most citedFreeze and Learn: Continual Learning with Selective Freezing for Speech Deepfake Detection

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Explainable Artifacts for Synthetic Western Blot Source Attribution

João Phillipe Cardenuto, Sara Mandelli, Daniel Moreira +3

Recent advancements in artificial intelligence have enabled generative models to produce synthetic scientific images that are indistinguishable from pristine ones, posing a challen…

eess.AS2024

DiffSSD: A Diffusion-Based Dataset For Speech Forensics

Kratika Bhagtani, Amit Kumar Singh Yadav, Paolo Bestagini +1

Diffusion-based speech generators are ubiquitous. These methods can generate very high quality synthetic speech and several recent incidents report their malicious use. To counter…

cs.SD20241 cited

Freeze and Learn: Continual Learning with Selective Freezing for Speech Deepfake Detection

Davide Salvi, Viola Negroni, Luca Bondi +2

In speech deepfake detection, one of the critical aspects is developing detectors able to generalize on unseen data and distinguish fake signals across different datasets. Common a…

eess.AS20241 cited

FakeMusicCaps: a Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models

Luca Comanducci, Paolo Bestagini, Stefano Tubaro

Text-To-Music (TTM) models have recently revolutionized the automatic music generation research field. Specifically, by reaching superior performances to all previous state-of-the-…

cs.SD20241 cited

Leveraging Mixture of Experts for Improved Speech Deepfake Detection

Viola Negroni, Davide Salvi, Alessandro Ilic Mezza +2

Speech deepfakes pose a significant threat to personal security and content authenticity. Several detectors have been proposed in the literature, and one of the primary challenges…