9 papers
Tracking the Trend in How Speech Synthesizers Deceive People
Milan Šalko, Anton Firc, Kamil Malinka +4
Advances in speech synthesis have made deepfake audio highly realistic. Earlier studies reported 70-80% human detection accuracy, but relied primarily on older synthesizers. We com…
The Last Mile of Deepfake Speech Detection: An Industry-Academia Experience Report
Anton Firc, Kamil Malinka, Vojtěch Staněk +2
Synthetic speech detection benchmarks now report sub-1% error rates on some in-domain evaluations, yet performance degrades under unseen attacks, channel mismatch, and distribution…
VQCSim: When Does Compile-Once Statevector Simulation Beat Generic Quantum Frameworks?
Anton Firc, Martin Perešíni, Vojtěch Mrázek +7
Hybrid quantum-classical machine learning workflows repeatedly evaluate many small parametrized circuits during training and model exploration. In this regime, framework dispatch a…
SpAArSIST: Sparsified AASIST for Efficient and Reliable Anti-Spoofing
Anton Firc, Vojtěch Staněk, Zbyněk Lička +2
We present SpAArSIST, a deployment-oriented refinement of the widely used AASIST graph pooling backend for self-supervised learning (SSL) based anti-spoofing. Motivated by redundan…
The Hidden Cost of Pairwise Verification in Synthetic Speech Source Tracing
Anton Firc, Zbyněk Lička, Vojtěch Staněk +1
Open-set source tracing is increasingly framed as a verification problem, motivating the use of pairwise metric-learning objectives from biometrics. We thus compare global anchorin…
What Do Deepfake Speech Detectors Actually Hear?
Vojtěch Staněk, Veronika Jirmusová, Anton Firc +3
Deepfake speech detectors often output a single score without explaining why an audio sample is flagged, where in the signal the evidence lies, or what cues drive the decision. We…