LakoreAI/stgram-mfn-dcase2020-dev

DCASE 2020 Task 2 — Development Dataset (STgram-MFN redistribution)

Redistribution of the DCASE 2020 Challenge Task 2 Development Dataset (Zenodo record 3678171) in the exact on-disk layout expected by the STgram-MFN reference runs. It contains MIMII and ToyADMOS normal/anomalous machine sounds for unsupervised anomalous-sound detection (ASD).

Original authors: Yuma Koizumi, Yohei Kawaguchi, Keisuke Imoto. License: CC BY-NC-SA 4.0 (non-commercial) — inherited from the source; attribute the original authors and keep any redistribution under the same terms.

Layout

<machine>/{train,test}/<label>_id_<XX>_<index>.wav

• <machine> ∈ fan, pump, slider, valve, ToyCar, ToyConveyor
• train/ — normal only
• test/ — normal + anomaly
• audio: mono, 16 kHz, 10 s (.wav, 16-bit PCM)

Labels

There is no separate label file — everything is encoded in the path:

Field	Source	Example
machine type	parent directory	fan
machine id (0–7)	id_XX token	id_00
normal / anomaly	filename prefix	anomaly → 1

STgram-MFN trains self-supervised by machine id (machine-id, 8 ids × 6 machines = 42 classes); the normal/anomaly split is used only for AUC/pAUC evaluation, never as a training target.

Statistics

• 6 machine types, 30,987 clips, ~9.7 GB
• train: normal only · test: normal + anomaly

Intended use

Reference backbone training + evaluation for the backbone-swap / INT8 quantization study (STgram-MFN vs. EfficientAT mn01) in LakoreAI/Research_AnomalySoundDetection. Evaluate with the official DCASE protocol (AUC / pAUC / mAUC).

Usage

from huggingface_hub import snapshot_download
snapshot_download(
    repo_id="LakoreAI/stgram-mfn-dcase2020-dev",
    repo_type="dataset", local_dir="data/raw",
)

uv run python scripts/data/prepare_data.py --root data/raw --check

Related

• Evaluation / additional-training set: LakoreAI/stgram-mfn-dcase2020-eval
• Source: https://zenodo.org/records/3678171

Citation

@inproceedings{koizumi2020dcase,
  title     = {Description and Discussion on DCASE2020 Challenge Task 2:
               Unsupervised Anomalous Sound Detection for Machine Condition Monitoring},
  author    = {Koizumi, Yuma and Kawaguchi, Yohei and Imoto, Keisuke and others},
  booktitle = {DCASE Workshop},
  year      = {2020}
}