audio-music-mir-post-public

Music information retrieval and tagging annotations: genre (FMA), instrument family (NSynth × 3, Medley-solos-DB), social tags (MagnaTagATune via LLARK), and large-scale Music4All metadata. Foundation for music understanding heads in audio LLMs.

Audio is not bundled in this repo. See download.sh and per-dataset data/<name>.info.json for the fetch recipe; run postlink_audio.py after fetching to rewrite the JSONL audio_path fields with absolute local paths.

Total: 137,223 rows across 7 datasets.

Datasets

Dataset	Rows	Source HF	License	Audio in this repo
FMA-GenreClassification	112	mdeff/fma	CC-BY-4.0	redistributable
LLARK_MagnaTagATune-mir	3,300	mulab-mir/lp-music-caps-magnatagatune-3k	CC-BY-NC-SA-3.0	redistributable
Medley-solos-DB-InstrClassification	22,916	confit/medley-solos-db	research	redistributable
Music4All	108,363	seungheondoh/enrich-music4all	CC-BY-4.0	redistributable
NSynth-Instrument	816	DynamicSuperb/InstrumentClassification_Nsynth	Apache-2.0	redistributable
NSynth-MIR	816	DynamicSuperb/InstrumentClassification_Nsynth	Apache-2.0	redistributable
NSynth-Source	900	DynamicSuperb/InstrumentSourceClassification_Nsynth	Apache-2.0	redistributable

Schema

Each JSONL record:

{
  "dataset": "<DatasetName>",
  "split": "train",
  "audio_path": "<basename or relative path>",
  "instruction": "<question or task prompt>",
  "response": "<answer / label / caption>",
  "meta": { "...": "..." }
}

After postlink_audio.py, a sibling data/<name>.with_audio.jsonl is produced with audio_path rewritten to absolute local paths.

How to use

git clone https://huggingface.co/datasets/vhands/audio-music-mir-post-public
cd audio-music-mir-post-public
bash download.sh                    # print per-dataset audio recipes
bash download.sh <DatasetName>      # print recipe for one dataset
# (manually fetch audio into audio/<DatasetName>/ per the recipe)
python3 postlink_audio.py           # rewrite JSONLs with absolute audio paths

Licenses

The bundle is offered under cc-by-nc-sa-3.0 — the most restrictive license among contained datasets. Per-dataset licenses are in the table above and in data/<name>.info.json. Attribution to upstream creators is required when redistributing.

Files

audio-music-mir-post-public/
├── README.md
├── dataset_manifest.json
├── domain_music_mir.jsonl           # joint, 137,223 rows
├── data/
│   ├── <DatasetName>.jsonl         (×7)
│   └── <DatasetName>.info.json     (×7)
├── audio/                          # populated by you
├── download.sh
└── postlink_audio.py

Companion bundles

• vhands/audio-emotion-post-public — 5 emotion datasets, 45k rows
• vhands/audio-reasoning-qa-post-public — 15 reasoning-QA datasets, 750k rows
• vhands/audio-music-mir-post-public — 7 music/MIR datasets, 137k rows
• vhands/audio-event-classification-post-public — 7 sound-event/scene datasets, 95k rows

Together these cover ~1 M rows of audio-LLM post-training annotations across 5 domains.