3rd ACM International Workshop on Multimedia AI against Disinformation (MAD’24)

On June 10, 2024, the 3rd edition of the ACM International Workshop on Multimedia AI against Disinformation (MAD’24) organized with the ACM International Conference on Multimedia Retrieval (ICMR’24) will take place in Phuket, Thailand.

Fraunhofer IDMT will support the organization of the workshop and present its latest work on visual and audio scene classification and speech detection there.

Anitha Bhat Talagini Ashoka, Luca Cuccovillo, Patrick Aichroth

This 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.

Jakob Abeßer, Luca Cuccovillo

This paper presents a baseline approach and an experimental protocol for a specific content verification problem: detecting discrepancies between the audio and video modalities in multimedia content. We first design and optimize an audio-visual scene classifier, to compare with existing classification baselines that use both modalities. Then, by applying this classifier separately to the audio and the visual modality, we can detect scene-class inconsistencies between them. To facilitate further research and provide a common evaluation platform, we introduce an experimental protocol and a benchmark dataset simulating such inconsistencies. Our approach achieves state-of-the-art results in scene classification and promising outcomes in audio-visual discrepancies detection, highlighting its potential in content verification applications.