/paper/2106.06103/) (2021)
- [Simple and Controllable Music Generation](https://mlsanity.com/paper/2306.05284/) (2023)
- [WaveGlow: A Flow-based Generative Network for Speech Synthesis](https://mlsanity.com/paper/1811.00002/) (2018)
- [Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search](https://mlsanity.com/paper/2005.11129/) (2020)
- [FMA: A Dataset For Music Analysis](https://mlsanity.com/paper/1612.01840/) (2016)
- [Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision](https://mlsanity.com/paper/2302.03540/) (2023)
- [Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec Language Modeling](https://mlsanity.com/paper/2303.03926/) (2023)
- [Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanisms](https://mlsanity.com/paper/2212.12678/) (2022)
- [RoSteALS: Robust Steganography using Autoencoder Latent Space](https://mlsanity.com/paper/2304.03400/) (2023)
- [Mega-TTS: Zero-Shot Text-to-Speech at Scale with Intrinsic Inductive Bias](https://mlsanity.com/paper/2306.03509/) (2023)
- [Make-A-Voice: Unified Voice Synthesis With Discrete Representation](https://mlsanity.com/paper/2305.19269/) (2023)
- [DeAR: A Deep-learning-based Audio Re-recording Resilient Watermarking](https://mlsanity.com/paper/2212.02339/) (2022)
- [Large-capacity and Flexible Video Steganography via Invertible Neural Network](https://mlsanity.com/paper/2304.12300/) (2023)
- [Reversible GANs for Memory-efficient Image-to-Image Translation](https://mlsanity.com/paper/1902.02729/) (2019)
- [Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural Network](https://mlsanity.com/paper/2207.11844/) (2022)
- [Towards Robust Image-in-Audio Deep Steganography](https://mlsanity.com/paper/2303.05007/) (2023)

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

- [Proactive Detection of Voice Cloning with Localized Watermarking](https://mlsanity.com/paper/2401.17264/) (2024)
- [SoK: Watermarking for AI-Generated Content](https://mlsanity.com/paper/2411.18479/) (2024)
- [Copyright Protection in Generative AI: A Technical Perspective](https://mlsanity.com/paper/2402.02333/) (2024)
- [AudioMarkBench: Benchmarking Robustness of Audio Watermarking](https://mlsanity.com/paper/2406.06979/) (2024)
- [Watermarking Techniques for Large Language Models: A Survey](https://mlsanity.com/paper/2409.00089/) (2024)
- [Images that Sound: Composing Images and Sounds on a Single Canvas](https://mlsanity.com/paper/2405.12221/) (2024)
- [SoK: Dataset Copyright Auditing in Machine Learning Systems](https://mlsanity.com/paper/2410.16618/) (2024)
- [SoK: On the Role and Future of AIGC Watermarking in the Era of Gen-AI](https://mlsanity.com/paper/2411.11478/) (2024)
- [SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography](https://mlsanity.com/paper/2503.06118/) (2025)
- [A Comprehensive Real-World Assessment of Audio Watermarking Algorithms: Will They Survive Neural Codecs?](https://mlsanity.com/paper/2505.19663/) (2025)
- [Steganalysis on Digital Watermarking: Is Your Defense Truly Impervious?](https://mlsanity.com/paper/2406.09026/) (2024)
- [Watermarking Without Standards Is Not AI Governance](https://mlsanity.com/paper/2505.23814/) (2025)
- [Collaborative Watermarking for Adversarial Speech Synthesis](https://mlsanity.com/paper/2309.15224/) (2023)
- [Detecting music deepfakes is easy but actually hard](https://mlsanity.com/paper/2405.04181/) (2024)
- [XAttnMark: Learning Robust Audio Watermarking with Cross-Attention](https://mlsanity.com/paper/2502.04230/) (2025)
- [Audio Codec Augmentation for Robust Collaborative Watermarking of Speech Synthesis](https://mlsanity.com/paper/2409.13382/) (2024)
- [Self Voice Conversion as an Attack against Neural Audio Watermarking](https://mlsanity.com/paper/2601.20432/) (2026)
- [VoiceMark: Zero-Shot Voice Cloning-Resistant Watermarking Approach Leveraging Speaker-Specific Latents](https://mlsanity.com/paper/2505.21568/) (2025)
- [WaveVerify: A Novel Audio Watermarking Framework for Media Authentication and Combatting Deepfakes](https://mlsanity.com/paper/2507.21150/) (2025)
- [HarmonicAttack: An Adaptive Cross-Domain Audio Watermark Removal](https://mlsanity.com/paper/2511.21577/) (2025)
- [The Impact of Audio Watermarking on Audio Anti-Spoofing Countermeasures](https://mlsanity.com/paper/2509.20736/) (2025)
- [Who Gets Flagged? The Pluralistic Evaluation Gap in AI Content Watermarking](https://mlsanity.com/paper/2604.13776/) (2026)
- [Hidden in Plain Tokens: Simply Robust, Gradient-Free Watermark for Synthetic Audio](https://mlsanity.com/paper/2605.25967/) (2026)
- [Prevailing Research Areas for Music AI in the Era of Foundation Models](https://mlsanity.com/paper/2409.09378/) (2024)
- [ErasableMask: A Robust and Erasable Privacy Protection Scheme against Black-box Face Recognition Models](https://mlsanity.com/paper/2412.17038/) (2024)
- [Steganography Beyond Space-Time with Chain of Multimodal AI](https://mlsanity.com/paper/2502.18547/) (2025)
- [SOLIDO: A Robust Watermarking Method for Speech Synthesis via Low-Rank Adaptation](https://mlsanity.com/paper/2504.15035/) (2025)
- [EchoMark: Perceptual Acoustic Environment Transfer with Watermark-Embedded Room Impulse Response](https://mlsanity.com/paper/2511.06458/) (2025)
- [VocBulwark: Towards Practical Generative Speech Watermarking via Additional-Parameter Injection](https://mlsanity.com/paper/2601.22556/) (2026)
- [SKeDA: A Generative Watermarking Framework for Text-to-video Diffusion Models](https://mlsanity.com/paper/2603.00194/) (2026)

## Abstract (arXiv)

Recent breakthroughs in zero-shot voice synthesis have enabled imitating a speaker's voice using just a few seconds of recording while maintaining a high level of realism. Alongside its potential benefits, this powerful technology introduces notable risks, including voice fraud and speaker impersonation. Unlike the conventional approach of solely relying on passive methods for detecting synthetic data, watermarking presents a proactive and robust defence mechanism against these looming risks. This paper introduces an innovative audio watermarking framework that encodes up to 32 bits of watermark within a mere 1-second audio snippet. The watermark is imperceptible to human senses and exhibits strong resilience against various attacks. It can serve as an effective identifier for synthesized voices and holds potential for broader applications in audio copyright protection. Moreover, this framework boasts high flexibility, allowing for the combination of multiple watermark segments to achieve heightened robustness and expanded capacity. Utilizing 10 to 20-second audio as the host, our approach demonstrates an average Bit Error Rate (BER) of 0.48% across ten common attacks, a remarkable reduction of over 2800% in BER compared to the state-of-the-art watermarking tool. See https://aka.ms/wavmark for demos of our work.