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--- |
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license: cc-by-nc-4.0 |
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task_categories: |
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- audio-classification |
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language: |
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- en |
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tags: |
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- deepfake |
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- deepfake-detection |
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- audio-deepfake |
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- audio-deepfake-detection |
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- mlaad |
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pretty_name: MLAAD tiny |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Welcome to MLAAD-tiny |
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**MLAAD-tiny** is a very small subset of the full [MLAAD](https://huggingface.co/datasets/mueller91/MLAAD) dataset, designed for **education, prototyping, and debugging**. |
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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. |
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## Dataset composition |
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### Bona-fide |
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- Source: [M-AILABS](https://github.com/i-celeste-aurora/m-ailabs-dataset) |
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- ~6,000 audio files |
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- ~1.9 GB |
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- English |
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### Spoof |
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- 64 TTS systems |
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- 100 samples per system (randomly selected from MLAAD) |
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- ~6,400 audio files |
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- ~2.3 GB |
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- English (for training) and German (for testing) |
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## License |
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- **Bona-fide audio** is redistributed from M-AILABS under its original license |
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(see `original/LICENSE`). |
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- **Spoofed audio** is redistributed under the **MLAAD v8 license (CC BY-NC 4.0)**. |
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