RAG-Audio: Retrieval-Augmented Generation for Faithful Brain-to-Audio Reconstruction
Brain-to-audio reconstruction is limited by \emph{prior domination}: when a pretrained generator is conditioned on a weak neural signal, it produces realistic but stimulus-inaccurate audio. We introduce RAG-Audio, which decodes fMRI into a semantic audio embedding, retrieves a matching real-audio exemplar, and initializes the frozen generator's sampling trajectory from that exemplar while retaining the decoded embedding as conditioning. On Brain2Music, RAG-Audio improves 10-way stimulus identification from $0.14$--$0.18$ for direct generation, near the $0.10$ chance level, to $0.40$--$0.43$, comparable to retrieval. It also reduces Fréchet Audio Distance by roughly an order of magnitude, ...
| Authors | Ambuj Mehrish, Sebastiano Vascon |
|---|---|
| Primary category | cs.SD |
| Published | 10 August 2026 |
| Last updated at source | 10 August 2026 |
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