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Research questionHow can speech enhancement adapt to mismatched deployment acoustics without labeled target audio?Speech enhancement models can lose quality when deployment noise differs from their training conditions. Test-time adaptation must therefore respond to acoustic mismatch without labeled target examples.
Audio & Speech
Audio & Speech Processing
Machine Learning
Latest papersRecent research connected to this question, newest first.Test-time adaptation for speech enhancement with an autoregressive speech priorThe work studies single-utterance adaptation of a pretrained speech enhancement model under training–testing noise mismatch, using an autoregressive prior learned from clean-speech latent representations. Experiments across multiple noisy speech datasets report speech-quality improvements, particularly under mismatched conditions; the supplied evidence does not specify deployment latency or other operational constraints.research paper · Sep 3, 2026
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