activity
20192026
most citedOpen Challenges in Synthetic Speech Detection

31 citations · 48 across the 8 of their papers we have counts for

collaborators

8 papers

eess.AS2026

Neural Encoding Detection is Not All You Need for Synthetic Speech Detection

Luca Cuccovillo, Xin Wang, Milica Gerhardt +1

This paper reviews the current state and emerging trends in synthetic speech detection. It outlines the main data-driven approaches, discusses the advantages and drawbacks of focus…

cs.SD2026

Multi-Task Transformer for Explainable Speech Deepfake Detection via Formant Modeling

Viola Negroni, Luca Cuccovillo, Paolo Bestagini +2

In this work, we introduce a multi-task transformer for speech deepfake detection, capable of predicting formant trajectories and voicing patterns over time, ultimately classifying…

cs.NE2025

What your brain activity says about you: A review of neuropsychiatric disorders identified in resting-state and sleep EEG data

J. E. M. Scanlon, A. Pelzer, M. Gharleghi +6

Electroencephalogram monitoring devices and online data repositories hold large amounts of data from individuals participating in research and medical studies without direct refere…

eess.AS2022★ 6 cited

Environment Classification via Blind Roomprints Estimation

Malte Baum, Luca Cuccovillo, Artem Yaroshchuk +1

In this paper we present a novel approach for environment classification for speech recordings, which does not require the selection of decaying reverberation tails. It is based on…

eess.AS2022★ 31 cited

Open Challenges in Synthetic Speech Detection

Luca Cuccovillo, Christoforos Papastergiopoulos, Anastasios Vafeiadis +4

In this paper the current status and open challenges of synthetic speech detection are addressed. The work comprises an initial analysis of available open datasets and of existing…

eess.AS2022★ 7 cited

Speaker-Independent Microphone Identification in Noisy Conditions

Antonio Giganti, Luca Cuccovillo, Paolo Bestagini +2

This work proposes a method for source device identification from speech recordings that applies neural-network-based denoising, to mitigate the impact of counter-forensics attacks…

eess.AS2022★ 4 cited

Spectral Denoising for Microphone Classification

L. Cuccovillo, A. Giganti, P. Bestagini +2

In this paper, we propose the use of denoising for microphone classification, to enable its usage for several key application domains that involve noisy conditions. We describe the…

cs.IR2019

Text Classification Components for Detecting Descriptions and Names of CAD models

Thomas Köllmer, Jens Hasselbach, Patrick Aichroth

We apply text analysis approaches for a specialized search engine for 3D CAD models and associated products. The main goals are to distinguish between actual product descriptions a…