8 papers
QAMO: Quality-aware Multi-centroid One-class Learning For Speech Deepfake Detection
Duc-Tuan Truong, Tianchi Liu, Ruijie Tao +3
Recent work shows that one-class learning can detect unseen deepfake attacks by modeling a compact distribution of bona fide speech around a single centroid. However, the single-ce…
Fine-Grained Frame Modeling in Multi-head Self-Attention for Speech Deepfake Detection
Tuan Dat Phuong, Duc-Tuan Truong, Long-Vu Hoang +1
Transformer-based models have shown strong performance in speech deepfake detection, largely due to the effectiveness of the multi-head self-attention (MHSA) mechanism. MHSA provid…
Addressing Gradient Misalignment in Data-Augmented Training for Robust Speech Deepfake Detection
Duc-Tuan Truong, Tianchi Liu, Junjie Li +3
In speech deepfake detection (SDD), data augmentation (DA) is commonly used to improve model generalization across varied speech conditions and spoofing attacks. However, during tr…
Xi+: Uncertainty Supervision for Robust Speaker Embedding
Junjie Li, Kong Aik Lee, Duc-Tuan Truong +2
There are various factors that can influence the performance of speaker recognition systems, such as emotion, language and other speaker-related or context-related variations. Sinc…
Nes2Net: A Lightweight Nested Architecture for Foundation Model Driven Speech Anti-spoofing
Tianchi Liu, Duc-Tuan Truong, Rohan Kumar Das +2
Speech foundation models have significantly advanced various speech-related tasks by providing exceptional representation capabilities. However, their high-dimensional output featu…
Room Impulse Responses help attackers to evade Deep Fake Detection
Hieu-Thi Luong, Duc-Tuan Truong, Kong Aik Lee +1
The ASVspoof 2021 benchmark, a widely-used evaluation framework for anti-spoofing, consists of two subsets: Logical Access (LA) and Deepfake (DF), featuring samples with varied cod…