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20242026
most citedASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale

5 citations · 8 across the 12 of their papers we have counts for

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8 papers · 1 filter

eess.AS2026

I Hear, Therefore I Trust: A Socio-Technical Investigation of Humans as Synthetic Speech Detectors

Lelia Erscoi, Tomi Kinnunen

Automatic deepfake detection has received considerable research attention, yet the socio-technical environment in which humans actually encounter synthetic speech remains poorly un…

eess.AS2025

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…

eess.AS2025

Causal Analysis of ASR Errors for Children: Quantifying the Impact of Physiological, Cognitive, and Extrinsic Factors

Vishwanath Pratap Singh, Md. Sahidullah, Tomi Kinnunen

The increasing use of children's automatic speech recognition (ASR) systems has spurred research efforts to improve the accuracy of models designed for children's speech in recent…

eess.AS2025

ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech

Xin Wang, Héctor Delgado, Hemlata Tak +26

ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake attacks as well as the design of detection solutions. We introduce…

eess.AS2024

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…

eess.AS2024★ 5 cited

ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale

Xin Wang, Hector Delgado, Hemlata Tak +10

ASVspoof 5 is the fifth edition in a series of challenges that promote the study of speech spoofing and deepfake attacks, and the design of detection solutions. Compared to previou…

eess.AS2024

Optimizing a-DCF for Spoofing-Robust Speaker Verification

Oğuzhan Kurnaz, Jagabandhu Mishra, Tomi H. Kinnunen +1

Automatic speaker verification (ASV) systems are vulnerable to spoofing attacks. We propose a spoofing-robust ASV system optimized directly for the recently introduced architecture…

eess.AS2024★ 1 cited

a-DCF: an architecture agnostic metric with application to spoofing-robust speaker verification

Hye-jin Shim, Jee-weon Jung, Tomi Kinnunen +3

Spoofing detection is today a mainstream research topic. Standard metrics can be applied to evaluate the performance of isolated spoofing detection solutions and others have been p…