Talagini Ashoka, Anitha BhatAnitha BhatTalagini AshokaCuccovillo, LucaLucaCuccovilloAichroth, PatrickPatrickAichroth2024-08-072024-08-072024https://publica.fraunhofer.de/handle/publica/47289010.1145/3643491.3660288This paper introduces a novel approach that enhances synthetic speech detection by applying Benford’s law analysis to the encoder embeddings. By leveraging Benford’s Law as supplementary information alongside the existing embeddings, the model gains a detailed understanding of both content-related features and numerical distribution patterns. Our approach demonstrates superior performance on the ASVspoof 2019 LA dataset, achieving an AUC score of 0.921, while providing enhanced interpretability.enmedia forensicsBenford’s lawaudio deepfakesaudio transformersynthetic speech detectionconference paper