MLAAD: The Multi-Language Audio Anti-Spoofing Dataset

Understand

This paper presents the Multi-Language Audio Anti-Spoofing Dataset (MLAAD), version 11: a dataset of synthetic audio to train and evaluate audio deepfake detection models.

• It features 205 Text-to-Speech (TTS) models, comprising a total of 1153.6 hours of synthetic voice in 54 different languages.
• To evaluate this dataset, we train three state-of-the-art deepfake detection models with MLAAD and observe that it demonstrates superior performance to comparable datasets like InTheWild and FakeOrReal when used as a training resource.
• Moreover, compared to the renowned ASVspoof 2019 dataset, MLAAD proves to be a complementary resource.