Taste-aware music retrieval from audio embeddings
Crossmodal correspondences between sound and taste are well established in psychology and neuroscience, but largely absent from content-based multimedia retrieval. We formalise taste-from-audio prediction as a content-based music information retrieval benchmark over a perceptually validated multi-source corpus, comparing ten frozen audio encoders from the four HEAR families under a shared multi-task regression head, with gated late-fusion as a configurable variant. In order to assess the effectiveness of the models, we compute absolute error and rank correlation. The strongest systems predict the five tastes within a macro RMSE of 0.134; on held-out real music their error is less than hal...
| Authors | Matteo Spanio, Antonio Rodà |
|---|---|
| Primary category | cs.SD |
| Published | 3 July 2026 |
| Last updated at source | 3 July 2026 |
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