5 citations · 14 across the 14 of their papers we have counts for
4 papers · 1 filter
Mixture of Low-Rank Adapter Experts in Generalizable Audio Deepfake Detection
Janne Laakkonen, Ivan Kukanov, Ville Hautamäki
Foundation models such as Wav2Vec2 excel at representation learning in speech tasks, including audio deepfake detection. However, after being fine-tuned on a fixed set of bonafide…
KLASSify to Verify: Audio-Visual Deepfake Detection Using SSL-based Audio and Handcrafted Visual Features
Ivan Kukanov, Jun Wah Ng
The rapid development of audio-driven talking head generators and advanced Text-To-Speech (TTS) models has led to more sophisticated temporal deepfakes. These advances highlight th…
Generalizable speech deepfake detection via meta-learned LoRA
Janne Laakkonen, Ivan Kukanov, Ville Hautamäki
Reliable detection of speech deepfakes (spoofs) must remain effective when the distribution of spoofing attacks shifts. We frame the task as domain generalization and show that ins…
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…