mueller91/MLAAD-tiny
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 -- se this notebook for example) 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. Download git lfs install git clone… See the full description on the dataset page: https://huggingface.co/datasets/mueller91/MLAAD-tiny.
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 -- se this notebook for example) 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.
Download
git lfs install
git clone https://huggingface.co/datasets/mueller91/MLAAD-tinyDataset 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).