18 citations · 50 across the 18 of their papers we have counts for
24 papers
NMINE: Normalized Mutual Information Neural Estimation
Petra Eerikinharju, Marko Tuononen, Ville Hautamäki
Mutual information is a general measure of statistical dependence that captures both linear and nonlinear relationships between random variables. For continuous and multidimensiona…
How Meta-Learning Shapes LoRA Adapter Geometry in Speech Deepfake Detection
Ivan Kukanov, Janne Laakkonen, Ville Hautamäki
Meta-learning for domain generalization (MLDG) improves out-of-distribution speech deepfake detection over empirical risk minimization (ERM) when both objectives train low-rank ada…
Zero-Shot Heart Rate Variability Forecasting from Consumer Wearables Using Time Series Foundation Models
Luukas Peräkylä, Fahad Sohrab, Ville Hautamäki +3
Short-term Heart Rate Variability (HRV) forecasting could provide clinicians with actionable lead time for detecting autonomic dysfunction and adverse cardiac events. Consumer wear…
Disentangling Speaker Traits for Deepfake Source Verification via Chebyshev Polynomial and Riemannian Metric Learning
Xi Xuan, Wenxin Zhang, Zhiyu Li +3
Speech deepfake source verification systems aims to determine whether two synthetic speech utterances originate from the same source generator, often assuming that the resulting so…
Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence
Edem Ahadzi, Vishwanath Pratap Singh, Tomi Kinnunen +1
In this work, we present the first study addressing automatic speech recognition (ASR) for children in an online learning setting. This is particularly important for both child-cen…
Meta-Learning Approaches for Improving Detection of Unseen Speech Deepfakes
Ivan Kukanov, Janne Laakkonen, Tomi Kinnunen +1
Current speech deepfake detection approaches perform satisfactorily against known adversaries; however, generalization to unseen attacks remains an open challenge. The proliferatio…