README.md

metadata

license: cc-by-nc-4.0
task_categories:
  - audio-classification
language:
  - en
tags:
  - deepfake
  - deepfake-detection
  - audio-deepfake
  - audio-deepfake-detection
  - mlaad
pretty_name: MLAAD tiny
size_categories:
  - 10K<n<100K

Welcome to MLAAD-tiny

MLAAD-tiny is a very small subset of the full MLAAD dataset, designed for education, prototyping, and debugging.

Many teaching environments (e.g. Colab, Kaggle, university notebooks) impose strict storage limits, which makes large-scale audio deepfake datasets impractical to use. To address this, we provide MLAAD-tiny, a compact yet representative version of MLAAD.

Dataset composition

Bona-fide

• Source: M-AILABS
• ~6,000 audio files
• ~1.9 GB
• English

Spoof

• 64 TTS systems
• 100 samples per system (randomly selected from MLAAD)
• ~6,400 audio files
• ~2.3 GB
• English (for training) and German (for testing)

License

• Bona-fide audio is redistributed from M-AILABS under its original license
  (see original/LICENSE).
• Spoofed audio is redistributed under the MLAAD v8 license (CC BY-NC 4.0).