6 citations · 25 across the 18 of their papers we have counts for
19 papers
Not All Deepfakes Are Created Equal: Triaging Audio Forgeries for Robust Deepfake Singer Identification
Davide Salvi, Hendrik Vincent Koops, Elio Quinton
The proliferation of highly realistic singing voice deepfakes presents a significant challenge to protecting artist likeness and content authenticity. Automatic singer identificati…
Forensic Similarity for Speech Deepfakes
Viola Negroni, Davide Salvi, Daniele Ugo Leonzio +2
In this paper, we introduce the concept of forensic similarity in the speech deepfake detection domain, which aims to determine whether two audio segments share the same underlying…
Attention-based Mixture of Experts for Robust Speech Deepfake Detection
Viola Negroni, Davide Salvi, Alessandro Ilic Mezza +2
AI-generated speech is becoming increasingly used in everyday life, powering virtual assistants, accessibility tools, and other applications. However, it is also being exploited fo…
Phoneme-Level Analysis for Person-of-Interest Speech Deepfake Detection
Davide Salvi, Viola Negroni, Sara Mandelli +2
Recent advances in generative AI have made the creation of speech deepfakes widely accessible, posing serious challenges to digital trust. To counter this, various speech deepfake…
Source Verification for Speech Deepfakes
Viola Negroni, Davide Salvi, Paolo Bestagini +1
With the proliferation of speech deepfake generators, it becomes crucial not only to assess the authenticity of synthetic audio but also to trace its origin. While source attributi…
Anomaly Detection and Localization for Speech Deepfakes via Feature Pyramid Matching
Emma Coletta, Davide Salvi, Viola Negroni +2
The rise of AI-driven generative models has enabled the creation of highly realistic speech deepfakes - synthetic audio signals that can imitate target speakers' voices - raising c…
Comparative Analysis of ASR Methods for Speech Deepfake Detection
Davide Salvi, Amit Kumar Singh Yadav, Kratika Bhagtani +3
Recent techniques for speech deepfake detection often rely on pre-trained self-supervised models. These systems, initially developed for Automatic Speech Recognition (ASR), have pr…
POLIPHONE: A Dataset for Smartphone Model Identification from Audio Recordings
Davide Salvi, Daniele Ugo Leonzio, Antonio Giganti +4
When dealing with multimedia data, source attribution is a key challenge from a forensic perspective. This task aims to determine how a given content was captured, providing valuab…
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…
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…
Analyzing the Impact of Splicing Artifacts in Partially Fake Speech Signals
Viola Negroni, Davide Salvi, Paolo Bestagini +1
Speech deepfake detection has recently gained significant attention within the multimedia forensics community. Related issues have also been explored, such as the identification of…
Deepfake Media Forensics: State of the Art and Challenges Ahead
Irene Amerini, Mauro Barni, Sebastiano Battiato +21
AI-generated synthetic media, also called Deepfakes, have significantly influenced so many domains, from entertainment to cybersecurity. Generative Adversarial Networks (GANs) and…
FairSSD: Understanding Bias in Synthetic Speech Detectors
Amit Kumar Singh Yadav, Kratika Bhagtani, Davide Salvi +2
Methods that can generate synthetic speech which is perceptually indistinguishable from speech recorded by a human speaker, are easily available. Several incidents report misuse of…
Listening Between the Lines: Synthetic Speech Detection Disregarding Verbal Content
Davide Salvi, Temesgen Semu Balcha, Paolo Bestagini +1
Recent advancements in synthetic speech generation have led to the creation of forged audio data that are almost indistinguishable from real speech. This phenomenon poses a new cha…
All-for-One and One-For-All: Deep learning-based feature fusion for Synthetic Speech Detection
Daniele Mari, Davide Salvi, Paolo Bestagini +1
Recent advances in deep learning and computer vision have made the synthesis and counterfeiting of multimedia content more accessible than ever, leading to possible threats and dan…
Combining Automatic Speaker Verification and Prosody Analysis for Synthetic Speech Detection
Luigi Attorresi, Davide Salvi, Clara Borrelli +2
The rapid spread of media content synthesis technology and the potentially damaging impact of audio and video deepfakes on people's lives have raised the need to implement systems…
TIMIT-TTS: a Text-to-Speech Dataset for Multimodal Synthetic Media Detection
Davide Salvi, Brian Hosler, Paolo Bestagini +2
With the rapid development of deep learning techniques, the generation and counterfeiting of multimedia material are becoming increasingly straightforward to perform. At the same t…
Parametric Optimization of Violin Top Plates using Machine Learning
Davide Salvi, Sebastian Gonzalez, Fabio Antonacci +1
We recently developed a neural network that receives as input the geometrical and mechanical parameters that define a violin top plate and gives as output its first ten eigenfreque…
A Data-Driven Approach to Violin Making
Sebastian Gonzalez, Davide Salvi, Daniel Baeza +2
Of all the characteristics of a violin, those that concern its shape are probably the most important ones, as the violin maker has complete control over them. Contemporary violin m…