Dataset Viewer
Auto-converted to Parquet Duplicate
mean
list
std
list
frames
int64
n_files
int64
manifest
list
[ 0.2544849917268572, -0.12198937206916516, -0.010053251759337297, -0.08641316137192688, 0.0636601761768548, -0.0667114214316907, 0.012210764924615973, 0.028573196351109203, -0.08323610942553004, -0.041251268261996626, -0.038016536048696786, -0.023131808138696246, 0.07445111874032852, 0.0517...
[ 1.0411281461334894, 0.9560335885691397, 0.9160925208493558, 0.8834822819338377, 0.9466352538916213, 0.9272088692513497, 0.8832150546124647, 0.8720315751730594, 0.933516222050337, 0.9264367396076914, 0.9458185280229375, 0.9251713196653699, 0.9219739354617876, 0.9799504951872332, 0.9086770...
155,070
74
[ "data/proc/test/instr_181523.npz", "data/proc/test/instr_2076.npz", "data/proc/test/instr_2191.npz", "data/proc/test/instr_2218.npz", "data/proc/test/instr_2243.npz", "data/proc/test/instr_2304.npz", "data/proc/test/instr_2382.npz", "data/proc/test/instr_2477.npz", "data/proc/test/instr_2575.npz", ...

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

singing-fm data/proc — YuE2-VAE latents + MERT-v2 features

Preprocessed training data for the singing-fm latent flow-matching project. Derived features only — no raw audio.

Contents

data_proc.tar.zst (tar.zst, ~6.5 GB) extracts to data/proc/:

Path What
train/*.z.npy 1462 files, fp16, YuE2-VAE posterior-mean latents z [T, 64] @ 25 Hz
train/*.h.npy 1462 files, fp16, MERT-v2 (layer 21) frame features h [T, 1024] @ 25 Hz (aligned to z)
test/*.npz 74 holdout files with z + h (KAD reference / cond source)
stats.json per-channel z mean/std used for train-time normalization (computed over test npz — replicate this exactly when de-normalizing)

stats.json is also at repo root for inspection.

Domains (filename prefixes)

Prefix Source Train files
speech_ EARS (Meta) 540
singing_ VocalSet 531
song_ Song Describer Dataset (vocal) 180
instr_ MusicNet (165) + SDD instrumental (46) 211

Test split = every 20th file of each domain's sorted list (--holdout_every 20), 74 files total, 1.7 h.

Reproduction

Built by the pipeline in the singing-fm repo (preproc.py): audio → YuE2-VAE (FP32) latents + MERT-v2 (FP16 weights, outside autocast) layer-21 features, both truncated to the common frame count. Deterministic given the source datasets (sorted globs, fixed holdout, random.seed(0) for MusicNet selection).

Sources & licenses

Features derived from four public research datasets: EARS, VocalSet, Song Describer Dataset, MusicNet. No raw audio is included; consult the original dataset releases for their respective licenses and citation requirements.

Downloads last month
40