Datasetpublic

xxuan-speech/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… See the full description on the dataset page: https://huggingface.co/datasets/xxuan-speech/MCL-MLAAD.

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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:

bash

pip install datasets

bash

huggingface-cli login

Load the dataset in Python:

bash

from datasets import load_dataset

# Download from HF and cache
ds = load_dataset("xxuan-speech/MCL-MLAAD")

# Optionally: Save the dataset to your own directory
ds.save_to_disk("mcl-mlaad_local")

Code:

A reference implementation Code is available at: https://github.com/xuanxixi/Multilingual-Source-Tracing

Bibtex:

bash

@misc{xuan2025multilingualsourcetracingspeech,
      title={Multilingual Source Tracing of Speech Deepfakes: A First Benchmark}, 
      author={Xi Xuan and Yang Xiao and Rohan Kumar Das and Tomi Kinnunen},
      year={2025},
      eprint={2508.04143},
      archivePrefix={arXiv},
      primaryClass={eess.AS},
      url={https://arxiv.org/abs/2508.04143}
}