AlignAudio: A Unified Dual-Alignment Framework for Noise-Robust Speech-Conditioned Generation
Speech-conditioned generation maps speech signals to target audio outputs. Prior end-to-end speech-conditioned generative models achieve high fidelity in clean acoustic conditions, but their performance degrades substantially under environmental noise. While prior noise-robust approaches have achieved significant success in feature-level purification, maintaining consistent generation under clean and noisy conditioning remains a key challenge. To address this, we propose AlignAudio, a noise-robust generative framework based on dual alignment: (i) aligning the representations of clean and noisy speech to preserve semantic cues, and (ii) enforcing generation-level consistency within a flow ...
| Authors | Yixuan Li, Xuenan Xu, Zeyu Xie et al. |
|---|---|
| Primary category | cs.SD |
| Published | 10 October 2026 |
| Last updated at source | 10 October 2026 |
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