Datasets:
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---
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](https://huggingface.co/datasets/mueller91/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](https://github.com/i-celeste-aurora/m-ailabs-dataset)
- ~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)**.
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