MADB
dataset·music aesthetics·active
Large music-aesthetics benchmark with multi-dimensional professional ratings and textual comments.
Verified facts
| Official site | https://github.com/knownree/madb ↗ |
|---|---|
| Geography | Global |
| arxiv | 2607.06929 |
| github repository | knownree/madb |
| size | tracks: 9999 · trained annotators: 30 · perceptual dimensions: 10 · ratings per track approx: 10 |
| scope | Human-aligned music aesthetic assessment and multimodal analysis. |
| genres | not publicly normalized |
| steward | MADB authors |
| creators | Sirui Zhang; Tianle Wang; Xinyi Tong; Peiyang Yu; Jishang Chen; Liangke Zhao; Haoxin Zhang; Duo Xu; Xin Jin; Feng Yu; Songchun Zhu |
| languages | not publicly normalized |
| modalities | music tracks; 10 perceptual ratings; overall score; textual comments |
| geographies | Global |
| access method | Project GitHub referenced by paper. |
| intended uses | music aesthetic assessment; human-aligned evaluation |
| related papers | MADB: A Large-Scale Music Aesthetics Dataset |
| annotation method | Thirty trained annotators; about ten ratings per track across ten dimensions and an overall score. |
| collection method | Tracks selected for large-scale professional aesthetic annotation. |
| current availability | Project page exists; release completeness requires review. |
| us market scope basis | Publicly available or materially used in US-facing music/audio-AI research. |
| limitations biases disputes | Very recent preprint with limited independent use and replication.; Track sources, genres and annotator demographics need audit. |
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