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arXiv · 2603.16805

Making Separation-First Multi-Stream Audio Watermarking Feasible via Joint Training

Houmin Sun·Zi Hu·Linxi Li·Yechen Wang·Liwei Jin·Carsten Maple·Ming Li
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Abstract

Modern audio is created by mixing stems from different sources, raising the question: can we independently watermark each stem and recover all watermarks after separation? We study a separation-first, multi-stream watermarking framework --embedding distinct information into stems using unique keys but a shared structure, mixing, separating, and decoding from each output. A naive pipeline (robust watermarking + off-the-shelf separation) yields poor bit recovery, showing robustness to generic distortions does not ensure robustness to separation artifacts. To enable this, we study separation-aware watermarking in a controlled verification pipeline, where the separator is part of the detector and can be selected or optimized together with the watermarking system. Experiments on speech+music and vocal+accompaniment mixtures show substantial gains in post-separation recovery while maintaining perceptual quality.

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Houmin Sun, Zi Hu, Linxi Li, Yechen Wang, Liwei Jin, Carsten Maple, Ming Li. 2026-03-17. Making Separation-First Multi-Stream Audio Watermarking Feasible via Joint Training. https://arxiv.org/abs/2603.16805

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