MLAAD
Datasets
All datasets matching “MLAAD”MLAAD
Introduction
Welcome to MLAAD: The Multi-Language Audio Anti-Spoofing Dataset -- a dataset to train, test and evaluate audio deepfake detection. See
the paper for more information.
License
MLAAD is published strictly for non-commercial academic research use, under the CC-BY-NC 4.0 license. Commercial use is not permitted.
Bibtex
If you use this dataset, please consider citing it as follows.
@article{muller2024mlaad,
title={MLAAD: The… See the full description on the dataset page: https://huggingface.co/datasets/mueller91/MLAAD.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.MCL-MLAAD
Introduction
MCL-MLAAD is the first multilingual benchmark for speech deepfake source tracing. It spans mono- and cross-lingual protocols, includes DSP and SSL baselines, studies language-specific fine-tuning for cross-lingual generalization, and tests robustness to unseen languages/speakers. See arXiv:2508.04143.
Download the Dataset
Install the datasets package:
pip install datasets
Log in with your Hugging Face account:
huggingface-cli login
Load the dataset in… See the full description on the dataset page: https://huggingface.co/datasets/xxuan-speech/MCL-MLAAD.DFADD_MLAAD_DiffSSD_VoxCeleb2MLAAD-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) 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/Saisaket25/MLAAD-tiny.v14-MLAAD-Fake-part_01