Saisaket25/MLAAD-tiny

MLAAD-tiny是完整MLAAD数据集的一个非常小的子集，专为教育、原型设计和调试而设计。由于许多教学环境(如Colab、Kaggle、大学笔记本)有严格的存储限制，使得大规模音频深度伪造数据集难以使用。为此，我们提供了MLAAD-tiny这个紧凑但具有代表性的版本。数据集包含真实音频(Bona-fide)和伪造音频(Spoof)两部分：真实音频来自M-AILABS数据集，约6,000个音频文件，1.9GB，英语；伪造音频包含64个TTS系统，每个系统随机选取100个样本，约6,400个音频文件，2.3GB，训练用英语，测试用德语。

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. The dataset consists of two parts: Bona-fide audio from M-AILABS dataset (~6,000 files, ~1.9GB, English) and Spoof audio from 64 TTS systems (100 samples per system randomly selected from MLAAD, ~6,400 files, ~2.3GB, English for training and German for testing).