Simplifying Robust Audio Watermarking

Multi-bit audio watermarking models are generally found vulnerable under deep watermark removal attacks, such as neural codec resynthesis and voice cloning. Existing methods jointly apply strategies like attack simulation, latent watermarking, and perceptual losses to improve robustness while preserving imperceptibility. However, we discover that most of these strategies are not necessary to achieve state-of-the-art robustness. To figure out key designs that enable robust audio watermarking, we propose SimpleMark, a simple yet effective audio watermarking framework. SimpleMark narrows down robust audio watermarking to two design choices: First, we embed the watermark through **bounded magnitude scaling** to control imperceptibility. Second, we detect watermark from **low-level audio representations** using a lightweight readout head to achieve robustness. Following these two designs, we build a series of lightweight audio watermarking models that surpass existing complex methods in robustness while maintaining competitive imperceptibility.